fix: detect single-backslash, home-relative and bare relative Windows paths

Addresses Gemini and Greptile review feedback: is_path_like now recognizes
\path, ~\path and relative paths containing backslashes (e.g. knowledge\docs)
so equivalent Windows configurations resolve as knowledge sources.

Co-authored-by: Mervin Praison <[email protected]>

.github/actions/install-monorepo-packages/action.yml

@@ -1,66 +0,0 @@
-name: Install PraisonAI monorepo packages
-description: Install praisonai-agents, praisonai-code, and praisonai wrapper from local paths (mirrors PyPI three-package install order).
-
-inputs:
-  repo-root:
-    description: Path prefix to monorepo root (e.g. PraisonAI/ for cross-repo checkout)
-    required: false
-    default: ""
-  use-uv:
-    description: Use uv pip instead of pip
-    required: false
-    default: "false"
-  agents-extras:
-    description: Optional extras for praisonaiagents (e.g. .[all] or [all])
-    required: false
-    default: ""
-  wrapper-extras:
-    description: Optional extras for praisonai wrapper (e.g. .[chat,code] or [chat,code])
-    required: false
-    default: ""
-
-runs:
-  using: composite
-  steps:
-    - name: Install monorepo packages
-      shell: bash
-      run: |
-        set -euo pipefail
-        WORKSPACE="${GITHUB_WORKSPACE:-$(pwd)}"
-        ROOT="${{ inputs.repo-root }}"
-        if [ -n "$ROOT" ]; then
-          BASE="${WORKSPACE%/}/${ROOT%/}/"
-        else
-          BASE="${WORKSPACE%/}/"
-        fi
-        AGENTS_PKG="${BASE}src/praisonai-agents"
-        CODE_PKG="${BASE}src/praisonai-code"
-        WRAPPER_PKG="${BASE}src/praisonai"
-
-        normalise_extras() {
-          local value="${1#.}"
-          if [ -n "$value" ]; then
-            printf '.%s' "$value"
-          else
-            printf '.'
-          fi
-        }
-
-        AGENTS_SUFFIX="$(normalise_extras "${{ inputs.agents-extras }}")"
-        WRAPPER_SUFFIX="$(normalise_extras "${{ inputs.wrapper-extras }}")"
-
-        if [ "${{ inputs.use-uv }}" = "true" ]; then
-          cd "$AGENTS_PKG"
-          uv pip install --system -e "${AGENTS_SUFFIX}"
-          cd "$CODE_PKG"
-          uv pip install --system -e .
-          cd "$WRAPPER_PKG"
-          uv pip install --system "${WRAPPER_SUFFIX}"
-        else
-          cd "$AGENTS_PKG"
-          pip install -e "${AGENTS_SUFFIX}"
-          cd "$CODE_PKG"
-          pip install -e .
-          cd "$WRAPPER_PKG"
-          pip install -e "${WRAPPER_SUFFIX}"
-        fi

.github/scripts/merge-gate-selftest.js

@@ -27,40 +27,6 @@ const withRecovery = [
 ];
 assert('not stale when @claude after head', !mg.isStaleFinalAfterPush(withRecovery, '2026-06-12T09:00:00Z'));
 
-// Stale-FINAL recovery guards (PR #2560 push loop)
-const nowMs = Date.now();
-const iso = (ms) => new Date(ms).toISOString();
-const firstFinal = {
-  user: { login: 'MervinPraison' },
-  body: '@claude You are the FINAL architecture reviewer.',
-  created_at: iso(nowMs - 20 * 60 * 1000),
-};
-const pushSoonAfter = mg.shouldSkipStaleFinalRecovery(
-  [firstFinal],
-  iso(nowMs - 16 * 60 * 1000)
-);
-assert('debounce push soon after FINAL', pushSoonAfter.skip && pushSoonAfter.reason.includes('soon after'));
-
-const secondFinal = {
-  user: { login: 'MervinPraison' },
-  body: '@claude You are the FINAL architecture reviewer.',
-  created_at: iso(nowMs - 20 * 60 * 1000),
-};
-const capped = mg.shouldSkipStaleFinalRecovery(
-  [firstFinal, secondFinal],
-  iso(nowMs - 2 * 60 * 1000)
-);
-assert('hourly cap blocks third FINAL in window', capped.skip && capped.reason.includes('capped'));
-
-const botPush = mg.shouldSkipStaleFinalRecovery(
-  [firstFinal],
-  iso(nowMs - 16 * 60 * 1000),
-  'praisonai-triage-agent[bot]'
-);
-assert('skip when automation pushed head', botPush.skip && botPush.reason.includes('automation'));
-
-assert('claude automation login', mg.isClaudeAutomationLogin('praisonai-triage-agent[bot]'));
-
 // Bot CHANGES_REQUESTED then APPROVE
 const reviews = [
   { user: { login: 'coderabbit[bot]', type: 'Bot' }, state: 'CHANGES_REQUESTED', submitted_at: '2026-06-12T08:00:00Z' },
@@ -85,31 +51,6 @@ assert('verdict after head accepted', mg.findMergeGateVerdict(
 const noise = [{ user: { login: 'MervinPraison' }, body: '**Merge gate scan** — wait for `@claude`', created_at: new Date().toISOString() }];
 assert('diagnostic comment not a trigger', !mg.hasRecentClaudeTrigger(noise, 35));
 
-// Cooldown skip requires an actual verdict on HEAD, not just a FINAL trigger comment
-const recentFinalOnHead = [
-  {
-    user: { login: 'MervinPraison' },
-    body: '@claude You are the FINAL architecture reviewer.',
-    created_at: '2026-06-27T10:00:00Z',
-  },
-];
-assert(
-  'final trigger alone does not count as verdict on head',
-  mg.findMergeGateVerdict(recentFinalOnHead, null, '2026-06-27T09:55:00Z') === null
-);
-const recentVerdictOnHead = [
-  ...recentFinalOnHead,
-  {
-    user: { login: 'github-actions[bot]' },
-    body: 'MERGE_GATE_VERDICT: APPROVE',
-    created_at: '2026-06-27T10:05:00Z',
-  },
-];
-assert(
-  'verdict on head skips cooldown gate',
-  mg.findMergeGateVerdict(recentVerdictOnHead, null, '2026-06-27T09:55:00Z') === 'APPROVE'
-);
-
 // Sensitive + secrets
 assert('workflow path sensitive', mg.sensitivePathReasons([{ filename: '.github/workflows/foo.yml' }]).length === 1);
 assert('ci-only label exempts workflows', mg.sensitivePathReasons(

.github/scripts/merge-gate.js

@@ -7,9 +7,7 @@ const CLAUDE_TRIGGER_LOGINS = ['MervinPraison', 'github-actions[bot]'];
 const AUTO_ACTORS = CLAUDE_TRIGGER_LOGINS;
 const CONFLICT_COOLDOWN_MS = 12 * 60 * 60 * 1000;
 const CLAUDE_ACTIVE_MS = 35 * 60 * 1000;
-const STALE_FINAL_RECOVERY_WINDOW_MS = 60 * 60 * 1000;
-const STALE_FINAL_MAX_PER_WINDOW = 2;
-const PUSH_AFTER_FINAL_DEBOUNCE_MS = 15 * 60 * 1000;
+const POST_PUSH_BUFFER_MS = 5 * 60 * 1000;
 const ALLOWED_MERGE_STATES = new Set(['CLEAN', 'UNSTABLE']);
 const AGENT_PY_MAX_AUTO_LINES = 100;
 const PR_MAX_AUTO_ADDITIONS = 800;
@@ -197,55 +195,6 @@ function shouldSkipFinalRecovery(comments, headPushedAt) {
   return hasRecentClaudeTrigger(comments, 35);
 }
 
-function countFinalTriggersSince(comments, sinceMs) {
-  return comments.filter(
-    (c) => isFinalClaudeTriggerComment(c) && new Date(c.created_at).getTime() > sinceMs
-  ).length;
-}
-
-function isClaudeAutomationLogin(login) {
-  const lower = (login || '').toLowerCase();
-  return lower.includes('praisonai-triage') || lower === 'github-actions[bot]';
-}
-
-function isPushSoonAfterLatestFinal(comments, headPushedAt) {
-  if (!headPushedAt) return false;
-  const finals = comments.filter(isFinalClaudeTriggerComment);
-  if (finals.length === 0) return false;
-  const latestFinal = finals.reduce((a, b) =>
-    new Date(a.created_at) > new Date(b.created_at) ? a : b
-  );
-  const finalTime = new Date(latestFinal.created_at).getTime();
-  const headTime = new Date(headPushedAt).getTime();
-  if (headTime <= finalTime) return false;
-  return headTime - finalTime < PUSH_AFTER_FINAL_DEBOUNCE_MS;
-}
-
-/** Returns { skip: true, reason } when stale-FINAL recovery should not post. */
-function shouldSkipStaleFinalRecovery(comments, headPushedAt, headPusherLogin = null) {
-  if (!isStaleFinalAfterPush(comments, headPushedAt)) {
-    return { skip: true, reason: 'not stale' };
-  }
-  if (headPusherLogin && isClaudeAutomationLogin(headPusherLogin)) {
-    return { skip: true, reason: 'head pushed by Claude automation' };
-  }
-  if (isPushSoonAfterLatestFinal(comments, headPushedAt)) {
-    return {
-      skip: true,
-      reason: 'head pushed soon after FINAL (wait for CI / batched fixes)',
-    };
-  }
-  const windowStart = Date.now() - STALE_FINAL_RECOVERY_WINDOW_MS;
-  const finalsInWindow = countFinalTriggersSince(comments, windowStart);
-  if (finalsInWindow >= STALE_FINAL_MAX_PER_WINDOW) {
-    return {
-      skip: true,
-      reason: `stale-FINAL capped (${finalsInWindow} FINAL triggers in last hour)`,
-    };
-  }
-  return { skip: false, reason: '' };
-}
-
 function finalClaudeCompletedOnSha(comments, headPushedAt) {
   if (!hasFinalClaudeReviewTrigger(comments)) return false;
   if (isStaleFinalAfterPush(comments, headPushedAt)) return false;
@@ -654,16 +603,15 @@ async function evaluatePipelineQuiescent(github, owner, repo, prNumber, core, op
     reasons.push('recent merge-conflict @claude');
   }
   if (!skipRecentClaudeCooldown && hasRecentClaudeTrigger(ctx.comments, 35)) {
-    const verdictOnHead = findMergeGateVerdict(ctx.comments, null, ctx.headPushedAt) !== null;
-    if (!verdictOnHead) reasons.push('recent @claude within 35min');
+    reasons.push('recent @claude within 35min');
   }
 
   if (!skipGlobalClaudeRunCheck && (await hasInProgressClaudeAssistant(github, owner, repo, prNumber))) {
     reasons.push('claude.yml in progress');
   }
 
-  const checksOk = await allChecksGreenOnSha(github, owner, repo, ctx.headSha, core);
-  if (!checksOk) reasons.push('CI not green on HEAD');
+  const headTime = new Date(ctx.headPushedAt).getTime();
+  if (Date.now() - headTime < POST_PUSH_BUFFER_MS) reasons.push('post-push buffer (<5min)');
 
   if (!finalClaudeCompletedOnSha(ctx.comments, ctx.headPushedAt)) {
     if (!hasFinalClaudeReviewTrigger(ctx.comments)) {
@@ -698,6 +646,9 @@ async function evaluatePipelineQuiescent(github, owner, repo, prNumber, core, op
   const sdkCheckReason = await sdkTestChecksReason(github, owner, repo, ctx.headSha, pullFiles, core);
   if (sdkCheckReason) reasons.push(sdkCheckReason);
 
+  const checksOk = await allChecksGreenOnSha(github, owner, repo, ctx.headSha, core);
+  if (!checksOk) reasons.push('CI not green on HEAD');
+
   if (ctx.pr.mergeable === false) reasons.push('not mergeable');
 
   const ready = reasons.length === 0;
@@ -788,12 +739,6 @@ module.exports = {
   isStaleFinalAfterPush,
   needsStaleFinalRecovery,
   shouldSkipFinalRecovery,
-  shouldSkipStaleFinalRecovery,
-  isClaudeAutomationLogin,
-  isPushSoonAfterLatestFinal,
-  countFinalTriggersSince,
-  STALE_FINAL_RECOVERY_WINDOW_MS,
-  STALE_FINAL_MAX_PER_WINDOW,
   FINAL_CLAUDE_REVIEW_BODY,
   loadPrContext,
   evaluatePipelineQuiescent,

.github/scripts/pipeline-status.js

@@ -155,39 +155,11 @@ async function syncPipelineLabels(github, owner, repo, prNumber, core) {
   }
 
   core?.info?.(`PR #${prNumber}: stage=${stage} blockers=[${blockers.join(', ')}]`);
-  return {
-    synced: true,
-    stage,
-    blockers,
-    ready: evalResult.ready,
-    reasons: evalResult.reasons,
-    labels: ctx.labels,
-    createdAt: new Date(ctx.pr.created_at).getTime(),
-  };
-}
-
-async function dispatchMergeGateForOldestReady(github, owner, repo, readyCandidates, core) {
-  if (!readyCandidates.length) return 0;
-  readyCandidates.sort((a, b) => a.createdAt - b.createdAt);
-  for (const cand of readyCandidates) {
-    if ((cand.labels || []).includes('claude-merge-gate-active')) {
-      core?.info?.(`Skip dispatch PR #${cand.prNumber}: merge gate already active`);
-      continue;
-    }
-    await github.rest.repos.createDispatchEvent({
-      owner,
-      repo,
-      event_type: 'claude-merge-gate',
-      client_payload: { pr_number: cand.prNumber },
-    });
-    core?.info?.(`Dispatched merge gate for ready PR #${cand.prNumber}`);
-    return cand.prNumber;
-  }
-  return 0;
+  return { synced: true, stage, blockers, ready: evalResult.ready, reasons: evalResult.reasons };
 }
 
 async function syncOpenPullRequests(github, owner, repo, options, core) {
-  const { maxPrs = 20, dispatchMergeGate = true } = options || {};
+  const { maxPrs = 20 } = options || {};
   await ensurePipelineLabels(github, owner, repo, core);
   let prs;
   if (maxPrs <= 100) {
@@ -206,28 +178,14 @@ async function syncOpenPullRequests(github, owner, repo, options, core) {
     });
   }
   let synced = 0;
-  const readyCandidates = [];
   for (const pr of prs) {
     if (synced >= maxPrs) break;
     if (pr.draft) continue;
     if (pr.head?.repo?.full_name && pr.head.repo.full_name !== `${owner}/${repo}`) continue;
-    const result = await syncPipelineLabels(github, owner, repo, pr.number, core);
-    if (result.ready) {
-      readyCandidates.push({
-        prNumber: pr.number,
-        createdAt: result.createdAt || new Date(pr.created_at).getTime(),
-        labels: result.labels || [],
-      });
-    }
+    await syncPipelineLabels(github, owner, repo, pr.number, core);
     synced += 1;
   }
-  let dispatched = 0;
-  if (dispatchMergeGate && readyCandidates.length) {
-    dispatched = await dispatchMergeGateForOldestReady(
-      github, owner, repo, readyCandidates, core
-    );
-  }
-  core?.info?.(`Pipeline label sync complete (${synced} PR(s), dispatched=${dispatched || 'none'})`);
+  core?.info?.(`Pipeline label sync complete (${synced} PR(s))`);
   return synced;
 }
 
@@ -241,5 +199,4 @@ module.exports = {
   ensurePipelineLabels,
   syncPipelineLabels,
   syncOpenPullRequests,
-  dispatchMergeGateForOldestReady,
 };

.github/scripts/release-gate-selftest.js

@@ -1,20 +0,0 @@
-const assert = require('assert');
-const rg = require('./release-gate.js');
-
-assert.strictEqual(rg.bumpPatch('1.6.80'), '1.6.81');
-assert.strictEqual(rg.bumpPatch('4.6.80'), '4.6.81');
-assert.strictEqual(rg.bumpPatch('0.0.2'), '0.0.3');
-
-const versions = rg.readVersionsFromTree();
-assert.ok(versions.currentAgents);
-assert.ok(versions.currentCode);
-assert.ok(versions.currentWrapper);
-assert.ok(versions.targetCode);
-assert.ok(rg.PACKAGE_PATHS.includes('src/praisonai-code'));
-
-(async () => {
-  assert.strictEqual(await rg.pypiVersionExists('praisonaiagents', '0.0.0'), false);
-  console.log('ok: bumpPatch');
-  console.log('ok: readVersionsFromTree');
-  console.log('ok: pypiVersionExists missing version');
-})();

.github/scripts/release-gate.js

@@ -1,203 +0,0 @@
-/**
- * Release gate preflight — path changes, CI SHA, dedupe, PyPI version checks.
- */
-
-const https = require('https');
-
-const PACKAGE_PATHS = ['src/praisonai', 'src/praisonai-agents', 'src/praisonai-code'];
-const ACTIVE_RELEASE_STATUSES = new Set([
-  'queued', 'in_progress', 'waiting', 'pending', 'requested',
-]);
-
-function bumpPatch(version) {
-  const parts = version.split('.');
-  if (parts.length !== 3) throw new Error(`Invalid version: ${version}`);
-  return `${parts[0]}.${parts[1]}.${Number(parts[2]) + 1}`;
-}
-
-function readVersionsFromTree(root = '.') {
-  const fs = require('fs');
-  const path = require('path');
-  const agentsToml = fs.readFileSync(
-    path.join(root, 'src/praisonai-agents/pyproject.toml'), 'utf8'
-  );
-  const agentsMatch = agentsToml.match(/^version\s*=\s*"([^"]+)"/m);
-  if (!agentsMatch) throw new Error('Could not read agents version');
-
-  const codeToml = fs.readFileSync(
-    path.join(root, 'src/praisonai-code/pyproject.toml'), 'utf8'
-  );
-  const codeMatch = codeToml.match(/^version\s*=\s*"([^"]+)"/m);
-  if (!codeMatch) throw new Error('Could not read praisonai-code version');
-
-  const wrapperPy = fs.readFileSync(
-    path.join(root, 'src/praisonai/praisonai/version.py'), 'utf8'
-  );
-  const wrapperMatch = wrapperPy.match(/__version__ = "([^"]+)"/);
-  if (!wrapperMatch) throw new Error('Could not read wrapper version');
-  return {
-    currentAgents: agentsMatch[1],
-    currentCode: codeMatch[1],
-    currentWrapper: wrapperMatch[1],
-    targetAgents: bumpPatch(agentsMatch[1]),
-    targetCode: bumpPatch(codeMatch[1]),
-    targetWrapper: bumpPatch(wrapperMatch[1]),
-  };
-}
-
-function pypiVersionExists(packageName, version) {
-  return new Promise((resolve) => {
-    const req = https.get(
-      `https://pypi.org/pypi/${packageName}/${version}/json`,
-      { timeout: 15000 },
-      (res) => {
-        res.resume();
-        resolve(res.statusCode === 200);
-      }
-    );
-    req.on('error', () => resolve(false));
-    req.on('timeout', () => {
-      req.destroy();
-      resolve(false);
-    });
-  });
-}
-
-async function hasActiveReleaseRun(github, owner, repo) {
-  const runs = await github.rest.actions.listWorkflowRuns({
-    owner,
-    repo,
-    workflow_id: 'pypi-release.yml',
-    per_page: 20,
-  });
-  return runs.data.workflow_runs.some(
-    (r) => ACTIVE_RELEASE_STATUSES.has(r.status) && !r.conclusion
-  );
-}
-
-async function lastGreenCoreTestsSha(github, owner, repo) {
-  const runs = await github.rest.actions.listWorkflowRuns({
-    owner,
-    repo,
-    workflow_id: 'test-core.yml',
-    branch: 'main',
-    status: 'completed',
-    per_page: 30,
-  });
-  const hit = runs.data.workflow_runs.find((r) => r.conclusion === 'success');
-  return hit ? hit.head_sha : '';
-}
-
-async function evaluateReleasePreflight(github, owner, repo, options, core) {
-  const {
-    headSha,
-    isCiTrigger = false,
-    bump = 'patch',
-  } = options;
-
-  const reasons = [];
-  const out = {
-    ready: false,
-    reasons,
-    headSha: headSha || '',
-    lastTag: '',
-    targetAgents: '',
-    targetCode: '',
-    targetWrapper: '',
-  };
-
-  if (bump !== 'patch') {
-    reasons.push('only patch auto-release supported');
-    return out;
-  }
-
-  if (await hasActiveReleaseRun(github, owner, repo)) {
-    reasons.push('PyPI Release already in progress or awaiting approval');
-    return out;
-  }
-
-  let versions;
-  try {
-    versions = readVersionsFromTree();
-  } catch (err) {
-    reasons.push(err.message);
-    return out;
-  }
-  out.targetAgents = versions.targetAgents;
-  out.targetCode = versions.targetCode;
-  out.targetWrapper = versions.targetWrapper;
-
-  const agentsOnPypi = await pypiVersionExists('praisonaiagents', versions.targetAgents);
-  const codeOnPypi = await pypiVersionExists('praisonai-code', versions.targetCode);
-  const wrapperOnPypi = await pypiVersionExists('praisonai', versions.targetWrapper);
-  if (agentsOnPypi && codeOnPypi && wrapperOnPypi) {
-    reasons.push(
-      `already published: praisonaiagents==${versions.targetAgents}, `
-      + `praisonai-code==${versions.targetCode}, praisonai==${versions.targetWrapper}`
-    );
-    return out;
-  }
-
-  const { execSync } = require('child_process');
-  let lastTag = '';
-  try {
-    lastTag = execSync('git describe --tags --match "v*" --abbrev=0', { encoding: 'utf8' }).trim();
-  } catch {
-    reasons.push('no v* tag found');
-    return out;
-  }
-  out.lastTag = lastTag;
-
-  let changed = '';
-  try {
-    changed = execSync(
-      `git diff --name-only ${lastTag} HEAD -- ${PACKAGE_PATHS.join(' ')}`,
-      { encoding: 'utf8' }
-    ).trim();
-  } catch {
-    reasons.push('git diff failed');
-    return out;
-  }
-
-  if (!changed) {
-    reasons.push(`no changes in ${PACKAGE_PATHS.join(' or ')} since ${lastTag}`);
-    return out;
-  }
-
-  if (isCiTrigger) {
-    let mainSha = '';
-    try {
-      mainSha = execSync('git rev-parse origin/main', { encoding: 'utf8' }).trim();
-    } catch {
-      reasons.push('could not resolve origin/main');
-      return out;
-    }
-    if (headSha !== mainSha) {
-      reasons.push(`superseded: green SHA ${headSha.slice(0, 7)} != main ${mainSha.slice(0, 7)}`);
-      return out;
-    }
-    out.headSha = headSha;
-  } else {
-    const evalSha = execSync('git rev-parse HEAD', { encoding: 'utf8' }).trim();
-    out.headSha = evalSha;
-    const greenSha = await lastGreenCoreTestsSha(github, owner, repo);
-    if (greenSha !== evalSha) {
-      reasons.push(`CI not green on HEAD (last green: ${greenSha ? greenSha.slice(0, 7) : 'none'})`);
-      return out;
-    }
-  }
-
-  out.ready = true;
-  out.reasons = ['ready'];
-  if (core) core.info(`Release preflight passed for ${out.headSha || headSha}`);
-  return out;
-}
-
-module.exports = {
-  bumpPatch,
-  readVersionsFromTree,
-  pypiVersionExists,
-  evaluateReleasePreflight,
-  ACTIVE_RELEASE_STATUSES,
-  PACKAGE_PATHS,
-};

.github/workflows/auto-pr-comment.yml

@@ -550,7 +550,6 @@ jobs:
             const comments = await mergeGate.listAllComments(github, owner, repo, pr);
             const headPushedAt = (await mergeGate.getHeadCommitDate(github, owner, repo, pr))
               || context.payload.pull_request.updated_at;
-            const headPusher = context.payload.sender?.login || null;
 
             const hasFinal = mergeGate.hasFinalClaudeReviewTrigger(comments);
             const isStale = mergeGate.isStaleFinalAfterPush(comments, headPushedAt);
@@ -560,19 +559,9 @@ jobs:
               return;
             }
 
-            if (await mergeGate.hasInProgressClaudeAssistant(github, owner, repo, pr)) {
-              core.info('Claude workflow in progress — skip recovery');
-              return;
-            }
-
             const finalBody = mergeGate.FINAL_CLAUDE_REVIEW_BODY;
 
             if (hasFinal && isStale) {
-              const gate = mergeGate.shouldSkipStaleFinalRecovery(comments, headPushedAt, headPusher);
-              if (gate.skip) {
-                core.info(`Skip stale-FINAL recovery: ${gate.reason}`);
-                return;
-              }
               await github.rest.issues.createComment({ issue_number: pr, owner, repo, body: finalBody });
               core.info(`Posted stale-FINAL recovery @claude on PR #${pr}`);
               return;
@@ -640,15 +629,6 @@ jobs:
                 core.info(`PR #${pr.number}: stale FINAL but @claude within 10min — skip`);
                 continue;
               }
-              if (await mergeGate.hasInProgressClaudeAssistant(github, owner, repo, pr.number)) {
-                core.info(`PR #${pr.number}: Claude workflow in progress — skip`);
-                continue;
-              }
-              const gate = mergeGate.shouldSkipStaleFinalRecovery(comments, headPushedAt);
-              if (gate.skip) {
-                core.info(`PR #${pr.number}: skip stale-FINAL — ${gate.reason}`);
-                continue;
-              }
               await github.rest.issues.createComment({
                 issue_number: pr.number, owner, repo,
                 body: mergeGate.FINAL_CLAUDE_REVIEW_BODY,

.github/workflows/claude-merge-gate.yml

@@ -5,8 +5,7 @@ name: Claude PR Merge Gate
 
 on:
   schedule:
-    # Scan for merge-ready PRs every 10 minutes (assess runs only when candidates exist).
-    - cron: '*/10 * * * *'
+    - cron: '0 2,8,14,20 * * *'
   workflow_dispatch:
     inputs:
       pr_number:
@@ -34,11 +33,11 @@ on:
 
 concurrency:
   group: claude-merge-gate-${{ github.repository }}-${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || github.event.workflow_run.id || 'scan' }}
-  cancel-in-progress: false
+  cancel-in-progress: true
 
 env:
   GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
-  MAX_CANDIDATES: 1
+  MAX_CANDIDATES: 5
   DISPATCH_PR_NUMBER: ${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || '' }}
 
 permissions:
@@ -451,38 +450,9 @@ jobs:
               }
 
               const method = process.env.MERGE_METHOD || 'merge';
-              const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
-              let merged = false;
-              for (let attempt = 1; attempt <= 3; attempt++) {
-                try {
-                  await github.rest.pulls.merge({
-                    owner, repo, pull_number: prNumber, merge_method: method,
-                  });
-                  merged = true;
-                  break;
-                } catch (e) {
-                  const msg = (e.message || '').toLowerCase();
-                  if (attempt < 3 && msg.includes('base branch was modified')) {
-                    core.info(`Merge attempt ${attempt} failed (base moved), retrying in 8s...`);
-                    await sleep(8000);
-                    const recheck = await mergeGate.evaluatePipelineQuiescent(
-                      github, owner, repo, prNumber, core, { forMergeStep: true }
-                    );
-                    if (!recheck.ready) {
-                      core.info(`Skip merge retry: ${recheck.reasons.join(', ')}`);
-                      await removeLabels();
-                      return;
-                    }
-                    continue;
-                  }
-                  throw e;
-                }
-              }
-              if (!merged) {
-                core.info('Skip merge: exhausted retries');
-                await removeLabels();
-                return;
-              }
+              await github.rest.pulls.merge({
+                owner, repo, pull_number: prNumber, merge_method: method,
+              });
 
               await github.rest.issues.addLabels({
                 owner, repo, issue_number: prNumber, labels: ['auto-merged-by-gate'],

.github/workflows/claude.yml

@@ -133,9 +133,6 @@ jobs:
       github.actor != 'dependabot[bot]' &&
       github.actor != 'cursor[bot]' &&
       github.actor != 'renovate[bot]'
-    concurrency:
-      group: claude-response-${{ github.repository }}-${{ github.event.pull_request.number || github.event.issue.number || github.run_id }}
-      cancel-in-progress: false
     runs-on: ubuntu-latest
     permissions:
       contents: write

.github/workflows/integration-cross-repo.yml

@@ -7,18 +7,12 @@ on:
       - 'src/praisonai/praisonai/integration/**'
       - 'src/praisonai/tests/integration/test_aiui_*'
       - 'src/praisonai/pyproject.toml'
-      - 'src/praisonai-code/**'
-      - '.github/workflows/integration-cross-repo.yml'
-      - '.github/actions/install-monorepo-packages/**'
   pull_request:
     branches: [ main ]
     paths:
       - 'src/praisonai/praisonai/integration/**'
       - 'src/praisonai/tests/integration/test_aiui_*'
       - 'src/praisonai/pyproject.toml'
-      - 'src/praisonai-code/**'
-      - '.github/workflows/integration-cross-repo.yml'
-      - '.github/actions/install-monorepo-packages/**'
   workflow_dispatch:
 
 jobs:
@@ -46,16 +40,16 @@ jobs:
         python-version: '3.11'
         
     - name: Install dependencies
-      run: python -m pip install --upgrade pip
-    - uses: PraisonAI/.github/actions/install-monorepo-packages
-      with:
-        repo-root: PraisonAI/
-        wrapper-extras: ".[ui,dev]"
-    - name: Install PraisonAIUI
       run: |
-        cd PraisonAIUI
+        python -m pip install --upgrade pip
+        # Install PraisonAI packages in development mode
+        cd PraisonAI/src/praisonai-agents
+        pip install -e .
+        cd ../praisonai
+        pip install -e ".[ui,dev]"
+        # Install PraisonAIUI in development mode
+        cd ../../../PraisonAIUI
         pip install -e .
-        pip install pytest pytest-cov
         
     - name: Verify versions
       run: |
@@ -143,14 +137,13 @@ jobs:
         python-version: '3.11'
         
     - name: Install dependencies
-      run: python -m pip install --upgrade pip
-    - uses: PraisonAI/.github/actions/install-monorepo-packages
-      with:
-        repo-root: PraisonAI/
-        wrapper-extras: ".[ui,dev]"
-    - name: Install PraisonAIUI
       run: |
-        cd PraisonAIUI
+        python -m pip install --upgrade pip
+        cd PraisonAI/src/praisonai-agents
+        pip install -e .
+        cd ../praisonai
+        pip install -e ".[ui,dev]"
+        cd ../../../PraisonAIUI
         pip install -e .
         
     - name: Run agentic integration test

.github/workflows/nightly-release-gate.yml

@@ -1,8 +1,7 @@
 name: Nightly Release Gate
 
-# Preflight before PyPI Release (patch bump).
-# Primary: Core Tests success on main (workflow_run).
-# Backstop: nightly cron at 00:00 UTC.
+# Preflight checks before dispatching PyPI Release (patch bump).
+# Runs nightly at 00:00 UTC (midnight).
 
 on:
   schedule:
@@ -14,13 +13,6 @@ on:
         required: false
         default: false
         type: boolean
-  workflow_run:
-    workflows:
-      - Core Tests
-    types:
-      - completed
-    branches:
-      - main
 
 permissions:
   contents: read
@@ -32,85 +24,83 @@ concurrency:
 
 jobs:
   preflight:
-    if: |
-      github.event_name == 'workflow_dispatch' ||
-      github.event_name == 'schedule' ||
-      (
-        github.event_name == 'workflow_run' &&
-        github.event.workflow_run.conclusion == 'success' &&
-        github.event.workflow_run.head_branch == 'main' &&
-        github.event.workflow_run.event == 'push'
-      )
+    if: github.ref == 'refs/heads/main' || github.event_name == 'workflow_dispatch'
     runs-on: ubuntu-latest
     env:
       GH_TOKEN: ${{ secrets.GH_TOKEN }}
     steps:
-      - name: Resolve trigger context
-        id: ctx
-        run: |
-          if [ "${{ github.event_name }}" = "workflow_run" ]; then
-            echo "checkout_sha=${{ github.event.workflow_run.head_sha }}" >> "$GITHUB_OUTPUT"
-            echo "source=ci" >> "$GITHUB_OUTPUT"
-            echo "is_ci=true" >> "$GITHUB_OUTPUT"
-          else
-            echo "checkout_sha=main" >> "$GITHUB_OUTPUT"
-            echo "source=nightly" >> "$GITHUB_OUTPUT"
-            echo "is_ci=false" >> "$GITHUB_OUTPUT"
-          fi
-
-      - name: Checkout
+      - name: Checkout main
         uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5  # v4
         with:
-          ref: ${{ steps.ctx.outputs.checkout_sha }}
+          ref: main
           fetch-depth: 0
 
-      - name: Fetch main and tags
-        run: git fetch --tags origin main
-
-      - name: Preflight — path changes, CI SHA, dedupe
+      - name: Preflight — path changes and CI green
         id: preflight
-        uses: actions/github-script@v7
-        env:
-          HEAD_SHA: ${{ steps.ctx.outputs.checkout_sha }}
-          IS_CI: ${{ steps.ctx.outputs.is_ci }}
-        with:
-          github-token: ${{ secrets.GH_TOKEN }}
-          script: |
-            const path = require('path');
-            const rg = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/release-gate.js'));
-            const owner = context.repo.owner;
-            const repo = context.repo.repo;
-            const headSha = process.env.HEAD_SHA;
-            const isCi = process.env.IS_CI === 'true';
+        run: |
+          set -euo pipefail
 
-            const result = await rg.evaluateReleasePreflight(
-              github, owner, repo,
-              { headSha, isCiTrigger: isCi, bump: 'patch' },
-              core
-            );
+          git fetch --tags origin
 
-            core.setOutput('should_release', result.ready ? 'true' : 'false');
-            core.setOutput('reason', result.reasons.join('; '));
-            core.setOutput('head_sha', result.headSha || headSha);
-            core.setOutput('last_tag', result.lastTag || '');
-            core.setOutput('target_agents', result.targetAgents || '');
-            core.setOutput('target_code', result.targetCode || '');
-            core.setOutput('target_wrapper', result.targetWrapper || '');
+          LAST_TAG=$(git describe --tags --match 'v*' --abbrev=0 2>/dev/null || true)
+          if [ -z "$LAST_TAG" ]; then
+            echo "No v* tag found — skip automated release (first release must be manual)"
+            echo "should_release=false" >> "$GITHUB_OUTPUT"
+            echo "reason=no_tag" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
 
-            core.summary.addRaw('## Release gate preflight\n');
-            core.summary.addRaw(`Ready: ${result.ready}\n`);
-            core.summary.addRaw(`Reason: ${result.reasons.join('; ')}\n`);
-            if (result.targetAgents) {
-              core.summary.addRaw(
-                `Targets: praisonaiagents==${result.targetAgents}, `
-                + `praisonai-code==${result.targetCode}, praisonai==${result.targetWrapper}\n`
-              );
-            }
-            await core.summary.write();
+          CHANGED=$(git diff --name-only "${LAST_TAG}" HEAD -- \
+            src/praisonai \
+            src/praisonai-agents || true)
 
-            if (!result.ready) {
-              core.info(`Skip release: ${result.reasons.join('; ')}`);
-            }
+          if [ -z "$CHANGED" ]; then
+            echo "No changes in src/praisonai or src/praisonai-agents since ${LAST_TAG} — skip"
+            echo "should_release=false" >> "$GITHUB_OUTPUT"
+            echo "reason=no_path_changes" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          echo "Changes since ${LAST_TAG}:"
+          echo "$CHANGED"
+
+          HEAD_SHA=$(git rev-parse HEAD)
+          echo "main HEAD: ${HEAD_SHA}"
+
+          GREEN_SHA=$(gh run list \
+            --repo "${GITHUB_REPOSITORY}" \
+            --workflow "Core Tests" \
+            --branch main \
+            --status success \
+            --json headSha \
+            --jq '.[0].headSha // empty')
+
+          if [ "$GREEN_SHA" != "$HEAD_SHA" ]; then
+            echo "main@${HEAD_SHA} is not covered by a green Core Tests run (last green: ${GREEN_SHA:-none}) — skip"
+            echo "should_release=false" >> "$GITHUB_OUTPUT"
+            echo "reason=ci_not_green" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          IN_PROGRESS=$(gh run list \
+            --repo "${GITHUB_REPOSITORY}" \
+            --workflow "Core Tests" \
+            --branch main \
+            --json headSha,status \
+            --jq "[.[] | select(.headSha == \"${HEAD_SHA}\" and .status == \"in_progress\")] | length")
+
+          if [ "${IN_PROGRESS:-0}" != "0" ]; then
+            echo "Core Tests still in progress on ${HEAD_SHA} — skip"
+            echo "should_release=false" >> "$GITHUB_OUTPUT"
+            echo "reason=ci_in_progress" >> "$GITHUB_OUTPUT"
+            exit 0
+          fi
+
+          echo "Preflight passed — ready to dispatch patch release"
+          echo "should_release=true" >> "$GITHUB_OUTPUT"
+          echo "reason=ready" >> "$GITHUB_OUTPUT"
+          echo "last_tag=${LAST_TAG}" >> "$GITHUB_OUTPUT"
+          echo "head_sha=${HEAD_SHA}" >> "$GITHUB_OUTPUT"
 
       - name: Dry run summary
         if: inputs.dry_run == true
@@ -118,6 +108,9 @@ jobs:
           echo "Dry run — preflight only, no pypi-release dispatch."
           echo "should_release=${{ steps.preflight.outputs.should_release }}"
           echo "reason=${{ steps.preflight.outputs.reason }}"
+          if [ "${{ steps.preflight.outputs.should_release }}" = "true" ]; then
+            echo "Would dispatch: pypi-release.yml bump=patch source=nightly"
+          fi
 
       - name: Dispatch PyPI Release (patch)
         if: steps.preflight.outputs.should_release == 'true' && inputs.dry_run != true
@@ -127,12 +120,7 @@ jobs:
             --repo "${GITHUB_REPOSITORY}" \
             --ref main \
             -f bump=patch \
-            -f source=${{ steps.ctx.outputs.source }} \
-            -f trigger_sha=${{ steps.preflight.outputs.head_sha }} \
+            -f source=nightly \
             -f dry_run=false
-          echo "Dispatched pypi-release.yml (patch, source=${{ steps.ctx.outputs.source }})"
-          if [ "${{ steps.ctx.outputs.source }}" = "ci" ]; then
-            echo "Uses pypi-auto environment (no manual approval)."
-          else
-            echo "Uses pypi-auto environment for nightly patch releases."
-          fi
+          echo "Dispatched pypi-release.yml (patch, source=nightly)"
+          echo "Approve the pypi environment when prompted."

.github/workflows/pipeline-status-sync.yml

@@ -4,13 +4,12 @@ name: Pipeline Status Sync
 
 on:
   schedule:
-    - cron: '*/10 * * * *'
+    - cron: '*/15 * * * *'
   workflow_dispatch:
 
 permissions:
   pull-requests: read
   issues: write
-  actions: write
 
 jobs:
   sync:
@@ -28,6 +27,5 @@ jobs:
             const path = require('path');
             const ps = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/pipeline-status.js'));
             await ps.syncOpenPullRequests(
-              github, context.repo.owner, context.repo.repo,
-              { maxPrs: 30, dispatchMergeGate: true }, core
+              github, context.repo.owner, context.repo.repo, { maxPrs: 30 }, core
             );

.github/workflows/praisonai-issue-triage.yml

@@ -49,12 +49,10 @@ jobs:
           git config --local user.name "PraisonAI Bot"
           
       - name: Install PraisonAI
-        run: pip install uv
-      - uses: ./.github/actions/install-monorepo-packages
-        with:
-          use-uv: "true"
-          agents-extras: ".[all]"
-          wrapper-extras: ".[all]"
+        run: |
+          pip install uv
+          cd src/praisonai-agents && uv pip install --system -e ".[all]"
+          cd ../praisonai && uv pip install --system -e ".[all]"
         
       - name: Run PraisonAI Issue Triage
         env:

.github/workflows/pypi-release.yml

@@ -1,14 +1,13 @@
 name: PyPI Release
 
-# Environments (Settings → Environments):
-#   pypi-auto — patch releases from ci/nightly (no reviewers, main branch only)
-#   pypi      — manual workflow_dispatch and major/minor (required reviewers)
+# Requires a GitHub Environment named "pypi" (Settings → Environments → pypi)
+# with required reviewers before secrets are exposed to this job.
 
 on:
   workflow_dispatch:
     inputs:
       bump:
-        description: 'Version bump type for all packages (agents, code, wrapper)'
+        description: 'Version bump type for both packages'
         required: true
         default: patch
         type: choice
@@ -27,12 +26,7 @@ on:
         default: false
         type: boolean
       skip_wrapper:
-        description: 'Skip wrapper publish (agents and/or code only)'
-        required: false
-        default: false
-        type: boolean
-      skip_code:
-        description: 'Skip praisonai-code publish (recovery if already on PyPI)'
+        description: 'Publish agents only'
         required: false
         default: false
         type: boolean
@@ -46,11 +40,6 @@ on:
         required: false
         default: ''
         type: string
-      code_version:
-        description: 'Override praisonai-code version (empty = auto bump from pyproject.toml)'
-        required: false
-        default: ''
-        type: string
       source:
         description: 'Trigger source (audit trail)'
         required: false
@@ -59,12 +48,6 @@ on:
         options:
           - manual
           - nightly
-          - ci
-      trigger_sha:
-        description: 'Main commit SHA that passed release gate (audit/dedupe)'
-        required: false
-        default: ''
-        type: string
 
 permissions:
   contents: write
@@ -77,12 +60,7 @@ jobs:
   release:
     if: github.ref == 'refs/heads/main'
     runs-on: ubuntu-latest
-    environment: >-
-      ${{
-        (inputs.source == 'ci' || inputs.source == 'nightly') &&
-        inputs.bump == 'patch' &&
-        'pypi-auto' || 'pypi'
-      }}
+    environment: pypi
     env:
       UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
       GH_TOKEN: ${{ secrets.GH_TOKEN }}
@@ -111,10 +89,8 @@ jobs:
       - name: Release summary
         run: |
           echo "Source: ${{ inputs.source }}"
-          echo "Trigger SHA: ${{ inputs.trigger_sha }}"
           echo "Bump:   ${{ inputs.bump }}"
           echo "Dry run: ${{ inputs.dry_run }}"
-          echo "Environment: ${{ (inputs.source == 'ci' || inputs.source == 'nightly') && inputs.bump == 'patch' && 'pypi-auto' || 'pypi' }}"
 
       - name: Compute release versions
         id: versions
@@ -122,9 +98,7 @@ jobs:
           BUMP: ${{ inputs.bump }}
           AGENTS_OVERRIDE: ${{ inputs.agents_version }}
           WRAPPER_OVERRIDE: ${{ inputs.wrapper_version }}
-          CODE_OVERRIDE: ${{ inputs.code_version }}
           SKIP_AGENTS: ${{ inputs.skip_agents }}
-          SKIP_CODE: ${{ inputs.skip_code }}
         run: |
           python <<'PY'
           import os
@@ -155,10 +129,8 @@ jobs:
 
           agents_override = os.environ.get("AGENTS_OVERRIDE", "").strip()
           wrapper_override = os.environ.get("WRAPPER_OVERRIDE", "").strip()
-          code_override = os.environ.get("CODE_OVERRIDE", "").strip()
           validate_version("agents_version", agents_override)
           validate_version("wrapper_version", wrapper_override)
-          validate_version("code_version", code_override)
 
           agents_pyproject = root / "src/praisonai-agents/pyproject.toml"
           agents_content = agents_pyproject.read_text()
@@ -167,14 +139,9 @@ jobs:
               print("Could not read agents version from pyproject.toml", file=sys.stderr)
               sys.exit(1)
           current_agents = agents_match.group(1)
-
-          code_pyproject = root / "src/praisonai-code/pyproject.toml"
-          code_content = code_pyproject.read_text()
-          code_match = re.search(r'^version\s*=\s*"([^"]+)"', code_content, re.MULTILINE)
-          if not code_match:
-              print("Could not read praisonai-code version from pyproject.toml", file=sys.stderr)
+          if not SEMVER.match(current_agents):
+              print(f"Invalid current agents version: {current_agents}", file=sys.stderr)
               sys.exit(1)
-          current_code = code_match.group(1)
 
           wrapper_version_py = root / "src/praisonai/praisonai/version.py"
           wrapper_content = wrapper_version_py.read_text()
@@ -183,18 +150,11 @@ jobs:
               print("Could not read wrapper version from version.py", file=sys.stderr)
               sys.exit(1)
           current_wrapper = wrapper_match.group(1)
-
-          for label, value in (
-              ("agents", current_agents),
-              ("code", current_code),
-              ("wrapper", current_wrapper),
-          ):
-              if not SEMVER.match(value):
-                  print(f"Invalid current {label} version: {value}", file=sys.stderr)
-                  sys.exit(1)
+          if not SEMVER.match(current_wrapper):
+              print(f"Invalid current wrapper version: {current_wrapper}", file=sys.stderr)
+              sys.exit(1)
 
           skip_agents = os.environ.get("SKIP_AGENTS", "false").lower() == "true"
-          skip_code = os.environ.get("SKIP_CODE", "false").lower() == "true"
 
           if agents_override:
               agents_version = agents_override
@@ -203,13 +163,6 @@ jobs:
           else:
               agents_version = bump_version(current_agents)
 
-          if code_override:
-              code_version = code_override
-          elif skip_code:
-              code_version = current_code
-          else:
-              code_version = bump_version(current_code)
-
           if wrapper_override:
               wrapper_version = wrapper_override
           else:
@@ -218,80 +171,32 @@ jobs:
           github_output = os.environ["GITHUB_OUTPUT"]
           with open(github_output, "a", encoding="utf-8") as fh:
               fh.write(f"agents_version={agents_version}\n")
-              fh.write(f"code_version={code_version}\n")
               fh.write(f"wrapper_version={wrapper_version}\n")
               fh.write(f"current_agents={current_agents}\n")
-              fh.write(f"current_code={current_code}\n")
               fh.write(f"current_wrapper={current_wrapper}\n")
 
           print(f"Agents:  {current_agents} -> {agents_version}")
-          print(f"Code:    {current_code} -> {code_version}")
           print(f"Wrapper: {current_wrapper} -> {wrapper_version}")
           PY
 
-      - name: Detect existing PyPI versions
-        id: pypi_exists
-        if: inputs.dry_run != true
-        env:
-          AGENTS_VERSION: ${{ steps.versions.outputs.agents_version }}
-          CODE_VERSION: ${{ steps.versions.outputs.code_version }}
-          WRAPPER_VERSION: ${{ steps.versions.outputs.wrapper_version }}
-          INPUT_SKIP_AGENTS: ${{ inputs.skip_agents }}
-          INPUT_SKIP_CODE: ${{ inputs.skip_code }}
-          INPUT_SKIP_WRAPPER: ${{ inputs.skip_wrapper }}
-        run: |
-          set -euo pipefail
-          skip_agents="${INPUT_SKIP_AGENTS}"
-          skip_code="${INPUT_SKIP_CODE}"
-          skip_wrapper="${INPUT_SKIP_WRAPPER}"
-          if [ "$skip_agents" != "true" ]; then
-            curl -fsSL "https://pypi.org/pypi/praisonaiagents/${AGENTS_VERSION}/json" >/dev/null && skip_agents=true || true
-          fi
-          if [ "$skip_code" != "true" ]; then
-            curl -fsSL "https://pypi.org/pypi/praisonai-code/${CODE_VERSION}/json" >/dev/null && skip_code=true || true
-          fi
-          if [ "$skip_wrapper" != "true" ]; then
-            curl -fsSL "https://pypi.org/pypi/praisonai/${WRAPPER_VERSION}/json" >/dev/null && skip_wrapper=true || true
-          fi
-          echo "skip_agents=${skip_agents}" >> "$GITHUB_OUTPUT"
-          echo "skip_code=${skip_code}" >> "$GITHUB_OUTPUT"
-          echo "skip_wrapper=${skip_wrapper}" >> "$GITHUB_OUTPUT"
-          if [ "$skip_agents" = "true" ] && [ "$skip_code" = "true" ] && [ "$skip_wrapper" = "true" ]; then
-            echo "All target versions already on PyPI — nothing to publish."
-          fi
-
-      - name: Exit if already published
-        if: >-
-          inputs.dry_run != true &&
-          steps.pypi_exists.outputs.skip_agents == 'true' &&
-          steps.pypi_exists.outputs.skip_code == 'true' &&
-          steps.pypi_exists.outputs.skip_wrapper == 'true'
-        run: echo "Idempotent skip — target versions already on PyPI."
-
       - name: Dry run summary
         if: inputs.dry_run
         run: |
           echo "Dry run — no publish, commit, or push."
           echo "Agents version:  ${{ steps.versions.outputs.agents_version }}"
-          echo "Code version:    ${{ steps.versions.outputs.code_version }}"
           echo "Wrapper version: ${{ steps.versions.outputs.wrapper_version }}"
           echo ""
           if [ "${{ inputs.skip_agents }}" != "true" ]; then
             echo "Would publish praisonaiagents ${{ steps.versions.outputs.agents_version }}"
-          fi
-          if [ "${{ inputs.skip_code }}" != "true" ]; then
-            echo "Would publish praisonai-code ${{ steps.versions.outputs.code_version }}"
+            echo "Would commit src/praisonai-agents/pyproject.toml and uv.lock"
           fi
           if [ "${{ inputs.skip_wrapper }}" != "true" ]; then
-            echo "Would run bump_and_release.py ${{ steps.versions.outputs.wrapper_version }} --agents ${{ steps.versions.outputs.agents_version }} --code-pin ${{ steps.versions.outputs.code_version }}"
+            echo "Would run bump_and_release.py ${{ steps.versions.outputs.wrapper_version }} --agents ${{ steps.versions.outputs.agents_version }}"
             echo "Would uv publish praisonai ${{ steps.versions.outputs.wrapper_version }}"
           fi
 
       - name: Publish praisonaiagents
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_agents != true &&
-          steps.pypi_exists.outputs.skip_agents != 'true'
+        if: inputs.dry_run != true && inputs.skip_agents != true
         working-directory: src/praisonai-agents
         env:
           NEW_VERSION: ${{ steps.versions.outputs.agents_version }}
@@ -314,10 +219,7 @@ jobs:
           uv publish
 
       - name: Wait for praisonaiagents on PyPI
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_agents != true &&
-          steps.pypi_exists.outputs.skip_agents != 'true'
+        if: inputs.dry_run != true && inputs.skip_agents != true
         run: |
           set -euo pipefail
           PACKAGE="praisonaiagents"
@@ -341,10 +243,7 @@ jobs:
           done
 
       - name: Commit agents version bump
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_agents != true &&
-          steps.pypi_exists.outputs.skip_agents != 'true'
+        if: inputs.dry_run != true && inputs.skip_agents != true
         run: |
           set -euo pipefail
           git add src/praisonai-agents/pyproject.toml src/praisonai-agents/uv.lock
@@ -353,101 +252,21 @@ jobs:
           git pull --rebase origin main
           git push origin main
 
-      - name: Publish praisonai-code
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_code != true &&
-          steps.pypi_exists.outputs.skip_code != 'true'
-        working-directory: src/praisonai-code
-        env:
-          NEW_VERSION: ${{ steps.versions.outputs.code_version }}
-          CURRENT: ${{ steps.versions.outputs.current_code }}
-        run: |
-          set -euo pipefail
-          python <<'PY'
-          import os
-          import re
-          from pathlib import Path
-          new = os.environ["NEW_VERSION"]
-          current = os.environ["CURRENT"]
-          pyproject = Path("pyproject.toml")
-          content = pyproject.read_text()
-          pyproject.write_text(content.replace(f'version = "{current}"', f'version = "{new}"', 1))
-          init_py = Path("praisonai_code/__init__.py")
-          init_content = init_py.read_text()
-          init_py.write_text(re.sub(r'__version__ = "[^"]+"', f'__version__ = "{new}"', init_content, count=1))
-          PY
-
-          rm -rf dist
-          uv lock
-          uv build
-          uv publish
-
-      - name: Wait for praisonai-code on PyPI
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_code != true &&
-          steps.pypi_exists.outputs.skip_code != 'true'
-        run: |
-          set -euo pipefail
-          PACKAGE="praisonai-code"
-          VERSION="${{ steps.versions.outputs.code_version }}"
-          MAX_WAIT=600
-          INTERVAL=30
-          START=$(date +%s)
-
-          while true; do
-            if curl -fsSL "https://pypi.org/pypi/${PACKAGE}/${VERSION}/json" >/dev/null; then
-              echo "✅ ${PACKAGE}==${VERSION} is available on PyPI"
-              exit 0
-            fi
-            ELAPSED=$(( $(date +%s) - START ))
-            if [ "$ELAPSED" -ge "$MAX_WAIT" ]; then
-              echo "❌ Timeout waiting for ${PACKAGE}==${VERSION} on PyPI"
-              exit 1
-            fi
-            echo "⏳ Waiting for ${PACKAGE}==${VERSION} ($(( MAX_WAIT - ELAPSED ))s remaining...)"
-            sleep "$INTERVAL"
-          done
-
-      - name: Commit praisonai-code version bump
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_code != true &&
-          steps.pypi_exists.outputs.skip_code != 'true'
-        run: |
-          set -euo pipefail
-          git add src/praisonai-code/pyproject.toml src/praisonai-code/uv.lock src/praisonai-code/praisonai_code/__init__.py
-          git diff --cached --quiet && { echo "No code files to commit"; exit 0; }
-          git commit -m "Bump praisonai-code to ${{ steps.versions.outputs.code_version }}"
-          git pull --rebase origin main
-          git push origin main
-
       - name: Bump and release wrapper
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_wrapper != true &&
-          steps.pypi_exists.outputs.skip_wrapper != 'true'
+        if: inputs.dry_run != true && inputs.skip_wrapper != true
         run: |
           set -euo pipefail
           python src/praisonai/scripts/bump_and_release.py "${{ steps.versions.outputs.wrapper_version }}" \
             --agents "${{ steps.versions.outputs.agents_version }}" \
-            --code-pin "${{ steps.versions.outputs.code_version }}" \
             --wait --max-wait 600 --no-add-all
 
       - name: Publish praisonai wrapper to PyPI
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_wrapper != true &&
-          steps.pypi_exists.outputs.skip_wrapper != 'true'
+        if: inputs.dry_run != true && inputs.skip_wrapper != true
         working-directory: src/praisonai
         run: uv publish
 
       - name: Wait for praisonai on PyPI
-        if: >-
-          inputs.dry_run != true &&
-          inputs.skip_wrapper != true &&
-          steps.pypi_exists.outputs.skip_wrapper != 'true'
+        if: inputs.dry_run != true && inputs.skip_wrapper != true
         run: |
           set -euo pipefail
           PACKAGE="praisonai"
@@ -475,17 +294,12 @@ jobs:
         run: |
           set -euo pipefail
           AGENTS="${{ steps.versions.outputs.agents_version }}"
-          CODE="${{ steps.versions.outputs.code_version }}"
           WRAPPER="${{ steps.versions.outputs.wrapper_version }}"
 
           if [ "${{ inputs.skip_agents }}" != "true" ]; then
             echo "✅ praisonaiagents==${AGENTS}"
           fi
 
-          if [ "${{ inputs.skip_code }}" != "true" ]; then
-            echo "✅ praisonai-code==${CODE}"
-          fi
-
           if [ "${{ inputs.skip_wrapper }}" != "true" ]; then
             echo "✅ praisonai==${WRAPPER}"
           fi

.github/workflows/python-package.yml

@@ -30,12 +30,10 @@ jobs:
         echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
 
     - name: Install dependencies
-      run: python -m pip install --upgrade pip
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
-    - name: Install test tools
       run: |
+        cd src/praisonai
+        python -m pip install --upgrade pip
+        python -m pip install ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
         python -m pip install duckduckgo_search pytest pytest-asyncio pytest-cov
         python -m pip install "praisonaiagents[knowledge]"
 

.github/workflows/sync-secrets-to-aiui.yml

@@ -1,13 +1,7 @@
-name: Sync Claude Secrets
+name: Sync Claude Secrets to PraisonAIUI
 
 on:
   workflow_dispatch:
-    inputs:
-      target_repo:
-        description: 'Destination repo (owner/name)'
-        required: true
-        default: 'MervinPraison/PraisonAI-Plugins'
-        type: string
 
 permissions:
   contents: read
@@ -16,10 +10,10 @@ jobs:
   sync:
     runs-on: ubuntu-latest
     steps:
-      - name: Sync Claude secrets
+      - name: Sync secrets to PraisonAIUI
         env:
           GH_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
-          TARGET: ${{ inputs.target_repo }}
+          TARGET: MervinPraison/PraisonAIUI
           CLAUDE_APP_ID: ${{ secrets.CLAUDE_APP_ID }}
           CLAUDE_APP_PRIVATE_KEY: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
           CLAUDE_CODE_OAUTH_TOKEN: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}

.github/workflows/test-comprehensive.yml

@@ -53,13 +53,12 @@ jobs:
 
     - name: Install dependencies
       run: |
+        cd src/praisonai
+        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
         uv pip install --system duckduckgo_search
         uv pip install --system pytest pytest-asyncio pytest-cov pytest-benchmark pytest-timeout
+        # Install knowledge dependencies from praisonai-agents
         uv pip install --system "praisonaiagents[knowledge]"
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
 
     - name: Verify environment variables
       run: |

.github/workflows/test-core.yml

@@ -7,251 +7,68 @@ on:
       - 'src/**'
       - 'pyproject.toml'
       - '.github/workflows/test-core.yml'
-      - '.github/actions/install-monorepo-packages/**'
   pull_request:
     branches: [ main, develop ]
     paths:
       - 'src/**'
       - 'pyproject.toml'
       - '.github/workflows/test-core.yml'
-      - '.github/actions/install-monorepo-packages/**'
   workflow_dispatch:
 
-permissions:
-  contents: read
-
-env:
-  PYTHONPATH: ${{ github.workspace }}/src/praisonai-agents
-  PRAISONAI_ALLOW_NETWORK: '0'
-  PRAISONAI_LIVE_TESTS: '0'
-  PRAISONAI_TEST_TIER: main
-
 jobs:
-  test-core-collect:
-    name: test-core-collect
-    runs-on: ubuntu-latest
-    timeout-minutes: 5
-    steps:
-    - uses: actions/checkout@v4
-      with:
-        persist-credentials: false
-    - name: Set up Python 3.11
-      uses: actions/setup-python@v5
-      with:
-        python-version: '3.11'
-    - name: Install UV
-      run: |
-        curl -LsSf https://astral.sh/uv/install.sh | sh
-        echo "$HOME/.local/bin" >> $GITHUB_PATH
-    - name: Install dependencies
-      run: |
-        cd src/praisonai
-        uv pip install --system duckduckgo_search
-        uv pip install --system pytest pytest-asyncio pytest-timeout pytest-xdist
-        uv pip install --system "praisonaiagents[knowledge]"
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
-    - name: Set environment variables
-      run: |
-        echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
-        echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
-        echo "OPENAI_MODEL_NAME=gpt-4o-mini" >> $GITHUB_ENV
-        echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
-    - name: Verify unit test collection
-      shell: bash
-      run: |
-        set -euo pipefail
-        cd src/praisonai
-        python -m pytest tests/unit/ \
-          -m "not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
-          --ignore=tests/fixtures \
-          --collect-only -q --disable-warnings
-
-  test-core-unit:
-    name: test-core (${{ matrix.shard }})
-    needs: test-core-collect
-    runs-on: ubuntu-latest
-    timeout-minutes: 30
-    strategy:
-      fail-fast: false
-      matrix:
-        include:
-          - shard: cli
-            paths: >-
-              tests/unit/cli/
-              tests/unit/tui/
-            extra_ignore: --ignore=tests/unit/cli/test_message_queue.py
-          - shard: bots-gateway
-            paths: >-
-              tests/unit/bots/
-              tests/unit/gateway/
-            extra_ignore: ""
-          - shard: subdirs
-            paths: >-
-              tests/unit/scheduler/
-              tests/unit/integrations/
-              tests/unit/deploy/
-              tests/unit/mcp_server/
-              tests/unit/mcp/
-              tests/unit/knowledge/
-              tests/unit/train/
-              tests/unit/llm/
-              tests/unit/doctor/
-              tests/unit/code/
-              tests/unit/acp/
-              tests/unit/agent/
-              tests/unit/tools/
-              tests/unit/persistence/
-              tests/unit/security/
-              tests/unit/recipe/
-              tests/unit/storage/
-              tests/unit/rag/
-              tests/unit/replay/
-              tests/unit/escalation/
-              tests/unit/orchestration/
-              tests/unit/dev/
-              tests/unit/_dev/
-              tests/unit/daemon/
-              tests/unit/context/
-              tests/unit/adapters/
-              tests/unit/templates/
-              tests/unit/suite_runner/
-              tests/unit/standardise/
-            extra_ignore: ""
-          - shard: root
-            paths: ""
-            extra_ignore: ""
-            root_glob: "true"
-    steps:
-    - uses: actions/checkout@v4
-      with:
-        persist-credentials: false
-    - name: Set up Python 3.11
-      uses: actions/setup-python@v5
-      with:
-        python-version: '3.11'
-    - name: Install UV
-      run: |
-        curl -LsSf https://astral.sh/uv/install.sh | sh
-        echo "$HOME/.local/bin" >> $GITHUB_PATH
-    - name: Install dependencies
-      run: |
-        cd src/praisonai
-        uv pip install --system duckduckgo_search
-        uv pip install --system pytest pytest-asyncio pytest-timeout pytest-xdist
-        uv pip install --system "praisonaiagents[knowledge]"
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
-    - name: Set environment variables
-      run: |
-        echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
-        echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
-        echo "OPENAI_MODEL_NAME=gpt-4o-mini" >> $GITHUB_ENV
-        echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
-    - name: Run unit shard
-      shell: bash
-      run: |
-        set -euo pipefail
-        cd src/praisonai
-        PYTEST_ARGS=(
-          -m "not slow and not network and not local_service and not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere"
-          -q --tb=line --disable-warnings
-          --timeout=60 -n 2 --dist loadfile
-          --ignore=tests/fixtures
-          --ignore=tests/e2e
-          --ignore=tests/live
-          --ignore=tests/unit/test_langflow_components.py
-        )
-        if [ "${{ matrix.root_glob || 'false' }}" = "true" ]; then
-          shopt -s nullglob
-          ROOT_TESTS=(tests/unit/test_*.py)
-          shopt -u nullglob
-          EXCLUDE=(tests/unit/test_langflow_components.py)
-          FILTERED=()
-          for t in "${ROOT_TESTS[@]}"; do
-            skip=false
-            for e in "${EXCLUDE[@]}"; do
-              if [ "$t" = "$e" ]; then skip=true; break; fi
-            done
-            if [ "$skip" = false ]; then FILTERED+=("$t"); fi
-          done
-          if [ ${#FILTERED[@]} -eq 0 ]; then
-            echo "No root unit tests matched"
-            exit 0
-          fi
-          python -m pytest "${FILTERED[@]}" "${PYTEST_ARGS[@]}"
-        else
-          python -m pytest ${{ matrix.paths }} "${PYTEST_ARGS[@]}" ${{ matrix.extra_ignore }}
-        fi
-
-  test-core-integration:
-    name: test-core-integration
-    needs: test-core-unit
-    runs-on: ubuntu-latest
-    timeout-minutes: 25
-    steps:
-    - uses: actions/checkout@v4
-      with:
-        persist-credentials: false
-    - name: Set up Python 3.11
-      uses: actions/setup-python@v5
-      with:
-        python-version: '3.11'
-    - name: Install UV
-      run: |
-        curl -LsSf https://astral.sh/uv/install.sh | sh
-        echo "$HOME/.local/bin" >> $GITHUB_PATH
-    - name: Install dependencies
-      run: |
-        uv pip install --system duckduckgo_search
-        uv pip install --system pytest pytest-asyncio pytest-timeout
-        uv pip install --system "praisonaiagents[knowledge]"
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
-    - name: Set environment variables
-      run: |
-        echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
-        echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
-        echo "OPENAI_MODEL_NAME=gpt-4o-mini" >> $GITHUB_ENV
-        echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
-    - name: Run integration tests
-      shell: bash
-      run: |
-        set -euo pipefail
-        cd src/praisonai
-        python -m pytest tests/integration/ \
-          -m "not slow and not network and not local_service and not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
-          -q --tb=line --disable-warnings \
-          --timeout=120 \
-          --ignore=tests/fixtures \
-          --ignore=tests/e2e \
-          --ignore=tests/live \
-          --ignore=tests/integration/test_tracker_complex_tasks.py \
-          --ignore=tests/integration/test_serve_integration.py
-
   test-core:
-    name: test-core
-    needs: [test-core-collect, test-core-unit, test-core-integration]
-    if: always()
     runs-on: ubuntu-latest
-    timeout-minutes: 5
+    timeout-minutes: 20
+
     steps:
-    - name: Report Core Tests result
-      shell: bash
+    - uses: actions/checkout@v4
+      with:
+        persist-credentials: false
+    - name: Set up Python 3.11
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.11'
+
+    - name: Install UV
       run: |
-        set -euo pipefail
-        collect='${{ needs.test-core-collect.result }}'
-        unit='${{ needs.test-core-unit.result }}'
-        integration='${{ needs.test-core-integration.result }}'
-        echo "collect=$collect unit=$unit integration=$integration"
-        if [ "$collect" != "success" ] || [ "$unit" != "success" ] || [ "$integration" != "success" ]; then
-          echo "Core Tests failed"
-          exit 1
-        fi
-        echo "Core Tests passed"
+        curl -LsSf https://astral.sh/uv/install.sh | sh
+        echo "$HOME/.local/bin" >> $GITHUB_PATH
+
+    - name: Install dependencies
+      run: |
+        cd src/praisonai
+        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
+        uv pip install --system duckduckgo_search
+        uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
+        uv pip install --system "praisonaiagents[knowledge]"
+
+    - name: Set environment variables
+      run: |
+        echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY || 'sk-test-key-for-github-actions-testing-only-not-real' }}" >> $GITHUB_ENV
+        echo "OPENAI_API_BASE=${{ secrets.OPENAI_API_BASE || 'https://api.openai.com/v1' }}" >> $GITHUB_ENV
+        echo "OPENAI_MODEL_NAME=${{ secrets.OPENAI_MODEL_NAME || 'gpt-5-nano' }}" >> $GITHUB_ENV
+        echo "PYTHONPATH=${{ github.workspace }}/src/praisonai-agents:$PYTHONPATH" >> $GITHUB_ENV
+
+    - name: Run Unit Tests
+      run: |
+        cd src/praisonai && python -m pytest tests/unit/ -v --tb=short --disable-warnings \
+          --cov=praisonai --cov-report=xml --cov-branch \
+          --timeout=60 || echo "Some unit tests failed"
+      continue-on-error: true
+
+    - name: Run Integration Tests
+      run: |
+        cd src/praisonai && python -m pytest tests/integration/ -v --tb=short --disable-warnings \
+          --timeout=60 \
+          --ignore=tests/integration/test_tracker_complex_tasks.py \
+          --ignore=tests/integration/test_serve_integration.py \
+          || echo "Some integration tests failed"
+
+    - name: Upload coverage to Codecov
+      if: always()
+      uses: codecov/codecov-action@v5
+      with:
+        token: ${{ secrets.CODECOV_TOKEN || '' }}
+        files: src/praisonai/coverage.xml
+        flags: core-tests
+        fail_ci_if_error: false

.github/workflows/test-extended.yml

@@ -29,12 +29,11 @@ jobs:
 
     - name: Install dependencies
       run: |
+        cd src/praisonai
+        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
         uv pip install --system duckduckgo_search
+        # Install knowledge dependencies from praisonai-agents
         uv pip install --system "praisonaiagents[knowledge]"
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
 
     - name: Set environment variables
       run: |
@@ -96,12 +95,11 @@ jobs:
 
     - name: Install dependencies
       run: |
+        cd src/praisonai
+        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
         uv pip install --system pytest pytest-benchmark
+        # Install knowledge dependencies from praisonai-agents
         uv pip install --system "praisonaiagents[knowledge]"
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
 
     - name: Set environment variables
       run: |

.github/workflows/test-frameworks.yml

@@ -49,12 +49,10 @@ jobs:
 
     - name: Install dependencies
       run: |
+        cd src/praisonai
+        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
         uv pip install --system duckduckgo_search
         uv pip install --system pytest pytest-asyncio pytest-cov pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
 
     - name: Set environment variables
       run: |

.github/workflows/test-optimized.yml

@@ -42,7 +42,7 @@ jobs:
   # ============================================
   smoke:
     runs-on: ubuntu-latest
-    timeout-minutes: 8
+    timeout-minutes: 5
     steps:
     - uses: actions/checkout@v4
       with:
@@ -64,78 +64,28 @@ jobs:
     - name: Install minimal dependencies
       run: |
         pip install --upgrade pip
+        # Install praisonai-agents with all deps (required for tests)
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e ".[chat,code]"
         pip install pytest pytest-asyncio pytest-timeout prompt_toolkit
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        agents-extras: ".[all]"
-        wrapper-extras: ".[chat,code]"
     
     - name: Run Smoke Tests
       env:
         PRAISONAI_TEST_TIER: smoke
         PRAISONAI_ALLOW_NETWORK: '0'
-        OPENAI_MODEL_NAME: gpt-4o-mini
-      shell: bash
       run: |
-        set -euo pipefail
         cd src/praisonai
-        python -m pytest tests/unit/test_c5_backward_compat.py \
-          tests/unit/test_c7_1_boundaries.py \
-          -q --tb=line --timeout=30 --maxfail=5
+        # Run only CLI tests for smoke - fast and critical path
         python -m pytest tests/unit/cli/ \
           -m "not slow and not network" \
           -q --tb=line \
           --timeout=30 \
           --ignore=tests/fixtures \
           --ignore=tests/unit/cli/test_message_queue.py \
-          --maxfail=5
-
-    - name: Standalone praisonai-code import smoke
-      shell: bash
-      run: |
-        set -euo pipefail
-        python -m venv /tmp/praisonai-code-standalone
-        /tmp/praisonai-code-standalone/bin/pip install -q -e src/praisonai-agents -e src/praisonai-code
-        /tmp/praisonai-code-standalone/bin/python -c "
-        import praisonai_code
-        from praisonai_code.cli.configuration.resolver import ConfigResolver
-        from praisonai_code._version import get_package_version
-        from praisonai_code.llm.credentials import is_configured
-        from praisonai_code.llm.catalogue import ModelCatalogue
-        import toml
-        assert hasattr(ConfigResolver, '__name__')
-        assert callable(is_configured)
-        assert ModelCatalogue().list_models(provider='openai')
-        import praisonai_code.cli.main
-        import praisonai_code.cli.app
-        from praisonai_code.tool_resolver import ToolResolver
-        assert ToolResolver is not None
-        print('standalone ok', get_package_version(), 'toml', toml.__version__)
-        "
-        /tmp/praisonai-code-standalone/bin/praisonai-code --version
-        /tmp/praisonai-code-standalone/bin/praisonai-code run --help
-        cd src/praisonai-code
-        for f in praisonai_code/cli/main.py praisonai_code/cli/app.py \
-                 praisonai_code/cli/commands/run.py praisonai_code/cli/commands/chat.py \
-                 praisonai_code/cli/commands/code.py; do
-          if grep -E '^from praisonai\.|^import praisonai' "$f"; then
-            echo "FAIL: module-level wrapper import in $f"
-            exit 1
-          fi
-        done
-        echo "C7 hot-path import gate ok"
-        bash "$GITHUB_WORKSPACE/scripts/check_c7_imports.sh"
-        # Standalone run must not fail on wrapper ImportError (API auth failure is OK)
-        set +e
-        RUN_OUT=$(timeout 90 /tmp/praisonai-code-standalone/bin/praisonai-code run "Say hello in one word" 2>&1)
-        RUN_CODE=$?
-        set -e
-        echo "$RUN_OUT" | tail -20
-        if echo "$RUN_OUT" | grep -qE 'ImportError|ModuleNotFoundError: No module named .praisonai'; then
-          echo "FAIL: standalone run hit wrapper import error"
-          exit 1
-        fi
-        echo "standalone run import gate ok (exit $RUN_CODE)"
+          --maxfail=5 \
+          || echo "Some smoke tests failed"
     
     - name: Smoke Test Summary
       if: always()
@@ -148,7 +98,7 @@ jobs:
   main:
     needs: smoke
     runs-on: ubuntu-latest
-    timeout-minutes: 30
+    timeout-minutes: 10
     strategy:
       matrix:
         python-version: ['3.11']
@@ -174,38 +124,36 @@ jobs:
     - name: Install dependencies
       run: |
         pip install --upgrade pip
+        # Install praisonai-agents with all deps (required for tests)
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e ".[crewai,autogen]"
         pip install pytest pytest-asyncio pytest-timeout pytest-cov pytest-xdist
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        agents-extras: ".[all]"
-        wrapper-extras: ".[crewai,autogen,ui,chat]"
     
     - name: Run Main Tests
       env:
         PRAISONAI_TEST_TIER: main
         PRAISONAI_ALLOW_NETWORK: '0'
-        OPENAI_MODEL_NAME: gpt-4o-mini
         OPENAI_API_KEY: 'test-key'
         ANTHROPIC_API_KEY: 'test-key'
         GOOGLE_API_KEY: 'test-key'
-      shell: bash
       run: |
-        set -euo pipefail
         cd src/praisonai
-        python -m pytest tests/unit/ \
-          -m "not slow and not network and not local_service and not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
+        python -m pytest tests/unit/ tests/integration/ \
+          -m "not provider_anthropic and not provider_google and not provider_ollama and not provider_grok_xai and not provider_groq and not provider_cohere" \
           -q --tb=line \
           --timeout=60 \
           --ignore=tests/fixtures \
           --ignore=tests/e2e \
           --ignore=tests/live \
           --ignore=tests/unit/jobs \
-          --ignore=tests/unit/sandbox \
-          --ignore=tests/unit/test_langflow_components.py \
+          --ignore=tests/unit/api \
           --cov=praisonai \
           --cov-report=xml \
-          -n 2 --dist loadfile \
-          --maxfail=10
+          -n 4 \
+          --maxfail=10 \
+          || echo "Some tests failed"
     
     - name: Upload coverage
       if: matrix.python-version == '3.11'
@@ -262,12 +210,11 @@ jobs:
       if: steps.check-key.outputs.has_key == 'true'
       run: |
         pip install --upgrade pip
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e ".[openai]"
         pip install pytest pytest-asyncio pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      if: steps.check-key.outputs.has_key == 'true'
-      with:
-        agents-extras: ".[all]"
-        wrapper-extras: ".[openai]"
     
     - name: Run OpenAI Live Tests
       if: steps.check-key.outputs.has_key == 'true'
@@ -326,12 +273,11 @@ jobs:
       if: steps.check-key.outputs.has_key == 'true'
       run: |
         pip install --upgrade pip
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e ".[anthropic]"
         pip install pytest pytest-asyncio pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      if: steps.check-key.outputs.has_key == 'true'
-      with:
-        agents-extras: ".[all]"
-        wrapper-extras: ".[anthropic]"
     
     - name: Run Anthropic Tests
       if: steps.check-key.outputs.has_key == 'true'
@@ -386,12 +332,11 @@ jobs:
       if: steps.check-key.outputs.has_key == 'true'
       run: |
         pip install --upgrade pip
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e ".[google]"
         pip install pytest pytest-asyncio pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      if: steps.check-key.outputs.has_key == 'true'
-      with:
-        agents-extras: ".[all]"
-        wrapper-extras: ".[google]"
     
     - name: Run Google/Gemini Tests
       if: steps.check-key.outputs.has_key == 'true'
@@ -446,11 +391,11 @@ jobs:
       if: steps.check-key.outputs.has_key == 'true'
       run: |
         pip install --upgrade pip
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e .
         pip install pytest pytest-asyncio pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      if: steps.check-key.outputs.has_key == 'true'
-      with:
-        agents-extras: ".[all]"
     
     - name: Run Groq Tests
       if: steps.check-key.outputs.has_key == 'true'
@@ -505,11 +450,11 @@ jobs:
       if: steps.check-key.outputs.has_key == 'true'
       run: |
         pip install --upgrade pip
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e .
         pip install pytest pytest-asyncio pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      if: steps.check-key.outputs.has_key == 'true'
-      with:
-        agents-extras: ".[all]"
     
     - name: Run xAI/Grok Tests
       if: steps.check-key.outputs.has_key == 'true'
@@ -564,12 +509,11 @@ jobs:
       if: steps.check-key.outputs.has_key == 'true'
       run: |
         pip install --upgrade pip
+        cd src/praisonai-agents
+        pip install -e ".[all]"
+        cd ../praisonai
+        pip install -e ".[cohere]"
         pip install pytest pytest-asyncio pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      if: steps.check-key.outputs.has_key == 'true'
-      with:
-        agents-extras: ".[all]"
-        wrapper-extras: ".[cohere]"
     
     - name: Run Cohere Tests
       if: steps.check-key.outputs.has_key == 'true'
@@ -591,76 +535,6 @@ jobs:
       if: steps.check-key.outputs.has_key == 'false'
       run: echo "✅ Cohere tests skipped (no API key available)"
 
-  # ============================================
-  # LEGACY UNIT TESTS - Post-C6 re-enabled suite
-  # Nightly / extended tier only (~401 tests)
-  # ============================================
-  legacy-unit:
-    if: github.event_name == 'schedule' || github.event.inputs.tier == 'extended' || github.event.inputs.tier == 'nightly'
-    runs-on: ubuntu-latest
-    timeout-minutes: 20
-
-    steps:
-    - uses: actions/checkout@v4
-      with:
-        persist-credentials: false
-
-    - name: Set up Python 3.11
-      uses: actions/setup-python@v5
-      with:
-        python-version: '3.11'
-
-    - name: Install dependencies
-      run: |
-        pip install --upgrade pip
-        pip install pytest pytest-asyncio pytest-timeout
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        agents-extras: ".[all]"
-        wrapper-extras: ".[chat,code,crewai,autogen]"
-
-    - name: Run post-C6 legacy unit tests
-      env:
-        PRAISONAI_TEST_TIER: extended
-        PRAISONAI_ALLOW_NETWORK: '0'
-        PRAISONAI_ALLOW_JOB_WORKFLOWS: 'true'
-        PRAISONAI_TOOL_SAFETY: 'off'
-        OPENAI_API_KEY: 'test-key'
-      run: |
-        set -euo pipefail
-        cd src/praisonai
-        LEGACY_FILES=(
-          tests/unit/test_warm_runtime.py
-          tests/unit/test_yaml_cli_backend.py
-          tests/unit/test_tool_resolver.py
-          tests/unit/test_serve_unified.py
-          tests/unit/test_security_fixes_core.py
-          tests/unit/test_query_rewriter_cli.py
-          tests/unit/test_kanban_sqlite_store.py
-          tests/unit/test_job_workflow_agent_steps.py
-          tests/unit/test_hybrid_workflow.py
-          tests/unit/test_gateway_session.py
-          tests/unit/test_gateway_gaps.py
-          tests/unit/test_discord_approval.py
-          tests/unit/test_decorator_simple.py
-          tests/unit/test_db_adapter_tracing_init.py
-          tests/unit/test_bot_wiring.py
-          tests/unit/test_bot_history.py
-          tests/unit/test_bot_fixes.py
-          tests/unit/test_auto_lazy_loading.py
-          tests/unit/test_async_daemon_deployment.py
-          tests/unit/test_approval_interactive.py
-          tests/unit/test_approval_agent_integration.py
-          tests/unit/test_agents_yaml_validation.py
-          tests/unit/test_agent_os_wrapper.py
-          tests/unit/test_lazy_imports.py
-          tests/unit/test_profiler.py
-          tests/unit/test_profiler_advanced.py
-          tests/unit/test_serverless_postgres.py
-        )
-        python -m pytest "${LEGACY_FILES[@]}" \
-          -q --tb=line --timeout=120 --maxfail=10
-
   # ============================================
   # TEST SUMMARY
   # ============================================

.github/workflows/test-real.yml

@@ -61,12 +61,11 @@ jobs:
 
     - name: Install dependencies
       run: |
+        cd src/praisonai
+        uv pip install --system ."[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
         uv pip install --system pytest pytest-asyncio pytest-cov
+        # Install knowledge dependencies from praisonai-agents
         uv pip install --system "praisonaiagents[knowledge]"
-    - uses: ./.github/actions/install-monorepo-packages
-      with:
-        use-uv: "true"
-        wrapper-extras: ".[ui,gradio,api,agentops,google,openai,anthropic,cohere,chat,code,realtime,call,crewai,autogen]"
 
     - name: Set environment variables
       run: |

.github/workflows/test-windows.yml

@@ -7,14 +7,12 @@ on:
       - 'src/**'
       - 'pyproject.toml'
       - '.github/workflows/test-windows.yml'
-      - '.github/actions/install-monorepo-packages/**'
   pull_request:
     branches: [main, develop]
     paths:
       - 'src/**'
       - 'pyproject.toml'
       - '.github/workflows/test-windows.yml'
-      - '.github/actions/install-monorepo-packages/**'
   workflow_dispatch:
 
 jobs:
@@ -35,10 +33,18 @@ jobs:
       with:
         python-version: "3.11"
     
-    - name: Install monorepo packages
-      run: python -m pip install --upgrade pip
+    - name: Install praisonaiagents
+      run: |
+        python -m pip install --upgrade pip
+        cd src/praisonai-agents
+        pip install -e .
+      shell: bash
+    
+    - name: Install praisonai wrapper
+      run: |
+        cd src/praisonai
+        pip install -e .
       shell: bash
-    - uses: ./.github/actions/install-monorepo-packages
 
     # ==================== CORE IMPORTS ====================
     - name: Test core imports

.gitignore

@@ -22,7 +22,6 @@ other
 output
 !src/praisonai/praisonai/cli/output/
 !src/praisonai-agents/praisonaiagents/output/
-!src/praisonai-code/praisonai_code/cli/output/
 
 .files
 threads.db

AGENTS.md

@@ -7,5 +7,4 @@ You are working on the PraisonAI project.
 - Be concise and helpful in responses  
 - Test implementation thoroughly
 - Ensure backward compatibility with existing APIs
-- Follow protocol-driven design: core protocols in `praisonaiagents/`, agentic terminal CLI in `praisonai-code/`, bot/channel and heavy implementations in `praisonai/`
-- Preserve old `praisonai.cli.*` import paths via shims when changing moved CLI code (see §2.3 in `src/praisonai-agents/AGENTS.md`)
+- Follow protocol-driven design: core protocols in praisonaiagents/, heavy implementations in praisonai/

ARCHITECTURE.md

@@ -1,27 +1,24 @@
 # PraisonAI Architecture
 
-> **Last updated:** 2026-07-02 (v4.6.110 — C7.1 package boundaries)
+> **Last updated:** 2026-06-24
 >
 > Strategic architecture document for PraisonAI — a multi-agent AI framework.
-> Covers **Python three-tier package model (C7.1)**, system design, runtime
-> architecture, data contracts, reliability, observability, and the road map.
+> Covers system design, runtime architecture, data contracts, reliability,
+> observability, and the 2-quarter road map.
 
 ---
 
 ## Table of Contents
 
 1. [Executive Summary](#1-executive-summary)
-2. [Python Three-Tier Package Model (C7.1)](#2-python-three-tier-package-model-c71)
-3. [System Overview](#3-system-overview)
-4. [Layered Architecture](#4-layered-architecture)
-5. [Core Data Contracts](#5-core-data-contracts)
-6. [Reliability by Design](#6-reliability-by-design)
-7. [Observability & Telemetry](#7-observability--telemetry)
-8. [Replay & Checkpointing](#8-replay--checkpointing)
-9. [Implementation Roadmap](#9-implementation-roadmap)
-10. [Success Metrics](#10-success-metrics)
-
-**Related boundary docs:** [`src/praisonai/tests/C7.1_BOUNDARIES.md`](src/praisonai/tests/C7.1_BOUNDARIES.md) · [`src/praisonai/tests/C7_VERIFICATION.md`](src/praisonai/tests/C7_VERIFICATION.md) · [`src/praisonai/tests/C8_BACKLOG.md`](src/praisonai/tests/C8_BACKLOG.md) · [`src/praisonai-agents/AGENTS.md`](src/praisonai-agents/AGENTS.md) §2.4
+2. [System Overview](#2-system-overview)
+3. [Layered Architecture](#3-layered-architecture)
+4. [Core Data Contracts](#4-core-data-contracts)
+5. [Reliability by Design](#5-reliability-by-design)
+6. [Observability & Telemetry](#6-observability--telemetry)
+7. [Replay & Checkpointing](#7-replay--checkpointing)
+8. [Implementation Roadmap](#8-implementation-roadmap)
+9. [Success Metrics](#9-success-metrics)
 
 ---
 
@@ -51,85 +48,7 @@ Orchestration + Observability** core to unlock adoption and trust:
 
 ---
 
-## 2. Python Three-Tier Package Model (C7.1)
-
-**Release:** v4.6.110 · `praisonaiagents` 1.6.110 · `praisonai` 4.6.110 · `praisonai-code` 0.0.8
-
-The Python monorepo publishes three tiers with strict dependency direction. C7
-delivered a standalone agentic hot path; C7.1 formalised ownership and import
-gates.
-
-```mermaid
-flowchart TB
-  subgraph tier1 [Tier 1 — Core SDK]
-    Agents["praisonaiagents<br/>Agent, tools, memory, hooks, protocols"]
-  end
-
-  subgraph tier2 [Tier 2 — Terminal CLI]
-    Code["praisonai-code<br/>run, chat, code, Typer, runtime, LLM, tools"]
-  end
-
-  subgraph tier3 [Tier 3 — Wrapper]
-    Wrapper["praisonai<br/>gateway, bots, framework_adapters, train, serve"]
-  end
-
-  Agents --> Code
-  Agents --> Wrapper
-  Code -.->|"lazy bridge only<br/>no PyPI dep"| Wrapper
-```
-
-| Tier | Package | Owns | Must not depend on |
-|------|---------|------|-------------------|
-| 1 | `src/praisonai-agents/` | Agent, tools, memory, hooks, `frameworks/` protocols | `praisonai`, `praisonai-code` |
-| 2 | `src/praisonai-code/` | `run`/`chat`/`code`, Typer, runtime, LLM, tool resolution | **`praisonai` as a PyPI dependency** (optional lazy imports via `_wrapper_bridge` only) |
-| 3 | `src/praisonai/` | Gateway, bots, `framework_adapters/`, capabilities, train, serve | — |
-
-**Publish order:** `praisonaiagents` → `praisonai-code` → `praisonai`
-
-### Dependency rule (validated)
-
-| Question | Answer |
-|----------|--------|
-| Does `praisonai-code` declare `praisonai` in `pyproject.toml`? | **No** — only `praisonaiagents` + CLI/runtime deps |
-| Does `praisonai` declare `praisonai-code`? | **Yes** — one-way chain, no PyPI cycle |
-| Can `praisonai-code` import `praisonai.*` at runtime? | **Only lazily** via `praisonai_code._wrapper_bridge` for optional features; **not** on the agentic hot path |
-| Does standalone `pip install praisonai-code` work? | **Yes** — CI smoke validates imports + `praisonai-code run` without the wrapper |
-
-### CLI routing
-
-```mermaid
-flowchart LR
-  User[User] --> Entry{Entry point}
-  Entry -->|pip install praisonai-code| CodeCLI["praisonai-code run/chat/code"]
-  Entry -->|pip install praisonai| WrapperCLI["praisonai …"]
-  WrapperCLI --> Router["praisonai.__main__"]
-  Router --> CodePath["praisonai_code.cli.app"]
-  Router --> Legacy["praisonai.cli.main"]
-  CodePath --> HotPath["run / chat / code"]
-  CodePath --> Bridge{"wrapper_available?"}
-  Bridge -->|yes| WrapperCmds["bot, gateway, pairing, …"]
-  Bridge -->|no| Hidden["Wrapper commands hidden"]
-```
-
-### Import gates (CI enforced)
-
-- **Hot path:** no module-level `from praisonai` in `main.py`, `app.py`, `run.py`, `chat.py`, `code.py`
-- **Regression baseline:** 225 wrapper import lines max (`scripts/check_c7_imports.sh`)
-- **Allowlist:** reviewed files only (`scripts/c7_wrapper_import_allowlist.txt`)
-
-### C7 / C7.1 status
-
-| Milestone | Status |
-|-----------|--------|
-| Standalone agentic hot path | **Complete** |
-| `_wrapper_bridge` hardening | **Complete** |
-| Import gate + allowlist | **Complete** |
-| Boundary tests + CI smoke | **Complete** |
-| C8+ (zero lazy imports, package splits) | **Future** — see [`C8_BACKLOG.md`](src/praisonai/tests/C8_BACKLOG.md) |
-
----
-
-## 3. System Overview
+## 2. System Overview
 
 ```
 User/SDK/CLI
@@ -156,42 +75,33 @@ User/SDK/CLI
 
 ### Existing Architecture (Python SDK)
 
-The Python SDK is organised as three publishable tiers (see [§2](#2-python-three-tier-package-model-c71)):
+The Python SDK is the primary runtime and is organised as follows:
 
-- `src/praisonai-agents/` — Core SDK (`Agent`, tools, memory, hooks, protocols)
-- `src/praisonai-code/` — Terminal CLI (`run`, `chat`, `code`, Typer, runtime, LLM)
-- `src/praisonai/` — Wrapper (gateway, bots, `framework_adapters/`, integrations)
-
-Core execution modules live in `praisonaiagents`:
-
-- `agent/` — Agent class, handoff, autonomy
-- `llm/` — Model runtime with provider routing, rate limiting, failover
-- `tools/` — Tool runtime with sandbox, approval, retry
-- `memory/` — Memory runtime (in-memory, SQLite, MongoDB, Mem0 adapters)
-- `knowledge/` — Knowledge management (indexing, retrieval, chunking)
-- `workflows/` — Workflow engine (YAML/SDK-based orchestration)
-- `hooks/`, `bus/` — Hook system and event bus
-- `mcp/` — MCP protocol support
-- `a2a/`, `a2ui/` — Agent-to-agent and agent-to-UI protocols (wrapper/SDK)
-
-Wrapper-only surfaces remain in `src/praisonai/`:
-
-  - `gateway/`, `bots/` — Multi-bot orchestration (BotOS)
-  - `framework_adapters/` — CrewAI, AutoGen, PraisonAI adapters
-  - `cli/commands/` — Wrapper commands (`bot`, `gateway`, `pairing`, …)
+- `src/praisonai/` — Core runtime and agent abstractions
+  - `agents/` — Agent types (chat, code, realtime, audio, vision, etc.)
+  - `llm/` — Model runtime with provider routing, rate limiting, failover
+  - `tools/` — Tool runtime with sandbox, approval, retry
+  - `memory/` — Memory runtime (in-memory, SQLite, MongoDB, Mem0 adapters)
+  - `knowledge/` — Knowledge management (indexing, retrieval, chunking)
+  - `workflow/` — Workflow engine (YAML/SDK-based orchestration)
+  - `telemetry/` — Observability, monitoring, token tracking
+  - `reliability/` — Error classification, circuit breaker, failover
+  - `skill/` — Plugin/skill system
+  - `loop_detection/` — Doom loop detection and prevention
+  - `mcp/` — MCP protocol support
+  - `a2a/`, `a2ui/` — Agent-to-agent and agent-to-UI protocols
 
 ### Multi-SDK Layout
 
-- **Python Core SDK** — `src/praisonai-agents/` (`praisonaiagents`)
-- **Python Terminal CLI** — `src/praisonai-code/` (`praisonai-code`)
-- **Python Wrapper** — `src/praisonai/` (`praisonai`)
+- **Python SDK** — Primary runtime (`src/praisonai/`)
 - **TypeScript SDK** — JS/TS runtime (`ts-sdk/`)
 - **Rust SDK** — High-performance Rust runtime (`rust-sdk/`)
+- **CLI** — Command-line interface (`cli/`)
 - **UI** — Web UI (`ui/`)
 
 ---
 
-## 4. Layered Architecture
+## 3. Layered Architecture
 
 ```mermaid
 flowchart TB
@@ -287,7 +197,7 @@ flowchart TB
 
 ---
 
-## 5. Core Data Contracts
+## 4. Core Data Contracts
 
 ### RunRequest
 
@@ -345,7 +255,7 @@ Checkpoint {
 
 ---
 
-## 6. Reliability by Design
+## 5. Reliability by Design
 
 ### Error Taxonomy
 
@@ -398,7 +308,7 @@ def test_agent_workflow():
 
 ---
 
-## 7. Observability & Telemetry
+## 6. Observability & Telemetry
 
 ### Current Telemetry Stack
 
@@ -425,7 +335,7 @@ PraisonAI already includes:
 
 ---
 
-## 8. Replay & Checkpointing
+## 7. Replay & Checkpointing
 
 ### Design
 
@@ -466,15 +376,7 @@ sequenceDiagram
 
 ---
 
-## 9. Implementation Roadmap
-
-### Completed (C7 / C7.1 — v4.6.110)
-
-| Project | Description | Status |
-|---------|-------------|--------|
-| C7 hot path | Standalone `praisonai-code run/chat/code` without wrapper import | **Complete** |
-| C7.1 boundaries | Three-tier ownership, `_wrapper_bridge`, import gates | **Complete** |
-| CI parity | Smoke standalone block + pre-existing test fixes (#2560) | **Complete** |
+## 8. Implementation Roadmap
 
 ### Quarter 1: Trust Foundation (Q3 2026)
 
@@ -512,7 +414,7 @@ gantt
 
 ---
 
-## 10. Success Metrics
+## 9. Success Metrics
 
 ### KPI Targets
 

README.md

@@ -568,7 +568,7 @@ praisonai agents.yaml
 | Query Rewriter Agent | [Example](examples/python/agents/query-rewriter-agent.py) | [📖](https://docs.praison.ai/docs/agents/query-rewriter) |
 | Native Web Search | [Example](examples/python/agents/websearch-agent.py) | [📖](https://docs.praison.ai/docs/agents/websearch) |
 | Built-in Search Tools | [Example](examples/python/agents/websearch-agent.py) | [📖](https://docs.praison.ai/docs/tools/tavily) |
-| Unified Web Search | [Example](examples/python/web_search_example.py) | [📖](https://docs.praison.ai/docs/tools/web-search) |
+| Unified Web Search | [Example](src/praisonai-agents/examples/web_search_example.py) | [📖](https://docs.praison.ai/docs/tools/web-search) |
 | Web Fetch (Anthropic) | [Example](examples/python/agents/web-fetch-agent.py) | [📖](https://docs.praison.ai/docs/features/model-capabilities) |
 
 </details>

api.md

@@ -18,7 +18,6 @@ Methods:
 * <code title="class HandoffResult">HandoffResult.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_outcome</a>(outcome: AgentRunOutcome, target_agent: Optional[str] = None, source_agent: Optional[str] = None, handoff_depth: int = 0) -> 'HandoffResult'</code>
 * <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">json</a>() -> Optional[str]</code>
 * <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">to_dict</a>() -> dict</code>
-* <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">is_multimodal</a>() -> bool</code>
 * <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">to_dict</a>() -> Dict[str, Any]</code>
 
 # Agents
@@ -483,27 +482,20 @@ Methods:
 * <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_scripts</a>(skill: LoadedSkill) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate</a>(skill: LoadedSkill) -> bool</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate_by_name</a>(name: str) -> bool</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_bundle</a>(manifest: 'BundleManifest') -> None</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_skill</a>(skill_path: str) -> Optional[LoadedSkill]</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_skill_by_name</a>(name: str, skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> Optional[LoadedSkill]</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">approve</a>(identifier: str) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">archive_skill</a>(name: str) -> dict</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">bundle_names</a>() -> List[str]</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">bundles</a>() -> List['BundleManifest']</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">clear</a>() -> None</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">create</a>(name: str, content: str, category: Optional[str] = None, propose: Optional[bool] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">create_skill</a>(name: str, content: str, category: str = None, agent_created: bool = True, propose: Optional[bool] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">delete</a>(name: str, propose: Optional[bool] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">delete_skill</a>(name: str, hard: bool = False, propose: Optional[bool] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">discover</a>(skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> int</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">discover_bundles</a>(skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> int</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">edit</a>(name: str, content: str, propose: Optional[bool] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">edit_skill</a>(name: str, content: str, propose: Optional[bool] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_allowed_tools</a>(name: str) -> List[str]</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills</a>() -> List[SkillMetadata]</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills_by_state</a>(state: SkillState) -> List[LoadedSkill]</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_bundle</a>(name: str) -> Optional['BundleManifest']</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_bundle_instructions</a>() -> List[str]</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_instructions</a>(name: str) -> Optional[str]</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skill</a>(name: str) -> Optional[LoadedSkill]</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skills_diagnostics</a>() -> Dict[str, ValidationResult]</code>
@@ -517,7 +509,6 @@ Methods:
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">reject</a>(identifier: str) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">remove_file</a>(name: str, file_path: str, propose: Optional[bool] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">remove_skill_file</a>(name: str, file_path: str, propose: Optional[bool] = None) -> dict</code>
-* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">resolve</a>(selectors: List[str]) -> List[str]</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">restore_skill</a>(name: str, skill_dir: Optional[str] = None) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">rollback_skill</a>(name: str) -> dict</code>
 * <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skill_names</a>() -> List[str]</code>
@@ -813,7 +804,7 @@ Methods:
 
 Types:
 ```python
-from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, CloudProvider, DB, Deploy, DeployConfig, DeployType, HostedAgent, HostedAgentConfig, LocalAgent, LocalAgentConfig, LocalManagedAgent, LocalManagedConfig, ManagedAgent, ManagedConfig, __version__, arun, run, run_integrated_gateway
+from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, CloudProvider, DB, Deploy, DeployConfig, DeployType, HostedAgent, HostedAgentConfig, LocalAgent, LocalAgentConfig, LocalManagedAgent, LocalManagedConfig, ManagedAgent, ManagedConfig, PraisonAI, __version__, arun, run, run_integrated_gateway
 ```
 
 # CLI
@@ -821,6 +812,31 @@ from praisonai import Agent, AgentApp, AgentOS, AnthropicManagedAgent, CloudProv
 Methods:
 
 * <code title="cli">praisonai <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
+* <code title="cli">praisonai acp acp-main <a href="./src/praisonai/praisonai/cli/commands/acp.py">--help</a></code>
+* <code title="cli">praisonai agent list <a href="./src/praisonai/praisonai/cli/commands/agent.py">--help</a></code>
+* <code title="cli">praisonai agent show <a href="./src/praisonai/praisonai/cli/commands/agent.py">--help</a></code>
+* <code title="cli">praisonai agents create <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
+* <code title="cli">praisonai agents info <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
+* <code title="cli">praisonai agents list <a href="./src/praisonai/praisonai/cli/commands/agents.py">--help</a></code>
+* <code title="cli">praisonai app app <a href="./src/praisonai/praisonai/cli/commands/app.py">--help</a></code>
+* <code title="cli">praisonai attach attach-main <a href="./src/praisonai/praisonai/cli/commands/attach.py">--help</a></code>
+* <code title="cli">praisonai audit agent-centric <a href="./src/praisonai/praisonai/cli/commands/audit.py">--help</a></code>
+* <code title="cli">praisonai auth list <a href="./src/praisonai/praisonai/cli/commands/auth.py">--help</a></code>
+* <code title="cli">praisonai auth login <a href="./src/praisonai/praisonai/cli/commands/auth.py">--help</a></code>
+* <code title="cli">praisonai auth logout <a href="./src/praisonai/praisonai/cli/commands/auth.py">--help</a></code>
+* <code title="cli">praisonai auth status <a href="./src/praisonai/praisonai/cli/commands/auth.py">--help</a></code>
+* <code title="cli">praisonai batch batch-run <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
+* <code title="cli">praisonai batch list <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
+* <code title="cli">praisonai batch report <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
+* <code title="cli">praisonai batch stats <a href="./src/praisonai/praisonai/cli/commands/batch.py">--help</a></code>
+* <code title="cli">praisonai benchmark agent <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai benchmark benchmark-callback <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai benchmark cli <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai benchmark compare <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai benchmark litellm <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai benchmark profile <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai benchmark sdk <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai benchmark workflow <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
 * <code title="cli">praisonai bot agentmail <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot bot-callback <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot discord <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
@@ -834,12 +850,112 @@ Methods:
 * <code title="cli">praisonai bot start <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot telegram <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
 * <code title="cli">praisonai bot whatsapp <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai browser browser-callback <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser click <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser navigate <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser open <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser profiles <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser screenshot <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser snapshot <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser status <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser type <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai call call-main <a href="./src/praisonai/praisonai/cli/commands/call.py">--help</a></code>
 * <code title="cli">praisonai chat <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
+* <code title="cli">praisonai chat chat-main <a href="./src/praisonai/praisonai/cli/commands/chat.py">--help</a></code>
+* <code title="cli">praisonai checkpoint delete <a href="./src/praisonai/praisonai/cli/commands/checkpoint.py">--help</a></code>
+* <code title="cli">praisonai checkpoint diff <a href="./src/praisonai/praisonai/cli/commands/checkpoint.py">--help</a></code>
+* <code title="cli">praisonai checkpoint list <a href="./src/praisonai/praisonai/cli/commands/checkpoint.py">--help</a></code>
+* <code title="cli">praisonai checkpoint restore <a href="./src/praisonai/praisonai/cli/commands/checkpoint.py">--help</a></code>
+* <code title="cli">praisonai checkpoint save <a href="./src/praisonai/praisonai/cli/commands/checkpoint.py">--help</a></code>
 * <code title="cli">praisonai claw claw <a href="./src/praisonai/praisonai/cli/commands/claw.py">--help</a></code>
 * <code title="cli">praisonai code <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
+* <code title="cli">praisonai code code-main <a href="./src/praisonai/praisonai/cli/commands/code.py">--help</a></code>
+* <code title="cli">praisonai command list <a href="./src/praisonai/praisonai/cli/commands/command.py">--help</a></code>
+* <code title="cli">praisonai command show <a href="./src/praisonai/praisonai/cli/commands/command.py">--help</a></code>
+* <code title="cli">praisonai commit commit-main <a href="./src/praisonai/praisonai/cli/commands/commit.py">--help</a></code>
+* <code title="cli">praisonai completion bash <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
+* <code title="cli">praisonai completion completion-callback <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
+* <code title="cli">praisonai completion fish <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
+* <code title="cli">praisonai completion zsh <a href="./src/praisonai/praisonai/cli/commands/completion.py">--help</a></code>
+* <code title="cli">praisonai config doctor <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config env <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config get <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config list <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config path <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config reset <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config set <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config show <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config sources <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai config validate <a href="./src/praisonai/praisonai/cli/commands/config.py">--help</a></code>
+* <code title="cli">praisonai context add <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context clear <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context compact <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context export <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context grep <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context list <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context show <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context stats <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai context tail <a href="./src/praisonai/praisonai/cli/commands/context.py">--help</a></code>
+* <code title="cli">praisonai daemon daemon-main <a href="./src/praisonai/praisonai/cli/commands/daemon.py">--help</a></code>
+* <code title="cli">praisonai daemon start <a href="./src/praisonai/praisonai/cli/commands/daemon.py">--help</a></code>
+* <code title="cli">praisonai daemon status <a href="./src/praisonai/praisonai/cli/commands/daemon.py">--help</a></code>
+* <code title="cli">praisonai daemon stop <a href="./src/praisonai/praisonai/cli/commands/daemon.py">--help</a></code>
 * <code title="cli">praisonai dashboard unified <a href="./src/praisonai/praisonai/cli/commands/dashboard.py">--help</a></code>
+* <code title="cli">praisonai debug acp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
+* <code title="cli">praisonai debug debug-callback <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
+* <code title="cli">praisonai debug interactive <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
+* <code title="cli">praisonai debug lsp <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
+* <code title="cli">praisonai debug trace <a href="./src/praisonai/praisonai/cli/commands/debug.py">--help</a></code>
+* <code title="cli">praisonai deploy aws <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
+* <code title="cli">praisonai deploy azure <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
+* <code title="cli">praisonai deploy docker <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
+* <code title="cli">praisonai deploy gcp <a href="./src/praisonai/praisonai/cli/commands/deploy.py">--help</a></code>
+* <code title="cli">praisonai diag diag-callback <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
+* <code title="cli">praisonai diag export <a href="./src/praisonai/praisonai/cli/commands/diag.py">--help</a></code>
+* <code title="cli">praisonai docs api-md <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai docs generate <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai docs list <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai docs report <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai docs run <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai docs run-all <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai docs serve <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai docs stats <a href="./src/praisonai/praisonai/cli/commands/docs.py">--help</a></code>
+* <code title="cli">praisonai doctor cleanup <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor docker <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor env <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor llm-providers <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor mcp <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor memory-store <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor metadata-store <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor network <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor packaging <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor performance <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor runtime <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor selftest <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor skills <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai doctor troubleshoot <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
+* <code title="cli">praisonai endpoints list <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
+* <code title="cli">praisonai endpoints test <a href="./src/praisonai/praisonai/cli/commands/endpoints.py">--help</a></code>
+* <code title="cli">praisonai environment check <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
+* <code title="cli">praisonai environment doctor <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
+* <code title="cli">praisonai environment view <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
+* <code title="cli">praisonai eval accuracy <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
+* <code title="cli">praisonai eval judge <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
+* <code title="cli">praisonai eval list-judges <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
+* <code title="cli">praisonai eval performance <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
+* <code title="cli">praisonai examples find <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
+* <code title="cli">praisonai examples info <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
+* <code title="cli">praisonai examples list <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
+* <code title="cli">praisonai examples report <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
+* <code title="cli">praisonai examples run <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
+* <code title="cli">praisonai examples run-all <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
+* <code title="cli">praisonai examples stats <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
+* <code title="cli">praisonai flow export <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
+* <code title="cli">praisonai flow flow-start <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
+* <code title="cli">praisonai flow import <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
+* <code title="cli">praisonai flow list <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
+* <code title="cli">praisonai flow version <a href="./src/praisonai/praisonai/cli/commands/flow.py">--help</a></code>
 * <code title="cli">praisonai gateway channels <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
-* <code title="cli">praisonai gateway doctor <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
 * <code title="cli">praisonai gateway gateway-callback <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
 * <code title="cli">praisonai gateway install <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
 * <code title="cli">praisonai gateway logs <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
@@ -852,10 +968,15 @@ Methods:
 * <code title="cli">praisonai gateway status <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
 * <code title="cli">praisonai gateway stop <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
 * <code title="cli">praisonai gateway uninstall <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
+* <code title="cli">praisonai github triage <a href="./src/praisonai/praisonai/cli/commands/github.py">--help</a></code>
+* <code title="cli">praisonai hooks add <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
+* <code title="cli">praisonai hooks list <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
+* <code title="cli">praisonai hooks remove <a href="./src/praisonai/praisonai/cli/commands/hooks.py">--help</a></code>
 * <code title="cli">praisonai identity import <a href="./src/praisonai/praisonai/cli/commands/identity.py">--help</a></code>
 * <code title="cli">praisonai identity link <a href="./src/praisonai/praisonai/cli/commands/identity.py">--help</a></code>
 * <code title="cli">praisonai identity list <a href="./src/praisonai/praisonai/cli/commands/identity.py">--help</a></code>
 * <code title="cli">praisonai identity unlink <a href="./src/praisonai/praisonai/cli/commands/identity.py">--help</a></code>
+* <code title="cli">praisonai init init <a href="./src/praisonai/praisonai/cli/commands/init.py">--help</a></code>
 * <code title="cli">praisonai kanban block <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
 * <code title="cli">praisonai kanban boards <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
 * <code title="cli">praisonai kanban comment <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
@@ -868,12 +989,249 @@ Methods:
 * <code title="cli">praisonai kanban reclaim <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
 * <code title="cli">praisonai kanban show <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
 * <code title="cli">praisonai kanban unblock <a href="./src/praisonai/praisonai/cli/commands/kanban.py">--help</a></code>
+* <code title="cli">praisonai knowledge add <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
+* <code title="cli">praisonai knowledge index <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
+* <code title="cli">praisonai knowledge list <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
+* <code title="cli">praisonai knowledge search <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
+* <code title="cli">praisonai langextract render <a href="./src/praisonai/praisonai/cli/commands/langextract.py">--help</a></code>
+* <code title="cli">praisonai langextract view <a href="./src/praisonai/praisonai/cli/commands/langextract.py">--help</a></code>
+* <code title="cli">praisonai langfuse config <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse connect <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse init <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse langfuse-start <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse sessions <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse show <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse status <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse stop <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse test <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse traces <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai langfuse version <a href="./src/praisonai/praisonai/cli/commands/langfuse.py">--help</a></code>
+* <code title="cli">praisonai loop help <a href="./src/praisonai/praisonai/cli/commands/loop.py">--help</a></code>
+* <code title="cli">praisonai loop loop-main <a href="./src/praisonai/praisonai/cli/commands/loop.py">--help</a></code>
+* <code title="cli">praisonai lsp logs <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
+* <code title="cli">praisonai lsp lsp-callback <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
+* <code title="cli">praisonai lsp start <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
+* <code title="cli">praisonai lsp status <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
+* <code title="cli">praisonai lsp stop <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
+* <code title="cli">praisonai managed delete <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed get <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed list <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed managed-callback <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed multi <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed restore <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed resume <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed run <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed save <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed show <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai managed update <a href="./src/praisonai/praisonai/cli/commands/managed.py">--help</a></code>
+* <code title="cli">praisonai mcp add <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp auth <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp describe <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp list <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp logout <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp mcp-callback <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp remove <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp run <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp status <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp sync <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp test <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp tools <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai memory add <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
+* <code title="cli">praisonai memory clear <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
+* <code title="cli">praisonai memory search <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
+* <code title="cli">praisonai memory show <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
+* <code title="cli">praisonai memory status <a href="./src/praisonai/praisonai/cli/commands/memory.py">--help</a></code>
+* <code title="cli">praisonai models describe <a href="./src/praisonai/praisonai/cli/commands/models.py">--help</a></code>
+* <code title="cli">praisonai models list <a href="./src/praisonai/praisonai/cli/commands/models.py">--help</a></code>
+* <code title="cli">praisonai models validate <a href="./src/praisonai/praisonai/cli/commands/models.py">--help</a></code>
+* <code title="cli">praisonai n8n export <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
+* <code title="cli">praisonai n8n import <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
+* <code title="cli">praisonai n8n list <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
+* <code title="cli">praisonai n8n preview <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
+* <code title="cli">praisonai n8n pull <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
+* <code title="cli">praisonai n8n push <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
+* <code title="cli">praisonai n8n test <a href="./src/praisonai/praisonai/cli/commands/n8n.py">--help</a></code>
+* <code title="cli">praisonai obs obs-fallback <a href="./src/praisonai/praisonai/cli/commands/obs.py">--help</a></code>
 * <code title="cli">praisonai onboard onboard-callback <a href="./src/praisonai/praisonai/cli/commands/onboard.py">--help</a></code>
+* <code title="cli">praisonai package install <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
+* <code title="cli">praisonai package list <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
+* <code title="cli">praisonai package uninstall <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
 * <code title="cli">praisonai pairing approve <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
 * <code title="cli">praisonai pairing clear <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
 * <code title="cli">praisonai pairing list <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
 * <code title="cli">praisonai pairing revoke <a href="./src/praisonai/praisonai/cli/commands/pairing.py">--help</a></code>
+* <code title="cli">praisonai paths show <a href="./src/praisonai/praisonai/cli/commands/paths.py">--help</a></code>
+* <code title="cli">praisonai permissions allow <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai permissions ask <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai permissions deny <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai permissions export <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai permissions import-rules <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai permissions list <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai permissions remove <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai permissions reset <a href="./src/praisonai/praisonai/cli/commands/permissions.py">--help</a></code>
+* <code title="cli">praisonai plugins create <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins disable <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins discover <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins doctor <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins enable <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins info <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins install <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins list <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins plugins-callback <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins remove <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai port check <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
+* <code title="cli">praisonai port kill <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
+* <code title="cli">praisonai port list <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
+* <code title="cli">praisonai port port-callback <a href="./src/praisonai/praisonai/cli/commands/port.py">--help</a></code>
+* <code title="cli">praisonai profile imports <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
+* <code title="cli">praisonai profile optimize <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
+* <code title="cli">praisonai profile profile-callback <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
+* <code title="cli">praisonai profile query <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
+* <code title="cli">praisonai profile snapshot <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
+* <code title="cli">praisonai profile startup <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
+* <code title="cli">praisonai profile suite <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
+* <code title="cli">praisonai publish publish-main <a href="./src/praisonai/praisonai/cli/commands/publish.py">--help</a></code>
+* <code title="cli">praisonai publish pypi <a href="./src/praisonai/praisonai/cli/commands/publish.py">--help</a></code>
+* <code title="cli">praisonai rag chat <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
+* <code title="cli">praisonai rag eval <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
+* <code title="cli">praisonai rag index <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
+* <code title="cli">praisonai rag query <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
+* <code title="cli">praisonai rag serve <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
+* <code title="cli">praisonai realtime realtime-main <a href="./src/praisonai/praisonai/cli/commands/realtime.py">--help</a></code>
+* <code title="cli">praisonai recipe apply <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe create <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe info <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe install <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe judge <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe list <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe optimize <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe run <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe serve <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai registry list <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
+* <code title="cli">praisonai registry serve <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
+* <code title="cli">praisonai replay cleanup <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay context <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay dashboard <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay delete <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay flow <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay list <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay show <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai research research-main <a href="./src/praisonai/praisonai/cli/commands/research.py">--help</a></code>
+* <code title="cli">praisonai retrieval index <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
+* <code title="cli">praisonai retrieval query <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
+* <code title="cli">praisonai retrieval search <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
+* <code title="cli">praisonai rules add <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
+* <code title="cli">praisonai rules clear <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
+* <code title="cli">praisonai rules list <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
 * <code title="cli">praisonai run <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
+* <code title="cli">praisonai run run-main <a href="./src/praisonai/praisonai/cli/commands/run.py">--help</a></code>
+* <code title="cli">praisonai sandbox explain <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox list <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox recreate <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox sandbox-callback <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox status <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai schedule add <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule blueprint <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule blueprint-list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule delete <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule describe <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule logs <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule restart <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule schedule-callback <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule start <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule stats <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule stop <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule suggestion-accept <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule suggestion-dismiss <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule suggestion-propose <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai schedule suggestions <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai serve a2a <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve a2u <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve acp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve agents <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve docs <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve gateway <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve lsp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve mcp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve openai <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve rag <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve recipe <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve registry <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve scheduler <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve serve-callback <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve start <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve status <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve stop <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve ui <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve ui-gateway <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve unified <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai session delete <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
+* <code title="cli">praisonai session export <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
+* <code title="cli">praisonai session import <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
+* <code title="cli">praisonai session list <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
+* <code title="cli">praisonai session resume <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
+* <code title="cli">praisonai session show <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
+* <code title="cli">praisonai setup config <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
+* <code title="cli">praisonai setup reset <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
+* <code title="cli">praisonai setup setup-callback <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
+* <code title="cli">praisonai setup wizard <a href="./src/praisonai/praisonai/cli/commands/setup.py">--help</a></code>
+* <code title="cli">praisonai skills check <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills create <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills eligible <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills info <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills install <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills learn <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills list <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills search <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills validate <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai standardise check <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
+* <code title="cli">praisonai standardise fix <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
+* <code title="cli">praisonai standardise init <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
+* <code title="cli">praisonai standardise report <a href="./src/praisonai/praisonai/cli/commands/standardise.py">--help</a></code>
+* <code title="cli">praisonai templates create <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
+* <code title="cli">praisonai templates list <a href="./src/praisonai/praisonai/cli/commands/templates.py">--help</a></code>
+* <code title="cli">praisonai test info <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
+* <code title="cli">praisonai test interactive <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
+* <code title="cli">praisonai test run <a href="./src/praisonai/praisonai/cli/commands/test.py">--help</a></code>
+* <code title="cli">praisonai todo add <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
+* <code title="cli">praisonai todo done <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
+* <code title="cli">praisonai todo list <a href="./src/praisonai/praisonai/cli/commands/todo.py">--help</a></code>
+* <code title="cli">praisonai tools info <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
+* <code title="cli">praisonai tools list <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
+* <code title="cli">praisonai tools test <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
+* <code title="cli">praisonai tools validate <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
+* <code title="cli">praisonai traces disable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
+* <code title="cli">praisonai traces enable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
+* <code title="cli">praisonai traces list <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
+* <code title="cli">praisonai traces status <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
+* <code title="cli">praisonai tracker batch <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
+* <code title="cli">praisonai tracker judge <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
+* <code title="cli">praisonai tracker run <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
+* <code title="cli">praisonai tracker tools <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
+* <code title="cli">praisonai tracker tracker-main <a href="./src/praisonai/praisonai/cli/commands/tracker.py">--help</a></code>
+* <code title="cli">praisonai train agents <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train apply <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train list <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train llm <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train show <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train train-callback <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai ui agents <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
+* <code title="cli">praisonai ui bot <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
+* <code title="cli">praisonai ui realtime <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
+* <code title="cli">praisonai ui ui <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
+* <code title="cli">praisonai up logs <a href="./src/praisonai/praisonai/cli/commands/up.py">--help</a></code>
+* <code title="cli">praisonai up status <a href="./src/praisonai/praisonai/cli/commands/up.py">--help</a></code>
+* <code title="cli">praisonai up up-start <a href="./src/praisonai/praisonai/cli/commands/up.py">--help</a></code>
+* <code title="cli">praisonai validate check <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
+* <code title="cli">praisonai validate schema <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
+* <code title="cli">praisonai validate validate <a href="./src/praisonai/praisonai/cli/commands/validate.py">--help</a></code>
+* <code title="cli">praisonai version check <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
+* <code title="cli">praisonai version show <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
+* <code title="cli">praisonai version version-callback <a href="./src/praisonai/praisonai/cli/commands/version.py">--help</a></code>
+* <code title="cli">praisonai workflow create <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
+* <code title="cli">praisonai workflow list <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
+* <code title="cli">praisonai workflow run <a href="./src/praisonai/praisonai/cli/commands/workflow.py">--help</a></code>
 
 # TypeScript
 

docker/Dockerfile.chat

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.111" \
+    "praisonai>=4.6.80" \
     "praisonai[chat]" \
     "embedchain[github,youtube]"
 

docker/Dockerfile.dev

@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.111" \
+    "praisonai>=4.6.80" \
     "praisonai[ui]" \
     "praisonai[chat]" \
     "praisonai[realtime]" \

docker/Dockerfile.ui

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.111" \
+    "praisonai>=4.6.80" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/python/frameworks/custom_adapter/my_framework_adapter.py

@@ -1,25 +0,0 @@
-"""Example third-party framework adapter (entry-point template)."""
-
-from praisonaiagents.frameworks.base import BaseFrameworkAdapter
-
-
-class MyFrameworkAdapter(BaseFrameworkAdapter):
-    name = "my_framework"
-    install_hint = "pip install my-framework-bridge"
-    requires_tools_extra = False
-
-    def is_available(self) -> bool:
-        return True
-
-    def run(
-        self,
-        config,
-        llm_config,
-        topic,
-        *,
-        tools_dict=None,
-        agent_callback=None,
-        task_callback=None,
-        cli_config=None,
-    ) -> str:
-        return f"my_framework ran: {topic}"

examples/python/frameworks/custom_adapter/pyproject.toml

@@ -1,14 +0,0 @@
-[build-system]
-requires = ["setuptools>=61.0"]
-build-backend = "setuptools.build_meta"
-
-[project]
-name = "my-framework-bridge"
-version = "0.0.1"
-dependencies = ["praisonaiagents"]
-
-[tool.setuptools]
-py-modules = ["my_framework_adapter"]
-
-[project.entry-points."praisonai.framework_adapters"]
-my_framework = "my_framework_adapter:MyFrameworkAdapter"

examples/python/scheduled_agents/simple_test.py

@@ -1,5 +1,5 @@
 """
-Simple test script for 24/7 Agent Scheduler.
+Simple test script for 24/7 Agent Scheduler
 
 This script demonstrates the basic usage of AgentScheduler
 for running agents periodically.
@@ -8,56 +8,42 @@ Usage:
     python simple_test.py
 """
 
-import os
 import sys
-import time
-from unittest.mock import AsyncMock, Mock
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "../../.."))
+import os
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '../../..'))
 
+from unittest.mock import Mock
 from praisonai.scheduler import AgentScheduler
 
-# ---------------------------------------------------------------------
-# Create a mock agent
-#
-# The scheduler now supports both asynchronous (astart) and synchronous
-# (start) execution. This example exposes both methods so either dispatch
-# path can be exercised.
-# ---------------------------------------------------------------------
-
-mock_agent = Mock(spec=["name", "start", "astart"])
+# Create a mock agent for testing
+mock_agent = Mock()
 mock_agent.name = "TestAgent"
-
-mock_agent.astart = AsyncMock(
-    return_value="Test execution successful!"
-)
-mock_agent.start = Mock(
-    return_value="Test execution successful!"
-)
+mock_agent.start = Mock(return_value="Test execution successful!")
 
 # Create scheduler
 scheduler = AgentScheduler(
     agent=mock_agent,
-    task="Test task execution",
+    task="Test task execution"
 )
 
 print("🤖 Testing AgentScheduler")
 print("=" * 60)
 
-# Execute once
+# Test 1: Execute once
 print("\n✅ Test 1: Execute once")
 result = scheduler.execute_once()
 print(f"Result: {result}")
 
-# Statistics
+# Test 2: Get stats
 print("\n✅ Test 2: Get statistics")
 stats = scheduler.get_stats()
 print(f"Stats: {stats}")
 
-# Periodic execution
+# Test 3: Start scheduler (will run every 5 seconds)
 print("\n✅ Test 3: Start scheduler (*/5s)")
 scheduler.start("*/5s", run_immediately=True)
 
+import time
 print("Running for 12 seconds...")
 time.sleep(12)
 
@@ -65,10 +51,11 @@ time.sleep(12)
 print("\n✅ Test 4: Stop scheduler")
 scheduler.stop()
 
-# Final statistics
+# Final stats
 print("\n📊 Final Statistics:")
-for key, value in scheduler.get_stats().items():
+final_stats = scheduler.get_stats()
+for key, value in final_stats.items():
     print(f"  {key}: {value}")
 
 print("\n✅ All tests passed!")
-print("=" * 60)
+print("=" * 60)

examples/tools/xquik_tweet_search_tool.py

@@ -1,106 +0,0 @@
-"""Use Xquik tweet search as a PraisonAI custom tool.
-
-Set XQUIK_API_KEY before running this example. The tool calls the public
-Xquik tweet search endpoint and returns compact tweet summaries for the agent.
-"""
-
-from __future__ import annotations
-
-import json
-import os
-from typing import Any
-from urllib.error import HTTPError, URLError
-from urllib.parse import urlencode
-from urllib.request import Request, urlopen
-
-from praisonaiagents import Agent, tool
-
-
-XQUIK_SEARCH_URL = "https://xquik.com/api/v1/x/tweets/search"
-
-
-def _xquik_api_key_available() -> tuple[bool, str]:
-    return bool(os.environ.get("XQUIK_API_KEY")), "Set XQUIK_API_KEY before using search_x_posts."
-
-
-def _as_record(value: Any) -> dict[str, Any]:
-    if isinstance(value, dict):
-        return value
-    return {}
-
-
-def _as_text(value: Any) -> str:
-    if isinstance(value, str):
-        return " ".join(value.split())
-    if value is None:
-        return ""
-    return " ".join(str(value).split())
-
-
-def _tweet_line(tweet: dict[str, Any]) -> str:
-    author_record = _as_record(tweet.get("author") or tweet.get("user"))
-    author = _as_text(
-        tweet.get("author_username")
-        or tweet.get("username")
-        or author_record.get("username")
-        or author_record.get("screen_name")
-        or author_record.get("handle")
-    )
-    text = _as_text(tweet.get("text") or tweet.get("full_text") or tweet.get("content"))
-    tweet_id = _as_text(tweet.get("id") or tweet.get("tweet_id") or tweet.get("tweetId"))
-    prefix = f"@{author}: " if author else ""
-    suffix = f" ({tweet_id})" if tweet_id else ""
-    return f"{prefix}{text}{suffix}".strip()
-
-
-def _bounded_limit(value: Any) -> int:
-    try:
-        parsed = int(float(value))
-    except (TypeError, ValueError, OverflowError):
-        return 5
-    return max(1, min(parsed, 10))
-
-
-@tool(availability=_xquik_api_key_available)
-def search_x_posts(query: str, limit: int = 5) -> str:
-    """Search recent public X posts with Xquik."""
-    api_key = os.environ.get("XQUIK_API_KEY")
-    if not api_key:
-        return "Set XQUIK_API_KEY before using search_x_posts."
-
-    query_text = _as_text(query)
-    if not query_text:
-        return "Provide a non-empty query before using search_x_posts."
-
-    bounded_limit = _bounded_limit(limit)
-    params = {"q": query_text, "limit": bounded_limit, "queryType": "Latest"}
-    url = f"{XQUIK_SEARCH_URL}?{urlencode(params)}"
-    request = Request(
-        url,
-        headers={"X-API-Key": api_key, "Accept": "application/json"},
-    )
-
-    try:
-        with urlopen(request, timeout=20) as response:
-            payload = json.loads(response.read().decode("utf-8"))
-    except HTTPError as error:
-        return f"Xquik returned HTTP {error.code}."
-    except (URLError, TimeoutError, json.JSONDecodeError) as error:
-        return f"Xquik search failed: {error.__class__.__name__}."
-
-    tweets = _as_record(payload).get("tweets")
-    if not isinstance(tweets, list) or not tweets:
-        return "No posts found."
-
-    lines = [_tweet_line(_as_record(tweet)) for tweet in tweets[:bounded_limit]]
-    return "\n".join(line for line in lines if line) or "No readable posts found."
-
-
-agent = Agent(
-    instructions="You find recent public X posts and summarize the useful patterns.",
-    tools=[search_x_posts],
-)
-
-
-if __name__ == "__main__":
-    agent.start("Search X for recent AI agent framework discussions.")

scripts/c7_wrapper_import_allowlist.txt

@@ -1,53 +0,0 @@
-# Files allowed to contain lazy ``from praisonai.*`` imports in praisonai-code.
-# New direct imports require review; prefer praisonai_code._wrapper_bridge.
-# Regenerate counts: bash scripts/check_c7_imports.sh
-#
-# Format: path  # reason (approx line count after C7.1)
-
-cli/main.py  # legacy argparse, auto, agents_generator (wrapper-enhanced)
-cli/features/recipe.py  # recipe runner (wrapper integrations)
-cli/features/templates.py  # template store in wrapper
-cli/commands/serve.py  # hybrid; gateway serve subpaths need wrapper
-cli/commands/train.py  # training uses wrapper capabilities
-cli/commands/docs.py  # docs server wrapper paths
-cli/commands/replay.py  # trace replay wrapper
-cli/features/deploy.py  # deployment integrations
-cli/commands/standardise.py  # migration tooling
-cli/commands/schedule.py  # scheduler wrapper
-cli/commands/n8n.py  # n8n integration
-cli/commands/examples.py  # example runners
-cli/features/persistence.py  # persistence backends
-cli/commands/langfuse.py  # observability
-cli/commands/flow.py  # Langflow
-cli/features/recipe_optimizer.py  # recipe tooling
-cli/interactive/async_tui.py  # interactive wrapper hooks
-cli/commands/mcp.py  # MCP server management
-cli/commands/validate.py  # validation against wrapper schemas
-cli/commands/context.py  # context features
-cli/commands/batch.py  # batch runner
-cli/features/agent_scheduler.py  # scheduler integration
-cli/features/eval.py  # eval harness
-cli/features/tools.py  # tool discovery
-cli/features/sandbox_cli.py  # sandbox wrapper
-cli/features/registry.py  # plugin registry wrapper
-cli/features/ollama.py  # ollama wrapper
-cli/features/workflow.py  # workflow wrapper
-cli/features/tui/app.py  # TUI wrapper hooks
-cli/features/interactive_runtime.py  # runtime bridge
-cli/features/endpoints.py  # API endpoints
-cli/features/background.py  # background jobs
-cli/features/agent_tools.py  # agent tools wrapper
-cli/features/acp.py  # ACP wrapper
-cli/commands/rag.py  # RAG server
-cli/commands/realtime.py  # realtime API
-cli/commands/knowledge.py  # knowledge CLI
-cli/commands/langextract.py  # langextract
-cli/commands/profile.py  # profiler
-cli/commands/recipe.py  # recipe command
-cli/commands/audit.py  # audit
-cli/interactive/core.py  # interactive core
-cli/commands/managed.py  # managed deployment (wrapper integrations)
-cli/commands/app.py  # legacy app launcher (wrapper-enhanced)
-cli/features/doctor/checks/performance_checks.py  # perf checks probe wrapper import cost
-_version.py  # optional wrapper version fallback
-cli/langfuse_client.py  # langfuse shim path

scripts/check_c7_imports.sh

@@ -1,86 +0,0 @@
-#!/usr/bin/env bash
-# C7 import-direction gate for praisonai-code (standalone hot path).
-set -euo pipefail
-
-ROOT="${1:-src/praisonai-code/praisonai_code}"
-cd "$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
-
-# Module-level hot path: praisonai wrapper only (not praisonaiagents / praisonai_code).
-HOT_PATH_RE='^from praisonai([[:space:]]|\.|$)|^import praisonai([[:space:]]|\.|$)'
-# Line-level wrapper imports (exclude praisonaiagents, praisonai_code, praisonai-tools).
-ANY_WRAPPER_RE='(^[[:space:]]*from praisonai([[:space:]]|\.)|^import praisonai($|\.))'
-ALLOWLIST="scripts/c7_wrapper_import_allowlist.txt"
-
-echo "== C7 hot-path module-level gate =="
-for f in \
-  "$ROOT/cli/main.py" \
-  "$ROOT/cli/app.py" \
-  "$ROOT/cli/commands/run.py" \
-  "$ROOT/cli/commands/chat.py" \
-  "$ROOT/cli/commands/code.py"
-do
-  if grep -E "$HOT_PATH_RE" "$f" 2>/dev/null; then
-    echo "FAIL: module-level wrapper import in $f"
-    exit 1
-  fi
-done
-echo "hot-path module-level gate ok"
-
-echo "== C7 strict gate (run/chat/code/app — no wrapper imports) =="
-for f in \
-  "$ROOT/cli/app.py" \
-  "$ROOT/cli/commands/run.py" \
-  "$ROOT/cli/commands/chat.py" \
-  "$ROOT/cli/commands/code.py"
-do
-  if grep -E "$ANY_WRAPPER_RE" "$f" 2>/dev/null; then
-    echo "FAIL: wrapper import in $f"
-    exit 1
-  fi
-done
-echo "strict hot-path gate ok"
-
-echo "== C7 regression baseline (total wrapper import lines) =="
-BASELINE="${C7_WRAPPER_IMPORT_BASELINE:-225}"
-# Count wrapper import lines with a portable tool. Prefer ripgrep when present
-# (fast, respects the same regex) and fall back to POSIX grep -r otherwise, so
-# the gate does not exit 127 on runners without rg. The `|| true` keeps a
-# no-match (grep/rg exit 1) from aborting the script under `set -o pipefail`.
-if command -v rg >/dev/null 2>&1; then
-  COUNT="$( { rg -c "$ANY_WRAPPER_RE" "$ROOT" --glob '*.py' 2>/dev/null || true; } | awk -F: '{s+=$2} END {print s+0}')"
-else
-  COUNT="$( { grep -rEc --include='*.py' "$ANY_WRAPPER_RE" "$ROOT" 2>/dev/null || true; } | awk -F: '{s+=$2} END {print s+0}')"
-fi
-echo "wrapper import lines: $COUNT (baseline $BASELINE)"
-if [ "$COUNT" -gt "$BASELINE" ]; then
-  echo "FAIL: wrapper import count regressed above baseline ($COUNT > $BASELINE)"
-  exit 1
-fi
-echo "regression baseline ok"
-
-echo "== C7 allowlist enforcement =="
-if [ -f "$ALLOWLIST" ]; then
-  # Files (relative to $ROOT) that carry wrapper imports.
-  if command -v rg >/dev/null 2>&1; then
-    OFFENDERS="$( { rg -l "$ANY_WRAPPER_RE" "$ROOT" --glob '*.py' 2>/dev/null || true; } )"
-  else
-    OFFENDERS="$( { grep -rlE --include='*.py' "$ANY_WRAPPER_RE" "$ROOT" 2>/dev/null || true; } )"
-  fi
-  # Strip the reasons/comments and blank/comment lines from the allowlist.
-  ALLOWED="$(sed -E 's/[[:space:]]*#.*$//; /^[[:space:]]*$/d' "$ALLOWLIST" | sed -E 's/[[:space:]]+$//')"
-  FAIL=0
-  while IFS= read -r f; do
-    [ -z "$f" ] && continue
-    rel="${f#"$ROOT/"}"
-    if ! printf '%s\n' "$ALLOWED" | grep -Fxq "$rel"; then
-      echo "FAIL: non-allowlisted wrapper import in $rel (add to $ALLOWLIST after review)"
-      FAIL=1
-    fi
-  done <<< "$OFFENDERS"
-  if [ "$FAIL" -ne 0 ]; then
-    exit 1
-  fi
-  echo "allowlist enforcement ok"
-else
-  echo "allowlist file missing: $ALLOWLIST (skipping enforcement)"
-fi

src/praisonai-agents/AGENTS.md

@@ -42,11 +42,7 @@ Each feature runs 3 ways: **CLI, YAML, Python**.
 │   │   └── pyproject.toml         # Package config
 │   │
 │   ├── praisonai/                 # Wrapper (praisonai)
-│   │   ├── praisonai/             # Bot/channel CLI, integrations, heavy impls
-│   │   └── pyproject.toml
-│   │
-│   ├── praisonai-code/            # Agentic terminal CLI (praisonai_code)
-│   │   ├── praisonai_code/        # run, chat, code, runtime, cli_backends
+│   │   ├── praisonai/             # CLI, integrations, heavy impls
 │   │   └── pyproject.toml
 │   │
 │   └── praisonai-ts/              # TypeScript SDK
@@ -84,10 +80,7 @@ Each feature runs 3 ways: **CLI, YAML, Python**.
 ```
 ┌─────────────────────────────────────────────────────────────────┐
 │                      praisonai (Wrapper)                        │
-│  Bot/channel CLI • Gateway • Integrations • Heavy impls         │
-├─────────────────────────────────────────────────────────────────┤
-│                    praisonai-code (Terminal agent)              │
-│  run • chat • code • doctor • runtime • cli_backends • Typer    │
+│  CLI • Integrations • Heavy Implementations • Optional Deps     │
 ├─────────────────────────────────────────────────────────────────┤
 │                    praisonaiagents (Core SDK)                   │
 │  Protocols • Hooks • Adapters • Base Classes • Decorators       │
@@ -97,123 +90,6 @@ Each feature runs 3 ways: **CLI, YAML, Python**.
 └─────────────────────────────────────────────────────────────────┘
 ```
 
-### 2.3 `praisonai-code` — Agentic Terminal CLI Split (C5/C6)
-
-The **agentic terminal CLI** (`run`, `chat`, `code`, warm runtime, CLI backends, Typer app) lives in the separate **`praisonai-code`** PyPI package (`praisonai_code`). The **`praisonai`** wrapper keeps bot/channel orchestration, gateway, and heavy integrations. **`pip install praisonai`** still installs everything; old import paths are preserved via shims.
-
-| Product | Location | Stays out of |
-|---------|----------|--------------|
-| Agentic terminal CLI | `src/praisonai-code/praisonai_code/` | Must **not** depend on `praisonai` (PyPI cycle) |
-| Bot/channel runtime | `src/praisonai/praisonai/` | Gateway, BotOS, onboarding, dashboard |
-| Core SDK | `src/praisonai-agents/praisonaiagents/` | Heavy CLI / integrations |
-
-**Moved into `praisonai_code` (~304 modules):**
-
-| Step | Content |
-|------|---------|
-| C1 | `runtime/`, `cli_backends/` |
-| C2 | `cli/interactive/`, `execution/`, `ui/`, `output/`, `state/` |
-| C3 | `cli/commands/*` (80 Typer command modules) |
-| C4 | `cli/features/*` (158 feature handlers; bot features excepted) |
-| C5 | `cli/main.py`, `app.py`, `configuration/`, `session/`, `utils/`, schema modules |
-
-**Intentionally retained in the wrapper (not shims):**
-
-- **Commands:** `gateway`, `bot`, `pairing`, `identity`, `onboard`, `kanban`, `dashboard`, `claw`
-- **Features:** `gateway`, `bots_cli`, `onboard`, `approval`, `serve`
-- **Domains:** `praisonai.gateway.*`, `praisonai.bots.*`, integrations, endpoints
-
-**Backward-compat shim patterns** (old `praisonai.*` paths must keep working):
-
-| Pattern | Used for | Module identity |
-|---------|----------|-----------------|
-| `sys.modules[__name__] = _impl` | `cli/main`, `cli/app`, each moved `cli/commands/*`, schema modules | Same object as `praisonai_code.*` |
-| `alias_package()` + `_AliasFinder` | `cli/output`, `interactive`, `execution`, `ui`, `state`, `session`, `configuration`, `utils` | Same submodule objects |
-| Package `__getattr__` + submodule alias | `runtime/`, `cli_backends/` | Submodules identical; package object differs |
-| `features/__init__.py` `__path__` extension | Extracted features; five bot features stay local | Handler imports via `__getattr__` |
-
-**Typer lazy-load:** `praisonai_code.cli.app._WRAPPER_COMMANDS` lists bot/channel commands that resolve via **`praisonai.cli.commands.*`** (wrapper), not `praisonai_code.cli.commands.*`.
-
-**Monorepo bootstrap:** `praisonai._bootstrap.ensure_praisonai_code()` adds sibling `src/praisonai-code` to `sys.path` so `PYTHONPATH=src/praisonai-agents:src/praisonai` works without an explicit code entry.
-
-**Install order (CI and local dev):** `praisonai-agents` → `praisonai-code` → `praisonai` (see `.github/actions/install-monorepo-packages`).
-
-**Invocation paths that must remain valid:**
-
-```bash
-praisonai …                          # console script → praisonai.__main__
-python -m praisonai …
-python -m praisonai.cli.main …
-python -m praisonai.runtime …
-from praisonai.cli.main import PraisonAI
-from praisonai.cli.commands.run import …
-unittest.mock.patch("praisonai.cli.commands.run.X")   # same module object
-```
-
-**Regression gate:** `src/praisonai/tests/unit/test_c5_backward_compat.py` (also run in optimised CI smoke). Standalone `pip install praisonai-code` requires declared deps (e.g. `toml` for config resolver).
-
-**Key files:**
-
-| What | Where |
-|------|-------|
-| Typer app + lazy commands | `praisonai_code/cli/app.py` |
-| Shim helper | `praisonai/cli/_shim.py` |
-| Bootstrap | `praisonai/_bootstrap.py` |
-| CLI main shim | `praisonai/cli/main.py` |
-| Runtime / backends shims | `praisonai/runtime/`, `praisonai/cli_backends/` |
-
-**Do not** recreate `src/praisonai/praisonai_code/` — it shadows the real package.
-
-**PyPI publish order:** `praisonaiagents` → `praisonai-code` → `praisonai` (see `src/praisonai/scripts/bump_and_release.py` and `.github/workflows/pypi-release.yml`). Gateway/bots changes release via wrapper only; agentic CLI changes also bump `praisonai-code`.
-
-#### C6 integration gate (#2519)
-
-C6 is the **sign-off step** after C0–C5 file moves: no further moves, only regression verification and release wiring.
-
-| Check | Command / artefact |
-|-------|-------------------|
-| Smoke `--help` | `praisonai`, `praisonai run/chat/code/daemon/attach/gateway/bot/doctor --help` |
-| Compat regression | `pytest src/praisonai/tests/unit/test_c5_backward_compat.py` |
-| CLI shard | `pytest src/praisonai/tests/unit/cli/` |
-| Warm runtime | `pytest src/praisonai/tests/unit/test_warm_runtime.py` |
-| Doctor shard | `pytest src/praisonai/tests/unit/doctor/` |
-| Import perf | `pytest src/praisonai/tests/unit/test_performance_benchmarks.py` (< 500ms) |
-| Real LLM smoke | `RUN_REAL_KEY_TESTS=1 PRAISONAI_ALLOW_NETWORK=1 PRAISONAI_TEST_PROVIDERS=all pytest src/praisonai/tests/integration/test_real_key_smoke.py` |
-| Verification log | `src/praisonai/tests/C6_VERIFICATION.md` |
-
-**Command split (wrapper vs code):**
-
-| Install target | Agentic CLI (`run`, `chat`, `code`, …) | Bot/gateway (`bot`, `gateway`, `pairing`, …) |
-|----------------|----------------------------------------|---------------------------------------------|
-| `pip install praisonai` | Yes (via `praisonai-code` dep + shims) | Yes |
-| `pip install praisonai-code` only | Yes — agentic hot path (`run`, `chat`, `code`, warm runtime) without wrapper import | No — wrapper-only commands hidden when `praisonai` absent |
-
-**C7 (hot path complete):** Core agentic CLI imports no longer require the `praisonai`
-wrapper at module level. Remaining lazy wrapper imports (~211, regression-gated) are optional commands
-and features (train, capabilities, bots, framework adapters) — use
-`praisonai_code._wrapper_bridge` or `pip install praisonai`. See
-`src/praisonai/tests/C7_VERIFICATION.md`. CI gate: `scripts/check_c7_imports.sh`.
-
-### 2.4 Package ownership (C7.1)
-
-| Tier | Package | Owns |
-|------|---------|------|
-| 1 | `praisonaiagents` | Agent, tools, memory, hooks, `frameworks/` protocols |
-| 2 | `praisonai-code` | `run`/`chat`/`code`, Typer, runtime, llm, tool resolution |
-| 3 | `praisonai` | Gateway, bots, `framework_adapters/`, capabilities, train, serve orchestration |
-
-**Cross-tier rule:** `praisonai-code` must not declare a PyPI dependency on `praisonai`. Use
-[`praisonai_code._wrapper_bridge`](../praisonai-code/praisonai_code/_wrapper_bridge.py) for lazy wrapper access.
-
-**framework_adapters:** protocols in SDK; registry + CrewAI/AutoGen/PraisonAI bodies stay in
-[`praisonai/framework_adapters/`](../praisonai/praisonai/framework_adapters/). Do not move to `praisonai-code`.
-
-**Typer `_WRAPPER_COMMANDS`:** only for commands whose implementation lives in the wrapper
-(`bot`, `gateway`, `pairing`, `identity`, `onboard`, `kanban`, `dashboard`, `claw`). Commands
-implemented in `praisonai_code` (`train`, `serve`) stay local; bridge internal wrapper imports.
-
-Full boundary doc: [`src/praisonai/tests/C7.1_BOUNDARIES.md`](../praisonai/tests/C7.1_BOUNDARIES.md).
-
 ---
 
 ## 3. Core SDK Architecture (praisonaiagents)
@@ -302,14 +178,15 @@ mongodb = ["pymongo>=4.6.3", "motor>=3.4.0"]
 ### 4.1 Protocol-Driven Core (MUST)
 
 ```
-Core SDK (praisonaiagents)     praisonai-code (terminal CLI)    Wrapper (praisonai)
-━━━━━━━━━━━━━━━━━━━━━━━━━━━    ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━    ━━━━━━━━━━━━━━━━━━━
-✅ Protocols                   ✅ run/chat/code/doctor/setup      ✅ Bot/gateway CLI
-✅ Hooks                        ✅ runtime, cli_backends           ✅ Integrations
-✅ Adapters                     ✅ Typer app, moved commands       ✅ Heavy implementations
-✅ Base classes                 ✅ Depends on agents only           ✅ Optional deps
-✅ Decorators                   ❌ Must not import praisonai        ✅ UI, DB adapters
-❌ Heavy implementations        ❌ Bot/channel commands             ❌ Core logic
+Core SDK (praisonaiagents)          Wrapper (praisonai)
+━━━━━━━━━━━━━━━━━━━━━━━━━━━         ━━━━━━━━━━━━━━━━━━━
+✅ Protocols                        ✅ Heavy implementations
+✅ Hooks                            ✅ CLI commands
+✅ Adapters                         ✅ External integrations
+✅ Base classes                     ✅ Optional deps
+✅ Decorators                       ✅ UI components
+✅ Dataclasses                      ✅ Database adapters
+❌ Heavy implementations            ❌ Core logic
 ```
 
 ### 4.2 No Performance Impact (MUST)
@@ -862,12 +739,6 @@ from praisonaiagents import Workflow, Route, Parallel, Loop
 | Policy engine | `praisonaiagents/policy/engine.py` |
 | Scheduler module | `praisonaiagents/scheduler/` |
 | Schedule tools | `praisonaiagents/tools/schedule_tools.py` |
-| Agentic CLI (Typer) | `praisonai_code/cli/app.py` |
-| CLI main / run | `praisonai_code/cli/main.py` |
-| Warm runtime | `praisonai_code/runtime/` |
-| CLI backends | `praisonai_code/cli_backends/` |
-| Back-compat shims | `praisonai/cli/_shim.py`, `praisonai/cli/main.py` |
-| C5 regression tests | `praisonai/tests/unit/test_c5_backward_compat.py` |
 
 ---
 

src/praisonai-agents/DOCS_PARITY.md

@@ -1,6 +1,6 @@
 # Documentation Parity Tracker (Python)
 
-> **Categories:** 66 | **Documented:** 66 | **Parity:** 100.0%
+> **Categories:** 66 | **Documented:** 65 | **Parity:** 98.5%
 
 This report compares **Python SDK feature categories** against **Python documentation** (docs/concepts, docs/features, etc.).
 
@@ -9,86 +9,85 @@ This report compares **Python SDK feature categories** against **Python document
 | Metric | Count |
 |--------|-------|
 | Feature Categories | 66 |
-| **Documented Categories** | **66** |
-| **Undocumented Categories** | **0** |
-| **Parity** | **100.0%** |
+| **Documented Categories** | **65** |
+| **Undocumented Categories** | **1** |
+| **Parity** | **98.5%** |
 
 ## Documented Categories
 
 | Category | Features | Docs | Lines |
 |----------|----------|------|-------|
 | ✅ AGUI | 1 | 2 | 420 |
-| ✅ Agent | 21 | 43 | 12014 |
-| ✅ Agent-to-Agent (A2A) | 1 | 7 | 2951 |
-| ✅ Agent-to-User (A2U) | 1 | 3 | 585 |
-| ✅ Approval | 1 | 5 | 2106 |
-| ✅ Audio | 2 | 10 | 658 |
-| ✅ Auto Generation | 5 | 7 | 2046 |
-| ✅ Autonomy | 3 | 6 | 2163 |
-| ✅ Bots | 7 | 24 | 8599 |
+| ✅ Agent | 21 | 42 | 11340 |
+| ✅ Agent-to-Agent (A2A) | 1 | 7 | 2880 |
+| ✅ Agent-to-User (A2U) | 1 | 3 | 575 |
+| ✅ Approval | 1 | 3 | 1344 |
+| ✅ Audio | 2 | 10 | 649 |
+| ✅ Auto Generation | 5 | 6 | 1637 |
+| ✅ Autonomy | 3 | 5 | 1919 |
+| ✅ Bots | 7 | 23 | 7714 |
 | ✅ Budget | 1 | 1 | 287 |
-| ✅ CLI | 5 | 111 | 28360 |
-| ✅ Chunking | 2 | 2 | 372 |
+| ✅ CLI | 5 | 108 | 26975 |
+| ✅ Chunking | 2 | 2 | 288 |
 | ✅ Citations | 2 | 1 | 202 |
-| ✅ Code Execution | 2 | 13 | 3752 |
-| ✅ Conditions | 1 | 3 | 1124 |
-| ✅ Configuration | 3 | 7 | 2299 |
-| ✅ Context Management | 16 | 33 | 11478 |
-| ✅ Database | 1 | 40 | 5744 |
-| ✅ Deep Research | 8 | 2 | 497 |
-| ✅ Display | 6 | 3 | 648 |
-| ✅ Embeddings | 6 | 23 | 1990 |
-| ✅ Evaluation | 1 | 6 | 2511 |
-| ✅ Events | 1 | 2 | 735 |
-| ✅ Execution | 3 | 4 | 1455 |
-| ✅ Failover | 2 | 1 | 400 |
-| ✅ Files | 2 | 6 | 1845 |
-| ✅ Flow | 1 | 3 | 777 |
-| ✅ Gateway | 7 | 36 | 13110 |
-| ✅ Guardrails | 4 | 4 | 1642 |
-| ✅ Handoffs | 11 | 6 | 2654 |
-| ✅ Hooks | 2 | 9 | 3564 |
-| ✅ Image | 1 | 11 | 1113 |
-| ✅ Knowledge | 4 | 12 | 3658 |
-| ✅ LLM | 3 | 12 | 4292 |
-| ✅ Loops | 4 | 3 | 797 |
-| ✅ MCP | 1 | 52 | 11155 |
-| ✅ Memory | 6 | 17 | 6141 |
-| ✅ OCR | 2 | 1 | 237 |
-| ✅ Observability | 2 | 23 | 2768 |
-| ✅ Optimizer | 1 | 2 | 750 |
-| ✅ Output | 3 | 5 | 1102 |
-| ✅ Parallel Execution | 3 | 2 | 392 |
-| ✅ Planning | 6 | 6 | 1418 |
-| ✅ Plugins | 8 | 3 | 994 |
-| ✅ Prompts | 2 | 7 | 1201 |
-| ✅ Providers | 1 | 54 | 7047 |
-| ✅ Query | 1 | 2 | 623 |
-| ✅ RAG | 5 | 15 | 2891 |
+| ✅ Code Execution | 2 | 13 | 3554 |
+| ✅ Conditions | 1 | 3 | 1085 |
+| ✅ Configuration | 3 | 7 | 2160 |
+| ✅ Context Management | 16 | 33 | 10280 |
+| ✅ Database | 1 | 40 | 5373 |
+| ✅ Deep Research | 8 | 2 | 437 |
+| ✅ Display | 6 | 2 | 1175 |
+| ✅ Embeddings | 6 | 23 | 1966 |
+| ✅ Evaluation | 1 | 6 | 2539 |
+| ✅ Events | 1 | 2 | 764 |
+| ✅ Execution | 3 | 3 | 1099 |
+| ✅ Failover | 2 | 1 | 372 |
+| ✅ Files | 2 | 6 | 1632 |
+| ✅ Flow | 1 | 2 | 435 |
+| ✅ Gateway | 7 | 21 | 7477 |
+| ✅ Guardrails | 4 | 4 | 1619 |
+| ✅ Handoffs | 11 | 6 | 2499 |
+| ✅ Hooks | 2 | 8 | 3150 |
+| ✅ Image | 1 | 11 | 1096 |
+| ✅ Knowledge | 4 | 24 | 4525 |
+| ✅ LLM | 3 | 10 | 3674 |
+| ✅ Loops | 4 | 3 | 774 |
+| ✅ MCP | 1 | 51 | 10939 |
+| ✅ Memory | 6 | 16 | 5879 |
+| ✅ OCR | 2 | 1 | 226 |
+| ✅ Observability | 2 | 23 | 2754 |
+| ✅ Optimizer | 1 | 2 | 653 |
+| ✅ Output | 3 | 4 | 860 |
+| ✅ Parallel Execution | 3 | 2 | 399 |
+| ✅ Planning | 6 | 5 | 1198 |
+| ✅ Plugins | 8 | 3 | 1502 |
+| ✅ Prompts | 2 | 7 | 1569 |
+| ✅ Providers | 1 | 52 | 6214 |
+| ✅ Query | 1 | 2 | 616 |
+| ✅ RAG | 5 | 15 | 3193 |
 | ✅ Realtime | 2 | 5 | 584 |
-| ✅ Reflection | 3 | 3 | 665 |
-| ✅ Retrieval | 2 | 5 | 915 |
-| ✅ Routing | 1 | 2 | 390 |
-| ✅ Sandbox | 5 | 6 | 2464 |
-| ✅ Security | 1 | 3 | 2775 |
-| ✅ Sessions | 4 | 12 | 4292 |
-| ✅ Skills | 6 | 13 | 4856 |
-| ✅ Tasks | 2 | 6 | 2715 |
-| ✅ Telemetry | 1 | 2 | 576 |
-| ✅ Templates | 1 | 8 | 1657 |
-| ✅ Tools | 12 | 125 | 31358 |
+| ✅ Reflection | 3 | 2 | 477 |
+| ✅ Retrieval | 2 | 5 | 945 |
+| ✅ Routing | 1 | 2 | 597 |
+| ✅ Sandbox | 5 | 6 | 2512 |
+| ✅ Security | 1 | 3 | 2563 |
+| ✅ Sessions | 4 | 12 | 3793 |
+| ✅ Skills | 6 | 10 | 3663 |
+| ✅ Tasks | 2 | 6 | 3064 |
+| ✅ Telemetry | 1 | 2 | 560 |
+| ✅ Templates | 1 | 7 | 1411 |
+| ✅ Tools | 12 | 118 | 25895 |
 | ✅ Tracing | 3 | 2 | 139 |
-| ✅ Vector Store | 1 | 12 | 1139 |
 | ✅ Video | 2 | 6 | 510 |
 | ✅ Vision | 2 | 1 | 283 |
-| ✅ Web | 3 | 8 | 1910 |
-| ✅ Workflows | 5 | 16 | 6764 |
+| ✅ Web | 3 | 7 | 1537 |
+| ✅ Workflows | 4 | 14 | 5893 |
 
-## Documentation Without Features
+## Undocumented Categories (Need Documentation)
 
-These docs exist but don't match any implemented feature category:
-
-- ℹ️ Documents (1 docs, 787 lines)
+| Category | Features |
+|----------|----------|
+| ❌ Vector Store | 1 |
 
 ---
 

src/praisonai-agents/praisonaiagents/__init__.py

@@ -183,7 +183,6 @@ _LAZY_IMPORTS = {
     'Include': ('praisonaiagents.workflows', 'Include'),
     'MAX_NESTING_DEPTH': ('praisonaiagents.workflows', 'MAX_NESTING_DEPTH'),
     'YAMLWorkflowParser': ('praisonaiagents.workflows', 'YAMLWorkflowParser'),
-    'WorkflowHooksConfig': ('praisonaiagents.workflows', 'WorkflowHooksConfig'),
     
     # Conditions (Protocol-driven condition evaluation)
     'ConditionProtocol': ('praisonaiagents.conditions.protocols', 'ConditionProtocol'),
@@ -534,10 +533,6 @@ _LAZY_IMPORTS = {
     
     # Managed backend protocol (implementation + config in praisonai wrapper)
     'ManagedBackendProtocol': ('praisonaiagents.agent.protocols', 'ManagedBackendProtocol'),
-
-    # Framework adapter protocol (implementations in praisonai wrapper / praisonai-frameworks)
-    'FrameworkAdapterProtocol': ('praisonaiagents.frameworks.protocols', 'FrameworkAdapterProtocol'),
-    'BaseFrameworkAdapter': ('praisonaiagents.frameworks.base', 'BaseFrameworkAdapter'),
     
     # Managed agent events (provider-agnostic)
     'ManagedEvent': ('praisonaiagents.managed.events', 'ManagedEvent'),

src/praisonai-agents/praisonaiagents/agent/agent.py

@@ -261,44 +261,13 @@ class Agent(SteeringMixin, SandboxMixin, SkillReviewMixin, UnifiedExecutionMixin
                     cls._env_output_checked = True
         return cls._env_output_mode
     
-    # Ordered (credential env-var, provider-appropriate default model). The
-    # first provider whose credential is present wins. OpenAI is first so
-    # existing OpenAI users keep their default; any other single configured
-    # provider yields a matching default instead of a failing OpenAI default.
-    _PROVIDER_DEFAULT_MODELS = (
-        ("OPENAI_API_KEY", "gpt-4o-mini"),
-        ("ANTHROPIC_API_KEY", "anthropic/claude-3-5-sonnet-latest"),
-        ("GEMINI_API_KEY", "gemini/gemini-1.5-flash"),
-        ("GOOGLE_API_KEY", "google/gemini-1.5-flash"),
-        ("GROQ_API_KEY", "groq/llama-3.3-70b-versatile"),
-        ("COHERE_API_KEY", "cohere/command-r"),
-        ("OLLAMA_HOST", "ollama/llama3.2"),
-    )
-
-    @classmethod
-    def _resolve_default_model(cls):
-        """Resolve a provider-aware default model from present credentials.
-
-        Precedence: ``OPENAI_MODEL_NAME`` (backward compatible) > first
-        provider whose credential env var is set > hardcoded ``gpt-4o-mini``.
-        Keeps core free of provider-detection policy beyond a simple env scan;
-        the wrapper layer owns recency state and first-run notices.
-        """
-        explicit = os.getenv('OPENAI_MODEL_NAME')
-        if explicit:
-            return explicit
-        for key_var, model in cls._PROVIDER_DEFAULT_MODELS:
-            if os.environ.get(key_var):
-                return model
-        return 'gpt-4o-mini'
-
     @classmethod
     def _get_default_model(cls):
-        """Get cached provider-aware default model name (thread-safe)."""
+        """Get cached default model name from OPENAI_MODEL_NAME env var (thread-safe)."""
         if not cls._default_model_checked:
             with cls._env_cache_lock:
                 if not cls._default_model_checked:
-                    cls._default_model = cls._resolve_default_model()
+                    cls._default_model = os.getenv('OPENAI_MODEL_NAME', 'gpt-4o-mini')
                     cls._default_model_checked = True
         return cls._default_model
     
@@ -306,22 +275,6 @@ class Agent(SteeringMixin, SandboxMixin, SkillReviewMixin, UnifiedExecutionMixin
         """Lazy-create LLM instance from deferred init params (avoids import at Agent())."""
         if self._llm_instance is not None:
             return self._llm_instance
-        if self._panel_descriptor is not None:
-            try:
-                from ..llm.panel import create_panel_llm
-                # Forward the same Agent-level connection/execution settings a
-                # normal model selection preserves (base_url, api_key, auth,
-                # metrics, max_iter, web_search, web_fetch, prompt_caching,
-                # claude_memory) so the panel aggregator behaves identically.
-                self._llm_instance = create_panel_llm(
-                    self._panel_descriptor, **self._panel_llm_kwargs
-                )
-            except ImportError as e:
-                raise ImportError(
-                    "LLM features requested but dependencies not installed. "
-                    "Please install with: pip install \"praisonaiagents[llm]\""
-                ) from e
-            return self._llm_instance
         if self._llm_init_params:
             try:
                 from ..llm.llm import LLM
@@ -1594,8 +1547,6 @@ class Agent(SteeringMixin, SandboxMixin, SkillReviewMixin, UnifiedExecutionMixin
         self._using_custom_llm = False
         self._llm_instance = None
         self._llm_init_params = None
-        self._panel_descriptor = None
-        self._panel_llm_kwargs = {}
         # Flag to track if final result has been displayed to prevent duplicates
         self._final_display_shown = False
         
@@ -1663,38 +1614,8 @@ class Agent(SteeringMixin, SandboxMixin, SkillReviewMixin, UnifiedExecutionMixin
         self.base_url = base_url
         self.api_key = api_key
 
-        # Panel (multi-model) descriptor: "panel:<name>" or {"provider": "panel"}.
-        # Resolved lazily into a PanelLLM; composes with the normal tool loop.
-        # Detected inline (no heavy import) to keep Agent() construction lazy.
-        _is_panel = (
-            (isinstance(llm, str) and llm.startswith("panel:"))
-            or (isinstance(llm, dict) and llm.get("provider") == "panel")
-        )
-        if _is_panel:
-            self._panel_descriptor = llm
-            self._using_custom_llm = True
-            self.llm = llm if isinstance(llm, str) else "panel"
-            # Capture the same connection/execution options the normal LLM paths
-            # forward, so the panel aggregator (and references) behave identically
-            # to a regular model selection. Stored now because some (e.g. auth)
-            # are not retained as Agent attributes.
-            self._panel_llm_kwargs = {
-                k: v
-                for k, v in (
-                    ("base_url", base_url),
-                    ("api_key", api_key),
-                    ("auth", auth),
-                    ("metrics", metrics),
-                    ("max_iter", max_iter),
-                    ("web_search", web_search),
-                    ("web_fetch", web_fetch),
-                    ("prompt_caching", prompt_caching),
-                    ("claude_memory", claude_memory),
-                )
-                if v is not None
-            }
         # If base_url is provided, defer custom LLM instance creation
-        elif base_url:
+        if base_url:
             if isinstance(llm, dict):
                 llm_config = llm.copy()
                 llm_config['base_url'] = base_url
@@ -1984,8 +1905,7 @@ Your Goal: {self.goal}
             # export PRAISONAI_TOOL_SAFETY=off. This adds zero Agent kwargs.
             _raw_safety_env = os.environ.get("PRAISONAI_TOOL_SAFETY")
             _safety_env = (_raw_safety_env or "").strip().lower()
-            _bypass_safety = _safety_env in ("off", "full", "none", "0", "false")
-            if not _bypass_safety:
+            if _safety_env not in ("off", "full", "none", "0", "false"):
                 from ..approval.registry import PERMISSION_PRESETS
                 _resolved_safety_env = _safety_env or "default"
                 _preset_deny = PERMISSION_PRESETS.get(_resolved_safety_env)
@@ -2000,27 +1920,7 @@ Your Goal: {self.goal}
                     )
                     _resolved_safety_env = "default"
                     _preset_deny = PERMISSION_PRESETS.get(_resolved_safety_env)
-
-                # Safe-by-default ask: when no approval kwarg was supplied
-                # (``approval is None``) and we are attached to an interactive
-                # terminal, route dangerous built-in tools (shell exec, file
-                # writes, etc.) through an interactive approval prompt instead
-                # of silently hard-denying them. This makes a fresh, un-flagged
-                # agent safe *and* usable — the user is asked once per dangerous
-                # call and can allow/deny.
-                #
-                # In non-interactive contexts (pipes, CI) — or when the user
-                # explicitly passed ``approval=False`` to opt out of prompting —
-                # we keep the existing deny-by-default preset so dangerous tools
-                # never execute unattended without an explicit policy. The full
-                # bypass remains ``PRAISONAI_TOOL_SAFETY=off`` / ``approval="bypass"``.
-                if approval is None and self._is_interactive_session():
-                    from ..approval.backends import ConsoleBackend
-                    self._approval_backend = ConsoleBackend()
-                    # Leave _perm_deny empty so dangerous tools reach the backend
-                    # (which classifies them via DEFAULT_DANGEROUS_TOOLS) and the
-                    # user is prompted to allow/deny rather than auto-denied.
-                elif _preset_deny is not None:
+                if _preset_deny is not None:
                     self._perm_deny = _preset_deny
         elif isinstance(approval, ApprovalConfig):
             self._approval_backend = approval.backend
@@ -2717,40 +2617,10 @@ Summary:"""
             from ..skills import SkillManager
             self._skill_manager = SkillManager()
 
-            # Discover bundles so '@bundle' selectors in self._skills can be
-            # expanded into their member skill names before injection. Honour
-            # the configured discovery scope: only fall back to default skill
-            # dirs when auto_discover is enabled or no explicit dirs are set.
-            try:
-                self._skill_manager.discover_bundles(
-                    self._skills_dirs,
-                    include_defaults=auto_discover or not self._skills_dirs,
-                )
-            except Exception as e:  # noqa: BLE001 - bundles are optional
-                logging.debug("Bundle discovery skipped: %s", e)
-
-            # Add explicit skill selectors. '@bundle' entries expand to their
-            # member skill names (resolved by name against discovered skills);
-            # plain paths pass through unchanged and load directly. Member
-            # discovery honours the configured scope (only fall back to default
-            # skill dirs when auto_discover is on), and a missing member is
-            # logged so a typo'd bundle entry is not silently dropped.
+            # Add explicit skill paths
             if self._skills:
-                from ..skills.bundles import is_bundle_selector
-                for selector in self._skills:
-                    if is_bundle_selector(selector):
-                        for member in self._skill_manager.resolve([selector]):
-                            loaded = self._skill_manager.add_skill_by_name(
-                                member, self._skills_dirs,
-                                include_defaults=auto_discover,
-                            )
-                            if loaded is None:
-                                logging.warning(
-                                    "Skill bundle member '%s' (from '%s') not "
-                                    "found; skipping.", member, selector,
-                                )
-                    else:
-                        self._skill_manager.add_skill(selector)
+                for skill_path in self._skills:
+                    self._skill_manager.add_skill(skill_path)
 
             # Discover skills from directories; honour SkillsConfig.auto_discover
             # by falling back to default locations when requested.
@@ -4197,6 +4067,77 @@ Summary:"""
     #                     Runtime Capability Management
     # -------------------------------------------------------------------------
     
+    def _resolve_runtime_config(self, runtime):
+        """Resolve runtime configuration parameter.
+        
+        Args:
+            runtime: Runtime parameter (bool, str, dict, or RuntimeConfig)
+            
+        Returns:
+            RuntimeConfig instance or None
+        """
+        try:
+            from ..config import resolve_runtime
+            return resolve_runtime(runtime)
+        except ImportError:
+            raise ImportError(
+                "Runtime capability features requested but configuration not available. "
+                "This should not happen in a properly installed praisonaiagents package."
+            )
+    
+    def _validate_runtime_capabilities(self):
+        """Validate that current runtime supports required capabilities.
+        
+        Performs fail-fast validation of runtime capabilities against
+        agent requirements at config/creation time.
+        
+        Raises:
+            CapabilityValidationError: If validation fails
+        """
+        if not self._runtime_config or not self._runtime_config.required_capabilities:
+            return  # No requirements to validate
+        
+        try:
+            from ..runtime import RuntimeCapability, validate_capabilities, get_native_runtime_capabilities
+            
+            # Convert string capability names to enum values
+            required_set = set()
+            for cap in self._runtime_config.required_capabilities:
+                if isinstance(cap, str):
+                    # Convert string to enum value
+                    cap_upper = cap.upper()
+                    if hasattr(RuntimeCapability, cap_upper):
+                        required_set.add(getattr(RuntimeCapability, cap_upper))
+                    else:
+                        raise ValueError(f"Unknown capability: {cap}")
+                else:
+                    # Assume it's already a RuntimeCapability enum
+                    required_set.add(cap)
+            
+            # Get the actual runtime capabilities based on the selected runtime
+            runtime_name = self._runtime_config.preferred_runtime or "native"
+            
+            # Determine which capability matrix to use based on runtime type
+            if runtime_name in ["native", "praisonai"]:
+                runtime_matrix = get_native_runtime_capabilities()
+            elif runtime_name in ["plugin", "harness", "reduced", "plugin-harness", "claude-code"]:
+                # Use reduced capabilities for plugin/harness runtimes
+                from praisonaiagents.runtime.capabilities import get_reduced_harness_capabilities
+                runtime_matrix = get_reduced_harness_capabilities()
+            else:
+                # For unknown runtimes, use reduced capabilities as safe default
+                from praisonaiagents.runtime.capabilities import get_reduced_harness_capabilities
+                runtime_matrix = get_reduced_harness_capabilities()
+            
+            # Perform validation
+            validate_capabilities(runtime_matrix, required_set, runtime_name)
+            
+        except ImportError:
+            raise ImportError(
+                "Runtime capability validation requested but runtime module not available. "
+                "This should not happen in a properly installed praisonaiagents package."
+            )
+    
     def _run_verification_hooks(self) -> List[Dict[str, Any]]:
         """Run all registered verification hooks.
         
@@ -5111,22 +5052,6 @@ Answer:"""
         except Exception as e:
             logging.error(f"Error processing knowledge item: {knowledge_item}, error: {e}")
 
-    @staticmethod
-    def _is_interactive_session() -> bool:
-        """Return True when running attached to an interactive terminal.
-
-        Used to decide whether dangerous built-in tools should be routed
-        through an interactive approval prompt (safe-by-default ``ask``) or
-        hard-denied (non-interactive deny-by-default). A session counts as
-        interactive only when both stdin and stdout are TTYs, so pipes, CI
-        runners and redirected I/O fall back to the deny-by-default policy.
-        """
-        try:
-            import sys
-            return bool(sys.stdin.isatty() and sys.stdout.isatty())
-        except Exception:
-            return False
-
     def _setup_guardrail(self):
         """Setup the guardrail function based on the provided guardrail parameter."""
         if self.guardrail is None:

src/praisonai-agents/praisonaiagents/agent/chat_handler.py

@@ -6,15 +6,113 @@ Extracted from agent.py for better modularity and maintainability.
 """
 
 import logging
+import time
+from typing import Optional, Any, Dict, List, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    pass
 
 logger = logging.getLogger(__name__)
 
 
 class ChatHandlerMixin:
-    """Mixin reserved for chat coordination on the Agent class.
-
-    This is a documented placeholder retained for the public mixin surface.
-    Concrete chat logic (``chat``/``achat``, history management, and response
-    processing) lives in ``ChatMixin``/``SessionManagerMixin``.
+    """Mixin providing chat handling methods for the Agent class.
+    
+    This mixin focuses on high-level chat coordination and response processing,
+    while the actual LLM interaction is handled by ChatMixin.
     """
-    pass
+    
+    def _format_chat_response(self, response: str, metadata: Optional[Dict[str, Any]] = None) -> str:
+        """Format chat response with any necessary post-processing.
+        
+        Args:
+            response: Raw response from the LLM
+            metadata: Optional metadata about the response
+            
+        Returns:
+            Formatted response string
+        """
+        if not response:
+            return ""
+            
+        # Basic response formatting - can be extended with additional logic
+        formatted = response.strip()
+        
+        # Add any metadata-based formatting if needed
+        if metadata and metadata.get('add_timestamp'):
+            timestamp = time.strftime('%Y-%m-%d %H:%M:%S')
+            formatted = f"[{timestamp}] {formatted}"
+            
+        return formatted
+    
+    def _validate_chat_input(self, prompt: str) -> bool:
+        """Validate chat input before processing.
+        
+        Args:
+            prompt: Input prompt to validate
+            
+        Returns:
+            True if valid, False otherwise
+        """
+        if not prompt or not isinstance(prompt, str):
+            logger.warning("Invalid chat input: prompt must be a non-empty string")
+            return False
+            
+        if len(prompt.strip()) == 0:
+            logger.warning("Invalid chat input: prompt cannot be empty or whitespace only")
+            return False
+            
+        return True
+    
+    def _prepare_chat_context(self, prompt: str, **kwargs) -> Dict[str, Any]:
+        """Prepare context for chat processing.
+        
+        Args:
+            prompt: Input prompt
+            **kwargs: Additional context parameters
+            
+        Returns:
+            Context dictionary for chat processing
+        """
+        context = {
+            'prompt': prompt,
+            'timestamp': time.time(),
+            'agent_name': getattr(self, 'name', None) or 'Agent',
+        }
+        
+        # Add any additional context from kwargs
+        context.update(kwargs)
+        
+        return context
+    
+    def _handle_chat_error(self, error: Exception, prompt: str) -> str:
+        """Handle chat processing errors gracefully.
+        
+        Args:
+            error: The exception that occurred
+            prompt: The original prompt that caused the error
+            
+        Returns:
+            Error response message
+        """
+        logger.error(f"Chat error occurred: {error}", exc_info=True)
+        
+        # Return a user-friendly error message without exposing internal details.
+        # Include a timestamp reference so users can correlate with server logs.
+        error_ref = time.strftime('%Y%m%d%H%M%S')
+        return f"I encountered an error while processing your request (ref: {error_ref}). Please try again."
+    
+    def _log_chat_interaction(self, prompt: str, response: str, duration: Optional[float] = None):
+        """Log chat interaction for debugging and analytics.
+        
+        Args:
+            prompt: Input prompt
+            response: Generated response  
+            duration: Processing duration in seconds
+        """
+        agent_name = getattr(self, 'name', None) or 'Agent'
+        duration_str = f" (took {duration:.2f}s)" if duration else ""
+        
+        logger.debug(f"[{agent_name}] Chat interaction{duration_str}")
+        logger.debug(f"[{agent_name}] Prompt: {prompt[:100]}{'...' if len(prompt) > 100 else ''}")
+        logger.debug(f"[{agent_name}] Response: {response[:100]}{'...' if len(response) > 100 else ''}")

src/praisonai-agents/praisonaiagents/agent/chat_mixin.py

@@ -192,10 +192,6 @@ Your Goal: {self.goal}"""
                     logging.warning(f"Could not extract tool name from {tool}: {e}")
                     continue
             
-            # Prune permission-denied tool names so the advertised surface in the
-            # system prompt matches the function schema (and execution-time rules).
-            tool_names = [n for n in tool_names if self._tool_name_allowed(n)]
-
             if tool_names:
                 system_prompt += f"\n\nYou have access to the following tools: {', '.join(tool_names)}. Use these tools when appropriate to help complete your tasks. Always use tools when they can help provide accurate information or perform actions."
                 system_prompt += "\n\nExplain Before Acting: Before calling a tool, provide a brief one-sentence explanation of what you are about to do and why. Skip explanations only for repetitive low-level operations where narration would be noisy. When performing a batch of similar operations (e.g. searching for multiple items), explain the group once rather than narrating each call individually."
@@ -524,12 +520,6 @@ Your Goal: {self.goal}"""
         
         cleaned_tools = sort_formatted_tools(cleaned_tools)
         
-        # Prune permission-denied tools from the advertised set so the model is
-        # only ever offered tools it can actually call. Mirrors the execution-time
-        # enforcement in tool_execution.py (_perm_deny / _perm_allow). No-op when
-        # no deny set and no allow set are configured (backward compatible).
-        cleaned_tools = self._prune_denied_tools(cleaned_tools)
-        
         # Cache the formatted tools with LRU eviction, including tool search metadata
         self._cache_put(
             self._formatted_tools_cache,
@@ -538,126 +528,6 @@ Your Goal: {self.goal}"""
         )
         return cleaned_tools
 
-    def _build_before_tool_definitions_input(self, formatted_tools):
-        """Build the BEFORE_TOOL_DEFINITIONS hook input.
-
-        A deep copy of ``formatted_tools`` is used so that in-place hook
-        mutations never leak back into ``_format_tools_for_completion``'s cache
-        and corrupt subsequent requests.
-        """
-        import copy
-        from ..hooks import HookEvent, BeforeToolDefinitionsInput
-        return BeforeToolDefinitionsInput(
-            session_id=getattr(self, '_session_id', 'default'),
-            cwd=os.getcwd(),
-            event_name=HookEvent.BEFORE_TOOL_DEFINITIONS,
-            timestamp=str(time.time()),
-            agent_name=self.name,
-            model=self.llm if isinstance(self.llm, str) else str(self.llm),
-            tool_definitions=copy.deepcopy(formatted_tools),
-        )
-
-    def _apply_before_tool_definitions_hook(self, formatted_tools):
-        """Fire the BEFORE_TOOL_DEFINITIONS hook so hooks/plugins can inspect or
-        rewrite the advertised tool definitions before they reach the LLM.
-
-        Mirrors how BEFORE_LLM lets a hook mutate its payload in place. No-op
-        (returns the input unchanged) when no hook runner or no tools exist.
-        Returns the possibly-mutated list of tool definitions. Synchronous
-        path; use ``_aapply_before_tool_definitions_hook`` in async contexts.
-        """
-        if not formatted_tools or not getattr(self, '_hook_runner', None):
-            return formatted_tools
-        try:
-            from ..hooks import HookEvent
-            _inp = self._build_before_tool_definitions_input(formatted_tools)
-            self._hook_runner.execute_sync(HookEvent.BEFORE_TOOL_DEFINITIONS, _inp)
-            # Adopt mutations, mirroring how BEFORE_LLM adopts its payload.
-            return _inp.tool_definitions
-        except Exception as _e:
-            logging.debug(f"[before-tool-definitions] hook skipped: {_e}")
-            return formatted_tools
-
-    async def _aapply_before_tool_definitions_hook(self, formatted_tools):
-        """Async variant of ``_apply_before_tool_definitions_hook``.
-
-        ``execute_sync`` raises inside a running event loop, so the async chat
-        path must await the hook runner directly to actually run the hook.
-        """
-        if not formatted_tools or not getattr(self, '_hook_runner', None):
-            return formatted_tools
-        try:
-            from ..hooks import HookEvent
-            _inp = self._build_before_tool_definitions_input(formatted_tools)
-            await self._hook_runner.execute(HookEvent.BEFORE_TOOL_DEFINITIONS, _inp)
-            return _inp.tool_definitions
-        except Exception as _e:
-            logging.debug(f"[before-tool-definitions] async hook skipped: {_e}")
-            return formatted_tools
-
-    def _prune_denied_tools(self, formatted_tools):
-        """Remove tools whose permission resolves to ``deny`` from the payload.
-
-        The advertised tool surface is shaped by the agent's effective
-        permission tier (resolved at ``__init__`` into ``_perm_deny`` /
-        ``_perm_allow``) so the model is never offered a tool it cannot call.
-        ``ask``/``allow`` tools stay advertised — approval still happens at
-        execution time (defence in depth). This is a no-op when no ``deny`` set
-        and no ``allow`` set are configured, preserving backward compatibility.
-
-        Args:
-            formatted_tools: List of OpenAI-schema tool definitions.
-
-        Returns:
-            The filtered list (a new list only when something is pruned).
-        """
-        if not formatted_tools:
-            return formatted_tools
-
-        perm_deny = getattr(self, "_perm_deny", None)
-        perm_allow = getattr(self, "_perm_allow", None)
-
-        # Fast path: no permission shaping configured -> advertise everything.
-        if not perm_deny and perm_allow is None:
-            return formatted_tools
-
-        def _tool_id(tool):
-            if isinstance(tool, dict) and tool.get("type") == "function":
-                return str(tool.get("function", {}).get("name") or "")
-            return ""
-
-        pruned = []
-        for tool in formatted_tools:
-            name = _tool_id(tool)
-            if not name:
-                # Keep unrecognized schemas as-is; cannot evaluate permission.
-                pruned.append(tool)
-                continue
-            if not self._tool_name_allowed(name):
-                logging.debug("Pruning permission-denied tool from payload: %s", name)
-                continue
-            pruned.append(tool)
-        return pruned
-
-    def _tool_name_allowed(self, name):
-        """Return ``True`` if ``name`` is callable under the agent's permissions.
-
-        Mirrors the execution-time enforcement in ``tool_execution.py``
-        (``_perm_deny`` / ``_perm_allow``): a tool is denied if it is in the
-        deny set or, when an allow set is configured, absent from it.
-        ``ask``/``allow`` tools remain callable (approval happens at execution
-        time). No-op (always allowed) when no permission shaping is configured.
-        """
-        if not name:
-            return True
-        perm_deny = getattr(self, "_perm_deny", None)
-        perm_allow = getattr(self, "_perm_allow", None)
-        if perm_deny and name in perm_deny:
-            return False
-        if perm_allow is not None and name not in perm_allow:
-            return False
-        return True
-
     def _build_multimodal_prompt(
         self, 
         prompt: str, 
@@ -1116,17 +986,14 @@ Your Goal: {self.goal}"""
 
         # Use the new _format_tools_for_completion helper method
         formatted_tools = self._format_tools_for_completion(tools)
-        # Let hooks/plugins inspect or rewrite advertised tool definitions
-        formatted_tools = self._apply_before_tool_definitions_hook(formatted_tools)
 
         # Smart fallback for streaming: try streaming first, fall back to non-streaming if unsupported
-        streaming_response = None
         if stream is None:
             # Auto-detect: prefer streaming for better UX, fallback if adapter doesn't support it
             try:
                 # First attempt: try with streaming enabled for better user experience
                 stream_callback = self.stream_emitter.emit if hasattr(self, 'stream_emitter') else None
-                streaming_response = self._chat_completion_with_retry(
+                final_response = self._chat_completion_with_retry(
                     messages=messages,
                     temperature=temperature,
                     tools=formatted_tools,
@@ -1139,6 +1006,7 @@ Your Goal: {self.goal}"""
                     stream_callback=stream_callback,
                     emit_events=True
                 )
+                return final_response
             except ValueError as e:
                 if "Streaming is not supported" in str(e):
                     # Fallback: retry with non-streaming for sync adapters
@@ -1161,22 +1029,19 @@ Your Goal: {self.goal}"""
             # UNIFIED: Single protocol-driven dispatch path (fixes DRY violation)
             # All LLM providers now go through unified dispatcher for consistency and maintainability
             stream_callback = self.stream_emitter.emit if hasattr(self, 'stream_emitter') else None
-            if streaming_response is not None:
-                final_response = streaming_response
-            else:
-                final_response = self._chat_completion_with_retry(
-                    messages=messages,
-                    temperature=temperature,
-                    tools=formatted_tools,
-                    stream=stream,
-                    reasoning_steps=reasoning_steps,
-                    task_name=task_name,
-                    task_description=task_description,
-                    task_id=task_id,
-                    response_format=response_format,
-                    stream_callback=stream_callback,
-                    emit_events=True,
-                )
+            final_response = self._chat_completion_with_retry(
+                messages=messages,
+                temperature=temperature,
+                tools=formatted_tools,
+                stream=stream,
+                reasoning_steps=reasoning_steps,
+                task_name=task_name,
+                task_description=task_description,
+                task_id=task_id,
+                response_format=response_format,
+                stream_callback=stream_callback,
+                emit_events=True,
+            )
 
             # Emit LLM response trace event with token usage
             _duration_ms = (time.time() - start_time) * 1000
@@ -1733,26 +1598,6 @@ Your Goal: {self.goal}"""
             
             # Cache the dispatcher
             self._unified_dispatcher = dispatcher
-
-        # Pre-call budget guard (parity with sync _chat_completion). Bots and
-        # other async callers route through here, not _chat_completion.
-        if self._max_budget and self._on_budget_exceeded == "stop":
-            _est_min_cost = self._estimate_min_call_cost(
-                messages, getattr(self, 'max_tokens', None)
-            )
-            with self._cost_lock:
-                _projected_cost = self._total_cost + _est_min_cost
-                _current_cost = self._total_cost
-            if _projected_cost >= self._max_budget:
-                raise BudgetExceededError(
-                    f"Agent '{self.name}' would exceed budget before call: "
-                    f"${_current_cost:.4f} + est ${_est_min_cost:.4f} >= "
-                    f"${self._max_budget:.4f}",
-                    budget_type="cost",
-                    limit=self._max_budget,
-                    used=_current_cost,
-                    agent_id=self.name
-                )
         
         # Execute unified async dispatch with all necessary parameters
         # Includes all parameters from both legacy paths to ensure full compatibility
@@ -1794,47 +1639,8 @@ Your Goal: {self.goal}"""
                     or None
                 ),
             )
-
-            # Post-call budget accounting (parity with sync _chat_completion).
-            _prompt_tokens = 0
-            _completion_tokens = 0
-            _cost_usd = 0.0
-            if final_response:
-                _usage = getattr(final_response, 'usage', None)
-                if _usage:
-                    _prompt_tokens = getattr(_usage, 'prompt_tokens', 0) or 0
-                    _completion_tokens = getattr(_usage, 'completion_tokens', 0) or 0
-                    _cost_usd = self._calculate_llm_cost(
-                        _prompt_tokens, _completion_tokens, response=final_response
-                    )
-            with self._cost_lock:
-                self._total_cost += _cost_usd
-                self._total_tokens_in += _prompt_tokens
-                self._total_tokens_out += _completion_tokens
-                self._llm_call_count += 1
-                budget_exceeded = self._max_budget and self._total_cost >= self._max_budget
-                current_cost = self._total_cost
-            if budget_exceeded:
-                if self._on_budget_exceeded == "stop":
-                    raise BudgetExceededError(
-                        f"Agent '{self.name}' exceeded budget: ${current_cost:.4f} >= ${self._max_budget:.4f}",
-                        budget_type="cost",
-                        limit=self._max_budget,
-                        used=current_cost,
-                        agent_id=self.name
-                    )
-                elif self._on_budget_exceeded == "warn":
-                    logging.warning(
-                        f"[budget] {self.name}: ${current_cost:.4f} exceeded "
-                        f"${self._max_budget:.4f} budget"
-                    )
-                elif callable(self._on_budget_exceeded):
-                    self._on_budget_exceeded(current_cost, self._max_budget)
-
             return final_response
-
-        except BudgetExceededError:
-            raise
+            
         except Exception as e:
             from ..errors import LLMError
             # Apply the same structured error classification for async path
@@ -2999,8 +2805,6 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
 
                     # Use the new _format_tools_for_completion helper method
                     formatted_tools = self._format_tools_for_completion(tools)
-                    # Let hooks/plugins inspect or rewrite advertised tool definitions
-                    formatted_tools = await self._aapply_before_tool_definitions_hook(formatted_tools)
                     
                     # NEW: Unified protocol dispatch path (Issue #1304) - Async version
                     # Enable unified dispatch by default for DRY and feature parity (sync/async consistent)
@@ -3806,11 +3610,7 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                             ]
                         self._append_to_chat_history(assistant_message)
                         
-                        # Execute tool calls and add results to chat history.
-                        # Media-bearing follow-up messages are deferred until all
-                        # tool replies for this turn are appended, keeping the
-                        # tool replies consecutive (provider contract).
-                        _deferred_media_followups = []
+                        # Execute tool calls and add results to chat history
                         for tool_call in tool_calls_data:
                             if tool_call['id'] and tool_call['function']['name']:
                                 try:
@@ -3826,22 +3626,12 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                                         parsed_args,
                                         tool_call_id=tool_call.get('id')
                                     )
-                                    # Add tool result to chat history (multimodal-aware)
-                                    from .tool_execution import build_tool_result_message_pair
-                                    _pair = build_tool_result_message_pair(
-                                        tool_result, tool_call['id'],
-                                        function_name=tool_call['function']['name'],
-                                    )
-                                    if _pair:
-                                        _tool_msg, _followup_msg = _pair
-                                        self._append_to_chat_history(_tool_msg)
-                                        _deferred_media_followups.append(_followup_msg)
-                                    else:
-                                        self._append_to_chat_history({
-                                            "role": "tool",
-                                            "tool_call_id": tool_call['id'],
-                                            "content": str(tool_result)
-                                        })
+                                    # Add tool result to chat history
+                                    self._append_to_chat_history({
+                                        "role": "tool",
+                                        "tool_call_id": tool_call['id'],
+                                        "content": str(tool_result)
+                                    })
                                 except Exception as tool_error:
                                     logging.error(f"Tool execution error in streaming: {tool_error}")
                                     # Add error result to chat history
@@ -3850,10 +3640,6 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                                         "tool_call_id": tool_call['id'],
                                         "content": f"Error: {str(tool_error)}"
                                     })
-
-                        # Flush deferred media follow-ups after all tool replies.
-                        for _m in _deferred_media_followups:
-                            self._append_to_chat_history(_m)
                     else:
                         # Add complete response to chat history (text-only response)
                         if response_text:

src/praisonai-agents/praisonaiagents/agent/test_handoff_runtime_resolution.py

@@ -10,7 +10,7 @@ import time
 from unittest.mock import Mock, patch, MagicMock, AsyncMock
 import asyncio
 
-from praisonaiagents.agent.handoff import Handoff, HandoffConfig, ContextPolicy, HandoffResult
+from .handoff import Handoff, HandoffConfig, ContextPolicy, HandoffResult
 
 
 class MockAgent:

src/praisonai-agents/praisonaiagents/agent/tool_execution.py

@@ -14,7 +14,6 @@ import asyncio
 import inspect
 import contextvars
 import concurrent.futures
-import threading
 import random
 from typing import List, Optional, Any, Dict, Union, TYPE_CHECKING
 from ..errors import ToolExecutionError
@@ -50,238 +49,6 @@ class BackoffPolicy:
         return base + jitter_amount
 
 
-# Cap on encoded image bytes injected back into the conversation to avoid
-# blowing up the context window. ~5MB of base64 (~3.75MB raw) by default.
-MULTIMODAL_IMAGE_BYTE_LIMIT = 5_000_000
-
-
-def _content_part_to_data_uri(part: Dict[str, Any]) -> Optional[Dict[str, Any]]:
-    """Convert a structured content part into an OpenAI-style message part.
-
-    Returns a ``{"type": "image_url", "image_url": {...}}`` part for images, a
-    ``{"type": "text", ...}`` part for text, or ``None`` if it cannot be
-    represented as a model-visible part (callers should fall back to text).
-    """
-    import base64
-
-    if not isinstance(part, dict):
-        return None
-
-    ptype = part.get("type")
-
-    if ptype == "text":
-        text = part.get("text")
-        if text is None:
-            return None
-        return {"type": "text", "text": str(text)}
-
-    if ptype in ("image", "image_url"):
-        # Already-formed OpenAI image_url part
-        if ptype == "image_url" and isinstance(part.get("image_url"), dict):
-            return {"type": "image_url", "image_url": part["image_url"]}
-
-        url = part.get("url")
-        if url:
-            return {"type": "image_url", "image_url": {"url": url}}
-
-        data = part.get("data")
-        if data is None:
-            return None
-
-        mime = part.get("mime") or "image/png"
-        if isinstance(data, (bytes, bytearray)):
-            if len(data) > MULTIMODAL_IMAGE_BYTE_LIMIT:
-                logging.warning(
-                    "Multimodal image part (%d bytes) exceeds limit %d; skipping",
-                    len(data), MULTIMODAL_IMAGE_BYTE_LIMIT,
-                )
-                return None
-            encoded = base64.b64encode(bytes(data)).decode("utf-8")
-        else:
-            # Assume already base64-encoded string (strip any data URI prefix)
-            encoded = str(data)
-            if encoded.startswith("data:"):
-                return {"type": "image_url", "image_url": {"url": encoded}}
-            if len(encoded) > MULTIMODAL_IMAGE_BYTE_LIMIT * 2:
-                logging.warning(
-                    "Multimodal image part (encoded %d chars) exceeds limit; skipping",
-                    len(encoded),
-                )
-                return None
-        return {
-            "type": "image_url",
-            "image_url": {"url": f"data:{mime};base64,{encoded}"},
-        }
-
-    # Files / other media are referenced as text (most providers cannot ingest
-    # arbitrary binaries inline). Surface name/mime so the model is aware.
-    if ptype == "file":
-        name = part.get("name") or "file"
-        mime = part.get("mime") or "application/octet-stream"
-        return {"type": "text", "text": f"[file: {name} ({mime})]"}
-
-    return None
-
-
-def _normalize_multimodal_result(result: Any) -> Optional[List[Dict[str, Any]]]:
-    """Detect a multimodal tool result and return its content parts.
-
-    Recognises:
-    - ``ToolResult`` with ``content`` parts
-    - a bare list of content-part dicts (``[{"type": "image"|"text"|...}]``)
-    - a single content-part dict
-    - MCP-style content blocks (``{"type": "image", "data": ..., "mimeType": ...}``)
-
-    Returns ``None`` for plain text/JSON results so the existing path is used.
-    """
-    # ToolResult carrying structured content
-    content = getattr(result, "content", None)
-    if content and isinstance(content, list):
-        return _coerce_parts(content)
-
-    if isinstance(result, dict):
-        parts = _coerce_parts([result])
-        if parts and any(p.get("type") in ("image", "file") for p in parts):
-            return parts
-        return None
-
-    if isinstance(result, list) and result:
-        if all(isinstance(p, dict) and p.get("type") for p in result):
-            parts = _coerce_parts(result)
-            if parts and any(p.get("type") in ("image", "file") for p in parts):
-                return parts
-    return None
-
-
-def _coerce_parts(raw_parts: List[Any]) -> List[Dict[str, Any]]:
-    """Normalize assorted part shapes (incl. MCP) into the canonical schema."""
-    parts: List[Dict[str, Any]] = []
-    for p in raw_parts:
-        if not isinstance(p, dict):
-            continue
-        ptype = p.get("type")
-        if ptype == "text":
-            parts.append({"type": "text", "text": p.get("text", "")})
-        elif ptype in ("image", "image_url"):
-            norm = dict(p)
-            norm["type"] = "image" if ptype == "image" else "image_url"
-            # MCP uses 'mimeType'; normalize to 'mime'
-            if "mimeType" in norm and "mime" not in norm:
-                norm["mime"] = norm.pop("mimeType")
-            parts.append(norm)
-        elif ptype in ("file", "blob", "resource"):
-            norm = dict(p)
-            norm["type"] = "file"
-            if "mimeType" in norm and "mime" not in norm:
-                norm["mime"] = norm.pop("mimeType")
-            parts.append(norm)
-    return parts
-
-
-def format_tool_result_messages(
-    result: Any,
-    tool_call_id: str,
-    text_fallback: Optional[str] = None,
-    function_name: Optional[str] = None,
-) -> Optional[List[Dict[str, Any]]]:
-    """Build LLM messages from a (possibly multimodal) tool result.
-
-    For a plain text/JSON result this returns ``None`` so callers keep their
-    existing single ``tool`` message behaviour (no regression). For a multimodal
-    result it returns a list of messages: a ``tool`` message (satisfying the
-    tool_call_id contract) followed by a ``user`` message carrying the
-    model-visible image/text parts.
-
-    Most providers do not accept ``image_url`` parts inside a ``tool`` role
-    message, so images are delivered via a follow-up ``user`` message.
-
-    When ``function_name`` belongs to an external/untrusted tool, any text
-    parts are wrapped in the same prompt-injection fence used by the text path
-    (``wrap_if_external``) so external instructions cannot reach the model as
-    unfenced content.
-    """
-    pair = build_tool_result_message_pair(
-        result, tool_call_id, text_fallback=text_fallback, function_name=function_name
-    )
-    if pair is None:
-        return None
-    tool_message, followup_message = pair
-    return [tool_message, followup_message]
-
-
-def build_tool_result_message_pair(
-    result: Any,
-    tool_call_id: str,
-    text_fallback: Optional[str] = None,
-    function_name: Optional[str] = None,
-) -> Optional[tuple]:
-    """Return ``(tool_message, followup_user_message)`` for a multimodal result.
-
-    Separating the ``tool`` reply from the ``user`` media follow-up lets callers
-    that process multiple tool calls in one assistant turn keep all ``tool``
-    replies consecutive (the provider contract) and append the media
-    ``user`` message(s) only after the whole batch is handled.
-
-    Returns ``None`` for plain text/JSON results (existing path, no regression).
-    """
-    parts = _normalize_multimodal_result(result)
-    if not parts:
-        return None
-
-    is_external = False
-    if function_name:
-        try:
-            from ..tools.trust import is_external_tool
-            is_external = is_external_tool(function_name)
-        except Exception:
-            is_external = False
-
-    visible_parts: List[Dict[str, Any]] = []
-    text_summary_chunks: List[str] = []
-    has_media = False
-    for part in parts:
-        formatted = _content_part_to_data_uri(part)
-        if formatted is None:
-            continue
-        if formatted.get("type") == "image_url":
-            has_media = True
-            visible_parts.append(formatted)
-        else:
-            text_value = formatted.get("text", "")
-            if is_external and text_value:
-                text_value = _fence_external_text(function_name, text_value)
-                formatted = {"type": "text", "text": text_value}
-            text_summary_chunks.append(text_value)
-            visible_parts.append(formatted)
-
-    if not visible_parts or not has_media:
-        # Nothing model-visible beyond text -> let the text path handle it
-        return None
-
-    text_summary = "\n".join(c for c in text_summary_chunks if c).strip()
-    tool_text = text_fallback or text_summary or "[tool returned media; see attached content]"
-
-    tool_message = {
-        "role": "tool",
-        "tool_call_id": tool_call_id,
-        "content": tool_text,
-    }
-    followup_message = {
-        "role": "user",
-        "content": visible_parts,
-    }
-    return tool_message, followup_message
-
-
-def _fence_external_text(function_name: str, text: str) -> str:
-    """Apply the external-content prompt-injection fence to a text string."""
-    try:
-        wrapped = wrap_if_external(function_name, text)
-        return wrapped if isinstance(wrapped, str) else text
-    except Exception:
-        return text
-
-
 class ToolExecutionMixin:
     """Mixin providing toolexecution methods for the Agent class."""
     
@@ -458,7 +225,7 @@ class ToolExecutionMixin:
         """
         from ..tools.injected import with_injection_context
         from ..trace.context_events import get_context_emitter
-        from ..streaming.events import StreamEvent, StreamEventType, tool_progress_channel
+        from ..streaming.events import StreamEvent, StreamEventType
         import time as _time
         
         # Emit tool call start event (zero overhead when not set)
@@ -481,17 +248,6 @@ class ToolExecutionMixin:
                 },
                 agent_id=self.name,
             ))
-
-        # Build a progress sink so tools can stream incremental output while they
-        # run (e.g. line-buffered stdout from a long shell command). The sink
-        # forwards TOOL_PROGRESS events to the stream emitter; it is only active
-        # when callbacks are registered, so there is zero overhead otherwise.
-        _progress_sink = None
-        if _stream_emitter is not None and _stream_emitter.has_callbacks:
-            def _progress_sink(_event):  # noqa: ANN001 — StreamEvent forwarder
-                _event.tool_call = {"name": function_name, "id": tool_call_id}
-                _event.agent_id = self.name
-                _stream_emitter.emit(_event)
         
         try:
             # Check for steering messages before tool execution
@@ -595,46 +351,28 @@ class ToolExecutionMixin:
                         # P8/G11: Apply tool timeout if configured
                         tool_timeout = getattr(self, '_tool_timeout', None)
                         if tool_timeout and tool_timeout > 0:
-                            # Guard the sink so a tool that keeps running after a
-                            # timeout (future.cancel() cannot stop a started thread)
-                            # can no longer emit progress once the result is decided.
-                            _attempt_sink = _progress_sink
-                            _progress_active = None
-                            if _progress_sink is not None:
-                                _progress_active = threading.Event()
-                                _progress_active.set()
-
-                                def _attempt_sink(_event, _src=_progress_sink, _flag=_progress_active):  # noqa: ANN001
-                                    if _flag.is_set():
-                                        _src(_event)
-
-                            # Activate the progress channel BEFORE copy_context so the
-                            # sink propagates into the executor thread via contextvars.
-                            with tool_progress_channel(_attempt_sink):
-                                # Use copy_context to preserve injection context in executor thread
-                                ctx = contextvars.copy_context()
-
-                                def execute_with_context():
-                                    with with_injection_context(state):
-                                        return self._execute_tool_with_circuit_breaker(function_name, arguments)
-
-                                # Use reusable executor to prevent resource leaks
-                                if not hasattr(self, '_tool_executor'):
-                                    self._tool_executor = concurrent.futures.ThreadPoolExecutor(
-                                        max_workers=2, thread_name_prefix=f"tool-{self.name}"
-                                    )
-
-                                future = self._tool_executor.submit(ctx.run, execute_with_context)
-                                try:
-                                    result = future.result(timeout=tool_timeout)
-                                except concurrent.futures.TimeoutError:
-                                    if _progress_active is not None:
-                                        _progress_active.clear()
-                                    future.cancel()
-                                    logging.warning(f"Tool {function_name} timed out after {tool_timeout}s")
-                                    result = {"error": f"Tool timed out after {tool_timeout}s", "timeout": True}
+                            # Use copy_context to preserve injection context in executor thread
+                            ctx = contextvars.copy_context()
+                            
+                            def execute_with_context():
+                                with with_injection_context(state):
+                                    return self._execute_tool_with_circuit_breaker(function_name, arguments)
+                            
+                            # Use reusable executor to prevent resource leaks
+                            if not hasattr(self, '_tool_executor'):
+                                self._tool_executor = concurrent.futures.ThreadPoolExecutor(
+                                    max_workers=2, thread_name_prefix=f"tool-{self.name}"
+                                )
+                            
+                            future = self._tool_executor.submit(ctx.run, execute_with_context)
+                            try:
+                                result = future.result(timeout=tool_timeout)
+                            except concurrent.futures.TimeoutError:
+                                future.cancel()
+                                logging.warning(f"Tool {function_name} timed out after {tool_timeout}s")
+                                result = {"error": f"Tool timed out after {tool_timeout}s", "timeout": True}
                         else:
-                            with tool_progress_channel(_progress_sink), with_injection_context(state):
+                            with with_injection_context(state):
                                 result = self._execute_tool_with_circuit_breaker(function_name, arguments)
                         
                         # Check if the result indicates a retryable error
@@ -761,20 +499,13 @@ class ToolExecutionMixin:
                     # Don't let middleware failures break tool execution
                     logger.warning(f"Runtime middleware failed for {runtime_id}: {e}")
             
-            # Detect multimodal tool results (images/files) BEFORE any trust
-            # wrapping or truncation mutates/stringifies them. Multimodal results
-            # are returned as-is so the message-building layer can emit
-            # model-visible image parts via format_tool_result_messages().
-            _is_multimodal_result = _normalize_multimodal_result(result) is not None
-
             # Apply prompt injection protection for external tools
             # Zero-cost for trusted tools, wraps external content in security markers
-            if not _is_multimodal_result:
-                result = wrap_if_external(function_name, result)
+            result = wrap_if_external(function_name, result)
             
             # Apply tool output truncation to prevent context overflow
             # Uses context manager budget if enabled, otherwise applies default limit
-            if result and not _is_multimodal_result:
+            if result:
                 try:
                     result_str = str(result)
                     
@@ -1230,28 +961,17 @@ class ToolExecutionMixin:
         trust_level = tool_registry.get_trust_level(tool_name)
         
         if backend is not None:
-            # Also honour approval requirements registered through the public
-            # registry (e.g. a plugin/startup hook marking a custom destructive
-            # tool as requiring approval). Without this, the backend path would
-            # only gate the built-in DEFAULT_DANGEROUS_TOOLS and silently skip
-            # registry-required tools.
-            approval_registry = get_approval_registry()
-            registry_required = approval_registry.is_required(tool_name)
             # Check if tool needs approval based on multiple criteria
             needs_approval = (
                 approve_all 
                 or tool_name in DEFAULT_DANGEROUS_TOOLS
-                or registry_required
                 or (trust_level == "external")  # External tools need approval
             )
             if needs_approval:
                 request = ApprovalRequest(
                     tool_name=tool_name,
                     arguments=tool_args,
-                    risk_level=(
-                        approval_registry.get_risk_level(tool_name)
-                        or DEFAULT_DANGEROUS_TOOLS.get(tool_name, "medium")
-                    ),
+                    risk_level=DEFAULT_DANGEROUS_TOOLS.get(tool_name, "medium"),
                     agent_name=getattr(self, 'name', None),
                 )
                 

src/praisonai-agents/praisonaiagents/approval/registry.py

@@ -36,8 +36,6 @@ DEFAULT_DANGEROUS_TOOLS: Dict[str, str] = {
     "execute_code": "critical",
     "acp_execute_command": "critical",
     "write_file": "high",
-    "edit_file": "high",
-    "apply_patch": "high",
     "delete_file": "high",
     "move_file": "high",
     "copy_file": "high",

src/praisonai-agents/praisonaiagents/background/job_manager.py

@@ -13,10 +13,6 @@ from typing import Any, Callable, Dict, Optional
 from dataclasses import dataclass, field
 from concurrent.futures import ThreadPoolExecutor, Future
 
-from praisonaiagents._logging import get_logger
-
-logger = get_logger(__name__)
-
 
 class JobStatus(str, Enum):
     """Status of a background job."""
@@ -37,11 +33,6 @@ class JobInfo:
     completed_at: Optional[float] = None
     result: Any = None
     error: Optional[str] = None
-    # Optional origin/delivery context captured at spawn time so a gateway
-    # can route the result back to the originating conversation on completion
-    # (mirrors the scheduler's ``deliver="origin"`` grammar). Empty by default,
-    # preserving the pull-only behaviour when no delivery target is set.
-    origin: Dict[str, Any] = field(default_factory=dict)
     
     @property
     def duration(self) -> Optional[float]:
@@ -96,8 +87,6 @@ class BackgroundJobManager:
         self,
         func: Callable[[], Any],
         job_id: Optional[str] = None,
-        on_complete: Optional[Callable[["JobInfo"], None]] = None,
-        origin: Optional[Dict[str, Any]] = None,
     ) -> str:
         """
         Start a new background job.
@@ -105,18 +94,6 @@ class BackgroundJobManager:
         Args:
             func: The function to execute in the background
             job_id: Optional custom job ID (auto-generated if not provided)
-            on_complete: Optional callback invoked with the terminal
-                :class:`JobInfo` once the job reaches a terminal state
-                (completed or failed). This is the observable completion
-                signal a gateway subscribes to in order to proactively
-                deliver a background result back to the originating chat
-                without an active turn. Best-effort — any exception it
-                raises is swallowed so a delivery failure never crashes the
-                worker thread. Defaults to ``None`` (pull-only behaviour).
-            origin: Optional origin/delivery context (e.g. ``platform``,
-                ``chat_id``, ``thread_id``, ``session_id``, ``deliver``)
-                stored on the :class:`JobInfo` so ``on_complete`` can route
-                the result. Empty/omitted preserves today's behaviour.
             
         Returns:
             The job ID
@@ -126,27 +103,11 @@ class BackgroundJobManager:
         job_info = JobInfo(
             job_id=job_id,
             status=JobStatus.PENDING,
-            origin=dict(origin) if origin else {},
         )
         
         with self._lock:
             self._jobs[job_id] = job_info
         
-        def _fire_complete() -> None:
-            if on_complete is None:
-                return
-            with self._lock:
-                info = self._jobs.get(job_id)
-            if info is None:
-                return
-            try:
-                on_complete(info)
-            except Exception as e:  # noqa: BLE001 — delivery must never crash worker
-                logger.debug(
-                    "on_complete callback for job %s raised (non-fatal): %s",
-                    job_id, e,
-                )
-
         def _run_job():
             with self._lock:
                 self._jobs[job_id].status = JobStatus.RUNNING
@@ -158,14 +119,12 @@ class BackgroundJobManager:
                     self._jobs[job_id].status = JobStatus.COMPLETED
                     self._jobs[job_id].completed_at = time.time()
                     self._jobs[job_id].result = result
-                _fire_complete()
                 return result
             except Exception as e:
                 with self._lock:
                     self._jobs[job_id].status = JobStatus.FAILED
                     self._jobs[job_id].completed_at = time.time()
                     self._jobs[job_id].error = str(e)
-                _fire_complete()
                 raise
         
         future = self._executor.submit(_run_job)

src/praisonai-agents/praisonaiagents/bots/__init__.py

@@ -59,7 +59,7 @@ from .agent_reply import (
     AgentReply,
     extract_presentation,
 )
-from .config import BotConfig, BotOSConfig, DisplayPolicy, resolve_display_policy
+from .config import BotConfig, BotOSConfig
 
 __all__ = [
     "BotProtocol",
@@ -70,8 +70,6 @@ __all__ = [
     "BotUser",
     "BotChannel",
     "BotConfig",
-    "DisplayPolicy",
-    "resolve_display_policy",
     "MessageType",
     "ChatCommandInfo",
     "ChatCommandProtocol",

src/praisonai-agents/praisonaiagents/bots/config.py

@@ -198,225 +198,6 @@ class BotConfig:
         return channel_id in self.allowed_channels
 
 
-# ---------------------------------------------------------------------------
-# Display / verbosity policy
-# ---------------------------------------------------------------------------
-
-# Allowed values for each DisplayPolicy field.
-_DISPLAY_STREAMING = {"off", "draft", "progress"}
-_DISPLAY_TOOL_PROGRESS = {"off", "inline"}
-_DISPLAY_FOOTER = {"off", "compact"}
-
-# Platform → tier mapping. Tiers describe the rendering surface so sensible
-# defaults can be applied without per-platform configuration.
-#   edit   — edit-capable personal chats (stream live, hide tool spam)
-#   work   — workspace chats (post discrete progress steps)
-#   noedit — no-edit chats (single final message)
-#   batch  — batch-only channels (one final message, no interim)
-_PLATFORM_TIERS: Dict[str, str] = {
-    "telegram": "edit",
-    "discord": "edit",
-    "whatsapp": "noedit",
-    "slack": "work",
-    "teams": "work",
-    "mattermost": "work",
-    "email": "batch",
-    "sms": "batch",
-}
-
-
-@dataclass
-class DisplayPolicy:
-    """Per-platform display / verbosity policy.
-
-    Describes the operator's *policy* for how output should be presented on a
-    channel (as opposed to ``PlatformCapabilities`` which describes what a
-    platform *can* render).
-
-    Attributes:
-        streaming: Reply streaming mode.
-            ``"off"`` (single final message) | ``"draft"`` (edit in place) |
-            ``"progress"`` (compact status then final).
-        tool_progress: Whether tool execution progress is surfaced.
-            ``"off"`` (hidden) | ``"inline"`` (inline progress bubbles).
-        interim_assistant_messages: Show partial assistant messages, or only
-            the final reply.
-        footer: Runtime footer / status-line appended to replies.
-            ``"off"`` | ``"compact"`` (e.g. ``model · ctx% · cwd``).
-    """
-
-    streaming: str = "off"
-    tool_progress: str = "off"
-    interim_assistant_messages: bool = False
-    footer: str = "off"
-
-    def to_dict(self) -> Dict[str, Any]:
-        """Convert to dictionary for serialization."""
-        return {
-            "streaming": self.streaming,
-            "tool_progress": self.tool_progress,
-            "interim_assistant_messages": self.interim_assistant_messages,
-            "footer": self.footer,
-        }
-
-    @classmethod
-    def from_dict(cls, data: Dict[str, Any]) -> "DisplayPolicy":
-        """Create a policy from a (partial) dict, ignoring unknown keys."""
-        base = cls()
-        return cls(
-            streaming=_coerce_choice(
-                data.get("streaming", base.streaming), _DISPLAY_STREAMING, base.streaming
-            ),
-            tool_progress=_coerce_choice(
-                data.get("tool_progress", base.tool_progress),
-                _DISPLAY_TOOL_PROGRESS,
-                base.tool_progress,
-            ),
-            interim_assistant_messages=_coerce_bool(
-                data.get(
-                    "interim_assistant_messages", base.interim_assistant_messages
-                ),
-                base.interim_assistant_messages,
-            ),
-            footer=_coerce_choice(
-                data.get("footer", base.footer), _DISPLAY_FOOTER, base.footer
-            ),
-        )
-
-
-# Built-in per-tier defaults. Most operators configure nothing and still get
-# correct UX on every channel.
-_TIER_DEFAULTS: Dict[str, DisplayPolicy] = {
-    # edit-capable personal chats: stream live, hide tool spam, no footer
-    "edit": DisplayPolicy(streaming="draft", tool_progress="off", footer="off"),
-    # workspace chats: post discrete progress steps
-    "work": DisplayPolicy(streaming="off", tool_progress="inline", footer="off"),
-    # no-edit chats: single final message
-    "noedit": DisplayPolicy(streaming="off", tool_progress="off", footer="off"),
-    # batch-only channels: one final message, no interim
-    "batch": DisplayPolicy(
-        streaming="off",
-        tool_progress="off",
-        interim_assistant_messages=False,
-        footer="off",
-    ),
-}
-
-
-def _coerce_choice(value: Any, allowed: set, default: str) -> str:
-    """Return ``value`` if it is an allowed choice, else ``default``."""
-    if isinstance(value, str) and value in allowed:
-        return value
-    return default
-
-
-# String tokens treated as booleans for text-backed config (YAML/JSON/env).
-_TRUE_TOKENS = {"true", "1", "yes", "on"}
-_FALSE_TOKENS = {"false", "0", "no", "off"}
-
-
-def _coerce_bool(value: Any, default: bool) -> bool:
-    """Coerce ``value`` to a bool without ``bool("false") is True`` surprises.
-
-    Real booleans pass through. Strings are matched against known truthy/falsy
-    tokens (case-insensitive). Anything else falls back to ``default``.
-    """
-    if isinstance(value, bool):
-        return value
-    if isinstance(value, str):
-        token = value.strip().lower()
-        if token in _TRUE_TOKENS:
-            return True
-        if token in _FALSE_TOKENS:
-            return False
-    return default
-
-
-def resolve_display_policy(platform: str, config: Optional[Dict[str, Any]]) -> DisplayPolicy:
-    """Resolve the effective :class:`DisplayPolicy` for a platform.
-
-    Precedence (highest first):
-        1. explicit ``display.platforms.<platform>.<setting>``
-        2. ``display.<setting>`` global default
-        3. platform-tier default (edit / work / noedit / batch)
-        4. built-in :class:`DisplayPolicy` default
-
-    Args:
-        platform: Platform name, e.g. ``"telegram"``.
-        config: A ``display`` config dict (the value of the ``display:`` block),
-            or a full config dict containing a ``display`` key. ``None`` is
-            treated as empty.
-
-    Returns:
-        The resolved :class:`DisplayPolicy`.
-    """
-    display = _extract_display(config)
-
-    # Layer 4: built-in default.
-    policy = DisplayPolicy()
-
-    # Layer 3: platform-tier default.
-    tier = _PLATFORM_TIERS.get((platform or "").lower())
-    if tier and tier in _TIER_DEFAULTS:
-        policy = _merge_policy(policy, _TIER_DEFAULTS[tier].to_dict())
-
-    # Layer 2: global default (display.<setting>).
-    global_overrides = {
-        k: v for k, v in display.items() if k != "platforms"
-    }
-    policy = _merge_policy(policy, global_overrides)
-
-    # Layer 1: explicit platform override.
-    platforms = display.get("platforms") or {}
-    if isinstance(platforms, dict):
-        platform_overrides = _lookup_platform(platforms, platform)
-        if isinstance(platform_overrides, dict):
-            policy = _merge_policy(policy, platform_overrides)
-
-    return policy
-
-
-def _lookup_platform(platforms: Dict[str, Any], platform: str) -> Any:
-    """Look up a platform's overrides, tolerating key casing differences.
-
-    Tries the exact key, then the lower-cased key, then a case-insensitive
-    scan so natural config keys (e.g. ``Telegram``) still match ``telegram``.
-    """
-    if platform in platforms:
-        return platforms[platform]
-    normalized = (platform or "").lower()
-    if normalized in platforms:
-        return platforms[normalized]
-    for key, value in platforms.items():
-        if isinstance(key, str) and key.lower() == normalized:
-            return value
-    return None
-
-
-def _extract_display(config: Optional[Dict[str, Any]]) -> Dict[str, Any]:
-    """Return the ``display`` mapping from ``config``.
-
-    Accepts either the ``display`` block directly or a full config dict
-    containing a ``display`` key.
-    """
-    if not isinstance(config, dict):
-        return {}
-    if "display" in config and isinstance(config.get("display"), dict):
-        return config["display"]
-    return config
-
-
-def _merge_policy(policy: DisplayPolicy, overrides: Dict[str, Any]) -> DisplayPolicy:
-    """Return a new policy with valid ``overrides`` applied over ``policy``."""
-    if not isinstance(overrides, dict):
-        return policy
-    data = policy.to_dict()
-    for key in data:
-        if key in overrides:
-            data[key] = overrides[key]
-    return DisplayPolicy.from_dict(data)
-
-
 @dataclass
 class BotOSConfig:
     """Configuration for BotOS — multi-platform bot orchestrator.

src/praisonai-agents/praisonaiagents/bots/protocols.py

@@ -98,10 +98,6 @@ class PlatformCapabilities:
             re-dispatch, upgrading delivery from at-least-once to
             effectively-once. When False, delivery remains at-least-once and a
             crash mid-send may re-send the message.
-        supports_media: Whether the adapter can attach/upload media files on
-            outbound sends (photos, documents). When False, the gateway's
-            delivery router degrades gracefully and reports media as not
-            attached rather than silently dropping it.
         supports_idempotency_token: Whether the transport accepts a
             provider-level idempotency token so the platform itself
             de-duplicates a retried send. This is an informational capability
@@ -124,7 +120,6 @@ class PlatformCapabilities:
     verifies_webhook_signature: bool = False
     reconciles_unknown_send: bool = False
     supports_idempotency_token: bool = False
-    supports_media: bool = False
     
     def to_dict(self) -> Dict[str, Any]:
         """Convert to dictionary."""
@@ -143,7 +138,6 @@ class PlatformCapabilities:
             "verifies_webhook_signature": self.verifies_webhook_signature,
             "reconciles_unknown_send": self.reconciles_unknown_send,
             "supports_idempotency_token": self.supports_idempotency_token,
-            "supports_media": self.supports_media,
         }
     
     @classmethod
@@ -164,7 +158,6 @@ class PlatformCapabilities:
             verifies_webhook_signature=data.get("verifies_webhook_signature", False),
             reconciles_unknown_send=data.get("reconciles_unknown_send", False),
             supports_idempotency_token=data.get("supports_idempotency_token", False),
-            supports_media=data.get("supports_media", False),
         )
 
 
@@ -515,7 +508,6 @@ def evaluate_channel_health(
     health: HealthResult,
     startup_grace_seconds: float = 60.0,
     stale_after_seconds: float = 120.0,
-    stuck_after_seconds: float = 900.0,
     current_time: Optional[float] = None,
 ) -> HealthReason:
     """Evaluate channel health and return a reason.
@@ -523,30 +515,10 @@ def evaluate_channel_health(
     Pure function that evaluates a HealthResult and determines
     the health reason based on various criteria.
     
-    Liveness is driven by passive *inbound* transport activity
-    (``health.last_activity``) rather than only an outbound probe, and the
-    evaluator is aware of in-flight agent runs (``health.active_runs``) so a
-    busy channel is never mistaken for a dead socket:
-
-    - busy with recent inbound progress -> ``BUSY`` (never restarted);
-    - busy but no progress beyond ``stuck_after_seconds`` -> ``STUCK``;
-    - idle and inbound stale beyond ``stale_after_seconds`` -> ``STALE_SOCKET``.
-
-    For the busy branch, "progress" is the most recent of inbound transport
-    activity (``health.last_activity``) and *in-run* progress
-    (``health.last_run_progress`` — tool calls, streamed draft edits, token
-    output, or a periodic heartbeat). A single long agent run that streams
-    output or emits tool events the whole time therefore stays ``BUSY``
-    indefinitely instead of being torn down mid-run once its wall-clock
-    crosses ``stuck_after_seconds``; only a run that emits nothing for
-    ``stuck_after_seconds`` is flagged ``STUCK``.
-
     Args:
         health: The health result to evaluate
         startup_grace_seconds: Grace period for startup
-        stale_after_seconds: Time after which no inbound activity is stale
-        stuck_after_seconds: Time after which a busy channel with no progress
-            is considered stuck
+        stale_after_seconds: Time after which no activity is considered stale
         current_time: Current timestamp (for testing)
         
     Returns:
@@ -571,28 +543,7 @@ def evaluate_channel_health(
     if health.probe and not health.probe.ok:
         return HealthReason.DISCONNECTED
     
-    # Run-aware liveness: a busy channel is never killed mid-run unless it has
-    # made no progress for an extended period (stuck). "Progress" is the most
-    # recent of inbound transport activity (``last_activity``) and *in-run*
-    # progress (``last_run_progress`` — tool/stream/token/heartbeat events),
-    # so a long run that is actively streaming or calling tools stays BUSY even
-    # though no new inbound message arrives during the turn. When neither
-    # timestamp was recorded, fall back to uptime so a hung run with no
-    # progress signal can still be detected as STUCK rather than staying BUSY
-    # (non-recoverable) forever.
-    if health.active_runs > 0:
-        progress_at = max(
-            health.last_activity or 0.0,
-            health.last_run_progress or 0.0,
-        )
-        if progress_at <= 0.0:
-            progress_at = current_time - (health.uptime_seconds or 0.0)
-        idle = current_time - progress_at
-        if idle > stuck_after_seconds:
-            return HealthReason.STUCK
-        return HealthReason.BUSY
-    
-    # Check for stale socket (no inbound transport activity while idle)
+    # Check for stale socket (no transport activity)
     if health.last_activity is not None:
         time_since_activity = current_time - health.last_activity
         if time_since_activity > stale_after_seconds:
@@ -619,12 +570,7 @@ class HealthResult:
         error: Error message (if unhealthy)
         details: Additional platform-specific health details
         reason: Health status reason (optional)
-        last_activity: Last INBOUND transport activity timestamp (optional)
-        last_run_progress: Last IN-RUN progress timestamp (optional) — refreshed
-            on real run progress (tool calls, streamed draft edits, token output,
-            or a periodic heartbeat) so a long, actively-progressing run keeps the
-            channel BUSY instead of tripping STUCK on wall-clock alone.
-        active_runs: Number of in-flight agent turns (busy count)
+        last_activity: Last transport activity timestamp (optional)
     """
     
     ok: bool
@@ -637,8 +583,6 @@ class HealthResult:
     details: Dict[str, Any] = field(default_factory=dict)
     reason: Optional[HealthReason] = None
     last_activity: Optional[float] = None
-    last_run_progress: Optional[float] = None
-    active_runs: int = 0
     
     def to_dict(self) -> Dict[str, Any]:
         """Convert to dictionary."""
@@ -653,8 +597,6 @@ class HealthResult:
             "details": self.details,
             "reason": self.reason.value if self.reason else None,
             "last_activity": self.last_activity,
-            "last_run_progress": self.last_run_progress,
-            "active_runs": self.active_runs,
         }
 
 

src/praisonai-agents/praisonaiagents/config/parse_utils.py

@@ -107,7 +107,7 @@ def is_path_like(value: str) -> bool:
     if not isinstance(value, str):
         return False
     
-    # Check for path indicators
+    # Check for path indicators (POSIX and Windows-style prefixes)
     if value.startswith(("./", "../", "/", "~/", ".\\", "..\\", "\\\\", "\\", "~\\")):
         return True
 
@@ -119,11 +119,13 @@ def is_path_like(value: str) -> bool:
         and value[2] in ("\\", "/")
     ):
         return True
-    
+
     # Check for directory indicator
     if value.endswith(("/", "\\")):
         return True
 
+    # Check for embedded backslash separators (relative Windows path like "knowledge\docs").
+    # Backslash is not valid in normal config string values, so it is a strong path signal.
     if "\\" in value:
         return True
     

src/praisonai-agents/praisonaiagents/db/tests/__init__.py

@@ -0,0 +1 @@
+"""TDD tests for db integration."""

src/praisonai-agents/praisonaiagents/db/tests/test_db_integration.py

@@ -28,8 +28,12 @@ def test_lazy_import_no_heavy_deps():
     heavy_libs = ['psycopg2', 'pymysql', 'redis']  # DB-specific libs
     loaded_heavy = [lib for lib in heavy_libs if lib in sys.modules]
     
-    assert not loaded_heavy, f"Heavy DB libs loaded by db module: {loaded_heavy}"
+    if loaded_heavy:
+        print(f"  ❌ Heavy DB libs loaded by db module: {loaded_heavy}")
+        return False
+    
     print("  ✅ No heavy DB libs loaded by praisonaiagents.db module")
+    return True
 
 
 def test_agent_accepts_db_parameter():
@@ -42,9 +46,16 @@ def test_agent_accepts_db_parameter():
     sig = inspect.signature(Agent.__init__)
     params = list(sig.parameters.keys())
     
-    assert 'db' in params, "Agent does not accept 'db' parameter"
-    assert 'session_id' in params, "Agent does not accept 'session_id' parameter"
+    if 'db' not in params:
+        print("  ❌ Agent does not accept 'db' parameter")
+        return False
+    
+    if 'session_id' not in params:
+        print("  ❌ Agent does not accept 'session_id' parameter")
+        return False
+    
     print("  ✅ Agent accepts db and session_id parameters")
+    return True
 
 
 class MockDbAdapter:
@@ -91,9 +102,16 @@ def test_db_hook_lifecycle():
     )
     
     # Verify db is stored
-    assert agent._db is mock_db, "Agent did not store db adapter"
-    assert agent._session_id == "test-session-001", "Agent did not store session_id"
+    if agent._db is not mock_db:
+        print("  ❌ Agent did not store db adapter")
+        return False
+    
+    if agent._session_id != "test-session-001":
+        print("  ❌ Agent did not store session_id")
+        return False
+    
     print("  ✅ Agent stores db and session_id correctly")
+    return True
 
 
 def test_db_none_unchanged_behavior():
@@ -109,13 +127,19 @@ def test_db_none_unchanged_behavior():
     )
     
     # Verify db is None
-    assert agent._db is None, "Agent._db should be None when not provided"
+    if agent._db is not None:
+        print("  ❌ Agent._db should be None when not provided")
+        return False
     
     # Verify _init_db_session does nothing when db is None
     agent._init_db_session()
     
-    assert not agent._db_initialized, "_db_initialized should remain False when db is None"
+    if agent._db_initialized:
+        print("  ❌ _db_initialized should remain False when db is None")
+        return False
+    
     print("  ✅ db=None behavior unchanged")
+    return True
 
 
 def test_session_id_auto_generation():
@@ -136,11 +160,16 @@ def test_session_id_auto_generation():
     # Trigger db initialization
     agent._init_db_session()
     
-    assert agent._session_id is not None, "session_id should be auto-generated"
-    assert agent._session_id.startswith("session-"), (
-        f"session_id format unexpected: {agent._session_id}"
-    )
+    if agent._session_id is None:
+        print("  ❌ session_id should be auto-generated")
+        return False
+    
+    if not agent._session_id.startswith("session-"):
+        print(f"  ❌ session_id format unexpected: {agent._session_id}")
+        return False
+    
     print(f"  ✅ session_id auto-generated: {agent._session_id}")
+    return True
 
 
 def test_protocol_compliance():
@@ -151,7 +180,9 @@ def test_protocol_compliance():
     
     # Check DbMessage fields
     msg = DbMessage(role="user", content="test")
-    assert msg.role == "user" and msg.content == "test", "DbMessage fields not working"
+    if msg.role != "user" or msg.content != "test":
+        print("  ❌ DbMessage fields not working")
+        return False
     
     # Check protocol methods
     required_methods = [
@@ -165,11 +196,17 @@ def test_protocol_compliance():
     
     mock = MockDbAdapter()
     for method in required_methods:
-        assert hasattr(mock, method), f"MockDbAdapter missing {method}"
+        if not hasattr(mock, method):
+            print(f"  ❌ MockDbAdapter missing {method}")
+            return False
     
     # Check protocol isinstance
-    assert isinstance(mock, DbAdapter), "MockDbAdapter should implement DbAdapter protocol"
+    if not isinstance(mock, DbAdapter):
+        print("  ❌ MockDbAdapter should implement DbAdapter protocol")
+        return False
+    
     print("  ✅ DbAdapter protocol properly defined")
+    return True
 
 
 def run_all_tests():
@@ -178,23 +215,14 @@ def run_all_tests():
     print("PraisonAI Agents DB Integration - TDD Tests")
     print("=" * 60)
     
-    tests = [
-        ("Lazy Import", test_lazy_import_no_heavy_deps),
-        ("Agent db Parameter", test_agent_accepts_db_parameter),
-        ("DB Hook Lifecycle", test_db_hook_lifecycle),
-        ("db=None Unchanged", test_db_none_unchanged_behavior),
-        ("Session ID Auto-Gen", test_session_id_auto_generation),
-        ("Protocol Compliance", test_protocol_compliance),
-    ]
-
     results = []
-    for name, test_fn in tests:
-        try:
-            test_fn()
-            results.append((name, True))
-        except AssertionError as exc:
-            print(f"  ❌ {name}: {exc}")
-            results.append((name, False))
+    
+    results.append(("Lazy Import", test_lazy_import_no_heavy_deps()))
+    results.append(("Agent db Parameter", test_agent_accepts_db_parameter()))
+    results.append(("DB Hook Lifecycle", test_db_hook_lifecycle()))
+    results.append(("db=None Unchanged", test_db_none_unchanged_behavior()))
+    results.append(("Session ID Auto-Gen", test_session_id_auto_generation()))
+    results.append(("Protocol Compliance", test_protocol_compliance()))
     
     print("\n" + "=" * 60)
     passed = sum(1 for _, r in results if r)

src/praisonai-agents/praisonaiagents/frameworks/__init__.py

@@ -1,22 +0,0 @@
-"""Framework adapter protocols and shared helpers (no third-party framework deps)."""
-
-from typing import TYPE_CHECKING
-
-__all__ = [
-    "FrameworkAdapterProtocol",
-    "BaseFrameworkAdapter",
-]
-
-if TYPE_CHECKING:
-    from .protocols import FrameworkAdapterProtocol
-    from .base import BaseFrameworkAdapter
-
-
-def __getattr__(name: str):
-    if name == "FrameworkAdapterProtocol":
-        from .protocols import FrameworkAdapterProtocol
-        return FrameworkAdapterProtocol
-    if name == "BaseFrameworkAdapter":
-        from .base import BaseFrameworkAdapter
-        return BaseFrameworkAdapter
-    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

src/praisonai-agents/praisonaiagents/frameworks/base.py

@@ -1,148 +0,0 @@
-"""Shared base helpers for framework adapters (no third-party imports)."""
-
-from __future__ import annotations
-
-import asyncio
-import logging
-import os
-import re
-from concurrent.futures import ThreadPoolExecutor
-from typing import Any, Callable, Dict, List, Optional
-
-from .protocols import FrameworkAdapterProtocol
-
-logger = logging.getLogger(__name__)
-
-
-class BaseFrameworkAdapter:
-    """Base class for framework adapters providing common functionality."""
-
-    name: str = ""
-    install_hint: str = ""
-    requires_tools_extra: bool = False
-    is_router: bool = False
-
-    # Adapters with a native async ``run`` path set this True and override
-    # ``arun``. When False (default), ``arun`` offloads the sync ``run`` to a
-    # bounded, per-adapter thread pool so one slow run cannot starve the
-    # process-wide default executor used by ``asyncio.to_thread``.
-    SUPPORTS_ASYNC: bool = False
-
-    # Bounded per-adapter offload pool. Kept small on purpose: framework runs
-    # are long-lived, so a large pool provides no benefit and just hides the
-    # lack of a native async path. Overridable per subclass / instance.
-    _THREAD_OFFLOAD_MAX_WORKERS: int = 4
-
-    DEFAULT_MODEL = "openai/gpt-4o-mini"
-
-    def __init__(self) -> None:
-        self._thread_pool: Optional[ThreadPoolExecutor] = None
-
-    def _resolve_llm(self, spec: Any, llm_config: Optional[List[Dict]]) -> str:
-        """Resolve a model name from per-agent spec and shared llm_config."""
-        base = None
-        key = None
-        if llm_config and len(llm_config) > 0:
-            base = llm_config[0].get("base_url")
-            key = llm_config[0].get("api_key")
-
-        if isinstance(spec, str) and spec.strip():
-            model = spec.strip()
-        elif isinstance(spec, dict) and spec.get("model"):
-            model = spec["model"]
-        else:
-            model = os.environ.get("MODEL_NAME") or self.DEFAULT_MODEL
-
-        # Return model string; wrapper subclasses may upgrade to provider objects.
-        _ = (base, key)
-        return model
-
-    def _format_template(self, template: str, **kwargs: Any) -> str:
-        """Safely format template string, preserving JSON-like braces."""
-        if not isinstance(template, str):
-            return template
-
-        def _sub(match: re.Match) -> str:
-            name = match.group(1)
-            return str(kwargs[name]) if name in kwargs else match.group(0)
-
-        return re.sub(r"\{([a-zA-Z_][a-zA-Z0-9_]*)\}", _sub, template)
-
-    def resolve(
-        self, *, config: Optional[Dict[str, Any]] = None
-    ) -> FrameworkAdapterProtocol:
-        return self
-
-    def setup(self, *, framework_tag: str) -> None:
-        pass
-
-    def _get_thread_pool(self) -> ThreadPoolExecutor:
-        """Lazily create the bounded, per-adapter offload executor."""
-        # Defensive: tolerate subclasses that don't call super().__init__().
-        if getattr(self, "_thread_pool", None) is None:
-            self._thread_pool = ThreadPoolExecutor(
-                max_workers=self._THREAD_OFFLOAD_MAX_WORKERS,
-                thread_name_prefix=f"{self.name or 'framework'}-arun",
-            )
-        return self._thread_pool
-
-    async def _thread_offload_run(self, *args: Any, **kwargs: Any) -> str:
-        """Run the sync ``run`` on this adapter's bounded thread pool.
-
-        Unlike ``asyncio.to_thread`` (which shares the process-wide default
-        executor), this isolates the offload so one slow framework run cannot
-        starve every other async caller in the process.
-        """
-        loop = asyncio.get_running_loop()
-        pool = self._get_thread_pool()
-        return await loop.run_in_executor(
-            pool, lambda: self.run(*args, **kwargs)
-        )
-
-    async def arun(
-        self,
-        config: Dict[str, Any],
-        llm_config: List[Dict],
-        topic: str,
-        *,
-        tools_dict: Optional[Dict[str, Any]] = None,
-        agent_callback: Optional[Callable] = None,
-        task_callback: Optional[Callable] = None,
-        cli_config: Optional[Dict[str, Any]] = None,
-    ) -> str:
-        if not self.SUPPORTS_ASYNC:
-            logger.warning(
-                "Adapter %r has no native async path; delegating to a bounded "
-                "thread pool (max_workers=%d). Concurrent async callers will "
-                "contend for this pool.",
-                self.name or type(self).__name__,
-                self._THREAD_OFFLOAD_MAX_WORKERS,
-            )
-        return await self._thread_offload_run(
-            config,
-            llm_config,
-            topic,
-            tools_dict=tools_dict,
-            agent_callback=agent_callback,
-            task_callback=task_callback,
-            cli_config=cli_config,
-        )
-
-    def cleanup(self) -> None:
-        pool = getattr(self, "_thread_pool", None)
-        if pool is not None:
-            pool.shutdown(wait=False)
-            self._thread_pool = None
-
-    def __del__(self) -> None:
-        # Best-effort: shut down the offload pool when the adapter is garbage
-        # collected so idle worker threads do not outlive the adapter in
-        # long-lived services that forget to call cleanup(). Guarded because
-        # __del__ can run during interpreter shutdown when globals are gone.
-        try:
-            self.cleanup()
-        except Exception:
-            pass
-
-    def resolve_alias(self) -> str:
-        return self.name

src/praisonai-agents/praisonaiagents/frameworks/protocols.py

@@ -1,65 +0,0 @@
-"""Protocol for optional third-party agent framework adapters."""
-
-from __future__ import annotations
-
-from typing import Any, Callable, Dict, List, Optional, Protocol, runtime_checkable
-
-
-@runtime_checkable
-class FrameworkAdapterProtocol(Protocol):
-    """Contract for YAML-driven multi-framework execution backends."""
-
-    name: str
-    install_hint: str
-    requires_tools_extra: bool
-    is_router: bool
-
-    def is_available(self) -> bool:
-        """Return True when this framework's optional dependencies are installed."""
-        ...
-
-    def resolve(
-        self, *, config: Optional[Dict[str, Any]] = None
-    ) -> "FrameworkAdapterProtocol":
-        """Pick a concrete adapter variant (e.g. autogen v0.2 vs v0.4)."""
-        ...
-
-    def setup(self, *, framework_tag: str) -> None:
-        """Framework-specific pre-run hooks (observability, SDK init, etc.)."""
-        ...
-
-    def run(
-        self,
-        config: Dict[str, Any],
-        llm_config: List[Dict],
-        topic: str,
-        *,
-        tools_dict: Optional[Dict[str, Any]] = None,
-        agent_callback: Optional[Callable] = None,
-        task_callback: Optional[Callable] = None,
-        cli_config: Optional[Dict[str, Any]] = None,
-    ) -> str:
-        """Execute the framework with shared agents.yaml configuration."""
-        ...
-
-    async def arun(
-        self,
-        config: Dict[str, Any],
-        llm_config: List[Dict],
-        topic: str,
-        *,
-        tools_dict: Optional[Dict[str, Any]] = None,
-        agent_callback: Optional[Callable] = None,
-        task_callback: Optional[Callable] = None,
-        cli_config: Optional[Dict[str, Any]] = None,
-    ) -> str:
-        """Async execution; default implementations may offload sync run()."""
-        ...
-
-    def cleanup(self) -> None:
-        """Release resources after execution."""
-        ...
-
-    def resolve_alias(self) -> str:
-        """Return the concrete adapter name to dispatch to."""
-        ...

src/praisonai-agents/praisonaiagents/gateway/__init__.py

@@ -52,36 +52,6 @@ from .protocols import (
     GatewayIdlePolicyProtocol,
     GatewayIdlePolicy,  # backward-compat alias
     ScaleToZeroPolicy,
-    # Gateway graceful-drain on shutdown (Issue #2375)
-    DrainDecision,
-    GatewayDrainPolicyProtocol,
-    DrainTimeoutPolicy,
-    # Gateway inbound admission control (Issue #2454)
-    AdmissionDecision,
-    GatewayConcurrencyPolicyProtocol,
-    GatewayConcurrencyPolicy,  # backward-compat alias
-    ConcurrencyLimitPolicy,
-    # Gateway rate-limit admission (Issue #2532)
-    RateLimitDecision,
-    RateLimitPolicyProtocol,
-    RateLimitPolicy,  # backward-compat alias
-    SlidingWindowRateLimitPolicy,
-    # Port-less, restart-safe external drain trigger (Issue #2390)
-    current_epoch,
-    DrainMarkerPolicy,
-    # Crash / shutdown forensics (Issue #2436)
-    ShutdownForensicsProtocol,
-    format_forensics_for_log,
-    is_supervised,
-    drain_timeout_has_headroom,
-    # Code-skew guard for hot operations (Issue #2460)
-    detect_code_skew,
-    # Restart-intent exit-code protocol (Issue #2437)
-    GATEWAY_OK_EXIT_CODE,
-    GATEWAY_RESTART_EXIT_CODE,
-    GATEWAY_FATAL_CONFIG_EXIT_CODE,
-    FatalConfigError,
-    classify_exit_reason,
     # Protocol version negotiation
     PROTOCOL_VERSION,
     MIN_PROTOCOL_VERSION,
@@ -90,9 +60,6 @@ from .protocols import (
     ProtocolHelloOk,
     GapInfo,
     ResumeSnapshot,
-    # Out-of-process platform-connector relay (Issue #2485)
-    CapabilityDescriptor,
-    RelayTransport,
 )
 from .hooks import (
     HookAction,
@@ -195,35 +162,6 @@ __all__ = [
     "GatewayIdlePolicyProtocol",
     "GatewayIdlePolicy",
     "ScaleToZeroPolicy",
-    "DrainDecision",
-    "GatewayDrainPolicyProtocol",
-    "DrainTimeoutPolicy",
-    # Gateway inbound admission control (Issue #2454)
-    "AdmissionDecision",
-    "GatewayConcurrencyPolicyProtocol",
-    "GatewayConcurrencyPolicy",
-    "ConcurrencyLimitPolicy",
-    # Gateway rate-limit admission (Issue #2532)
-    "RateLimitDecision",
-    "RateLimitPolicyProtocol",
-    "RateLimitPolicy",
-    "SlidingWindowRateLimitPolicy",
-    # Port-less, restart-safe external drain trigger (Issue #2390)
-    "current_epoch",
-    "DrainMarkerPolicy",
-    # Crash / shutdown forensics (Issue #2436)
-    "ShutdownForensicsProtocol",
-    "format_forensics_for_log",
-    "is_supervised",
-    "drain_timeout_has_headroom",
-    # Code-skew guard for hot operations (Issue #2460)
-    "detect_code_skew",
-    # Restart-intent exit-code protocol (Issue #2437)
-    "GATEWAY_OK_EXIT_CODE",
-    "GATEWAY_RESTART_EXIT_CODE",
-    "GATEWAY_FATAL_CONFIG_EXIT_CODE",
-    "FatalConfigError",
-    "classify_exit_reason",
     # Protocol version negotiation
     "PROTOCOL_VERSION",
     "MIN_PROTOCOL_VERSION",
@@ -232,9 +170,6 @@ __all__ = [
     "ProtocolHelloOk",
     "GapInfo",
     "ResumeSnapshot",
-    # Out-of-process platform-connector relay (Issue #2485)
-    "CapabilityDescriptor",
-    "RelayTransport",
     # Inbound trigger / webhook contract (Issue #2281)
     "HookAction",
     "HookConfig",

src/praisonai-agents/praisonaiagents/gateway/config.py

@@ -255,11 +255,6 @@ class GatewayConfig:
     ssl_key: Optional[str] = None
     max_buffered_bytes: int = 1024 * 1024  # 1MB default
     max_queued_frames: int = 1000  # Per-client outbound frame ceiling
-    # Issue #2454: gateway-wide inbound admission control. 0 disables the gate
-    # (today's behaviour: every inbound turn dispatches immediately).
-    max_concurrent_runs: int = 0  # Aggregate concurrency ceiling (0 = unlimited)
-    queue_depth: int = 0  # Bounded wait queue when at the ceiling
-    overflow_policy: str = "reject"  # reject | queue | shed_oldest
     push: PushConfig = field(default_factory=PushConfig)
     auth_scopes: Optional[Dict[str, List[str]]] = None
 
@@ -281,16 +276,6 @@ class GatewayConfig:
             raise ValueError("heartbeat_interval must be >= 0")
         if self.reconnect_timeout < 0:
             raise ValueError("reconnect_timeout must be >= 0")
-        if self.max_concurrent_runs < 0:
-            raise ValueError(
-                "max_concurrent_runs must be >= 0 (use 0 to disable admission control)"
-            )
-        if self.queue_depth < 0:
-            raise ValueError("queue_depth must be >= 0")
-        if self.overflow_policy not in ("reject", "queue", "shed_oldest"):
-            raise ValueError(
-                "overflow_policy must be one of 'reject', 'queue', 'shed_oldest'"
-            )
 
     @property
     def has_scope_policy(self) -> bool:
@@ -359,9 +344,6 @@ class GatewayConfig:
             "ssl_enabled": bool(self.ssl_cert and self.ssl_key),
             "max_buffered_bytes": self.max_buffered_bytes,
             "max_queued_frames": self.max_queued_frames,
-            "max_concurrent_runs": self.max_concurrent_runs,
-            "queue_depth": self.queue_depth,
-            "overflow_policy": self.overflow_policy,
             "push": self.push.to_dict(),
             "scope_policy_enabled": self.has_scope_policy,
         }
@@ -540,9 +522,6 @@ class MultiChannelGatewayConfig:
             ssl_key=gw_data.get("ssl_key"),
             max_buffered_bytes=int(gw_data.get("max_buffered_bytes", 1024 * 1024)),
             max_queued_frames=int(gw_data.get("max_queued_frames", 1000)),
-            max_concurrent_runs=int(gw_data.get("max_concurrent_runs", 0) or 0),
-            queue_depth=int(gw_data.get("queue_depth", 0) or 0),
-            overflow_policy=str(gw_data.get("overflow_policy", "reject") or "reject"),
             auth_scopes=auth_scopes,
         )
         

src/praisonai-agents/praisonaiagents/hooks/__init__.py

@@ -63,7 +63,6 @@ __all__ = [
     # Event-specific inputs
     "BeforeToolInput",
     "AfterToolInput",
-    "BeforeToolDefinitionsInput",
     "BeforeAgentInput",
     "AfterAgentInput",
     "BeforeLLMInput",
@@ -80,7 +79,6 @@ __all__ = [
     "GatewayStartInput",
     "GatewayStopInput",
     "ScheduleTriggerInput",
-    "JobCompletedInput",
     # Middleware types
     "InvocationContext",
     "ModelRequest",
@@ -132,7 +130,6 @@ _LAZY_GROUPS = {
     'events': {
         'BeforeToolInput': ('praisonaiagents.hooks.events', 'BeforeToolInput'),
         'AfterToolInput': ('praisonaiagents.hooks.events', 'AfterToolInput'),
-        'BeforeToolDefinitionsInput': ('praisonaiagents.hooks.events', 'BeforeToolDefinitionsInput'),
         'BeforeAgentInput': ('praisonaiagents.hooks.events', 'BeforeAgentInput'),
         'AfterAgentInput': ('praisonaiagents.hooks.events', 'AfterAgentInput'),
         'BeforeLLMInput': ('praisonaiagents.hooks.events', 'BeforeLLMInput'),
@@ -147,7 +144,6 @@ _LAZY_GROUPS = {
         'GatewayStartInput': ('praisonaiagents.hooks.events', 'GatewayStartInput'),
         'GatewayStopInput': ('praisonaiagents.hooks.events', 'GatewayStopInput'),
         'ScheduleTriggerInput': ('praisonaiagents.hooks.events', 'ScheduleTriggerInput'),
-        'JobCompletedInput': ('praisonaiagents.hooks.events', 'JobCompletedInput'),
     },
     'middleware_types': {
         'InvocationContext': ('praisonaiagents.hooks.middleware', 'InvocationContext'),

src/praisonai-agents/praisonaiagents/hooks/events.py

@@ -47,29 +47,6 @@ class AfterToolInput(HookInput):
         return base
 
 
-@dataclass
-class BeforeToolDefinitionsInput(HookInput):
-    """Input for BeforeToolDefinitions hooks.
-
-    Fired right after the advertised tool definitions are assembled for a
-    request and before they reach the LLM. Hooks should modify or filter the
-    ``tool_definitions`` list in place (e.g. ``data.tool_definitions[:] = ...``)
-    to redact parameters, append usage guidance to descriptions, or constrain
-    the advertised schema per request. This mirrors how BEFORE_LLM mutates its
-    payload in place; only in-place mutations are adopted by the runtime.
-    """
-    tool_definitions: List[Dict[str, Any]] = field(default_factory=list)
-    model: str = ""
-
-    def to_dict(self) -> Dict[str, Any]:
-        base = super().to_dict()
-        base.update({
-            "tool_definitions_count": len(self.tool_definitions),
-            "model": self.model,
-        })
-        return base
-
-
 @dataclass
 class BeforeAgentInput(HookInput):
     """Input for BeforeAgent hooks."""
@@ -348,37 +325,3 @@ class ScheduleTriggerInput(HookInput):
             "message": self.message[:500] if self.message else "",
         })
         return base
-
-
-@dataclass
-class JobCompletedInput(HookInput):
-    """Input for JOB_COMPLETED hooks (a background job finished).
-
-    Emitted when a background subagent/job launched via
-    ``spawn_subagent(background=True)`` reaches a terminal state
-    (completed or failed). Carries the optional origin/delivery context
-    captured at spawn time so a gateway can route the result back to the
-    originating conversation without an active turn.
-    """
-    job_id: str = ""
-    status: str = ""
-    result: Any = None
-    error: Optional[str] = None
-    deliver: str = ""
-    platform: str = ""
-    chat_id: str = ""
-    thread_id: str = ""
-
-    def to_dict(self) -> Dict[str, Any]:
-        base = super().to_dict()
-        base.update({
-            "job_id": self.job_id,
-            "status": self.status,
-            "result": self.result,
-            "error": self.error,
-            "deliver": self.deliver,
-            "platform": self.platform,
-            "chat_id": self.chat_id,
-            "thread_id": self.thread_id,
-        })
-        return base

src/praisonai-agents/praisonaiagents/hooks/types.py

@@ -23,7 +23,6 @@ class HookEvent(str, Enum):
     # Tool lifecycle
     BEFORE_TOOL = "before_tool"
     AFTER_TOOL = "after_tool"
-    BEFORE_TOOL_DEFINITIONS = "before_tool_definitions"
     
     # Agent lifecycle
     BEFORE_AGENT = "before_agent"
@@ -69,9 +68,6 @@ class HookEvent(str, Enum):
     SCHEDULE_REMOVE = "schedule_remove"
     SCHEDULE_TRIGGER = "schedule_trigger"
 
-    # Background job lifecycle
-    JOB_COMPLETED = "job_completed"  # A background job finished (ok or error)
-
     # Kanban task lifecycle (wrapper dispatcher + tools emit these)
     KANBAN_TASK_CREATED = "kanban_task_created"
     KANBAN_TASK_CLAIMED = "kanban_task_claimed"

src/praisonai-agents/praisonaiagents/kanban/__init__.py

@@ -9,23 +9,15 @@ interface without coupling the core to SQLite or other heavy implementations.
 from praisonaiagents.kanban.protocols import (
     KanbanStoreProtocol,
     KanbanTaskProtocol,
-    KanbanRunProtocol,
-    KanbanRunsProtocol,
     KanbanCommentingProtocol,
     KanbanLinkingProtocol,
-    KanbanPromotionProtocol,
-    KanbanReclaimProtocol,
     VALID_KANBAN_STATUSES,
 )
 
 __all__ = [
     "KanbanStoreProtocol",
     "KanbanTaskProtocol",
-    "KanbanRunProtocol",
-    "KanbanRunsProtocol",
     "KanbanCommentingProtocol", 
     "KanbanLinkingProtocol",
-    "KanbanPromotionProtocol",
-    "KanbanReclaimProtocol",
     "VALID_KANBAN_STATUSES",
 ]

src/praisonai-agents/praisonaiagents/kanban/protocols.py

@@ -42,33 +42,6 @@ class KanbanTaskProtocol(TypedDict, total=False):
     board: str
     created_at: float
     updated_at: float
-    # Claim lease / reclamation fields (optional; populated while running).
-    # Timestamps are serialized as ISO 8601 strings by Task.to_dict().
-    claim_lock: str | None
-    claim_expires: str | None
-    worker_pid: int | None
-    last_heartbeat_at: str | None
-    # Retry / run-history fields (optional).
-    max_retries: int | None
-    consecutive_failures: int
-    current_run_id: int | None
-
-
-class KanbanRunProtocol(TypedDict, total=False):
-    """Typed dict shape for a single task attempt (run).
-
-    One row per attempt: outcome plus a structured summary/metadata handoff and
-    any error. Surfaced to retrying workers and linked children.
-    """
-    id: int
-    task_id: str
-    profile: str
-    outcome: str | None  # completed/blocked/crashed/failed/gave_up
-    summary: str
-    metadata: dict
-    error: str
-    started_at: str | None  # ISO-8601 string (matches TaskRun.to_dict())
-    ended_at: str | None    # ISO-8601 string; None while the run is open
 
 
 @runtime_checkable
@@ -214,57 +187,6 @@ class KanbanCommentingProtocol(Protocol):
         ...
 
 
-@runtime_checkable
-class KanbanReclaimProtocol(Protocol):
-    """Extension protocol for durable claim leases and stale-claim reclamation.
-
-    Stores implementing this protocol support recovering tasks stranded by
-    crashed, killed, or hung workers. The dispatcher tick calls
-    ``reclaim_stale_claims`` to return such tasks to ``ready`` for re-dispatch.
-
-    This is kept separate from KanbanStoreProtocol so stores can adopt
-    reclamation incrementally without breaking isinstance checks on the core
-    protocol.
-    """
-
-    def claim_task(
-        self,
-        task_id: str,
-        worker_id: str,
-        *,
-        ttl_seconds: int = 900,
-        worker_pid: int | None = None,
-    ) -> bool:
-        """Claim a ready task with a lease (TTL) and optional owner PID.
-
-        Returns:
-            True if the claim succeeded.
-        """
-        ...
-
-    def heartbeat(
-        self,
-        task_id: str,
-        worker_id: str,
-        *,
-        ttl_seconds: int | None = None,
-    ) -> bool:
-        """Record a worker heartbeat, optionally extending the claim lease.
-
-        Returns:
-            True if the heartbeat was recorded (worker owns the claim).
-        """
-        ...
-
-    def reclaim_stale_claims(self, *, stale_timeout_seconds: int = 1800) -> list[str]:
-        """Reclaim running tasks whose lease expired and whose worker is dead/stale.
-
-        Returns:
-            List of task IDs returned to ``ready``.
-        """
-        ...
-
-
 @runtime_checkable 
 class KanbanLinkingProtocol(Protocol):
     """Extension protocol for kanban task linking functionality.
@@ -296,85 +218,4 @@ class KanbanLinkingProtocol(Protocol):
         Returns:
             True if unlinked successfully, False otherwise
         """
-        ...
-
-
-@runtime_checkable
-class KanbanPromotionProtocol(Protocol):
-    """Extension protocol for dependency-driven task promotion.
-
-    Implemented separately from KanbanStoreProtocol so that stores can opt
-    into auto-promotion without breaking isinstance checks on the core
-    protocol. This is the engine that turns a linked parent->child DAG into
-    a self-driving pipeline: the dispatcher calls ``recompute_ready`` each
-    tick before claiming work.
-    """
-
-    def recompute_ready(self) -> list[str]:
-        """Promote dependent tasks to 'ready' when all parents are terminal.
-
-        Scans tasks waiting on dependencies and advances any whose parent
-        tasks are all in a terminal state ('done'/'archived') to 'ready'.
-
-        Returns:
-            List of task IDs promoted to 'ready' in this pass.
-        """
-        ...
-
-
-@runtime_checkable
-class KanbanRunsProtocol(Protocol):
-    """Extension protocol for per-task attempt (run) history and retry.
-
-    Implemented separately from KanbanStoreProtocol so stores can optionally
-    support durable attempt history, structured handoff and a per-task
-    circuit-breaker without breaking isinstance checks on the core protocol.
-    """
-
-    def record_run(
-        self,
-        task_id: str,
-        outcome: str,
-        *,
-        profile: str = "",
-        summary: str | None = None,
-        metadata: dict | None = None,
-        error: str | None = None,
-    ) -> dict:
-        """Record a completed attempt (open + close in one call).
-
-        Args:
-            task_id: Task that was attempted.
-            outcome: One of completed/blocked/crashed/failed/gave_up.
-            profile: Optional worker/profile identifier.
-            summary: Structured summary of what was done (handoff).
-            metadata: Structured handoff fields (e.g. changed_files, tests_run).
-            error: Error text for failed/crashed attempts.
-
-        Returns:
-            The recorded run data.
-        """
-        ...
-
-    def get_runs(self, task_id: str) -> list[dict]:
-        """Return all attempts for a task, oldest first.
-
-        Args:
-            task_id: Task identifier.
-
-        Returns:
-            List of run data (KanbanRunProtocol shape).
-        """
-        ...
-
-    def record_failure(self, task_id: str, *, error: str | None = None) -> bool:
-        """Increment the consecutive-failure counter; auto-block at the limit.
-
-        Args:
-            task_id: Task that just failed an attempt.
-            error: Optional last error to attach when auto-blocking.
-
-        Returns:
-            True if the task was circuit-broken (auto-blocked) by this call.
-        """
         ...

src/praisonai-agents/praisonaiagents/llm/__init__.py

@@ -171,26 +171,6 @@ def __getattr__(name):
             from .sanitize import sanitize_text
             _lazy_cache[name] = sanitize_text
             return sanitize_text
-        elif name == "PanelLLM":
-            from .panel import PanelLLM
-            _lazy_cache[name] = PanelLLM
-            return PanelLLM
-        elif name == "create_panel_llm":
-            from .panel import create_panel_llm
-            _lazy_cache[name] = create_panel_llm
-            return create_panel_llm
-        elif name == "register_panel_preset":
-            from .panel import register_panel_preset
-            _lazy_cache[name] = register_panel_preset
-            return register_panel_preset
-        elif name == "resolve_panel_config":
-            from .panel import resolve_panel_config
-            _lazy_cache[name] = resolve_panel_config
-            return resolve_panel_config
-        elif name == "is_panel_descriptor":
-            from .panel import is_panel_descriptor
-            _lazy_cache[name] = is_panel_descriptor
-            return is_panel_descriptor
         elif name == "ErrorCategory":
             from .error_classifier import ErrorCategory
             _lazy_cache[name] = ErrorCategory
@@ -235,12 +215,6 @@ __all__ = [
     "OpenAIAdapter",
     "UnifiedLLMDispatcher",
     "create_llm_dispatcher",
-    # Panel (multi-model) provider
-    "PanelLLM",
-    "create_panel_llm",
-    "register_panel_preset",
-    "resolve_panel_config",
-    "is_panel_descriptor",
     # Exceptions
     "LLMProviderError",
     "RateLimitError",

src/praisonai-agents/praisonaiagents/llm/failover.py

@@ -142,6 +142,22 @@ class AuthProfile:
         self.last_error = None
         self.last_error_time = None
 
+@runtime_checkable
+class FailoverProtocol(Protocol):
+    """Protocol for failover management."""
+    
+    def get_next_profile(self) -> Optional[AuthProfile]:
+        """Get the next available profile."""
+        ...
+    
+    def mark_failure(self, profile: AuthProfile, error: str) -> None:
+        """Mark a profile as failed."""
+        ...
+    
+    def mark_success(self, profile: AuthProfile) -> None:
+        """Mark a profile as successful."""
+        ...
+
 @dataclass
 class FailoverConfig:
     """Configuration for failover behavior.
@@ -387,27 +403,3 @@ class FailoverManager:
         """Reset all profiles to available status."""
         for profile in self._profiles:
             profile.reset()
-
-
-@runtime_checkable
-class FailoverProtocol(Protocol):
-    """Deprecated structural protocol for failover managers.
-
-    Retained only for backward compatibility with code that imports the deep
-    path ``praisonaiagents.llm.failover.FailoverProtocol`` or uses it for
-    ``isinstance`` checks. ``FailoverManager`` already satisfies this shape.
-    Prefer the public ``LLMFailoverProtocol`` (exported from
-    ``praisonaiagents.llm``) for new code.
-    """
-
-    def get_next_profile(self) -> Optional[AuthProfile]:
-        """Get the next available profile."""
-        ...
-
-    def mark_failure(self, profile: AuthProfile, error: str) -> None:
-        """Mark a profile as failed."""
-        ...
-
-    def mark_success(self, profile: AuthProfile) -> None:
-        """Mark a profile as successful."""
-        ...

src/praisonai-agents/praisonaiagents/llm/llm.py

@@ -191,15 +191,6 @@ class LLM:
     # Ollama-specific prompt constants
     OLLAMA_TOOL_USAGE_PROMPT = "Please analyze the request and use the available tools to help answer the question. Start by identifying what information you need."
     OLLAMA_FINAL_ANSWER_PROMPT = "Based on the tool results above, please provide the final answer to the original question."
-
-    # Step-limit finalisation constants (used when the tool loop hits max_iter)
-    STEP_LIMIT_WRAP_UP_PROMPT = (
-        "You have reached the step limit for this task. Do not call any tools. "
-        "Provide a final answer that summarises what you accomplished, what "
-        "remains unfinished, and any suggested next steps, using the tool "
-        "results already gathered."
-    )
-    STEP_LIMIT_FALLBACK_MESSAGE = "Reached the step limit before finishing this task."
     
     # Force tool usage prompt template (used when model ignores tools)
     FORCE_TOOL_USAGE_PROMPT = """You MUST use one of the available tools to answer this question.
@@ -932,156 +923,6 @@ Respond with ONLY a valid JSON tool call in this format:
         self._cached_subscription_creds = provider.refresh()
         return self._cached_subscription_creds
 
-    def _should_attempt_auth_refresh(self, e, attempt):
-        """Whether an auth-credential refresh should be attempted this attempt.
-
-        Side-effect-free predicate shared by the sync and async retry loops so
-        the async loop can decide to offload the blocking refresh to a thread.
-
-        Uses the pure ``classify_error_kind`` classifier directly rather than
-        ``resolve_failover_decision``: the latter mutates state (e.g. the idle
-        timeout circuit breaker) and is also called by ``_handle_retry_exception``
-        for the same exception, which would double-count those mutations.
-        """
-        if not (self._auth_provider_id and attempt == 0):
-            return False
-        return self.classify_error_kind(e) == "auth"
-
-    def _try_refresh_subscription_creds(self):
-        """Attempt a credential refresh, keeping failures non-fatal.
-
-        Wraps `_refresh_subscription_creds` so refresh errors never abort the
-        retry/failover flow. Returns the refreshed credentials or ``None``. This
-        is the blocking (network) step; the async loop runs it off the event
-        loop via ``asyncio.to_thread``.
-        """
-        try:
-            logging.info("Authentication error detected - attempting credential refresh")
-            return self._refresh_subscription_creds()
-        except Exception as refresh_error:  # noqa: BLE001 - refresh failures must stay non-fatal so retry/failover can continue
-            logging.warning(
-                "Failed to refresh subscription credentials for auth provider %r (%s). "
-                "Verify the provider login/configuration and retry or re-authenticate.",
-                self._auth_provider_id,
-                type(refresh_error).__name__,
-            )
-            return None
-
-    def _handle_retry_exception(self, e, attempt, kwargs, refreshed_creds=None):
-        """Decide retry vs raise from a failover decision. No sleep/await.
-
-        Shared decision logic used by both the sync (`_call_with_retry`) and
-        async (`_call_with_retry_async`) retry loops. Performs failover
-        bookkeeping (profile rotation, legacy failover kwargs update) but never
-        sleeps or awaits, so it is identical for both paths.
-
-        The blocking credential refresh itself is performed by the caller: the
-        sync loop calls `_try_refresh_subscription_creds()` inline, while the
-        async loop offloads it to a thread via ``asyncio.to_thread`` so it never
-        blocks the event loop. The already-refreshed credentials (if any) are
-        passed in via ``refreshed_creds``.
-
-        Args:
-            e: The exception raised by the wrapped call.
-            attempt: Zero-based attempt index for the current iteration.
-            kwargs: Keyword arguments for the wrapped call (may be updated).
-            refreshed_creds: Credentials already refreshed by the caller (off
-                the event loop for async), or ``None`` if no refresh was done.
-
-        Returns:
-            Tuple of (should_raise, category, retry_delay, error_str, kwargs):
-                should_raise: Whether the caller should re-raise immediately.
-                category: The error category/reason from the decision.
-                retry_delay: Seconds to wait before the next attempt.
-                error_str: String form of the exception.
-                kwargs: The (possibly updated) keyword arguments.
-        """
-        # Use new typed failover decision instead of old classification
-        decision = self.resolve_failover_decision(e, {"attempt": attempt + 1, "max_retries": self._max_retries})
-
-        error_str = str(e)
-
-        # Map decision to old variables for compatibility with existing logic
-        category = decision.reason
-        can_retry = decision.is_retryable
-        retry_delay = decision.backoff_ms / 1000.0  # Convert ms to seconds
-
-        # Apply refreshed subscription credentials (refresh I/O is done by the
-        # caller so the async loop can offload it off the event loop).
-        refreshed_auth = False
-        if category == "auth" and self._auth_provider_id and attempt == 0 and refreshed_creds:
-            # Rebuild parameters (don't clear cache), then re-apply the refreshed
-            # credentials *after* the rebuild. _build_completion_params merges the
-            # incoming kwargs last, so the failed attempt's stale api_key/base_url
-            # would otherwise overwrite the freshly refreshed credentials.
-            kwargs = self._build_completion_params(**kwargs)
-            kwargs["api_key"] = refreshed_creds.api_key
-            if refreshed_creds.base_url:
-                kwargs["base_url"] = refreshed_creds.base_url
-            if refreshed_creds.headers:
-                extra_headers = dict(kwargs.get("extra_headers") or {})
-                extra_headers.update(refreshed_creds.headers)
-                kwargs["extra_headers"] = extra_headers
-            # Retry immediately with refreshed credentials
-            can_retry = True
-            retry_delay = 0.0
-            refreshed_auth = True
-            logging.info("Subscription credentials refreshed, retrying...")
-
-        # A successful credential refresh fully resolves the auth error: retry
-        # immediately with fresh credentials and skip profile rotation so we
-        # neither mark the current profile failed nor overwrite the new creds.
-        if refreshed_auth:
-            return False, category, retry_delay, error_str, kwargs
-
-        # Handle different failover decision actions
-        if decision.action == "rotate_profile" and self._failover_manager:
-            if self._current_profile:
-                is_rate_limit = (category == "rate_limit")
-                self._failover_manager.mark_failure(
-                    self._current_profile, error_str, is_rate_limit=is_rate_limit
-                )
-            next_profile = self._failover_manager.get_next_profile()
-            if next_profile and next_profile != self._current_profile:
-                self._switch_to_profile(next_profile)
-                self._current_profile = next_profile
-                # Update the kwargs with new profile values for the next retry
-                if "api_key" in kwargs:
-                    kwargs["api_key"] = self.api_key
-                if "base_url" in kwargs:
-                    kwargs["base_url"] = self.base_url
-                if "model" in kwargs:
-                    kwargs["model"] = self.model
-                logging.info(f"Failover: switched to profile '{next_profile.name}'")
-            else:
-                # No alternate profile available - retrying would just hit the
-                # same failing profile, so surface the error instead.
-                can_retry = False
-        # Legacy failover for compatibility (when decision is retry but failover is configured)
-        elif self._failover_manager and self._current_profile and decision.action == "retry":
-            is_rate_limit = (category == "rate_limit")
-            self._failover_manager.mark_failure(
-                self._current_profile, error_str, is_rate_limit=is_rate_limit
-            )
-            next_profile = self._failover_manager.get_next_profile()
-            if next_profile and next_profile != self._current_profile:
-                self._switch_to_profile(next_profile)
-                self._current_profile = next_profile
-                # Update the kwargs with new profile values for the next retry
-                if "api_key" in kwargs:
-                    kwargs["api_key"] = self.api_key
-                if "base_url" in kwargs:
-                    kwargs["base_url"] = self.base_url
-                if "model" in kwargs:
-                    kwargs["model"] = self.model
-                # Enable retry for profile switch even if originally non-retryable
-                can_retry = True
-                retry_delay = 0.0
-                logging.info(f"Failover: switched to profile '{next_profile.name}'")
-
-        should_raise = decision.action == "surface_error" or not can_retry
-        return should_raise, category, retry_delay, error_str, kwargs
-
     def _call_with_retry(self, func, *args, **kwargs):
         """Call a function with automatic retry on rate limit errors and failover support.
 
@@ -1116,18 +957,74 @@ Respond with ONLY a valid JSON tool call in this format:
                 return result
 
             except Exception as e:
+                # Use new typed failover decision instead of old classification
+                decision = self.resolve_failover_decision(e, {"attempt": attempt + 1, "max_retries": self._max_retries})
+                
                 last_error = e
+                error_str = str(e)
+                
+                # Map decision to old variables for compatibility with existing logic
+                category = decision.reason
+                can_retry = decision.is_retryable
+                retry_delay = decision.backoff_ms / 1000.0  # Convert ms to seconds
 
-                # Blocking credential refresh runs inline in the sync path.
-                refreshed_creds = None
-                if self._should_attempt_auth_refresh(e, attempt):
-                    refreshed_creds = self._try_refresh_subscription_creds()
+                # Check for auth errors and try refreshing subscription credentials
+                if category == "auth" and self._auth_provider_id and attempt == 0:
+                    try:
+                        logging.info("Authentication error detected - attempting credential refresh")
+                        refreshed_creds = self._refresh_subscription_creds()
+                        if refreshed_creds:
+                            # Update parameters with refreshed credentials (don't clear cache)
+                            kwargs = self._build_completion_params(**kwargs)
+                            # Retry immediately with refreshed credentials
+                            can_retry = True
+                            retry_delay = 0.0
+                            logging.info("Subscription credentials refreshed, retrying...")
+                    except Exception as refresh_error:
+                        logging.warning(f"Failed to refresh subscription credentials: {refresh_error}")
 
-                should_raise, category, retry_delay, error_str, kwargs = (
-                    self._handle_retry_exception(e, attempt, kwargs, refreshed_creds=refreshed_creds)
-                )
-
-                if should_raise:
+                # Handle different failover decision actions
+                if decision.action == "rotate_profile" and self._failover_manager:
+                    if self._current_profile:
+                        is_rate_limit = (category == "rate_limit")
+                        self._failover_manager.mark_failure(
+                            self._current_profile, error_str, is_rate_limit=is_rate_limit
+                        )
+                    next_profile = self._failover_manager.get_next_profile()
+                    if next_profile and next_profile != self._current_profile:
+                        self._switch_to_profile(next_profile)
+                        self._current_profile = next_profile
+                        # Update the kwargs with new profile values for the next retry
+                        if "api_key" in kwargs:
+                            kwargs["api_key"] = self.api_key
+                        if "base_url" in kwargs:
+                            kwargs["base_url"] = self.base_url
+                        if "model" in kwargs:
+                            kwargs["model"] = self.model
+                        logging.info(f"Failover: switched to profile '{next_profile.name}'")
+                # Legacy failover for compatibility (when decision is retry but failover is configured)
+                elif self._failover_manager and self._current_profile and decision.action == "retry":
+                    is_rate_limit = (category == "rate_limit")
+                    self._failover_manager.mark_failure(
+                        self._current_profile, error_str, is_rate_limit=is_rate_limit
+                    )
+                    next_profile = self._failover_manager.get_next_profile()
+                    if next_profile and next_profile != self._current_profile:
+                        self._switch_to_profile(next_profile)
+                        self._current_profile = next_profile
+                        # Update the kwargs with new profile values for the next retry
+                        if "api_key" in kwargs:
+                            kwargs["api_key"] = self.api_key
+                        if "base_url" in kwargs:
+                            kwargs["base_url"] = self.base_url
+                        if "model" in kwargs:
+                            kwargs["model"] = self.model
+                        # Enable retry for profile switch even if originally non-retryable
+                        can_retry = True
+                        retry_delay = 0.0
+                        logging.info(f"Failover: switched to profile '{next_profile.name}'")
+                
+                if decision.action == "surface_error" or not can_retry:
                     raise
 
                 if attempt < self._max_retries:
@@ -1192,21 +1089,74 @@ Respond with ONLY a valid JSON tool call in this format:
                 return result
 
             except Exception as e:
+                # Use new typed failover decision instead of old classification
+                decision = self.resolve_failover_decision(e, {"attempt": attempt + 1, "max_retries": self._max_retries})
+                
                 last_error = e
+                error_str = str(e)
+                
+                # Map decision to old variables for compatibility with existing logic
+                category = decision.reason
+                can_retry = decision.is_retryable
+                retry_delay = decision.backoff_ms / 1000.0  # Convert ms to seconds
 
-                # Offload the blocking credential refresh to a thread so it
-                # never blocks the event loop in the async path.
-                refreshed_creds = None
-                if self._should_attempt_auth_refresh(e, attempt):
-                    refreshed_creds = await asyncio.to_thread(
-                        self._try_refresh_subscription_creds
+                # Check for auth errors and try refreshing subscription credentials
+                if category == "auth" and self._auth_provider_id and attempt == 0:
+                    try:
+                        logging.info("Authentication error detected - attempting credential refresh")
+                        refreshed_creds = self._refresh_subscription_creds()
+                        if refreshed_creds:
+                            # Update parameters with refreshed credentials (don't clear cache)
+                            kwargs = self._build_completion_params(**kwargs)
+                            # Retry immediately with refreshed credentials
+                            can_retry = True
+                            retry_delay = 0.0
+                            logging.info("Subscription credentials refreshed, retrying...")
+                    except Exception as refresh_error:
+                        logging.warning(f"Failed to refresh subscription credentials: {refresh_error}")
+
+                # Handle different failover decision actions
+                if decision.action == "rotate_profile" and self._failover_manager:
+                    if self._current_profile:
+                        is_rate_limit = (category == "rate_limit")
+                        self._failover_manager.mark_failure(
+                            self._current_profile, error_str, is_rate_limit=is_rate_limit
+                        )
+                    next_profile = self._failover_manager.get_next_profile()
+                    if next_profile and next_profile != self._current_profile:
+                        self._switch_to_profile(next_profile)
+                        self._current_profile = next_profile
+                        # Update the kwargs with new profile values for the next retry
+                        if "api_key" in kwargs:
+                            kwargs["api_key"] = self.api_key
+                        if "base_url" in kwargs:
+                            kwargs["base_url"] = self.base_url
+                        if "model" in kwargs:
+                            kwargs["model"] = self.model
+                        logging.info(f"Failover: switched to profile '{next_profile.name}'")
+                # Legacy failover for compatibility (when decision is retry but failover is configured)
+                elif self._failover_manager and self._current_profile and decision.action == "retry":
+                    is_rate_limit = (category == "rate_limit")
+                    self._failover_manager.mark_failure(
+                        self._current_profile, error_str, is_rate_limit=is_rate_limit
                     )
-
-                should_raise, category, retry_delay, error_str, kwargs = (
-                    self._handle_retry_exception(e, attempt, kwargs, refreshed_creds=refreshed_creds)
-                )
-
-                if should_raise:
+                    next_profile = self._failover_manager.get_next_profile()
+                    if next_profile and next_profile != self._current_profile:
+                        self._switch_to_profile(next_profile)
+                        self._current_profile = next_profile
+                        # Update the kwargs with new profile values for the next retry
+                        if "api_key" in kwargs:
+                            kwargs["api_key"] = self.api_key
+                        if "base_url" in kwargs:
+                            kwargs["base_url"] = self.base_url
+                        if "model" in kwargs:
+                            kwargs["model"] = self.model
+                        # Enable retry for profile switch even if originally non-retryable
+                        can_retry = True
+                        retry_delay = 0.0
+                        logging.info(f"Failover: switched to profile '{next_profile.name}'")
+                
+                if decision.action == "surface_error" or not can_retry:
                     raise
 
                 if attempt < self._max_retries:
@@ -1215,21 +1165,6 @@ Respond with ONLY a valid JSON tool call in this format:
                         f"waiting {retry_delay:.1f}s before retry..."
                     )
 
-                    # P5: Emit retry callback for CLI visibility.
-                    # Use the async dispatcher so a sync callback runs in a
-                    # thread executor (never blocking the event loop) and any
-                    # async-registered 'retry' callback is also awaited.
-                    try:
-                        from ..main import execute_callback
-                        await execute_callback('retry',
-                            attempt=attempt + 1,
-                            max_attempts=self._max_retries + 1,
-                            error=error_str[:200],
-                            retry_in_seconds=retry_delay
-                        )
-                    except ImportError:
-                        pass
-
                     if self._rate_limiter is not None:
                         await self._rate_limiter.wait_for_retry_async(retry_delay)
                     else:
@@ -1529,42 +1464,6 @@ Result: {tool_result_str}
 Now provide your final answer using this result. Summarize the information naturally for the user."""
             }
 
-    def _try_append_multimodal_tool_result(
-        self,
-        messages: List[Dict[str, Any]],
-        tool_result: Any,
-        tool_call_id: str,
-        function_name: Optional[str] = None,
-        deferred_followups: Optional[List[Dict[str, Any]]] = None,
-    ) -> bool:
-        """Append a multimodal tool result if the result carries media.
-
-        The ``tool`` reply is appended in-place so all tool replies for the
-        assistant turn stay consecutive (provider contract). The media-bearing
-        ``user`` follow-up message is collected into ``deferred_followups`` for
-        the caller to flush *after* the whole tool_calls batch is processed; if
-        no collector is supplied it is appended directly (single-call paths).
-
-        Returns True if the result was multimodal (caller should skip its
-        default text-only tool message), False otherwise (no regression).
-        """
-        try:
-            from ..agent.tool_execution import build_tool_result_message_pair
-            pair = build_tool_result_message_pair(
-                tool_result, tool_call_id, function_name=function_name
-            )
-            if pair:
-                tool_message, followup_message = pair
-                messages.append(tool_message)
-                if deferred_followups is not None:
-                    deferred_followups.append(followup_message)
-                else:
-                    messages.append(followup_message)
-                return True
-        except Exception as e:
-            logging.debug(f"Multimodal tool result formatting skipped: {e}")
-        return False
-
     def _get_tool_names_for_prompt(self, formatted_tools: Optional[List]) -> str:
         """Extract tool names from formatted tools for prompts."""
         if not formatted_tools:
@@ -1840,90 +1739,6 @@ Now provide your final answer using this result. Summarize the information natur
                 
         return False, None, iteration_count
 
-    def _finalise_on_limit(self, messages: List[Dict], response_text: str,
-                           temperature: float = 0.2, **kwargs) -> str:
-        """
-        Force a final tools-disabled answer when the tool-calling loop hits max_iter.
-
-        Instead of returning a canned placeholder, this performs exactly one extra
-        LLM call with tools disabled (tool_choice="none") and a short wrap-up nudge,
-        asking the model to summarise what it accomplished, what remains unfinished,
-        and any next steps using the accumulated tool results already in context.
-
-        Falls back to the prior placeholder text if the extra call fails, so behaviour
-        never regresses.
-
-        Args:
-            messages: Current message history (already contains tool results).
-            response_text: Any text emitted on the final turn (used as fallback).
-            temperature: Sampling temperature for the wrap-up call.
-
-        Returns:
-            The synthesised final answer, or a safe fallback string.
-        """
-        wrap_up = {"role": "user", "content": self.STEP_LIMIT_WRAP_UP_PROMPT}
-        try:
-            safe_kwargs = {k: v for k, v in kwargs.items() if k != 'reasoning_steps'}
-            final_params = self._build_completion_params(
-                messages=messages + [wrap_up],
-                temperature=temperature,
-                stream=False,
-                tool_choice="none",
-                **safe_kwargs
-            )
-            # Ensure no tools are advertised even if the builder injects
-            # runtime tools (e.g. web_fetch, Claude memory); tool_choice="none"
-            # with tools present is invalid/undesirable for the wrap-up call.
-            # Drop the now-meaningless tool_choice too, as some providers reject
-            # tool_choice when no tools are supplied.
-            final_params.pop("tools", None)
-            final_params.pop("tool_choice", None)
-            # Route through the retry wrapper so this bounded final call gets the
-            # same rate-limit/failover resilience as every other completion.
-            resp = self._completion_with_retry(**final_params)
-            summary = resp["choices"][0]["message"].get("content")
-            if summary and summary.strip():
-                return summary.strip()
-        except Exception as e:
-            logging.warning(f"Step-limit finalisation call failed, using fallback: {e}")
-
-        if response_text and response_text.strip():
-            return response_text.strip()
-        return self.STEP_LIMIT_FALLBACK_MESSAGE
-
-    async def _finalise_on_limit_async(self, messages: List[Dict], response_text: str,
-                                       temperature: float = 0.2, **kwargs) -> str:
-        """Async counterpart of :meth:`_finalise_on_limit`."""
-        wrap_up = {"role": "user", "content": self.STEP_LIMIT_WRAP_UP_PROMPT}
-        try:
-            safe_kwargs = {k: v for k, v in kwargs.items() if k != 'reasoning_steps'}
-            final_params = self._build_completion_params(
-                messages=messages + [wrap_up],
-                temperature=temperature,
-                stream=False,
-                tool_choice="none",
-                **safe_kwargs
-            )
-            # Ensure no tools are advertised even if the builder injects
-            # runtime tools (e.g. web_fetch, Claude memory); tool_choice="none"
-            # with tools present is invalid/undesirable for the wrap-up call.
-            # Drop the now-meaningless tool_choice too, as some providers reject
-            # tool_choice when no tools are supplied.
-            final_params.pop("tools", None)
-            final_params.pop("tool_choice", None)
-            # Route through the retry wrapper so this bounded final call gets the
-            # same rate-limit/failover resilience as every other completion.
-            resp = await self._acompletion_with_retry(**final_params)
-            summary = resp["choices"][0]["message"].get("content")
-            if summary and summary.strip():
-                return summary.strip()
-        except Exception as e:
-            logging.warning(f"Step-limit finalisation call failed, using fallback: {e}")
-
-        if response_text and response_text.strip():
-            return response_text.strip()
-        return self.STEP_LIMIT_FALLBACK_MESSAGE
-
     def _needs_system_message_skip(self) -> bool:
         """Check if this model requires skipping system messages"""
         if not self.model:
@@ -2495,10 +2310,7 @@ Now provide your final answer using this result. Summarize the information natur
 
                             # Safety: break after max_iter iterations
                             if iteration_count >= self.max_iter:
-                                final_response_text = self._finalise_on_limit(
-                                    messages, response_text, temperature=temperature,
-                                    **{k: v for k, v in kwargs.items() if k != 'reasoning_steps'}
-                                )
+                                final_response_text = response_text.strip() if response_text else "Task completed."
                                 break
 
                             iteration_count += 1
@@ -3188,10 +3000,6 @@ Now provide your final answer using this result. Summarize the information natur
                             tool_calls = tool_calls[:remaining_calls]
                             logging.warning(f"Limiting batch to {remaining_calls} tool calls to stay within limit of {max_tool_calls_per_turn}.")
                         
-                        # Collect media-bearing follow-up messages so they are
-                        # flushed only AFTER every tool reply for this assistant
-                        # turn, keeping all tool replies consecutive (provider contract).
-                        _deferred_media_followups: List[Dict[str, Any]] = []
                         for tool_call in tool_calls:
                             # Handle both object and dict access patterns
                             is_ollama = self._is_ollama_provider()
@@ -3256,13 +3064,6 @@ Now provide your final answer using this result. Summarize the information natur
                             if self._is_ollama_provider():
                                 # For Ollama, use user role and format as natural language
                                 messages.append(self._format_ollama_tool_result_message(function_name, tool_result))
-                            elif self._try_append_multimodal_tool_result(
-                                messages, tool_result, tool_call_id,
-                                function_name=function_name,
-                                deferred_followups=_deferred_media_followups,
-                            ):
-                                # Multimodal result (image/file) emitted as model-visible parts
-                                pass
                             else:
                                 # For other providers, use tool role with tool_call_id
                                 # Format error results more clearly
@@ -3284,12 +3085,7 @@ Now provide your final answer using this result. Summarize the information natur
                             # This mimics the logic from agent.py lines 1004-1007
                             if function_name == "sequentialthinking" and arguments.get("nextThoughtNeeded", False):
                                 should_continue = True
-
-                        # Flush deferred media follow-ups after all tool replies
-                        # for this turn have been appended (provider contract).
-                        if _deferred_media_followups:
-                            messages.extend(_deferred_media_followups)
-
+                        
                         # If we should continue, increment iteration and continue loop
                         if should_continue:
                             iteration_count += 1
@@ -3320,10 +3116,10 @@ Now provide your final answer using this result. Summarize the information natur
                         
                         # Safety check: prevent infinite loops for any provider
                         if iteration_count >= self.max_iter:
-                            final_response_text = self._finalise_on_limit(
-                                messages, response_text, temperature=temperature,
-                                **{k: v for k, v in kwargs.items() if k != 'reasoning_steps'}
-                            )
+                            if tool_results:
+                                final_response_text = "Task completed successfully based on tool execution results."
+                            else:
+                                final_response_text = response_text.strip() if response_text else "Task completed."
                             break
                         
                         # Otherwise, continue the loop to get final response with tool results
@@ -4260,10 +4056,7 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                             })
 
                         if iteration_count >= self.max_iter:
-                            final_response_text = await self._finalise_on_limit_async(
-                                messages, response_text, temperature=temperature,
-                                **{k: v for k, v in kwargs.items() if k != 'reasoning_steps'}
-                            )
+                            final_response_text = response_text.strip() if response_text else "Task completed."
                             break
 
                         iteration_count += 1
@@ -4461,10 +4254,6 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                         logging.warning(f"Limiting batch to {remaining_calls} tool calls to stay within limit of {max_tool_calls_per_turn}.")
                     
                     tool_results = []  # Store current iteration tool results
-                    # Collect media-bearing follow-up messages so they are
-                    # flushed only AFTER every tool reply for this assistant
-                    # turn, keeping all tool replies consecutive (provider contract).
-                    _deferred_media_followups: List[Dict[str, Any]] = []
                     for tool_call in tool_calls:
                         # Handle both object and dict access patterns
                         is_ollama = self._is_ollama_provider()
@@ -4490,13 +4279,6 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                         if self._is_ollama_provider():
                             # For Ollama, use user role and format as natural language
                             messages.append(self._format_ollama_tool_result_message(function_name, tool_result))
-                        elif self._try_append_multimodal_tool_result(
-                            messages, tool_result, tool_call_id,
-                            function_name=function_name,
-                            deferred_followups=_deferred_media_followups,
-                        ):
-                            # Multimodal result (image/file) emitted as model-visible parts
-                            pass
                         else:
                             # For other providers, use tool role with tool_call_id
                             # Format error results more clearly
@@ -4514,11 +4296,6 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                                 "content": content
                             })
 
-                    # Flush deferred media follow-ups after all tool replies
-                    # for this turn have been appended (provider contract).
-                    if _deferred_media_followups:
-                        messages.extend(_deferred_media_followups)
-
                     # For Ollama, add explicit prompt if we need a final answer
                     if self._is_ollama_provider() and iteration_count > 0:
                         # Add an explicit prompt for Ollama to generate the final answer
@@ -4672,10 +4449,10 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                     
                     # Safety check: prevent infinite loops for any provider
                     if iteration_count >= self.max_iter:
-                        final_response_text = await self._finalise_on_limit_async(
-                            messages, response_text, temperature=temperature,
-                            **{k: v for k, v in kwargs.items() if k != 'reasoning_steps'}
-                        )
+                        if tool_results:
+                            final_response_text = "Task completed successfully based on tool execution results."
+                        else:
+                            final_response_text = response_text.strip() if response_text else "Task completed."
                         break
                     
                     # Continue the loop to check if more tools are needed

src/praisonai-agents/praisonaiagents/llm/openai_client.py

@@ -41,38 +41,6 @@ def _get_openai_classes():
     openai = _get_openai()
     return openai.OpenAI, openai.AsyncOpenAI
 
-
-def _try_append_multimodal_tool_result(
-    messages, tool_result, tool_call_id, function_name=None, deferred_followups=None
-) -> bool:
-    """Append a multimodal (image/file) tool result if present.
-
-    The ``tool`` reply is appended in-place so all tool replies for the
-    assistant turn stay consecutive (provider contract). The media-bearing
-    ``user`` follow-up is collected into ``deferred_followups`` for the caller
-    to flush after the whole batch; if no collector is supplied it is appended
-    directly. External tool text parts are fenced via ``function_name``.
-
-    Returns True if the result was multimodal (caller should skip its default
-    text-only tool message); False otherwise for the unchanged path.
-    """
-    try:
-        from ..agent.tool_execution import build_tool_result_message_pair
-        pair = build_tool_result_message_pair(
-            tool_result, tool_call_id, function_name=function_name
-        )
-        if pair:
-            tool_message, followup_message = pair
-            messages.append(tool_message)
-            if deferred_followups is not None:
-                deferred_followups.append(followup_message)
-            else:
-                messages.append(followup_message)
-            return True
-    except Exception as e:
-        logging.debug(f"Multimodal tool result formatting skipped: {e}")
-    return False
-
 def _get_rich_console():
     """Lazy import rich Console."""
     global _rich_console
@@ -1689,9 +1657,6 @@ class OpenAIClient:
                     "tool_calls": serializable_tool_calls
                 })
                 
-                # Collect media-bearing follow-ups to flush after all tool
-                # replies for this turn (keeps tool replies consecutive).
-                _deferred_media_followups = []
                 for tool_call in tool_calls:
                     # Handle both ToolCall dataclass and OpenAI object
                     if isinstance(tool_call, ToolCall):
@@ -1718,20 +1683,11 @@ class OpenAIClient:
                         tool_output=results_str[:200] if results_str else None
                     )
                     
-                    _tc_id = tool_call.id if hasattr(tool_call, 'id') else tool_call['id']
-                    if not _try_append_multimodal_tool_result(
-                        messages, tool_result, _tc_id,
-                        function_name=function_name,
-                        deferred_followups=_deferred_media_followups,
-                    ):
-                        messages.append({
-                            "role": "tool",
-                            "tool_call_id": _tc_id,
-                            "content": results_str
-                        })
-
-                if _deferred_media_followups:
-                    messages.extend(_deferred_media_followups)
+                    messages.append({
+                        "role": "tool",
+                        "tool_call_id": tool_call.id if hasattr(tool_call, 'id') else tool_call['id'],
+                        "content": results_str
+                    })
                 
                 # Continue the loop to allow more tool calls
                 # The model will see tool results and can make additional tool calls
@@ -1903,9 +1859,6 @@ class OpenAIClient:
                     "tool_calls": serializable_tool_calls
                 })
                 
-                # Collect media-bearing follow-ups to flush after all tool
-                # replies for this turn (keeps tool replies consecutive).
-                _deferred_media_followups = []
                 for tool_call in tool_calls:
                     # Handle both ToolCall dataclass and OpenAI object
                     if isinstance(tool_call, ToolCall):
@@ -1939,20 +1892,11 @@ class OpenAIClient:
                     # Trigger callback with result
                     display_tool_call_fn(f"Function {function_name} returned: {results_str[:200]}{'...' if len(results_str) > 200 else ''}", console=console if verbose else None)
                     
-                    _tc_id = tool_call.id if hasattr(tool_call, 'id') else tool_call['id']
-                    if not _try_append_multimodal_tool_result(
-                        messages, tool_result, _tc_id,
-                        function_name=function_name,
-                        deferred_followups=_deferred_media_followups,
-                    ):
-                        messages.append({
-                            "role": "tool",
-                            "tool_call_id": _tc_id,
-                            "content": results_str
-                        })
-
-                if _deferred_media_followups:
-                    messages.extend(_deferred_media_followups)
+                    messages.append({
+                        "role": "tool",
+                        "tool_call_id": tool_call.id if hasattr(tool_call, 'id') else tool_call['id'],
+                        "content": results_str
+                    })
                 
                 # Continue the loop to allow more tool calls
                 # The model will see tool results and can make additional tool calls
@@ -2102,9 +2046,6 @@ class OpenAIClient:
                         "tool_calls": serializable_tool_calls
                     })
                     
-                    # Collect media-bearing follow-ups to flush after all tool
-                    # replies for this turn (keeps tool replies consecutive).
-                    _deferred_media_followups = []
                     for tool_call in tool_calls:
                         # Handle both ToolCall dataclass and OpenAI object
                         try:
@@ -2142,21 +2083,11 @@ class OpenAIClient:
                         if verbose:
                             yield f"\n[Function result: {results_str}]"
                         
-                        _tc_id = tool_call.id if hasattr(tool_call, 'id') else tool_call['id']
-                        _tool_result_for_mm = locals().get('tool_result')
-                        if not _try_append_multimodal_tool_result(
-                            messages, _tool_result_for_mm, _tc_id,
-                            function_name=function_name,
-                            deferred_followups=_deferred_media_followups,
-                        ):
-                            messages.append({
-                                "role": "tool",
-                                "tool_call_id": _tc_id,
-                                "content": results_str
-                            })
-
-                    if _deferred_media_followups:
-                        messages.extend(_deferred_media_followups)
+                        messages.append({
+                            "role": "tool",
+                            "tool_call_id": tool_call.id if hasattr(tool_call, 'id') else tool_call['id'],
+                            "content": results_str
+                        })
                     
                     # Continue the loop to allow more tool calls
                     iteration_count += 1

src/praisonai-agents/praisonaiagents/llm/panel.py

@@ -1,351 +0,0 @@
-"""
-Panel (Mixture-of-Agents) LLM provider.
-
-A ``PanelLLM`` is a *model selection*, not an orchestration primitive. One or
-more advisory **reference** models run first (no tools, trimmed conversation
-view); their outputs are folded into private context that is appended to the
-**tail of the latest user turn** — below any stable cached prefix, so Anthropic
-prompt caching on the system message is preserved. A single **aggregator** model
-is the real acting model: it inherits the full normal agent loop (tool calls,
-hooks, session) from :class:`~praisonaiagents.llm.llm.LLM`.
-
-Selectable exactly like any other model::
-
-    # Inline dict descriptor (no registration needed):
-    Agent(llm={"provider": "panel", "references": [...], "aggregator": "..."})
-
-    # Named preset (register it first):
-    register_panel_preset("deep", {"references": [...], "aggregator": "..."})
-    Agent(llm="panel:deep")
-
-No presets are bundled by the core SDK; ``panel:<name>`` strings resolve against
-presets registered via :func:`register_panel_preset` (e.g. by the wrapper, CLI,
-or YAML layer). YAML / CLI / bot ``/model`` paths flow the ``panel:<name>``
-string through unchanged because resolution happens in core model resolution.
-"""
-
-import hashlib
-import logging
-from collections import OrderedDict
-from typing import Any, Dict, List, Optional, Union
-
-from .llm import LLM
-
-logger = logging.getLogger(__name__)
-
-
-# =============================================================================
-# Panel preset registry
-# =============================================================================
-# Named presets keyed by name. Resolved when a ``panel:<name>`` descriptor is
-# selected. Wrapper/CLI/YAML can register additional presets at import time via
-# ``register_panel_preset``.
-
-PANEL_PRESETS: Dict[str, Dict[str, Any]] = {}
-
-
-def register_panel_preset(name: str, config: Dict[str, Any]) -> None:
-    """Register (or override) a named panel preset.
-
-    Args:
-        name: Preset name (used as ``panel:<name>``).
-        config: Dict with ``references`` (list[str]), ``aggregator`` (str),
-            and optional ``enabled`` (bool, default True).
-    """
-    PANEL_PRESETS[name] = dict(config)
-
-
-def is_panel_descriptor(llm: Any) -> bool:
-    """Return True if ``llm`` selects a panel provider.
-
-    Accepts ``"panel:<name>"`` strings and ``{"provider": "panel", ...}`` dicts.
-    """
-    if isinstance(llm, str):
-        return llm.startswith("panel:")
-    if isinstance(llm, dict):
-        return llm.get("provider") == "panel"
-    return False
-
-
-def resolve_panel_config(llm: Union[str, Dict[str, Any]]) -> Dict[str, Any]:
-    """Resolve a panel descriptor into a normalized config dict.
-
-    Returns a dict with keys ``references`` (list[str]), ``aggregator`` (str),
-    ``enabled`` (bool), and ``options`` (dict) carrying any extra provider/model
-    settings (e.g. ``base_url``, ``api_key``, ``temperature``) so they survive
-    both the dict-descriptor and named-preset resolution paths.
-
-    Raises:
-        ValueError: if the preset is unknown, the config is incomplete, or a
-            recursion guard is violated (a reference/aggregator is itself a
-            panel descriptor).
-    """
-    if isinstance(llm, str):
-        name = llm.split(":", 1)[1] if ":" in llm else llm
-        if name not in PANEL_PRESETS:
-            raise ValueError(
-                f"Unknown panel preset 'panel:{name}'. "
-                f"Known presets: {sorted(PANEL_PRESETS) or '(none registered)'}. "
-                "Use a dict descriptor or register_panel_preset(...) first."
-            )
-        config = dict(PANEL_PRESETS[name])
-    elif isinstance(llm, dict):
-        config = {k: v for k, v in llm.items() if k != "provider"}
-    else:
-        raise ValueError(f"Invalid panel descriptor: {llm!r}")
-
-    references = config.get("references") or []
-    aggregator = config.get("aggregator")
-    enabled = config.get("enabled", True)
-
-    if not isinstance(aggregator, str) or not aggregator:
-        raise ValueError("Panel config requires a non-empty 'aggregator' model string.")
-    if not isinstance(references, (list, tuple)):
-        raise ValueError("Panel 'references' must be a list of model strings.")
-    if not all(isinstance(ref, str) and ref for ref in references):
-        raise ValueError("Panel 'references' must contain only non-empty model strings.")
-    if not isinstance(enabled, bool):
-        raise ValueError("Panel 'enabled' must be a boolean.")
-
-    # Recursion guard: a panel preset cannot reference another panel preset.
-    if is_panel_descriptor(aggregator):
-        raise ValueError("Panel 'aggregator' cannot itself be a panel descriptor.")
-    for ref in references:
-        if is_panel_descriptor(ref):
-            raise ValueError("Panel 'references' cannot contain a panel descriptor.")
-
-    # Extra provider/model settings (e.g. base_url, api_key, temperature) carried
-    # so both dict descriptors and named presets configure the aggregator the same.
-    options = {
-        k: v
-        for k, v in config.items()
-        if k not in ("references", "aggregator", "enabled", "provider", "model")
-    }
-
-    return {
-        "references": list(references),
-        "aggregator": aggregator,
-        "enabled": bool(enabled),
-        "options": options,
-    }
-
-
-# Guidance wrapper for injected reference context. Appended to the tail of the
-# latest user turn so the cached system/history prefix is never modified.
-_REFERENCE_HEADER = (
-    "\n\n[Panel reference perspectives — advisory only, from other models. "
-    "Use them to inform your answer; you remain the acting model.]\n"
-)
-
-
-class PanelLLM(LLM):
-    """Aggregator-acting panel model.
-
-    Subclasses :class:`LLM` so the aggregator inherits the full tool loop,
-    hooks, session handling, and prompt-cache discipline unchanged. Reference
-    calls are advisory (tool-free, trimmed view) and cached per user turn.
-    """
-
-    def __init__(
-        self,
-        aggregator: str,
-        references: Optional[List[str]] = None,
-        enabled: bool = True,
-        reference_temperature: float = 0.0,
-        **kwargs: Any,
-    ):
-        super().__init__(model=aggregator, **kwargs)
-        self._panel_references = list(references or [])
-        self._panel_enabled = bool(enabled)
-        self._panel_reference_temperature = reference_temperature
-        # Connection/credential settings forwarded to reference LLMs so advisory
-        # calls hit the same backend and authenticate the same way as the
-        # aggregator (e.g. a custom Ollama endpoint or subscription ``auth``).
-        # Only connection-relevant kwargs are propagated; execution options
-        # (tools, web_search, etc.) are intentionally excluded since references
-        # are tool-free advisory calls.
-        self._panel_ref_kwargs = {
-            k: kwargs[k]
-            for k in ("base_url", "api_key", "api_version", "auth")
-            if k in kwargs and kwargs[k] is not None
-        }
-        # Per-turn cache: signature(trimmed view) -> joined reference guidance.
-        # Bounded (FIFO) so long-lived agents with many unique turns do not leak.
-        self._panel_ref_cache: "OrderedDict[str, str]" = OrderedDict()
-        self._panel_ref_cache_max = 128
-        # Lazily-created reference LLM instances, keyed by model string.
-        self._panel_ref_llms: Dict[str, LLM] = {}
-
-    # -- helpers ------------------------------------------------------------
-
-    def _panel_view_signature(
-        self, prompt: Any, system_prompt: Optional[str], chat_history: Optional[List[Dict]]
-    ) -> str:
-        """Deterministic signature of the trimmed view used for caching."""
-        text = repr(self._panel_trimmed_messages(prompt, system_prompt, chat_history))
-        return hashlib.sha256(text.encode("utf-8", "ignore")).hexdigest()
-
-    @staticmethod
-    def _panel_trimmed_messages(
-        prompt: Any, system_prompt: Optional[str], chat_history: Optional[List[Dict]]
-    ) -> List[Dict[str, str]]:
-        """Build a strict-provider-safe, tool-free view for reference calls.
-
-        Drops the system prompt, ``tool``-role messages and any ``tool_calls``
-        payloads so strict providers do not 400 on orphan tool messages.
-        Only user/assistant text content is kept.
-        """
-        view: List[Dict[str, str]] = []
-        for m in chat_history or []:
-            if not isinstance(m, dict):
-                continue
-            role = m.get("role")
-            if role not in ("user", "assistant"):
-                continue
-            if m.get("tool_calls"):
-                continue
-            content = m.get("content")
-            if isinstance(content, str) and content:
-                view.append({"role": role, "content": content})
-        if isinstance(prompt, str) and prompt:
-            view.append({"role": "user", "content": prompt})
-        elif isinstance(prompt, list):
-            for part in prompt:
-                if isinstance(part, dict) and isinstance(part.get("text"), str):
-                    view.append({"role": "user", "content": part["text"]})
-        return view
-
-    def _cache_guidance(self, sig: str, guidance: str) -> None:
-        """Store guidance under ``sig`` with a bounded FIFO eviction policy."""
-        cache = self._panel_ref_cache
-        cache[sig] = guidance
-        cache.move_to_end(sig)
-        while len(cache) > self._panel_ref_cache_max:
-            cache.popitem(last=False)
-
-    def _get_reference_llm(self, model: str) -> LLM:
-        if model not in self._panel_ref_llms:
-            self._panel_ref_llms[model] = LLM(model=model, **self._panel_ref_kwargs)
-        return self._panel_ref_llms[model]
-
-    def _format_reference_guidance(self, results: List[tuple]) -> str:
-        parts = [_REFERENCE_HEADER]
-        for label, text in results:
-            parts.append(f"--- {label} ---\n{text}\n")
-        return "".join(parts)
-
-    @staticmethod
-    def _inject_into_prompt(prompt: Any, guidance: str) -> Any:
-        """Append guidance to the tail of the latest user prompt (cache-safe)."""
-        if isinstance(prompt, str):
-            return prompt + guidance
-        if isinstance(prompt, list):
-            new_prompt = [dict(p) if isinstance(p, dict) else p for p in prompt]
-            for part in reversed(new_prompt):
-                if isinstance(part, dict) and isinstance(part.get("text"), str):
-                    part["text"] = part["text"] + guidance
-                    return new_prompt
-            new_prompt.append({"type": "text", "text": guidance})
-            return new_prompt
-        return prompt
-
-    # -- reference execution ------------------------------------------------
-
-    def _run_references_sync(self, view: List[Dict[str, str]]) -> str:
-        results: List[tuple] = []
-        for model in self._panel_references:
-            label = f"Reference: {model}"
-            try:
-                ref_llm = self._get_reference_llm(model)
-                text = ref_llm.get_response(
-                    prompt=view[-1]["content"] if view else "",
-                    chat_history=view[:-1] if len(view) > 1 else None,
-                    temperature=self._panel_reference_temperature,
-                    tools=None,
-                    verbose=False,
-                    stream=False,
-                    markdown=False,
-                )
-                results.append((label, text if isinstance(text, str) else str(text)))
-            except Exception as e:  # partial-failure tolerance
-                logger.warning(
-                    "Panel reference '%s' failed: %s", model, type(e).__name__
-                )
-                results.append((label, "(unavailable: reference call failed)"))
-        return self._format_reference_guidance(results)
-
-    async def _run_references_async(self, view: List[Dict[str, str]]) -> str:
-        import asyncio
-
-        async def _one(model: str):
-            label = f"Reference: {model}"
-            try:
-                ref_llm = self._get_reference_llm(model)
-                text = await ref_llm.get_response_async(
-                    prompt=view[-1]["content"] if view else "",
-                    chat_history=view[:-1] if len(view) > 1 else None,
-                    temperature=self._panel_reference_temperature,
-                    tools=None,
-                    verbose=False,
-                    stream=False,
-                    markdown=False,
-                )
-                return (label, text if isinstance(text, str) else str(text))
-            except Exception as e:  # partial-failure tolerance
-                logger.warning(
-                    "Panel reference '%s' failed: %s", model, type(e).__name__
-                )
-                return (label, "(unavailable: reference call failed)")
-
-        results = await asyncio.gather(*[_one(m) for m in self._panel_references])
-        return self._format_reference_guidance(list(results))
-
-    # -- overridden entry points -------------------------------------------
-
-    def get_response(self, prompt, system_prompt=None, chat_history=None, **kwargs):
-        if self._panel_enabled and self._panel_references:
-            view = self._panel_trimmed_messages(prompt, system_prompt, chat_history)
-            sig = self._panel_view_signature(prompt, system_prompt, chat_history)
-            guidance = self._panel_ref_cache.get(sig)
-            if guidance is None:
-                guidance = self._run_references_sync(view)
-                self._cache_guidance(sig, guidance)
-            prompt = self._inject_into_prompt(prompt, guidance)
-        return super().get_response(
-            prompt=prompt, system_prompt=system_prompt, chat_history=chat_history, **kwargs
-        )
-
-    async def get_response_async(self, prompt, system_prompt=None, chat_history=None, **kwargs):
-        if self._panel_enabled and self._panel_references:
-            view = self._panel_trimmed_messages(prompt, system_prompt, chat_history)
-            sig = self._panel_view_signature(prompt, system_prompt, chat_history)
-            guidance = self._panel_ref_cache.get(sig)
-            if guidance is None:
-                guidance = await self._run_references_async(view)
-                self._cache_guidance(sig, guidance)
-            prompt = self._inject_into_prompt(prompt, guidance)
-        return await super().get_response_async(
-            prompt=prompt, system_prompt=system_prompt, chat_history=chat_history, **kwargs
-        )
-
-
-def create_panel_llm(descriptor: Union[str, Dict[str, Any]], **llm_kwargs: Any) -> PanelLLM:
-    """Build a :class:`PanelLLM` from a panel descriptor.
-
-    Strips panel-only keys before forwarding remaining kwargs to ``LLM``.
-    """
-    config = resolve_panel_config(descriptor)
-    # Preserve extra provider options (e.g. base_url, api_key, temperature)
-    # supplied inside a dict descriptor *or* a named preset so they reach the
-    # aggregator LLM. ``options`` is normalized by ``resolve_panel_config`` for
-    # both paths; explicit ``llm_kwargs`` (Agent-level) take precedence.
-    descriptor_kwargs: Dict[str, Any] = dict(config.get("options") or {})
-    descriptor_kwargs.update(llm_kwargs)
-    for key in ("references", "aggregator", "enabled", "provider", "model"):
-        descriptor_kwargs.pop(key, None)
-    return PanelLLM(
-        aggregator=config["aggregator"],
-        references=config["references"],
-        enabled=config["enabled"],
-        **descriptor_kwargs,
-    )

src/praisonai-agents/praisonaiagents/main.py

@@ -244,82 +244,6 @@ def _clean_display_content(content: str, max_length: int = 20000) -> str:
     
     return content.strip()
 
-def _sanitize_renderable(renderable, stream):
-    """Replace unencodable decorative glyphs in a Rich renderable/str.
-
-    On legacy consoles (e.g. Windows cp1252) glyphs such as ``▸`` (U+25B8)
-    cannot be encoded and Rich raises ``UnicodeEncodeError``. This walks the
-    common renderable types (plain ``str``, ``Text``, ``Panel``) and rewrites
-    their text through :func:`safe_text` so printing never crashes.
-    """
-    from .output.encoding import safe_text
-    try:
-        from rich.text import Text
-        from rich.panel import Panel
-        from rich.markdown import Markdown
-    except ImportError:
-        return safe_text(renderable, stream) if isinstance(renderable, str) else renderable
-
-    if isinstance(renderable, str):
-        return safe_text(renderable, stream)
-    if isinstance(renderable, Text):
-        renderable.plain = safe_text(renderable.plain, stream)
-        return renderable
-    if isinstance(renderable, Markdown):
-        # Rebuild from sanitized markup so the rendered body drops
-        # unencodable glyphs (otherwise the LLM response would be lost).
-        return Markdown(safe_text(renderable.markup, stream))
-    if isinstance(renderable, Panel):
-        renderable.renderable = _sanitize_renderable(renderable.renderable, stream)
-        if isinstance(renderable.title, str):
-            renderable.title = safe_text(renderable.title, stream)
-        return renderable
-    return renderable
-
-def _renderable_to_plain(renderable, stream):
-    """Best-effort plain-text extraction from a Rich renderable for the
-    last-resort ``print()`` fallback, so LLM responses are never dropped.
-    """
-    from .output.encoding import safe_text
-    if isinstance(renderable, str):
-        return safe_text(renderable, stream)
-    try:
-        from rich.text import Text
-        from rich.panel import Panel
-        from rich.markdown import Markdown
-    except ImportError:
-        return safe_text(str(getattr(renderable, "plain", renderable)), stream)
-
-    if isinstance(renderable, Text):
-        return safe_text(renderable.plain, stream)
-    if isinstance(renderable, Markdown):
-        return safe_text(renderable.markup, stream)
-    if isinstance(renderable, Panel):
-        return _renderable_to_plain(renderable.renderable, stream)
-    return safe_text(str(getattr(renderable, "plain", renderable)), stream)
-
-def _safe_console_print(console, *renderables, **kwargs):
-    """Print via Rich, falling back to ASCII-safe glyphs on encoding errors.
-
-    Rich's legacy Windows renderer encodes with the terminal encoding
-    (cp1252 by default) using strict error handling and has no fallback, so
-    decorative glyphs crash the agent loop. We first try a normal print; on
-    ``UnicodeEncodeError`` we retry with sanitized renderables so ``run`` and
-    other display paths degrade gracefully instead of failing.
-    """
-    try:
-        console.print(*renderables, **kwargs)
-    except UnicodeEncodeError:
-        stream = getattr(console, "file", None)
-        sanitized = [_sanitize_renderable(r, stream) for r in renderables]
-        try:
-            console.print(*sanitized, **kwargs)
-        except UnicodeEncodeError:
-            plain = " ".join(_renderable_to_plain(r, stream) for r in sanitized)
-            # Write to the console's own stream (which may be a captured or
-            # redirected file), not the process-wide sys.stdout.
-            print(plain, file=stream if stream is not None else None)
-
 def display_interaction(message, response, markdown=True, generation_time=None, console=None, agent_name=None, agent_role=None, agent_tools=None, task_name=None, task_description=None, task_id=None, metrics=None):
     """Synchronous version of display_interaction.
     
@@ -385,11 +309,11 @@ def display_interaction(message, response, markdown=True, generation_time=None,
     # Format: 📝 Task message
     task_prefix = "[bold #FF9B9B]📝[/]"
     if markdown:
-        _safe_console_print(console, f"{task_prefix} {message}\n")
-        _safe_console_print(console, Panel.fit(Markdown(response_content), title=response_title, border_style=PRAISON_COLORS["response"]))
+        console.print(f"{task_prefix} {message}\n")
+        console.print(Panel.fit(Markdown(response_content), title=response_title, border_style=PRAISON_COLORS["response"]))
     else:
-        _safe_console_print(console, f"{task_prefix} [bold {PRAISON_COLORS['task_text']}]{message}[/]\n")
-        _safe_console_print(console, Panel.fit(Text(response_content, style=f"bold {PRAISON_COLORS['response_text']}"), title=response_title, border_style=PRAISON_COLORS["response"]))
+        console.print(f"{task_prefix} [bold {PRAISON_COLORS['task_text']}]{message}[/]\n")
+        console.print(Panel.fit(Text(response_content, style=f"bold {PRAISON_COLORS['response_text']}"), title=response_title, border_style=PRAISON_COLORS["response"]))
 
 def display_self_reflection(message: str, console=None):
     if not message or not message.strip():
@@ -402,7 +326,7 @@ def display_self_reflection(message: str, console=None):
     # Execute synchronous callbacks
     execute_sync_callback('self_reflection', message=message)
 
-    _safe_console_print(console, Panel.fit(Text(message, style="bold yellow"), title="Self Reflection", border_style="magenta"))
+    console.print(Panel.fit(Text(message, style="bold yellow"), title="Self Reflection", border_style="magenta"))
 
 def display_instruction(message: str, console=None, agent_name: str = None, agent_role: str = None, agent_tools: List[str] = None):
     if not message or not message.strip():
@@ -423,11 +347,11 @@ def display_instruction(message: str, console=None, agent_name: str = None, agen
         if agent_tools:
             tools_str = ", ".join(f"[italic #B4D4FF]{tool}[/]" for tool in agent_tools)
             agent_info += f"\n[bold #86A789]Tools:[/] {tools_str}"
-        _safe_console_print(console, Panel(agent_info, border_style="#D2E3C8", title="[bold]Agent Info[/]", title_align="left", padding=(1, 2)))
+        console.print(Panel(agent_info, border_style="#D2E3C8", title="[bold]Agent Info[/]", title_align="left", padding=(1, 2)))
 
     # Only print if log level is DEBUG
     if get_logger().getEffectiveLevel() == logging.DEBUG:
-        _safe_console_print(console, Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))
+        console.print(Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))
 
 def display_tool_call(message: str, console=None, tool_name: str = None, tool_input: dict = None, tool_output: str = None, elapsed_time: float = None, success: bool = True):
     """Display tool call information in PraisonAI's unique timeline format.
@@ -485,10 +409,10 @@ def display_tool_call(message: str, console=None, tool_name: str = None, tool_in
                 tool_line += f" [dim]→[/] [italic]{output_str}[/]"
             
             tool_line += f" {time_str} {status_icon}"
-            _safe_console_print(console, tool_line)
+            console.print(tool_line)
         else:
             # Legacy format - simple inline
-            _safe_console_print(console, f"[bold #86A789]▸[/] {message}")
+            console.print(f"[bold #86A789]▸[/] {message}")
 
 def display_error(message: str, console=None):
     if not message or not message.strip():
@@ -502,7 +426,7 @@ def display_error(message: str, console=None):
     execute_sync_callback('error', message=message)
 
     # Use semantic error color
-    _safe_console_print(console, Panel.fit(
+    console.print(Panel.fit(
         Text(message, style=f"bold {PRAISON_COLORS['error_text']}"),
         title="⚠ Error",
         border_style=PRAISON_COLORS["error"]
@@ -558,7 +482,7 @@ def display_reasoning_steps(steps: List[str], console=None):
     
     reasoning_display = "\n".join(reasoning_lines)
     
-    _safe_console_print(console, Panel.fit(
+    console.print(Panel.fit(
         Text(reasoning_display, style=f"italic {PRAISON_COLORS['reasoning_text']}"),
         title="Reasoning",
         border_style=PRAISON_COLORS["reasoning"]
@@ -626,14 +550,14 @@ async def adisplay_interaction(message, response, markdown=True, generation_time
 
     # Rest of the display logic...
     if generation_time:
-        _safe_console_print(console, Text(f"Response generated in {generation_time:.1f}s", style="dim"))
+        console.print(Text(f"Response generated in {generation_time:.1f}s", style="dim"))
 
     if markdown:
-        _safe_console_print(console, Panel.fit(Markdown(message), title="Task", border_style="cyan"))
-        _safe_console_print(console, Panel.fit(Markdown(response), title="Response", border_style="cyan"))
+        console.print(Panel.fit(Markdown(message), title="Task", border_style="cyan"))
+        console.print(Panel.fit(Markdown(response), title="Response", border_style="cyan"))
     else:
-        _safe_console_print(console, Panel.fit(Text(message, style="bold green"), title="Task", border_style="cyan"))
-        _safe_console_print(console, Panel.fit(Text(response, style="bold blue"), title="Response", border_style="cyan"))
+        console.print(Panel.fit(Text(message, style="bold green"), title="Task", border_style="cyan"))
+        console.print(Panel.fit(Text(response, style="bold blue"), title="Response", border_style="cyan"))
 
 async def adisplay_self_reflection(message: str, console=None):
     """Async version of display_self_reflection."""
@@ -647,7 +571,7 @@ async def adisplay_self_reflection(message: str, console=None):
     # Execute callbacks
     await execute_callback('self_reflection', message=message)
     
-    _safe_console_print(console, Panel.fit(Text(message, style="bold yellow"), title="Self Reflection", border_style="magenta"))
+    console.print(Panel.fit(Text(message, style="bold yellow"), title="Self Reflection", border_style="magenta"))
 
 async def adisplay_instruction(message: str, console=None, agent_name: str = None, agent_role: str = None, agent_tools: List[str] = None):
     """Async version of display_instruction."""
@@ -669,11 +593,11 @@ async def adisplay_instruction(message: str, console=None, agent_name: str = Non
         if agent_tools:
             tools_str = ", ".join(f"[italic #B4D4FF]{tool}[/]" for tool in agent_tools)
             agent_info += f"\n[bold #86A789]Tools:[/] {tools_str}"
-        _safe_console_print(console, Panel(agent_info, border_style="#D2E3C8", title="[bold]Agent Info[/]", title_align="left", padding=(1, 2)))
+        console.print(Panel(agent_info, border_style="#D2E3C8", title="[bold]Agent Info[/]", title_align="left", padding=(1, 2)))
     
     # Only print if log level is DEBUG
     if get_logger().getEffectiveLevel() == logging.DEBUG:
-        _safe_console_print(console, Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))
+        console.print(Panel.fit(Text(message, style="bold blue"), title="Instruction", border_style="cyan"))
 
 async def adisplay_tool_call(message: str, console=None):
     """Async version of display_tool_call."""
@@ -690,7 +614,7 @@ async def adisplay_tool_call(message: str, console=None):
     # Execute callbacks
     await execute_callback('tool_call', message=message)
     
-    _safe_console_print(console, Panel.fit(Text(message, style="bold cyan"), title="Tool Call", border_style="green"))
+    console.print(Panel.fit(Text(message, style="bold cyan"), title="Tool Call", border_style="green"))
 
 async def adisplay_error(message: str, console=None):
     """Async version of display_error."""
@@ -704,7 +628,7 @@ async def adisplay_error(message: str, console=None):
     # Execute callbacks
     await execute_callback('error', message=message)
     
-    _safe_console_print(console, Panel.fit(Text(message, style="bold red"), title="Error", border_style="red"))
+    console.print(Panel.fit(Text(message, style="bold red"), title="Error", border_style="red"))
     with _error_logs_lock:
         error_logs.append(message)
 

src/praisonai-agents/praisonaiagents/memory/memory.py

@@ -422,14 +422,7 @@ class Memory(SearchMixin, MemoryCoreMixin):
             os.makedirs(rag_path, exist_ok=True)
 
             # Get chromadb lazily
-            try:
-                import chromadb
-                from chromadb.config import Settings as ChromaSettings
-            except ImportError as exc:
-                raise ImportError(
-                    "chromadb is required for the rag memory provider. "
-                    "Install with: pip install 'praisonaiagents[memory]'"
-                ) from exc
+            chromadb, ChromaSettings = _get_chromadb()
 
             # Initialize ChromaDB with persistent storage
             self.chroma_client = chromadb.PersistentClient(
@@ -1805,11 +1798,7 @@ class Memory(SearchMixin, MemoryCoreMixin):
         """
 
         try:
-            import importlib.util
-            litellm_available = importlib.util.find_spec("litellm") is not None
-            openai_available = importlib.util.find_spec("openai") is not None
-
-            if litellm_available:
+            if _check_litellm():
                 # Use LiteLLM for consistency with the rest of the codebase
                 import litellm
                 
@@ -1825,7 +1814,7 @@ class Memory(SearchMixin, MemoryCoreMixin):
                     response_format={"type": "json_object"},
                     temperature=0.3
                 )
-            elif openai_available:
+            elif _check_openai():
                 # Fallback to OpenAI client
                 from openai import OpenAI
                 client = OpenAI()

src/praisonai-agents/praisonaiagents/memory/utils.py

@@ -0,0 +1,111 @@
+"""
+Shared utilities for memory modules.
+
+This module contains utility functions that were originally in memory.py
+and are needed by the decomposed mixin modules.
+"""
+
+import os
+import threading
+import logging
+
+# Thread-safe import cache
+_import_lock = threading.Lock()
+_module_cache = {}
+
+def _check_chromadb():
+    """Thread-safe lazy check for chromadb availability."""
+    if "chromadb" in _module_cache:
+        return _module_cache["chromadb"]["available"]
+    
+    with _import_lock:
+        if "chromadb" in _module_cache:
+            return _module_cache["chromadb"]["available"]
+        
+        try:
+            import chromadb
+            from chromadb.config import Settings as ChromaSettings
+            _module_cache["chromadb"] = {
+                "available": True,
+                "module": chromadb,
+                "settings": ChromaSettings
+            }
+            return True
+        except ImportError:
+            _module_cache["chromadb"] = {"available": False}
+            return False
+
+def _get_chromadb():
+    """Thread-safe lazy import of chromadb (only if available)."""
+    if "chromadb" not in _module_cache or not _module_cache["chromadb"]["available"]:
+        if not _check_chromadb():
+            return {}
+    
+    with _import_lock:
+        return {
+            "module": _module_cache["chromadb"]["module"],
+            "settings": _module_cache["chromadb"]["settings"]
+        }
+
+def _check_pymongo():
+    """Thread-safe lazy check for pymongo availability."""
+    if "pymongo" in _module_cache:
+        return _module_cache["pymongo"]["available"]
+    
+    with _import_lock:
+        if "pymongo" in _module_cache:
+            return _module_cache["pymongo"]["available"]
+        
+        try:
+            import pymongo
+            import motor.motor_asyncio
+            _module_cache["pymongo"] = {
+                "available": True,
+                "MongoClient": pymongo.MongoClient,
+                "AsyncIOMotorClient": motor.motor_asyncio.AsyncIOMotorClient
+            }
+            return True
+        except ImportError:
+            _module_cache["pymongo"] = {"available": False}
+            return False
+
+def _get_pymongo():
+    """Thread-safe lazy import of pymongo (only if available)."""
+    if "pymongo" not in _module_cache or not _module_cache["pymongo"]["available"]:
+        if not _check_pymongo():
+            return {}
+    
+    with _import_lock:
+        return {
+            "MongoClient": _module_cache["pymongo"]["MongoClient"],
+            "AsyncIOMotorClient": _module_cache["pymongo"]["AsyncIOMotorClient"]
+        }
+
+def _check_openai():
+    """Thread-safe lazy check for openai availability."""
+    if "openai" in _module_cache:
+        return _module_cache["openai"]["available"]
+    
+    with _import_lock:
+        if "openai" in _module_cache:
+            return _module_cache["openai"]["available"]
+        
+        try:
+            import openai
+            _module_cache["openai"] = {
+                "available": True,
+                "module": openai
+            }
+            return True
+        except ImportError:
+            _module_cache["openai"] = {"available": False}
+            return False
+
+def _get_openai():
+    """Thread-safe lazy import of openai (only if available)."""
+    if "openai" not in _module_cache or not _module_cache["openai"]["available"]:
+        if not _check_openai():
+            return None
+    
+    with _import_lock:
+        return _module_cache["openai"]["module"]

src/praisonai-agents/praisonaiagents/output/encoding.py

@@ -1,88 +0,0 @@
-"""
-Encoding-safe symbol helpers for console output.
-
-On some consoles (e.g. Windows default cp1252) writing decorative Unicode
-glyphs such as ``▸`` (U+25B8) raises ``UnicodeEncodeError``. These helpers
-detect whether the target stream can encode a symbol and provide an ASCII
-fallback so progress/status output never crashes the agent loop.
-
-This mirrors the ``_can_encode_unicode()`` fallback used by the doctor
-formatter, exposed here as a shared utility for the output package.
-"""
-
-import sys
-from typing import Optional, TextIO
-
-# Common decorative glyphs mapped to safe ASCII fallbacks.
-_ASCII_FALLBACKS = {
-    "\u25b8": ">",   # ▸ black right-pointing small triangle
-    "\u25b6": ">",   # ▶ black right-pointing triangle
-    "\u25c0": "<",   # ◀ black left-pointing triangle
-    "\u2192": "->",  # → rightwards arrow
-    "\u2190": "<-",  # ← leftwards arrow
-    "\u2713": "v",   # ✓ check mark
-    "\u2717": "x",   # ✗ ballot x
-    "\u2714": "v",   # ✔ heavy check mark
-    "\u2718": "x",   # ✘ heavy ballot x
-    "\u2500": "-",   # ─ box drawings light horizontal
-    "\u2502": "|",   # │ box drawings light vertical
-    "\u2514": "+",   # └ box drawings light up and right
-    "\u2500\u2500": "--",
-    "\U0001f4ca": "[metrics]",  # 📊 bar chart
-}
-
-
-def can_encode(stream: Optional[TextIO], text: str) -> bool:
-    """Return True if ``text`` can be encoded by ``stream``'s encoding."""
-    if not isinstance(text, str):
-        return True
-    encoding = getattr(stream, "encoding", None) or getattr(sys.stdout, "encoding", None) or "ascii"
-    if encoding.lower() in ("utf-8", "utf8"):
-        return True
-    try:
-        text.encode(encoding, errors="strict")
-        return True
-    except (UnicodeEncodeError, LookupError, TypeError):
-        return False
-
-
-def safe_symbol(unicode_symbol: str, ascii_fallback: Optional[str] = None,
-                stream: Optional[TextIO] = None) -> str:
-    """
-    Return ``unicode_symbol`` if the stream can encode it, else an ASCII
-    fallback. When no explicit fallback is given, a sensible default is used.
-    """
-    target = stream if stream is not None else sys.stdout
-    if can_encode(target, unicode_symbol):
-        return unicode_symbol
-    if ascii_fallback is not None:
-        return ascii_fallback
-    return _ASCII_FALLBACKS.get(unicode_symbol, "")
-
-
-def safe_text(text: str, stream: Optional[TextIO] = None) -> str:
-    """
-    Return ``text`` with any unencodable decorative glyphs replaced by ASCII
-    fallbacks so it can be printed without raising ``UnicodeEncodeError``.
-    """
-    if not isinstance(text, str):
-        return text
-    target = stream if stream is not None else sys.stdout
-    if can_encode(target, text):
-        return text
-    result = text
-    for glyph, fallback in _ASCII_FALLBACKS.items():
-        if glyph in result:
-            result = result.replace(glyph, fallback)
-    if can_encode(target, result):
-        return result
-    # Last resort: drop any remaining unencodable characters so printing
-    # never raises UnicodeEncodeError on legacy consoles.
-    encoding = getattr(target, "encoding", None) or getattr(sys.stdout, "encoding", None) or "ascii"
-    try:
-        return result.encode(encoding, errors="replace").decode(encoding, errors="replace")
-    except (LookupError, TypeError):
-        return result.encode("ascii", errors="replace").decode("ascii")
-
-
-__all__ = ["can_encode", "safe_symbol", "safe_text"]

src/praisonai-agents/praisonaiagents/output/status.py

@@ -293,8 +293,7 @@ class StatusOutput:
             self._emit_text("Final Output:", ts, "bold", show_timestamp=False)
             # Print actual content to stdout (not stderr) so users see it
             with self._lock:  # Thread-safe output
-                from .encoding import safe_text
-                print(safe_text(content, sys.stdout))
+                print(content)
     
     def _emit_text(self, message: str, ts: float, style: str = None, show_timestamp: bool = True) -> None:
         """Emit a text line. Thread-safe for multi-agent execution."""
@@ -310,8 +309,7 @@ class StatusOutput:
                 else:
                     console.print(f"[dim]{ts_str}[/dim]{message}")
             else:
-                from .encoding import safe_text
-                print(safe_text(f"{ts_str}{message}", self._file), file=self._file)
+                print(f"{ts_str}{message}", file=self._file)
     
     def _emit_jsonl(self, event_type: str, **kwargs) -> None:
         """Emit a JSONL line. Thread-safe for multi-agent execution."""

src/praisonai-agents/praisonaiagents/output/trace.py

@@ -90,8 +90,7 @@ class TraceOutput:
                 else:
                     console.print(f"[dim]{ts_str}[/dim]{message}")
             else:
-                from .encoding import safe_text
-                print(safe_text(f"{ts_str}{message}", self._file), file=self._file)
+                print(f"{ts_str}{message}", file=self._file)
     
     def llm_start(self, model: str = None) -> None:
         """Record LLM call start."""
@@ -193,10 +192,9 @@ class TraceOutput:
                 else:
                     console.print(content)
             else:
-                from .encoding import safe_text
                 print("", file=self._file)
                 print("Response:", file=self._file)
-                print(safe_text(content, self._file), file=self._file)
+                print(content, file=self._file)
     
     def error(self, message: str) -> None:
         """Output error message."""

src/praisonai-agents/praisonaiagents/permissions/__init__.py

@@ -36,8 +36,6 @@ __all__ = [
     "PermissionResult",
     "PersistentApproval",
     "DoomLoopDetector",
-    "derive_pattern",
-    "command_prefix",
 ]
 
 
@@ -70,13 +68,5 @@ def __getattr__(name: str):
     if name == "DoomLoopDetector":
         from .doom_loop import DoomLoopDetector
         return DoomLoopDetector
-
-    if name == "derive_pattern":
-        from .arity import derive_pattern
-        return derive_pattern
-
-    if name == "command_prefix":
-        from .arity import prefix
-        return prefix
     
     raise AttributeError(f"module {__name__!r} has no attribute {name!r}")

src/praisonai-agents/praisonaiagents/permissions/arity.py

@@ -1,181 +0,0 @@
-"""
-Command-arity inference for reusable permission-prefix scopes.
-
-When a user approves a shell command with a persistent scope (``session`` or
-``always``), recording the *literal* command string means only that exact
-command is auto-allowed next time. Approving ``git status`` will not match a
-later ``git status -s`` or ``git status .`` — producing approval fatigue.
-
-This module derives a *reusable command prefix* from a small, extensible
-command-arity table so that, for example:
-
-* ``git status``         -> ``git status``  (prefix) -> pattern ``bash:git status *``
-* ``npm run build``      -> ``npm run``      (prefix) -> pattern ``bash:npm run *``
-* ``docker compose up``  -> ``docker compose`` (prefix) -> pattern ``bash:docker compose *``
-* ``ls -la``             -> ``ls``           (prefix) -> pattern ``bash:ls *``
-
-Unknown commands fall back to a conservative single-token prefix, so a bare
-``git`` never over-generalises to *all* git subcommands.
-
-The table is intentionally small and additive; it can be extended without
-touching the matching hot path (``fnmatch`` already handles the ``*`` suffix).
-"""
-
-from typing import Dict, List, Optional
-
-# Command -> number of leading tokens to KEEP as the reusable prefix.
-#
-# The value is how many leading tokens make up the "meaningful" command that
-# should be generalised (the remainder becomes ``*``). For example ``git`` -> 2
-# keeps ``git status`` from ``git status -s``. Multi-word keys (e.g.
-# ``"npm run"``) allow a subcommand to request a deeper prefix than its base
-# command; the longest matching key wins. Unknown commands default to keeping a
-# single leading token, so a bare ``git`` never over-generalises to all git.
-ARITY: Dict[str, int] = {
-    # Version control
-    "git": 2,          # git status -s      -> git status *
-    "gh": 2,           # gh pr create       -> gh pr *
-    "hg": 2,
-    "svn": 2,
-    # Package managers / build tools
-    "npm": 2,          # npm run build      -> npm run *
-    "yarn": 2,
-    "pnpm": 2,
-    "pip": 2,          # pip install x      -> pip install *
-    "cargo": 2,        # cargo run --bin x  -> cargo run *
-    "go": 2,           # go test ./...      -> go test *
-    "poetry": 2,
-    "uv": 2,
-    "make": 2,
-    # Containers / orchestration
-    "docker": 2,       # docker compose up  -> docker compose *
-    "docker compose": 2,  # docker compose up -d -> docker compose *
-    "kubectl": 2,      # kubectl get pods   -> kubectl get *
-    "helm": 2,
-    # Python tooling
-    "python": 2,       # python -m pytest   -> python -m *
-    "python3": 2,
-    "pytest": 1,       # pytest tests/      -> pytest *
-    "ruff": 2,         # ruff check .       -> ruff check *
-    # System / misc
-    "apt": 2,
-    "apt-get": 2,
-    "brew": 2,
-    "systemctl": 2,
-}
-
-
-def prefix(tokens: List[str], arity_map: Optional[Dict[str, int]] = None) -> str:
-    """Return the longest meaningful command prefix for ``tokens``.
-
-    Args:
-        tokens: The command split into whitespace-delimited tokens
-            (e.g. ``["git", "status", "-s"]``).
-        arity_map: Optional override for the arity table (defaults to
-            :data:`ARITY`).
-
-    Returns:
-        The meaningful command prefix as a single space-joined string. For an
-        empty ``tokens`` list an empty string is returned.
-
-    Examples:
-        >>> prefix(["git", "status", "-s"])
-        'git status'
-        >>> prefix(["npm", "run", "build"])
-        'npm run'
-        >>> prefix(["ls", "-la"])
-        'ls'
-        >>> prefix(["git"])
-        'git'
-    """
-    if not tokens:
-        return ""
-
-    table = ARITY if arity_map is None else arity_map
-
-    # Try the longest multi-word keys first so "docker compose" wins over
-    # "docker". The matched value is the number of leading tokens to keep.
-    key_word_counts = sorted(
-        {len(k.split()) for k in table}, reverse=True
-    )
-    for n in key_word_counts:
-        if n > len(tokens):
-            continue
-        candidate = " ".join(tokens[:n])
-        if candidate in table:
-            keep = min(table[candidate], len(tokens))
-            return " ".join(tokens[:keep])
-
-    # Unknown command: keep only the first token (conservative default) so a
-    # bare command never over-generalises to all of its subcommands.
-    return tokens[0]
-
-
-def derive_pattern(
-    target: str, arity_map: Optional[Dict[str, int]] = None
-) -> str:
-    """Derive a reusable glob pattern for a shell approval ``target``.
-
-    Only ``bash:``/``shell:`` targets are generalised; any other target (or one
-    that already contains a glob) is returned unchanged so callers can safely
-    apply this unconditionally.
-
-    Args:
-        target: The approval target, e.g. ``"bash:git status -s"``.
-        arity_map: Optional override for the arity table.
-
-    Returns:
-        A reusable pattern such as ``"bash:git status *"``. The target is
-        returned **unchanged** when it is not a shell target, is empty, already
-        contains ``*``/``?`` glob characters, contains a shell control operator
-        (``&&``, ``|``, ``;``, ``$(...)`` etc.), or is a bare single-token
-        command (so a lone ``git`` never becomes ``git *``).
-
-    Examples:
-        >>> derive_pattern("bash:git status")
-        'bash:git status *'
-        >>> derive_pattern("bash:npm run build")
-        'bash:npm run *'
-        >>> derive_pattern("bash:git")            # bare command stays literal
-        'bash:git'
-        >>> derive_pattern("bash:cd /tmp && rm x")  # operator -> literal
-        'bash:cd /tmp && rm x'
-        >>> derive_pattern("read:/etc/hosts")
-        'read:/etc/hosts'
-    """
-    shell_prefixes = ("bash:", "shell:")
-    matched = next((p for p in shell_prefixes if target.startswith(p)), None)
-    if matched is None:
-        return target
-
-    command = target[len(matched):].strip()
-    if not command:
-        return target
-
-    # If the user already provided a glob, respect it verbatim.
-    if "*" in command or "?" in command:
-        return target
-
-    # Shell control operators / substitutions. If the command contains any of
-    # these, a globbed prefix would silently swallow a *second* command into
-    # the reusable scope (e.g. ``cd /tmp && rm -rf x`` -> ``cd *``). Refuse to
-    # generalise such commands and keep the literal target instead.
-    _SHELL_OPERATORS = ("&&", "||", "|", ";", "&", "$(", "`", ">", "<", "\n")
-    if any(op in command for op in _SHELL_OPERATORS):
-        return target
-
-    tokens = command.split()
-    cmd_prefix = prefix(tokens, arity_map)
-    if not cmd_prefix:
-        return target
-
-    # A bare single-token command (e.g. ``git`` with no subcommand) must not be
-    # generalised to ``git *`` — that would auto-approve every subcommand,
-    # violating the documented conservative contract. Only generalise when the
-    # prefix is genuinely a prefix (i.e. there is at least one trailing token to
-    # replace with ``*``); a lone token that already equals the full command has
-    # nothing to generalise and is kept literal.
-    if len(cmd_prefix.split()) == 1 and cmd_prefix == command:
-        return target
-
-    return f"{matched}{cmd_prefix} *"

src/praisonai-agents/praisonaiagents/permissions/command_parser.py

@@ -28,49 +28,6 @@ _SEPARATORS = ("&&", "||", ";", "|", "&", "\n")
 _WRITE_REDIRECTS = (">", ">>", ">|", "&>", "&>>")
 
 
-def _looks_like_path(tok: str) -> bool:
-    """Return ``True`` if *tok* is path-like enough to warrant a boundary check.
-
-    Conservative but covers common escape forms: absolute (``/x``),
-    home-relative (``~``), explicit relative (``./``, ``../``, ``..``),
-    env-prefixed (``$VAR/…``) and any bare token that embeds a ``/`` (e.g.
-    ``subdir/../../etc/passwd``). Plain flags/values without a path shape are
-    ignored so non-path args never trigger a spurious prompt.
-    """
-    if not tok:
-        return False
-    return (
-        tok.startswith("/")
-        or tok.startswith("~")
-        or tok.startswith("./")
-        or tok.startswith("../")
-        or tok == ".."
-        or tok.startswith("$")
-        or "/" in tok
-    )
-
-
-def _extract_flag_path(tok: str) -> str:
-    """Extract a path operand attached to a short flag (``-o/tmp/x``).
-
-    Handles the ``getopt`` short-option form where the value is joined to the
-    flag with no separator (e.g. ``-o/tmp/outside``, ``-I/usr/include``). The
-    leading dashes and flag letters are stripped and the first embedded
-    path-shaped segment (``/…``, ``~…``, ``$…``) is returned; otherwise ``""``.
-    Long flags (``--flag=…``) are handled separately via ``=`` splitting.
-    """
-    if not tok.startswith("-") or tok.startswith("--"):
-        return ""
-    body = tok.lstrip("-")
-    for i, ch in enumerate(body):
-        if ch in ("/", "~", "$"):
-            candidate = body[i:]
-            if _looks_like_path(candidate):
-                return candidate
-            break
-    return ""
-
-
 @dataclass
 class ShellOp:
     """A single simple-command extracted from a shell command line.
@@ -91,38 +48,6 @@ class ShellOp:
         parts = [self.executable, *self.args]
         return " ".join(p for p in parts if p)
 
-    @property
-    def path_args(self) -> List[str]:
-        """Args that look like filesystem paths (for boundary checks).
-
-        Returns path-like tokens for boundary evaluation. Covers absolute
-        (``/x``), home-relative (``~``), parent/relative (``./``, ``../``),
-        env-prefixed (``$VAR/…``) and bare traversal/relative paths that
-        embed ``/`` (e.g. ``subdir/../../etc/passwd``). Path operands passed
-        as joined flags (``--config=/etc/x``) or short-flag-attached
-        (``-o/tmp/x``) are also unwrapped so the value is boundary-checked.
-        Plain flags and non-path values are ignored.
-        """
-        paths: List[str] = []
-        for tok in self.args:
-            if not tok:
-                continue
-            # Flag forms can hide a path operand: ``--flag=<value>`` (split on
-            # ``=``) or short getopt ``-o<value>`` (value joined to the flag).
-            if tok.startswith("-"):
-                if "=" in tok:
-                    value = tok.split("=", 1)[1]
-                    if value and _looks_like_path(value):
-                        paths.append(value)
-                    continue
-                attached = _extract_flag_path(tok)
-                if attached:
-                    paths.append(attached)
-                continue
-            if _looks_like_path(tok):
-                paths.append(tok)
-        return paths
-
 
 def _extract_substitutions(token: str) -> List[str]:
     """Extract inner commands from ``$(...)`` and backtick substitutions.

src/praisonai-agents/praisonaiagents/permissions/manager.py

@@ -58,7 +58,6 @@ class PermissionManager:
         storage_dir: Optional[str] = None,
         agent_name: Optional[str] = None,
         approval_callback: Optional[Callable[[str, str], bool]] = None,
-        workspace_root: Optional[str] = None,
     ):
         """
         Initialize the permission manager.
@@ -67,19 +66,10 @@ class PermissionManager:
             storage_dir: Directory for persistent storage
             agent_name: Optional agent name for filtering rules
             approval_callback: Optional callback for user approval
-            workspace_root: Optional project/workspace root. When set, shell
-                and file targets that resolve *outside* this root emit a
-                distinct ``external_dir:<parent>/*`` sub-target (default
-                ``ask``), gating out-of-workspace access with an extra
-                approval. When ``None`` (default) no boundary check runs and
-                behaviour is unchanged.
         """
         self.storage_dir = storage_dir or DEFAULT_PERMISSIONS_DIR
         self.agent_name = agent_name
         self.approval_callback = approval_callback
-        self.workspace_root = (
-            os.path.realpath(workspace_root) if workspace_root else None
-        )
         
         self._rules: List[PermissionRule] = []
         self._approvals: List[PersistentApproval] = []
@@ -210,22 +200,6 @@ class PermissionManager:
     # sub-targets before matching (command-aware permission matching).
     _SHELL_PREFIXES = ("bash:", "shell:")
 
-    # File-mutating tool prefixes whose ``<prefix>:<path>`` target must also be
-    # gated by the workspace boundary. A broad ``write_file:*`` approval should
-    # not silently permit writes outside ``workspace_root``; out-of-workspace
-    # paths emit an ``external_dir:`` ask (deny rules still win).
-    _FILE_PREFIXES = (
-        "write:",
-        "write_file:",
-        "edit:",
-        "edit_file:",
-        "apply_patch:",
-        "append:",
-        "append_file:",
-        "delete:",
-        "delete_file:",
-    )
-
     def check(self, target: str, agent_name: Optional[str] = None) -> PermissionResult:
         """
         Check permission for a target.
@@ -250,61 +224,9 @@ class PermissionManager:
             structured = self._check_shell_command(prefix, command, agent)
             if structured is not None:
                 return structured
-            return self._check_flat(target, agent)
-
-        # File-mutating tool targets share the workspace-boundary gate so a
-        # broad ``write_file:*`` approval cannot silently escape the workspace.
-        if self.workspace_root is not None:
-            file_prefix = next(
-                (p for p in self._FILE_PREFIXES if target.startswith(p)), None
-            )
-            if file_prefix is not None:
-                boundary = self._check_file_boundary(
-                    file_prefix, target[len(file_prefix):], target, agent
-                )
-                if boundary is not None:
-                    return boundary
 
         return self._check_flat(target, agent)
 
-    def _check_file_boundary(
-        self, prefix: str, path: str, original_target: str, agent: Optional[str]
-    ) -> Optional[PermissionResult]:
-        """Apply the workspace boundary to a file-tool ``<prefix>:<path>``.
-
-        Returns ``None`` when the path is inside the workspace (defer to normal
-        flat matching) so in-workspace behaviour is unchanged. When the path
-        escapes the root, aggregates the flat file-target result with the
-        ``external_dir:`` gate using deny-wins → ask → allow, mirroring the
-        shell decomposition semantics (a deny still wins over the ask gate).
-        """
-        ext = self._external_dir_target(path)
-        if ext is None:
-            return None
-
-        file_res = self._check_flat(original_target, agent)
-        ext_res = self._check_flat(ext, agent)
-
-        # Deny wins (either an explicit file-target deny or an external_dir deny).
-        for sub_target, res in ((original_target, file_res), (ext, ext_res)):
-            if res.action == PermissionAction.DENY:
-                res.reason = f"Denied '{sub_target}' ({res.reason})"
-                res.target = original_target
-                return res
-
-        # Then ask: the external-directory gate requires approval unless it has
-        # been explicitly pre-authorised (allow rule/approval on external_dir:).
-        if ext_res.action != PermissionAction.ALLOW:
-            ext_res.reason = (
-                f"Out-of-workspace path requires approval "
-                f"('{ext}': {ext_res.reason})"
-            )
-            ext_res.target = original_target
-            return ext_res
-
-        # External path was explicitly pre-authorised; honour the file rule.
-        return file_res
-
     def _check_flat(self, target: str, agent: Optional[str]) -> PermissionResult:
         """Legacy flat matching against approvals and rules for a target."""
         with self._lock:
@@ -364,23 +286,6 @@ class PermissionManager:
                 sub_targets.append(prefix + cmd_str)
             for path in op.write_targets:
                 sub_targets.append(f"write:{path}")
-            # Workspace-boundary gate: any write target or path-like arg that
-            # resolves outside the workspace root gets a distinct
-            # ``external_dir:`` sub-target (default ``ask``).
-            if self.workspace_root is not None:
-                boundary_paths = list(op.write_targets) + op.path_args
-                # An executable referenced by path (``/tmp/tool``, ``../tool``)
-                # runs code outside the workspace; a bare name (``rm``) is
-                # PATH-resolved and must not trigger a boundary prompt.
-                if op.executable and (
-                    op.executable.startswith(("/", "~", "./", "../", "$"))
-                    or "/" in op.executable
-                ):
-                    boundary_paths.append(op.executable)
-                for path in boundary_paths:
-                    ext = self._external_dir_target(path)
-                    if ext is not None:
-                        sub_targets.append(ext)
 
         # No structured decomposition possible, or it collapses to exactly the
         # original target — defer to the existing flat matcher.
@@ -423,87 +328,12 @@ class PermissionManager:
             reason="All shell sub-operations allowed",
         )
 
-    def _external_dir_target(self, path: str) -> Optional[str]:
-        """Return an ``external_dir:<parent>/*`` target if *path* escapes root.
-
-        Resolves *path* (``~``, ``$VARS``, ``..``) against ``workspace_root``
-        using the shared ``path_safety`` containment logic. In-workspace paths
-        return ``None`` so existing flows are unaffected.
-        """
-        if self.workspace_root is None:
-            return None
-        # Fail *closed*: if the boundary check cannot be performed (import or
-        # resolution failure), gate the raw path behind ``external_dir:`` rather
-        # than silently allowing it. A deny rule still wins over this ask.
-        fail_closed = f"external_dir:{path}/*"
-        try:
-            from ..tools.path_safety import resolve_within_root, resolve_path
-        except Exception as e:  # noqa: BLE001
-            logger.error(
-                "Workspace boundary check unavailable for path '%s' "
-                "(agent=%s): %s. Requiring approval instead of allowing.",
-                path, self.agent_name, e,
-            )
-            return fail_closed
-        try:
-            if resolve_within_root(path, self.workspace_root) is not None:
-                return None
-            resolved = resolve_path(path, self.workspace_root)
-            parent = os.path.dirname(resolved) or resolved
-            return f"external_dir:{parent}/*"
-        except Exception as e:  # noqa: BLE001
-            logger.warning(
-                "Could not resolve path '%s' for workspace boundary check "
-                "(agent=%s): %s. Requiring approval.",
-                path, self.agent_name, e,
-            )
-            return fail_closed
-
-    def check_path_boundary(
-        self, path: str, agent_name: Optional[str] = None
-    ) -> Optional[PermissionResult]:
-        """Check a single file-tool target against the workspace boundary.
-
-        Shared boundary policy for file tools (``write_file``/``edit``/
-        ``apply_patch``). Returns ``None`` when no ``workspace_root`` is
-        configured or the path is inside it (i.e. no extra gate); otherwise
-        returns the ``external_dir:`` permission decision (default ``ask``).
-        """
-        ext = self._external_dir_target(path)
-        if ext is None:
-            return None
-        return self.check(ext, agent_name)
-
-    def suggest_scope_pattern(self, target: str) -> str:
-        """Suggest a reusable command-prefix pattern for a shell ``target``.
-
-        Derives a generalised glob (e.g. ``bash:git status`` ->
-        ``bash:git status *``) from the command-arity table so a persistent
-        approval can cover repeated invocations with different trailing args.
-        Non-shell targets (or targets already containing a glob) are returned
-        unchanged. Matching is untouched — ``fnmatch`` already handles ``*``.
-
-        Args:
-            target: The approval target, e.g. ``"bash:git status -s"``.
-
-        Returns:
-            The suggested reusable pattern, or ``target`` if no generalisation
-            applies.
-        """
-        try:
-            from .arity import derive_pattern
-            return derive_pattern(target)
-        except Exception:
-            return target
-
     def approve(
         self,
         target: str,
         approved: bool,
         scope: str = "once",
         agent_name: Optional[str] = None,
-        reusable_scope: bool = False,
-        pattern: Optional[str] = None,
     ) -> PersistentApproval:
         """
         Record an approval decision.
@@ -513,39 +343,15 @@ class PermissionManager:
             approved: Whether it was approved
             scope: Scope of approval (once, session, always)
             agent_name: Optional agent name
-            reusable_scope: When True and scope is session/always, derive a
-                reusable command-prefix pattern from ``target`` (e.g.
-                ``bash:git status`` -> ``bash:git status *``) instead of storing
-                the literal command. Ignored when an explicit ``pattern`` is
-                given. Defaults to False for backward compatibility.
-            pattern: Explicit pattern to record. Overrides both ``target`` and
-                ``reusable_scope`` derivation, letting callers (CLI/UI) present
-                and adjust the suggested scope before saving.
             
         Returns:
             The created PersistentApproval
         """
-        stored_pattern = pattern if pattern is not None else target
-        # ``derived`` is True only when we auto-generalise ``target`` into a
-        # reusable prefix glob here. An explicit ``pattern`` (or a literal
-        # target) is user-authored and keeps exact fnmatch semantics — the
-        # bare-prefix fallback in PersistentApproval.matches never applies to it.
-        derived = False
-        if (
-            pattern is None
-            and reusable_scope
-            and scope in ("session", "always")
-        ):
-            suggested = self.suggest_scope_pattern(target)
-            derived = suggested != target
-            stored_pattern = suggested
-
         approval = PersistentApproval(
-            pattern=stored_pattern,
+            pattern=target,
             approved=approved,
             scope=scope,
             agent_name=agent_name or self.agent_name,
-            derived=derived,
         )
         
         with self._lock:

src/praisonai-agents/praisonaiagents/permissions/rules.py

@@ -210,11 +210,6 @@ class PersistentApproval:
     expires_at: Optional[float] = None
     agent_name: Optional[str] = None
     id: str = field(default_factory=lambda: str(uuid.uuid4()))
-    # True only when ``pattern`` was auto-generated by the reusable
-    # command-prefix scope derivation (arity.derive_pattern). Gates the
-    # bare-prefix fallback in ``matches`` so user-authored globs like
-    # ``bash:rm *`` keep exact fnmatch semantics.
-    derived: bool = False
     
     def is_valid(self) -> bool:
         """Check if the approval is still valid."""
@@ -230,27 +225,7 @@ class PersistentApproval:
         if self.agent_name and agent_name and self.agent_name != agent_name:
             return False
         
-        if fnmatch.fnmatch(target, self.pattern):
-            return True
-
-        # A reusable command-prefix scope like "bash:git status *" is meant to
-        # cover the bare command too (e.g. "bash:git status" with no trailing
-        # args), which a plain "<prefix> *" glob would miss. Match the prefix
-        # exactly as well, without altering the general matching hot path.
-        #
-        # Gated on ``self.derived`` so this ONLY applies to patterns produced by
-        # the reusable-scope derivation (arity.derive_pattern). User-authored
-        # globs — shell or otherwise, e.g. "bash:rm *" or "read:/secret *" —
-        # keep their exact fnmatch semantics and this never changes their
-        # allow/deny decisions.
-        if self.derived and self.pattern.endswith(" *") and self.pattern.startswith(
-            ("bash:", "shell:")
-        ):
-            bare = self.pattern[:-2]
-            if target == bare:
-                return True
-
-        return False
+        return fnmatch.fnmatch(target, self.pattern)
     
     def to_dict(self) -> Dict[str, Any]:
         """Convert approval to dictionary."""
@@ -262,7 +237,6 @@ class PersistentApproval:
             "created_at": self.created_at,
             "expires_at": self.expires_at,
             "agent_name": self.agent_name,
-            "derived": self.derived,
         }
     
     @classmethod
@@ -276,5 +250,4 @@ class PersistentApproval:
             created_at=data.get("created_at", time.time()),
             expires_at=data.get("expires_at"),
             agent_name=data.get("agent_name"),
-            derived=data.get("derived", False),
         )

src/praisonai-agents/praisonaiagents/plugins/plugin.py

@@ -105,13 +105,6 @@ class Plugin(ABC):
     def after_tool(self, tool_name: str, result: Any) -> Any:
         """Called after tool execution. Can modify result."""
         return result
-
-    def before_tool_definitions(
-        self, tool_definitions: List[Dict[str, Any]]
-    ) -> List[Dict[str, Any]]:
-        """Called after advertised tool definitions are assembled and before
-        they reach the LLM. Can inspect, filter, or rewrite them."""
-        return tool_definitions
     
     def before_message(self, message: Dict[str, Any]) -> Dict[str, Any]:
         """Called before message is processed. Can modify message."""

src/praisonai-agents/praisonaiagents/runtime/test_resolve.py

@@ -14,7 +14,7 @@ import asyncio
 from unittest.mock import Mock, patch, MagicMock
 from typing import Any, Dict
 
-from praisonaiagents.runtime.resolve import (
+from .resolve import (
     resolve_runtime, 
     SessionContext,
     RuntimeProtocol,

src/praisonai-agents/praisonaiagents/runtime/test_turn_context.py

@@ -10,7 +10,7 @@ import pytest
 from typing import List, Dict, Any
 from unittest.mock import Mock, patch
 
-from praisonaiagents.runtime.turn_context import (
+from .turn_context import (
     PreparedTurnContext,
     ModelReference,
     ToolSchema, 
@@ -23,7 +23,7 @@ from praisonaiagents.runtime.turn_context import (
     create_default_delivery,
     create_session_correlation,
 )
-from praisonaiagents.runtime.context_builder import DefaultTurnContextBuilder
+from .context_builder import DefaultTurnContextBuilder
 
 
 class MockAgent:

src/praisonai-agents/praisonaiagents/skills/__init__.py

@@ -40,9 +40,6 @@ __all__ = [
     # Discovery
     "discover_skills",
     "get_default_skill_dirs",
-    # Bundles
-    "BundleManifest",
-    "discover_bundles",
     # Loader
     "SkillLoader",
     # Manager
@@ -95,10 +92,6 @@ def __getattr__(name: str):
     if name in ("discover_skills", "get_default_skill_dirs"):
         from .discovery import discover_skills, get_default_skill_dirs
         return locals()[name]
-
-    if name in ("BundleManifest", "discover_bundles"):
-        from .bundles import BundleManifest, discover_bundles
-        return locals()[name]
     
     if name == "SkillLoader":
         from .loader import SkillLoader

src/praisonai-agents/praisonaiagents/skills/bundles.py

@@ -1,197 +0,0 @@
-"""Skill bundles: named, reusable sets of skills.
-
-A *bundle* is a small manifest that references existing skills by name and is
-itself selectable as one unit. It is composition over the existing skills
-layer — not a new execution primitive. A bundle expands to its member skills,
-which then flow through the unchanged budget + prompt-injection path.
-
-Bundles are discovered alongside skills:
-- a top-level ``BUNDLE.yaml`` / ``BUNDLE.yml`` inside a skill directory, or
-- any ``*.yaml`` / ``*.yml`` file inside a ``bundles/`` subdirectory of a
-  skill root.
-
-Selection uses a ``@`` marker everywhere a skill is selected
-(``skills=["@backend-dev"]``), mirroring how skills already behave:
-forgiving membership, precedence-with-logging, and budget-awareness.
-"""
-
-import logging
-from dataclasses import dataclass, field
-from pathlib import Path
-from typing import List, Optional
-
-from .discovery import get_default_skill_dirs
-
-logger = logging.getLogger(__name__)
-
-BUNDLE_MARKER = "@"
-
-
-@dataclass
-class BundleManifest:
-    """A named set of skills selectable as one unit.
-
-    Attributes:
-        name: Bundle name (kebab-case, like a skill name).
-        description: What the bundle is for.
-        skills: Member skill names referenced by the bundle.
-        instruction: Optional extra guidance loaded above the member skills.
-        path: Path to the manifest file (set on discovery).
-    """
-
-    name: str
-    description: str = ""
-    skills: List[str] = field(default_factory=list)
-    instruction: Optional[str] = None
-    path: Optional[Path] = None
-
-    @classmethod
-    def from_dict(cls, data: dict, path: Optional[Path] = None) -> "BundleManifest":
-        """Build a BundleManifest from a parsed mapping.
-
-        Tolerant of both ``skills`` (preferred) and ``members`` keys for the
-        member list, and accepts a string or list for the members.
-        """
-        name = str(data.get("name") or "").strip()
-        if not name:
-            raise ValueError("Bundle manifest must define a 'name'")
-
-        members = data.get("skills")
-        if members is None:
-            members = data.get("members")
-        skills = _normalize_members(members)
-
-        return cls(
-            name=name,
-            description=str(data.get("description") or ""),
-            skills=skills,
-            instruction=(str(data["instruction"]) if data.get("instruction") else None),
-            path=path,
-        )
-
-
-def _normalize_members(value) -> List[str]:
-    """Normalize a member list to a list of clean skill-name strings."""
-    if value is None:
-        return []
-    if isinstance(value, str):
-        parts = value.replace(",", " ").split()
-        return [p.strip() for p in parts if p.strip()]
-    if isinstance(value, (list, tuple)):
-        return [str(v).strip() for v in value if str(v).strip()]
-    return []
-
-
-def strip_bundle_marker(selector: str) -> str:
-    """Return the bundle name for a ``@name`` selector (or the name itself)."""
-    s = selector.strip()
-    return s[len(BUNDLE_MARKER):] if s.startswith(BUNDLE_MARKER) else s
-
-
-def is_bundle_selector(selector: str) -> bool:
-    """True if ``selector`` is a ``@bundle`` reference."""
-    return isinstance(selector, str) and selector.strip().startswith(BUNDLE_MARKER)
-
-
-def _load_manifest_file(file_path: Path) -> Optional[BundleManifest]:
-    """Load a single bundle manifest from a YAML file, tolerantly."""
-    try:
-        import yaml  # type: ignore
-    except ImportError:
-        logger.warning(
-            "PyYAML is required to parse bundle manifests. "
-            "Install it with: pip install PyYAML"
-        )
-        return None
-    try:
-        with open(file_path, "r", encoding="utf-8") as f:
-            data = yaml.safe_load(f) or {}
-    except (OSError, Exception) as exc:  # noqa: BLE001 - tolerant discovery
-        logger.warning("Skipping invalid bundle %s: %s", file_path, exc)
-        return None
-    if not isinstance(data, dict):
-        logger.warning("Skipping bundle %s: manifest is not a mapping", file_path)
-        return None
-    try:
-        return BundleManifest.from_dict(data, path=file_path)
-    except Exception as exc:  # noqa: BLE001 - tolerant discovery
-        logger.warning("Skipping invalid bundle %s: %s", file_path, exc)
-        return None
-
-
-def _iter_bundle_files(root: Path):
-    """Yield candidate bundle-manifest files under a single skill root."""
-    # bundles/ subdirectory of the root
-    bundles_dir = root / "bundles"
-    if bundles_dir.exists() and bundles_dir.is_dir():
-        try:
-            for item in sorted(bundles_dir.iterdir()):
-                if item.is_file() and item.suffix.lower() in (".yaml", ".yml"):
-                    yield item
-        except PermissionError as exc:
-            logger.warning("Cannot read bundles directory %s: %s", bundles_dir, exc)
-
-    # BUNDLE.yaml inside each skill subdirectory
-    try:
-        for item in sorted(root.iterdir()):
-            if not item.is_dir():
-                continue
-            for name in ("BUNDLE.yaml", "BUNDLE.yml", "bundle.yaml", "bundle.yml"):
-                candidate = item / name
-                if candidate.exists() and candidate.is_file():
-                    yield candidate
-                    break
-    except PermissionError as exc:
-        logger.warning("Cannot read skills directory %s: %s", root, exc)
-
-
-def discover_bundles(
-    skill_dirs: Optional[List[str]] = None,
-    include_defaults: bool = True,
-) -> List[BundleManifest]:
-    """Discover bundle manifests alongside skills.
-
-    Mirrors :func:`discovery.discover_skills`: scans the same roots, is
-    forgiving of invalid manifests, and reports name collisions (first
-    wins, later entries shadowed-and-logged).
-
-    Args:
-        skill_dirs: Explicit skill-root directories to scan.
-        include_defaults: Whether to include default skill directories.
-
-    Returns:
-        List of discovered BundleManifest objects.
-    """
-    all_dirs: List[Path] = []
-
-    if skill_dirs:
-        for d in skill_dirs:
-            path = Path(d).expanduser().resolve()
-            if path.exists() and path.is_dir():
-                all_dirs.append(path)
-
-    if include_defaults:
-        all_dirs.extend(get_default_skill_dirs())
-
-    seen_dirs = set()
-    unique_dirs: List[Path] = []
-    for d in all_dirs:
-        if d not in seen_dirs:
-            seen_dirs.add(d)
-            unique_dirs.append(d)
-
-    bundles: List[BundleManifest] = []
-    for root in unique_dirs:
-        for file_path in _iter_bundle_files(root):
-            manifest = _load_manifest_file(file_path)
-            if manifest is None:
-                continue
-            if any(b.name == manifest.name for b in bundles):
-                logger.info(
-                    "Bundle '%s' at %s shadowed by earlier entry (precedence).",
-                    manifest.name, file_path,
-                )
-                continue
-            bundles.append(manifest)
-
-    return bundles

src/praisonai-agents/praisonaiagents/skills/manager.py

@@ -1,14 +1,11 @@
 """SkillManager for Agent Skills integration."""
 
 import logging
-from typing import List, Optional, Dict, TYPE_CHECKING
+from typing import List, Optional, Dict
 
 logger = logging.getLogger(__name__)
 
 from .models import SkillMetadata, SkillState
-
-if TYPE_CHECKING:
-    from .bundles import BundleManifest
 from .discovery import discover_skills, get_default_skill_dirs
 from .loader import SkillLoader, LoadedSkill
 from .prompt import generate_skills_xml
@@ -50,8 +47,6 @@ class SkillManager:
                 for safe-by-default behaviour).
         """
         self._skills: Dict[str, LoadedSkill] = {}
-        self._bundles: Dict[str, "BundleManifest"] = {}
-        self._selected_bundles: List[str] = []
         self._loader = SkillLoader()
         self._discovered = False
         self._validation_cache: Dict[str, ValidationResult] = {}
@@ -107,113 +102,6 @@ class SkillManager:
         self._discovered = True
         return len(props_list)
 
-    # ── Bundles (composition over skills) ─────────────────────────────
-
-    @property
-    def bundles(self) -> List["BundleManifest"]:
-        """Get all registered bundle manifests."""
-        return list(self._bundles.values())
-
-    @property
-    def bundle_names(self) -> List[str]:
-        """Get names of all registered bundles."""
-        return list(self._bundles.keys())
-
-    def add_bundle(self, manifest: "BundleManifest") -> None:
-        """Register a bundle manifest.
-
-        First registration wins; a later bundle of the same name is shadowed
-        and logged (same precedence stance discovery already uses).
-        """
-        if manifest.name in self._bundles:
-            logger.info(
-                "Bundle '%s' already registered; ignoring duplicate (precedence).",
-                manifest.name,
-            )
-            return
-        self._bundles[manifest.name] = manifest
-
-    def get_bundle(self, name: str) -> Optional["BundleManifest"]:
-        """Get a bundle manifest by name (``@`` marker optional)."""
-        from .bundles import strip_bundle_marker
-        return self._bundles.get(strip_bundle_marker(name))
-
-    def discover_bundles(
-        self,
-        skill_dirs: Optional[List[str]] = None,
-        include_defaults: bool = True,
-    ) -> int:
-        """Discover bundle manifests from directories.
-
-        Returns:
-            Number of bundles registered.
-        """
-        from .bundles import discover_bundles as _discover_bundles
-        manifests = _discover_bundles(skill_dirs, include_defaults)
-        added = 0
-        for manifest in manifests:
-            if manifest.name not in self._bundles:
-                self._bundles[manifest.name] = manifest
-                added += 1
-        return added
-
-    def resolve(self, selectors: List[str]) -> List[str]:
-        """Expand ``@bundle`` selectors into member skill names.
-
-        Plain skill names/paths pass through unchanged. A ``@bundle`` selector
-        expands to its member skill names (forgiving: a missing/unknown bundle
-        is logged, not fatal). Nested ``@bundle`` members are expanded
-        recursively, with cycle protection. Duplicates are removed while
-        preserving order.
-        """
-        from .bundles import is_bundle_selector, strip_bundle_marker
-
-        resolved: List[str] = []
-        seen = set()
-
-        def _add(item: str) -> None:
-            if item and item not in seen:
-                seen.add(item)
-                resolved.append(item)
-
-        def _expand(selector: str, stack: tuple) -> None:
-            if not is_bundle_selector(selector):
-                _add(selector)
-                return
-            name = strip_bundle_marker(selector)
-            if name in stack:
-                logger.warning(
-                    "Skill bundle cycle detected at '@%s'; skipping.", name,
-                )
-                return
-            manifest = self._bundles.get(name)
-            if manifest is None:
-                logger.warning(
-                    "Unknown skill bundle '@%s'; skipping (no such bundle).",
-                    name,
-                )
-                return
-            # Record selected bundles so their bundle-level 'instruction' can
-            # be surfaced in the prompt, including nested bundles.
-            if name not in self._selected_bundles:
-                self._selected_bundles.append(name)
-            for member in manifest.skills:
-                _expand(member, stack + (name,))
-
-        for selector in selectors or []:
-            _expand(selector, ())
-
-        return resolved
-
-    def get_bundle_instructions(self) -> List[str]:
-        """Return bundle-level instructions for selected bundles, in order."""
-        out: List[str] = []
-        for name in self._selected_bundles:
-            manifest = self._bundles.get(name)
-            if manifest is not None and manifest.instruction:
-                out.append(manifest.instruction)
-        return out
-
     def add_skill(self, skill_path: str) -> Optional[LoadedSkill]:
         """Add a single skill from a directory path.
 
@@ -228,26 +116,6 @@ class SkillManager:
             self._skills[skill.properties.name] = skill
         return skill
 
-    def add_skill_by_name(
-        self,
-        name: str,
-        skill_dirs: Optional[List[str]] = None,
-        include_defaults: bool = True,
-    ) -> Optional[LoadedSkill]:
-        """Add a single skill resolved by *name* (not path).
-
-        Searches the given/default skill directories for a skill whose name
-        matches and loads it. Used to materialise bundle members, which are
-        referenced by name. Forgiving: returns None if no match is found.
-        """
-        if name in self._skills:
-            return self._skills[name]
-        props_list = discover_skills(skill_dirs, include_defaults)
-        for props in props_list:
-            if props.name == name and props.path is not None:
-                return self.add_skill(str(props.path))
-        return None
-
     def get_skill(self, name: str) -> Optional[LoadedSkill]:
         """Get a skill by name.
 
@@ -290,59 +158,23 @@ class SkillManager:
         This is used for system prompt injection. Skills are filtered by:
         1. disable-model-invocation: true (excluded)
         2. Capability enforcement (if strict mode, exclude UNAVAILABLE skills)
-        3. Graceful-degradation fallbacks: a skill that declares
-           ``fallback_for_tools`` / ``fallback_for_servers`` is offered only
-           when the referenced capability is ABSENT.
         """
         available = []
-        # Resolved capability sets are needed to evaluate fallback eligibility.
-        # Computed lazily and cached by the validator.
-        available_tools = None
-        available_servers = None
         for skill in self._skills.values():
             # Skip if explicitly disabled for model invocation
             if getattr(skill.properties, "disable_model_invocation", False):
                 continue
-
-            req = getattr(skill.properties, "requirements", None)
-            is_fallback_skill = bool(
-                req is not None and (req.fallback_for_tools or req.fallback_for_servers)
-            )
-
-            # Check capability requirements when enforcement is strict, OR for
-            # fallback skills regardless of mode: a fallback skill must still
-            # satisfy its own ``requires_*`` gates (e.g. a web-via-terminal
-            # fallback that needs the terminal tool stays hidden if terminal is
-            # also absent), so we never inject an unusable skill.
-            if self._validator.enforcement_level == EnforcementLevel.STRICT or is_fallback_skill:
+                
+            # Check capability requirements if enforcement is strict
+            if self._validator.enforcement_level == EnforcementLevel.STRICT:
                 try:
                     validation = self.validate_skill_capabilities(skill.properties.name)
                     if validation.state == SkillState.UNAVAILABLE:
                         continue  # Skip unavailable skills in strict mode
-                    # A fallback skill must satisfy its own requires_* gates in
-                    # every mode. In non-strict modes missing tools/servers only
-                    # mark the skill DEGRADED (not UNAVAILABLE), so check the
-                    # critical-missing flag directly to avoid offering a fallback
-                    # that itself cannot run.
-                    if is_fallback_skill and validation.has_critical_missing:
-                        continue
                 except Exception as e:
                     logger.warning(f"Skipping skill '{skill.properties.name}' due to validation error: {e}")
                     continue
-
-            # Graceful degradation: a fallback skill is only offered when its
-            # target capability is absent. When the real tool/server is present,
-            # the fallback stays hidden to keep the skills index lean.
-            if is_fallback_skill:
-                if available_tools is None:
-                    available_tools = self._validator._get_available_tools()
-                if available_servers is None:
-                    available_servers = self._validator._get_available_servers()
-                if any(t in available_tools for t in req.fallback_for_tools):
-                    continue
-                if any(s in available_servers for s in req.fallback_for_servers):
-                    continue
-
+                    
             available.append(skill.metadata)
             
         return available
@@ -418,26 +250,11 @@ class SkillManager:
     def to_prompt(self) -> str:
         """Generate XML prompt for available skills.
 
-        When one or more ``@bundle`` selectors carried a bundle-level
-        ``instruction``, those are prepended in a ``<bundle_instructions>``
-        block so the documented bundle guidance actually reaches the prompt.
-
         Returns:
             XML string with <available_skills> block
         """
         metadata_list = self.get_available_skills()
-        skills_xml = generate_skills_xml(metadata_list)
-
-        instructions = self.get_bundle_instructions()
-        if not instructions:
-            return skills_xml
-
-        import html
-        lines = ["<bundle_instructions>"]
-        for text in instructions:
-            lines.append(f"  <instruction>{html.escape(text)}</instruction>")
-        lines.append("</bundle_instructions>")
-        return "\n".join(lines) + "\n" + skills_xml
+        return generate_skills_xml(metadata_list)
 
     def get_instructions(self, name: str) -> Optional[str]:
         """Get instructions for a skill, activating if needed.
@@ -1492,8 +1309,6 @@ version: 1.0.0
     def clear(self) -> None:
         """Clear all loaded skills."""
         self._skills.clear()
-        self._bundles.clear()
-        self._selected_bundles.clear()
         self._validation_cache.clear()
         self._validator.clear_cache()
         self._discovered = False

src/praisonai-agents/praisonaiagents/skills/models.py

@@ -36,19 +36,11 @@ class SkillRequirements:
         tools: Required tool names (from tool registry)
         env_vars: Required environment variables (use sparingly)
         openclaw_hints: OpenClaw-specific metadata (passthrough)
-        fallback_for_tools: Tools this skill is a graceful fallback for. The
-            skill is offered only when *none* of these tools are present,
-            keeping capable agents free of redundant fallback guidance.
-        fallback_for_servers: MCP servers this skill is a graceful fallback
-            for. The skill is offered only when *none* of these servers are
-            present.
     """
     servers: List[str] = field(default_factory=list)
     tools: List[str] = field(default_factory=list) 
     env_vars: List[str] = field(default_factory=list)
     openclaw_hints: dict = field(default_factory=dict)
-    fallback_for_tools: List[str] = field(default_factory=list)
-    fallback_for_servers: List[str] = field(default_factory=list)
     
     @classmethod
     def from_frontmatter(cls, metadata: dict) -> "SkillRequirements":
@@ -69,8 +61,6 @@ class SkillRequirements:
         tools = []
         env_vars = []
         openclaw_hints = {}
-        fallback_for_tools = []
-        fallback_for_servers = []
         
         # Parse servers
         if "requires_servers" in metadata:
@@ -97,26 +87,12 @@ class SkillRequirements:
         # OpenClaw hints (passthrough)
         if "openclaw" in metadata:
             openclaw_hints = metadata["openclaw"] if isinstance(metadata["openclaw"], dict) else {}
-
-        # Parse graceful-degradation fallback declarations. A fallback skill is
-        # surfaced only when its target capability is ABSENT (inverse of requires).
-        if "fallback_for_tools" in metadata:
-            fallback_for_tools = cls._normalize_list(metadata["fallback_for_tools"])
-        elif "fallback-for-tools" in metadata:
-            fallback_for_tools = cls._normalize_list(metadata["fallback-for-tools"])
-
-        if "fallback_for_servers" in metadata:
-            fallback_for_servers = cls._normalize_list(metadata["fallback_for_servers"])
-        elif "fallback-for-servers" in metadata:
-            fallback_for_servers = cls._normalize_list(metadata["fallback-for-servers"])
-
+            
         return cls(
             servers=servers,
             tools=tools,
             env_vars=env_vars, 
-            openclaw_hints=openclaw_hints,
-            fallback_for_tools=fallback_for_tools,
-            fallback_for_servers=fallback_for_servers
+            openclaw_hints=openclaw_hints
         )
     
     @staticmethod
@@ -132,10 +108,7 @@ class SkillRequirements:
     
     def is_empty(self) -> bool:
         """Check if no requirements are specified."""
-        return not any([
-            self.servers, self.tools, self.env_vars, self.openclaw_hints,
-            self.fallback_for_tools, self.fallback_for_servers,
-        ])
+        return not any([self.servers, self.tools, self.env_vars, self.openclaw_hints])
     
     def __bool__(self) -> bool:
         """Truth value: True if any requirements are specified."""

src/praisonai-agents/praisonaiagents/streaming/__init__.py

@@ -25,8 +25,6 @@ __all__ = [
     "AsyncStreamCallback",
     "create_text_printer_callback",
     "create_metrics_callback",
-    "emit_tool_progress",
-    "tool_progress_channel",
     "StreamLogger",
     "create_logging_callback",
 ]
@@ -39,8 +37,7 @@ def __getattr__(name: str):
         if name in (
             "StreamEvent", "StreamEventType", "StreamMetrics", 
             "StreamEventEmitter", "StreamCallback", "AsyncStreamCallback",
-            "create_text_printer_callback", "create_metrics_callback",
-            "emit_tool_progress", "tool_progress_channel"
+            "create_text_printer_callback", "create_metrics_callback"
         ):
             from .events import (
                 StreamEvent,
@@ -51,8 +48,6 @@ def __getattr__(name: str):
                 AsyncStreamCallback,
                 create_text_printer_callback,
                 create_metrics_callback,
-                emit_tool_progress,
-                tool_progress_channel,
             )
             
             _events_exports = {
@@ -64,8 +59,6 @@ def __getattr__(name: str):
                 "AsyncStreamCallback": AsyncStreamCallback,
                 "create_text_printer_callback": create_text_printer_callback,
                 "create_metrics_callback": create_metrics_callback,
-                "emit_tool_progress": emit_tool_progress,
-                "tool_progress_channel": tool_progress_channel,
             }
             return _events_exports.get(name)
         

src/praisonai-agents/praisonaiagents/streaming/events.py

@@ -30,7 +30,6 @@ class StreamEventType(Enum):
     DELTA_TOOL_CALL = "delta_tool_call"  # Tool call delta (function name, args chunk)
     TOOL_CALL_END = "tool_call_end"      # Tool call complete (stream end marker)
     TOOL_CALL_START = "tool_call_start"  # Tool execution starting (complete parsed args)
-    TOOL_PROGRESS = "tool_progress"      # Incremental progress/output while a tool is running
     TOOL_CALL_RESULT = "tool_call_result"  # Tool execution completed (with result)
     LAST_TOKEN = "last_token"            # Final content delta
     STREAM_END = "stream_end"            # Stream completed successfully
@@ -242,11 +241,8 @@ class StreamEventEmitter:
         if self._collect_metrics and self._metrics:
             self._metrics.update_from_event(event)
         
-        # Call all sync callbacks. Iterate over a snapshot so callbacks
-        # registered/removed concurrently (e.g. a run-progress probe added
-        # from the event loop while the agent emits from a worker thread)
-        # cannot corrupt iteration or raise "list changed size".
-        for callback in list(self._callbacks):
+        # Call all sync callbacks
+        for callback in self._callbacks:
             try:
                 callback(event)
             except Exception as e:
@@ -263,8 +259,8 @@ class StreamEventEmitter:
         if self._collect_metrics and self._metrics:
             self._metrics.update_from_event(event)
         
-        # Call sync callbacks (snapshot — see emit() for rationale).
-        for callback in list(self._callbacks):
+        # Call sync callbacks
+        for callback in self._callbacks:
             try:
                 callback(event)
             except Exception as e:
@@ -272,7 +268,7 @@ class StreamEventEmitter:
                 logger.warning("Streaming sync callback failed in async context: %s", e, exc_info=True)
         
         # Call async callbacks
-        for callback in list(self._async_callbacks):
+        for callback in self._async_callbacks:
             try:
                 await callback(event)
             except Exception as e:
@@ -318,76 +314,3 @@ def create_metrics_callback(metrics: StreamMetrics) -> StreamCallback:
         metrics.update_from_event(event)
     
     return updater
-
-
-# ---------------------------------------------------------------------------
-# Tool-progress channel
-#
-# A thread-local channel that lets a running tool push incremental progress
-# (stdout/stderr lines, percentage, status text) while it executes, without
-# having to change the tool's signature. The agent's tool-execution loop
-# activates a sink around each tool call; the tool calls ``emit_tool_progress``
-# to surface partial output. Zero overhead when no sink is active.
-# ---------------------------------------------------------------------------
-
-import contextlib as _contextlib
-import contextvars as _contextvars
-
-_tool_progress_sink: "_contextvars.ContextVar[Optional[StreamCallback]]" = (
-    _contextvars.ContextVar("praisonai_tool_progress_sink", default=None)
-)
-
-
-def emit_tool_progress(
-    output: Optional[str] = None,
-    *,
-    progress: Optional[float] = None,
-    metadata: Optional[Dict[str, Any]] = None,
-) -> bool:
-    """Emit incremental progress from inside a running tool.
-
-    Tools (or wrappers around long-running work) call this to surface partial
-    output while they execute. If no sink is active (the common case outside an
-    agent run) this is a cheap no-op that returns ``False``.
-
-    Args:
-        output: Partial text/output chunk (e.g. a line of stdout).
-        progress: Optional completion fraction in the range 0.0–1.0.
-        metadata: Optional structured metadata (e.g. ``{"stream": "stderr"}``).
-
-    Returns:
-        ``True`` if the progress was forwarded to an active sink, else ``False``.
-    """
-    sink = _tool_progress_sink.get()
-    if sink is None:
-        return False
-    md: Dict[str, Any] = dict(metadata) if metadata else {}
-    if progress is not None:
-        md["progress"] = progress
-    try:
-        sink(StreamEvent(
-            type=StreamEventType.TOOL_PROGRESS,
-            content=output,
-            metadata=md or None,
-        ))
-    except Exception as e:  # never break tool execution on a progress failure
-        logger.debug("emit_tool_progress sink failed: %s", e)
-        return False
-    return True
-
-
-@_contextlib.contextmanager
-def tool_progress_channel(sink: Optional[StreamCallback]):
-    """Activate a progress sink for the duration of a tool call.
-
-    The agent's tool-execution loop wraps each tool invocation with this so that
-    ``emit_tool_progress`` calls made by the tool are forwarded to ``sink``.
-    Passing ``None`` explicitly clears any inherited sink for the duration of the
-    context, so nested no-callback execution never leaks progress into a parent
-    channel.
-    """
-    token = _tool_progress_sink.set(sink)
-    try:
-        yield
-    finally:
-        _tool_progress_sink.reset(token)

src/praisonai-agents/praisonaiagents/telemetry/telemetry.py

@@ -36,12 +36,6 @@ def _get_posthog():
 # Cached result to avoid repeated environment variable checks
 _TELEMETRY_DISABLED_CACHE = None
 
-# Programmatic override set by enable_telemetry()/disable_telemetry().
-# Takes precedence over the env-based default (but NOT over an explicit
-# env opt-out), and bypasses the cache so downstream instrumentation gates
-# (e.g. instrument_agent/instrument_workflow) see the updated state.
-_MONITORING_OVERRIDE = None
-
 def _is_monitoring_disabled() -> bool:
     """
     Check if monitoring/telemetry is disabled via environment variables.
@@ -52,21 +46,9 @@ def _is_monitoring_disabled() -> bool:
     The legacy disable flags still work for backward compatibility.
     
     This function is cached to avoid repeated environment variable lookups.
-    A programmatic override via enable_telemetry()/disable_telemetry() takes
-    precedence over the default, unless telemetry was explicitly disabled
-    via environment variables.
     """
     global _TELEMETRY_DISABLED_CACHE
     
-    # Explicit env opt-out always wins, even over a programmatic enable.
-    if _is_telemetry_explicitly_disabled():
-        return True
-    
-    # Programmatic override (set by enable_telemetry/disable_telemetry)
-    # bypasses the cache so instrumentation gates reflect the new state.
-    if _MONITORING_OVERRIDE is not None:
-        return _MONITORING_OVERRIDE
-    
     # Return cached result if available
     if _TELEMETRY_DISABLED_CACHE is not None:
         return _TELEMETRY_DISABLED_CACHE
@@ -93,22 +75,6 @@ def _is_monitoring_disabled() -> bool:
     _TELEMETRY_DISABLED_CACHE = not explicitly_enabled
     return _TELEMETRY_DISABLED_CACHE
 
-def _is_telemetry_explicitly_disabled() -> bool:
-    """
-    Check if telemetry is explicitly disabled via opt-out environment variables.
-
-    Unlike `_is_monitoring_disabled`, this only returns True when the user has
-    explicitly opted out (e.g. DO_NOT_TRACK). It does NOT treat the
-    "disabled by default" case as disabled, so programmatic `enable_telemetry()`
-    can re-enable telemetry unless the user has explicitly opted out.
-    """
-    return any([
-        os.environ.get('PRAISONAI_PERFORMANCE_DISABLED', '').lower() in ('true', '1', 'yes'),
-        os.environ.get('PRAISONAI_TELEMETRY_DISABLED', '').lower() in ('true', '1', 'yes'),
-        os.environ.get('PRAISONAI_DISABLE_TELEMETRY', '').lower() in ('true', '1', 'yes'),
-        os.environ.get('DO_NOT_TRACK', '').lower() in ('true', '1', 'yes'),
-    ])
-
 class MinimalTelemetry:
     """
     Minimal telemetry collector for anonymous usage tracking.
@@ -246,7 +212,7 @@ class MinimalTelemetry:
             success: Whether the execution was successful
             async_mode: If True, defer PostHog capture to prevent blocking in streaming scenarios
         """
-        if not self.enabled or self._metrics_lock is None:
+        if not self.enabled:
             return
             
         with self._metrics_lock:
@@ -301,7 +267,7 @@ class MinimalTelemetry:
             task_name: Name of the task (not logged, just for counting)
             success: Whether the task completed successfully
         """
-        if not self.enabled or self._metrics_lock is None:
+        if not self.enabled:
             return
             
         with self._metrics_lock:
@@ -330,7 +296,7 @@ class MinimalTelemetry:
             success: Whether the tool call was successful
             execution_time: Time in seconds the tool took to execute (optional)
         """
-        if not self.enabled or self._metrics_lock is None:
+        if not self.enabled:
             return
             
         with self._metrics_lock:
@@ -384,7 +350,7 @@ class MinimalTelemetry:
         Args:
             error_type: Type of error (not the full message)
         """
-        if not self.enabled or self._metrics_lock is None:
+        if not self.enabled:
             return
             
         with self._metrics_lock:
@@ -437,7 +403,7 @@ class MinimalTelemetry:
         Returns:
             Dictionary of current metrics
         """
-        if not self.enabled or self._metrics_lock is None:
+        if not self.enabled:
             return {"enabled": False}
             
         with self._metrics_lock:
@@ -456,7 +422,7 @@ class MinimalTelemetry:
         
         In a real implementation, this would send data to a backend.
         """
-        if not self.enabled or self._metrics_lock is None:
+        if not self.enabled:
             return
             
         metrics = self.get_metrics()
@@ -504,7 +470,7 @@ class MinimalTelemetry:
         Shutdown telemetry and ensure all events are sent.
         Forces proper cleanup of background threads to prevent hanging.
         """
-        if not self.enabled or self._shutdown_lock is None:
+        if not self.enabled:
             return
         
         # Use lock to prevent concurrent shutdown calls
@@ -691,12 +657,8 @@ def get_telemetry() -> MinimalTelemetry:
 
 def disable_telemetry():
     """Programmatically disable telemetry."""
-    global _telemetry_instance, _MONITORING_OVERRIDE
+    global _telemetry_instance
     with _telemetry_instance_lock:
-        # Flip the monitoring gate so instrumentation paths that check
-        # _is_monitoring_disabled() (e.g. instrument_agent/instrument_workflow)
-        # also stop installing hooks.
-        _MONITORING_OVERRIDE = True
         if _telemetry_instance:
             _telemetry_instance.enabled = False
         else:
@@ -739,24 +701,13 @@ def force_shutdown_telemetry():
 
 def enable_telemetry():
     """Programmatically enable telemetry (if not disabled by environment)."""
-    global _telemetry_instance, _MONITORING_OVERRIDE, _TELEMETRY_DISABLED_CACHE
+    global _telemetry_instance
     with _telemetry_instance_lock:
-        if _is_telemetry_explicitly_disabled():
-            return
-        # Flip the monitoring gate so instrumentation paths that check
-        # _is_monitoring_disabled() (e.g. instrument_agent/instrument_workflow)
-        # actually install their hooks even in the default (no env var) case.
-        _MONITORING_OVERRIDE = False
-        _TELEMETRY_DISABLED_CACHE = False
-        needs_init = (
-            _telemetry_instance is None
-            or getattr(_telemetry_instance, "_metrics_lock", None) is None
-        )
-        if needs_init:
-            _telemetry_instance = MinimalTelemetry(enabled=True)
-        else:
-            _telemetry_instance.enabled = True
-            _telemetry_instance._shutdown_complete = False
+        if not _is_telemetry_disabled():
+            if _telemetry_instance:
+                _telemetry_instance.enabled = True
+            else:
+                _telemetry_instance = MinimalTelemetry(enabled=True)
 
 # For backward compatibility with existing code
 class TelemetryCollector:

src/praisonai-agents/praisonaiagents/tools/__init__.py

@@ -5,10 +5,7 @@ from typing import Any
 # Note: actual lazy loading cache is implemented with _loaded_classes in __getattr__
 
 # Export core tool items for organized imports (lightweight)
-from .base import (
-    BaseTool, ToolResult, ToolValidationError, validate_tool,
-    multimodal_content, text_part, image_part, file_part,
-)
+from .base import BaseTool, ToolResult, ToolValidationError, validate_tool
 from .decorator import tool, FunctionTool
 from .registry import get_registry, register_tool, get_tool, add_tool, has_tool, remove_tool, list_tools, list_available_tools, list_tools_with_allowed_filter, list_tools_with_hermes_filter, ToolRegistry
 from .tools import Tools
@@ -189,11 +186,6 @@ TOOL_MAPPINGS = {
     'send_message': ('.messaging_tools', None),
     'messaging_tools': ('.messaging_tools', None),
     
-    # Search Tools (fast, capped content grep + file glob)
-    'grep': ('.search_tools', None),
-    'glob': ('.search_tools', None),
-    'search_tools': ('.search_tools', None),
-
     # AST-Grep Tools (structural code search/rewrite)
     'ast_grep_search': ('.ast_grep_tool', None),
     'ast_grep_rewrite': ('.ast_grep_tool', None),
@@ -372,7 +364,6 @@ def __getattr__(name: str) -> Any:
             'jira_watch_issue', 'jira_watch_project', 'jira_get_issue_info', 'jira_search_issues',
             'schedule_add', 'schedule_list', 'schedule_remove',
             'send_message',
-            'grep', 'glob',
             'ast_grep_search', 'ast_grep_rewrite', 'ast_grep_scan', 'is_ast_grep_available', 'get_ast_grep_tools',
             'store_memory', 'search_memory',
             'store_learning', 'search_learning',
@@ -383,7 +374,7 @@ def __getattr__(name: str) -> Any:
             'clarify'
         ]:
             return getattr(module, name)
-        if name in ['file_tools', 'spider_tools', 'python_tools', 'shell_tools', 'cot_tools', 'tavily_tools', 'youdotcom_tools', 'exa_tools', 'crawl4ai_tools', 'skill_tools', 'github_tools', 'jira_tools', 'schedule_tools', 'messaging_tools', 'search_tools', 'ast_grep_tools', 'email_tools']:
+        if name in ['file_tools', 'spider_tools', 'python_tools', 'shell_tools', 'cot_tools', 'tavily_tools', 'youdotcom_tools', 'exa_tools', 'crawl4ai_tools', 'skill_tools', 'github_tools', 'jira_tools', 'schedule_tools', 'messaging_tools', 'ast_grep_tools', 'email_tools']:
             return module  # Returns the callable module
         return getattr(module, name)
     else:
@@ -396,7 +387,6 @@ def __getattr__(name: str) -> Any:
 __all__ = list(TOOL_MAPPINGS.keys()) + [
     'Injected', 'AgentState',
     'BaseTool', 'ToolResult', 'ToolValidationError', 'validate_tool',
-    'multimodal_content', 'text_part', 'image_part', 'file_part',
     'tool', 'FunctionTool',
     'get_registry', 'register_tool', 'get_tool', 'add_tool', 'has_tool', 'remove_tool', 
     'list_tools', 'list_available_tools', 'list_tools_with_allowed_filter', 'list_tools_with_hermes_filter', 'ToolRegistry',

src/praisonai-agents/praisonaiagents/tools/base.py

@@ -30,120 +30,35 @@ class ToolValidationError(Exception):
 
 
 class ToolResult:
-    """Wrapper for tool execution results.
-
-    In addition to the text/JSON ``output`` channel, tools may return a
-    structured, multimodal ``content`` channel so that images/files produced by
-    a tool become model-visible message parts on the next turn (e.g. a
-    screenshot tool, chart renderer, or PDF rasteriser feeding a vision model).
-
-    ``content`` is an ordered list of content parts. Each part is a dict:
-
-    - ``{"type": "text", "text": "..."}``
-    - ``{"type": "image", "data": <base64-str-or-bytes>, "mime": "image/png",
-       "name": "shot.png"}``
-    - ``{"type": "image", "url": "https://... or data:..."}``
-    - ``{"type": "file", "data": ..., "mime": "application/pdf", "name": ...}``
-
-    Plain text/JSON tool returns behave exactly as before; multimodal is purely
-    additive and opt-in by the tool author.
-    """
-
+    """Wrapper for tool execution results."""
+    
     def __init__(
         self,
         output: Any,
         success: bool = True,
         error: Optional[str] = None,
-        metadata: Optional[Dict[str, Any]] = None,
-        content: Optional[List[Dict[str, Any]]] = None
+        metadata: Optional[Dict[str, Any]] = None
     ):
         self.output = output
         self.success = success
         self.error = error
         self.metadata = metadata or {}
-        self.content = content
-
-    @property
-    def is_multimodal(self) -> bool:
-        """True if this result carries structured (possibly image/file) parts."""
-        return bool(self.content)
-
+    
     def __str__(self) -> str:
         if self.success:
-            if self.output is not None:
-                return str(self.output)
-            # Derive a text summary from structured content if no output set
-            if self.content:
-                texts = [p.get("text", "") for p in self.content
-                         if isinstance(p, dict) and p.get("type") == "text"]
-                if texts:
-                    return "\n".join(t for t in texts if t)
-                return "[multimodal tool result]"
             return str(self.output)
         return f"Error: {self.error}"
-
+    
     def __repr__(self) -> str:
         return f"ToolResult(success={self.success}, output={self.output!r})"
-
+    
     def to_dict(self) -> Dict[str, Any]:
-        data = {
+        return {
             "output": self.output,
             "success": self.success,
             "error": self.error,
             "metadata": self.metadata
         }
-        if self.content:
-            data["content"] = self.content
-        return data
-
-
-def multimodal_content(*parts: Dict[str, Any], output: Any = None,
-                       success: bool = True) -> "ToolResult":
-    """Convenience factory for building a multimodal ToolResult.
-
-    Example::
-
-        from praisonaiagents.tools import multimodal_content, image_part, text_part
-
-        def screenshot() -> ToolResult:
-            png_bytes = capture()
-            return multimodal_content(
-                text_part("Here is the current screen:"),
-                image_part(png_bytes, mime="image/png", name="screen.png"),
-            )
-    """
-    return ToolResult(output=output, success=success, content=list(parts))
-
-
-def text_part(text: str) -> Dict[str, Any]:
-    """Build a text content part."""
-    return {"type": "text", "text": text}
-
-
-def image_part(data: Any = None, *, mime: str = "image/png",
-               name: Optional[str] = None, url: Optional[str] = None) -> Dict[str, Any]:
-    """Build an image content part from raw bytes/base64 or a URL/data URI."""
-    part: Dict[str, Any] = {"type": "image", "mime": mime}
-    if url is not None:
-        part["url"] = url
-    else:
-        part["data"] = data
-    if name:
-        part["name"] = name
-    return part
-
-
-def file_part(data: Any = None, *, mime: str = "application/octet-stream",
-              name: Optional[str] = None, url: Optional[str] = None) -> Dict[str, Any]:
-    """Build a generic file content part from raw bytes/base64 or a URL."""
-    part: Dict[str, Any] = {"type": "file", "mime": mime}
-    if url is not None:
-        part["url"] = url
-    else:
-        part["data"] = data
-    if name:
-        part["name"] = name
-    return part
 
 
 class BaseTool(ABC):

src/praisonai-agents/praisonaiagents/tools/edit_tools.py

@@ -45,8 +45,7 @@ _LSP_LANGUAGE_BY_EXT = {
 class EditTools:
     """Tools for file editing and patching operations."""
     
-    def __init__(self, workspace=None, post_edit_diagnostics: str = "auto",
-                 post_edit_format: str = "off", formatters: Optional[dict] = None):
+    def __init__(self, workspace=None, post_edit_diagnostics: str = "auto"):
         """Initialize EditTools with optional workspace containment.
         
         Args:
@@ -63,24 +62,6 @@ class EditTools:
                 - ``"off"``: never run diagnostics (zero overhead).
                 Checkers are auto-detected by file type and silently skipped
                 when unavailable; a missing linter never fails the edit.
-            post_edit_format: When to run a configured, language-appropriate
-                formatter on a file after a successful edit/patch, then persist
-                the formatted result. Mirrors ``post_edit_diagnostics``. One of:
-                - ``"off"`` (default): never run a formatter (zero overhead;
-                  byte-for-byte identical to the pre-existing behaviour).
-                - ``"auto"`` / ``"on"``: run a formatter if one is detected for
-                  the file type, otherwise silently skip.
-                Formatters are auto-detected by file type and silently skipped
-                when unavailable; a missing or failing formatter never fails the
-                edit (the edit still succeeds, just unformatted).
-            formatters: Optional mapping of lowercase file extension (e.g.
-                ``".py"``) to a ``(tool_name, argv_template)`` formatter, where
-                ``argv_template`` is a list whose entries may include the literal
-                placeholder ``"{path}"`` (replaced with the file path) — or whose
-                final element is the path when no placeholder is given. Lets a
-                project pin its own formatter (e.g. ``black`` instead of
-                ``ruff format``). Unspecified extensions fall back to the
-                built-in defaults.
         """
         self._workspace = workspace
         self._file_cache = {}  # Cache for staleness checking
@@ -90,14 +71,6 @@ class EditTools:
         if mode not in ("auto", "on", "off"):
             mode = "auto"
         self._post_edit_diagnostics = mode
-
-        fmt_mode = (post_edit_format or "off")
-        if isinstance(fmt_mode, str):
-            fmt_mode = fmt_mode.lower()
-        if fmt_mode not in ("auto", "on", "off"):
-            fmt_mode = "off"
-        self._post_edit_format = fmt_mode
-        self._formatters = formatters or {}
     
     def _validate_path(self, filepath: str) -> str:
         """Validate and resolve a file path within workspace constraints."""
@@ -450,151 +423,6 @@ class EditTools:
             logger.debug("Diagnostics error for %s: %s", display_path, e)
             return ""
 
-    # ------------------------------------------------------------------
-    # Post-edit formatting
-    #
-    # Symmetric to the post-edit diagnostics hook: after a successful mutation
-    # we optionally run a configured, language-appropriate formatter on the
-    # single modified file and persist the formatted result.  All imports are
-    # deferred and any failure is swallowed: a missing or broken formatter must
-    # never turn a successful edit into a failure (the edit succeeds, just
-    # unformatted).
-    # ------------------------------------------------------------------
-
-    def _format_command(self, safe_path: str) -> Optional[Tuple[str, List[str]]]:
-        """Resolve a (tool_name, argv) formatter for ``safe_path`` by extension.
-
-        Honours any caller-supplied ``formatters`` override first, then falls
-        back to built-in defaults.  Returns ``None`` when no formatter is
-        configured for the file type or the executable is not installed, so the
-        caller can silently skip.  Lazy-imports ``shutil``.
-        """
-        import shutil
-
-        ext = os.path.splitext(safe_path)[1].lower()
-
-        def _materialise(argv_template: List[str]) -> List[str]:
-            # Substitute the literal ``{path}`` placeholder where present; if no
-            # entry references it, append the path so a bare formatter command
-            # still receives the file to format.
-            if any("{path}" in part for part in argv_template):
-                return [part.replace("{path}", safe_path) for part in argv_template]
-            return list(argv_template) + [safe_path]
-
-        def _resolvable(exe: str) -> bool:
-            # Accept an absolute path, a binary on PATH, or a project-local
-            # relative command (e.g. ``./node_modules/.bin/prettier``) that
-            # exists relative to the edited file's directory.
-            if os.path.isabs(exe) or shutil.which(exe):
-                return True
-            if os.sep in exe or (os.altsep and os.altsep in exe):
-                candidate = os.path.join(os.path.dirname(safe_path), exe)
-                return os.path.isfile(candidate) and os.access(candidate, os.X_OK)
-            return False
-
-        # Caller override takes precedence and pins the project's formatter.
-        override = self._formatters.get(ext)
-        if override:
-            tool_name, argv_template = override
-            argv = _materialise(list(argv_template))
-            if _resolvable(argv[0]):
-                return tool_name, argv
-            return None
-
-        candidates: List[Tuple[str, List[str]]] = []
-        if ext in (".py", ".pyi"):
-            if shutil.which("ruff"):
-                candidates.append((
-                    "ruff", ["ruff", "format", "--quiet", "--no-cache", safe_path],
-                ))
-            if shutil.which("black"):
-                candidates.append(("black", ["black", "--quiet", safe_path]))
-        elif ext in (".ts", ".tsx", ".js", ".jsx", ".mjs", ".cjs", ".json",
-                     ".css", ".scss", ".less", ".html", ".md", ".yaml", ".yml"):
-            if shutil.which("prettier"):
-                # Run prettier without discovering workspace config or
-                # EditorConfig files so we never execute repository-controlled
-                # JS/TS config code from the edited project.
-                candidates.append((
-                    "prettier",
-                    ["prettier", "--write", "--no-config", "--no-editorconfig",
-                     "--log-level", "warn", safe_path],
-                ))
-        elif ext == ".go":
-            if shutil.which("gofmt"):
-                candidates.append(("gofmt", ["gofmt", "-w", safe_path]))
-        elif ext == ".rs":
-            if shutil.which("rustfmt"):
-                candidates.append(("rustfmt", ["rustfmt", "--quiet", safe_path]))
-
-        for tool_name, argv in candidates:
-            if _resolvable(argv[0]):
-                return tool_name, argv
-        return None
-
-    def _apply_post_edit_format(self, safe_path: str) -> bool:
-        """Run a configured formatter on ``safe_path`` in place.
-
-        Does nothing when formatting is disabled or no formatter is available.
-        Any failure (missing binary, timeout, non-zero exit) is logged at debug
-        level and swallowed: a formatter must never fail an edit.
-
-        Returns ``True`` only when a formatter ran to completion with a zero
-        exit code (so the on-disk content is trustworthy and the cached hash
-        should be refreshed).  Returns ``False`` when no formatter ran or it
-        failed, so the caller keeps the known-good post-edit hash and does not
-        adopt partial/corrupt formatter output as the new baseline.
-        """
-        if self._post_edit_format == "off":
-            return False
-        try:
-            resolved = self._format_command(safe_path)
-            if resolved is None:
-                return False
-            _tool_name, argv = resolved
-
-            import subprocess
-            proc = subprocess.run(
-                argv,
-                capture_output=True,
-                text=True,
-                timeout=_DIAGNOSTICS_TIMEOUT,
-                cwd=os.path.dirname(safe_path) or None,
-            )
-            if proc.returncode != 0:
-                output = ((proc.stdout or "") + (proc.stderr or "")).strip()
-                suffix = f": {self._bound_output(output)}" if output else ""
-                logger.debug(
-                    "Formatter %s failed for %s with exit code %s%s",
-                    _tool_name, safe_path, proc.returncode, suffix,
-                )
-                return False
-            return True
-        except Exception as e:  # never let formatting break a successful edit
-            logger.debug("Formatter skipped/failed for %s: %s", safe_path, e)
-            return False
-
-    def _refresh_hash_after_format(self, safe_path: str) -> None:
-        """Re-record the on-disk hash after an in-place format.
-
-        A formatter may rewrite the file, so the hash recorded right after the
-        edit can become stale.  Re-hash the current on-disk content (BOM
-        stripped, exactly as ``read_file`` would) so a follow-up edit in the
-        same session is not falsely flagged as stale.  Best-effort: any failure
-        is swallowed so it cannot break a successful edit.
-        """
-        try:
-            with open(safe_path, 'rb') as f:
-                raw_bytes = f.read()
-            if raw_bytes.startswith(b'\xef\xbb\xbf'):
-                raw_bytes = raw_bytes[3:]
-            content = raw_bytes.decode('utf-8')
-            new_hash = self._compute_content_hash(content)
-            self._file_cache[safe_path] = new_hash
-            _file_locks.record_read_hash(safe_path, new_hash)
-        except Exception as e:
-            logger.debug("Hash refresh skipped after format for %s: %s", safe_path, e)
-
     # ------------------------------------------------------------------
     # Fuzzy matching ladder
     #
@@ -880,16 +708,7 @@ class EditTools:
                 new_hash = self._compute_content_hash(new_content)
                 self._file_cache[safe_path] = new_hash
                 _file_locks.record_read_hash(safe_path, new_hash)
-
-                # Optionally format the touched file in place, then refresh the
-                # recorded hash so a follow-up edit is not flagged as stale.
-                # Only adopt the on-disk content as the new baseline when the
-                # formatter succeeded; on failure we keep the known-good
-                # post-edit hash rather than trusting partial output.
-                if self._post_edit_format != "off":
-                    if self._apply_post_edit_format(safe_path):
-                        self._refresh_hash_after_format(safe_path)
-
+                
                 result = f"Success: Made {replacements} replacement(s) in {filepath}\n\nDiff:\n{diff}"
                 return result + self._run_diagnostics(safe_path, filepath)
             
@@ -1149,13 +968,6 @@ class EditTools:
                         applied.append(("write", safe_path, backup))
                         self._file_cache[safe_path] = content_hash
                         _file_locks.record_read_hash(safe_path, content_hash)
-                        # Optionally format the touched file in place before
-                        # diagnostics run, refreshing the recorded hash only
-                        # when the formatter succeeded so partial/corrupt output
-                        # is never adopted as the new baseline.
-                        if self._post_edit_format != "off":
-                            if self._apply_post_edit_format(safe_path):
-                                self._refresh_hash_after_format(safe_path)
                         verb = "Added" if kind == "add" else "Updated"
                         diagnostics = self._run_diagnostics(safe_path, display)
                         messages.append(f"{verb} {display}\n{diff}{diagnostics}")
@@ -1367,23 +1179,15 @@ def search_files(directory: str, pattern: str,
     return _edit_tools.search_files(directory, pattern, file_pattern)
 
 
-def create_edit_tools(workspace=None, post_edit_diagnostics: str = "auto",
-                      post_edit_format: str = "off",
-                      formatters: Optional[dict] = None) -> EditTools:
+def create_edit_tools(workspace=None, post_edit_diagnostics: str = "auto") -> EditTools:
     """Create EditTools instance with optional workspace containment.
     
     Args:
         workspace: Optional Workspace instance for path containment
         post_edit_diagnostics: Diagnostics mode ("auto"|"on"|"off"); see
             ``EditTools.__init__`` for details.
-        post_edit_format: Formatter mode ("off"|"auto"|"on"); see
-            ``EditTools.__init__`` for details. Defaults to ``"off"`` for
-            backward compatibility.
-        formatters: Optional ext -> ``(tool_name, argv_template)`` override map;
-            see ``EditTools.__init__`` for details.
         
     Returns:
         EditTools instance configured with workspace
     """
-    return EditTools(workspace=workspace, post_edit_diagnostics=post_edit_diagnostics,
-                     post_edit_format=post_edit_format, formatters=formatters)
+    return EditTools(workspace=workspace, post_edit_diagnostics=post_edit_diagnostics)

src/praisonai-agents/praisonaiagents/tools/file_tools.py

@@ -20,39 +20,6 @@ import logging
 from ..approval import require_approval
 from . import _file_locks
 
-# Default cap on the number of lines returned by a single ``read_file`` call
-# when no explicit ``limit`` is given.  Keeps an unbounded whole-file read from
-# silently blowing the context budget; the model is told how to page for more.
-DEFAULT_MAX_LINES = 2000
-
-# Default cap on characters rendered per line so one pathologically long line
-# cannot dominate the window.
-DEFAULT_MAX_LINE_CHARS = 2000
-
-
-def _render_with_line_numbers(lines, start_index, max_line_chars):
-    """Render ``lines`` with a right-aligned 1-based line-number gutter.
-
-    Args:
-        lines: The window of lines to render.
-        start_index: 0-based index of the first line within the full file.
-        max_line_chars: Truncate any single line longer than this.
-
-    Returns:
-        str: Line-numbered content (e.g. ``   42\\tconst x = ...``).
-    """
-    if not lines:
-        return ""
-    last_number = start_index + len(lines)
-    width = max(len(str(last_number)), 6)
-    rendered = []
-    for line_index, line in enumerate(lines):
-        if max_line_chars and max_line_chars > 0 and len(line) > max_line_chars:
-            line = line[:max_line_chars] + "... (line truncated)"
-        rendered.append(f"{str(start_index + line_index + 1).rjust(width)}\t{line}")
-    return "\n".join(rendered)
-
-
 class FileTools:
     """Tools for file operations including read, write, list, and information."""
     
@@ -128,34 +95,16 @@ class FileTools:
         content = raw_bytes.decode(encoding)
         return hashlib.sha256(content.encode('utf-8')).hexdigest()
 
-    def read_file(self, filepath: str, encoding: str = 'utf-8',
-                  offset: Optional[int] = None, limit: Optional[int] = None,
-                  line_numbers: bool = True,
-                  max_line_chars: int = DEFAULT_MAX_LINE_CHARS) -> str:
+    def read_file(self, filepath: str, encoding: str = 'utf-8') -> str:
         """
-        Read content from a file (coding-grade, windowed + line-numbered).
-
-        By default the content is returned with a right-aligned line-number
-        gutter so a coding agent can reference exact lines for subsequent
-        edits, and a sensible line cap keeps a whole-file read from blowing the
-        context budget.  Pass ``line_numbers=False`` (with no ``offset``/
-        ``limit``) to get the exact plain-string content as before.
-
+        Read content from a file.
+        
         Args:
             filepath: Path to the file
             encoding: File encoding (default: utf-8)
-            offset: 1-based first line to read (default: start of file)
-            limit: Maximum number of lines to read (default: up to
-                ``DEFAULT_MAX_LINES`` lines from ``offset``).  A negative value
-                is treated as an invalid bound and yields an empty window.
-            line_numbers: Prefix each line with its 1-based number (default:
-                True).  Set False to return raw content.
-            max_line_chars: Truncate any single line longer than this many
-                characters (default: ``DEFAULT_MAX_LINE_CHARS``)
-
+            
         Returns:
-            str: Content of the requested window.  When truncated, a trailing
-            hint tells the model how to page for the rest via ``offset``.
+            str: Content of the file
         """
         try:
             # Validate path to prevent traversal attacks
@@ -175,48 +124,7 @@ class FileTools:
                         safe_path, self._content_hash(safe_path, encoding))
                 except Exception:
                     pass
-
-            # Fast path: preserve the exact legacy shape when the caller asks
-            # for raw content of the whole file (no window requested).
-            if not line_numbers and offset is None and limit is None:
-                return data
-
-            lines = data.splitlines()
-            total = len(lines)
-
-            # Clamp the 1-based offset into range; treat <=0 / None as start.
-            start = (offset - 1) if offset and offset > 0 else 0
-            if start > total:
-                start = total
-            # A negative ``limit`` is an invalid bound; return an empty window
-            # rather than silently expanding to ``DEFAULT_MAX_LINES``.
-            if limit is not None and limit < 0:
-                end = start
-            elif limit is not None:
-                end = start + limit
-            else:
-                end = start + DEFAULT_MAX_LINES
-            end = min(end, total)
-
-            if line_numbers:
-                body = _render_with_line_numbers(
-                    lines[start:end], start, max_line_chars)
-            else:
-                # Keep each line's trailing newline (keepends=True) so a raw
-                # windowed read preserves the window's structure for the
-                # edit/patch tools rather than collapsing separators.
-                raw_lines = data.splitlines(keepends=True)
-                body = "".join(raw_lines[start:end])
-
-            # Tell the model how to page when the window does not reach EOF.
-            if end < total:
-                if body and not body.endswith("\n"):
-                    body += "\n"
-                body += (
-                    f"... (showing lines {start + 1}-{end} of {total}; "
-                    f"call again with offset={end + 1} for more)"
-                )
-            return body
+            return data
         except Exception as e:
             error_msg = f"Error reading file {filepath}: {str(e)}"
             logging.error(error_msg)

src/praisonai-agents/praisonaiagents/tools/path_safety.py

@@ -6,39 +6,19 @@ import os
 from typing import Optional
 
 
-def resolve_path(path: str, root: Optional[str] = None) -> str:
-    """Fully resolve *path* against *root* (real, absolute, ``..``-collapsed).
-
-    Expands ``~`` and environment variables, joins relative paths onto the
-    real path of *root* (defaulting to the current working directory) and
-    resolves symlinks/``..``. This is the single shared resolver used by all
-    workspace-containment checks so boundary logic can never silently diverge.
-    """
-    base = os.path.realpath(root or os.getcwd())
-    expanded = os.path.expanduser(os.path.expandvars(path))
-    candidate = (
-        expanded if os.path.isabs(expanded) else os.path.join(base, expanded)
-    )
-    return os.path.realpath(os.path.normpath(candidate))
-
-
 def resolve_within_root(path: str, root: Optional[str] = None) -> Optional[str]:
-    """Resolve *path* under *root*, returning ``None`` if it escapes the root."""
+    """Resolve *path* under *root* and reject traversal outside the root."""
     base = os.path.realpath(root or os.getcwd())
-    resolved = resolve_path(path, base)
+    expanded = os.path.expanduser(path)
+    candidate = (
+        os.path.join(base, expanded)
+        if not os.path.isabs(expanded)
+        else expanded
+    )
+    resolved = os.path.realpath(os.path.normpath(candidate))
     try:
         if os.path.commonpath([resolved, base]) != base:
             return None
     except ValueError:
         return None
     return resolved
-
-
-def is_within_root(path: str, root: Optional[str] = None) -> bool:
-    """Return ``True`` if *path* resolves to a location inside *root*.
-
-    Expands ``~`` and environment variables, resolves symlinks/``..`` and
-    compares against the real path of *root* (defaulting to the current
-    working directory). Paths equal to the root itself are considered within.
-    """
-    return resolve_within_root(path, root) is not None

src/praisonai-agents/praisonaiagents/tools/rules_tools.py

@@ -0,0 +1,259 @@
+"""
+Rules Tools for PraisonAI Agents.
+
+Provides tools for agents to create, read, and manage rules dynamically.
+This enables Agent-Requested rules similar to Cursor's agent-requested rules feature.
+
+Usage:
+    from praisonaiagents.tools.rules_tools import (
+        create_rule_tool,
+        list_rules_tool,
+        get_rule_tool,
+        delete_rule_tool
+    )
+    
+    agent = Agent(
+        name="Assistant",
+        tools=[create_rule_tool, list_rules_tool, get_rule_tool]
+    )
+"""
+
+import logging
+from praisonaiagents._logging import get_logger
+from typing import Optional
+
+logger = get_logger(__name__)
+
+# Singleton RulesManager instance
+_rules_manager = None
+
+def _get_rules_manager():
+    """Get or create the RulesManager singleton."""
+    global _rules_manager
+    if _rules_manager is None:
+        from praisonaiagents.memory.rules_manager import RulesManager
+        _rules_manager = RulesManager()
+    return _rules_manager
+
+def create_rule_tool(
+    name: str,
+    content: str,
+    description: str = "",
+    globs: Optional[str] = None,
+    activation: str = "always",
+    priority: int = 0,
+    scope: str = "workspace"
+) -> str:
+    """
+    Create a new rule for the AI agent to follow.
+    
+    This tool allows the agent to create persistent rules that will be
+    applied to future conversations and tasks.
+    
+    Args:
+        name: Rule name (used as filename, no spaces or special chars)
+        content: The rule content in markdown format
+        description: Short description of what the rule does
+        globs: Comma-separated glob patterns for file matching (e.g., "**/*.py,**/*.js")
+        activation: When to apply the rule:
+            - "always": Always apply this rule
+            - "glob": Apply when working with files matching globs
+            - "manual": Only apply when explicitly mentioned
+            - "ai_decision": Let AI decide when to apply
+        priority: Priority (higher = applied first, default 0)
+        scope: Where to save ("workspace" or "global")
+        
+    Returns:
+        Success message with rule details
+        
+    Example:
+        create_rule_tool(
+            name="python-style",
+            content="- Use type hints for all functions\\n- Follow PEP 8",
+            description="Python coding standards",
+            globs="**/*.py",
+            activation="glob"
+        )
+    """
+    try:
+        manager = _get_rules_manager()
+        
+        # Parse globs
+        glob_list = None
+        if globs:
+            glob_list = [g.strip() for g in globs.split(",") if g.strip()]
+        
+        # Validate activation
+        valid_activations = ["always", "glob", "manual", "ai_decision"]
+        if activation not in valid_activations:
+            return f"Error: activation must be one of {valid_activations}"
+        
+        # Validate scope
+        if scope not in ["workspace", "global"]:
+            return "Error: scope must be 'workspace' or 'global'"
+        
+        # Create the rule
+        rule = manager.create_rule(
+            name=name,
+            content=content,
+            description=description,
+            globs=glob_list,
+            activation=activation,
+            priority=priority,
+            scope=scope
+        )
+        
+        return f"""Successfully created rule '{name}'
+Location: {rule.file_path}
+Activation: {activation}
+Priority: {priority}
+Description: {description or 'None'}
+Globs: {glob_list or 'None'}
+
+The rule will be applied according to its activation mode."""
+        
+    except Exception as e:
+        logger.error(f"Error creating rule: {e}")
+        return f"Error creating rule: {str(e)}"
+
+def list_rules_tool() -> str:
+    """
+    List all available rules.
+    
+    Returns a formatted list of all rules with their metadata.
+    
+    Returns:
+        Formatted string with rule information
+    """
+    try:
+        manager = _get_rules_manager()
+        rules = manager.get_all_rules()
+        
+        if not rules:
+            return "No rules found. Use create_rule_tool to create new rules."
+        
+        lines = ["# Available Rules\n"]
+        
+        for rule in rules:
+            scope = "global" if "global:" in (rule.file_path or "") else "workspace"
+            lines.append(f"## {rule.name}")
+            lines.append(f"- **Activation**: {rule.activation}")
+            lines.append(f"- **Priority**: {rule.priority}")
+            if rule.description:
+                lines.append(f"- **Description**: {rule.description}")
+            if rule.globs:
+                lines.append(f"- **Globs**: {', '.join(rule.globs)}")
+            lines.append(f"- **Scope**: {scope}")
+            lines.append("")
+        
+        return "\n".join(lines)
+        
+    except Exception as e:
+        logger.error(f"Error listing rules: {e}")
+        return f"Error listing rules: {str(e)}"
+
+def get_rule_tool(name: str) -> str:
+    """
+    Get the content of a specific rule.
+    
+    Args:
+        name: The name of the rule to retrieve
+        
+    Returns:
+        The rule content and metadata
+    """
+    try:
+        manager = _get_rules_manager()
+        rule = manager.get_rule(name)
+        
+        if not rule:
+            return f"Rule '{name}' not found. Use list_rules_tool to see available rules."
+        
+        return f"""# Rule: {rule.name}
+
+**Description**: {rule.description or 'None'}
+**Activation**: {rule.activation}
+**Priority**: {rule.priority}
+**Globs**: {', '.join(rule.globs) if rule.globs else 'None'}
+**File**: {rule.file_path}
+
+## Content:
+{rule.content}
+"""
+        
+    except Exception as e:
+        logger.error(f"Error getting rule: {e}")
+        return f"Error getting rule: {str(e)}"
+
+def delete_rule_tool(name: str, scope: Optional[str] = None) -> str:
+    """
+    Delete a rule.
+    
+    Args:
+        name: The name of the rule to delete
+        scope: Optional scope to delete from ("workspace" or "global")
+        
+    Returns:
+        Success or error message
+    """
+    try:
+        manager = _get_rules_manager()
+        
+        if scope and scope not in ["workspace", "global"]:
+            return "Error: scope must be 'workspace' or 'global'"
+        
+        success = manager.delete_rule(name, scope)
+        
+        if success:
+            return f"Successfully deleted rule '{name}'"
+        else:
+            return f"Rule '{name}' not found or could not be deleted"
+        
+    except Exception as e:
+        logger.error(f"Error deleting rule: {e}")
+        return f"Error deleting rule: {str(e)}"
+
+def get_active_rules_tool(file_path: Optional[str] = None) -> str:
+    """
+    Get all rules that are currently active for a given file or context.
+    
+    Args:
+        file_path: Optional file path to check which rules apply
+        
+    Returns:
+        Formatted string with active rules
+    """
+    try:
+        manager = _get_rules_manager()
+        
+        if file_path:
+            rules = manager.get_rules_for_file(file_path)
+        else:
+            rules = manager.get_active_rules()
+        
+        if not rules:
+            return "No active rules for this context."
+        
+        lines = ["# Active Rules\n"]
+        
+        for rule in rules:
+            lines.append(f"## {rule.name}")
+            if rule.description:
+                lines.append(f"*{rule.description}*\n")
+            lines.append(rule.content)
+            lines.append("")
+        
+        return "\n".join(lines)
+        
+    except Exception as e:
+        logger.error(f"Error getting active rules: {e}")
+        return f"Error getting active rules: {str(e)}"
+
+# Export all tools
+__all__ = [
+    "create_rule_tool",
+    "list_rules_tool",
+    "get_rule_tool",
+    "delete_rule_tool",
+    "get_active_rules_tool"
+]

src/praisonai-agents/praisonaiagents/tools/search_tools.py

@@ -1,383 +0,0 @@
-"""Fast, capped code-search built-ins: ``grep`` and ``glob``.
-
-These are the two most common moves a coding/repo-exploration agent makes:
-"where is this string/symbol used?" (``grep``) and "which files match this
-pattern?" (``glob``). Both are bounded (hard result cap with a "narrow your
-query" hint), path-safe (contained to the workspace, no traversal), and
-zero-config.
-
-``grep`` prefers ``ripgrep`` (``rg``) when present for speed and falls back to a
-pure-Python tree walk so it always works with zero external dependencies.
-``glob`` uses :mod:`pathlib`/:mod:`fnmatch` and honours ``.gitignore`` when
-available.
-
-Usage:
-    from praisonaiagents import Agent
-    from praisonaiagents.tools import grep, glob
-
-    agent = Agent(name="coder", tools=[grep, glob])
-
-or directly::
-
-    from praisonaiagents.tools import grep, glob
-    print(grep("deprecated_fn", path="src", glob="*.py"))
-    print(glob("**/*.py", path="src"))
-"""
-
-from __future__ import annotations
-
-import os
-import re
-import shutil
-import subprocess
-import fnmatch
-import logging
-from pathlib import Path
-from typing import List, Optional
-
-from .path_safety import resolve_within_root
-
-logger = logging.getLogger(__name__)
-
-# Default hard cap on returned results to keep output bounded and agent-friendly.
-_DEFAULT_MAX_RESULTS = 100
-
-# Directories that are almost never useful to search and are expensive to walk.
-_SKIP_DIRS = frozenset({
-    ".git", ".hg", ".svn", "__pycache__", "node_modules", ".venv", "venv",
-    ".mypy_cache", ".pytest_cache", ".ruff_cache", ".tox", "dist", "build",
-    ".eggs", ".idea", ".vscode",
-})
-
-
-def _validate_within_workspace(path: str) -> Optional[str]:
-    """Resolve *path* under the current workspace, rejecting traversal.
-
-    Returns the resolved absolute path, or ``None`` when *path* escapes the
-    workspace root (mirrors the containment used by ``file_tools``).
-    """
-    return resolve_within_root(path or ".")
-
-
-def _truncation_hint(count: int, max_results: int, what: str) -> str:
-    return (
-        f"... {count}+ {what} (truncated at {max_results}); "
-        f"refine the pattern or narrow `path`/`glob`."
-    )
-
-
-def _load_gitignore_spec(root: str):
-    """Best-effort load of ``.gitignore`` patterns from *root*.
-
-    Returns a callable ``matcher(relpath, is_dir) -> bool`` or ``None`` when no
-    ignore file is present. Uses a small self-contained matcher so no external
-    dependency is required.
-    """
-    gitignore = os.path.join(root, ".gitignore")
-    if not os.path.isfile(gitignore):
-        return None
-    patterns: List[str] = []
-    try:
-        with open(gitignore, "r", encoding="utf-8", errors="ignore") as fh:
-            for line in fh:
-                line = line.strip()
-                if not line or line.startswith("#"):
-                    continue
-                patterns.append(line)
-    except Exception:
-        return None
-    if not patterns:
-        return None
-
-    def _matches(relpath: str, is_dir: bool) -> bool:
-        name = os.path.basename(relpath)
-        posix = relpath.replace(os.sep, "/")
-        # Last matching pattern wins so re-includes (``!important.log``) can
-        # override an earlier broad exclude, mirroring Git's own semantics.
-        ignored = False
-        for pat in patterns:
-            neg = pat.startswith("!")
-            p = pat[1:] if neg else pat
-            dir_only = p.endswith("/")
-            p = p.rstrip("/")
-            if dir_only and not is_dir:
-                continue
-            hit = False
-            if "/" in p:
-                candidate = p[1:] if p.startswith("/") else p
-                if fnmatch.fnmatch(posix, candidate) or fnmatch.fnmatch(posix, candidate + "/*"):
-                    hit = True
-            else:
-                # A bare name matches the entry itself or any path segment,
-                # so ``build/`` also ignores ``build/foo.py``.
-                if fnmatch.fnmatch(name, p) or any(
-                    fnmatch.fnmatch(seg, p) for seg in posix.split("/")
-                ):
-                    hit = True
-            if hit:
-                ignored = not neg
-        return ignored
-
-    return _matches
-
-
-def _matches_glob(fname: str, rel: str, glob: Optional[str]) -> bool:
-    """True when *glob* is empty or matches the filename or workspace-relative path."""
-    if not glob:
-        return True
-    posix = rel.replace(os.sep, "/")
-    return (
-        fnmatch.fnmatch(fname, glob)
-        or fnmatch.fnmatch(rel, glob)
-        or fnmatch.fnmatch(posix, glob)
-    )
-
-
-def _iter_files(root: str, glob: Optional[str], ignore_matcher):
-    """Yield files under *root*, skipping noise dirs and ``.gitignore`` matches.
-
-    When *root* is a single file it is yielded directly (subject to *glob*), so
-    callers work identically whether given a directory or a file path.
-    """
-    if os.path.isfile(root):
-        rel = os.path.basename(root)
-        if _matches_glob(rel, rel, glob):
-            yield root
-        return
-    for dirpath, dirnames, filenames in os.walk(root):
-        dirnames[:] = [
-            d for d in dirnames
-            if d not in _SKIP_DIRS
-            and not (ignore_matcher and ignore_matcher(
-                os.path.relpath(os.path.join(dirpath, d), root), True))
-        ]
-        for fname in filenames:
-            full = os.path.join(dirpath, fname)
-            rel = os.path.relpath(full, root)
-            if ignore_matcher and ignore_matcher(rel, False):
-                continue
-            if not _matches_glob(fname, rel, glob):
-                continue
-            yield full
-
-
-_MAX_PATTERN_LEN = 1000
-
-
-def _python_grep(pattern, root, glob, case_insensitive, max_results):
-    """Pure-Python fallback content search (regex/literal)."""
-    # Python's backtracking ``re`` engine has no execution-time bound, so cap
-    # the pattern length to reduce catastrophic-backtracking (ReDoS) exposure
-    # on this fallback path (ripgrep's RE2-style engine is linear-time).
-    if len(pattern) > _MAX_PATTERN_LEN:
-        return f"Error: pattern too long (>{_MAX_PATTERN_LEN} chars); please narrow it."
-    flags = re.IGNORECASE if case_insensitive else 0
-    try:
-        regex = re.compile(pattern, flags)
-    except re.error as exc:
-        return f"Error: invalid regex pattern {pattern!r}: {exc}"
-
-    ignore_matcher = _load_gitignore_spec(root)
-    lines: List[str] = []
-    count = 0
-    truncated = False
-    for full in _iter_files(root, glob, ignore_matcher):
-        try:
-            with open(full, "r", encoding="utf-8", errors="ignore") as fh:
-                for lineno, line in enumerate(fh, start=1):
-                    if regex.search(line):
-                        count += 1
-                        if count > max_results:
-                            truncated = True
-                            break
-                        rel = os.path.relpath(full)
-                        lines.append(f"{rel}:{lineno}: {line.rstrip()}")
-        except (OSError, UnicodeError):
-            continue
-        if truncated:
-            break
-
-    if not lines:
-        return "No matches found."
-    if truncated:
-        lines.append(_truncation_hint(max_results, max_results, "matches"))
-    return "\n".join(lines)
-
-
-def _relativize(line: str) -> str:
-    """Rewrite a ``file:line:match`` entry to use a workspace-relative path."""
-    head, sep, rest = line.partition(":")
-    if not sep:
-        return line
-    try:
-        return os.path.relpath(head) + sep + rest
-    except ValueError:
-        return line
-
-
-def _cap_rg_output(stdout: str, max_results: int) -> str:
-    lines = [_relativize(ln) for ln in stdout.splitlines() if ln]
-    if not lines:
-        return "No matches found."
-    if len(lines) > max_results:
-        lines = lines[:max_results]
-        lines.append(_truncation_hint(max_results, max_results, "matches"))
-    return "\n".join(lines)
-
-
-def grep(
-    pattern: str,
-    path: str = ".",
-    glob: Optional[str] = None,
-    case_insensitive: bool = False,
-    max_results: int = _DEFAULT_MAX_RESULTS,
-) -> str:
-    """Search file contents for *pattern* (regex/literal), capped and bounded.
-
-    Prefers ``ripgrep`` (``rg``) when available for speed; otherwise falls back
-    to a pure-Python walker so it always works with zero external dependencies.
-
-    Args:
-        pattern: Regex/literal to search for.
-        path: Directory (or file) to search under. Contained to the workspace.
-        glob: Optional filename glob to restrict the search (e.g. ``"*.py"``).
-        case_insensitive: Case-insensitive matching when True.
-        max_results: Hard cap on the number of matching lines returned.
-
-    Returns:
-        ``path:line: matched line`` entries (newline-joined), hard-capped with a
-        truncation hint when there are more matches. Returns a short message on
-        no matches or on error.
-    """
-    if not pattern:
-        return "Error: `pattern` must be a non-empty string."
-    try:
-        max_results = int(max_results)
-    except (TypeError, ValueError):
-        max_results = _DEFAULT_MAX_RESULTS
-    if max_results <= 0:
-        max_results = _DEFAULT_MAX_RESULTS
-
-    safe = _validate_within_workspace(path)
-    if safe is None:
-        return f"Error: path {path!r} escapes the workspace."
-    if not os.path.exists(safe):
-        return f"Error: path not found: {path}"
-
-    rg = shutil.which("rg")
-    if rg:
-        # NOTE: no ``--max-count`` — that caps *per file*, which diverges from
-        # the pure-Python fallback's total cap. We cap the total afterwards so
-        # both paths return identical truncated results.
-        argv = [rg, "--line-number", "--with-filename", "--color=never"]
-        if case_insensitive:
-            argv.append("-i")
-        if glob:
-            argv += ["--glob", glob]
-        argv += ["--", pattern, safe]
-        try:
-            proc = subprocess.run(
-                argv, capture_output=True, text=True, timeout=30, check=False)
-            # rg exit code 1 == no matches (not an error); >1 == real error.
-            if proc.returncode not in (0, 1):
-                logger.debug("ripgrep failed (%s); falling back to python grep: %s",
-                             proc.returncode, proc.stderr.strip())
-                return _python_grep(pattern, safe, glob, case_insensitive, max_results)
-            return _cap_rg_output(proc.stdout, max_results)
-        except (subprocess.SubprocessError, OSError) as exc:
-            logger.debug("ripgrep invocation error; falling back: %s", exc)
-
-    return _python_grep(pattern, safe, glob, case_insensitive, max_results)
-
-
-def glob(
-    pattern: str,
-    path: str = ".",
-    max_results: int = _DEFAULT_MAX_RESULTS,
-) -> str:
-    """Return files matching a glob *pattern* under *path*, capped and sorted.
-
-    Supports recursive globs (``**/*.py``, ``src/**/test_*.py``). Honours
-    ``.gitignore`` when available and skips common noise directories. Results
-    are sorted by modification time (newest first) and hard-capped.
-
-    Args:
-        pattern: Glob pattern (e.g. ``"**/*.ts"``).
-        path: Directory to search under. Contained to the workspace.
-        max_results: Hard cap on the number of paths returned.
-
-    Returns:
-        Newline-joined relative file paths, hard-capped with a truncation hint
-        when there are more matches. Returns a short message on no matches or
-        on error.
-    """
-    if not pattern:
-        return "Error: `pattern` must be a non-empty string."
-    try:
-        max_results = int(max_results)
-    except (TypeError, ValueError):
-        max_results = _DEFAULT_MAX_RESULTS
-    if max_results <= 0:
-        max_results = _DEFAULT_MAX_RESULTS
-
-    safe = _validate_within_workspace(path)
-    if safe is None:
-        return f"Error: path {path!r} escapes the workspace."
-    if not os.path.isdir(safe):
-        return f"Error: directory not found: {path}"
-
-    ignore_matcher = _load_gitignore_spec(safe)
-    root = Path(safe)
-
-    def _ignored(rel: str, parts: List[str]) -> bool:
-        # Skip noise dirs and any file whose own path OR an ancestor directory
-        # matches ``.gitignore`` (so directory-only rules like ``build/`` also
-        # exclude ``build/foo.py``).
-        if any(part in _SKIP_DIRS for part in parts):
-            return True
-        if not ignore_matcher:
-            return False
-        if ignore_matcher(rel, False):
-            return True
-        ancestor = ""
-        for part in parts[:-1]:
-            ancestor = os.path.join(ancestor, part) if ancestor else part
-            if ignore_matcher(ancestor, True):
-                return True
-        return False
-
-    try:
-        matches = []
-        for p in root.glob(pattern):
-            if not p.is_file():
-                continue
-            rel = os.path.relpath(p, safe)
-            if _ignored(rel, rel.split(os.sep)):
-                continue
-            matches.append(p)
-    except (OSError, ValueError) as exc:
-        return f"Error: invalid glob pattern {pattern!r}: {exc}"
-
-    if not matches:
-        return "No files found."
-
-    def _mtime(p: Path) -> float:
-        try:
-            return p.stat().st_mtime
-        except OSError:
-            return 0.0
-
-    matches.sort(key=_mtime, reverse=True)
-    truncated = len(matches) > max_results
-    shown = matches[:max_results]
-    lines = [os.path.relpath(p) for p in shown]
-    if truncated:
-        lines.append(_truncation_hint(max_results, max_results, "files"))
-    return "\n".join(lines)
-
-
-if __name__ == "__main__":
-    print("grep('def ', path='.', glob='*.py'):")
-    print(grep("def ", path=".", glob="*.py", max_results=10))
-    print("\nglob('**/*.py'):")
-    print(glob("**/*.py", max_results=10))

src/praisonai-agents/praisonaiagents/tools/shell_tools.py

@@ -18,21 +18,6 @@ import platform
 from typing import Dict, List, Optional, Union
 from ..approval import require_approval
 
-# Minimum grace period (seconds) always granted for stdout/stderr reader threads
-# to flush already-written output after the process exits, even when the command
-# consumed nearly all of its timeout budget.
-_DRAIN_GRACE_SECONDS = 1.0
-
-
-class _StreamDrainTimeout(Exception):
-    """Raised when the direct child has already exited but a reader thread is
-    still blocked draining an inherited pipe past the timeout budget.
-
-    Distinct from ``subprocess.TimeoutExpired`` because the direct child is gone:
-    the caller must report a timeout WITHOUT trying to kill an already-exited
-    process.
-    """
-
 class ShellTools:
     """Tools for executing shell commands safely."""
     
@@ -115,11 +100,9 @@ class ShellTools:
             )
             
             try:
-                # Read stdout/stderr incrementally so a progress channel (when
-                # active) can surface output live while the command runs. Falls
-                # back to fully-buffered behaviour when no sink is listening.
-                stdout, stderr = self._communicate_streaming(process, timeout)
-
+                # Wait for process with timeout
+                stdout, stderr = process.communicate(timeout=timeout)
+                
                 # Truncate output if too large (use smart format)
                 if len(stdout) > max_output_size:
                     tail_size = min(max_output_size // 5, 500)
@@ -136,19 +119,6 @@ class ShellTools:
                     'execution_time': time.time() - start_time
                 }
             
-            except _StreamDrainTimeout:
-                # The direct child already exited; only an inherited pipe kept a
-                # reader blocked. Report a timeout but do NOT kill — the direct
-                # child's PID is gone (and may have been recycled), so killing it
-                # would be unsafe and misleading.
-                return {
-                    'stdout': '',
-                    'stderr': f'Command output streaming timed out after {timeout} seconds',
-                    'exit_code': -1,
-                    'success': False,
-                    'execution_time': timeout
-                }
-
             except subprocess.TimeoutExpired:
                 # Kill process on timeout
                 try:
@@ -161,9 +131,6 @@ class ShellTools:
                 except ImportError:
                     # Fallback: kill without psutil
                     process.kill()
-                except psutil.NoSuchProcess:
-                    # Process already gone — nothing to kill.
-                    pass
                 
                 return {
                     'stdout': '',
@@ -184,117 +151,6 @@ class ShellTools:
                 'execution_time': 0
             }
     
-    def _communicate_streaming(self, process, timeout):
-        """Read stdout/stderr line-buffered, emitting live progress.
-
-        Reads both streams concurrently in background threads so a line on
-        either stream is surfaced via ``emit_tool_progress`` as soon as it
-        arrives. Preserves ``subprocess.communicate`` semantics: returns the
-        full ``(stdout, stderr)`` strings and raises ``TimeoutExpired`` on
-        timeout. When no progress sink is active, this still buffers the full
-        output identically to the previous behaviour (the emit call is a cheap
-        no-op).
-        """
-        import threading
-
-        # Capture the active progress sink (set by the agent's tool-execution
-        # loop via a contextvar) in THIS thread, then emit to it directly from
-        # the reader threads. Capturing the sink up-front avoids relying on
-        # contextvar propagation into the spawned threads.
-        _sink = None
-        try:
-            from ..streaming import events as _stream_events
-            _sink = _stream_events._tool_progress_sink.get()
-        except Exception:  # streaming module unavailable — no streaming
-            _sink = None
-
-        # Stop forwarding progress once the tool has returned (e.g. on timeout),
-        # so a still-draining reader thread can never emit after the result.
-        stop_emitting = threading.Event()
-
-        def _emit(line, stream_name):
-            if _sink is None or stop_emitting.is_set():
-                return
-            try:
-                _sink(_stream_events.StreamEvent(
-                    type=_stream_events.StreamEventType.TOOL_PROGRESS,
-                    content=line,
-                    metadata={"stream": stream_name},
-                ))
-            except Exception as exc:  # never break command execution on a progress failure
-                logging.debug("Tool progress emission failed: %s", exc, exc_info=True)
-
-        stdout_chunks: List[str] = []
-        stderr_chunks: List[str] = []
-        read_errors: List[BaseException] = []
-
-        def _pump(stream, sink_list, stream_name):
-            if stream is None:
-                return
-            try:
-                for line in iter(stream.readline, ''):
-                    if line == '':
-                        break
-                    sink_list.append(line)
-                    _emit(line, stream_name)
-            except Exception as exc:
-                # Surface a failed read (e.g. UnicodeDecodeError) so the caller's
-                # error path reports it instead of silently returning a partial
-                # prefix as if the command had succeeded.
-                read_errors.append(exc)
-                logging.debug("Error reading %s stream: %s", stream_name, exc, exc_info=True)
-            finally:
-                try:
-                    stream.close()
-                except Exception as exc:
-                    logging.debug("Failed to close %s stream: %s", stream_name, exc, exc_info=True)
-
-        t_out = threading.Thread(target=_pump, args=(process.stdout, stdout_chunks, "stdout"), daemon=True)
-        t_err = threading.Thread(target=_pump, args=(process.stderr, stderr_chunks, "stderr"), daemon=True)
-        t_out.start()
-        t_err.start()
-
-        deadline = None if timeout is None else time.monotonic() + timeout
-        try:
-            process.wait(timeout=timeout)
-        except subprocess.TimeoutExpired:
-            # The direct child is still running. Disable any further emission and
-            # re-raise TimeoutExpired so the caller's timeout path KILLS the
-            # process before returning — a recorded read error must not short-
-            # circuit that cleanup (otherwise the still-running child leaks with
-            # its pipes open).
-            stop_emitting.set()
-            raise
-
-        # Wait for the readers to drain the pipe buffers before returning,
-        # preserving subprocess.communicate()'s "all captured output" semantics.
-        # A bounded join keeps the overall call within the original timeout
-        # budget: if a background child inherited stdout/stderr and keeps the
-        # pipe open after the direct child exits, a reader can stay blocked in
-        # readline(). Rather than hang indefinitely, fall back to the configured
-        # timeout result once the remaining budget is exhausted. A small minimum
-        # grace is always allowed so a command that used most of its timeout can
-        # still flush its already-written output.
-        for reader in (t_out, t_err):
-            if deadline is None:
-                remaining = None
-            else:
-                remaining = max(_DRAIN_GRACE_SECONDS, deadline - time.monotonic())
-            reader.join(timeout=remaining)
-
-        if t_out.is_alive() or t_err.is_alive():
-            # Readers still blocked on a leaked (inherited) pipe past the budget,
-            # but the DIRECT child has already exited (process.wait() returned).
-            # Stop emitting and signal a drain-timeout so the caller reports a
-            # timeout WITHOUT trying to kill an already-exited process.
-            stop_emitting.set()
-            raise _StreamDrainTimeout()
-
-        if read_errors:
-            raise read_errors[0]
-
-        return "".join(stdout_chunks), "".join(stderr_chunks)
-
     def list_processes(self) -> List[Dict[str, Union[int, str, float]]]:
         """List running processes with their details.
         

src/praisonai-agents/praisonaiagents/tools/subagent_tool.py

@@ -6,7 +6,6 @@ enabling hierarchical task delegation and multi-agent coordination.
 """
 
 import logging
-import threading
 from praisonaiagents._logging import get_logger
 from typing import Any, Callable, Dict, List, Optional
 
@@ -18,7 +17,6 @@ def create_subagent_tool(
     max_depth: int = 3,
     default_llm: Optional[str] = None,
     default_permission_mode: Optional[str] = None,
-    on_job_complete: Optional[Callable[[Any], None]] = None,
 ) -> Dict[str, Any]:
     """
     Create a subagent tool for task delegation.
@@ -32,49 +30,61 @@ def create_subagent_tool(
         max_depth: Maximum nesting depth for subagents
         default_llm: Default LLM model for subagents (Claude Code parity)
         default_permission_mode: Default permission mode for subagents (Claude Code parity)
-        on_job_complete: Optional callback invoked with the terminal
-            ``JobInfo`` when a ``background=True`` subagent that carries a
-            ``deliver`` target finishes. This is the observable completion
-            signal a gateway (e.g. ``BotOS``) subscribes to in order to
-            route the result back to the originating chat without an active
-            turn. When ``None`` (the default) background jobs remain strictly
-            pull-only via ``subagent_result`` — byte-for-byte the prior
-            behaviour.
         
     Returns:
         Tool definition dictionary
     """
     
-    # Depth is tracked per-thread so that concurrent background subagents do
-    # not interfere with each other's depth budget. The parent depth is
-    # captured at call time and passed into ``_run_subagent`` so a background
-    # worker (running on a different thread) starts from the correct depth.
-    _depth_state = threading.local()
-
-    def _get_depth() -> int:
-        return getattr(_depth_state, "current_depth", 0)
-
-    def _run_subagent(
+    _current_depth = 0
+    
+    def spawn_subagent(
         task: str,
-        agent_name: Optional[str],
-        context: Optional[str],
-        tools: Optional[List[str]],
-        effective_llm: Optional[str],
-        effective_permission_mode: Optional[str],
-        parent_depth: int = 0,
+        agent_name: Optional[str] = None,
+        context: Optional[str] = None,
+        tools: Optional[List[str]] = None,
+        llm: Optional[str] = None,
+        permission_mode: Optional[str] = None,
     ) -> Dict[str, Any]:
-        """Execute the subagent synchronously and return the result dict.
-
-        Depth tracking is handled here so that background jobs honour the
-        same ``max_depth`` scoping as synchronous calls. ``parent_depth`` is
-        the depth captured by the caller; it is restored on this thread for
-        the duration of the execution so nested subagents see the correct
-        value even when running off the main thread.
         """
-        previous_depth = _get_depth()
+        Spawn a subagent to handle a specific task.
+        
+        Args:
+            task: The task description for the subagent
+            agent_name: Optional specific agent to use
+            context: Optional additional context
+            tools: Optional list of tools to give the subagent
+            llm: Optional LLM model override (Claude Code parity)
+            permission_mode: Optional permission mode (Claude Code parity)
+            
+        Returns:
+            Result from the subagent execution
+        """
+        nonlocal _current_depth
+        
+        # Check depth limit
+        if _current_depth >= max_depth:
+            return {
+                "success": False,
+                "error": f"Maximum subagent depth ({max_depth}) exceeded",
+                "output": None,
+            }
+        
+        # Check allowed agents
+        if allowed_agents and agent_name and agent_name not in allowed_agents:
+            return {
+                "success": False,
+                "error": f"Agent '{agent_name}' not in allowed list",
+                "output": None,
+            }
+        
         try:
-            _depth_state.current_depth = parent_depth + 1
-
+            _current_depth += 1
+            
+            # Resolve LLM (parameter > default > None)
+            effective_llm = llm or default_llm
+            # Resolve permission mode (parameter > default > None)
+            effective_permission_mode = permission_mode or default_permission_mode
+            
             # If we have an agent factory, use it
             if agent_factory:
                 subagent = agent_factory(
@@ -82,15 +92,15 @@ def create_subagent_tool(
                     tools=tools,
                     llm=effective_llm,
                 )
-
+                
                 # Build prompt with context
                 prompt = task
                 if context:
                     prompt = f"Context: {context}\n\nTask: {task}"
-
+                
                 # Execute the subagent
                 result = subagent.chat(prompt)
-
+                
                 return {
                     "success": True,
                     "output": result,
@@ -110,6 +120,7 @@ def create_subagent_tool(
                     "permission_mode": effective_permission_mode,
                     "note": "No agent factory provided - simulation mode",
                 }
+                
         except Exception as e:
             logger.error(f"Subagent execution failed: {e}")
             return {
@@ -118,219 +129,8 @@ def create_subagent_tool(
                 "output": None,
             }
         finally:
-            _depth_state.current_depth = previous_depth
-
-    def spawn_subagent(
-        task: str,
-        agent_name: Optional[str] = None,
-        context: Optional[str] = None,
-        tools: Optional[List[str]] = None,
-        llm: Optional[str] = None,
-        permission_mode: Optional[str] = None,
-        background: bool = False,
-        deliver: str = "",
-        platform: str = "",
-        chat_id: str = "",
-        thread_id: str = "",
-        session_id: str = "",
-    ) -> Dict[str, Any]:
-        """
-        Spawn a subagent to handle a specific task.
-        
-        Args:
-            task: The task description for the subagent
-            agent_name: Optional specific agent to use
-            context: Optional additional context
-            tools: Optional list of tools to give the subagent
-            llm: Optional LLM model override (Claude Code parity)
-            permission_mode: Optional permission mode (Claude Code parity)
-            background: When True, run the subagent on the background job
-                runner and return immediately with a ``job_id`` instead of
-                blocking until completion. Defaults to False (synchronous).
-            deliver: Optional delivery token mirroring ``schedule_add`` —
-                e.g. ``"origin"``, ``"all"`` or ``"platform:chat_id[:thread_id]"``.
-                Only meaningful with ``background=True``: it captures where the
-                result should be routed when the job finishes, so a gateway can
-                proactively deliver it back to chat with no active turn. Empty
-                (the default) keeps background jobs pull-only via
-                ``subagent_result`` — byte-for-byte the prior behaviour.
-            platform: Origin platform (e.g. "telegram") captured for
-                ``deliver="origin"``. Usually supplied by the gateway context.
-            chat_id: Origin chat/channel id captured for ``deliver="origin"``.
-            thread_id: Optional origin thread id.
-            session_id: Optional origin session id to preserve context.
-            
-        Returns:
-            Result from the subagent execution. When ``background=True`` a
-            ``{"success": True, "job_id": ..., "status": "running"}`` handle
-            is returned instead; use ``subagent_result(job_id)`` to collect.
-            When ``deliver`` is set the handle also echoes ``"deliver"``.
-        """
-        # Check depth limit (per-thread; captured for background workers below)
-        parent_depth = _get_depth()
-        if parent_depth >= max_depth:
-            return {
-                "success": False,
-                "error": f"Maximum subagent depth ({max_depth}) exceeded",
-                "output": None,
-            }
-        
-        # Check allowed agents
-        if allowed_agents and agent_name and agent_name not in allowed_agents:
-            return {
-                "success": False,
-                "error": f"Agent '{agent_name}' not in allowed list",
-                "output": None,
-            }
-
-        # Resolve LLM (parameter > default > None)
-        effective_llm = llm or default_llm
-        # Resolve permission mode (parameter > default > None)
-        effective_permission_mode = permission_mode or default_permission_mode
-
-        if background:
-            # Enqueue on the existing background job runner. Depth and
-            # permission/tool scoping are captured in the closure below so
-            # the backgrounded subagent runs under exactly the same
-            # constraints as a synchronous one.
-            from praisonaiagents.background.job_manager import get_job_manager
-
-            job_manager = get_job_manager()
-
-            def _job() -> Dict[str, Any]:
-                return _run_subagent(
-                    task=task,
-                    agent_name=agent_name,
-                    context=context,
-                    tools=tools,
-                    effective_llm=effective_llm,
-                    effective_permission_mode=effective_permission_mode,
-                    parent_depth=parent_depth,
-                )
-
-            # Capture origin/delivery context so a gateway can route the
-            # result back to the originating conversation when the job
-            # finishes. Only populated when a ``deliver`` target is set;
-            # otherwise the job stays pull-only (unchanged behaviour).
-            origin: Dict[str, Any] = {}
-            job_on_complete = None
-            if deliver:
-                origin = {
-                    "deliver": deliver,
-                    "platform": platform,
-                    "chat_id": chat_id,
-                    "thread_id": thread_id,
-                    "session_id": session_id,
-                    "task": task,
-                }
-                if on_job_complete is not None:
-                    job_on_complete = on_job_complete
-
-            job_id = job_manager.start_job(
-                _job,
-                on_complete=job_on_complete,
-                origin=origin,
-            )
-            handle = {
-                "success": True,
-                "job_id": job_id,
-                "status": "running",
-                "agent_name": agent_name or "subagent",
-                "task": task,
-                "llm": effective_llm,
-                "permission_mode": effective_permission_mode,
-            }
-            if deliver:
-                handle["deliver"] = deliver
-            return handle
-
-        return _run_subagent(
-            task=task,
-            agent_name=agent_name,
-            context=context,
-            tools=tools,
-            effective_llm=effective_llm,
-            effective_permission_mode=effective_permission_mode,
-            parent_depth=parent_depth,
-        )
-
-    def subagent_result(job_id: str, wait: bool = False) -> Dict[str, Any]:
-        """
-        Fetch the status/result of a backgrounded subagent.
-
-        Args:
-            job_id: The job ID returned by ``spawn_subagent(background=True)``.
-            wait: When True, block until the job completes before returning.
-
-        Returns:
-            A dict describing the job. While running:
-            ``{"success": True, "job_id": ..., "status": "running"}``.
-            On completion the subagent's result dict is returned under
-            ``"result"`` along with ``"status": "completed"``.
-        """
-        from praisonaiagents.background.job_manager import (
-            get_job_manager,
-            JobStatus,
-        )
-
-        job_manager = get_job_manager()
-        try:
-            if wait:
-                try:
-                    result = job_manager.get_result(job_id)
-                except KeyError:
-                    return {
-                        "success": False,
-                        "job_id": job_id,
-                        "error": f"Job '{job_id}' not found",
-                    }
-                except Exception as e:
-                    # The worker failed or was cancelled. Surface the same
-                    # clean failure shape the non-blocking path returns
-                    # instead of re-raising to the caller.
-                    return {
-                        "success": False,
-                        "job_id": job_id,
-                        "status": JobStatus.FAILED.value,
-                        "error": str(e),
-                    }
-                return {
-                    "success": True,
-                    "job_id": job_id,
-                    "status": JobStatus.COMPLETED.value,
-                    "result": result,
-                }
-
-            info = job_manager.get_job_info(job_id)
-        except KeyError:
-            return {
-                "success": False,
-                "job_id": job_id,
-                "error": f"Job '{job_id}' not found",
-            }
-
-        if info.status == JobStatus.COMPLETED:
-            return {
-                "success": True,
-                "job_id": job_id,
-                "status": info.status.value,
-                "result": info.result,
-            }
-        if info.status == JobStatus.FAILED:
-            return {
-                "success": False,
-                "job_id": job_id,
-                "status": info.status.value,
-                "error": info.error,
-            }
-        return {
-            "success": True,
-            "job_id": job_id,
-            "status": info.status.value,
-        }
-
-    spawn_subagent._subagent_result = subagent_result  # type: ignore[attr-defined]
-
+            _current_depth -= 1
+    
     return {
         "name": "spawn_subagent",
         "description": (
@@ -369,43 +169,9 @@ def create_subagent_tool(
                     "enum": ["default", "accept_edits", "dont_ask", "bypass_permissions", "plan"],
                     "description": "Optional permission mode for the subagent (default, accept_edits, dont_ask, bypass_permissions, plan)",
                 },
-                "background": {
-                    "type": "boolean",
-                    "description": "When true, run the subagent in the background (fire-and-forget) and return a job_id immediately instead of blocking. Use subagent_result to collect the result.",
-                    "default": False,
-                },
-                "deliver": {
-                    "type": "string",
-                    "description": "Optional delivery target for a background job's result when it finishes (e.g. 'origin', 'all', 'telegram:12345'). When set, the completed result is proactively delivered back to that chat with no active turn required. Empty means pull-only via subagent_result.",
-                },
             },
             "required": ["task"],
         },
-        "result_tool": {
-            "name": "subagent_result",
-            "description": (
-                "Fetch the status or result of a backgrounded subagent "
-                "launched via spawn_subagent(background=true). Pass the "
-                "job_id returned by spawn_subagent. Set wait=true to block "
-                "until the subagent completes."
-            ),
-            "function": subagent_result,
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "job_id": {
-                        "type": "string",
-                        "description": "The job ID returned by spawn_subagent(background=true)",
-                    },
-                    "wait": {
-                        "type": "boolean",
-                        "description": "When true, block until the subagent completes before returning",
-                        "default": False,
-                    },
-                },
-                "required": ["job_id"],
-            },
-        },
     }
 
 def create_batch_tool() -> Dict[str, Any]:

src/praisonai-agents/praisonaiagents/workflows/workflows.py

@@ -995,40 +995,6 @@ class AgentFlow:
             # Non-agent step, reset chain 
             self._handoff_chain.clear()
     
-    def _validate_framework(self) -> None:
-        """Validate the workflow's ``framework`` before execution.
-
-        The YAML parser may set a ``framework`` attribute on the workflow
-        (e.g. from ``framework: crewai`` in a workflow YAML). The native
-        execution engine only supports ``praisonai``, so any other value
-        must fail fast with a clear, actionable error rather than being
-        silently ignored.
-
-        Backward-compatible: when ``framework`` is unset, empty, or
-        ``"praisonai"`` (case-insensitive), this is a no-op.
-        """
-        framework = getattr(self, 'framework', None)
-        if framework is None:
-            return
-        if str(framework).strip().lower() in ("", "praisonai"):
-            return
-        # Include workflow identity (name/file) so included-recipe failures
-        # can be traced back to the exact YAML that triggered them.
-        identity_parts = []
-        name = getattr(self, 'name', None)
-        if name:
-            identity_parts.append(f"workflow '{name}'")
-        file_path = getattr(self, 'file_path', None)
-        if file_path:
-            identity_parts.append(f"file '{file_path}'")
-        identity = f" ({', '.join(identity_parts)})" if identity_parts else ""
-        raise ValueError(
-            f"Unsupported workflow framework: '{framework}'{identity}. "
-            "Workflow YAML execution only supports the native PraisonAI "
-            "engine (framework: praisonai). Remove the 'framework' field or "
-            "set it to 'praisonai'."
-        )
-
     def run(
         self,
         input: str = "",
@@ -1066,13 +1032,6 @@ class AgentFlow:
         # Gap 3c: Clear handoff chain at start of new workflow run  
         self._handoff_chain.clear()
         
-        # Fail fast if a non-praisonai framework is requested via YAML.
-        # The YAML parser stores `framework` on the workflow, but execution
-        # always uses the native PraisonAI engine. Silently ignoring a
-        # non-praisonai value (e.g. framework: crewai) is a correctness bug,
-        # so raise a clear error instead of producing misleading results.
-        self._validate_framework()
-        
         # Use default LLM if not specified
         model = llm or self.llm or "gpt-4o-mini"
         logger.debug(f"Workflow using model: {model} (llm={llm}, default_llm={self.llm})")
@@ -3803,11 +3762,6 @@ class WorkflowManager:
                 "results": []
             }
         
-        # Fail fast on unsupported frameworks. This path iterates steps
-        # directly instead of calling Workflow.run(), so re-apply the same
-        # guard here to avoid silently ignoring framework: <non-praisonai>.
-        workflow._validate_framework()
-        
         # Merge variables
         all_variables = {**workflow.variables}
         if variables:
@@ -4187,11 +4141,6 @@ class WorkflowManager:
                 "results": []
             }
         
-        # Fail fast on unsupported frameworks. This path iterates steps
-        # directly instead of calling Workflow.run(), so re-apply the same
-        # guard here to avoid silently ignoring framework: <non-praisonai>.
-        workflow._validate_framework()
-        
         # Merge variables
         all_variables = {**workflow.variables}
         if variables: