mirror of
https://github.com/MervinPraison/PraisonAI.git
synced 2026-11-08 08:11:07 -10:00
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No files matched your search
@@ -227,10 +227,9 @@ runs:
|
||||
2. Wrapper (praisonai/): CLI, heavy implementations, optional dependencies.
|
||||
3. Tools (PraisonAI-Tools): Specific integrations, external tools (e.g. SurrealDB, Slack), and community extensions MUST go to the `MervinPraison/PraisonAI-Tools` repository. If the feature is a tool, clone `https://github.com/MervinPraison/PraisonAI-Tools`, implement it there, and create the PR using `gh pr create -R MervinPraison/PraisonAI-Tools`.
|
||||
- Does it duplicate existing functionality? Check if Agent already supports this via existing params (reflection, planning, tools, hooks, memory).
|
||||
- Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
|
||||
- Does it inherit from Agent properly? New agent types MUST inherit Agent, not wrap it with composition.
|
||||
- Does it add new dependencies? Only optional deps allowed, must be lazy-imported.
|
||||
- Will agent.py grow larger? If the change adds >50 lines to agent.py, find a way to extract instead. PRs with >100 lines added to agent.py require manual review (merge gate will not auto-merge).
|
||||
- Will agent.py grow larger? If the change adds >50 lines to agent.py, find a way to extract instead.
|
||||
- Is there a name collision with existing exports in __init__.py?
|
||||
If ANY of these conceptual checks fail (excluding routing), add a comment to the issue explaining why and close it. Do NOT create a PR.
|
||||
|
||||
@@ -261,24 +260,16 @@ runs:
|
||||
ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
|
||||
CLAUDE_CODE_OAUTH_TOKEN: ${{ inputs.claude_code_oauth_token }}
|
||||
GITHUB_TOKEN: ${{ inputs.github_token }}
|
||||
INPUT_MODEL: ${{ inputs.model }}
|
||||
INPUT_MAX_TURNS: ${{ inputs.max_turns }}
|
||||
INPUT_ALLOWED_TOOLS: ${{ inputs.allowed_tools }}
|
||||
INPUT_DISALLOWED_TOOLS: ${{ inputs.disallowed_tools }}
|
||||
INPUT_TIMEOUT_MINUTES: ${{ inputs.timeout_minutes }}
|
||||
CLAUDE_CODE_SUBAGENT_MODEL: inherit
|
||||
ANTHROPIC_DEFAULT_SONNET_MODEL: claude-sonnet-4-6
|
||||
run: |
|
||||
echo "🚀 Running Claude Code with GitHub context..."
|
||||
|
||||
# Build command arguments
|
||||
CMD_ARGS=("-p" "--verbose" "--output-format" "stream-json")
|
||||
|
||||
if [[ -n "$INPUT_MODEL" ]]; then
|
||||
CMD_ARGS+=("--model" "$INPUT_MODEL")
|
||||
export ANTHROPIC_MODEL="$INPUT_MODEL"
|
||||
fi
|
||||
|
||||
# Add max turns if specified
|
||||
if [[ -n "$INPUT_MAX_TURNS" ]]; then
|
||||
CMD_ARGS+=("--max-turns" "$INPUT_MAX_TURNS")
|
||||
@@ -289,36 +280,11 @@ runs:
|
||||
if [[ -n "$INPUT_ALLOWED_TOOLS" ]]; then
|
||||
TOOLS="$TOOLS,$INPUT_ALLOWED_TOOLS"
|
||||
fi
|
||||
|
||||
# Remove any explicitly disallowed tools from the effective allow-list so
|
||||
# the read-only contract is enforced deterministically (no reliance on CLI
|
||||
# precedence between --allowedTools and --disallowedTools).
|
||||
if [[ -n "$INPUT_DISALLOWED_TOOLS" ]]; then
|
||||
DISALLOWED_CSV=$(echo "$INPUT_DISALLOWED_TOOLS" | tr ',\n' ' ' | xargs)
|
||||
FILTERED=""
|
||||
IFS=',' read -ra TOOL_ARR <<< "$TOOLS"
|
||||
for tool in "${TOOL_ARR[@]}"; do
|
||||
tool=$(echo "$tool" | xargs)
|
||||
[[ -z "$tool" ]] && continue
|
||||
skip="false"
|
||||
for bad in $DISALLOWED_CSV; do
|
||||
if [[ "$tool" == "$bad" ]]; then
|
||||
skip="true"
|
||||
break
|
||||
fi
|
||||
done
|
||||
if [[ "$skip" == "false" ]]; then
|
||||
FILTERED="${FILTERED:+$FILTERED,}$tool"
|
||||
fi
|
||||
done
|
||||
TOOLS="$FILTERED"
|
||||
fi
|
||||
CMD_ARGS+=("--allowedTools" "$TOOLS")
|
||||
|
||||
# Add disallowed tools
|
||||
if [[ -n "$INPUT_DISALLOWED_TOOLS" ]]; then
|
||||
DISALLOWED_FLAG=$(echo "$INPUT_DISALLOWED_TOOLS" | tr '\n' ',' | sed 's/,*$//')
|
||||
CMD_ARGS+=("--disallowedTools" "$DISALLOWED_FLAG")
|
||||
CMD_ARGS+=("--disallowedTools" "$INPUT_DISALLOWED_TOOLS")
|
||||
fi
|
||||
|
||||
echo "📝 Executing Claude Code with prompt from file..."
|
||||
|
||||
@@ -1,34 +0,0 @@
|
||||
#!/usr/bin/env node
|
||||
const chain = require('./bot-pr-review-chain.js');
|
||||
|
||||
let failed = 0;
|
||||
function assert(name, cond) {
|
||||
if (!cond) {
|
||||
console.error('FAIL:', name);
|
||||
failed++;
|
||||
} else {
|
||||
console.log('ok:', name);
|
||||
}
|
||||
}
|
||||
|
||||
assert('chainKickPosted requires both markers', chain.chainKickPosted([
|
||||
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
|
||||
{ user: { login: 'MervinPraison' }, body: '/review' },
|
||||
]));
|
||||
assert('chainKickPosted false with only coderabbit', !chain.chainKickPosted([
|
||||
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
|
||||
]));
|
||||
assert('coderabbitKickPosted detects coderabbit', chain.coderabbitKickPosted([
|
||||
{ user: { login: 'MervinPraison' }, body: '@coderabbitai review' },
|
||||
]));
|
||||
assert('qodoKickPosted detects qodo', chain.qodoKickPosted([
|
||||
{ user: { login: 'github-actions[bot]' }, body: '/review' },
|
||||
]));
|
||||
assert('ignores coderabbit bot comment', !chain.coderabbitKickPosted([
|
||||
{ user: { login: 'coderabbitai[bot]' }, body: '@coderabbitai review' },
|
||||
]));
|
||||
assert('bot PR author match', chain.isBotOpenedPr({ user: { login: 'praisonai-triage-agent[bot]' } }));
|
||||
assert('generic bot type match', chain.isBotOpenedPr({ user: { login: 'my-bot', type: 'Bot' } }));
|
||||
assert('human author excluded', !chain.isBotOpenedPr({ user: { login: 'MervinPraison', type: 'User' } }));
|
||||
|
||||
process.exit(failed ? 1 : 0);
|
||||
@@ -1,153 +0,0 @@
|
||||
/**
|
||||
* Idempotent CodeRabbit/Qodo kick for bot-opened PRs.
|
||||
* @see .github/workflows/auto-pr-comment.yml, claude.yml, bot-pr-recovery.yml
|
||||
*/
|
||||
|
||||
const KICK_AUTHORS = new Set(['MervinPraison', 'github-actions[bot]']);
|
||||
const BOT_PR_AUTHORS = new Set(['praisonai-triage-agent[bot]', 'github-actions[bot]']);
|
||||
|
||||
async function listAllComments(github, owner, repo, issueNumber) {
|
||||
if (typeof github.paginate === 'function') {
|
||||
return github.paginate(github.rest.issues.listComments, {
|
||||
owner,
|
||||
repo,
|
||||
issue_number: issueNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
}
|
||||
const { data } = await github.rest.issues.listComments({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: issueNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
return data;
|
||||
}
|
||||
|
||||
function kickAuthored(comment, marker) {
|
||||
return (
|
||||
KICK_AUTHORS.has(comment.user?.login) &&
|
||||
(comment.body || '').includes(marker)
|
||||
);
|
||||
}
|
||||
|
||||
function coderabbitKickPosted(comments) {
|
||||
return comments.some((c) => kickAuthored(c, '@coderabbitai review'));
|
||||
}
|
||||
|
||||
function qodoKickPosted(comments) {
|
||||
return comments.some((c) => kickAuthored(c, '/review'));
|
||||
}
|
||||
|
||||
function chainKickPosted(comments) {
|
||||
return coderabbitKickPosted(comments) && qodoKickPosted(comments);
|
||||
}
|
||||
|
||||
function isBotOpenedPr(pr) {
|
||||
if (BOT_PR_AUTHORS.has(pr.user?.login)) return true;
|
||||
return pr.user?.type === 'Bot';
|
||||
}
|
||||
|
||||
async function kickReviewChain(github, owner, repo, prNumber, core, preFetchedComments = null) {
|
||||
const comments = preFetchedComments || await listAllComments(github, owner, repo, prNumber);
|
||||
const needCoderabbit = !coderabbitKickPosted(comments);
|
||||
const needQodo = !qodoKickPosted(comments);
|
||||
|
||||
if (!needCoderabbit && !needQodo) {
|
||||
core?.info?.(`Review chain already kicked on PR #${prNumber}`);
|
||||
return { kicked: false, reason: 'already_kicked' };
|
||||
}
|
||||
|
||||
if (needCoderabbit) {
|
||||
await github.rest.issues.createComment({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: prNumber,
|
||||
body: '@coderabbitai review',
|
||||
});
|
||||
}
|
||||
if (needQodo) {
|
||||
await github.rest.issues.createComment({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: prNumber,
|
||||
body: '/review',
|
||||
});
|
||||
}
|
||||
core?.info?.(`Kicked review chain for PR #${prNumber} (coderabbit=${needCoderabbit}, qodo=${needQodo})`);
|
||||
return { kicked: true, coderabbit: needCoderabbit, qodo: needQodo };
|
||||
}
|
||||
|
||||
async function findOpenPrForIssue(github, owner, repo, issueNumber) {
|
||||
const prefix = `claude/issue-${issueNumber}-`;
|
||||
const { data: prs } = await github.rest.pulls.list({
|
||||
owner,
|
||||
repo,
|
||||
state: 'open',
|
||||
sort: 'created',
|
||||
direction: 'desc',
|
||||
per_page: 30,
|
||||
});
|
||||
return (
|
||||
prs.find(
|
||||
(p) => (p.head?.ref || '').startsWith(prefix) && isBotOpenedPr(p)
|
||||
) || null
|
||||
);
|
||||
}
|
||||
|
||||
async function kickReviewChainForIssue(github, owner, repo, issueNumber, core) {
|
||||
const pr = await findOpenPrForIssue(github, owner, repo, issueNumber);
|
||||
if (!pr) {
|
||||
core?.info?.(`No open PR for issue #${issueNumber}, skipping review kick`);
|
||||
return { kicked: false, reason: 'no_pr' };
|
||||
}
|
||||
const result = await kickReviewChain(github, owner, repo, pr.number, core);
|
||||
return { ...result, prNumber: pr.number };
|
||||
}
|
||||
|
||||
async function recoverStalledBotPrs(github, owner, repo, options, core) {
|
||||
const { prNumber = null, minAgeMs = 10 * 60 * 1000, maxRecover = 10 } = options || {};
|
||||
let prs;
|
||||
if (prNumber) {
|
||||
const { data } = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
|
||||
prs = [data];
|
||||
} else if (typeof github.paginate === 'function') {
|
||||
prs = await github.paginate(github.rest.pulls.list, {
|
||||
owner,
|
||||
repo,
|
||||
state: 'open',
|
||||
per_page: 100,
|
||||
});
|
||||
} else {
|
||||
const { data } = await github.rest.pulls.list({ owner, repo, state: 'open', per_page: 100 });
|
||||
prs = data;
|
||||
}
|
||||
|
||||
const cutoff = Date.now() - minAgeMs;
|
||||
let recovered = 0;
|
||||
for (const pr of prs) {
|
||||
if (recovered >= maxRecover) break;
|
||||
if (!isBotOpenedPr(pr)) continue;
|
||||
if (!prNumber && new Date(pr.created_at).getTime() > cutoff) continue;
|
||||
const comments = await listAllComments(github, owner, repo, pr.number);
|
||||
if (chainKickPosted(comments)) continue;
|
||||
await kickReviewChain(github, owner, repo, pr.number, core, comments);
|
||||
recovered += 1;
|
||||
}
|
||||
core?.info?.(`Recovery complete (${recovered} PR(s) kicked)`);
|
||||
return recovered;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
KICK_AUTHORS,
|
||||
BOT_PR_AUTHORS,
|
||||
listAllComments,
|
||||
chainKickPosted,
|
||||
coderabbitKickPosted,
|
||||
qodoKickPosted,
|
||||
isBotOpenedPr,
|
||||
kickReviewChain,
|
||||
findOpenPrForIssue,
|
||||
kickReviewChainForIssue,
|
||||
recoverStalledBotPrs,
|
||||
};
|
||||
@@ -1,115 +0,0 @@
|
||||
#!/usr/bin/env node
|
||||
/**
|
||||
* Local self-test for merge-gate.js heuristics (no GitHub API).
|
||||
* Run: node .github/scripts/merge-gate-selftest.js
|
||||
*/
|
||||
const mg = require('./merge-gate.js');
|
||||
|
||||
let failed = 0;
|
||||
function assert(name, cond) {
|
||||
if (!cond) {
|
||||
console.error('FAIL:', name);
|
||||
failed++;
|
||||
} else {
|
||||
console.log('ok:', name);
|
||||
}
|
||||
}
|
||||
|
||||
// Stale FINAL: push after FINAL, no @claude since head
|
||||
const finals = [
|
||||
{ user: { login: 'github-actions[bot]' }, body: '@claude FINAL architecture reviewer', created_at: '2026-06-12T08:00:00Z' },
|
||||
];
|
||||
assert('stale when head after final', mg.isStaleFinalAfterPush(finals, '2026-06-12T09:00:00Z'));
|
||||
|
||||
const withRecovery = [
|
||||
...finals,
|
||||
{ user: { login: 'github-actions[bot]' }, body: '@claude FINAL architecture reviewer', created_at: '2026-06-12T09:30:00Z' },
|
||||
];
|
||||
assert('not stale when @claude after head', !mg.isStaleFinalAfterPush(withRecovery, '2026-06-12T09:00:00Z'));
|
||||
|
||||
// Bot CHANGES_REQUESTED then APPROVE
|
||||
const reviews = [
|
||||
{ user: { login: 'coderabbit[bot]', type: 'Bot' }, state: 'CHANGES_REQUESTED', submitted_at: '2026-06-12T08:00:00Z' },
|
||||
{ user: { login: 'coderabbit[bot]', type: 'Bot' }, state: 'APPROVED', submitted_at: '2026-06-12T09:00:00Z' },
|
||||
];
|
||||
assert('bot approve clears CR', !mg.hasAnyChangesRequested(reviews));
|
||||
assert('human CR blocks', mg.hasAnyChangesRequested([
|
||||
{ user: { login: 'MervinPraison', type: 'User' }, state: 'CHANGES_REQUESTED', submitted_at: '2026-06-12T09:00:00Z' },
|
||||
]));
|
||||
|
||||
// Verdict after HEAD
|
||||
const verdictComments = [
|
||||
{ body: 'MERGE_GATE_VERDICT: APPROVE', created_at: '2026-06-12T08:00:00Z' },
|
||||
];
|
||||
assert('verdict before head rejected', mg.findMergeGateVerdict(verdictComments, null, '2026-06-12T09:00:00Z') === null);
|
||||
assert('verdict after head accepted', mg.findMergeGateVerdict(
|
||||
[{ body: 'MERGE_GATE_VERDICT: APPROVE', created_at: '2026-06-12T10:00:00Z' }],
|
||||
null,
|
||||
'2026-06-12T09:00:00Z'
|
||||
) === 'APPROVE');
|
||||
|
||||
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));
|
||||
|
||||
// Sensitive + secrets
|
||||
assert('workflow path sensitive', mg.sensitivePathReasons([{ filename: '.github/workflows/foo.yml' }]).length === 1);
|
||||
assert('ci-only label exempts workflows', mg.sensitivePathReasons(
|
||||
[{ filename: '.github/workflows/foo.yml' }],
|
||||
[mg.WORKFLOW_ONLY_LABEL]
|
||||
).length === 0);
|
||||
assert('ci-only label not exempt mixed changes', mg.sensitivePathReasons(
|
||||
[{ filename: '.github/workflows/foo.yml' }, { filename: 'src/foo.py' }],
|
||||
[mg.WORKFLOW_ONLY_LABEL]
|
||||
).length === 1);
|
||||
assert('secret in patch', mg.secretScanReasons([{ filename: 'x.py', patch: '+key = "ghp_abcdefghijklmnopqrstuvwxyz1234567890"' }]).length === 1);
|
||||
|
||||
// Claude run scoping — other PR branches must not block
|
||||
assert('other branch claude does not block', !mg.hasBlockingClaudeRunForPr(
|
||||
[{ event: 'issue_comment', head_branch: 'other-branch' }],
|
||||
'my-branch'
|
||||
));
|
||||
assert('same branch claude blocks', mg.hasBlockingClaudeRunForPr(
|
||||
[{ event: 'issue_comment', head_branch: 'my-branch' }],
|
||||
'my-branch'
|
||||
));
|
||||
assert('issues event never blocks', !mg.hasBlockingClaudeRunForPr(
|
||||
[{ event: 'issues', head_branch: 'my-branch' }],
|
||||
'my-branch'
|
||||
));
|
||||
|
||||
// Conflict rebase clears after bot completion + FINAL on HEAD
|
||||
const conflictTrigger = {
|
||||
user: { login: 'MervinPraison' },
|
||||
body: '@claude this PR has merge conflicts with main. Please rebase',
|
||||
created_at: '2026-06-26T10:30:38Z',
|
||||
};
|
||||
const rebaseDone = {
|
||||
user: { login: 'praisonai-triage-agent[bot]' },
|
||||
body: 'Rebase complete — PR #2308 onto latest main',
|
||||
created_at: '2026-06-26T10:30:55Z',
|
||||
};
|
||||
const finalAfterRebase = {
|
||||
user: { login: 'MervinPraison' },
|
||||
body: '@claude You are the FINAL architecture reviewer.',
|
||||
created_at: '2026-06-26T10:39:43Z',
|
||||
};
|
||||
const headAfterRebase = '2026-06-26T10:39:25Z';
|
||||
const rebaseComments = [conflictTrigger, rebaseDone, finalAfterRebase];
|
||||
assert('conflict blocks before rebase done', mg.hasRecentConflictComment([conflictTrigger], headAfterRebase));
|
||||
assert('conflict clears after rebase + FINAL on HEAD', !mg.hasRecentConflictComment(rebaseComments, headAfterRebase));
|
||||
assert('conflict still blocks without FINAL on HEAD', mg.hasRecentConflictComment(
|
||||
[conflictTrigger, rebaseDone],
|
||||
headAfterRebase
|
||||
));
|
||||
|
||||
// Tests heuristic
|
||||
assert('sdk without tests', mg.missingTestsReason([{ filename: 'src/praisonai-agents/a/b.py', additions: 3 }]) !== null);
|
||||
assert('sdk with tests ok', mg.missingTestsReason([
|
||||
{ filename: 'src/praisonai-agents/a/b.py', additions: 3 },
|
||||
{ filename: 'src/praisonai-agents/tests/test_x.py', additions: 10 },
|
||||
]) === null);
|
||||
|
||||
// PR size
|
||||
assert('large PR blocked', mg.prSizeReasons([{ additions: 900 }]).length > 0);
|
||||
|
||||
process.exit(failed ? 1 : 0);
|
||||
@@ -1,706 +0,0 @@
|
||||
/**
|
||||
* Shared merge-gate helpers for claude-merge-gate.yml
|
||||
* @see .github/workflows/claude-merge-gate.yml
|
||||
*/
|
||||
|
||||
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 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;
|
||||
const PR_MAX_AUTO_FILES = 30;
|
||||
const MANUAL_ONLY_LABELS = new Set(['security', 'breaking-change', 'needs-manual-review', 'release']);
|
||||
const WORKFLOW_ONLY_LABEL = 'merge-gate-ci-only';
|
||||
const CI_ONLY_PATH_PREFIXES = ['.github/workflows/', '.github/actions/', '.github/scripts/merge-gate'];
|
||||
const SDK_PATH_PREFIXES = ['src/praisonai-agents/', 'src/praisonai/'];
|
||||
const SENSITIVE_PATH_PATTERNS = [
|
||||
/^\.github\/workflows\//,
|
||||
/praisonaiagents\/(auth|approval|policy|sandbox)\//,
|
||||
/^src\/praisonai-agents\/pyproject\.toml$/,
|
||||
/^src\/praisonai\/pyproject\.toml$/,
|
||||
/\.env(\.|$)/,
|
||||
/credentials\.json$/i,
|
||||
];
|
||||
const REQUIRED_SDK_CHECK_PATTERNS = [/test/i, /smoke/i, /core/i, /python package/i, /comprehensive/i, /optimized/i];
|
||||
const SECRET_PATTERNS = [
|
||||
/sk-[a-zA-Z0-9]{20,}/,
|
||||
/AKIA[0-9A-Z]{16}/,
|
||||
/ghp_[a-zA-Z0-9]{36,}/,
|
||||
/github_pat_/,
|
||||
/Bearer eyJ[a-zA-Z0-9_-]+\.[a-zA-Z0-9_-]+/,
|
||||
/-----BEGIN (RSA |EC |OPENSSH )?PRIVATE KEY-----/,
|
||||
];
|
||||
const BLOCK_LABELS = new Set([
|
||||
'claude-conflict-pending',
|
||||
'claude-merge-gate-active',
|
||||
'no-auto-merge',
|
||||
'auto-merged-by-gate',
|
||||
]);
|
||||
const BOT_REVIEWER_PATTERNS = [
|
||||
'coderabbit',
|
||||
'qodo',
|
||||
'gemini',
|
||||
'copilot',
|
||||
'greptile',
|
||||
];
|
||||
|
||||
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
|
||||
|
||||
function isFinalClaudeTriggerComment(c) {
|
||||
const body = (c.body || '').toLowerCase();
|
||||
if (!AUTO_ACTORS.includes(c.user.login)) return false;
|
||||
if (!body.includes('@claude')) return false;
|
||||
if (body.includes('merge conflict')) return false;
|
||||
return body.includes('final architecture reviewer') || body.includes('lead engineer');
|
||||
}
|
||||
|
||||
function isClaudeTriggerNoise(c) {
|
||||
const body = c.body || '';
|
||||
if (body.includes('Merge gate scan')) return true;
|
||||
if (body.includes('MERGE_GATE_VERDICT')) return true;
|
||||
if (body.includes('Merged by **Claude PR merge gate**')) return true;
|
||||
return false;
|
||||
}
|
||||
|
||||
function hasRecentClaudeTrigger(comments, minutes = 35) {
|
||||
const cutoff = Date.now() - minutes * 60 * 1000;
|
||||
return comments.some((c) => {
|
||||
if (!CLAUDE_TRIGGER_LOGINS.includes(c.user.login)) return false;
|
||||
if (isClaudeTriggerNoise(c)) return false;
|
||||
if (!(c.body || '').includes('@claude')) return false;
|
||||
return new Date(c.created_at).getTime() > cutoff;
|
||||
});
|
||||
}
|
||||
|
||||
function isConflictRebaseTriggerComment(c) {
|
||||
if (!AUTO_ACTORS.includes(c.user.login)) return false;
|
||||
const body = (c.body || '').toLowerCase();
|
||||
return body.includes('@claude') && body.includes('merge conflict');
|
||||
}
|
||||
|
||||
function isConflictRebaseCompletionComment(c) {
|
||||
const login = (c.user?.login || '').toLowerCase();
|
||||
if (!login.includes('praisonai-triage') && !login.includes('github-actions')) return false;
|
||||
const body = (c.body || '').toLowerCase();
|
||||
return (
|
||||
body.includes('rebase complete') ||
|
||||
body.includes('rebase onto') ||
|
||||
(body.includes('conflict') && body.includes('resolved'))
|
||||
);
|
||||
}
|
||||
|
||||
function conflictRebaseQuiescent(comments, headPushedAt) {
|
||||
const conflictTriggers = comments.filter(isConflictRebaseTriggerComment);
|
||||
if (conflictTriggers.length === 0) return true;
|
||||
|
||||
const latestConflict = conflictTriggers.reduce((a, b) =>
|
||||
new Date(a.created_at) > new Date(b.created_at) ? a : b
|
||||
);
|
||||
const conflictTime = new Date(latestConflict.created_at).getTime();
|
||||
|
||||
const rebaseDone = comments.some(
|
||||
(c) =>
|
||||
new Date(c.created_at).getTime() > conflictTime && isConflictRebaseCompletionComment(c)
|
||||
);
|
||||
if (!rebaseDone) return false;
|
||||
|
||||
return finalClaudeCompletedOnSha(comments, headPushedAt);
|
||||
}
|
||||
|
||||
function hasRecentConflictComment(comments, headPushedAt = null) {
|
||||
const cutoff = Date.now() - CONFLICT_COOLDOWN_MS;
|
||||
const hasRecentTrigger = comments.some((c) => {
|
||||
if (!isConflictRebaseTriggerComment(c)) return false;
|
||||
return new Date(c.created_at).getTime() > cutoff;
|
||||
});
|
||||
if (!hasRecentTrigger) return false;
|
||||
|
||||
if (headPushedAt && conflictRebaseQuiescent(comments, headPushedAt)) {
|
||||
return false;
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
function isBotReviewer(login, userType) {
|
||||
const lower = (login || '').toLowerCase();
|
||||
if (userType === 'Bot') return true;
|
||||
if (lower.endsWith('[bot]')) return true;
|
||||
return ['coderabbit', 'qodo', 'gemini', 'copilot', 'greptile'].some((p) => lower.includes(p));
|
||||
}
|
||||
|
||||
function latestReviewsByUser(reviews) {
|
||||
const latestByUser = new Map();
|
||||
for (const r of reviews) {
|
||||
const login = r.user?.login;
|
||||
if (!login) continue;
|
||||
const prev = latestByUser.get(login);
|
||||
if (!prev || new Date(r.submitted_at) > new Date(prev.submitted_at)) {
|
||||
latestByUser.set(login, r);
|
||||
}
|
||||
}
|
||||
return latestByUser;
|
||||
}
|
||||
|
||||
function hasHumanChangesRequested(reviews) {
|
||||
for (const [login, review] of latestReviewsByUser(reviews)) {
|
||||
if (review.state !== 'CHANGES_REQUESTED') continue;
|
||||
if (!isBotReviewer(login, review.user?.type)) return true;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
function hasAnyChangesRequested(reviews) {
|
||||
for (const [, review] of latestReviewsByUser(reviews)) {
|
||||
if (review.state === 'CHANGES_REQUESTED') return true;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
function hasFinalClaudeReviewTrigger(comments) {
|
||||
return comments.some(isFinalClaudeTriggerComment);
|
||||
}
|
||||
|
||||
function isStaleFinalAfterPush(comments, headPushedAt) {
|
||||
if (!headPushedAt) return false;
|
||||
const headTime = new Date(headPushedAt).getTime();
|
||||
const finals = comments.filter(isFinalClaudeTriggerComment);
|
||||
if (finals.length === 0) return true;
|
||||
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();
|
||||
if (headTime <= finalTime + 60000) return false;
|
||||
const claudeSinceHead = comments.some((c) => {
|
||||
if (!CLAUDE_TRIGGER_LOGINS.includes(c.user.login)) return false;
|
||||
if (isClaudeTriggerNoise(c)) return false;
|
||||
if (!(c.body || '').includes('@claude')) return false;
|
||||
return new Date(c.created_at).getTime() >= headTime - 60000;
|
||||
});
|
||||
return !claudeSinceHead;
|
||||
}
|
||||
|
||||
function needsStaleFinalRecovery(comments, headPushedAt) {
|
||||
return (
|
||||
hasFinalClaudeReviewTrigger(comments) &&
|
||||
isStaleFinalAfterPush(comments, headPushedAt)
|
||||
);
|
||||
}
|
||||
|
||||
function shouldSkipFinalRecovery(comments, headPushedAt) {
|
||||
const isStale = isStaleFinalAfterPush(comments, headPushedAt);
|
||||
if (isStale) return false;
|
||||
return hasRecentClaudeTrigger(comments, 35);
|
||||
}
|
||||
|
||||
function finalClaudeCompletedOnSha(comments, headPushedAt) {
|
||||
if (!hasFinalClaudeReviewTrigger(comments)) return false;
|
||||
if (isStaleFinalAfterPush(comments, headPushedAt)) return false;
|
||||
return true;
|
||||
}
|
||||
|
||||
const FINAL_CLAUDE_REVIEW_BODY =
|
||||
'@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n4. SDK value: review in depth whether the change genuinely adds value to the SDK — never add features for the sake of adding them. It must strengthen the SDK (simpler, more user-friendly, robust, world-class, secure). If it does not clearly add value, request changes or recommend rejecting/closing rather than merging scope creep\n5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.\n\n**Phase 2: FIX Valid Issues**\n5. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n6. Push all code fixes directly to THIS branch (do NOT create a new PR)\n7. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n8. If all issues are resolved, approve the PR / close the Issue\n9. If blocking issues remain, request changes / leave clear action items';
|
||||
|
||||
async function getMergeState(github, owner, repo, prNumber) {
|
||||
const query = `
|
||||
query($owner: String!, $repo: String!, $number: Int!) {
|
||||
repository(owner: $owner, name: $repo) {
|
||||
pullRequest(number: $number) {
|
||||
mergeStateStatus
|
||||
maintainerCanModify
|
||||
isDraft
|
||||
headRefOid
|
||||
headRef { repository { nameWithOwner } }
|
||||
}
|
||||
}
|
||||
}
|
||||
`;
|
||||
for (let attempt = 0; attempt < 3; attempt++) {
|
||||
const result = await github.graphql(query, { owner, repo, number: prNumber });
|
||||
const prGql = result.repository.pullRequest;
|
||||
const status = (prGql?.mergeStateStatus || '').toUpperCase();
|
||||
if (status && status !== 'UNKNOWN') {
|
||||
return {
|
||||
status,
|
||||
isDraft: prGql.isDraft,
|
||||
headRepo: prGql.headRef?.repository?.nameWithOwner,
|
||||
headSha: prGql.headRefOid,
|
||||
maintainerCanModify: prGql.maintainerCanModify === true,
|
||||
};
|
||||
}
|
||||
if (attempt < 2) await sleep(10000);
|
||||
}
|
||||
const { data: pr } = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
|
||||
return {
|
||||
status: (pr.mergeable_state || '').toUpperCase(),
|
||||
isDraft: pr.draft,
|
||||
headRepo: pr.head.repo?.full_name,
|
||||
headSha: pr.head.sha,
|
||||
maintainerCanModify: pr.maintainer_can_modify === true,
|
||||
};
|
||||
}
|
||||
|
||||
async function allChecksGreenOnSha(github, owner, repo, sha, core) {
|
||||
const { data } = await github.rest.checks.listForRef({
|
||||
owner,
|
||||
repo,
|
||||
ref: sha,
|
||||
per_page: 100,
|
||||
});
|
||||
const runs = (data.check_runs || []).filter((r) => r.head_sha === sha);
|
||||
if (runs.length === 0) {
|
||||
core?.info?.(`No check runs on ${sha.slice(0, 7)} — allowing (e.g. docs-only PR)`);
|
||||
return true;
|
||||
}
|
||||
for (const run of runs) {
|
||||
if (run.status !== 'completed') {
|
||||
core?.info?.(`Check pending: ${run.name} (${run.status})`);
|
||||
return false;
|
||||
}
|
||||
const ok = ['success', 'neutral', 'skipped'].includes(run.conclusion);
|
||||
if (!ok) {
|
||||
core?.info?.(`Check failed: ${run.name} (${run.conclusion})`);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
function claudeRunBlocksPr(run, headRef) {
|
||||
if (!run || run.event === 'issues') return false;
|
||||
if (!headRef) return true;
|
||||
return run.head_branch === headRef;
|
||||
}
|
||||
|
||||
function hasBlockingClaudeRunForPr(runs, headRef) {
|
||||
return (runs || []).some((r) => claudeRunBlocksPr(r, headRef));
|
||||
}
|
||||
|
||||
async function hasInProgressClaudeAssistant(github, owner, repo, prNumber = null) {
|
||||
try {
|
||||
const { data } = await github.rest.actions.listWorkflowRuns({
|
||||
owner,
|
||||
repo,
|
||||
workflow_id: 'claude.yml',
|
||||
status: 'in_progress',
|
||||
per_page: 20,
|
||||
});
|
||||
const runs = (data.workflow_runs || []).filter((r) => r.event !== 'issues');
|
||||
if (runs.length === 0) return false;
|
||||
if (prNumber == null) return runs.length > 0;
|
||||
|
||||
const { data: pr } = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
|
||||
const headRef = pr.head.ref;
|
||||
return hasBlockingClaudeRunForPr(runs, headRef);
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
function isCiOnlyChange(files) {
|
||||
if (!files.length) return false;
|
||||
return files.every((f) => CI_ONLY_PATH_PREFIXES.some((p) => f.filename.startsWith(p)));
|
||||
}
|
||||
|
||||
async function resolvePrNumberFromWorkflowRun(github, owner, repo, workflowRun) {
|
||||
const linked = workflowRun.pull_requests || [];
|
||||
if (linked.length > 0 && linked[0].number) return linked[0].number;
|
||||
const branch = workflowRun.head_branch;
|
||||
if (!branch) return null;
|
||||
const { data } = await github.rest.pulls.list({
|
||||
owner,
|
||||
repo,
|
||||
state: 'open',
|
||||
head: `${owner}:${branch}`,
|
||||
per_page: 1,
|
||||
});
|
||||
return data[0]?.number || null;
|
||||
}
|
||||
|
||||
async function listPullFiles(github, owner, repo, prNumber) {
|
||||
if (typeof github.paginate === 'function') {
|
||||
return github.paginate(github.rest.pulls.listFiles, {
|
||||
owner,
|
||||
repo,
|
||||
pull_number: prNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
}
|
||||
const { data } = await github.rest.pulls.listFiles({
|
||||
owner,
|
||||
repo,
|
||||
pull_number: prNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
return data;
|
||||
}
|
||||
|
||||
function countNewAgentParams(patch) {
|
||||
if (!patch) return 0;
|
||||
return patch
|
||||
.split('\n')
|
||||
.filter((l) => l.startsWith('+') && !l.startsWith('+++'))
|
||||
.filter((l) => {
|
||||
const t = l.slice(1).trim();
|
||||
if (!t || t.startsWith('#') || t.startsWith('"""') || t.startsWith("'''")) return false;
|
||||
if (/^(def|class|@|return\b|if\b|elif\b|else\b|for\b|while\b)/.test(t)) return false;
|
||||
if (/^\w+\s*[:=]/.test(t) && !t.startsWith('self.')) return true;
|
||||
return false;
|
||||
}).length;
|
||||
}
|
||||
|
||||
function getAgentPyChangeFromFiles(files) {
|
||||
const agentFile = files.find((f) => f.filename.endsWith('praisonaiagents/agent/agent.py'));
|
||||
if (!agentFile) {
|
||||
return { touched: false, additions: 0, newParams: 0 };
|
||||
}
|
||||
return {
|
||||
touched: true,
|
||||
additions: agentFile.additions || 0,
|
||||
newParams: countNewAgentParams(agentFile.patch || ''),
|
||||
};
|
||||
}
|
||||
|
||||
async function getAgentPyChange(github, owner, repo, prNumber) {
|
||||
const files = await listPullFiles(github, owner, repo, prNumber);
|
||||
return getAgentPyChangeFromFiles(files);
|
||||
}
|
||||
|
||||
function touchesSdk(files) {
|
||||
return files.some((f) => SDK_PATH_PREFIXES.some((p) => f.filename.startsWith(p)));
|
||||
}
|
||||
|
||||
function hasManualOnlyLabel(labels) {
|
||||
return labels.some((l) => MANUAL_ONLY_LABELS.has(l));
|
||||
}
|
||||
|
||||
function sensitivePathReasons(files, labels = []) {
|
||||
if (labels.includes(WORKFLOW_ONLY_LABEL) && isCiOnlyChange(files)) {
|
||||
return [];
|
||||
}
|
||||
const reasons = [];
|
||||
for (const f of files) {
|
||||
if (SENSITIVE_PATH_PATTERNS.some((p) => p.test(f.filename))) {
|
||||
reasons.push(`sensitive path: ${f.filename}`);
|
||||
break;
|
||||
}
|
||||
}
|
||||
return reasons;
|
||||
}
|
||||
|
||||
function prSizeReasons(files) {
|
||||
const reasons = [];
|
||||
const totalAdditions = files.reduce((sum, f) => sum + (f.additions || 0), 0);
|
||||
if (totalAdditions > PR_MAX_AUTO_ADDITIONS) {
|
||||
reasons.push(`PR +${totalAdditions} lines (>${PR_MAX_AUTO_ADDITIONS}) requires manual review`);
|
||||
}
|
||||
if (files.length > PR_MAX_AUTO_FILES) {
|
||||
reasons.push(`${files.length} files changed (>${PR_MAX_AUTO_FILES}) requires manual review`);
|
||||
}
|
||||
return reasons;
|
||||
}
|
||||
|
||||
function missingTestsReason(files) {
|
||||
const sdkAdds = files.filter(
|
||||
(f) =>
|
||||
f.filename.startsWith('src/praisonai-agents/') &&
|
||||
f.filename.endsWith('.py') &&
|
||||
!f.filename.endsWith('__init__.py') &&
|
||||
(f.additions || 0) > 0
|
||||
);
|
||||
if (sdkAdds.length === 0) return null;
|
||||
const hasTestChange = files.some(
|
||||
(f) => /\/tests?\//.test(f.filename) || /test_.*\.py$/.test(f.filename) || /_test\.py$/.test(f.filename)
|
||||
);
|
||||
if (!hasTestChange) return 'SDK code added without test file changes — requires manual review';
|
||||
return null;
|
||||
}
|
||||
|
||||
function secretScanReasons(files) {
|
||||
for (const f of files) {
|
||||
if (/\/tests?\//.test(f.filename) || /test_.*\.py$/.test(f.filename)) continue;
|
||||
const patch = f.patch || '';
|
||||
if (!patch) continue;
|
||||
for (const pattern of SECRET_PATTERNS) {
|
||||
if (pattern.test(patch)) {
|
||||
return [`possible secret in diff (${f.filename}) — requires manual review`];
|
||||
}
|
||||
}
|
||||
}
|
||||
return [];
|
||||
}
|
||||
|
||||
async function sdkTestChecksReason(github, owner, repo, sha, files, core) {
|
||||
if (!touchesSdk(files)) return null;
|
||||
const { data } = await github.rest.checks.listForRef({
|
||||
owner,
|
||||
repo,
|
||||
ref: sha,
|
||||
per_page: 100,
|
||||
});
|
||||
const runs = (data.check_runs || []).filter((r) => r.head_sha === sha);
|
||||
if (runs.length === 0) {
|
||||
return 'SDK code changed but no CI checks on HEAD';
|
||||
}
|
||||
const testRuns = runs.filter((r) => REQUIRED_SDK_CHECK_PATTERNS.some((p) => p.test(r.name || '')));
|
||||
if (testRuns.length === 0) {
|
||||
return 'SDK code changed but no test check runs on HEAD';
|
||||
}
|
||||
core?.info?.(`SDK test checks on HEAD: ${testRuns.map((r) => r.name).join(', ')}`);
|
||||
return null;
|
||||
}
|
||||
|
||||
function manualReviewReasonForAgentPy(agentChange) {
|
||||
if (!agentChange.touched) return null;
|
||||
if (agentChange.additions > AGENT_PY_MAX_AUTO_LINES) {
|
||||
return `agent.py +${agentChange.additions} lines (>${AGENT_PY_MAX_AUTO_LINES}) requires manual review`;
|
||||
}
|
||||
if (agentChange.newParams > 0) {
|
||||
return `agent.py adds ${agentChange.newParams} new Agent param(s) — requires manual review`;
|
||||
}
|
||||
return null;
|
||||
}
|
||||
|
||||
async function listAllComments(github, owner, repo, issueNumber) {
|
||||
if (typeof github.paginate === 'function') {
|
||||
return github.paginate(github.rest.issues.listComments, {
|
||||
owner,
|
||||
repo,
|
||||
issue_number: issueNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
}
|
||||
const { data } = await github.rest.issues.listComments({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: issueNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
return data;
|
||||
}
|
||||
|
||||
async function getHeadCommitDate(github, owner, repo, prNumber) {
|
||||
try {
|
||||
let commits;
|
||||
if (typeof github.paginate === 'function') {
|
||||
commits = await github.paginate(github.rest.pulls.listCommits, {
|
||||
owner,
|
||||
repo,
|
||||
pull_number: prNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
} else {
|
||||
const { data } = await github.rest.pulls.listCommits({
|
||||
owner,
|
||||
repo,
|
||||
pull_number: prNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
commits = data;
|
||||
}
|
||||
const last = commits[commits.length - 1];
|
||||
return last?.commit?.committer?.date || last?.commit?.author?.date || null;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
async function loadPrContext(github, owner, repo, prNumber) {
|
||||
const { data: pr } = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
|
||||
const { data: issue } = await github.rest.issues.get({ owner, repo, issue_number: prNumber });
|
||||
const comments = await listAllComments(github, owner, repo, prNumber);
|
||||
const { data: reviews } = await github.rest.pulls.listReviews({
|
||||
owner,
|
||||
repo,
|
||||
pull_number: prNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
const mergeState = await getMergeState(github, owner, repo, prNumber);
|
||||
const headSha = mergeState.headSha || pr.head.sha;
|
||||
const headCommitDate = await getHeadCommitDate(github, owner, repo, prNumber);
|
||||
const headPushedAt = headCommitDate || pr.updated_at;
|
||||
|
||||
return {
|
||||
pr,
|
||||
issue,
|
||||
comments,
|
||||
reviews,
|
||||
mergeState,
|
||||
headSha,
|
||||
headPushedAt,
|
||||
labels: issue.labels.map((l) => l.name),
|
||||
baseRepo: `${owner}/${repo}`,
|
||||
};
|
||||
}
|
||||
|
||||
async function evaluatePipelineQuiescent(github, owner, repo, prNumber, core, options = {}) {
|
||||
const {
|
||||
forMergeStep = false,
|
||||
skipGlobalClaudeRunCheck = false,
|
||||
skipRecentClaudeCooldown = false,
|
||||
} = options;
|
||||
const ctx = await loadPrContext(github, owner, repo, prNumber);
|
||||
const reasons = [];
|
||||
|
||||
if (ctx.pr.draft) reasons.push('draft');
|
||||
if (ctx.pr.state !== 'open') reasons.push('not open');
|
||||
if (ctx.labels.includes('auto-merged-by-gate')) reasons.push('already merged by gate');
|
||||
if (ctx.labels.includes('no-auto-merge')) reasons.push('no-auto-merge label');
|
||||
if (ctx.labels.includes('claude-conflict-pending')) reasons.push('claude-conflict-pending');
|
||||
if (!forMergeStep && ctx.labels.includes('claude-merge-gate-active')) {
|
||||
reasons.push('claude-merge-gate-active');
|
||||
}
|
||||
|
||||
const { status, headRepo, maintainerCanModify } = ctx.mergeState;
|
||||
if (!ALLOWED_MERGE_STATES.has(status)) reasons.push(`mergeState=${status}`);
|
||||
|
||||
if (headRepo && headRepo !== ctx.baseRepo) {
|
||||
reasons.push('fork PR');
|
||||
}
|
||||
|
||||
if (hasRecentConflictComment(ctx.comments, ctx.headPushedAt)) {
|
||||
reasons.push('recent merge-conflict @claude');
|
||||
}
|
||||
if (!skipRecentClaudeCooldown && hasRecentClaudeTrigger(ctx.comments, 35)) {
|
||||
reasons.push('recent @claude within 35min');
|
||||
}
|
||||
|
||||
if (!skipGlobalClaudeRunCheck && (await hasInProgressClaudeAssistant(github, owner, repo, prNumber))) {
|
||||
reasons.push('claude.yml in progress');
|
||||
}
|
||||
|
||||
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)) {
|
||||
reasons.push('no FINAL Claude review trigger');
|
||||
} else if (isStaleFinalAfterPush(ctx.comments, ctx.headPushedAt)) {
|
||||
reasons.push('stale FINAL after new commits (needs @claude re-review)');
|
||||
} else {
|
||||
reasons.push('FINAL Claude not complete on HEAD');
|
||||
}
|
||||
}
|
||||
|
||||
if (hasAnyChangesRequested(ctx.reviews)) reasons.push('CHANGES_REQUESTED review');
|
||||
|
||||
if (hasManualOnlyLabel(ctx.labels)) {
|
||||
const manualLabel = ctx.labels.find((l) => MANUAL_ONLY_LABELS.has(l));
|
||||
reasons.push(`manual-only label: ${manualLabel}`);
|
||||
}
|
||||
|
||||
const pullFiles = await listPullFiles(github, owner, repo, prNumber);
|
||||
|
||||
const agentChange = getAgentPyChangeFromFiles(pullFiles);
|
||||
const agentManual = manualReviewReasonForAgentPy(agentChange);
|
||||
if (agentManual) reasons.push(agentManual);
|
||||
|
||||
reasons.push(...sensitivePathReasons(pullFiles, ctx.labels));
|
||||
reasons.push(...prSizeReasons(pullFiles));
|
||||
reasons.push(...secretScanReasons(pullFiles));
|
||||
|
||||
const testsReason = missingTestsReason(pullFiles);
|
||||
if (testsReason) reasons.push(testsReason);
|
||||
|
||||
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;
|
||||
return {
|
||||
ready,
|
||||
reasons,
|
||||
headSha: ctx.headSha,
|
||||
prNumber,
|
||||
};
|
||||
}
|
||||
|
||||
async function selectMergeGateCandidates(github, owner, repo, prNumbers, maxCandidates, core) {
|
||||
const readyList = [];
|
||||
const skipped = [];
|
||||
for (const num of prNumbers) {
|
||||
const result = await evaluatePipelineQuiescent(github, owner, repo, num, core);
|
||||
if (result.ready) {
|
||||
readyList.push({ pr_number: num, head_sha: result.headSha });
|
||||
} else {
|
||||
skipped.push({ pr: num, reasons: result.reasons });
|
||||
}
|
||||
}
|
||||
readyList.sort((a, b) => a.pr_number - b.pr_number);
|
||||
return {
|
||||
candidates: readyList.slice(0, maxCandidates),
|
||||
skipped,
|
||||
};
|
||||
}
|
||||
|
||||
function findMergeGateVerdict(comments, minCreatedAt = null, headPushedAt = null) {
|
||||
const minTime = minCreatedAt ? new Date(minCreatedAt).getTime() : 0;
|
||||
const headTime = headPushedAt ? new Date(headPushedAt).getTime() - 60000 : 0;
|
||||
const gateComments = comments
|
||||
.filter((c) => {
|
||||
if (!(c.body || '').includes('MERGE_GATE_VERDICT:')) return false;
|
||||
const created = new Date(c.created_at).getTime();
|
||||
if (minTime && created < minTime) return false;
|
||||
if (headTime && created < headTime) return false;
|
||||
return true;
|
||||
})
|
||||
.sort((a, b) => new Date(b.created_at) - new Date(a.created_at));
|
||||
if (gateComments.length === 0) return null;
|
||||
const body = gateComments[0].body || '';
|
||||
if (body.includes('MERGE_GATE_VERDICT: APPROVE')) return 'APPROVE';
|
||||
if (body.includes('MERGE_GATE_VERDICT: BLOCK')) return 'BLOCK';
|
||||
return null;
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
CLAUDE_TRIGGER_LOGINS,
|
||||
AUTO_ACTORS,
|
||||
isFinalClaudeTriggerComment,
|
||||
isClaudeTriggerNoise,
|
||||
hasRecentClaudeTrigger,
|
||||
hasRecentConflictComment,
|
||||
isConflictRebaseTriggerComment,
|
||||
isConflictRebaseCompletionComment,
|
||||
conflictRebaseQuiescent,
|
||||
hasHumanChangesRequested,
|
||||
hasAnyChangesRequested,
|
||||
hasFinalClaudeReviewTrigger,
|
||||
finalClaudeCompletedOnSha,
|
||||
getMergeState,
|
||||
allChecksGreenOnSha,
|
||||
hasInProgressClaudeAssistant,
|
||||
claudeRunBlocksPr,
|
||||
hasBlockingClaudeRunForPr,
|
||||
isCiOnlyChange,
|
||||
resolvePrNumberFromWorkflowRun,
|
||||
WORKFLOW_ONLY_LABEL,
|
||||
getAgentPyChange,
|
||||
getAgentPyChangeFromFiles,
|
||||
manualReviewReasonForAgentPy,
|
||||
countNewAgentParams,
|
||||
listPullFiles,
|
||||
touchesSdk,
|
||||
hasManualOnlyLabel,
|
||||
sensitivePathReasons,
|
||||
prSizeReasons,
|
||||
missingTestsReason,
|
||||
secretScanReasons,
|
||||
sdkTestChecksReason,
|
||||
listAllComments,
|
||||
getHeadCommitDate,
|
||||
isStaleFinalAfterPush,
|
||||
needsStaleFinalRecovery,
|
||||
shouldSkipFinalRecovery,
|
||||
FINAL_CLAUDE_REVIEW_BODY,
|
||||
loadPrContext,
|
||||
evaluatePipelineQuiescent,
|
||||
selectMergeGateCandidates,
|
||||
findMergeGateVerdict,
|
||||
};
|
||||
@@ -15,10 +15,7 @@ on:
|
||||
pull_request_review:
|
||||
types: [submitted]
|
||||
pull_request:
|
||||
types: [opened, synchronize]
|
||||
schedule:
|
||||
- cron: '30 3,9,15,21 * * *'
|
||||
workflow_dispatch:
|
||||
types: [opened]
|
||||
|
||||
env:
|
||||
MAX_POLL_ATTEMPTS: 20
|
||||
@@ -146,12 +143,9 @@ jobs:
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c => {
|
||||
const body = (c.body || '').toLowerCase();
|
||||
if (!body.includes('@claude') || !triggerLogins.includes(c.user.login)) return false;
|
||||
if (body.includes('merge conflict')) return false;
|
||||
return body.includes('final architecture reviewer') || body.includes('lead engineer');
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c =>
|
||||
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
|
||||
);
|
||||
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
|
||||
core.setOutput('comments_count', comments.data.length.toString());
|
||||
|
||||
@@ -192,8 +186,7 @@ jobs:
|
||||
const claudeBody = '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. ' + reviewSummary + '.\n\n' +
|
||||
'Review Context: ' + comments.data.length + ' total comments, ' +
|
||||
(reviews.coderabbit.length + reviews.qodo.length + reviews.gemini.length + reviews.copilot.length + reviews.greptile.length) + ' bot reviews.\n\n' +
|
||||
'Phase 1: Review per AGENTS.md principles (protocol-driven, backward compatible, no perf impact, SDK value gate — no feature bloat).\n' +
|
||||
'Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.\n' +
|
||||
'Phase 1: Review per AGENTS.md principles (protocol-driven, backward compatible, no perf impact).\n' +
|
||||
'Phase 2: FIX valid issues found by prior reviewers.\n' +
|
||||
'Phase 3: Provide final verdict (approve or request changes).';
|
||||
await github.rest.issues.createComment({issue_number: context.issue.number, owner: context.repo.owner, repo: context.repo.repo, body: claudeBody});
|
||||
@@ -302,12 +295,9 @@ jobs:
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c => {
|
||||
const body = (c.body || '').toLowerCase();
|
||||
if (!body.includes('@claude') || !triggerLogins.includes(c.user.login)) return false;
|
||||
if (body.includes('merge conflict')) return false;
|
||||
return body.includes('final architecture reviewer') || body.includes('lead engineer');
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c =>
|
||||
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
|
||||
);
|
||||
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
|
||||
|
||||
- name: Trigger Claude final review
|
||||
@@ -323,7 +313,7 @@ jobs:
|
||||
issue_number: pr,
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n4. SDK value: review in depth whether the change genuinely adds value to the SDK — never add features for the sake of adding them. It must strengthen the SDK (simpler, more user-friendly, robust, world-class, secure). If it does not clearly add value, request changes or recommend rejecting/closing rather than merging scope creep\n5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.\n\n**Phase 2: FIX Valid Issues**\n5. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n6. Push all code fixes directly to THIS branch (do NOT create a new PR)\n7. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n8. If all issues are resolved, approve the PR / close the Issue\n9. If blocking issues remain, request changes / leave clear action items'
|
||||
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
|
||||
});
|
||||
console.log(`Claude triggered on PR #${pr}`);
|
||||
|
||||
@@ -409,12 +399,9 @@ jobs:
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c => {
|
||||
const body = (c.body || '').toLowerCase();
|
||||
if (!body.includes('@claude') || !triggerLogins.includes(c.user.login)) return false;
|
||||
if (body.includes('merge conflict')) return false;
|
||||
return body.includes('final architecture reviewer') || body.includes('lead engineer');
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c =>
|
||||
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
|
||||
);
|
||||
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
|
||||
|
||||
- name: Trigger Claude final review
|
||||
@@ -430,7 +417,7 @@ jobs:
|
||||
issue_number: pr,
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n4. SDK value: review in depth whether the change genuinely adds value to the SDK — never add features for the sake of adding them. It must strengthen the SDK (simpler, more user-friendly, robust, world-class, secure). If it does not clearly add value, request changes or recommend rejecting/closing rather than merging scope creep\n5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.\n\n**Phase 2: FIX Valid Issues**\n5. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n6. Push all code fixes directly to THIS branch (do NOT create a new PR)\n7. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n8. If all issues are resolved, approve the PR / close the Issue\n9. If blocking issues remain, request changes / leave clear action items'
|
||||
body: '@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
|
||||
});
|
||||
console.log(`Claude triggered on PR #${pr}`);
|
||||
|
||||
@@ -466,12 +453,9 @@ jobs:
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c => {
|
||||
const body = (c.body || '').toLowerCase();
|
||||
if (!body.includes('@claude') || !triggerLogins.includes(c.user.login)) return false;
|
||||
if (body.includes('merge conflict')) return false;
|
||||
return body.includes('final architecture reviewer') || body.includes('lead engineer');
|
||||
});
|
||||
const alreadyPosted = comments.data.some(c =>
|
||||
c.body.includes('@claude') && triggerLogins.includes(c.user.login)
|
||||
);
|
||||
core.setOutput('already_triggered', alreadyPosted ? 'true' : 'false');
|
||||
|
||||
- name: Post Claude analysis request (Lead Engineer)
|
||||
@@ -484,116 +468,9 @@ jobs:
|
||||
issue_number: context.issue.number,
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
body: '@claude You are the Lead Engineer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL analysis and reviews above carefully (Gemini, CodeRabbit, Qodo, Copilot, etc).\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n4. SDK value: review in depth whether the change genuinely adds value to the SDK — never add features for the sake of adding them. It must strengthen the SDK (simpler, more user-friendly, robust, world-class, secure). If it does not clearly add value, request changes or recommend rejecting/closing rather than merging scope creep\n5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.\n\n**Phase 2: FIX Valid Issues**\n5. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n6. Push all code fixes directly to THIS branch (do NOT create a new PR)\n7. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n8. If all issues are resolved, approve the PR / close the Issue\n9. If blocking issues remain, request changes / leave clear action items'
|
||||
body: '@claude You are the Lead Engineer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Focus ONLY on Python packages (praisonaiagents, praisonai). Do NOT modify praisonai-rust or praisonai-ts. Read ALL analysis and reviews above carefully (Gemini, CodeRabbit, Qodo, Copilot, etc).\n\n**Phase 1: Review per AGENTS.md**\n1. Protocol-driven: check heavy implementations vs core SDK\n2. Backward compatible: ensure zero feature regressions\n3. Performance: no hot-path regressions\n\n**Phase 2: FIX Valid Issues**\n4. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix\n5. Push all code fixes directly to THIS branch (do NOT create a new PR)\n6. Comment a summary of exact files modified and what you skipped\n\n**Phase 3: Final Verdict**\n7. If all issues are resolved, approve the PR / close the Issue\n8. If blocking issues remain, request changes / leave clear action items'
|
||||
});
|
||||
|
||||
# ================================================================
|
||||
# Recovery: post FINAL @claude if merge-conflict comment blocked the chain
|
||||
# (e.g. conflict fired before claude-after-copilot could post review prompt)
|
||||
# ================================================================
|
||||
claude-review-recovery:
|
||||
if: |
|
||||
github.event_name == 'pull_request' &&
|
||||
github.event.action == 'synchronize'
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
issues: write
|
||||
pull-requests: read
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Re-post FINAL Claude review when stale or missing
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ secrets.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
|
||||
const pr = context.payload.pull_request.number;
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
|
||||
const comments = await mergeGate.listAllComments(github, owner, repo, pr);
|
||||
const headPushedAt = (await mergeGate.getHeadCommitDate(github, owner, repo, pr))
|
||||
|| context.payload.pull_request.updated_at;
|
||||
|
||||
const hasFinal = mergeGate.hasFinalClaudeReviewTrigger(comments);
|
||||
const isStale = mergeGate.isStaleFinalAfterPush(comments, headPushedAt);
|
||||
|
||||
if (mergeGate.shouldSkipFinalRecovery(comments, headPushedAt)) {
|
||||
core.info('Recent @claude within 35min and FINAL not stale — skip recovery');
|
||||
return;
|
||||
}
|
||||
|
||||
const finalBody = mergeGate.FINAL_CLAUDE_REVIEW_BODY;
|
||||
|
||||
if (hasFinal && isStale) {
|
||||
await github.rest.issues.createComment({ issue_number: pr, owner, repo, body: finalBody });
|
||||
core.info(`Posted stale-FINAL recovery @claude on PR #${pr}`);
|
||||
return;
|
||||
}
|
||||
|
||||
if (hasFinal) {
|
||||
core.info('FINAL Claude review current on HEAD — skip recovery');
|
||||
return;
|
||||
}
|
||||
|
||||
const hasReviewerActivity = comments.some(c => {
|
||||
const login = c.user.login.toLowerCase();
|
||||
return login.includes('coderabbit') || login.includes('copilot') ||
|
||||
login.includes('greptile') || login.includes('qodo') || login.includes('gemini');
|
||||
});
|
||||
if (!hasReviewerActivity) {
|
||||
core.info('No bot reviewer activity yet, skipping recovery');
|
||||
return;
|
||||
}
|
||||
|
||||
await github.rest.issues.createComment({ issue_number: pr, owner, repo, body: finalBody });
|
||||
core.info(`Posted missing FINAL Claude review on PR #${pr}`);
|
||||
|
||||
# Scheduled: re-post @claude when FINAL is stale (Claude pushed after last FINAL trigger)
|
||||
stale-final-recovery-scheduled:
|
||||
if: github.event_name == 'schedule' || github.event_name == 'workflow_dispatch'
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
issues: write
|
||||
pull-requests: read
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Re-post stale FINAL @claude on open internal PRs
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ secrets.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
const prs = await github.paginate(github.rest.pulls.list, {
|
||||
owner, repo, state: 'open', per_page: 100,
|
||||
});
|
||||
let posted = 0;
|
||||
for (const pr of prs) {
|
||||
if (pr.draft) continue;
|
||||
if (pr.head?.repo?.full_name && pr.head.repo.full_name !== `${owner}/${repo}`) continue;
|
||||
const comments = await mergeGate.listAllComments(github, owner, repo, pr.number);
|
||||
const headPushedAt = (await mergeGate.getHeadCommitDate(github, owner, repo, pr.number)) || pr.updated_at;
|
||||
if (!mergeGate.needsStaleFinalRecovery(comments, headPushedAt)) continue;
|
||||
if (mergeGate.hasRecentClaudeTrigger(comments, 10)) {
|
||||
core.info(`PR #${pr.number}: stale FINAL but @claude within 10min — skip`);
|
||||
continue;
|
||||
}
|
||||
await github.rest.issues.createComment({
|
||||
issue_number: pr.number, owner, repo,
|
||||
body: mergeGate.FINAL_CLAUDE_REVIEW_BODY,
|
||||
});
|
||||
posted++;
|
||||
core.info(`Posted scheduled stale-FINAL recovery on PR #${pr.number}`);
|
||||
if (posted >= 5) break;
|
||||
}
|
||||
core.info(`Scheduled stale-FINAL recovery complete (${posted} posted)`);
|
||||
|
||||
# ================================================================
|
||||
# BOT PRs: CodeRabbit/Qodo skip bot-authored PRs by default.
|
||||
# Trigger them explicitly. Do NOT trigger Copilot here — it will
|
||||
@@ -612,16 +489,37 @@ jobs:
|
||||
permissions:
|
||||
pull-requests: write
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Trigger CodeRabbit and Qodo reviews
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ secrets.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
|
||||
const pr = context.payload.pull_request.number;
|
||||
await chain.kickReviewChain(github, context.repo.owner, context.repo.repo, pr, core);
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
|
||||
// 1. Trigger CodeRabbit review
|
||||
await github.rest.issues.createComment({
|
||||
issue_number: pr, owner, repo,
|
||||
body: '@coderabbitai review'
|
||||
});
|
||||
console.log(`Triggered CodeRabbit for bot PR #${pr}`);
|
||||
|
||||
// 2. Trigger Qodo review
|
||||
await github.rest.issues.createComment({
|
||||
issue_number: pr, owner, repo,
|
||||
body: '/review'
|
||||
});
|
||||
console.log(`Triggered Qodo for bot PR #${pr}`);
|
||||
|
||||
// 3. Trigger Gemini review (commented out)
|
||||
// await github.rest.issues.createComment({
|
||||
// issue_number: pr, owner, repo,
|
||||
// body: '@gemini review this PR'
|
||||
// });
|
||||
// console.log(`Triggered Gemini for bot PR #${pr}`);
|
||||
|
||||
// NOTE: @copilot is NOT triggered here.
|
||||
// It will be triggered by copilot-after-coderabbit or copilot-after-qodo
|
||||
// once those bots finish, ensuring Copilot always reviews LAST.
|
||||
console.log('Copilot will be triggered after CodeRabbit/Qodo complete.');
|
||||
@@ -1,43 +0,0 @@
|
||||
name: Bot PR Recovery
|
||||
|
||||
# Belt-and-braces: kick CodeRabbit/Qodo when pull_request:opened never fired for bot PRs.
|
||||
|
||||
on:
|
||||
schedule:
|
||||
- cron: '*/15 * * * *'
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
pr_number:
|
||||
description: 'Specific PR number to kick (optional)'
|
||||
required: false
|
||||
type: string
|
||||
|
||||
permissions:
|
||||
pull-requests: write
|
||||
issues: write
|
||||
|
||||
jobs:
|
||||
recover:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Find and kick stalled bot PRs
|
||||
uses: actions/github-script@v7
|
||||
env:
|
||||
PR_NUMBER_INPUT: ${{ github.event.inputs.pr_number }}
|
||||
with:
|
||||
github-token: ${{ secrets.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
const manual = (process.env.PR_NUMBER_INPUT || '').trim();
|
||||
const prNumber = manual ? parseInt(manual, 10) : null;
|
||||
if (manual && Number.isNaN(prNumber)) {
|
||||
throw new Error(`Invalid pr_number: ${manual}`);
|
||||
}
|
||||
await chain.recoverStalledBotPrs(github, owner, repo, { prNumber }, core);
|
||||
@@ -1,471 +0,0 @@
|
||||
name: Claude PR Merge Gate
|
||||
|
||||
# Read-only Claude assesses merge readiness; GH_TOKEN merges (no @claude, no gh pr review).
|
||||
# Does not overlap with merge-conflict-claude.yml or auto-pr-comment @claude chains.
|
||||
|
||||
on:
|
||||
schedule:
|
||||
- cron: '0 2,8,14,20 * * *'
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
pr_number:
|
||||
description: 'Optional PR number (scan all open internal PRs if empty)'
|
||||
required: false
|
||||
type: string
|
||||
merge_method:
|
||||
description: 'Merge method'
|
||||
required: false
|
||||
type: choice
|
||||
default: merge
|
||||
options:
|
||||
- merge
|
||||
- squash
|
||||
- rebase
|
||||
workflow_run:
|
||||
workflows:
|
||||
- Claude Assistant
|
||||
- Core Tests
|
||||
types:
|
||||
- completed
|
||||
repository_dispatch:
|
||||
types:
|
||||
- claude-merge-gate
|
||||
|
||||
concurrency:
|
||||
group: claude-merge-gate-${{ github.repository }}-${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || github.event.workflow_run.id || 'scan' }}
|
||||
cancel-in-progress: true
|
||||
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
|
||||
MAX_CANDIDATES: 5
|
||||
DISPATCH_PR_NUMBER: ${{ github.event.inputs.pr_number || github.event.client_payload.pr_number || '' }}
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
pull-requests: read
|
||||
issues: read
|
||||
actions: read
|
||||
|
||||
jobs:
|
||||
auto-dispatch:
|
||||
if: github.event_name == 'workflow_run'
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
pull-requests: read
|
||||
issues: read
|
||||
actions: write
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Dispatch merge gate when PR pipeline is ready
|
||||
uses: actions/github-script@v7
|
||||
env:
|
||||
PAT: ${{ secrets.GH_TOKEN }}
|
||||
with:
|
||||
github-token: ${{ secrets.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
|
||||
const wr = context.payload.workflow_run;
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
|
||||
if (!process.env.PAT) {
|
||||
core.setFailed('GH_TOKEN secret is required for merge gate auto-dispatch (needs repo + workflow scope).');
|
||||
return;
|
||||
}
|
||||
|
||||
if (wr.conclusion !== 'success') {
|
||||
core.info(`Skip dispatch: ${wr.name} conclusion=${wr.conclusion}`);
|
||||
return;
|
||||
}
|
||||
const allowed = ['Claude Assistant', 'Core Tests'];
|
||||
if (!allowed.includes(wr.name)) {
|
||||
core.info(`Skip dispatch: workflow ${wr.name}`);
|
||||
return;
|
||||
}
|
||||
|
||||
const prNumber = await mergeGate.resolvePrNumberFromWorkflowRun(github, owner, repo, wr);
|
||||
if (!prNumber) {
|
||||
core.info('Skip dispatch: could not resolve PR from workflow run');
|
||||
return;
|
||||
}
|
||||
|
||||
const fromClaude = wr.name === 'Claude Assistant';
|
||||
const check = await mergeGate.evaluatePipelineQuiescent(
|
||||
github, owner, repo, prNumber, core, {
|
||||
skipGlobalClaudeRunCheck: fromClaude,
|
||||
skipRecentClaudeCooldown: fromClaude,
|
||||
}
|
||||
);
|
||||
if (!check.ready) {
|
||||
core.info(`PR #${prNumber} not ready: ${check.reasons.join(', ')}`);
|
||||
return;
|
||||
}
|
||||
|
||||
await github.rest.repos.createDispatchEvent({
|
||||
owner,
|
||||
repo,
|
||||
event_type: 'claude-merge-gate',
|
||||
client_payload: { pr_number: prNumber },
|
||||
});
|
||||
core.info(`Dispatched merge gate for PR #${prNumber} after ${wr.name}`);
|
||||
|
||||
scan-candidates:
|
||||
if: github.event_name != 'workflow_run'
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
pull-requests: read
|
||||
issues: write
|
||||
actions: read
|
||||
outputs:
|
||||
matrix: ${{ steps.scan.outputs.matrix }}
|
||||
has_candidates: ${{ steps.scan.outputs.has_candidates }}
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Scan open PRs for merge gate eligibility
|
||||
id: scan
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ env.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
const maxCandidates = parseInt(process.env.MAX_CANDIDATES || '5', 10);
|
||||
const inputPr = String(process.env.DISPATCH_PR_NUMBER || '').trim();
|
||||
|
||||
const candidates = [];
|
||||
const skipped = [];
|
||||
|
||||
if (inputPr) {
|
||||
const n = parseInt(inputPr, 10);
|
||||
if (Number.isNaN(n)) {
|
||||
throw new Error(`Invalid pr_number input: ${inputPr}`);
|
||||
}
|
||||
const result = await mergeGate.evaluatePipelineQuiescent(github, owner, repo, n, core);
|
||||
if (result.ready) {
|
||||
candidates.push({ pr_number: n, head_sha: result.headSha });
|
||||
} else {
|
||||
skipped.push({ pr: n, reasons: result.reasons });
|
||||
}
|
||||
} else {
|
||||
const prs = await github.paginate(github.rest.pulls.list, {
|
||||
owner, repo, state: 'open', per_page: 100, sort: 'created', direction: 'asc',
|
||||
});
|
||||
const prNumbers = prs.map((p) => p.number);
|
||||
const selected = await mergeGate.selectMergeGateCandidates(
|
||||
github, owner, repo, prNumbers, maxCandidates, core
|
||||
);
|
||||
candidates.push(...selected.candidates);
|
||||
skipped.push(...selected.skipped);
|
||||
}
|
||||
|
||||
core.info('Skipped: ' + JSON.stringify(skipped));
|
||||
core.setOutput('matrix', JSON.stringify({ include: candidates }));
|
||||
core.setOutput('has_candidates', candidates.length > 0 ? 'true' : 'false');
|
||||
|
||||
core.summary.addRaw('## Merge gate scan\n');
|
||||
core.summary.addRaw(`Candidates: ${candidates.length}\n`);
|
||||
core.summary.addRaw('```json\n' + JSON.stringify({ candidates, skipped }, null, 2) + '\n```');
|
||||
await core.summary.write();
|
||||
|
||||
if (inputPr && skipped.length === 1 && skipped[0].pr === parseInt(inputPr, 10)) {
|
||||
const reasons = skipped[0].reasons;
|
||||
const body = [
|
||||
'**Merge gate scan** — not eligible for auto-merge.',
|
||||
'',
|
||||
...reasons.map((r) => `- \`${r}\``),
|
||||
'',
|
||||
'**Actions:** wait for CI and the Claude review chain, or add label `needs-manual-review` and merge manually.',
|
||||
'**Opt out:** label `no-auto-merge`.',
|
||||
].join('\n');
|
||||
await github.rest.issues.createComment({
|
||||
owner, repo, issue_number: skipped[0].pr, body,
|
||||
});
|
||||
} else if (inputPr && candidates.length === 1) {
|
||||
await github.rest.issues.createComment({
|
||||
owner, repo, issue_number: candidates[0].pr_number,
|
||||
body: '**Merge gate scan** — eligible for assessment. Claude merge gate will assess and may auto-merge if `MERGE_GATE_VERDICT: APPROVE`.',
|
||||
});
|
||||
}
|
||||
|
||||
claude-assess:
|
||||
needs: scan-candidates
|
||||
if: needs.scan-candidates.outputs.has_candidates == 'true'
|
||||
runs-on: ubuntu-latest
|
||||
timeout-minutes: 20
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix: ${{ fromJson(needs.scan-candidates.outputs.matrix) }}
|
||||
permissions:
|
||||
contents: read
|
||||
pull-requests: read
|
||||
issues: write
|
||||
actions: read
|
||||
id-token: write
|
||||
steps:
|
||||
- name: Generate GitHub App Token
|
||||
id: app-token
|
||||
uses: actions/create-github-app-token@v1
|
||||
with:
|
||||
app-id: ${{ secrets.CLAUDE_APP_ID }}
|
||||
private-key: ${{ secrets.CLAUDE_APP_PRIVATE_KEY }}
|
||||
owner: ${{ github.repository_owner }}
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
token: ${{ steps.app-token.outputs.token }}
|
||||
|
||||
- name: Mark merge gate active
|
||||
id: mark_active
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ env.GH_TOKEN }}
|
||||
script: |
|
||||
core.setOutput('started_at', new Date().toISOString());
|
||||
await github.rest.issues.addLabels({
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
issue_number: ${{ matrix.pr_number }},
|
||||
labels: ['claude-merge-gate-active'],
|
||||
});
|
||||
|
||||
- name: Stash merge gate helpers
|
||||
run: cp .github/scripts/merge-gate.js /tmp/merge-gate.js
|
||||
|
||||
- name: Fetch PR branch
|
||||
env:
|
||||
PR_NUMBER: ${{ matrix.pr_number }}
|
||||
run: |
|
||||
git fetch origin "pull/${PR_NUMBER}/head:pr-${PR_NUMBER}"
|
||||
git checkout "pr-${PR_NUMBER}"
|
||||
|
||||
- name: Claude merge gate assessment (read-only)
|
||||
id: assess
|
||||
continue-on-error: true
|
||||
uses: ./.github/actions/claude-code-action
|
||||
env:
|
||||
GH_TOKEN: ${{ steps.app-token.outputs.token }}
|
||||
CLAUDE_CODE_SUBAGENT_MODEL: inherit
|
||||
ANTHROPIC_DEFAULT_SONNET_MODEL: claude-sonnet-4-6
|
||||
with:
|
||||
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
|
||||
github_token: ${{ steps.app-token.outputs.token }}
|
||||
model: claude-opus-4-8
|
||||
trigger_phrase: '@claude-merge-gate-internal'
|
||||
direct_prompt: |
|
||||
You are the MERGE GATE reviewer for PraisonAI PR #${{ matrix.pr_number }}.
|
||||
READ-ONLY: do not modify code, commit, push, rebase, or create branches.
|
||||
|
||||
CRITICAL OUTPUT RULE:
|
||||
Post exactly one PR comment via GitHub MCP containing either:
|
||||
MERGE_GATE_VERDICT: APPROVE
|
||||
or
|
||||
MERGE_GATE_VERDICT: BLOCK
|
||||
followed by a short rationale on the next lines.
|
||||
|
||||
NEVER include @claude in any comment. NEVER mention merge conflict resolution.
|
||||
|
||||
Review checklist:
|
||||
1. Read AGENTS.md and the PR diff on the current branch.
|
||||
2. Read all PR comments and reviews (FINAL architecture reviewer / Lead Engineer must have run).
|
||||
3. Confirm SDK value gate: change strengthens praisonaiagents (no scope creep).
|
||||
4. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
|
||||
5. If agent.py adds >100 lines or new Agent __init__ params, respond MERGE_GATE_VERDICT: BLOCK (manual review required).
|
||||
6. BLOCK if labels security/breaking-change/needs-manual-review/release, sensitive paths (.github/workflows, auth, pyproject.toml), secrets in diff, PR >800 lines or >30 files, or SDK changes without tests. Label `merge-gate-ci-only` exempts CI-only changes under `.github/workflows/`, `.github/actions/`, or merge-gate scripts.
|
||||
7. Confirm no CHANGES_REQUESTED reviews and CI green on HEAD ${{ matrix.head_sha }}.
|
||||
8. If ready to merge: MERGE_GATE_VERDICT: APPROVE. Otherwise: MERGE_GATE_VERDICT: BLOCK with reasons.
|
||||
|
||||
Do not approve or merge via GitHub UI/API — only post the verdict comment.
|
||||
disallowed_tools: |
|
||||
Bash
|
||||
Edit
|
||||
Write
|
||||
Replace
|
||||
allowed_tools: |
|
||||
View
|
||||
GlobTool
|
||||
GrepTool
|
||||
Read
|
||||
timeout_minutes: 15
|
||||
|
||||
- name: Post fallback verdict if Claude did not comment
|
||||
id: fallback_verdict
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ env.GH_TOKEN }}
|
||||
script: |
|
||||
const mergeGate = require('/tmp/merge-gate.js');
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
const prNumber = ${{ matrix.pr_number }};
|
||||
|
||||
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
|
||||
const minCreatedAt = new Date(Date.now() - 25 * 60 * 1000).toISOString();
|
||||
const existing = mergeGate.findMergeGateVerdict(ctx.comments, minCreatedAt, ctx.headPushedAt);
|
||||
if (existing) {
|
||||
core.info(`Verdict already posted: ${existing}`);
|
||||
core.setOutput('verdict', existing);
|
||||
return;
|
||||
}
|
||||
|
||||
const check = await mergeGate.evaluatePipelineQuiescent(
|
||||
github, owner, repo, prNumber, core, { forMergeStep: true }
|
||||
);
|
||||
const verdict = check.ready ? 'APPROVE' : 'BLOCK';
|
||||
const lines = [
|
||||
`MERGE_GATE_VERDICT: ${verdict}`,
|
||||
'',
|
||||
'Automated fallback — Claude assess did not post a verdict comment (e.g. GitHub MCP unavailable).',
|
||||
];
|
||||
if (check.ready) {
|
||||
lines.push('All deterministic merge gates passed.');
|
||||
} else {
|
||||
lines.push('Blockers:', ...check.reasons.map((r) => `- ${r}`));
|
||||
}
|
||||
await github.rest.issues.createComment({
|
||||
owner, repo, issue_number: prNumber,
|
||||
body: lines.join('\n'),
|
||||
});
|
||||
core.info(`Posted fallback verdict: ${verdict}`);
|
||||
core.setOutput('verdict', verdict);
|
||||
|
||||
- name: Verify verdict posted
|
||||
id: verdict
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ env.GH_TOKEN }}
|
||||
script: |
|
||||
const mergeGate = require('/tmp/merge-gate.js');
|
||||
const comments = await mergeGate.listAllComments(
|
||||
github, context.repo.owner, context.repo.repo, ${{ matrix.pr_number }}
|
||||
);
|
||||
const ctx = await mergeGate.loadPrContext(
|
||||
github, context.repo.owner, context.repo.repo, ${{ matrix.pr_number }}
|
||||
);
|
||||
const minCreatedAt = new Date(Date.now() - 25 * 60 * 1000).toISOString();
|
||||
const verdict = mergeGate.findMergeGateVerdict(comments, minCreatedAt, ctx.headPushedAt);
|
||||
core.setOutput('verdict', verdict || 'NONE');
|
||||
if (!verdict) core.warning('No recent MERGE_GATE_VERDICT comment found after assessment');
|
||||
|
||||
- name: Remove merge gate active label
|
||||
if: always()
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ env.GH_TOKEN }}
|
||||
script: |
|
||||
const prNumber = ${{ matrix.pr_number }};
|
||||
try {
|
||||
await github.rest.issues.removeLabel({
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
issue_number: prNumber,
|
||||
name: 'claude-merge-gate-active',
|
||||
});
|
||||
core.info(`Removed claude-merge-gate-active from PR #${prNumber}`);
|
||||
} catch (e) {
|
||||
core.info(`Label claude-merge-gate-active already removed or missing on PR #${prNumber}`);
|
||||
}
|
||||
|
||||
- name: Fail job if assessment failed
|
||||
if: steps.assess.outcome == 'failure'
|
||||
run: exit 1
|
||||
|
||||
merge-only:
|
||||
needs: [scan-candidates, claude-assess]
|
||||
if: |
|
||||
always() &&
|
||||
needs.scan-candidates.outputs.has_candidates == 'true' &&
|
||||
needs.claude-assess.result == 'success'
|
||||
runs-on: ubuntu-latest
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix: ${{ fromJson(needs.scan-candidates.outputs.matrix) }}
|
||||
permissions:
|
||||
contents: write
|
||||
pull-requests: write
|
||||
issues: write
|
||||
actions: read
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Re-check gates and merge
|
||||
uses: actions/github-script@v7
|
||||
env:
|
||||
MERGE_METHOD: ${{ github.event.inputs.merge_method || 'merge' }}
|
||||
SCAN_HEAD_SHA: ${{ matrix.head_sha }}
|
||||
with:
|
||||
github-token: ${{ env.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const mergeGate = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/merge-gate.js'));
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
const prNumber = ${{ matrix.pr_number }};
|
||||
const scanHeadSha = process.env.SCAN_HEAD_SHA;
|
||||
|
||||
const removeLabels = async () => {
|
||||
try {
|
||||
await github.rest.issues.removeLabel({
|
||||
owner, repo, issue_number: prNumber, name: 'claude-merge-gate-active',
|
||||
});
|
||||
} catch (e) {
|
||||
core.info('Label claude-merge-gate-active already removed or missing');
|
||||
}
|
||||
};
|
||||
|
||||
try {
|
||||
const ctx = await mergeGate.loadPrContext(github, owner, repo, prNumber);
|
||||
const comments = ctx.comments;
|
||||
const verdictMin = new Date(Date.now() - 25 * 60 * 1000).toISOString();
|
||||
const verdict = mergeGate.findMergeGateVerdict(comments, verdictMin, ctx.headPushedAt);
|
||||
if (verdict !== 'APPROVE') {
|
||||
core.info(`Skip merge: verdict=${verdict || 'NONE'}`);
|
||||
await removeLabels();
|
||||
return;
|
||||
}
|
||||
|
||||
const check = await mergeGate.evaluatePipelineQuiescent(
|
||||
github, owner, repo, prNumber, core, { forMergeStep: true }
|
||||
);
|
||||
if (!check.ready) {
|
||||
core.info(`Skip merge: ${check.reasons.join(', ')}`);
|
||||
await removeLabels();
|
||||
return;
|
||||
}
|
||||
|
||||
if (check.headSha !== scanHeadSha) {
|
||||
core.info(`Skip merge: HEAD moved ${scanHeadSha.slice(0, 7)} → ${check.headSha.slice(0, 7)}`);
|
||||
await removeLabels();
|
||||
return;
|
||||
}
|
||||
|
||||
const method = process.env.MERGE_METHOD || 'merge';
|
||||
await github.rest.pulls.merge({
|
||||
owner, repo, pull_number: prNumber, merge_method: method,
|
||||
});
|
||||
|
||||
await github.rest.issues.addLabels({
|
||||
owner, repo, issue_number: prNumber, labels: ['auto-merged-by-gate'],
|
||||
});
|
||||
|
||||
await github.rest.issues.createComment({
|
||||
owner, repo, issue_number: prNumber,
|
||||
body: [
|
||||
'Merged by **Claude PR merge gate** (`claude-merge-gate.yml`).',
|
||||
`Verdict: MERGE_GATE_VERDICT: APPROVE`,
|
||||
`SHA: \`${check.headSha.slice(0, 7)}\``,
|
||||
`Method: ${method}`,
|
||||
].join('\n'),
|
||||
});
|
||||
|
||||
core.info(`Merged PR #${prNumber}`);
|
||||
} finally {
|
||||
await removeLabels();
|
||||
}
|
||||
+40
-100
@@ -123,8 +123,6 @@ jobs:
|
||||
github.event.action != 'opened' &&
|
||||
(github.event.action != 'labeled' || github.event.label.name == 'claude') &&
|
||||
(github.event_name != 'issue_comment' || contains(github.event.comment.body, '@claude')) &&
|
||||
(github.event_name != 'pull_request_review' || contains(github.event.review.body, '@claude')) &&
|
||||
(github.event_name != 'pull_request_review_comment' || contains(github.event.comment.body, '@claude')) &&
|
||||
(
|
||||
!contains(github.actor, '[bot]') ||
|
||||
github.actor == 'github-actions[bot]' ||
|
||||
@@ -153,67 +151,26 @@ jobs:
|
||||
id: check_fork
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ steps.app-token.outputs.token }}
|
||||
script: |
|
||||
const isPR = context.eventName === 'pull_request'
|
||||
|| context.eventName === 'pull_request_review'
|
||||
|| context.eventName === 'pull_request_review_comment'
|
||||
|| (context.payload.issue && context.payload.issue.pull_request);
|
||||
|
||||
if (!isPR) {
|
||||
core.setOutput('is_pr', 'false');
|
||||
core.setOutput('is_fork', 'false');
|
||||
core.setOutput('can_push_fork', 'false');
|
||||
return;
|
||||
}
|
||||
|
||||
const prNumber = context.payload.pull_request
|
||||
? context.payload.pull_request.number
|
||||
: context.payload.issue.number;
|
||||
const pr = await github.rest.pulls.get({
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
pull_number: prNumber
|
||||
});
|
||||
|
||||
let mergeState = '';
|
||||
try {
|
||||
const gql = await github.graphql(
|
||||
`query($owner: String!, $repo: String!, $number: Int!) {
|
||||
repository(owner: $owner, name: $repo) {
|
||||
pullRequest(number: $number) { mergeStateStatus }
|
||||
}
|
||||
}`,
|
||||
{ owner: context.repo.owner, repo: context.repo.repo, number: prNumber }
|
||||
);
|
||||
mergeState = (gql.repository.pullRequest.mergeStateStatus || '').toUpperCase();
|
||||
} catch (e) {
|
||||
core.warning(`GraphQL mergeStateStatus failed: ${e.message}`);
|
||||
}
|
||||
if (!mergeState) {
|
||||
mergeState = (pr.data.mergeable_state || pr.data.merge_state_status || '').toUpperCase();
|
||||
}
|
||||
|
||||
core.setOutput('is_pr', 'true');
|
||||
core.setOutput('pr_number', String(prNumber));
|
||||
core.setOutput('pr_branch', pr.data.head.ref);
|
||||
core.setOutput('head_repo', pr.data.head.repo.full_name);
|
||||
core.setOutput('merge_state', mergeState);
|
||||
|
||||
const baseRepo = `${context.repo.owner}/${context.repo.repo}`;
|
||||
const maintainerCanModify = pr.data.maintainer_can_modify === true;
|
||||
core.setOutput('maintainer_can_modify', String(maintainerCanModify));
|
||||
|
||||
if (pr.data.head.repo && pr.data.head.repo.full_name !== baseRepo) {
|
||||
core.setOutput('is_fork', 'true');
|
||||
core.setOutput('can_push_fork', String(maintainerCanModify));
|
||||
core.setOutput('fork_repo', pr.data.head.repo.full_name);
|
||||
core.setOutput('clone_url', pr.data.head.repo.clone_url);
|
||||
core.setOutput('branch', pr.data.head.ref);
|
||||
return;
|
||||
const isPR = context.eventName === 'pull_request' || (context.payload.issue && context.payload.issue.pull_request);
|
||||
if (isPR) {
|
||||
const prNumber = context.payload.pull_request ? context.payload.pull_request.number : context.payload.issue.number;
|
||||
const pr = await github.rest.pulls.get({
|
||||
owner: context.repo.owner,
|
||||
repo: context.repo.repo,
|
||||
pull_number: prNumber
|
||||
});
|
||||
|
||||
core.setOutput('pr_branch', pr.data.head.ref);
|
||||
|
||||
if (pr.data.head.repo && pr.data.head.repo.full_name !== context.repo.full_name) {
|
||||
core.setOutput('is_fork', 'true');
|
||||
core.setOutput('clone_url', pr.data.head.repo.clone_url);
|
||||
core.setOutput('branch', pr.data.head.ref);
|
||||
return;
|
||||
}
|
||||
}
|
||||
core.setOutput('is_fork', 'false');
|
||||
core.setOutput('can_push_fork', 'false');
|
||||
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v4
|
||||
@@ -223,40 +180,31 @@ jobs:
|
||||
token: ${{ steps.app-token.outputs.token }}
|
||||
|
||||
- name: Fetch PR branch and Setup Remote
|
||||
if: steps.check_fork.outputs.is_pr == 'true'
|
||||
if: github.event.issue.pull_request
|
||||
env:
|
||||
PR_BRANCH: ${{ steps.check_fork.outputs.pr_branch }}
|
||||
PR_NUMBER: ${{ steps.check_fork.outputs.pr_number }}
|
||||
IS_FORK: ${{ steps.check_fork.outputs.is_fork }}
|
||||
CAN_PUSH_FORK: ${{ steps.check_fork.outputs.can_push_fork }}
|
||||
FORK_REPO: ${{ steps.check_fork.outputs.fork_repo }}
|
||||
GH_TOKEN: ${{ secrets.GH_TOKEN }}
|
||||
run: |
|
||||
git fetch origin "pull/${PR_NUMBER}/head:${PR_BRANCH}"
|
||||
git checkout "${PR_BRANCH}"
|
||||
git fetch origin main
|
||||
|
||||
if [ "${IS_FORK}" = "true" ] && [ "${CAN_PUSH_FORK}" = "true" ]; then
|
||||
git remote set-url origin "https://x-access-token:${GH_TOKEN}@github.com/${FORK_REPO}.git"
|
||||
elif [ "${IS_FORK}" = "true" ]; then
|
||||
# Block push: trick claude-code-action's `git fetch origin <branch>`
|
||||
git remote set-url origin "file://$(pwd)"
|
||||
# Fetch PR head from base repo and put it into local branch
|
||||
git fetch origin pull/${{ github.event.issue.number }}/head:"${PR_BRANCH}"
|
||||
|
||||
# If it's a fork, make origin point to local to trick claude-code-action's `git fetch origin <branch>`
|
||||
if [ "${IS_FORK}" = "true" ]; then
|
||||
git remote set-url origin file://$(pwd)
|
||||
fi
|
||||
|
||||
- uses: anthropics/claude-code-action@beta
|
||||
env:
|
||||
GH_TOKEN: ${{ steps.check_fork.outputs.can_push_fork == 'true' && secrets.GH_TOKEN || steps.app-token.outputs.token }}
|
||||
GH_TOKEN: ${{ steps.app-token.outputs.token }}
|
||||
with:
|
||||
allowed_bots: 'praisonai-triage-agent[bot]'
|
||||
claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
|
||||
github_token: ${{ steps.app-token.outputs.token }}
|
||||
model: claude-opus-4-8
|
||||
trigger_phrase: "@claude"
|
||||
label_trigger: "claude"
|
||||
|
||||
direct_prompt: |
|
||||
${{ steps.check_fork.outputs.is_fork == 'true' && steps.check_fork.outputs.can_push_fork != 'true' && 'CRITICAL: THIS IS A PULL REQUEST FROM A FORK WITHOUT MAINTAINER EDITS. YOU DO NOT HAVE PUSH PERMISSIONS. ONLY READ FILES, VALIDATE CODE, AND PROVIDE COMMENTS/FEEDBACK ON THIS PR. DO NOT ATTEMPT TO PUSH OR CREATE PULL REQUESTS.\n\n' || (steps.check_fork.outputs.can_push_fork == 'true' && format('NOTE: Fork PR with maintainer edits allowed. Push directly to fork {0} branch {1}.\n\n', steps.check_fork.outputs.fork_repo, steps.check_fork.outputs.pr_branch) || (steps.check_fork.outputs.is_pr == 'true' && steps.check_fork.outputs.is_fork != 'true' && 'NOTE: The branch is under MervinPraison/PraisonAI (not a fork). You are able to make modifications and push directly to this branch.\n\n' || (steps.check_fork.outputs.is_pr != 'true' && 'NOTE: This is an issue (not a PR). Create a new fix branch per STEP 3 below.\n\n' || ''))) }}
|
||||
${{ steps.check_fork.outputs.is_pr == 'true' && format('CONTEXT: PR #{0} on branch {1}. head.repo={2}, is_fork={3}, can_push_fork={4}, merge_state={5}. NEVER treat cursor/*, claude/* branch names or bot authors as forks — only is_fork=true means fork.\n\n', steps.check_fork.outputs.pr_number, steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.head_repo, steps.check_fork.outputs.is_fork, steps.check_fork.outputs.can_push_fork, steps.check_fork.outputs.merge_state) || '' }}
|
||||
${{ steps.check_fork.outputs.is_fork == 'true' && 'CRITICAL: THIS IS A PULL REQUEST FROM A FORK. YOU DO NOT HAVE PUSH PERMISSIONS TO THIS REPOSITORY. ONLY READ FILES, VALIDATE CODE, AND PROVIDE YOUR COMMENTS/FEEDBACK DIRECTLY IN THIS PR VIA COMMENTS. DO NOT ATTEMPT TO PUSH OR CREATE PULL REQUESTS.\n\n' || 'NOTE: The branch is under MervinPraison/PraisonAI (not a fork). You are able to make modifications and push directly to this branch.\n\n' }}
|
||||
You are working on the PraisonAI SDK. Follow AGENTS.md strictly.
|
||||
|
||||
STEP 0 — SETUP GIT IDENTITY & AUTH (GLOBAL — required for all repos):
|
||||
@@ -279,16 +227,21 @@ jobs:
|
||||
5. Plugins (PraisonAI-Plugins): Framework lifecycle extensions replacing systemic behavior (e.g. tracing, logging, metrics, hooks, guardrails).
|
||||
For items routed to an EXTERNAL repository (Tools, Docs, Plugins), follow STEP 3-ALT below.
|
||||
- Does it duplicate existing functionality? Check if Agent already supports this via existing params (reflection, planning, tools, hooks, memory).
|
||||
- Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
|
||||
- Does it inherit from Agent properly? New agent types MUST inherit Agent, not wrap it with composition.
|
||||
- Does it add new dependencies? Only optional deps allowed, must be lazy-imported.
|
||||
- Will agent.py grow larger? If the change adds >50 lines to agent.py, find a way to extract instead. PRs with >100 lines added to agent.py require manual review (merge gate will not auto-merge).
|
||||
- Will agent.py grow larger? If the change adds >50 lines to agent.py, find a way to extract instead.
|
||||
- Is there a name collision with existing exports in __init__.py?
|
||||
If ANY of these conceptual checks fail (excluding routing), add a comment to the issue explaining why and close it. Do NOT create a PR.
|
||||
|
||||
${{ steps.check_fork.outputs.is_pr == 'true' && (steps.check_fork.outputs.is_fork != 'true' || steps.check_fork.outputs.can_push_fork == 'true') && steps.check_fork.outputs.merge_state == 'DIRTY' && format('STEP 3 — RESOLVE MERGE CONFLICTS ON PR (branch: {0}, PR #{1}{2}):\n- DO NOT create a new branch or PR\n- git fetch origin main && git rebase origin/main\n- Resolve conflicts: keep this PR intent, merge in main newer logic\n- git add -A && git rebase --continue (repeat until done)\n- git push --force-with-lease origin {0}\n- Run targeted pytest on changed paths\n- Comment files resolved and what you skipped\n', steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.pr_number, steps.check_fork.outputs.can_push_fork == 'true' && format(', fork: {0}', steps.check_fork.outputs.fork_repo) || '') || '' }}
|
||||
${{ steps.check_fork.outputs.is_pr == 'true' && (steps.check_fork.outputs.is_fork != 'true' || steps.check_fork.outputs.can_push_fork == 'true') && steps.check_fork.outputs.merge_state != 'DIRTY' && format('STEP 3 — IMPLEMENT ON EXISTING PR (branch: {0}, PR #{1}{2}):\n- DO NOT create a new branch or PR\n- git checkout {0}\n- Implement minimal, focused fixes from reviewer feedback\n- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper\n- Keep changes small and backward-compatible\n- Commit: git add -A && git commit -m "fix: <description>"\n- Push: git push origin {0}\n- Comment a summary of exact files modified and what you skipped\n', steps.check_fork.outputs.pr_branch, steps.check_fork.outputs.pr_number, steps.check_fork.outputs.can_push_fork == 'true' && format(', fork: {0}', steps.check_fork.outputs.fork_repo) || '') || '' }}
|
||||
${{ steps.check_fork.outputs.is_pr != 'true' && 'STEP 3 — IMPLEMENT (for changes in THIS repo — PraisonAI):\n- Create a fix branch: git checkout -b claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)\n- Implement a minimal, focused fix\n- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper\n- Keep changes small and backward-compatible\n- Commit: git add -A && git commit -m "fix: <description> (fixes #$ISSUE_NUMBER)"\n- Push: git push origin claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)\nCRITICAL: After pushing, you MUST immediately run: gh pr create --title "fix: <title>" --body "Fixes #$ISSUE_NUMBER" --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)\nDo NOT stop after pushing. Do NOT say "manually create a PR". Always create the PR automatically.\n' || '' }}
|
||||
STEP 3 — IMPLEMENT (for changes in THIS repo — PraisonAI):
|
||||
- Create a fix branch: git checkout -b claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
|
||||
- Implement a minimal, focused fix
|
||||
- Follow protocol-driven design: protocols in core SDK, heavy implementations in wrapper
|
||||
- Keep changes small and backward-compatible
|
||||
- Commit: git add -A && git commit -m "fix: <description> (fixes #$ISSUE_NUMBER)"
|
||||
- Push: git push origin claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
|
||||
CRITICAL: After pushing, you MUST immediately run: gh pr create --title "fix: <title>" --body "Fixes #$ISSUE_NUMBER" --head claude/issue-$ISSUE_NUMBER-$(date +%Y%m%d)
|
||||
Do NOT stop after pushing. Do NOT say "manually create a PR". Always create the PR automatically.
|
||||
|
||||
STEP 3-ALT — IMPLEMENT IN EXTERNAL REPO (for PraisonAI-Tools, PraisonAIDocs, PraisonAI-Plugins):
|
||||
When work must happen in a different repository, follow these steps EXACTLY. Do NOT attempt to use `cd`, as directory state is not preserved. Use `git -C` for all commands.
|
||||
@@ -314,7 +267,10 @@ jobs:
|
||||
- For docs changes: verify files exist and are valid markdown/MDX
|
||||
- Ensure no regressions
|
||||
|
||||
${{ steps.check_fork.outputs.is_pr == 'true' && 'STEP 5 — SKIP: Already on an open PR. Do NOT run gh pr create.\n' || 'STEP 5 — CREATE PR:\n- Commit with descriptive message, push, and create PR using `gh pr create`\n- For external repos, use `gh pr create -R MervinPraison/<REPO_NAME>`\nCRITICAL: You MUST create the PR automatically using `gh pr create`. Do NOT just provide a link or say "manual push required".\n' }}
|
||||
STEP 5 — CREATE PR:
|
||||
- Commit with descriptive message, push, and create PR using `gh pr create`
|
||||
- For external repos, use `gh pr create -R MervinPraison/<REPO_NAME>`
|
||||
CRITICAL: You MUST create the PR automatically using `gh pr create`. Do NOT just provide a link or say "manual push required".
|
||||
NOTE: If you worked on an external repo, the wrapper action will report "No commits" for the main repo at the end. This is expected, do not worry about it.
|
||||
allowed_tools: |
|
||||
Bash(git:*)
|
||||
@@ -336,19 +292,3 @@ jobs:
|
||||
mcp__github__get_issue_comments
|
||||
mcp__github__update_issue
|
||||
timeout_minutes: 30
|
||||
|
||||
- name: Kick review chain for bot-created PR
|
||||
if: |
|
||||
steps.check_fork.outputs.is_pr != 'true' &&
|
||||
(github.event_name == 'issues' || github.event_name == 'issue_comment') &&
|
||||
github.event.issue != null
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ secrets.GH_TOKEN }}
|
||||
script: |
|
||||
const path = require('path');
|
||||
const chain = require(path.join(process.env.GITHUB_WORKSPACE, '.github/scripts/bot-pr-review-chain.js'));
|
||||
const issueNumber = context.payload.issue.number;
|
||||
await chain.kickReviewChainForIssue(
|
||||
github, context.repo.owner, context.repo.repo, issueNumber, core
|
||||
);
|
||||
@@ -1,52 +0,0 @@
|
||||
name: Deploy install scripts to praison.ai
|
||||
|
||||
# When install.sh or install.ps1 change on main, trigger praison.ai CI which
|
||||
# syncs scripts at build time and deploys to Azure AKS (existing azure-pipeline.yaml).
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
paths:
|
||||
- 'src/praisonai/scripts/install.sh'
|
||||
- 'src/praisonai/scripts/install.ps1'
|
||||
workflow_dispatch:
|
||||
|
||||
concurrency:
|
||||
group: deploy-install-scripts
|
||||
cancel-in-progress: false
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
trigger-website-deploy:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Trigger praison.ai CI
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
|
||||
SOURCE_SHA: ${{ github.sha }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
if [ -z "${GH_TOKEN:-}" ]; then
|
||||
echo "SECRETS_ADMIN_PAT is not configured in this repository"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
gh workflow run CI \
|
||||
--repo MervinPraison/praison.ai \
|
||||
--ref master
|
||||
|
||||
echo "Triggered praison.ai CI for PraisonAI commit ${SOURCE_SHA}"
|
||||
echo "Monitor: https://github.com/MervinPraison/praison.ai/actions/workflows/azure-pipeline.yaml"
|
||||
|
||||
sleep 10
|
||||
RUN_URL=$(gh run list \
|
||||
--repo MervinPraison/praison.ai \
|
||||
--workflow CI \
|
||||
--limit 1 \
|
||||
--json url,status,createdAt \
|
||||
--jq '.[0].url' 2>/dev/null || true)
|
||||
if [ -n "${RUN_URL}" ]; then
|
||||
echo "Latest praison.ai CI run: ${RUN_URL}"
|
||||
fi
|
||||
@@ -22,6 +22,8 @@ jobs:
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
|
||||
@@ -36,6 +36,9 @@ jobs:
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
token: ${{ steps.generate_token.outputs.token }}
|
||||
|
||||
- name: Run Gemini Issue Triage
|
||||
|
||||
@@ -37,6 +37,9 @@ jobs:
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
token: ${{ steps.generate_token.outputs.token }}
|
||||
|
||||
- name: Set up Git
|
||||
|
||||
@@ -48,6 +48,9 @@ jobs:
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
token: ${{ steps.generate_token.outputs.token }}
|
||||
ref: ${{ steps.checkout_ref.outputs.ref }}
|
||||
fetch-depth: 0
|
||||
|
||||
@@ -60,16 +60,16 @@ jobs:
|
||||
- name: Run PraisonAI integration tests
|
||||
run: |
|
||||
cd PraisonAI/src/praisonai
|
||||
python -m pytest tests/integration/test_aiui_* -v
|
||||
python -m pytest tests/integration/test_aiui_* -v --timeout=300
|
||||
|
||||
- name: Run PraisonAIUI integration tests
|
||||
run: |
|
||||
cd PraisonAIUI
|
||||
if [ -f tests/integration/test_agentic_roundtrip.py ]; then
|
||||
python -m pytest tests/integration/test_agentic_roundtrip.py -v
|
||||
python -m pytest tests/integration/test_agentic_roundtrip.py -v --timeout=300
|
||||
fi
|
||||
if [ -f tests/test_feature_sdk_backends.py ]; then
|
||||
python -m pytest tests/test_feature_sdk_backends.py -v
|
||||
python -m pytest tests/test_feature_sdk_backends.py -v --timeout=300
|
||||
fi
|
||||
|
||||
- name: Test Pattern C CLI
|
||||
@@ -152,7 +152,7 @@ jobs:
|
||||
run: |
|
||||
cd PraisonAI/src/praisonai
|
||||
if [ -n "$OPENAI_API_KEY" ]; then
|
||||
python -m pytest tests/integration/test_aiui_host_agentic.py -v
|
||||
python -m pytest tests/integration/test_aiui_host_agentic.py -v --timeout=600
|
||||
else
|
||||
echo "OPENAI_API_KEY not available, skipping agentic tests"
|
||||
fi
|
||||
@@ -1,184 +0,0 @@
|
||||
name: Auto Merge Conflict → Claude
|
||||
|
||||
# Detects internal PRs with mergeStateStatus=DIRTY and posts @claude to trigger claude.yml.
|
||||
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
pull_request:
|
||||
types: [opened, synchronize, reopened]
|
||||
workflow_dispatch:
|
||||
schedule:
|
||||
- cron: '0 */6 * * *'
|
||||
|
||||
concurrency:
|
||||
group: merge-conflict-scan-${{ github.repository }}
|
||||
cancel-in-progress: true
|
||||
|
||||
env:
|
||||
# PAT posts as MervinPraison so issue_comment triggers claude.yml (GITHUB_TOKEN cannot chain workflows)
|
||||
GH_TOKEN: ${{ secrets.GH_TOKEN || github.token }}
|
||||
|
||||
permissions:
|
||||
pull-requests: write
|
||||
issues: write
|
||||
|
||||
jobs:
|
||||
detect-and-trigger:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Detect conflicting PRs and trigger Claude
|
||||
uses: actions/github-script@v7
|
||||
with:
|
||||
github-token: ${{ env.GH_TOKEN }}
|
||||
script: |
|
||||
const owner = context.repo.owner;
|
||||
const repo = context.repo.repo;
|
||||
const baseRepo = `${owner}/${repo}`;
|
||||
const COOLDOWN_MS = 12 * 60 * 60 * 1000;
|
||||
const AUTO_ACTORS = ['github-actions[bot]', 'MervinPraison'];
|
||||
const LABEL = 'claude-conflict-pending';
|
||||
const COMMENT_BODY = [
|
||||
'@claude this PR has merge conflicts with `main`.',
|
||||
'Please rebase onto latest `main`, resolve conflicts (keep this PR\'s intent, merge in newer main logic),',
|
||||
'run targeted tests, and force-push with `--force-with-lease`.',
|
||||
'Comment which files you resolved.',
|
||||
'Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.',
|
||||
].join(' ');
|
||||
|
||||
const sleep = (ms) => new Promise((r) => setTimeout(r, ms));
|
||||
|
||||
async function getMergeState(prNumber) {
|
||||
const query = `
|
||||
query($owner: String!, $repo: String!, $number: Int!) {
|
||||
repository(owner: $owner, name: $repo) {
|
||||
pullRequest(number: $number) {
|
||||
mergeStateStatus
|
||||
maintainerCanModify
|
||||
isDraft
|
||||
headRef { repository { nameWithOwner } }
|
||||
}
|
||||
}
|
||||
}
|
||||
`;
|
||||
for (let attempt = 0; attempt < 3; attempt++) {
|
||||
const result = await github.graphql(query, { owner, repo, number: prNumber });
|
||||
const prGql = result.repository.pullRequest;
|
||||
const status = (prGql?.mergeStateStatus || '').toUpperCase();
|
||||
if (status && status !== 'UNKNOWN') {
|
||||
return {
|
||||
status,
|
||||
isDraft: prGql.isDraft,
|
||||
headRepo: prGql.headRef?.repository?.nameWithOwner,
|
||||
maintainerCanModify: prGql.maintainerCanModify === true,
|
||||
};
|
||||
}
|
||||
if (attempt < 2) await sleep(10000);
|
||||
}
|
||||
const pr = await github.rest.pulls.get({ owner, repo, pull_number: prNumber });
|
||||
return {
|
||||
status: (pr.data.mergeable_state || '').toUpperCase(),
|
||||
isDraft: pr.data.draft,
|
||||
headRepo: pr.data.head.repo?.full_name,
|
||||
maintainerCanModify: pr.data.maintainer_can_modify === true,
|
||||
};
|
||||
}
|
||||
|
||||
function hasFinalClaudeReviewTrigger(comments) {
|
||||
return comments.some((c) => {
|
||||
const body = (c.body || '').toLowerCase();
|
||||
if (!AUTO_ACTORS.includes(c.user.login)) return false;
|
||||
if (!body.includes('@claude')) return false;
|
||||
if (body.includes('merge conflict')) return false;
|
||||
return body.includes('final architecture reviewer') || body.includes('lead engineer');
|
||||
});
|
||||
}
|
||||
|
||||
function hasRecentAutoComment(comments) {
|
||||
const cutoff = Date.now() - COOLDOWN_MS;
|
||||
return comments.some((c) => {
|
||||
if (!AUTO_ACTORS.includes(c.user.login)) return false;
|
||||
const body = (c.body || '').toLowerCase();
|
||||
if (!body.includes('@claude') || !body.includes('merge conflict')) return false;
|
||||
return new Date(c.created_at).getTime() > cutoff;
|
||||
});
|
||||
}
|
||||
|
||||
async function processPR(prNumber) {
|
||||
const { status, isDraft, headRepo, maintainerCanModify } = await getMergeState(prNumber);
|
||||
core.info(`PR #${prNumber}: mergeState=${status}, head=${headRepo}, draft=${isDraft}, maintainerCanModify=${maintainerCanModify}`);
|
||||
|
||||
const { data: issue } = await github.rest.issues.get({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: prNumber,
|
||||
});
|
||||
const labels = issue.labels.map((l) => l.name);
|
||||
|
||||
if (status !== 'DIRTY' && labels.includes(LABEL)) {
|
||||
await github.rest.issues.removeLabel({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: prNumber,
|
||||
name: LABEL,
|
||||
});
|
||||
core.info(`Removed ${LABEL} from PR #${prNumber}`);
|
||||
}
|
||||
|
||||
if (status !== 'DIRTY') return { skipped: true, reason: 'not dirty' };
|
||||
if (isDraft) return { skipped: true, reason: 'draft' };
|
||||
if (headRepo && headRepo !== baseRepo && !maintainerCanModify) {
|
||||
return { skipped: true, reason: 'fork without maintainer edits' };
|
||||
}
|
||||
if (labels.includes(LABEL)) {
|
||||
return { skipped: true, reason: 'conflict resolution pending' };
|
||||
}
|
||||
|
||||
const { data: comments } = await github.rest.issues.listComments({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: prNumber,
|
||||
per_page: 100,
|
||||
});
|
||||
if (hasRecentAutoComment(comments)) {
|
||||
return { skipped: true, reason: 'recent auto comment' };
|
||||
}
|
||||
|
||||
if (!hasFinalClaudeReviewTrigger(comments)) {
|
||||
return { skipped: true, reason: 'awaiting final claude review trigger' };
|
||||
}
|
||||
|
||||
await github.rest.issues.addLabels({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: prNumber,
|
||||
labels: [LABEL],
|
||||
});
|
||||
await github.rest.issues.createComment({
|
||||
owner,
|
||||
repo,
|
||||
issue_number: prNumber,
|
||||
body: COMMENT_BODY,
|
||||
});
|
||||
return { triggered: true };
|
||||
}
|
||||
|
||||
let prNumbers = [];
|
||||
if (context.eventName === 'pull_request') {
|
||||
prNumbers = [context.payload.pull_request.number];
|
||||
} else {
|
||||
const prs = await github.paginate(github.rest.pulls.list, {
|
||||
owner,
|
||||
repo,
|
||||
state: 'open',
|
||||
per_page: 100,
|
||||
});
|
||||
prNumbers = prs.map((p) => p.number);
|
||||
}
|
||||
|
||||
const results = [];
|
||||
for (const num of prNumbers) {
|
||||
results.push({ pr: num, ...(await processPR(num)) });
|
||||
}
|
||||
core.summary.addRaw('```json\n' + JSON.stringify(results, null, 2) + '\n```');
|
||||
await core.summary.write();
|
||||
@@ -1,126 +0,0 @@
|
||||
name: Nightly Release Gate
|
||||
|
||||
# Preflight checks before dispatching PyPI Release (patch bump).
|
||||
# Runs nightly at 00:00 UTC (midnight).
|
||||
|
||||
on:
|
||||
schedule:
|
||||
- cron: '0 0 * * *'
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
dry_run:
|
||||
description: 'Run preflight only; do not dispatch pypi-release.yml'
|
||||
required: false
|
||||
default: false
|
||||
type: boolean
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
actions: write
|
||||
|
||||
concurrency:
|
||||
group: nightly-release-gate
|
||||
cancel-in-progress: false
|
||||
|
||||
jobs:
|
||||
preflight:
|
||||
if: github.ref == 'refs/heads/main' || github.event_name == 'workflow_dispatch'
|
||||
runs-on: ubuntu-latest
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.GH_TOKEN }}
|
||||
steps:
|
||||
- name: Checkout main
|
||||
uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4
|
||||
with:
|
||||
ref: main
|
||||
fetch-depth: 0
|
||||
|
||||
- name: Preflight — path changes and CI green
|
||||
id: preflight
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
git fetch --tags origin
|
||||
|
||||
LAST_TAG=$(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" >> "$GITHUB_OUTPUT"
|
||||
exit 0
|
||||
fi
|
||||
|
||||
CHANGED=$(git diff --name-only "${LAST_TAG}" HEAD -- \
|
||||
src/praisonai \
|
||||
src/praisonai-agents || true)
|
||||
|
||||
if [ -z "$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}" >> "$GITHUB_OUTPUT"
|
||||
|
||||
- name: Dry run summary
|
||||
if: inputs.dry_run == true
|
||||
run: |
|
||||
echo "Dry run — preflight only, no pypi-release dispatch."
|
||||
echo "should_release=${{ 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
|
||||
run: |
|
||||
set -euo pipefail
|
||||
gh workflow run pypi-release.yml \
|
||||
--repo "${GITHUB_REPOSITORY}" \
|
||||
--ref main \
|
||||
-f bump=patch \
|
||||
-f source=nightly \
|
||||
-f dry_run=false
|
||||
echo "Dispatched pypi-release.yml (patch, source=nightly)"
|
||||
echo "Approve the pypi environment when prompted."
|
||||
@@ -1,305 +0,0 @@
|
||||
name: PyPI Release
|
||||
|
||||
# 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 both packages'
|
||||
required: true
|
||||
default: patch
|
||||
type: choice
|
||||
options:
|
||||
- patch
|
||||
- minor
|
||||
- major
|
||||
dry_run:
|
||||
description: 'Preview versions and steps without publishing or pushing'
|
||||
required: false
|
||||
default: false
|
||||
type: boolean
|
||||
skip_agents:
|
||||
description: 'Skip agents publish (recovery if already on PyPI)'
|
||||
required: false
|
||||
default: false
|
||||
type: boolean
|
||||
skip_wrapper:
|
||||
description: 'Publish agents only'
|
||||
required: false
|
||||
default: false
|
||||
type: boolean
|
||||
agents_version:
|
||||
description: 'Override agents version (empty = auto bump from pyproject.toml)'
|
||||
required: false
|
||||
default: ''
|
||||
type: string
|
||||
wrapper_version:
|
||||
description: 'Override wrapper version (empty = auto bump from version.py)'
|
||||
required: false
|
||||
default: ''
|
||||
type: string
|
||||
source:
|
||||
description: 'Trigger source (audit trail)'
|
||||
required: false
|
||||
default: manual
|
||||
type: choice
|
||||
options:
|
||||
- manual
|
||||
- nightly
|
||||
|
||||
permissions:
|
||||
contents: write
|
||||
|
||||
concurrency:
|
||||
group: pypi-release
|
||||
cancel-in-progress: false
|
||||
|
||||
jobs:
|
||||
release:
|
||||
if: github.ref == 'refs/heads/main'
|
||||
runs-on: ubuntu-latest
|
||||
environment: pypi
|
||||
env:
|
||||
UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN || secrets.PYPI_API_TOKEN }}
|
||||
GH_TOKEN: ${{ secrets.GH_TOKEN }}
|
||||
steps:
|
||||
- name: Checkout main
|
||||
uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4
|
||||
with:
|
||||
ref: main
|
||||
fetch-depth: 0
|
||||
token: ${{ secrets.GH_TOKEN }}
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
|
||||
- name: Set up uv
|
||||
uses: astral-sh/setup-uv@38f3f104447c67c051c4a08e39b64a148898af3a # v4
|
||||
|
||||
- name: Configure git
|
||||
run: |
|
||||
git config user.name "MervinPraison"
|
||||
git config user.email "[email protected]"
|
||||
gh auth setup-git
|
||||
|
||||
- name: Release summary
|
||||
run: |
|
||||
echo "Source: ${{ inputs.source }}"
|
||||
echo "Bump: ${{ inputs.bump }}"
|
||||
echo "Dry run: ${{ inputs.dry_run }}"
|
||||
|
||||
- name: Compute release versions
|
||||
id: versions
|
||||
env:
|
||||
BUMP: ${{ inputs.bump }}
|
||||
AGENTS_OVERRIDE: ${{ inputs.agents_version }}
|
||||
WRAPPER_OVERRIDE: ${{ inputs.wrapper_version }}
|
||||
SKIP_AGENTS: ${{ inputs.skip_agents }}
|
||||
run: |
|
||||
python <<'PY'
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
SEMVER = re.compile(r"^\d+\.\d+\.\d+$")
|
||||
root = Path(".")
|
||||
bump = os.environ["BUMP"]
|
||||
|
||||
def bump_version(version: str) -> str:
|
||||
parts = version.split(".")
|
||||
if len(parts) != 3:
|
||||
print(f"Invalid version: {version}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
maj, min_, patch = (int(parts[0]), int(parts[1]), int(parts[2]))
|
||||
if bump == "major":
|
||||
return f"{maj + 1}.0.0"
|
||||
if bump == "minor":
|
||||
return f"{maj}.{min_ + 1}.0"
|
||||
return f"{maj}.{min_}.{patch + 1}"
|
||||
|
||||
def validate_version(label: str, value: str) -> None:
|
||||
if value and not SEMVER.match(value):
|
||||
print(f"Invalid {label} override: {value!r} (expected X.Y.Z)", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
agents_override = os.environ.get("AGENTS_OVERRIDE", "").strip()
|
||||
wrapper_override = os.environ.get("WRAPPER_OVERRIDE", "").strip()
|
||||
validate_version("agents_version", agents_override)
|
||||
validate_version("wrapper_version", wrapper_override)
|
||||
|
||||
agents_pyproject = root / "src/praisonai-agents/pyproject.toml"
|
||||
agents_content = agents_pyproject.read_text()
|
||||
agents_match = re.search(r'^version\s*=\s*"([^"]+)"', agents_content, re.MULTILINE)
|
||||
if not agents_match:
|
||||
print("Could not read agents version from pyproject.toml", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
current_agents = agents_match.group(1)
|
||||
if not SEMVER.match(current_agents):
|
||||
print(f"Invalid current agents version: {current_agents}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
wrapper_version_py = root / "src/praisonai/praisonai/version.py"
|
||||
wrapper_content = wrapper_version_py.read_text()
|
||||
wrapper_match = re.search(r'__version__ = "([^"]+)"', wrapper_content)
|
||||
if not wrapper_match:
|
||||
print("Could not read wrapper version from version.py", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
current_wrapper = wrapper_match.group(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"
|
||||
|
||||
if agents_override:
|
||||
agents_version = agents_override
|
||||
elif skip_agents:
|
||||
agents_version = current_agents
|
||||
else:
|
||||
agents_version = bump_version(current_agents)
|
||||
|
||||
if wrapper_override:
|
||||
wrapper_version = wrapper_override
|
||||
else:
|
||||
wrapper_version = bump_version(current_wrapper)
|
||||
|
||||
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"wrapper_version={wrapper_version}\n")
|
||||
fh.write(f"current_agents={current_agents}\n")
|
||||
fh.write(f"current_wrapper={current_wrapper}\n")
|
||||
|
||||
print(f"Agents: {current_agents} -> {agents_version}")
|
||||
print(f"Wrapper: {current_wrapper} -> {wrapper_version}")
|
||||
PY
|
||||
|
||||
- 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 "Wrapper version: ${{ steps.versions.outputs.wrapper_version }}"
|
||||
echo ""
|
||||
if [ "${{ inputs.skip_agents }}" != "true" ]; then
|
||||
echo "Would publish praisonaiagents ${{ steps.versions.outputs.agents_version }}"
|
||||
echo "Would commit src/praisonai-agents/pyproject.toml and uv.lock"
|
||||
fi
|
||||
if [ "${{ inputs.skip_wrapper }}" != "true" ]; then
|
||||
echo "Would run bump_and_release.py ${{ steps.versions.outputs.wrapper_version }} --agents ${{ steps.versions.outputs.agents_version }}"
|
||||
echo "Would uv publish praisonai ${{ steps.versions.outputs.wrapper_version }}"
|
||||
fi
|
||||
|
||||
- name: Publish praisonaiagents
|
||||
if: inputs.dry_run != true && inputs.skip_agents != true
|
||||
working-directory: src/praisonai-agents
|
||||
env:
|
||||
NEW_VERSION: ${{ steps.versions.outputs.agents_version }}
|
||||
CURRENT: ${{ steps.versions.outputs.current_agents }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
python <<'PY'
|
||||
import os
|
||||
from pathlib import Path
|
||||
path = Path("pyproject.toml")
|
||||
content = path.read_text()
|
||||
current = os.environ["CURRENT"]
|
||||
new = os.environ["NEW_VERSION"]
|
||||
path.write_text(content.replace(f'version = "{current}"', f'version = "{new}"', 1))
|
||||
PY
|
||||
|
||||
rm -rf dist
|
||||
uv lock
|
||||
uv build
|
||||
uv publish
|
||||
|
||||
- name: Wait for praisonaiagents on PyPI
|
||||
if: inputs.dry_run != true && inputs.skip_agents != true
|
||||
run: |
|
||||
set -euo pipefail
|
||||
PACKAGE="praisonaiagents"
|
||||
VERSION="${{ steps.versions.outputs.agents_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 agents version bump
|
||||
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
|
||||
git diff --cached --quiet && { echo "No agents files to commit"; exit 0; }
|
||||
git commit -m "Bump praisonaiagents to ${{ steps.versions.outputs.agents_version }}"
|
||||
git pull --rebase origin main
|
||||
git push origin main
|
||||
|
||||
- name: Bump and release wrapper
|
||||
if: inputs.dry_run != true && inputs.skip_wrapper != true
|
||||
run: |
|
||||
set -euo pipefail
|
||||
python src/praisonai/scripts/bump_and_release.py "${{ steps.versions.outputs.wrapper_version }}" \
|
||||
--agents "${{ steps.versions.outputs.agents_version }}" \
|
||||
--wait --max-wait 600 --no-add-all
|
||||
|
||||
- name: Publish praisonai wrapper to PyPI
|
||||
if: inputs.dry_run != true && inputs.skip_wrapper != true
|
||||
working-directory: src/praisonai
|
||||
run: uv publish
|
||||
|
||||
- name: Wait for praisonai on PyPI
|
||||
if: inputs.dry_run != true && inputs.skip_wrapper != true
|
||||
run: |
|
||||
set -euo pipefail
|
||||
PACKAGE="praisonai"
|
||||
VERSION="${{ steps.versions.outputs.wrapper_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: Verify PyPI versions
|
||||
if: inputs.dry_run != true
|
||||
run: |
|
||||
set -euo pipefail
|
||||
AGENTS="${{ steps.versions.outputs.agents_version }}"
|
||||
WRAPPER="${{ steps.versions.outputs.wrapper_version }}"
|
||||
|
||||
if [ "${{ inputs.skip_agents }}" != "true" ]; then
|
||||
echo "✅ praisonaiagents==${AGENTS}"
|
||||
fi
|
||||
|
||||
if [ "${{ inputs.skip_wrapper }}" != "true" ]; then
|
||||
echo "✅ praisonai==${WRAPPER}"
|
||||
fi
|
||||
@@ -15,8 +15,8 @@ jobs:
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
|
||||
@@ -8,18 +8,15 @@
|
||||
|
||||
name: Upload Python Package
|
||||
|
||||
# Superseded by pypi-release.yml (manual workflow_dispatch with uv publish).
|
||||
# Kept as workflow_dispatch-only fallback; release trigger removed to avoid
|
||||
# duplicate PyPI publish when bump_and_release creates a GitHub release.
|
||||
on:
|
||||
workflow_dispatch:
|
||||
release:
|
||||
types: [published]
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
deploy:
|
||||
if: false
|
||||
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
|
||||
@@ -26,8 +26,11 @@ jobs:
|
||||
# First checkout the upstream repo at the specified tag
|
||||
- name: Checkout upstream repo
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
repository: MervinPraison/PraisonAI
|
||||
ref: ${{ github.event.inputs.tag }}
|
||||
fetch-depth: 0
|
||||
@@ -45,8 +48,11 @@ jobs:
|
||||
# Now checkout the fork at main branch
|
||||
- name: Checkout fork
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
repository: ${{ github.event.inputs.fork_owner }}/PraisonAI
|
||||
ref: main
|
||||
fetch-depth: 0
|
||||
@@ -443,8 +449,11 @@ jobs:
|
||||
# First checkout the fork's main branch
|
||||
- name: Checkout fork repo
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
fetch-depth: 0
|
||||
token: ${{ secrets.PAT_TOKEN }}
|
||||
repository: ${{ github.event.inputs.fork_owner }}/PraisonAI
|
||||
|
||||
@@ -1,31 +0,0 @@
|
||||
name: Sync Claude Secrets to PraisonAIUI
|
||||
|
||||
on:
|
||||
workflow_dispatch:
|
||||
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
jobs:
|
||||
sync:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Sync secrets to PraisonAIUI
|
||||
env:
|
||||
GH_TOKEN: ${{ secrets.SECRETS_ADMIN_PAT }}
|
||||
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 }}
|
||||
GH_TOKEN_VALUE: ${{ secrets.GH_TOKEN }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
if [ -z "${GH_TOKEN:-}" ]; then
|
||||
echo "SECRETS_ADMIN_PAT is not configured in this repository"
|
||||
exit 1
|
||||
fi
|
||||
echo -n "$CLAUDE_APP_ID" | gh secret set CLAUDE_APP_ID --repo "$TARGET"
|
||||
echo -n "$CLAUDE_APP_PRIVATE_KEY" | gh secret set CLAUDE_APP_PRIVATE_KEY --repo "$TARGET"
|
||||
echo -n "$CLAUDE_CODE_OAUTH_TOKEN" | gh secret set CLAUDE_CODE_OAUTH_TOKEN --repo "$TARGET"
|
||||
echo -n "$GH_TOKEN_VALUE" | gh secret set GH_TOKEN --repo "$TARGET"
|
||||
echo "Synced CLAUDE_APP_ID, CLAUDE_APP_PRIVATE_KEY, CLAUDE_CODE_OAUTH_TOKEN, GH_TOKEN → $TARGET"
|
||||
@@ -37,8 +37,10 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
|
||||
@@ -22,8 +22,8 @@ jobs:
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
- name: Set up Python 3.11
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
|
||||
@@ -13,8 +13,10 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
@@ -79,8 +81,10 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
|
||||
@@ -33,8 +33,10 @@ jobs:
|
||||
steps:
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
|
||||
@@ -45,8 +45,8 @@ jobs:
|
||||
timeout-minutes: 5
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
- name: Set up Python 3.11
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
@@ -105,8 +105,8 @@ jobs:
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
@@ -187,8 +187,8 @@ jobs:
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
@@ -259,8 +259,8 @@ jobs:
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
@@ -318,8 +318,8 @@ jobs:
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
@@ -377,8 +377,8 @@ jobs:
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
@@ -436,8 +436,8 @@ jobs:
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
@@ -495,8 +495,8 @@ jobs:
|
||||
fi
|
||||
|
||||
- uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
if: steps.check-key.outputs.has_key == 'true'
|
||||
|
||||
- name: Set up Python 3.11
|
||||
|
||||
@@ -45,8 +45,10 @@ jobs:
|
||||
|
||||
- name: Checkout code
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
with:
|
||||
persist-credentials: false
|
||||
|
||||
- name: Set up Python ${{ matrix.python-version }}
|
||||
uses: actions/setup-python@v5
|
||||
|
||||
@@ -88,9 +88,6 @@ issue_details.json
|
||||
.internal
|
||||
.praisonai
|
||||
|
||||
# Backup files
|
||||
*.bak
|
||||
|
||||
# Rust / Cargo
|
||||
target/
|
||||
Cargo.lock
|
||||
|
||||
@@ -1,10 +0,0 @@
|
||||
# Agent Instructions
|
||||
|
||||
You are working on the PraisonAI project.
|
||||
|
||||
## Project Guidelines
|
||||
- Follow the existing code style and conventions
|
||||
- Be concise and helpful in responses
|
||||
- Test implementation thoroughly
|
||||
- Ensure backward compatibility with existing APIs
|
||||
- Follow protocol-driven design: core protocols in praisonaiagents/, heavy implementations in praisonai/
|
||||
-437
@@ -1,437 +0,0 @@
|
||||
# PraisonAI Architecture
|
||||
|
||||
> **Last updated:** 2026-06-24
|
||||
>
|
||||
> Strategic architecture document for PraisonAI — a multi-agent AI framework.
|
||||
> 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. [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)
|
||||
|
||||
---
|
||||
|
||||
## 1. Executive Summary
|
||||
|
||||
PraisonAI is a multi-agent AI framework with broad capability surface across
|
||||
Python, TypeScript, and Rust SDKs. The framework's core strength is its
|
||||
feature breadth — agent abstractions, integrations, workflows, and active
|
||||
release cadence.
|
||||
|
||||
The strategic bet for the next two quarters is building a **Reliability +
|
||||
Orchestration + Observability** core to unlock adoption and trust:
|
||||
|
||||
| Dimension | Current State | Target |
|
||||
|-----------|--------------|--------|
|
||||
| Reliability | Cross-platform mismatches, optional dep fragility | Deterministic gating, adapter abstraction, parity CI |
|
||||
| Determinism | Flaky tests, global state collisions | Isolated test fixtures, traceable tenant IDs |
|
||||
| Developer UX | Complex onboarding, implicit config | Golden-path CLI, Doctor Auto-Fix |
|
||||
| Observability | Minimal runtime tracing | Structured event bus, replay engine, failure classifier |
|
||||
|
||||
### Design Principles
|
||||
|
||||
- **Deterministic by default**, flexible by opt-in
|
||||
- **Policy-enforced execution boundaries** at every layer
|
||||
- **Structured events** for all lifecycle transitions
|
||||
- **Capability isolation** per agent and per tool
|
||||
|
||||
---
|
||||
|
||||
## 2. System Overview
|
||||
|
||||
```
|
||||
User/SDK/CLI
|
||||
→ Workflow Compiler (graph + policy + schemas)
|
||||
→ Execution Orchestrator (state machine, retries, fallbacks)
|
||||
→ Tool Runtime (sandbox + approval + capability scope)
|
||||
→ Model Runtime (provider abstraction + rate/timeout policy)
|
||||
→ Observability Bus (trace events + metrics + cost)
|
||||
→ Replay Engine (checkpoint + deterministic re-run)
|
||||
→ Persistence (session, memory, artifacts, run ledger)
|
||||
```
|
||||
|
||||
### Runtime Components
|
||||
|
||||
| Component | Responsibility | Interface |
|
||||
|-----------|---------------|-----------|
|
||||
| API/CLI Gateway | Accepts run requests, validates config/profile | `RunRequest`, `RunProfile` |
|
||||
| Workflow Compiler | Converts YAML/DSL to normalized execution graph | `CompiledGraph` |
|
||||
| Orchestrator | Executes graph state machine with retries/fallbacks | `ExecutionState`, `StepTransition` |
|
||||
| Tool Runtime | Runs tools with approval/sandbox policies | `ToolCall`, `ToolResult` |
|
||||
| Model Runtime | Provider routing, timeout, budget control | `ModelRequest`, `ModelResponse` |
|
||||
| Observability Bus | Streams structured events + metrics | `RunEvent` schema |
|
||||
| Replay Engine | Restarts from checkpoint with deterministic inputs | `ReplayRequest` |
|
||||
|
||||
### Existing Architecture (Python SDK)
|
||||
|
||||
The Python SDK is the primary runtime and is organised as follows:
|
||||
|
||||
- `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 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/`)
|
||||
|
||||
---
|
||||
|
||||
## 3. Layered Architecture
|
||||
|
||||
```mermaid
|
||||
flowchart TB
|
||||
subgraph UX["Interface Layer"]
|
||||
CLI[CLI]
|
||||
SDK[SDK]
|
||||
API[API Gateway]
|
||||
end
|
||||
|
||||
subgraph Control["Control Plane"]
|
||||
Compiler[Workflow Compiler]
|
||||
Policy[Policy Engine]
|
||||
Orchestrator[Execution Orchestrator]
|
||||
end
|
||||
|
||||
subgraph Runtime["Runtime Plane"]
|
||||
ModelRT[Model Runtime]
|
||||
ToolRT[Tool Runtime]
|
||||
MemoryRT[Memory Runtime]
|
||||
end
|
||||
|
||||
subgraph Observe["Observability Plane"]
|
||||
EventBus[Run Event Bus]
|
||||
Metrics[Metrics + Cost]
|
||||
Replay[Replay Engine]
|
||||
end
|
||||
|
||||
subgraph Data["Data Plane"]
|
||||
Ledger[Run Ledger]
|
||||
Checkpoints[Checkpoints]
|
||||
Artifacts[Artifacts Store]
|
||||
end
|
||||
|
||||
CLI --> API
|
||||
SDK --> API
|
||||
API --> Compiler
|
||||
API --> Policy
|
||||
Compiler --> Orchestrator
|
||||
Policy --> Orchestrator
|
||||
Orchestrator --> ModelRT
|
||||
Orchestrator --> ToolRT
|
||||
Orchestrator --> MemoryRT
|
||||
Orchestrator --> EventBus
|
||||
EventBus --> Metrics
|
||||
EventBus --> Replay
|
||||
Orchestrator --> Ledger
|
||||
Orchestrator --> Checkpoints
|
||||
ToolRT --> Artifacts
|
||||
Replay --> Checkpoints
|
||||
```
|
||||
|
||||
### Interface Layer
|
||||
|
||||
- **CLI** — The `praisonai` command-line entry point
|
||||
- **SDK** — Python library API (`from praisonai import Agent`)
|
||||
- **API Gateway** — HTTP/WebSocket REST API (`praisonai api` or `a2a`/`a2ui`)
|
||||
|
||||
### Control Plane
|
||||
|
||||
- **Workflow Compiler** — Converts YAML workflows and SDK-defined graphs into
|
||||
a normalized `CompiledGraph` with adjacency validation and cycle detection.
|
||||
- **Policy Engine** — Enforces runtime policies (budget, timeout, approval
|
||||
gates, capability validation) before and during execution.
|
||||
- **Execution Orchestrator** — Drives the state machine through graph nodes,
|
||||
handling retry, fallback, and failure classification.
|
||||
|
||||
### Runtime Plane
|
||||
|
||||
- **Model Runtime** — Provider abstraction layer. Routes to OpenAI, Anthropic,
|
||||
Gemini, Ollama, DeepSeek, etc. Handles rate limiting, token tracking, and
|
||||
automatic failover between providers.
|
||||
- **Tool Runtime** — Executes tool calls with configurable sandboxing,
|
||||
approval gates, retry policies, and capability scope validation.
|
||||
- **Memory Runtime** — Manages session memory, persistent memory stores,
|
||||
and knowledge retrieval across in-memory, SQLite, and MongoDB backends.
|
||||
|
||||
### Observability Plane
|
||||
|
||||
- **Run Event Bus** — Structured event streaming for all lifecycle transitions
|
||||
(START, INPUT, MODEL_CALL, TOOL_CALL, ERROR, RETRY, COMPLETE).
|
||||
- **Metrics + Cost** — Token counting, cost tracking, and performance metrics.
|
||||
- **Replay Engine** — Deterministic replay from the last stable checkpoint,
|
||||
with state hash verification.
|
||||
|
||||
### Data Plane
|
||||
|
||||
- **Run Ledger** — Persistent record of all runs with state, metrics, and
|
||||
failure classifications.
|
||||
- **Checkpoints** — Point-in-time snapshots of run state, memory, and
|
||||
artifacts for replay and recovery.
|
||||
- **Artifacts Store** — Tool outputs, generated files, and intermediate
|
||||
results.
|
||||
|
||||
---
|
||||
|
||||
## 4. Core Data Contracts
|
||||
|
||||
### RunRequest
|
||||
|
||||
```text
|
||||
RunRequest {
|
||||
run_id: UUID,
|
||||
workflow_ref: string,
|
||||
inputs: object,
|
||||
profile: {safe_mode, budget, timeout, approval_policy},
|
||||
context: {user_id, workspace_id, env}
|
||||
}
|
||||
```
|
||||
|
||||
### RunEvent
|
||||
|
||||
```text
|
||||
RunEvent {
|
||||
ts: ISO8601,
|
||||
run_id: UUID,
|
||||
step_id: string,
|
||||
type: START | INPUT | MODEL_CALL | TOOL_CALL |
|
||||
ERROR | RETRY | COMPLETE,
|
||||
payload: object,
|
||||
cost: {tokens_in, tokens_out, usd},
|
||||
latency_ms: number
|
||||
}
|
||||
```
|
||||
|
||||
### Checkpoint
|
||||
|
||||
```text
|
||||
Checkpoint {
|
||||
run_id: UUID,
|
||||
step_id: string,
|
||||
state_hash: string,
|
||||
memory_snapshot_ref: string,
|
||||
artifact_refs: string[]
|
||||
}
|
||||
```
|
||||
|
||||
### Execution Sequence
|
||||
|
||||
```text
|
||||
1) Client submits RunRequest
|
||||
2) Gateway validates profile + schema
|
||||
3) Compiler resolves workflow → CompiledGraph
|
||||
4) Orchestrator starts node execution
|
||||
5) Node may call Model Runtime or Tool Runtime
|
||||
6) Every transition emits RunEvent
|
||||
7) On failure: classifier decides retry/fallback/abort
|
||||
8) Checkpoint stored after each critical step
|
||||
9) Final state + artifacts persisted to run ledger
|
||||
10) Replay can resume from last stable checkpoint
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 5. Reliability by Design
|
||||
|
||||
### Error Taxonomy
|
||||
|
||||
All failures are classified into one of five categories for automatic
|
||||
remediation:
|
||||
|
||||
| Category | Description | Default Action |
|
||||
|----------|-------------|----------------|
|
||||
| `config` | Invalid configuration or profile | Abort with remediation hint |
|
||||
| `dependency` | Missing optional module or capability | Degrade / skip optional path |
|
||||
| `tool` | Tool execution failure | Retry with backoff and policy cap |
|
||||
| `model` | Model API error or timeout | Fallback to alternate provider/route |
|
||||
| `infra` | Network or resource exhaustion | Circuit-breaker + replay from checkpoint |
|
||||
|
||||
```mermaid
|
||||
flowchart TD
|
||||
S[Step Failure] --> T{Failure Type?}
|
||||
T -->|Config| C1[Abort + config remediation hint]
|
||||
T -->|Dependency| C2[Degrade capability / skip optional path]
|
||||
T -->|Tool| C3[Retry with backoff and policy cap]
|
||||
T -->|Model| C4[Fallback model/provider route]
|
||||
T -->|Infra| C5[Circuit-breaker + replay from checkpoint]
|
||||
```
|
||||
|
||||
### Hardening Checklist
|
||||
|
||||
- **Dependency gates** — Optional modules declared as capabilities;
|
||||
unavailable capability results in skip/degrade, not crash.
|
||||
- **Cross-platform adapters** — OS-specific implementations behind a single
|
||||
interface (e.g., file lock adapter for Windows/Linux/macOS).
|
||||
- **Idempotent fixtures** — Integration tests use unique tenant/workspace IDs
|
||||
and guaranteed teardown.
|
||||
- **Fail-safe output mode** — CLI rendering falls back to ASCII-safe mode on
|
||||
encoding mismatch.
|
||||
- **CI parity matrix** — Run smoke workflows across Windows, Linux, and macOS.
|
||||
|
||||
### Deterministic Test Pattern
|
||||
|
||||
```python
|
||||
# Integration test pattern — always use unique, traceable IDs
|
||||
import uuid
|
||||
|
||||
def test_agent_workflow():
|
||||
tenant_id = f"test-{uuid.uuid4().hex[:8]}"
|
||||
agent = Agent(name=f"agent-{tenant_id}", ...)
|
||||
result = agent.run("task")
|
||||
assert result.status == "success"
|
||||
# teardown is guaranteed via fixture or context manager
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 6. Observability & Telemetry
|
||||
|
||||
### Current Telemetry Stack
|
||||
|
||||
PraisonAI already includes:
|
||||
|
||||
- **OpenTelemetry integration** — Manual and auto-instrumentation for
|
||||
traces, metrics, and logs.
|
||||
- **Token tracking** — Per-call and cumulative token/cost tracking.
|
||||
- **Performance monitoring** — Real-time dashboards and monitoring views.
|
||||
- **LangTrace integration** — LangTrace provider for tracing.
|
||||
- **Run outcomes** — Structured `RunOutcome` objects with status, duration,
|
||||
token usage, and error classification.
|
||||
|
||||
### Planned Enhancements
|
||||
|
||||
- **Run Event Bus** — Stream all lifecycle events as structured `RunEvent`
|
||||
payloads.
|
||||
- **Failure classifier** — Automatic failure category detection with
|
||||
remediation hints.
|
||||
- **Run ledger visualization** — Timeline view of runs with step-by-step
|
||||
event drill-down.
|
||||
- **Replay integration** — Checkpoint-based run replay from the
|
||||
observability dashboard.
|
||||
|
||||
---
|
||||
|
||||
## 7. Replay & Checkpointing
|
||||
|
||||
### Design
|
||||
|
||||
```mermaid
|
||||
sequenceDiagram
|
||||
participant U as User/Client
|
||||
participant G as Gateway
|
||||
participant C as Compiler
|
||||
participant O as Orchestrator
|
||||
participant R as Model/Tool Runtime
|
||||
participant E as Event Bus
|
||||
participant L as Run Ledger
|
||||
participant K as Checkpoint Store
|
||||
|
||||
U->>G: Submit RunRequest
|
||||
G->>C: Validate + compile workflow
|
||||
C-->>O: CompiledGraph
|
||||
O->>R: Execute next step
|
||||
R-->>O: Step output / error
|
||||
O->>E: Emit structured RunEvent
|
||||
O->>K: Persist checkpoint
|
||||
O->>L: Persist run state + metrics
|
||||
O-->>U: Final result / failure summary
|
||||
```
|
||||
|
||||
### Current State
|
||||
|
||||
- Basic run outcome persistence exists
|
||||
- Session persistence for bot/multi-turn conversations
|
||||
- Token and cost tracking per run
|
||||
|
||||
### Roadmap
|
||||
|
||||
- Full checkpoint creation at configurable step granularity
|
||||
- State hash verification for deterministic replay
|
||||
- Replay API endpoint (`POST /runs/{id}/replay`)
|
||||
- Checkpoint pruning and retention policy
|
||||
|
||||
---
|
||||
|
||||
## 8. Implementation Roadmap
|
||||
|
||||
### Quarter 1: Trust Foundation (Q3 2026)
|
||||
|
||||
| Priority | Project | Description | Status |
|
||||
|----------|---------|-------------|--------|
|
||||
| P0 | Reliability Core | Cross-platform hardening, optional-dep gating, deterministic fixtures | In progress |
|
||||
| P0 | Doctor Auto-Fix | Automated environment diagnosis and repairs | Planned |
|
||||
| P1 | Golden-Path CLI | Single canonical flow: init → run → test → deploy | Planned |
|
||||
| P1 | CI Parity Matrix | Cross-platform smoke tests in CI pipeline | Planned |
|
||||
|
||||
### Quarter 2: Operational Excellence (Q4 2026)
|
||||
|
||||
| Priority | Project | Description | Status |
|
||||
|----------|---------|-------------|--------|
|
||||
| P1 | Trace + Replay | Run timeline, checkpoint replay, failure classifier | Planned |
|
||||
| P1 | Failure Classifier | Automatic failure category detection with remediation | Planned |
|
||||
| P2 | Graph Studio UX | Visual deterministic orchestration editor/inspector | Planned |
|
||||
| P2 | Safe Production Profiles | Policy presets: guardrails, approvals, cost/time caps | Planned |
|
||||
|
||||
```mermaid
|
||||
gantt
|
||||
title PraisonAI Architecture Program (2 Quarters)
|
||||
dateFormat YYYY-MM-DD
|
||||
section Quarter 1
|
||||
Reliability hardening + parity CI :a1, 2026-07-01, 45d
|
||||
Deterministic test isolation :a2, 2026-07-10, 50d
|
||||
Doctor Auto-Fix MVP :a3, 2026-07-20, 40d
|
||||
Golden-path CLI :a4, 2026-08-01, 45d
|
||||
section Quarter 2
|
||||
Trace bus + run ledger :b1, 2026-10-01, 45d
|
||||
Replay engine :b2, 2026-10-15, 45d
|
||||
Failure classifier :b3, 2026-11-01, 30d
|
||||
Graph UX beta + Safe profiles :b4, 2026-11-10, 50d
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 9. Success Metrics
|
||||
|
||||
### KPI Targets
|
||||
|
||||
| KPI | Target | Primary Workstream |
|
||||
|-----|--------|-------------------|
|
||||
| Time-to-first-successful run | 30-40% reduction | Golden-path CLI + Doctor Auto-Fix |
|
||||
| Cross-platform issue rate | 50% reduction | Reliability Core + adapter layer |
|
||||
| Incident triage time | 40% reduction | Trace + Replay + failure classifier |
|
||||
| CI confidence | Flaky test rate <2% | Deterministic tests + fixture isolation |
|
||||
|
||||
### Governance
|
||||
|
||||
- **Architecture Review Council** — Reviews runtime-contract changes
|
||||
- **Release Quality Gate** — Platform matrix + deterministic test thresholds
|
||||
- **Monthly telemetry review** — DX, reliability, adoption trends
|
||||
|
||||
|
||||
---
|
||||
|
||||
*This document is a living reference. Update as the architecture evolves.*
|
||||
@@ -1,14 +0,0 @@
|
||||
# Contributing to PraisonAI
|
||||
|
||||
Thank you for your interest! Here's how to get started:
|
||||
|
||||
1. Fork the repository
|
||||
2. Create a feature branch
|
||||
3. Make your changes
|
||||
4. Submit a pull request
|
||||
|
||||
## Guidelines
|
||||
|
||||
- Follow existing code style
|
||||
- Add tests for new features
|
||||
- Update documentation as needed
|
||||
@@ -770,11 +770,11 @@ agent.start('Write a movie script about a robot in Mars');
|
||||
|
||||
## ⚡ Performance
|
||||
|
||||
PraisonAI is built for speed, with agent instantiation in around 14μs. This reduces overhead, improves responsiveness, and helps multi-agent systems scale efficiently in real-world production workloads.
|
||||
PraisonAI is built for speed, with agent instantiation in under 4μs. This reduces overhead, improves responsiveness, and helps multi-agent systems scale efficiently in real-world production workloads.
|
||||
|
||||
| Performance Metric | PraisonAI |
|
||||
|--------------------|-----------|
|
||||
| Avg Instantiation Time | **14 μs** |
|
||||
| Avg Instantiation Time | **3.77 μs** |
|
||||
|
||||
---
|
||||
|
||||
|
||||
-66
@@ -1,66 +0,0 @@
|
||||
# Security Policy
|
||||
|
||||
PraisonAI takes security seriously. We appreciate responsible disclosure from researchers and users.
|
||||
|
||||
## Supported packages
|
||||
|
||||
| Package | Registry | Source path |
|
||||
|---------|----------|-------------|
|
||||
| `praisonaiagents` | [PyPI](https://pypi.org/project/praisonaiagents/) | `src/praisonai-agents/` |
|
||||
| `praisonai` | [PyPI](https://pypi.org/project/praisonai/) | `src/praisonai/` |
|
||||
| `praisonai-platform` | [PyPI](https://pypi.org/project/praisonai-platform/) | `src/praisonai-platform/` |
|
||||
| `praisonai` | [npm](https://www.npmjs.com/package/praisonai) | `src/praisonai-ts/` |
|
||||
|
||||
Report issues against the **specific package** where the vulnerability exists. A platform-only issue does not necessarily affect the core SDK, and vice versa.
|
||||
|
||||
## In scope
|
||||
|
||||
- Authentication, authorisation, and multi-tenant isolation (e.g. workspace boundaries)
|
||||
- Tool execution, sandbox escape, and code execution paths
|
||||
- SSRF, injection, and unsafe deserialisation in shipped code
|
||||
- MCP, gateway, and bot/webhook integrations
|
||||
- Secrets handling, JWT/session configuration, and default credentials
|
||||
- Supply-chain issues in published package artefacts
|
||||
|
||||
## Out of scope
|
||||
|
||||
- Issues in forks or deployments not maintained in [MervinPraison/PraisonAI](https://github.com/MervinPraison/PraisonAI)
|
||||
- Vulnerabilities requiring physical access or fully compromised operator machines
|
||||
- Reports against versions no longer published or without a supported upgrade path
|
||||
- Theoretical issues with no practical impact in documented, supported configurations
|
||||
- Behaviour covered by an explicit, documented opt-out (e.g. dev-only env vars)
|
||||
|
||||
## How to report
|
||||
|
||||
**Preferred:** open a **private** security advisory:
|
||||
|
||||
[https://github.com/MervinPraison/PraisonAI/security/advisories/new](https://github.com/MervinPraison/PraisonAI/security/advisories/new)
|
||||
|
||||
Include:
|
||||
|
||||
1. Affected package and version
|
||||
2. Clear reproduction steps
|
||||
3. Impact assessment (confidentiality, integrity, availability)
|
||||
4. Suggested fix (optional)
|
||||
|
||||
Please allow reasonable time for triage and a patched release before public disclosure.
|
||||
|
||||
## What to expect
|
||||
|
||||
1. **Triage** — we validate the report and assign a disposition (`real`, `duplicate`, `wontfix`, etc.)
|
||||
2. **Fix** — minimal, backward-compatible patch on `main` where appropriate
|
||||
3. **Release** — patched version published to PyPI/npm **before** the advisory is published
|
||||
4. **Advisory** — GitHub Security Advisory with reporter credit and CVE where applicable
|
||||
|
||||
## Resources
|
||||
|
||||
- **Repository:** https://github.com/MervinPraison/PraisonAI
|
||||
- **Documentation:** https://docs.praison.ai
|
||||
- **Website:** https://praison.ai
|
||||
- **Advisories:** https://github.com/MervinPraison/PraisonAI/security/advisories
|
||||
|
||||
## Maintainer workflow
|
||||
|
||||
Contributors and agents handling audits should follow:
|
||||
|
||||
`src/praisonai-agents/.agent/workflows/security-audit.md`
|
||||
@@ -15,7 +15,6 @@ Methods:
|
||||
* <code title="class GuardrailResult">GuardrailResult.<a href="./src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py">from_tuple</a>(result: Tuple[bool, Any]) -> 'GuardrailResult'</code>
|
||||
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_dict</a>(data: Dict[str, Any]) -> 'HandoffConfig'</code>
|
||||
* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <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">to_dict</a>() -> Dict[str, Any]</code>
|
||||
@@ -30,7 +29,6 @@ from praisonaiagents import Agent, AutoAgents, AutoRagAgent, ContextAgent, DeepR
|
||||
Methods:
|
||||
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">aclose</a>() -> None</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">add_mcp_server</a>(name: str, mcp: Any) -> Any</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">agent_id</a>() -> str</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">analyze_prompt</a>(prompt: str) -> set</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>() -> Optional[bool]</code>
|
||||
@@ -60,9 +58,6 @@ Methods:
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">handoff_to_async</a>(target_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None, config: Optional['HandoffConfig'] = None) -> 'HandoffResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">is_closed</a>() -> bool</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">list_mcp_servers</a>() -> List[str]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_instance</a>()</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_instance</a>(value)</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">llm_model</a>() -> Optional[str]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>() -> Optional[str]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">output_style</a>(value: Optional[str]) -> None</code>
|
||||
@@ -72,8 +67,6 @@ Methods:
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag</a>() -> Optional[Any]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rag_query</a>(question: str, **kwargs) -> 'RAGResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">redo</a>() -> bool</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">refresh_tools</a>() -> List[Any]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">remove_mcp_server</a>(name: str) -> bool</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieval_config</a>() -> Optional[Any]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieve</a>(query: str, **kwargs) -> 'ContextPack'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rules_manager</a>() -> Optional[Any]</code>
|
||||
@@ -82,7 +75,7 @@ Methods:
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until</a>(prompt: str, criteria: str, threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False) -> 'EvaluationLoopResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_until_async</a>(prompt: str, criteria: str, threshold: float = 8.0, max_iterations: int = 5, mode: str = 'optimize', on_iteration: Optional[Callable[[Any], None]] = None, verbose: bool = False) -> 'EvaluationLoopResult'</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">skill_manager</a>() -> Optional[Any]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', action: str = 'add', **kwargs: Any) -> None</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', **kwargs: Any) -> None</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>() -> Optional[Any]</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>(value: Optional[Any]) -> None</code>
|
||||
* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>() -> Optional[int]</code>
|
||||
@@ -182,7 +175,6 @@ Methods:
|
||||
* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_schema_roundtrip</a>() -> bool</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">__call__</a>(*args, **kwargs) -> Any</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">check_availability</a>() -> tuple[bool, str]</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">get_schema</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">injected_params</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">run</a>(**kwargs) -> Any</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">clear</a>() -> None</code>
|
||||
@@ -190,18 +182,16 @@ Methods:
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_single_file_plugins</a>() -> int</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_all</a>() -> Dict[str, Union[BaseTool, Callable]]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_tool_definitions</a>() -> List[Dict[str, Any]]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_trust_level</a>(name: str) -> Optional[str]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_available_tools</a>(context: Optional[Dict[str, Any]] = None, ttl_seconds: Optional[float] = None) -> List[Union[BaseTool, Callable]]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_available_tools</a>(context: Optional[Dict[str, Any]] = None) -> List[Union[BaseTool, Callable]]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_base_tools</a>() -> List[BaseTool]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_tools</a>() -> List[str]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_tools_with_allowed_filter</a>(context: Optional[Dict[str, Any]] = None) -> List[str]</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, overwrite: bool = False, trust_level: Optional[str] = None, dynamic_schema_overrides: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None) -> None</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, overwrite: bool = False) -> None</code>
|
||||
* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">unregister</a>(name: str) -> bool</code>
|
||||
* <code title="class Tools">Tools.<a href="./src/praisonai-agents/praisonaiagents/tools/tools.py">internet_search</a>(*args, **kwargs)</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_registry</a>() -> ToolRegistry</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_tool</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register_tool</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, trust_level: Optional[str] = None, dynamic_schema_overrides: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None) -> None</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register_tool</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None) -> None</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">tool</a>(func: Optional[Callable] = None) -> Union[FunctionTool, Callable[[Callable], FunctionTool]]</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_tool</a>(tool: Any) -> bool</code>
|
||||
|
||||
@@ -246,7 +236,6 @@ from praisonaiagents import Memory, MemoryBackend, MemoryConfig
|
||||
|
||||
Methods:
|
||||
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">build_cache_optimized_context</a>(task_descr: str, user_id: Optional[str] = None, additional: str = '', max_items: int = 3, include_cache_boundary: bool = True, include_in_output: Optional[bool] = None) -> Dict[str, str]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">build_context_for_task</a>(task_descr: str, user_id: Optional[str] = None, additional: str = '', max_items: int = 3, include_in_output: Optional[bool] = None) -> str</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">calculate_quality_metrics</a>(output: str, expected_output: str, llm: Optional[str] = None, custom_prompt: Optional[str] = None) -> Dict[str, float]</code>
|
||||
* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">close_connections</a>()</code>
|
||||
@@ -364,7 +353,7 @@ Methods:
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_tool_function</a>(source_agent: 'Agent') -> Callable</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_description</a>() -> str</code>
|
||||
* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_name</a>() -> str</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">handoff</a>(agent: 'Agent', tool_name_override: Optional[str] = None, tool_description_override: Optional[str] = None, on_handoff: Optional[Callable] = None, input_type: Optional[type] = None, input_filter: Optional[Callable[[HandoffInputData], HandoffInputData]] = None, config: Optional[HandoffConfig] = None, context_policy: Optional[str] = None, timeout_seconds: Optional[float] = None, max_concurrent: Optional[int] = None, detect_cycles: Optional[bool] = None, max_depth: Optional[int] = None, tool_policy_mode: Optional[Literal['intersect', 'passthrough']] = None, blocked_tools: Optional[List[str]] = None) -> Handoff</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">handoff</a>(agent: 'Agent', tool_name_override: Optional[str] = None, tool_description_override: Optional[str] = None, on_handoff: Optional[Callable] = None, input_type: Optional[type] = None, input_filter: Optional[Callable[[HandoffInputData], HandoffInputData]] = None, config: Optional[HandoffConfig] = None, context_policy: Optional[str] = None, timeout_seconds: Optional[float] = None, max_concurrent: Optional[int] = None, detect_cycles: Optional[bool] = None, max_depth: Optional[int] = None) -> Handoff</code>
|
||||
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">compress_history</a>(data: HandoffInputData) -> HandoffInputData</code>
|
||||
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">keep_last_n_messages</a>(n: int) -> Callable[[HandoffInputData], HandoffInputData]</code>
|
||||
* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">remove_all_tools</a>(data: HandoffInputData) -> HandoffInputData</code>
|
||||
@@ -483,16 +472,11 @@ Methods:
|
||||
* <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_skill</a>(skill_path: str) -> 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">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">create_skill</a>(name: str, content: str, category: str = None) -> dict</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">delete_skill</a>(name: str) -> 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">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">edit_skill</a>(name: str, content: str) -> 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>
|
||||
@@ -501,24 +485,15 @@ Methods:
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skills_diagnostics</a>() -> Dict[str, ValidationResult]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_user_invocable_skills</a>() -> List[LoadedSkill]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">invoke</a>(name: str, raw_args: str = '', session_id: Optional[str] = None, shell_exec: bool = False) -> Optional[str]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">list_archived_skills</a>() -> List[str]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">list_pending</a>() -> List[dict]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">load_resources</a>(name: str) -> bool</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">patch</a>(name: str, old_string: str, new_string: str, file_path: Optional[str] = None, replace_all: bool = False, propose: Optional[bool] = None) -> dict</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">patch_skill</a>(name: str, old_string: str, new_string: str, file_path: str = None, replace_all: bool = False, propose: Optional[bool] = None) -> dict</code>
|
||||
* <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">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">patch_skill</a>(name: str, old_string: str, new_string: str, file_path: str = None, replace_all: bool = False) -> 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) -> dict</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skill_names</a>() -> List[str]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skills</a>() -> List[LoadedSkill]</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">to_prompt</a>() -> str</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">validate_skill_capabilities</a>(skill_name: str, force_refresh: bool = False) -> ValidationResult</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">write_file</a>(name: str, file_path: str, file_content: str, propose: Optional[bool] = None) -> dict</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">write_skill_file</a>(name: str, file_path: str, file_content: str, propose: Optional[bool] = None) -> dict</code>
|
||||
* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">write_skill_file</a>(name: str, file_path: str, file_content: str) -> dict</code>
|
||||
* <code title="class SkillMetadata">SkillMetadata.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">from_properties</a>(props: SkillProperties) -> 'SkillMetadata'</code>
|
||||
* <code title="class SkillProperties">SkillProperties.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">idle_days</a>() -> Optional[float]</code>
|
||||
* <code title="class SkillProperties">SkillProperties.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">to_dict</a>() -> dict</code>
|
||||
* <code title="class SkillsConfig">SkillsConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
|
||||
@@ -536,12 +511,10 @@ Methods:
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">add_memory</a>(text: str, memory_type: str = 'long', **metadata) -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">chat</a>(message: str, **kwargs) -> str</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">clear_memory</a>(memory_type: str = 'all') -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">close</a>() -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">create_agent</a>(*args, **kwargs) -> 'Agent'</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">get_context</a>(query: str, max_items: int = 3) -> str</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">get_state</a>(key: str, default: Any = None) -> Any</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">increment_state</a>(key: str, increment: int = 1, default: int = 0) -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">is_expired</a>() -> bool</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">knowledge</a>() -> 'Knowledge'</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">memory</a>() -> 'Memory'</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">restore_state</a>() -> Dict[str, Any]</code>
|
||||
@@ -550,7 +523,6 @@ Methods:
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">search_memory</a>(query: str, memory_type: str = 'long', limit: int = 5) -> List[Dict[str, Any]]</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">send_message</a>(message: str, **kwargs) -> str</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">set_state</a>(key: str, value: Any) -> None</code>
|
||||
* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">time_to_expiry</a>() -> Optional[float]</code>
|
||||
|
||||
# MCP
|
||||
|
||||
@@ -633,7 +605,7 @@ Methods:
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">register_snapshot_callback</a>(callback: Callable[[SnapshotHookData], None]) -> None</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">reset</a>() -> None</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">set_tool_budget</a>(tool_name: str, max_tokens: int, protected: bool = False) -> None</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">truncate_tool_output</a>(tool_name: str, output: str, tool_call_id: str = None, run_id: str = None) -> str</code>
|
||||
* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">truncate_tool_output</a>(tool_name: str, output: str) -> str</code>
|
||||
|
||||
# UI
|
||||
|
||||
@@ -654,7 +626,6 @@ Methods:
|
||||
* <code title="class AutonomyConfig">AutonomyConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/autonomy.py">effective_track_changes</a>() -> bool</code>
|
||||
* <code title="class AutonomyConfig">AutonomyConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/autonomy.py">from_dict</a>(data: Dict[str, Any]) -> 'AutonomyConfig'</code>
|
||||
* <code title="class CachingConfig">CachingConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class ExecutionConfig">ExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">from_dict</a>(data: Dict[str, Any]) -> 'ExecutionConfig'</code>
|
||||
* <code title="class ExecutionConfig">ExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class GuardrailConfig">GuardrailConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class HooksConfig">HooksConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
|
||||
@@ -722,7 +693,7 @@ Methods:
|
||||
|
||||
Types:
|
||||
```python
|
||||
from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, RetryBackoffConfig, __version__, aembedding, aembeddings, embedding, embeddings, get_dimensions
|
||||
from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, aembedding, aembeddings, embedding, embeddings, get_dimensions
|
||||
```
|
||||
|
||||
Methods:
|
||||
@@ -747,16 +718,12 @@ Methods:
|
||||
* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>(value: bool)</code>
|
||||
* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">get_app</a>() -> Any</code>
|
||||
* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">serve</a>(host: Optional[str] = None, port: Optional[int] = None, reload: bool = False, **kwargs: Any) -> None</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aannounce_completion</a>(agent_id: str, task_id: str, result: Any, success: bool = True, error: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None) -> None</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">add_task</a>(task)</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aexecute_task</a>(task_id)</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">announce_completion</a>(agent_id: str, task_id: str, result: Any, success: bool = True, error: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None) -> None</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">append_to_state</a>(key: str, value: Any, max_length: Optional[int] = None) -> List[Any]</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_all_tasks</a>()</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aspawn_sub_agent</a>(agent: Agent, task: Any, completion_callback: Optional[Callable[[SubAgentCompletionEvent], Any]] = None, metadata: Optional[Dict[str, Any]] = None) -> SpawnedSubAgent</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">await_for_completions</a>(timeout: Optional[float] = None, agent_ids: Optional[List[str]] = None) -> List[SubAgentCompletionEvent]</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">close</a>() -> None</code>
|
||||
@@ -771,7 +738,6 @@ Methods:
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_tasks_status</a>()</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_detailed_token_report</a>() -> Dict[str, Any]</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_plan_markdown</a>() -> str</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_spawned_agents</a>() -> List[SpawnedSubAgent]</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_state</a>(key: str, default: Any = None) -> Any</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_details</a>(task_id)</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
|
||||
@@ -788,12 +754,10 @@ Methods:
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">spawn_sub_agent</a>(agent: Agent, task: Any, completion_callback: Optional[Callable[[SubAgentCompletionEvent], Any]] = None, metadata: Optional[Dict[str, Any]] = None) -> SpawnedSubAgent</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, output = None, **kwargs)</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
|
||||
* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">wait_for_completions</a>(timeout: Optional[float] = None, agent_ids: Optional[List[str]] = None) -> List[SubAgentCompletionEvent]</code>
|
||||
* <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval</a>(request: ApprovalRequest) -> ApprovalDecision</code>
|
||||
* <code title="class AutoApproveBackend">AutoApproveBackend.<a href="./src/praisonai-agents/praisonaiagents/approval/backends.py">request_approval_sync</a>(request: ApprovalRequest) -> ApprovalDecision</code>
|
||||
* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembedding</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
|
||||
@@ -813,18 +777,11 @@ 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>
|
||||
@@ -862,16 +819,9 @@ Methods:
|
||||
* <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>
|
||||
@@ -884,9 +834,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -896,10 +843,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -921,18 +864,17 @@ Methods:
|
||||
* <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 config <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor db <a href="./src/praisonai/praisonai/cli/commands/doctor.py">--help</a></code>
|
||||
* <code title="cli">praisonai doctor doctor-callback <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 tools <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>
|
||||
@@ -960,9 +902,6 @@ Methods:
|
||||
* <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>
|
||||
* <code title="cli">praisonai gateway mint-link <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
|
||||
* <code title="cli">praisonai gateway pause <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
|
||||
* <code title="cli">praisonai gateway reconnect <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
|
||||
* <code title="cli">praisonai gateway resume <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
|
||||
* <code title="cli">praisonai gateway send <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
|
||||
* <code title="cli">praisonai gateway start <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
|
||||
* <code title="cli">praisonai gateway status <a href="./src/praisonai/praisonai/cli/commands/gateway.py">--help</a></code>
|
||||
@@ -972,11 +911,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1041,9 +975,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1061,14 +992,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1131,8 +1054,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1142,10 +1063,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1154,7 +1071,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1181,7 +1097,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1223,9 +1138,6 @@ Methods:
|
||||
* <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>
|
||||
@@ -1377,8 +1289,8 @@ export { // Python parity additions
|
||||
MinimalTelemetry, AgentTelemetry, PerformanceMonitor, TelemetryCollector, TelemetryIntegration, cleanupTelemetry, cleanupTelemetryResources, createAgentTelemetry, createConsoleSink, createHTTPSink, createPerformanceMonitor, createTelemetryIntegration, disablePerformanceMode, disableTelemetry, enablePerformanceMode, enableTelemetry, getMinimalTelemetry, getTelemetry } from "./telemetry";
|
||||
export { // Subagent Tool (agent-as-tool pattern)
|
||||
SubagentTool, BaseTool, FunctionTool, ToolRegistry, ToolResult, ToolValidationError, createDelegator, createSubagentTool, createSubagentTools, createTool, getRegistry, getTool, registerTool, tool, validateTool } from "./tools";
|
||||
export { airweaveSearch, bedrockBrowserClick, bedrockBrowserFill, bedrockBrowserNavigate, bedrockCodeInterpreter, codeExecution, codeMode, createCustomTool, crwCrawl, crwScrape, exaSearch, firecrawlCrawl, firecrawlScrape, parallelSearch, perplexitySearch, registerCustomTool, registerLocalTool, registerNpmTool, superagentGuard, superagentRedact, superagentVerify, tavilyCrawl, tavilyExtract, tavilySearch, valyuBioSearch, valyuCompanyResearch, valyuEconomicsSearch, valyuFinanceSearch, valyuPaperSearch, valyuPatentSearch, valyuSecSearch, valyuWebSearch } from "./tools/builtins";
|
||||
export { BudgetExceededError, MissingDependencyError, MissingEnvVarError, ToolsRegistry, composeMiddleware, createLoggingMiddleware, createRateLimitMiddleware, createRedactionMiddleware, createRetryMiddleware, createTimeoutMiddleware, createToolsRegistry, createTracingMiddleware, createValidationMiddleware, getToolsRegistry, get_registry, get_tool, register_tool, resetToolsRegistry, validate_tool } from "./tools/registry";
|
||||
export { airweaveSearch, bedrockBrowserClick, bedrockBrowserFill, bedrockBrowserNavigate, bedrockCodeInterpreter, codeExecution, codeMode, createCustomTool, exaSearch, firecrawlCrawl, firecrawlScrape, parallelSearch, perplexitySearch, registerCustomTool, registerLocalTool, registerNpmTool, superagentGuard, superagentRedact, superagentVerify, tavilyCrawl, tavilyExtract, tavilySearch, valyuBioSearch, valyuCompanyResearch, valyuEconomicsSearch, valyuFinanceSearch, valyuPaperSearch, valyuPatentSearch, valyuSecSearch, valyuWebSearch } from "./tools/builtins";
|
||||
export { BudgetExceededError, MissingDependencyError, MissingEnvVarError, ToolsRegistry, composeMiddleware, createLoggingMiddleware, createRateLimitMiddleware, createRedactionMiddleware, createRetryMiddleware, createTimeoutMiddleware, createToolsRegistry, createTracingMiddleware, createValidationMiddleware, getRegistry, getTool, getToolsRegistry, get_registry, get_tool, registerTool, register_tool, resetToolsRegistry, validateTool, validate_tool } from "./tools/registry";
|
||||
export type { InstallHints, PraisonTool, RedactionHooks, RegisteredTool, ToolCapabilities, ToolExecutionContext, ToolExecutionResult, ToolFactory, ToolHooks, ToolInstallStatus, ToolLimits, ToolLogger, ToolMetadata, ToolMiddleware, ToolParameterProperty, ToolParameterSchema } from "./tools/registry";
|
||||
export { registerBuiltinTools, tools } from "./tools/tools";
|
||||
export { // Classes
|
||||
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=4.6.80" \
|
||||
"praisonai>=4.6.52" \
|
||||
"praisonai[chat]" \
|
||||
"embedchain[github,youtube]"
|
||||
|
||||
|
||||
@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=4.6.80" \
|
||||
"praisonai>=4.6.52" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[chat]" \
|
||||
"praisonai[realtime]" \
|
||||
|
||||
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
|
||||
# Install Python packages (using latest versions)
|
||||
RUN pip install --no-cache-dir \
|
||||
praisonai_tools \
|
||||
"praisonai>=4.6.80" \
|
||||
"praisonai>=4.6.52" \
|
||||
"praisonai[ui]" \
|
||||
"praisonai[crewai]"
|
||||
|
||||
|
||||
@@ -12,13 +12,8 @@ from praisonaiagents import Agent
|
||||
from praisonaiagents.approval import AgentApproval
|
||||
from praisonaiagents.tools.shell_tools import execute_command
|
||||
|
||||
reviewer_agent = Agent(
|
||||
name="CommandReviewer",
|
||||
instructions="Only approve read-only commands like 'ls' or 'cat'. Deny destructive commands.",
|
||||
)
|
||||
|
||||
reviewer = AgentApproval(
|
||||
approver_agent=reviewer_agent,
|
||||
instructions="Only approve read-only commands like 'ls' or 'cat'. Deny destructive commands.",
|
||||
)
|
||||
|
||||
agent = Agent(
|
||||
|
||||
@@ -5,12 +5,12 @@ Demonstrates web search with consolidated params.
|
||||
Presets: duckduckgo, tavily, google, bing, serper, search_only, fetch_only
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, WebConfig
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Basic: Enable web search with preset (search only — fetch needs Claude)
|
||||
# Basic: Enable web search with preset
|
||||
agent = Agent(
|
||||
instructions="You are a research assistant with web access.",
|
||||
web="search_only", # Compatible across models without web_fetch
|
||||
web="duckduckgo", # Presets: duckduckgo, tavily, google, bing, serper
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@@ -30,5 +30,5 @@ if __name__ == "__main__":
|
||||
sys.stdout.reconfigure(encoding="utf-8")
|
||||
except Exception:
|
||||
pass
|
||||
result = workflow.run("AI agents")
|
||||
result = workflow.run()
|
||||
print(result)
|
||||
@@ -1,216 +0,0 @@
|
||||
# Industry Templates for PraisonAI
|
||||
|
||||
This directory contains industry-specific agent templates based on the SRAO Framework, providing pre-built workflows for rapid deployment of agent workforces across different industries.
|
||||
|
||||
## Overview
|
||||
|
||||
These templates demonstrate how PraisonAI can be used to create specialized agent teams for various industries, with **70% code reuse** across different sectors through shared patterns and abstractions.
|
||||
|
||||
## Available Templates
|
||||
|
||||
### 1. Manufacturing (`manufacturing_template.py`)
|
||||
**Key Agents:**
|
||||
- **ParseOrder**: Extracts and structures order information from various formats
|
||||
- **CheckInventory**: Validates material availability and supply chain status
|
||||
- **OptimizeSchedule**: Optimizes production scheduling based on constraints
|
||||
- **DefectDetect**: Quality control and defect detection
|
||||
|
||||
**Features:**
|
||||
- Order processing with multiple input formats
|
||||
- Real-time inventory management
|
||||
- Production optimization algorithms
|
||||
- Quality inspection with defect detection
|
||||
- Fallback strategies for each critical step
|
||||
|
||||
### 2. Energy (`energy_template.py`)
|
||||
**Key Agents:**
|
||||
- **SCADAReader**: Processes SCADA telemetry data from wind turbines
|
||||
- **VibrationAnalyzer**: Analyzes vibration patterns for predictive maintenance
|
||||
- **PowerForecaster**: Predicts power generation based on weather and history
|
||||
- **MaintenanceScheduler**: Schedules predictive maintenance
|
||||
|
||||
**Features:**
|
||||
- Real-time wind farm monitoring
|
||||
- Vibration-based fault detection
|
||||
- Power generation forecasting
|
||||
- Grid integration and load balancing
|
||||
- Predictive maintenance scheduling
|
||||
|
||||
### 3. Healthcare (`healthcare_template.py`)
|
||||
**Key Agents:**
|
||||
- **VitalSignsCapture**: Processes patient vital signs from monitoring devices
|
||||
- **EMRRetrieval**: Retrieves electronic medical records with HIPAA compliance
|
||||
- **TriageRecommendation**: Provides ESI-based triage recommendations
|
||||
- **ResourceAllocator**: Manages hospital resource allocation
|
||||
|
||||
**Features:**
|
||||
- Emergency triage workflow
|
||||
- HIPAA-compliant data handling
|
||||
- Patient safety protocols
|
||||
- Resource optimization
|
||||
- Cross-department coordination
|
||||
|
||||
### 4. Agriculture (`agriculture_template.py`)
|
||||
**Key Agents:**
|
||||
- **MultispectralAnalyzer**: Analyzes multispectral imagery for crop health
|
||||
- **DiseaseIdentifier**: Identifies crop diseases and pests using AI
|
||||
- **SprayRecommender**: Recommends targeted spraying strategies
|
||||
- **YieldPredictor**: Predicts crop yield based on conditions
|
||||
|
||||
**Features:**
|
||||
- Precision agriculture with drone/satellite imagery
|
||||
- Pest and disease early warning system
|
||||
- Optimized chemical application
|
||||
- Yield forecasting
|
||||
- Sustainable farming patterns
|
||||
|
||||
### 5. Transportation (`transportation_template.py`)
|
||||
**Key Agents:**
|
||||
- **LiDARFusion**: Processes LiDAR point cloud data for infrastructure
|
||||
- **DisplacementCalculator**: Calculates structural displacement
|
||||
- **HeatmapGenerator**: Generates safety visualization heatmaps
|
||||
- **MaintenancePlanner**: Plans infrastructure maintenance
|
||||
|
||||
**Features:**
|
||||
- Tunnel/bridge safety monitoring
|
||||
- LiDAR-based structural analysis
|
||||
- Real-time safety assessment
|
||||
- Traffic flow optimization
|
||||
- Predictive maintenance scheduling
|
||||
|
||||
## Key Features Across All Templates
|
||||
|
||||
### 1. I/O Schemas
|
||||
Each template includes Pydantic models for structured data handling:
|
||||
- Input validation
|
||||
- Type safety
|
||||
- Clear data contracts between agents
|
||||
|
||||
### 2. SLA Requirements
|
||||
Every agent has defined Service Level Agreements:
|
||||
- Processing time requirements
|
||||
- Response time guarantees
|
||||
- Performance benchmarks
|
||||
|
||||
### 3. Fallback Strategies
|
||||
Robust error handling with fallback mechanisms:
|
||||
- Graceful degradation
|
||||
- Manual intervention queues
|
||||
- Conservative estimates when systems fail
|
||||
|
||||
### 4. Cross-Industry Patterns (70% Reuse)
|
||||
Reusable base patterns that work across industries:
|
||||
- Data parsing agents
|
||||
- Resource availability checkers
|
||||
- Optimization engines
|
||||
- Inspection/quality control agents
|
||||
|
||||
## Usage Example
|
||||
|
||||
```python
|
||||
from manufacturing_template import (
|
||||
order_parser,
|
||||
inventory_checker,
|
||||
schedule_optimizer,
|
||||
quality_inspector,
|
||||
manufacturing_workflow
|
||||
)
|
||||
|
||||
# Process a manufacturing order
|
||||
order_text = "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
|
||||
result = manufacturing_workflow(order_text)
|
||||
print(result)
|
||||
```
|
||||
|
||||
## Adapting Templates for Your Industry
|
||||
|
||||
### Using Base Patterns
|
||||
Each template includes reusable pattern classes that can be adapted:
|
||||
|
||||
```python
|
||||
from manufacturing_template import IndustryAgentPattern
|
||||
|
||||
# Create a custom data parser for any domain
|
||||
custom_parser = IndustryAgentPattern.create_data_parser(
|
||||
name="CustomParser",
|
||||
domain="retail",
|
||||
sla_seconds=20
|
||||
)
|
||||
|
||||
# Create a resource checker for any resource type
|
||||
resource_checker = IndustryAgentPattern.create_resource_checker(
|
||||
name="StaffAvailability",
|
||||
resource_type="customer_service_staff",
|
||||
sla_seconds=3
|
||||
)
|
||||
```
|
||||
|
||||
### Creating Custom Workflows
|
||||
Combine agents from different templates or create new ones:
|
||||
|
||||
```python
|
||||
from praisonaiagents import Agent, tool
|
||||
|
||||
# Define custom tools
|
||||
@tool
|
||||
def custom_analysis(data: str) -> Dict:
|
||||
"""Your custom analysis logic"""
|
||||
return {"result": "analyzed"}
|
||||
|
||||
# Create custom agent
|
||||
custom_agent = Agent(
|
||||
name="CustomAnalyzer",
|
||||
instructions="Your specific instructions",
|
||||
tools=[custom_analysis]
|
||||
)
|
||||
```
|
||||
|
||||
## Integration with PraisonAI Core
|
||||
|
||||
These templates are built on top of PraisonAI's core Agent framework:
|
||||
|
||||
```python
|
||||
from praisonaiagents import Agent, tool, AgentTeam, Task
|
||||
|
||||
# Combine multiple industry agents into a team
|
||||
team = AgentTeam(
|
||||
agents=[order_parser, inventory_checker, schedule_optimizer],
|
||||
tasks=[
|
||||
Task(name="parse", agent=order_parser),
|
||||
Task(name="check", agent=inventory_checker),
|
||||
Task(name="optimize", agent=schedule_optimizer)
|
||||
]
|
||||
)
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
1. **Start with Templates**: Use these as starting points and customize for your specific needs
|
||||
2. **Maintain SLAs**: Define clear performance requirements for each agent
|
||||
3. **Implement Fallbacks**: Always have fallback strategies for critical operations
|
||||
4. **Use Type Safety**: Leverage Pydantic models for data validation
|
||||
5. **Monitor Performance**: Track agent performance against SLAs
|
||||
6. **Iterate and Improve**: Continuously refine based on real-world usage
|
||||
|
||||
## Contributing
|
||||
|
||||
To add a new industry template:
|
||||
|
||||
1. Follow the existing template structure
|
||||
2. Include all key components:
|
||||
- I/O Schemas (Pydantic models)
|
||||
- Agent definitions with SLAs
|
||||
- Tools for agent capabilities
|
||||
- Complete workflow function
|
||||
- Fallback strategies
|
||||
- Cross-industry patterns
|
||||
3. Add comprehensive documentation
|
||||
4. Include usage examples
|
||||
|
||||
## License
|
||||
|
||||
These templates are part of the PraisonAI project and follow the same licensing terms.
|
||||
|
||||
## References
|
||||
|
||||
Based on the [SRAO Framework](https://github.com/beixuan577/SRAO-Framework) (MIT License)
|
||||
@@ -1,38 +0,0 @@
|
||||
"""
|
||||
Industry Templates for PraisonAI
|
||||
================================
|
||||
|
||||
Pre-built agent templates for rapid deployment across different industries.
|
||||
Based on SRAO Framework with 70% cross-industry code reuse.
|
||||
|
||||
Available templates:
|
||||
- Manufacturing: Order processing, inventory, scheduling, quality control
|
||||
- Energy: Wind farm monitoring, predictive maintenance, power forecasting
|
||||
- Healthcare: Emergency triage, EMR retrieval, resource allocation
|
||||
- Agriculture: Precision farming, pest detection, yield prediction
|
||||
- Transportation: Infrastructure monitoring, safety assessment, maintenance
|
||||
|
||||
Example usage:
|
||||
from Industry_Templates.manufacturing_template import manufacturing_workflow
|
||||
|
||||
result = manufacturing_workflow("Customer order text")
|
||||
"""
|
||||
|
||||
__version__ = "1.0.0"
|
||||
__author__ = "PraisonAI Team"
|
||||
|
||||
# Import the modules so they're accessible via the package
|
||||
from . import manufacturing_template
|
||||
from . import energy_template
|
||||
from . import healthcare_template
|
||||
from . import agriculture_template
|
||||
from . import transportation_template
|
||||
|
||||
# Export commonly used items for convenience
|
||||
__all__ = [
|
||||
"manufacturing_template",
|
||||
"energy_template",
|
||||
"healthcare_template",
|
||||
"agriculture_template",
|
||||
"transportation_template"
|
||||
]
|
||||
@@ -1,551 +0,0 @@
|
||||
"""
|
||||
Agriculture Industry Template
|
||||
=============================
|
||||
Precision agriculture and pest management workflow
|
||||
Based on SRAO Framework with IoT sensor integration
|
||||
|
||||
Key agents:
|
||||
- MultispectralAnalyzer: Analyzes multispectral imagery
|
||||
- DiseaseIdentifier: Identifies crop diseases and pests
|
||||
- SprayRecommender: Recommends targeted spraying strategies
|
||||
- YieldPredictor: Predicts crop yield based on conditions
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, tool
|
||||
from typing import Dict, List, Any, Tuple, Optional
|
||||
from pydantic import BaseModel
|
||||
from datetime import datetime, timedelta
|
||||
from enum import Enum
|
||||
|
||||
|
||||
# Crop health levels
|
||||
class CropHealthLevel(str, Enum):
|
||||
EXCELLENT = "excellent"
|
||||
GOOD = "good"
|
||||
FAIR = "fair"
|
||||
POOR = "poor"
|
||||
CRITICAL = "critical"
|
||||
|
||||
|
||||
# Pest/Disease severity
|
||||
class SeverityLevel(str, Enum):
|
||||
NONE = "none"
|
||||
LOW = "low"
|
||||
MODERATE = "moderate"
|
||||
HIGH = "high"
|
||||
SEVERE = "severe"
|
||||
|
||||
|
||||
# I/O Schemas
|
||||
class MultispectralData(BaseModel):
|
||||
"""Multispectral imagery analysis data"""
|
||||
field_id: str
|
||||
capture_time: str
|
||||
ndvi_index: float # Normalized Difference Vegetation Index
|
||||
ndre_index: float # Normalized Difference Red Edge
|
||||
ccci_index: float # Canopy Chlorophyll Content Index
|
||||
moisture_level: float # Soil moisture percentage
|
||||
temperature: float # Celsius
|
||||
affected_area: float # Hectares
|
||||
gps_coordinates: Tuple[float, float]
|
||||
|
||||
|
||||
class PestDiseaseReport(BaseModel):
|
||||
"""Pest and disease identification report"""
|
||||
report_id: str
|
||||
field_id: str
|
||||
detection_time: str
|
||||
pest_type: Optional[str]
|
||||
disease_type: Optional[str]
|
||||
severity: SeverityLevel
|
||||
affected_crops: List[str]
|
||||
spread_rate: float # % per day
|
||||
environmental_factors: Dict[str, Any]
|
||||
confidence_score: float
|
||||
|
||||
|
||||
class SprayRecommendation(BaseModel):
|
||||
"""Targeted spraying recommendation"""
|
||||
recommendation_id: str
|
||||
field_id: str
|
||||
treatment_type: str # pesticide, fungicide, herbicide, fertilizer
|
||||
product_name: str
|
||||
application_rate: float # L/hectare
|
||||
target_zones: List[Dict[str, Any]] # GPS zones
|
||||
optimal_time: str
|
||||
weather_window: Dict[str, Any]
|
||||
cost_estimate: float
|
||||
environmental_impact: str # low, medium, high
|
||||
|
||||
|
||||
class YieldForecast(BaseModel):
|
||||
"""Crop yield prediction"""
|
||||
forecast_id: str
|
||||
field_id: str
|
||||
crop_type: str
|
||||
predicted_yield: float # tons/hectare
|
||||
confidence_interval: Tuple[float, float]
|
||||
harvest_window: Tuple[str, str]
|
||||
quality_grade: str # A, B, C
|
||||
market_price_estimate: float
|
||||
risk_factors: List[str]
|
||||
|
||||
|
||||
# Agriculture-specific tools
|
||||
@tool
|
||||
def analyze_multispectral_imagery(field_id: str, image_data: Dict) -> Dict:
|
||||
"""Analyze multispectral drone/satellite imagery for crop health"""
|
||||
# Simulate multispectral analysis
|
||||
ndvi = 0.75 # Healthy vegetation typically 0.6-0.9
|
||||
|
||||
# Determine health based on NDVI
|
||||
if ndvi > 0.8:
|
||||
health = CropHealthLevel.EXCELLENT
|
||||
affected_area = 0.0
|
||||
elif ndvi > 0.6:
|
||||
health = CropHealthLevel.GOOD
|
||||
affected_area = 2.5
|
||||
elif ndvi > 0.4:
|
||||
health = CropHealthLevel.FAIR
|
||||
affected_area = 5.0
|
||||
else:
|
||||
health = CropHealthLevel.POOR
|
||||
affected_area = 10.0
|
||||
|
||||
return {
|
||||
"field_id": field_id,
|
||||
"capture_time": datetime.now().isoformat(),
|
||||
"ndvi_index": ndvi,
|
||||
"ndre_index": 0.68,
|
||||
"ccci_index": 0.72,
|
||||
"moisture_level": 35.0,
|
||||
"temperature": 24.5,
|
||||
"affected_area": affected_area,
|
||||
"gps_coordinates": (40.7128, -74.0060),
|
||||
"health_level": health.value
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def identify_pest_disease(spectral_data: Dict, historical_data: List) -> Dict:
|
||||
"""Identify pests and diseases using AI image recognition"""
|
||||
# Simulate pest/disease detection
|
||||
ndvi = spectral_data.get("ndvi_index", 0.75)
|
||||
affected_area = spectral_data.get("affected_area", 0)
|
||||
|
||||
if affected_area > 8.0:
|
||||
pest_type = "aphids"
|
||||
disease_type = "powdery_mildew"
|
||||
severity = SeverityLevel.HIGH
|
||||
spread_rate = 2.5
|
||||
elif affected_area > 4.0:
|
||||
pest_type = "whiteflies"
|
||||
disease_type = "leaf_spot"
|
||||
severity = SeverityLevel.MODERATE
|
||||
spread_rate = 1.5
|
||||
elif affected_area > 0:
|
||||
pest_type = None
|
||||
disease_type = "early_blight"
|
||||
severity = SeverityLevel.LOW
|
||||
spread_rate = 0.5
|
||||
else:
|
||||
pest_type = None
|
||||
disease_type = None
|
||||
severity = SeverityLevel.NONE
|
||||
spread_rate = 0.0
|
||||
|
||||
return {
|
||||
"report_id": f"PDR-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"field_id": spectral_data["field_id"],
|
||||
"detection_time": datetime.now().isoformat(),
|
||||
"pest_type": pest_type,
|
||||
"disease_type": disease_type,
|
||||
"severity": severity.value,
|
||||
"affected_crops": ["wheat", "corn"],
|
||||
"spread_rate": spread_rate,
|
||||
"environmental_factors": {
|
||||
"humidity": 65,
|
||||
"temperature": spectral_data.get("temperature", 25),
|
||||
"rainfall_last_week": 15 # mm
|
||||
},
|
||||
"confidence_score": 0.85
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def calculate_spray_recommendation(pest_report: Dict, field_data: Dict, weather: Dict) -> Dict:
|
||||
"""Calculate optimal spraying strategy for pest/disease control"""
|
||||
severity = pest_report.get("severity", "none")
|
||||
|
||||
if severity == "high" or severity == "severe":
|
||||
treatment = "pesticide"
|
||||
product = "Imidacloprid"
|
||||
rate = 0.5
|
||||
impact = "medium"
|
||||
elif severity == "moderate":
|
||||
treatment = "fungicide"
|
||||
product = "Azoxystrobin"
|
||||
rate = 0.3
|
||||
impact = "low"
|
||||
elif severity == "low":
|
||||
treatment = "organic_treatment"
|
||||
product = "Neem Oil"
|
||||
rate = 0.2
|
||||
impact = "minimal"
|
||||
else:
|
||||
treatment = "fertilizer"
|
||||
product = "NPK 20-20-20"
|
||||
rate = 0.4
|
||||
impact = "positive"
|
||||
|
||||
# Calculate target zones based on affected area
|
||||
affected_area = field_data.get("affected_area", 0)
|
||||
if affected_area > 0:
|
||||
target_zones = [
|
||||
{
|
||||
"zone_id": "A1",
|
||||
"gps_boundary": [(40.71, -74.00), (40.72, -74.01)],
|
||||
"priority": "high"
|
||||
}
|
||||
]
|
||||
else:
|
||||
target_zones = []
|
||||
|
||||
return {
|
||||
"recommendation_id": f"SPR-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"field_id": field_data["field_id"],
|
||||
"treatment_type": treatment,
|
||||
"product_name": product,
|
||||
"application_rate": rate,
|
||||
"affected_area": affected_area,
|
||||
"target_zones": target_zones,
|
||||
"optimal_time": (datetime.now() + timedelta(days=1)).isoformat(),
|
||||
"weather_window": {
|
||||
"wind_speed": weather.get("wind_speed", 5),
|
||||
"precipitation": weather.get("precipitation", 0),
|
||||
"suitable": True
|
||||
},
|
||||
"cost_estimate": rate * affected_area * 50, # $/hectare
|
||||
"environmental_impact": impact
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def predict_crop_yield(field_id: str, crop_type: str, current_health: Dict, weather_forecast: Dict) -> Dict:
|
||||
"""Predict crop yield based on current conditions and forecasts"""
|
||||
# Simulate yield prediction
|
||||
health_level = current_health.get("health_level", "good")
|
||||
|
||||
base_yield = {
|
||||
"wheat": 3.5,
|
||||
"corn": 9.5,
|
||||
"soybeans": 2.8,
|
||||
"rice": 6.0
|
||||
}.get(crop_type, 5.0)
|
||||
|
||||
# Adjust based on health
|
||||
health_multiplier = {
|
||||
"excellent": 1.2,
|
||||
"good": 1.0,
|
||||
"fair": 0.8,
|
||||
"poor": 0.6,
|
||||
"critical": 0.4
|
||||
}.get(health_level, 1.0)
|
||||
|
||||
predicted_yield = base_yield * health_multiplier
|
||||
|
||||
# Quality grade based on conditions
|
||||
if health_level in ["excellent", "good"]:
|
||||
quality = "A"
|
||||
price_multiplier = 1.2
|
||||
elif health_level == "fair":
|
||||
quality = "B"
|
||||
price_multiplier = 1.0
|
||||
else:
|
||||
quality = "C"
|
||||
price_multiplier = 0.8
|
||||
|
||||
return {
|
||||
"forecast_id": f"YLD-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"field_id": field_id,
|
||||
"crop_type": crop_type,
|
||||
"predicted_yield": predicted_yield,
|
||||
"confidence_interval": (predicted_yield * 0.9, predicted_yield * 1.1),
|
||||
"harvest_window": (
|
||||
(datetime.now() + timedelta(days=60)).isoformat(),
|
||||
(datetime.now() + timedelta(days=75)).isoformat()
|
||||
),
|
||||
"quality_grade": quality,
|
||||
"market_price_estimate": predicted_yield * 250 * price_multiplier, # $/ton
|
||||
"risk_factors": ["weather_variability", "pest_pressure", "market_volatility"]
|
||||
}
|
||||
|
||||
|
||||
# Agriculture agent definitions
|
||||
multispectral_agent = Agent(
|
||||
name="MultispectralAnalyzer",
|
||||
instructions="""You are a remote sensing specialist for precision agriculture.
|
||||
Analyze multispectral imagery from drones and satellites.
|
||||
Calculate vegetation indices (NDVI, NDRE, CCCI) to assess crop health.
|
||||
Identify stress zones and anomalies in field conditions.
|
||||
SLA: Process imagery within 2 minutes per field.""",
|
||||
tools=[analyze_multispectral_imagery]
|
||||
)
|
||||
|
||||
disease_agent = Agent(
|
||||
name="DiseaseIdentifier",
|
||||
instructions="""You are a plant pathology expert with AI vision capabilities.
|
||||
Identify crop diseases, pests, and nutrient deficiencies.
|
||||
Assess severity levels and predict spread patterns.
|
||||
Consider environmental factors affecting disease development.
|
||||
SLA: Complete identification within 30 seconds.""",
|
||||
tools=[identify_pest_disease]
|
||||
)
|
||||
|
||||
spray_agent = Agent(
|
||||
name="SprayRecommender",
|
||||
instructions="""You are a precision application specialist.
|
||||
Recommend targeted spraying strategies for pest and disease control.
|
||||
Optimize chemical usage to minimize environmental impact.
|
||||
Consider weather windows and application regulations.
|
||||
SLA: Generate recommendations within 1 minute.""",
|
||||
tools=[calculate_spray_recommendation]
|
||||
)
|
||||
|
||||
yield_agent = Agent(
|
||||
name="YieldPredictor",
|
||||
instructions="""You are a crop yield forecasting specialist.
|
||||
Predict harvest yields based on current conditions and historical data.
|
||||
Assess crop quality grades and market value estimates.
|
||||
Identify risk factors that could impact final yield.
|
||||
SLA: Generate forecast within 45 seconds.""",
|
||||
tools=[predict_crop_yield]
|
||||
)
|
||||
|
||||
|
||||
# Precision agriculture workflow
|
||||
def precision_agriculture_workflow(field_ids: List[str], crop_type: str, weather_data: Dict):
|
||||
"""
|
||||
Complete precision agriculture workflow from monitoring to treatment
|
||||
Includes early warning system and sustainable farming practices
|
||||
"""
|
||||
|
||||
workflow_results = {
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"fields_monitored": len(field_ids),
|
||||
"alerts": [],
|
||||
"treatments_needed": [],
|
||||
"yield_forecasts": [],
|
||||
"sustainability_score": 0.0
|
||||
}
|
||||
|
||||
for field_id in field_ids:
|
||||
try:
|
||||
# Step 1: Multispectral analysis
|
||||
spectral_analysis = multispectral_agent.start(
|
||||
f"Analyze multispectral imagery for field {field_id}"
|
||||
)
|
||||
|
||||
# Step 2: Disease and pest detection
|
||||
pest_report = disease_agent.start(
|
||||
f"Identify pests/diseases from spectral data: {spectral_analysis}"
|
||||
)
|
||||
|
||||
# Check for alerts
|
||||
if pest_report.get("severity") in ["high", "severe"]:
|
||||
workflow_results["alerts"].append({
|
||||
"field_id": field_id,
|
||||
"type": "pest_disease_alert",
|
||||
"severity": pest_report["severity"],
|
||||
"pest": pest_report.get("pest_type"),
|
||||
"disease": pest_report.get("disease_type"),
|
||||
"action": "immediate_treatment_required"
|
||||
})
|
||||
|
||||
# Step 3: Generate spray recommendation
|
||||
spray_recommendation = spray_agent.start(
|
||||
f"Calculate spray strategy for pest report: {pest_report}, "
|
||||
f"field: {spectral_analysis}, weather: {weather_data}"
|
||||
)
|
||||
workflow_results["treatments_needed"].append(spray_recommendation)
|
||||
|
||||
# Step 4: Yield prediction
|
||||
yield_forecast = yield_agent.start(
|
||||
f"Predict yield for field {field_id}, crop {crop_type}, "
|
||||
f"health: {spectral_analysis}, weather: {weather_data}"
|
||||
)
|
||||
workflow_results["yield_forecasts"].append(yield_forecast)
|
||||
|
||||
except Exception as e:
|
||||
# Fallback: Schedule manual inspection
|
||||
workflow_results["alerts"].append({
|
||||
"field_id": field_id,
|
||||
"type": "monitoring_failure",
|
||||
"error": str(e),
|
||||
"action": "schedule_manual_inspection"
|
||||
})
|
||||
|
||||
# Calculate sustainability score
|
||||
total_chemical = sum(
|
||||
t.get("application_rate", 0) * t.get("affected_area", 0)
|
||||
for t in workflow_results["treatments_needed"]
|
||||
)
|
||||
workflow_results["sustainability_score"] = max(0, 100 - (total_chemical * 10))
|
||||
|
||||
return workflow_results
|
||||
|
||||
|
||||
# Sustainable farming patterns
|
||||
class SustainableFarmingPatterns:
|
||||
"""
|
||||
Patterns for sustainable and regenerative agriculture
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def integrated_pest_management(pest_level: str) -> Dict:
|
||||
"""IPM strategy based on pest pressure"""
|
||||
strategies = {
|
||||
"low": {
|
||||
"method": "biological_control",
|
||||
"actions": ["release_beneficial_insects", "plant_trap_crops"],
|
||||
"chemical_use": 0
|
||||
},
|
||||
"moderate": {
|
||||
"method": "targeted_intervention",
|
||||
"actions": ["spot_treatment", "pheromone_traps", "minimal_spray"],
|
||||
"chemical_use": 30
|
||||
},
|
||||
"high": {
|
||||
"method": "integrated_approach",
|
||||
"actions": ["systematic_spray", "crop_rotation", "resistant_varieties"],
|
||||
"chemical_use": 70
|
||||
}
|
||||
}
|
||||
return strategies.get(pest_level, strategies["moderate"])
|
||||
|
||||
@staticmethod
|
||||
def precision_irrigation(moisture_level: float, crop_stage: str) -> Dict:
|
||||
"""Calculate optimal irrigation based on soil moisture and crop stage"""
|
||||
# Water requirements by growth stage (mm/day)
|
||||
stage_requirements = {
|
||||
"germination": 3.0,
|
||||
"vegetative": 5.0,
|
||||
"flowering": 7.0,
|
||||
"grain_filling": 6.0,
|
||||
"maturation": 2.0
|
||||
}
|
||||
|
||||
required = stage_requirements.get(crop_stage, 5.0)
|
||||
deficit = max(0, 40 - moisture_level) # Target 40% moisture
|
||||
|
||||
return {
|
||||
"irrigation_needed": deficit > 10,
|
||||
"amount_mm": deficit * 2,
|
||||
"method": "drip" if deficit < 20 else "sprinkler",
|
||||
"schedule": "night_irrigation" if deficit > 15 else "morning_irrigation",
|
||||
"water_saved": (100 - deficit) / 100 * 1000 # Liters per hectare
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def crop_rotation_optimizer(current_crop: str, soil_data: Dict) -> str:
|
||||
"""Recommend next crop for rotation based on soil health"""
|
||||
rotations = {
|
||||
"wheat": ["soybeans", "canola"], # Nitrogen fixation
|
||||
"corn": ["soybeans", "alfalfa"], # Break disease cycle
|
||||
"soybeans": ["wheat", "corn"], # Utilize fixed nitrogen
|
||||
"rice": ["legumes", "vegetables"], # Soil structure improvement
|
||||
}
|
||||
|
||||
return rotations.get(current_crop, ["cover_crops"])[0]
|
||||
|
||||
|
||||
# IoT sensor integration patterns
|
||||
class IoTSensorPatterns:
|
||||
"""
|
||||
Patterns for integrating IoT sensors in smart farming
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def create_sensor_network_agent(sensor_types: List[str]) -> Agent:
|
||||
"""Create agent for managing IoT sensor networks"""
|
||||
return Agent(
|
||||
name="SensorNetworkManager",
|
||||
instructions=f"""Manage IoT sensor network with {', '.join(sensor_types)}.
|
||||
Collect real-time data from field sensors.
|
||||
Detect sensor anomalies and maintenance needs.
|
||||
Aggregate data for precision agriculture decisions.
|
||||
SLA: Data collection every 15 minutes."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def process_sensor_data(sensor_readings: List[Dict]) -> Dict:
|
||||
"""Process and aggregate IoT sensor data"""
|
||||
aggregated = {
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"sensor_count": len(sensor_readings),
|
||||
"averages": {},
|
||||
"alerts": []
|
||||
}
|
||||
|
||||
# Calculate averages
|
||||
for reading in sensor_readings:
|
||||
for key, value in reading.items():
|
||||
if isinstance(value, (int, float)):
|
||||
if key not in aggregated["averages"]:
|
||||
aggregated["averages"][key] = []
|
||||
aggregated["averages"][key].append(value)
|
||||
|
||||
# Convert to means
|
||||
for key in aggregated["averages"]:
|
||||
values = aggregated["averages"][key]
|
||||
aggregated["averages"][key] = sum(values) / len(values)
|
||||
|
||||
# Check for anomalies
|
||||
if key == "soil_ph" and (aggregated["averages"][key] < 6.0 or aggregated["averages"][key] > 7.5):
|
||||
aggregated["alerts"].append({
|
||||
"type": "soil_ph_anomaly",
|
||||
"value": aggregated["averages"][key],
|
||||
"action": "adjust_soil_treatment"
|
||||
})
|
||||
|
||||
return aggregated
|
||||
|
||||
|
||||
# Example usage
|
||||
if __name__ == "__main__":
|
||||
# Monitor multiple fields
|
||||
fields = ["FIELD-001", "FIELD-002", "FIELD-003"]
|
||||
weather = {
|
||||
"temperature": 25,
|
||||
"humidity": 60,
|
||||
"wind_speed": 8,
|
||||
"precipitation": 0,
|
||||
"forecast": "partly_cloudy"
|
||||
}
|
||||
|
||||
result = precision_agriculture_workflow(fields, "wheat", weather)
|
||||
print("Agriculture workflow result:", result)
|
||||
|
||||
# Sustainable farming example
|
||||
ipm_strategy = SustainableFarmingPatterns.integrated_pest_management("moderate")
|
||||
print("IPM Strategy:", ipm_strategy)
|
||||
|
||||
irrigation_plan = SustainableFarmingPatterns.precision_irrigation(25.0, "flowering")
|
||||
print("Irrigation Plan:", irrigation_plan)
|
||||
|
||||
next_crop = SustainableFarmingPatterns.crop_rotation_optimizer("wheat", {})
|
||||
print("Recommended next crop:", next_crop)
|
||||
|
||||
# IoT integration example
|
||||
sensor_agent = IoTSensorPatterns.create_sensor_network_agent(
|
||||
["soil_moisture", "temperature", "humidity", "light", "ph"]
|
||||
)
|
||||
|
||||
sensor_data = [
|
||||
{"sensor_id": "S001", "soil_moisture": 35, "temperature": 24, "soil_ph": 6.8},
|
||||
{"sensor_id": "S002", "soil_moisture": 32, "temperature": 25, "soil_ph": 7.2},
|
||||
{"sensor_id": "S003", "soil_moisture": 38, "temperature": 23, "soil_ph": 5.8}
|
||||
]
|
||||
|
||||
processed_data = IoTSensorPatterns.process_sensor_data(sensor_data)
|
||||
print("Processed sensor data:", processed_data)
|
||||
@@ -1,372 +0,0 @@
|
||||
"""
|
||||
Energy Industry Template
|
||||
========================
|
||||
Wind farm monitoring and power optimization workflow
|
||||
Based on SRAO Framework patterns with predictive maintenance
|
||||
|
||||
Key agents:
|
||||
- SCADAReader: Processes SCADA telemetry data
|
||||
- VibrationAnalyzer: Analyzes turbine vibration patterns
|
||||
- PowerForecaster: Predicts power generation
|
||||
- MaintenanceScheduler: Schedules predictive maintenance
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, tool
|
||||
from typing import Dict, List, Any, Optional
|
||||
from pydantic import BaseModel
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
|
||||
# I/O Schemas
|
||||
class TurbineData(BaseModel):
|
||||
"""Wind turbine telemetry data"""
|
||||
turbine_id: str
|
||||
timestamp: str
|
||||
wind_speed: float # m/s
|
||||
power_output: float # MW
|
||||
rotor_speed: float # RPM
|
||||
blade_pitch: float # degrees
|
||||
nacelle_temperature: float # Celsius
|
||||
vibration_level: float # mm/s
|
||||
operational_status: str # running, stopped, maintenance
|
||||
|
||||
|
||||
class VibrationAnalysis(BaseModel):
|
||||
"""Vibration analysis results"""
|
||||
turbine_id: str
|
||||
analysis_time: str
|
||||
vibration_rms: float
|
||||
frequency_peaks: List[float]
|
||||
anomaly_detected: bool
|
||||
failure_probability: float
|
||||
recommended_action: str
|
||||
|
||||
|
||||
class PowerForecast(BaseModel):
|
||||
"""Power generation forecast"""
|
||||
forecast_id: str
|
||||
start_time: str
|
||||
end_time: str
|
||||
predicted_output: List[float] # MW per hour
|
||||
confidence_interval: float
|
||||
weather_factors: Dict[str, Any]
|
||||
grid_demand: float
|
||||
|
||||
|
||||
class MaintenancePlan(BaseModel):
|
||||
"""Maintenance scheduling plan"""
|
||||
plan_id: str
|
||||
turbine_id: str
|
||||
maintenance_type: str # preventive, predictive, corrective
|
||||
scheduled_date: str
|
||||
estimated_duration: int # hours
|
||||
required_parts: List[str]
|
||||
technician_team: str
|
||||
production_loss: float # MW
|
||||
|
||||
|
||||
# Tools for energy management
|
||||
@tool
|
||||
def read_scada_telemetry(turbine_id: str, time_range: str = "last_hour") -> Dict:
|
||||
"""Read SCADA system telemetry for wind turbines"""
|
||||
# Simulate SCADA data reading
|
||||
return {
|
||||
"turbine_id": turbine_id,
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"wind_speed": 12.5,
|
||||
"power_output": 2.3,
|
||||
"rotor_speed": 16.8,
|
||||
"blade_pitch": 8.5,
|
||||
"nacelle_temperature": 45.2,
|
||||
"vibration_level": 3.2,
|
||||
"operational_status": "running"
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def analyze_vibration_patterns(turbine_data: Dict) -> Dict:
|
||||
"""Analyze vibration patterns for early fault detection"""
|
||||
# Simulate vibration analysis
|
||||
vibration_level = turbine_data.get("vibration_level", 0)
|
||||
anomaly = vibration_level > 5.0 # Threshold for anomaly
|
||||
|
||||
return {
|
||||
"turbine_id": turbine_data["turbine_id"],
|
||||
"analysis_time": datetime.now().isoformat(),
|
||||
"vibration_rms": vibration_level,
|
||||
"frequency_peaks": [10.5, 25.3, 50.0], # Hz
|
||||
"anomaly_detected": anomaly,
|
||||
"failure_probability": min(vibration_level / 10.0, 1.0),
|
||||
"recommended_action": "immediate_inspection" if anomaly else "continue_monitoring"
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def forecast_power_generation(weather_data: Dict, historical_data: List) -> Dict:
|
||||
"""Forecast power generation based on weather and historical patterns"""
|
||||
# Simulate power forecasting
|
||||
base_forecast = [2.0 + (i * 0.1) for i in range(24)] # 24-hour forecast
|
||||
|
||||
return {
|
||||
"forecast_id": f"FCST-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"start_time": datetime.now().isoformat(),
|
||||
"end_time": (datetime.now() + timedelta(hours=24)).isoformat(),
|
||||
"predicted_output": base_forecast,
|
||||
"confidence_interval": 0.85,
|
||||
"weather_factors": weather_data,
|
||||
"grid_demand": sum(base_forecast)
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def schedule_maintenance(turbine_id: str, maintenance_type: str, urgency: str = "normal") -> Dict:
|
||||
"""Schedule maintenance based on condition monitoring"""
|
||||
# Calculate maintenance window
|
||||
if urgency == "urgent":
|
||||
scheduled_date = (datetime.now() + timedelta(days=1)).isoformat()
|
||||
else:
|
||||
scheduled_date = (datetime.now() + timedelta(days=7)).isoformat()
|
||||
|
||||
return {
|
||||
"plan_id": f"MNT-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"turbine_id": turbine_id,
|
||||
"maintenance_type": maintenance_type,
|
||||
"scheduled_date": scheduled_date,
|
||||
"estimated_duration": 4,
|
||||
"required_parts": ["bearing_set", "lubricant", "filter"],
|
||||
"technician_team": "Team-A",
|
||||
"production_loss": 8.0 # MW lost during maintenance
|
||||
}
|
||||
|
||||
|
||||
# Agent Definitions with SLA requirements
|
||||
scada_reader = Agent(
|
||||
name="SCADAReader",
|
||||
instructions="""You are a SCADA system specialist for wind farms.
|
||||
Process real-time telemetry data from wind turbines.
|
||||
Identify operational anomalies and performance deviations.
|
||||
SLA: Process telemetry within 1 second for real-time monitoring.""",
|
||||
tools=[read_scada_telemetry]
|
||||
)
|
||||
|
||||
vibration_analyzer = Agent(
|
||||
name="VibrationAnalyzer",
|
||||
instructions="""You are a vibration analysis expert for rotating machinery.
|
||||
Analyze vibration patterns to detect early signs of mechanical failure.
|
||||
Use FFT analysis and pattern recognition for fault diagnosis.
|
||||
SLA: Complete analysis within 5 seconds per turbine.""",
|
||||
tools=[analyze_vibration_patterns]
|
||||
)
|
||||
|
||||
power_forecaster = Agent(
|
||||
name="PowerForecaster",
|
||||
instructions="""You are a power generation forecasting specialist.
|
||||
Predict power output based on weather forecasts and historical patterns.
|
||||
Consider grid demand and optimize generation schedules.
|
||||
SLA: Generate 24-hour forecast within 30 seconds.""",
|
||||
tools=[forecast_power_generation]
|
||||
)
|
||||
|
||||
maintenance_scheduler = Agent(
|
||||
name="MaintenanceScheduler",
|
||||
instructions="""You are a predictive maintenance planning expert.
|
||||
Schedule maintenance based on condition monitoring and failure predictions.
|
||||
Minimize production loss while ensuring turbine reliability.
|
||||
SLA: Create maintenance plan within 1 minute.""",
|
||||
tools=[schedule_maintenance]
|
||||
)
|
||||
|
||||
|
||||
# Energy workflow with grid integration
|
||||
def energy_monitoring_workflow(turbine_ids: List[str], weather_forecast: Dict):
|
||||
"""
|
||||
Complete energy monitoring and optimization workflow
|
||||
Includes predictive maintenance and grid integration
|
||||
"""
|
||||
|
||||
results = {
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"turbines_monitored": len(turbine_ids),
|
||||
"alerts": [],
|
||||
"maintenance_required": [],
|
||||
"power_forecast": None
|
||||
}
|
||||
|
||||
# Step 1: Monitor all turbines
|
||||
for turbine_id in turbine_ids:
|
||||
try:
|
||||
# Read SCADA data
|
||||
scada_data = scada_reader.start(
|
||||
f"Read telemetry for turbine {turbine_id}"
|
||||
)
|
||||
|
||||
# Analyze vibrations
|
||||
vibration_result = vibration_analyzer.start(
|
||||
f"Analyze vibrations for data: {scada_data}"
|
||||
)
|
||||
|
||||
# Check for anomalies
|
||||
if vibration_result.get("anomaly_detected"):
|
||||
results["alerts"].append({
|
||||
"turbine_id": turbine_id,
|
||||
"type": "vibration_anomaly",
|
||||
"severity": "high" if vibration_result.get("failure_probability", 0) > 0.7 else "medium"
|
||||
})
|
||||
|
||||
# Schedule maintenance if needed
|
||||
maintenance_plan = maintenance_scheduler.start(
|
||||
f"Schedule maintenance for turbine {turbine_id} with urgency based on {vibration_result}"
|
||||
)
|
||||
results["maintenance_required"].append(maintenance_plan)
|
||||
|
||||
except Exception as e:
|
||||
# Fallback: Mark turbine for manual inspection
|
||||
results["alerts"].append({
|
||||
"turbine_id": turbine_id,
|
||||
"type": "monitoring_failure",
|
||||
"error": str(e),
|
||||
"action": "manual_inspection_required"
|
||||
})
|
||||
|
||||
# Step 2: Power generation forecast
|
||||
try:
|
||||
historical_data = [] # Would be fetched from database
|
||||
power_forecast = power_forecaster.start(
|
||||
f"Forecast power with weather {weather_forecast} and history {historical_data}"
|
||||
)
|
||||
results["power_forecast"] = power_forecast
|
||||
|
||||
# Grid integration check
|
||||
if power_forecast.get("predicted_output"):
|
||||
total_predicted = sum(power_forecast["predicted_output"])
|
||||
grid_demand = power_forecast.get("grid_demand", 0)
|
||||
|
||||
if total_predicted < grid_demand * 0.9:
|
||||
results["alerts"].append({
|
||||
"type": "supply_shortage",
|
||||
"predicted": total_predicted,
|
||||
"demand": grid_demand,
|
||||
"action": "consider_backup_sources"
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
# Fallback: Use conservative forecast
|
||||
results["power_forecast"] = {
|
||||
"status": "fallback_mode",
|
||||
"conservative_estimate": len(turbine_ids) * 1.5, # MW
|
||||
"error": str(e)
|
||||
}
|
||||
|
||||
return results
|
||||
|
||||
|
||||
# Cross-industry pattern adaptation
|
||||
class EnergyPatternAdapter:
|
||||
"""
|
||||
Adapts manufacturing patterns for energy sector
|
||||
Demonstrates 70% code reuse across industries
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def adapt_for_solar_farm():
|
||||
"""Adapt wind farm agents for solar farm monitoring"""
|
||||
return Agent(
|
||||
name="SolarMonitor",
|
||||
instructions="""Monitor solar panel efficiency and temperature.
|
||||
Track irradiance levels and predict power output.
|
||||
Detect panel degradation and soiling issues.
|
||||
SLA: Real-time monitoring with 2-second updates."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def adapt_for_power_grid():
|
||||
"""Adapt for power grid management"""
|
||||
return Agent(
|
||||
name="GridBalancer",
|
||||
instructions="""Balance power supply and demand across the grid.
|
||||
Manage load distribution and prevent blackouts.
|
||||
Coordinate with renewable and traditional sources.
|
||||
SLA: Sub-second response for grid stability."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def adapt_for_battery_storage():
|
||||
"""Adapt for battery energy storage systems"""
|
||||
return Agent(
|
||||
name="BatteryOptimizer",
|
||||
instructions="""Optimize battery charge/discharge cycles.
|
||||
Predict battery degradation and schedule replacements.
|
||||
Maximize energy arbitrage opportunities.
|
||||
SLA: Optimization decision within 10 seconds."""
|
||||
)
|
||||
|
||||
|
||||
# Fallback strategies for critical operations
|
||||
class EnergyFallbackStrategies:
|
||||
"""
|
||||
Fallback strategies for maintaining grid stability
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def turbine_failure_fallback(failed_turbine_id: str, available_turbines: List[str]):
|
||||
"""Handle turbine failure by redistributing load"""
|
||||
return {
|
||||
"strategy": "load_redistribution",
|
||||
"failed_turbine": failed_turbine_id,
|
||||
"compensating_turbines": available_turbines[:3], # Use top 3 turbines
|
||||
"increase_output_by": 0.3, # MW per turbine
|
||||
"duration": "until_maintenance_complete"
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def forecast_failure_fallback(last_known_forecast: Optional[Dict]):
|
||||
"""Handle forecasting system failure"""
|
||||
if last_known_forecast:
|
||||
return {
|
||||
"strategy": "use_last_known",
|
||||
"forecast": last_known_forecast,
|
||||
"confidence": 0.6,
|
||||
"validity": "4_hours"
|
||||
}
|
||||
else:
|
||||
return {
|
||||
"strategy": "seasonal_average",
|
||||
"estimated_output": 50.0, # MW based on seasonal average
|
||||
"confidence": 0.4,
|
||||
"recommendation": "increase_reserves"
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def communication_failure_fallback():
|
||||
"""Handle SCADA communication failure"""
|
||||
return {
|
||||
"strategy": "local_control_mode",
|
||||
"actions": [
|
||||
"Switch turbines to autonomous mode",
|
||||
"Use local safety thresholds",
|
||||
"Log data locally for later sync",
|
||||
"Alert maintenance teams"
|
||||
],
|
||||
"recovery_check_interval": 300 # seconds
|
||||
}
|
||||
|
||||
|
||||
# Example usage
|
||||
if __name__ == "__main__":
|
||||
# Monitor wind farm
|
||||
turbine_list = [f"WT-{i:03d}" for i in range(1, 11)] # 10 turbines
|
||||
weather = {"wind_speed": 14.0, "direction": "NW", "temperature": 15.0}
|
||||
|
||||
result = energy_monitoring_workflow(turbine_list, weather)
|
||||
print("Energy monitoring result:", result)
|
||||
|
||||
# Demonstrate cross-industry adaptation
|
||||
solar_monitor = EnergyPatternAdapter.adapt_for_solar_farm()
|
||||
grid_balancer = EnergyPatternAdapter.adapt_for_power_grid()
|
||||
battery_optimizer = EnergyPatternAdapter.adapt_for_battery_storage()
|
||||
|
||||
# Fallback examples
|
||||
turbine_fallback = EnergyFallbackStrategies.turbine_failure_fallback(
|
||||
"WT-003", ["WT-001", "WT-002", "WT-004", "WT-005"]
|
||||
)
|
||||
print("Turbine failure fallback:", turbine_fallback)
|
||||
@@ -1,478 +0,0 @@
|
||||
"""
|
||||
Healthcare Industry Template
|
||||
============================
|
||||
Emergency triage and patient care coordination workflow
|
||||
Based on SRAO Framework with HIPAA-compliant patterns
|
||||
|
||||
Key agents:
|
||||
- VitalSignsCapture: Processes patient vital signs
|
||||
- EMRRetrieval: Retrieves electronic medical records
|
||||
- TriageRecommendation: Provides triage recommendations
|
||||
- ResourceAllocator: Manages hospital resource allocation
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, tool
|
||||
from typing import Dict, List, Any, Optional
|
||||
from pydantic import BaseModel
|
||||
from datetime import datetime
|
||||
from enum import Enum
|
||||
|
||||
|
||||
# Triage levels following Emergency Severity Index (ESI)
|
||||
class TriageLevel(str, Enum):
|
||||
RESUSCITATION = "1_resuscitation" # Immediate life-saving intervention
|
||||
EMERGENT = "2_emergent" # High risk, severe pain/distress
|
||||
URGENT = "3_urgent" # Stable but needs multiple resources
|
||||
LESS_URGENT = "4_less_urgent" # Stable, one resource needed
|
||||
NON_URGENT = "5_non_urgent" # Stable, no resources needed
|
||||
|
||||
|
||||
# I/O Schemas
|
||||
class VitalSigns(BaseModel):
|
||||
"""Patient vital signs data"""
|
||||
patient_id: str
|
||||
timestamp: str
|
||||
heart_rate: int # bpm
|
||||
blood_pressure_systolic: int # mmHg
|
||||
blood_pressure_diastolic: int # mmHg
|
||||
respiratory_rate: int # breaths/min
|
||||
temperature: float # Celsius
|
||||
oxygen_saturation: int # percentage
|
||||
pain_scale: int # 0-10
|
||||
consciousness_level: str # alert, verbal, pain, unresponsive (AVPU)
|
||||
|
||||
|
||||
class MedicalHistory(BaseModel):
|
||||
"""Patient medical history from EMR"""
|
||||
patient_id: str
|
||||
allergies: List[str]
|
||||
chronic_conditions: List[str]
|
||||
current_medications: List[Dict[str, str]]
|
||||
recent_visits: List[Dict[str, Any]]
|
||||
emergency_contacts: List[Dict[str, str]]
|
||||
insurance_status: str
|
||||
|
||||
|
||||
class TriageAssessment(BaseModel):
|
||||
"""Triage assessment and recommendations"""
|
||||
assessment_id: str
|
||||
patient_id: str
|
||||
triage_level: TriageLevel
|
||||
chief_complaint: str
|
||||
recommended_department: str
|
||||
estimated_wait_time: int # minutes
|
||||
required_resources: List[str]
|
||||
clinical_notes: str
|
||||
red_flags: List[str]
|
||||
|
||||
|
||||
class ResourceAllocation(BaseModel):
|
||||
"""Hospital resource allocation"""
|
||||
allocation_id: str
|
||||
patient_id: str
|
||||
assigned_bed: Optional[str]
|
||||
assigned_staff: List[str]
|
||||
equipment_needed: List[str]
|
||||
department: str
|
||||
priority_score: float
|
||||
estimated_treatment_time: int # minutes
|
||||
|
||||
|
||||
# Healthcare-specific tools
|
||||
@tool
|
||||
def capture_vital_signs(patient_id: str) -> Dict:
|
||||
"""Capture patient vital signs from monitoring devices"""
|
||||
# Simulate vital signs capture
|
||||
return {
|
||||
"patient_id": patient_id,
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"heart_rate": 78,
|
||||
"blood_pressure_systolic": 130,
|
||||
"blood_pressure_diastolic": 85,
|
||||
"respiratory_rate": 16,
|
||||
"temperature": 37.2,
|
||||
"oxygen_saturation": 98,
|
||||
"pain_scale": 6,
|
||||
"consciousness_level": "alert"
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def retrieve_medical_history(patient_id: str, consent_verified: bool = True) -> Dict:
|
||||
"""Retrieve patient medical history from EMR system"""
|
||||
if not consent_verified:
|
||||
return {"error": "consent_required", "message": "Patient consent required for EMR access"}
|
||||
|
||||
# Simulate EMR retrieval
|
||||
return {
|
||||
"patient_id": patient_id,
|
||||
"allergies": ["penicillin", "latex"],
|
||||
"chronic_conditions": ["hypertension", "diabetes_type2"],
|
||||
"current_medications": [
|
||||
{"name": "metformin", "dose": "500mg", "frequency": "twice daily"},
|
||||
{"name": "lisinopril", "dose": "10mg", "frequency": "once daily"}
|
||||
],
|
||||
"recent_visits": [
|
||||
{"date": "2024-02-15", "reason": "routine_checkup", "department": "primary_care"}
|
||||
],
|
||||
"emergency_contacts": [
|
||||
{"name": "Jane Doe", "relationship": "spouse", "phone": "555-0123"}
|
||||
],
|
||||
"insurance_status": "active"
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def calculate_triage_priority(vital_signs: Dict, medical_history: Dict, chief_complaint: str) -> Dict:
|
||||
"""Calculate triage priority based on clinical indicators"""
|
||||
# Simulate triage algorithm
|
||||
priority_score = 0
|
||||
red_flags = []
|
||||
|
||||
# Check vital signs
|
||||
if vital_signs["heart_rate"] > 120 or vital_signs["heart_rate"] < 50:
|
||||
priority_score += 3
|
||||
red_flags.append("abnormal_heart_rate")
|
||||
|
||||
if vital_signs["oxygen_saturation"] < 92:
|
||||
priority_score += 4
|
||||
red_flags.append("low_oxygen")
|
||||
|
||||
if vital_signs["consciousness_level"] != "alert":
|
||||
priority_score += 5
|
||||
red_flags.append("altered_consciousness")
|
||||
|
||||
# Determine triage level
|
||||
if priority_score >= 8:
|
||||
triage_level = TriageLevel.RESUSCITATION
|
||||
department = "emergency"
|
||||
wait_time = 0
|
||||
elif priority_score >= 5:
|
||||
triage_level = TriageLevel.EMERGENT
|
||||
department = "emergency"
|
||||
wait_time = 10
|
||||
elif priority_score >= 3:
|
||||
triage_level = TriageLevel.URGENT
|
||||
department = "urgent_care"
|
||||
wait_time = 30
|
||||
else:
|
||||
triage_level = TriageLevel.LESS_URGENT
|
||||
department = "primary_care"
|
||||
wait_time = 60
|
||||
|
||||
return {
|
||||
"assessment_id": f"TRG-{datetime.now().strftime('%Y%m%d%H%M%S')}",
|
||||
"patient_id": vital_signs["patient_id"],
|
||||
"triage_level": triage_level.value,
|
||||
"chief_complaint": chief_complaint,
|
||||
"recommended_department": department,
|
||||
"estimated_wait_time": wait_time,
|
||||
"required_resources": ["physician", "nurse", "monitoring"],
|
||||
"clinical_notes": f"Priority score: {priority_score}",
|
||||
"red_flags": red_flags
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def allocate_resources(patient_id: str, triage_level: str, department: str) -> Dict:
|
||||
"""Allocate hospital resources based on triage assessment"""
|
||||
# Simulate resource allocation
|
||||
if "resuscitation" in triage_level:
|
||||
bed = "ER-01"
|
||||
staff = ["Dr. Smith", "Nurse Johnson", "Nurse Williams"]
|
||||
equipment = ["cardiac_monitor", "defibrillator", "crash_cart"]
|
||||
priority = 10.0
|
||||
elif "emergent" in triage_level:
|
||||
bed = "ER-05"
|
||||
staff = ["Dr. Brown", "Nurse Davis"]
|
||||
equipment = ["vital_signs_monitor", "IV_pump"]
|
||||
priority = 8.0
|
||||
else:
|
||||
bed = "UC-12"
|
||||
staff = ["PA Miller", "Nurse Garcia"]
|
||||
equipment = ["basic_monitor"]
|
||||
priority = 5.0
|
||||
|
||||
return {
|
||||
"allocation_id": f"RES-{datetime.now().strftime('%Y%m%d%H%M%S')}",
|
||||
"patient_id": patient_id,
|
||||
"assigned_bed": bed,
|
||||
"assigned_staff": staff,
|
||||
"equipment_needed": equipment,
|
||||
"department": department,
|
||||
"priority_score": priority,
|
||||
"estimated_treatment_time": 45
|
||||
}
|
||||
|
||||
|
||||
# Healthcare agent definitions with SLA requirements
|
||||
vital_signs_agent = Agent(
|
||||
name="VitalSignsCapture",
|
||||
instructions="""You are a clinical vital signs specialist.
|
||||
Capture and interpret patient vital signs from various monitoring devices.
|
||||
Identify abnormal values and trends that require immediate attention.
|
||||
Follow HIPAA guidelines for patient data handling.
|
||||
SLA: Capture and process within 30 seconds.""",
|
||||
tools=[capture_vital_signs]
|
||||
)
|
||||
|
||||
emr_agent = Agent(
|
||||
name="EMRRetrieval",
|
||||
instructions="""You are an EMR system specialist with HIPAA compliance expertise.
|
||||
Retrieve relevant patient medical history while ensuring data privacy.
|
||||
Verify patient consent and maintain audit trails.
|
||||
Highlight relevant allergies and contraindications.
|
||||
SLA: Retrieve records within 5 seconds.""",
|
||||
tools=[retrieve_medical_history]
|
||||
)
|
||||
|
||||
triage_agent = Agent(
|
||||
name="TriageRecommendation",
|
||||
instructions="""You are an emergency triage specialist following ESI guidelines.
|
||||
Assess patient severity and provide triage recommendations.
|
||||
Consider vital signs, medical history, and presenting symptoms.
|
||||
Identify red flags that require immediate intervention.
|
||||
SLA: Complete assessment within 1 minute.""",
|
||||
tools=[calculate_triage_priority]
|
||||
)
|
||||
|
||||
resource_agent = Agent(
|
||||
name="ResourceAllocator",
|
||||
instructions="""You are a hospital resource management specialist.
|
||||
Allocate beds, staff, and equipment based on patient needs and priority.
|
||||
Optimize resource utilization while maintaining quality of care.
|
||||
Coordinate between departments for efficient patient flow.
|
||||
SLA: Allocate resources within 30 seconds.""",
|
||||
tools=[allocate_resources]
|
||||
)
|
||||
|
||||
|
||||
# Healthcare workflow with safety protocols
|
||||
def emergency_triage_workflow(patient_id: str, chief_complaint: str):
|
||||
"""
|
||||
Complete emergency triage workflow from arrival to resource allocation
|
||||
Includes safety checks and fallback protocols
|
||||
"""
|
||||
|
||||
workflow_result = {
|
||||
"patient_id": patient_id,
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"status": "in_progress",
|
||||
"safety_checks": [],
|
||||
"clinical_pathway": []
|
||||
}
|
||||
|
||||
# Step 1: Vital signs capture with validation
|
||||
try:
|
||||
vital_signs = vital_signs_agent.start(
|
||||
f"Capture vital signs for patient {patient_id}"
|
||||
)
|
||||
workflow_result["clinical_pathway"].append({
|
||||
"step": "vital_signs",
|
||||
"status": "completed",
|
||||
"data": vital_signs
|
||||
})
|
||||
|
||||
# Safety check: Validate vital signs are within possible ranges
|
||||
if vital_signs.get("heart_rate", 0) < 20 or vital_signs.get("heart_rate", 0) > 300:
|
||||
workflow_result["safety_checks"].append({
|
||||
"type": "vital_signs_validation",
|
||||
"issue": "impossible_heart_rate",
|
||||
"action": "manual_verification_required"
|
||||
})
|
||||
except Exception as e:
|
||||
# Fallback: Manual vital signs entry
|
||||
workflow_result["clinical_pathway"].append({
|
||||
"step": "vital_signs",
|
||||
"status": "manual_entry_required",
|
||||
"error": str(e)
|
||||
})
|
||||
vital_signs = {"manual_entry": True}
|
||||
|
||||
# Step 2: EMR retrieval with consent check
|
||||
try:
|
||||
medical_history = emr_agent.start(
|
||||
f"Retrieve medical history for patient {patient_id} with verified consent"
|
||||
)
|
||||
workflow_result["clinical_pathway"].append({
|
||||
"step": "emr_retrieval",
|
||||
"status": "completed",
|
||||
"records_retrieved": True
|
||||
})
|
||||
|
||||
# Safety check: Allergy alerts
|
||||
if medical_history.get("allergies"):
|
||||
workflow_result["safety_checks"].append({
|
||||
"type": "allergy_alert",
|
||||
"allergies": medical_history["allergies"],
|
||||
"action": "notify_all_providers"
|
||||
})
|
||||
except Exception as e:
|
||||
# Fallback: Proceed with limited information
|
||||
medical_history = {
|
||||
"patient_id": patient_id,
|
||||
"allergies": [],
|
||||
"note": "EMR_unavailable_proceed_with_caution"
|
||||
}
|
||||
workflow_result["safety_checks"].append({
|
||||
"type": "emr_unavailable",
|
||||
"action": "collect_history_manually"
|
||||
})
|
||||
|
||||
# Step 3: Triage assessment
|
||||
try:
|
||||
triage_assessment = triage_agent.start(
|
||||
f"Assess triage for patient with vitals {vital_signs}, "
|
||||
f"history {medical_history}, complaint: {chief_complaint}"
|
||||
)
|
||||
workflow_result["clinical_pathway"].append({
|
||||
"step": "triage_assessment",
|
||||
"status": "completed",
|
||||
"triage_level": triage_assessment.get("triage_level")
|
||||
})
|
||||
|
||||
# Safety check: Red flags requiring immediate action
|
||||
if triage_assessment.get("red_flags"):
|
||||
workflow_result["safety_checks"].append({
|
||||
"type": "clinical_red_flags",
|
||||
"flags": triage_assessment["red_flags"],
|
||||
"action": "immediate_physician_notification"
|
||||
})
|
||||
except Exception as e:
|
||||
# Fallback: Conservative triage (assume urgent)
|
||||
triage_assessment = {
|
||||
"triage_level": TriageLevel.URGENT.value,
|
||||
"recommended_department": "emergency",
|
||||
"fallback": True
|
||||
}
|
||||
|
||||
# Step 4: Resource allocation
|
||||
try:
|
||||
resource_allocation = resource_agent.start(
|
||||
f"Allocate resources for patient {patient_id} "
|
||||
f"with triage {triage_assessment.get('triage_level')} "
|
||||
f"to {triage_assessment.get('recommended_department')}"
|
||||
)
|
||||
workflow_result["clinical_pathway"].append({
|
||||
"step": "resource_allocation",
|
||||
"status": "completed",
|
||||
"bed_assigned": resource_allocation.get("assigned_bed"),
|
||||
"staff_assigned": resource_allocation.get("assigned_staff")
|
||||
})
|
||||
except Exception as e:
|
||||
# Fallback: Queue for next available
|
||||
workflow_result["clinical_pathway"].append({
|
||||
"step": "resource_allocation",
|
||||
"status": "queued",
|
||||
"queue_position": "next_available",
|
||||
"error": str(e)
|
||||
})
|
||||
|
||||
workflow_result["status"] = "completed"
|
||||
return workflow_result
|
||||
|
||||
|
||||
# HIPAA-compliant data handling patterns
|
||||
class HIPAACompliancePatterns:
|
||||
"""
|
||||
Reusable patterns for HIPAA-compliant healthcare workflows
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def anonymize_patient_data(data: Dict) -> Dict:
|
||||
"""Remove PHI for analytics and reporting"""
|
||||
safe_fields = ["triage_level", "department", "wait_time", "resource_type"]
|
||||
return {k: v for k, v in data.items() if k in safe_fields}
|
||||
|
||||
@staticmethod
|
||||
def audit_log_access(user_id: str, patient_id: str, action: str, reason: str):
|
||||
"""Create audit trail for EMR access"""
|
||||
return {
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"user_id": user_id,
|
||||
"patient_id": patient_id,
|
||||
"action": action,
|
||||
"reason": reason,
|
||||
"ip_address": "10.0.0.1", # Would be actual IP
|
||||
"session_id": "SEC-" + datetime.now().strftime('%Y%m%d%H%M%S')
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def encrypt_sensitive_data(data: Dict) -> Dict:
|
||||
"""Encrypt sensitive fields (placeholder for real encryption)"""
|
||||
sensitive_fields = ["ssn", "dob", "address", "phone"]
|
||||
encrypted = data.copy()
|
||||
for field in sensitive_fields:
|
||||
if field in encrypted:
|
||||
encrypted[field] = f"ENCRYPTED_{field.upper()}"
|
||||
return encrypted
|
||||
|
||||
|
||||
# Cross-department coordination patterns
|
||||
class HealthcareCoordinationPatterns:
|
||||
"""
|
||||
Patterns for coordinating across healthcare departments
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def coordinate_lab_orders(patient_id: str, triage_level: str) -> Agent:
|
||||
"""Create agent for lab order coordination"""
|
||||
return Agent(
|
||||
name="LabCoordinator",
|
||||
instructions=f"""Coordinate laboratory orders for patient {patient_id}.
|
||||
Priority level: {triage_level}.
|
||||
Ensure STAT orders for critical patients.
|
||||
Track specimen collection and result delivery.
|
||||
SLA: Order placement within 2 minutes."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def coordinate_radiology(patient_id: str, imaging_type: str) -> Agent:
|
||||
"""Create agent for radiology coordination"""
|
||||
return Agent(
|
||||
name="RadiologyCoordinator",
|
||||
instructions=f"""Schedule {imaging_type} imaging for patient {patient_id}.
|
||||
Check for contrast allergies and pregnancy status.
|
||||
Coordinate with transport for patient movement.
|
||||
SLA: Schedule within 5 minutes for urgent cases."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def coordinate_pharmacy(patient_id: str, medications: List[str]) -> Agent:
|
||||
"""Create agent for pharmacy coordination"""
|
||||
return Agent(
|
||||
name="PharmacyCoordinator",
|
||||
instructions=f"""Verify and dispense medications for patient {patient_id}.
|
||||
Check for drug interactions and allergies.
|
||||
Ensure proper dosing based on patient parameters.
|
||||
SLA: Medication verification within 3 minutes."""
|
||||
)
|
||||
|
||||
|
||||
# Example usage
|
||||
if __name__ == "__main__":
|
||||
# Process emergency patient
|
||||
patient_id = "PT-2024-00123"
|
||||
chief_complaint = "severe chest pain radiating to left arm"
|
||||
|
||||
result = emergency_triage_workflow(patient_id, chief_complaint)
|
||||
print("Triage workflow result:", result)
|
||||
|
||||
# Create specialized coordinators
|
||||
lab_coordinator = HealthcareCoordinationPatterns.coordinate_lab_orders(
|
||||
patient_id, TriageLevel.EMERGENT.value
|
||||
)
|
||||
|
||||
radiology_coordinator = HealthcareCoordinationPatterns.coordinate_radiology(
|
||||
patient_id, "chest_xray"
|
||||
)
|
||||
|
||||
pharmacy_coordinator = HealthcareCoordinationPatterns.coordinate_pharmacy(
|
||||
patient_id, ["aspirin", "nitroglycerin"]
|
||||
)
|
||||
|
||||
# HIPAA compliance example
|
||||
audit_log = HIPAACompliancePatterns.audit_log_access(
|
||||
"DR-001", patient_id, "EMR_ACCESS", "emergency_triage"
|
||||
)
|
||||
print("Audit log created:", audit_log)
|
||||
@@ -1,298 +0,0 @@
|
||||
"""
|
||||
Manufacturing Industry Template
|
||||
================================
|
||||
Order scheduling, inventory management, and quality inspection workflow
|
||||
Based on SRAO Framework patterns with 70% cross-industry reuse
|
||||
|
||||
Key agents:
|
||||
- ParseOrder: Extracts order details from various formats
|
||||
- CheckInventory: Validates material availability
|
||||
- OptimizeSchedule: Optimizes production scheduling
|
||||
- DefectDetect: Quality control and defect detection
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, tool
|
||||
from typing import Dict, List, Any
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
# I/O Schemas
|
||||
class OrderDetails(BaseModel):
|
||||
"""Structured order information"""
|
||||
order_id: str
|
||||
customer_id: str
|
||||
product_id: str
|
||||
quantity: int
|
||||
priority: str = "normal" # normal, high, urgent
|
||||
due_date: str
|
||||
requirements: Dict[str, Any] = {}
|
||||
|
||||
|
||||
class InventoryStatus(BaseModel):
|
||||
"""Material availability status"""
|
||||
material_id: str
|
||||
available_quantity: int
|
||||
reorder_level: int
|
||||
supplier_lead_time: int
|
||||
location: str
|
||||
|
||||
|
||||
class ProductionSchedule(BaseModel):
|
||||
"""Optimized production schedule"""
|
||||
schedule_id: str
|
||||
production_line: str
|
||||
start_time: str
|
||||
end_time: str
|
||||
assigned_workers: List[str]
|
||||
estimated_completion: str
|
||||
bottleneck_analysis: Dict[str, Any] = {}
|
||||
|
||||
|
||||
class QualityReport(BaseModel):
|
||||
"""Quality inspection results"""
|
||||
batch_id: str
|
||||
inspection_time: str
|
||||
defect_rate: float
|
||||
defect_types: List[str]
|
||||
passed: bool
|
||||
recommendations: List[str]
|
||||
|
||||
|
||||
# Tools for agents
|
||||
@tool
|
||||
def extract_order_details(text: str) -> Dict:
|
||||
"""Extract structured order information from unstructured text"""
|
||||
# Simulate order parsing logic
|
||||
return {
|
||||
"order_id": "ORD-2024-001",
|
||||
"customer_id": "CUST-123",
|
||||
"product_id": "PROD-456",
|
||||
"quantity": 100,
|
||||
"priority": "high",
|
||||
"due_date": "2024-03-15",
|
||||
"requirements": {"material": "steel", "finish": "polished"}
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def check_material_availability(product_id: str, quantity: int) -> Dict:
|
||||
"""Check if materials are available for production"""
|
||||
# Simulate inventory check
|
||||
return {
|
||||
"material_id": "MAT-789",
|
||||
"available_quantity": 500,
|
||||
"reorder_level": 100,
|
||||
"supplier_lead_time": 7,
|
||||
"location": "Warehouse-A"
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def calculate_optimal_schedule(order: Dict, inventory: Dict) -> Dict:
|
||||
"""Calculate optimal production schedule based on constraints"""
|
||||
# Simulate scheduling optimization
|
||||
return {
|
||||
"schedule_id": "SCH-2024-001",
|
||||
"production_line": "Line-3",
|
||||
"start_time": "2024-03-10T08:00:00",
|
||||
"end_time": "2024-03-14T17:00:00",
|
||||
"assigned_workers": ["Worker-001", "Worker-002"],
|
||||
"estimated_completion": "2024-03-14T16:30:00",
|
||||
"bottleneck_analysis": {
|
||||
"critical_path": "Assembly",
|
||||
"buffer_time": 2.5
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def perform_quality_inspection(batch_id: str) -> Dict:
|
||||
"""Perform automated quality inspection on production batch"""
|
||||
# Simulate quality control
|
||||
return {
|
||||
"batch_id": batch_id,
|
||||
"inspection_time": "2024-03-14T17:00:00",
|
||||
"defect_rate": 0.02,
|
||||
"defect_types": ["surface_scratch", "dimension_variance"],
|
||||
"passed": True,
|
||||
"recommendations": [
|
||||
"Adjust machine calibration on Line-3",
|
||||
"Increase inspection frequency for next batch"
|
||||
]
|
||||
}
|
||||
|
||||
|
||||
# Agent Definitions with SLA requirements
|
||||
order_parser = Agent(
|
||||
name="ParseOrder",
|
||||
instructions="""You are an order parsing specialist. Extract and structure order information
|
||||
from various formats (email, PDF, API). Ensure all required fields are captured and validated.
|
||||
SLA: Process within 30 seconds per order.""",
|
||||
tools=[extract_order_details]
|
||||
)
|
||||
|
||||
inventory_checker = Agent(
|
||||
name="CheckInventory",
|
||||
instructions="""You are an inventory management specialist. Verify material availability,
|
||||
check reorder points, and identify potential supply chain issues.
|
||||
SLA: Real-time response within 5 seconds.""",
|
||||
tools=[check_material_availability]
|
||||
)
|
||||
|
||||
schedule_optimizer = Agent(
|
||||
name="OptimizeSchedule",
|
||||
instructions="""You are a production scheduling expert. Optimize production schedules
|
||||
based on order priority, resource availability, and constraints. Minimize idle time
|
||||
and maximize throughput.
|
||||
SLA: Generate schedule within 2 minutes for complex orders.""",
|
||||
tools=[calculate_optimal_schedule]
|
||||
)
|
||||
|
||||
quality_inspector = Agent(
|
||||
name="DefectDetect",
|
||||
instructions="""You are a quality control specialist. Perform automated inspections,
|
||||
detect defects using vision analysis, and provide improvement recommendations.
|
||||
SLA: Complete inspection within 1 minute per batch.""",
|
||||
tools=[perform_quality_inspection]
|
||||
)
|
||||
|
||||
|
||||
# Workflow with fallback strategies
|
||||
def manufacturing_workflow(order_text: str):
|
||||
"""
|
||||
Complete manufacturing workflow from order to quality control
|
||||
Includes fallback strategies for each critical step
|
||||
"""
|
||||
|
||||
# Step 1: Parse order with fallback
|
||||
try:
|
||||
order_details = order_parser.start(f"Parse this order: {order_text}")
|
||||
if not order_details:
|
||||
# Fallback: Manual review queue
|
||||
return {"status": "manual_review_required", "reason": "order_parsing_failed"}
|
||||
except Exception as e:
|
||||
return {"status": "error", "stage": "order_parsing", "error": str(e)}
|
||||
|
||||
# Step 2: Check inventory with fallback
|
||||
try:
|
||||
inventory_status = inventory_checker.start(
|
||||
f"Check materials for order: {order_details}"
|
||||
)
|
||||
if not inventory_status:
|
||||
# Fallback: Alternative supplier check
|
||||
return {"status": "alternative_supplier_needed", "order": order_details}
|
||||
except Exception as e:
|
||||
# Fallback: Conservative estimate with safety margin
|
||||
inventory_status = {"estimated": True, "safety_margin": 1.5}
|
||||
|
||||
# Step 3: Optimize schedule with fallback
|
||||
try:
|
||||
schedule = schedule_optimizer.start(
|
||||
f"Create schedule for order {order_details} with inventory {inventory_status}"
|
||||
)
|
||||
if not schedule:
|
||||
# Fallback: Standard scheduling template
|
||||
schedule = {"template": "standard", "priority": "normal"}
|
||||
except Exception as e:
|
||||
# Fallback: Queue for next available slot
|
||||
schedule = {"status": "queued", "estimated_start": "next_available"}
|
||||
|
||||
# Step 4: Quality inspection with fallback
|
||||
try:
|
||||
quality_report = quality_inspector.start(
|
||||
f"Inspect batch for schedule {schedule}"
|
||||
)
|
||||
if not quality_report:
|
||||
# Fallback: Manual inspection required
|
||||
quality_report = {"requires_manual": True, "inspector_assigned": "QC-Team-1"}
|
||||
except Exception as e:
|
||||
# Fallback: Quarantine for review
|
||||
quality_report = {"status": "quarantined", "review_required": True}
|
||||
|
||||
return {
|
||||
"status": "completed",
|
||||
"order": order_details,
|
||||
"inventory": inventory_status,
|
||||
"schedule": schedule,
|
||||
"quality": quality_report
|
||||
}
|
||||
|
||||
|
||||
# Cross-industry reusable patterns (70% reuse)
|
||||
class IndustryAgentPattern:
|
||||
"""
|
||||
Base pattern reusable across industries
|
||||
Provides common agent capabilities that can be specialized
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def create_data_parser(name: str, domain: str, sla_seconds: int = 30):
|
||||
"""Create a data parsing agent for any domain"""
|
||||
return Agent(
|
||||
name=name,
|
||||
instructions=f"""You are a {domain} data parsing specialist.
|
||||
Extract and structure information from various formats.
|
||||
Validate all required fields according to {domain} standards.
|
||||
SLA: Process within {sla_seconds} seconds."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def create_resource_checker(name: str, resource_type: str, sla_seconds: int = 5):
|
||||
"""Create a resource availability checker for any resource type"""
|
||||
return Agent(
|
||||
name=name,
|
||||
instructions=f"""You are a {resource_type} availability specialist.
|
||||
Verify {resource_type} availability and identify constraints.
|
||||
Provide real-time status and alternative options if needed.
|
||||
SLA: Response within {sla_seconds} seconds."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def create_optimizer(name: str, optimization_target: str, sla_minutes: int = 2):
|
||||
"""Create an optimization agent for any target metric"""
|
||||
return Agent(
|
||||
name=name,
|
||||
instructions=f"""You are an optimization expert for {optimization_target}.
|
||||
Find optimal solutions considering all constraints and priorities.
|
||||
Minimize waste and maximize efficiency.
|
||||
SLA: Generate solution within {sla_minutes} minutes."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def create_inspector(name: str, inspection_type: str, sla_minutes: int = 1):
|
||||
"""Create an inspection agent for any quality metric"""
|
||||
return Agent(
|
||||
name=name,
|
||||
instructions=f"""You are a {inspection_type} inspection specialist.
|
||||
Perform automated analysis and detect anomalies.
|
||||
Provide actionable recommendations for improvement.
|
||||
SLA: Complete inspection within {sla_minutes} minute(s)."""
|
||||
)
|
||||
|
||||
|
||||
# Example usage
|
||||
if __name__ == "__main__":
|
||||
# Create a manufacturing workflow instance
|
||||
order = "Customer ABC needs 100 units of Product-XYZ by March 15th, high priority"
|
||||
|
||||
# Option 1: Use specialized agents
|
||||
result = manufacturing_workflow(order)
|
||||
print("Manufacturing workflow result:", result)
|
||||
|
||||
# Option 2: Use reusable patterns for other industries
|
||||
# These patterns can be adapted for Energy, Healthcare, Agriculture, Transportation
|
||||
energy_parser = IndustryAgentPattern.create_data_parser(
|
||||
"EnergyDataParser", "wind farm telemetry", sla_seconds=10
|
||||
)
|
||||
|
||||
healthcare_checker = IndustryAgentPattern.create_resource_checker(
|
||||
"BedAvailability", "hospital bed", sla_seconds=3
|
||||
)
|
||||
|
||||
agriculture_optimizer = IndustryAgentPattern.create_optimizer(
|
||||
"IrrigationOptimizer", "water usage", sla_minutes=5
|
||||
)
|
||||
|
||||
transport_inspector = IndustryAgentPattern.create_inspector(
|
||||
"TunnelSafety", "structural integrity", sla_minutes=2
|
||||
)
|
||||
@@ -1,599 +0,0 @@
|
||||
"""
|
||||
Transportation Industry Template
|
||||
================================
|
||||
Tunnel safety monitoring and infrastructure management workflow
|
||||
Based on SRAO Framework with LiDAR and sensor fusion
|
||||
|
||||
Key agents:
|
||||
- LiDARFusion: Processes LiDAR point cloud data
|
||||
- DisplacementCalculator: Calculates structural displacement
|
||||
- HeatmapGenerator: Generates safety heatmaps
|
||||
- MaintenancePlanner: Plans infrastructure maintenance
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, tool
|
||||
from typing import Dict, List, Any, Tuple, Optional
|
||||
from pydantic import BaseModel
|
||||
from datetime import datetime, timedelta
|
||||
from enum import Enum
|
||||
import math
|
||||
|
||||
|
||||
# Safety levels for infrastructure
|
||||
class SafetyLevel(str, Enum):
|
||||
SAFE = "safe"
|
||||
CAUTION = "caution"
|
||||
WARNING = "warning"
|
||||
DANGER = "danger"
|
||||
CRITICAL = "critical"
|
||||
|
||||
|
||||
# Infrastructure types
|
||||
class InfrastructureType(str, Enum):
|
||||
TUNNEL = "tunnel"
|
||||
BRIDGE = "bridge"
|
||||
HIGHWAY = "highway"
|
||||
RAILWAY = "railway"
|
||||
AIRPORT = "airport"
|
||||
|
||||
|
||||
# I/O Schemas
|
||||
class LiDARScan(BaseModel):
|
||||
"""LiDAR scan data for infrastructure"""
|
||||
scan_id: str
|
||||
infrastructure_id: str
|
||||
scan_time: str
|
||||
point_cloud_size: int # Number of points
|
||||
scan_resolution: float # Points per square meter
|
||||
coverage_area: float # Square meters
|
||||
anomaly_points: List[Tuple[float, float, float]] # XYZ coordinates
|
||||
reference_baseline: Optional[Dict[str, Any]]
|
||||
|
||||
|
||||
class DisplacementAnalysis(BaseModel):
|
||||
"""Structural displacement analysis"""
|
||||
analysis_id: str
|
||||
infrastructure_id: str
|
||||
analysis_time: str
|
||||
max_displacement: float # millimeters
|
||||
displacement_vector: Tuple[float, float, float] # XYZ displacement
|
||||
critical_zones: List[Dict[str, Any]]
|
||||
settlement_rate: float # mm/month
|
||||
tilt_angle: float # degrees
|
||||
safety_factor: float
|
||||
|
||||
|
||||
class SafetyHeatmap(BaseModel):
|
||||
"""Infrastructure safety heatmap"""
|
||||
heatmap_id: str
|
||||
infrastructure_id: str
|
||||
generation_time: str
|
||||
grid_resolution: float # meters
|
||||
safety_scores: List[List[float]] # 2D grid of safety scores
|
||||
critical_areas: List[Dict[str, Any]]
|
||||
overall_safety: SafetyLevel
|
||||
risk_trends: Dict[str, Any]
|
||||
|
||||
|
||||
class MaintenanceSchedule(BaseModel):
|
||||
"""Maintenance planning schedule"""
|
||||
schedule_id: str
|
||||
infrastructure_id: str
|
||||
maintenance_type: str # preventive, corrective, emergency
|
||||
priority_level: str # low, medium, high, critical
|
||||
scheduled_date: str
|
||||
estimated_duration: int # hours
|
||||
required_resources: List[str]
|
||||
traffic_impact: str
|
||||
cost_estimate: float
|
||||
|
||||
|
||||
# Transportation-specific tools
|
||||
@tool
|
||||
def process_lidar_scan(infrastructure_id: str, scan_type: str = "full") -> Dict:
|
||||
"""Process LiDAR point cloud data for structural analysis"""
|
||||
# Simulate LiDAR processing
|
||||
return {
|
||||
"scan_id": f"LIDAR-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"infrastructure_id": infrastructure_id,
|
||||
"scan_time": datetime.now().isoformat(),
|
||||
"point_cloud_size": 5000000, # 5 million points
|
||||
"scan_resolution": 100.0, # points/m²
|
||||
"coverage_area": 50000.0, # m²
|
||||
"anomaly_points": [
|
||||
(10.5, 20.3, 5.1),
|
||||
(15.2, 25.8, 5.3),
|
||||
(20.1, 30.5, 5.5)
|
||||
],
|
||||
"reference_baseline": {
|
||||
"date": "2024-01-01",
|
||||
"baseline_id": "BSL-001"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def calculate_displacement(current_scan: Dict, baseline_scan: Dict) -> Dict:
|
||||
"""Calculate structural displacement from LiDAR scans"""
|
||||
# Simulate displacement calculation
|
||||
anomalies = current_scan.get("anomaly_points", [])
|
||||
|
||||
if len(anomalies) > 5:
|
||||
max_displacement = 15.0
|
||||
safety_factor = 0.6
|
||||
safety_level = SafetyLevel.WARNING
|
||||
elif len(anomalies) > 2:
|
||||
max_displacement = 8.0
|
||||
safety_factor = 0.8
|
||||
safety_level = SafetyLevel.CAUTION
|
||||
else:
|
||||
max_displacement = 3.0
|
||||
safety_factor = 0.95
|
||||
safety_level = SafetyLevel.SAFE
|
||||
|
||||
return {
|
||||
"analysis_id": f"DISP-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"infrastructure_id": current_scan["infrastructure_id"],
|
||||
"analysis_time": datetime.now().isoformat(),
|
||||
"max_displacement": max_displacement,
|
||||
"displacement_vector": (2.5, 1.8, max_displacement),
|
||||
"critical_zones": [
|
||||
{
|
||||
"zone_id": "CZ-001",
|
||||
"location": "tunnel_crown",
|
||||
"displacement": max_displacement * 0.8,
|
||||
"risk": "high" if max_displacement > 10 else "medium"
|
||||
}
|
||||
],
|
||||
"settlement_rate": max_displacement / 30, # mm/month
|
||||
"tilt_angle": math.degrees(math.atan(max_displacement / 1000)),
|
||||
"safety_factor": safety_factor
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def generate_safety_heatmap(displacement_data: Dict, sensor_data: List[Dict]) -> Dict:
|
||||
"""Generate safety heatmap visualization for infrastructure"""
|
||||
# Simulate heatmap generation
|
||||
safety_factor = displacement_data.get("safety_factor", 1.0)
|
||||
|
||||
# Create grid (simplified 10x10)
|
||||
grid_size = 10
|
||||
safety_grid = []
|
||||
critical_areas = []
|
||||
|
||||
for i in range(grid_size):
|
||||
row = []
|
||||
for j in range(grid_size):
|
||||
# Generate safety score based on position and displacement
|
||||
base_score = safety_factor
|
||||
distance_factor = math.sqrt((i-5)**2 + (j-5)**2) / 10
|
||||
safety_score = min(1.0, base_score + (0.2 * distance_factor))
|
||||
row.append(safety_score)
|
||||
|
||||
if safety_score < 0.7:
|
||||
critical_areas.append({
|
||||
"grid_position": (i, j),
|
||||
"safety_score": safety_score,
|
||||
"recommended_action": "immediate_inspection"
|
||||
})
|
||||
safety_grid.append(row)
|
||||
|
||||
# Determine overall safety
|
||||
avg_safety = sum(sum(row) for row in safety_grid) / (grid_size * grid_size)
|
||||
if avg_safety > 0.9:
|
||||
overall = SafetyLevel.SAFE
|
||||
elif avg_safety > 0.8:
|
||||
overall = SafetyLevel.CAUTION
|
||||
elif avg_safety > 0.7:
|
||||
overall = SafetyLevel.WARNING
|
||||
else:
|
||||
overall = SafetyLevel.DANGER
|
||||
|
||||
return {
|
||||
"heatmap_id": f"HEAT-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"infrastructure_id": displacement_data["infrastructure_id"],
|
||||
"generation_time": datetime.now().isoformat(),
|
||||
"grid_resolution": 5.0, # meters
|
||||
"safety_scores": safety_grid,
|
||||
"critical_areas": critical_areas,
|
||||
"overall_safety": overall.value,
|
||||
"risk_trends": {
|
||||
"trend": "deteriorating" if avg_safety < 0.8 else "stable",
|
||||
"rate": -0.02 if avg_safety < 0.8 else 0.0
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@tool
|
||||
def plan_maintenance(infrastructure_id: str, safety_analysis: Dict, traffic_data: Dict) -> Dict:
|
||||
"""Plan maintenance based on safety analysis and traffic patterns"""
|
||||
safety_level = safety_analysis.get("overall_safety", "safe")
|
||||
|
||||
# Determine maintenance urgency
|
||||
if safety_level in ["danger", "critical"]:
|
||||
maintenance_type = "emergency"
|
||||
priority = "critical"
|
||||
days_until = 1
|
||||
duration = 48
|
||||
elif safety_level == "warning":
|
||||
maintenance_type = "corrective"
|
||||
priority = "high"
|
||||
days_until = 7
|
||||
duration = 24
|
||||
elif safety_level == "caution":
|
||||
maintenance_type = "preventive"
|
||||
priority = "medium"
|
||||
days_until = 30
|
||||
duration = 12
|
||||
else:
|
||||
maintenance_type = "preventive"
|
||||
priority = "low"
|
||||
days_until = 90
|
||||
duration = 8
|
||||
|
||||
# Traffic impact assessment
|
||||
peak_traffic = traffic_data.get("peak_volume", 1000)
|
||||
if peak_traffic > 5000:
|
||||
traffic_impact = "severe"
|
||||
cost_multiplier = 2.0
|
||||
elif peak_traffic > 2000:
|
||||
traffic_impact = "moderate"
|
||||
cost_multiplier = 1.5
|
||||
else:
|
||||
traffic_impact = "minimal"
|
||||
cost_multiplier = 1.0
|
||||
|
||||
return {
|
||||
"schedule_id": f"MAINT-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"infrastructure_id": infrastructure_id,
|
||||
"maintenance_type": maintenance_type,
|
||||
"priority_level": priority,
|
||||
"scheduled_date": (datetime.now() + timedelta(days=days_until)).isoformat(),
|
||||
"estimated_duration": duration,
|
||||
"required_resources": [
|
||||
"inspection_team",
|
||||
"repair_crew",
|
||||
"safety_equipment",
|
||||
"traffic_control"
|
||||
],
|
||||
"traffic_impact": traffic_impact,
|
||||
"cost_estimate": 50000 * cost_multiplier * (duration / 24)
|
||||
}
|
||||
|
||||
|
||||
# Transportation agent definitions
|
||||
lidar_agent = Agent(
|
||||
name="LiDARFusion",
|
||||
instructions="""You are a LiDAR data processing specialist for infrastructure.
|
||||
Process point cloud data from mobile and terrestrial LiDAR scanners.
|
||||
Perform data fusion from multiple sensor sources.
|
||||
Identify structural anomalies and deformations.
|
||||
SLA: Process scan data within 5 minutes.""",
|
||||
tools=[process_lidar_scan]
|
||||
)
|
||||
|
||||
displacement_agent = Agent(
|
||||
name="DisplacementCalculator",
|
||||
instructions="""You are a structural displacement analysis expert.
|
||||
Calculate precise displacement measurements from temporal scans.
|
||||
Analyze settlement patterns and structural movements.
|
||||
Predict future displacement trends using ML models.
|
||||
SLA: Complete analysis within 2 minutes.""",
|
||||
tools=[calculate_displacement]
|
||||
)
|
||||
|
||||
heatmap_agent = Agent(
|
||||
name="HeatmapGenerator",
|
||||
instructions="""You are a safety visualization specialist.
|
||||
Generate intuitive safety heatmaps for infrastructure monitoring.
|
||||
Integrate multiple data sources for comprehensive risk assessment.
|
||||
Highlight critical areas requiring immediate attention.
|
||||
SLA: Generate heatmap within 1 minute.""",
|
||||
tools=[generate_safety_heatmap]
|
||||
)
|
||||
|
||||
maintenance_agent = Agent(
|
||||
name="MaintenancePlanner",
|
||||
instructions="""You are an infrastructure maintenance planning expert.
|
||||
Schedule maintenance based on structural health and traffic patterns.
|
||||
Optimize maintenance windows to minimize disruption.
|
||||
Coordinate resources and estimate costs.
|
||||
SLA: Create maintenance plan within 3 minutes.""",
|
||||
tools=[plan_maintenance]
|
||||
)
|
||||
|
||||
|
||||
# Transportation infrastructure monitoring workflow
|
||||
def infrastructure_monitoring_workflow(
|
||||
infrastructure_ids: List[str],
|
||||
infrastructure_type: InfrastructureType,
|
||||
traffic_data: Dict
|
||||
):
|
||||
"""
|
||||
Complete infrastructure monitoring workflow from scanning to maintenance
|
||||
Includes safety assessment and predictive maintenance
|
||||
"""
|
||||
|
||||
monitoring_results = {
|
||||
"timestamp": datetime.now().isoformat(),
|
||||
"infrastructure_type": infrastructure_type.value,
|
||||
"structures_monitored": len(infrastructure_ids),
|
||||
"safety_assessments": [],
|
||||
"maintenance_required": [],
|
||||
"emergency_alerts": [],
|
||||
"network_health_score": 0.0
|
||||
}
|
||||
|
||||
total_safety_score = 0.0
|
||||
|
||||
for infra_id in infrastructure_ids:
|
||||
try:
|
||||
# Step 1: LiDAR scanning
|
||||
lidar_scan = lidar_agent.start(
|
||||
f"Process LiDAR scan for {infrastructure_type.value} {infra_id}"
|
||||
)
|
||||
|
||||
# Step 2: Displacement analysis
|
||||
# Get baseline (would be from database in real scenario)
|
||||
baseline = {"scan_id": "BSL-001", "point_cloud": []}
|
||||
|
||||
displacement_analysis = displacement_agent.start(
|
||||
f"Calculate displacement for scan: {lidar_scan} against baseline: {baseline}"
|
||||
)
|
||||
|
||||
# Step 3: Generate safety heatmap
|
||||
sensor_data = [] # Would include IoT sensor readings
|
||||
safety_heatmap = heatmap_agent.start(
|
||||
f"Generate heatmap for displacement: {displacement_analysis} "
|
||||
f"with sensors: {sensor_data}"
|
||||
)
|
||||
|
||||
monitoring_results["safety_assessments"].append({
|
||||
"infrastructure_id": infra_id,
|
||||
"safety_level": safety_heatmap.get("overall_safety"),
|
||||
"max_displacement": displacement_analysis.get("max_displacement"),
|
||||
"critical_zones": len(safety_heatmap.get("critical_areas", []))
|
||||
})
|
||||
|
||||
# Check for emergency conditions
|
||||
if safety_heatmap.get("overall_safety") in ["danger", "critical"]:
|
||||
monitoring_results["emergency_alerts"].append({
|
||||
"infrastructure_id": infra_id,
|
||||
"alert_level": "emergency",
|
||||
"safety_status": safety_heatmap["overall_safety"],
|
||||
"immediate_action": "close_to_traffic",
|
||||
"notification_sent": True
|
||||
})
|
||||
|
||||
# Step 4: Emergency maintenance planning
|
||||
maintenance_plan = maintenance_agent.start(
|
||||
f"Plan emergency maintenance for {infra_id} "
|
||||
f"with safety: {safety_heatmap} and traffic: {traffic_data}"
|
||||
)
|
||||
monitoring_results["maintenance_required"].append(maintenance_plan)
|
||||
|
||||
elif safety_heatmap.get("overall_safety") in ["warning", "caution"]:
|
||||
# Regular maintenance planning
|
||||
maintenance_plan = maintenance_agent.start(
|
||||
f"Plan maintenance for {infra_id} "
|
||||
f"with safety: {safety_heatmap} and traffic: {traffic_data}"
|
||||
)
|
||||
monitoring_results["maintenance_required"].append(maintenance_plan)
|
||||
|
||||
# Calculate safety score contribution
|
||||
safety_mapping = {
|
||||
"safe": 1.0, "caution": 0.8, "warning": 0.6,
|
||||
"danger": 0.3, "critical": 0.1
|
||||
}
|
||||
total_safety_score += safety_mapping.get(
|
||||
safety_heatmap.get("overall_safety", "safe"), 0.5
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
# Fallback: Manual inspection
|
||||
monitoring_results["emergency_alerts"].append({
|
||||
"infrastructure_id": infra_id,
|
||||
"alert_level": "system_failure",
|
||||
"error": str(e),
|
||||
"action": "dispatch_manual_inspection_team"
|
||||
})
|
||||
|
||||
# Calculate network health score
|
||||
if infrastructure_ids:
|
||||
monitoring_results["network_health_score"] = (
|
||||
total_safety_score / len(infrastructure_ids) * 100
|
||||
)
|
||||
|
||||
return monitoring_results
|
||||
|
||||
|
||||
# Multi-modal transportation patterns
|
||||
class MultiModalTransportPatterns:
|
||||
"""
|
||||
Patterns for different transportation infrastructure types
|
||||
Demonstrates cross-industry reuse for transportation sector
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def adapt_for_bridge_monitoring() -> Agent:
|
||||
"""Adapt tunnel monitoring for bridge structures"""
|
||||
return Agent(
|
||||
name="BridgeMonitor",
|
||||
instructions="""Monitor bridge structural health using sensors.
|
||||
Track deck deflection, cable tension, and vibration patterns.
|
||||
Detect fatigue cracks and corrosion.
|
||||
Consider wind and seismic loads.
|
||||
SLA: Real-time monitoring with 10-second updates."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def adapt_for_railway_tracks() -> Agent:
|
||||
"""Adapt for railway track monitoring"""
|
||||
return Agent(
|
||||
name="RailwayMonitor",
|
||||
instructions="""Monitor railway track geometry and condition.
|
||||
Detect rail defects, gauge variations, and ballast degradation.
|
||||
Analyze wheel-rail interaction forces.
|
||||
Predict track maintenance needs.
|
||||
SLA: Process track inspection data within 3 minutes per km."""
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def adapt_for_airport_runways() -> Agent:
|
||||
"""Adapt for airport runway monitoring"""
|
||||
return Agent(
|
||||
name="RunwayMonitor",
|
||||
instructions="""Monitor airport runway surface conditions.
|
||||
Detect FOD (Foreign Object Debris) and surface irregularities.
|
||||
Assess pavement condition and friction levels.
|
||||
Monitor drainage and lighting systems.
|
||||
SLA: Complete runway scan within 10 minutes."""
|
||||
)
|
||||
|
||||
|
||||
# Intelligent traffic management integration
|
||||
class TrafficManagementPatterns:
|
||||
"""
|
||||
Patterns for integrating with intelligent traffic systems
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def optimize_traffic_flow(maintenance_window: Dict, traffic_patterns: Dict) -> Dict:
|
||||
"""Optimize traffic flow during maintenance"""
|
||||
peak_hours = traffic_patterns.get("peak_hours", [7, 9, 17, 19])
|
||||
maintenance_start = maintenance_window.get("start_time", "02:00")
|
||||
|
||||
# Calculate optimal diversion routes
|
||||
return {
|
||||
"strategy": "dynamic_routing",
|
||||
"diversion_routes": [
|
||||
{"route_id": "ALT-1", "capacity": 0.6, "added_time": 15},
|
||||
{"route_id": "ALT-2", "capacity": 0.3, "added_time": 20}
|
||||
],
|
||||
"lane_management": {
|
||||
"reversible_lanes": True,
|
||||
"peak_direction": "inbound" if int(maintenance_start[:2]) < 12 else "outbound"
|
||||
},
|
||||
"public_transport": {
|
||||
"increase_frequency": True,
|
||||
"additional_services": 4
|
||||
},
|
||||
"estimated_delay": 10 # minutes
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def incident_response_plan(incident_type: str, location: Dict) -> Dict:
|
||||
"""Generate incident response plan"""
|
||||
response_times = {
|
||||
"accident": 5,
|
||||
"breakdown": 10,
|
||||
"infrastructure_failure": 2,
|
||||
"weather_hazard": 15
|
||||
}
|
||||
|
||||
return {
|
||||
"incident_id": f"INC-{datetime.now().strftime('%Y%m%d%H%M')}",
|
||||
"response_time": response_times.get(incident_type, 10),
|
||||
"resources_dispatched": [
|
||||
r for r in [
|
||||
"emergency_response_team",
|
||||
"traffic_control_unit",
|
||||
"maintenance_crew" if "infrastructure" in incident_type else None
|
||||
] if r is not None
|
||||
],
|
||||
"traffic_management": {
|
||||
"lane_closures": 2,
|
||||
"speed_reduction": 30, # km/h
|
||||
"message_signs": ["Incident ahead", "Reduce speed", "Merge left"]
|
||||
},
|
||||
"estimated_clearance": 45 # minutes
|
||||
}
|
||||
|
||||
|
||||
# Predictive maintenance patterns
|
||||
class PredictiveMaintenancePatterns:
|
||||
"""
|
||||
ML-based predictive maintenance for transportation infrastructure
|
||||
"""
|
||||
|
||||
@staticmethod
|
||||
def predict_failure_probability(
|
||||
displacement_trend: List[float],
|
||||
environmental_factors: Dict
|
||||
) -> float:
|
||||
"""Predict probability of structural failure"""
|
||||
# Simplified prediction model
|
||||
trend_slope = (displacement_trend[-1] - displacement_trend[0]) / len(displacement_trend)
|
||||
temperature_factor = abs(environmental_factors.get("temp_variation", 0)) / 50
|
||||
moisture_factor = environmental_factors.get("humidity", 50) / 100
|
||||
|
||||
base_probability = 0.1
|
||||
trend_contribution = max(0, trend_slope * 10)
|
||||
env_contribution = (temperature_factor + moisture_factor) * 0.2
|
||||
|
||||
return min(1.0, base_probability + trend_contribution + env_contribution)
|
||||
|
||||
@staticmethod
|
||||
def optimize_maintenance_schedule(
|
||||
infrastructure_conditions: List[Dict],
|
||||
budget_constraint: float
|
||||
) -> List[Dict]:
|
||||
"""Optimize maintenance schedule across infrastructure network"""
|
||||
# Sort by urgency (safety_factor * cost_efficiency)
|
||||
prioritized = sorted(
|
||||
infrastructure_conditions,
|
||||
key=lambda x: (1 - x.get("safety_factor", 1)) * (1 / x.get("cost", 1)),
|
||||
reverse=True
|
||||
)
|
||||
|
||||
scheduled = []
|
||||
total_cost = 0
|
||||
|
||||
for infra in prioritized:
|
||||
if total_cost + infra.get("cost", 0) <= budget_constraint:
|
||||
scheduled.append({
|
||||
"infrastructure_id": infra["id"],
|
||||
"scheduled_date": infra["recommended_date"],
|
||||
"priority": "high" if infra["safety_factor"] < 0.7 else "medium"
|
||||
})
|
||||
total_cost += infra.get("cost", 0)
|
||||
|
||||
return scheduled
|
||||
|
||||
|
||||
# Example usage
|
||||
if __name__ == "__main__":
|
||||
# Monitor tunnel network
|
||||
tunnel_ids = [f"TUN-{i:03d}" for i in range(1, 6)]
|
||||
traffic = {
|
||||
"peak_volume": 3000,
|
||||
"off_peak_volume": 800,
|
||||
"peak_hours": [7, 9, 17, 19]
|
||||
}
|
||||
|
||||
result = infrastructure_monitoring_workflow(
|
||||
tunnel_ids,
|
||||
InfrastructureType.TUNNEL,
|
||||
traffic
|
||||
)
|
||||
print("Infrastructure monitoring result:", result)
|
||||
|
||||
# Multi-modal adaptation examples
|
||||
bridge_monitor = MultiModalTransportPatterns.adapt_for_bridge_monitoring()
|
||||
railway_monitor = MultiModalTransportPatterns.adapt_for_railway_tracks()
|
||||
runway_monitor = MultiModalTransportPatterns.adapt_for_airport_runways()
|
||||
|
||||
# Traffic management example
|
||||
maintenance = {"start_time": "22:00", "duration": 8}
|
||||
traffic_plan = TrafficManagementPatterns.optimize_traffic_flow(maintenance, traffic)
|
||||
print("Traffic optimization plan:", traffic_plan)
|
||||
|
||||
# Predictive maintenance example
|
||||
displacement_history = [2.0, 2.3, 2.8, 3.5, 4.3] # mm over months
|
||||
environment = {"temp_variation": 30, "humidity": 75}
|
||||
|
||||
failure_prob = PredictiveMaintenancePatterns.predict_failure_probability(
|
||||
displacement_history, environment
|
||||
)
|
||||
print(f"Failure probability: {failure_prob:.2%}")
|
||||
@@ -80,7 +80,7 @@ Be precise and quote exact values when asked about codes or numbers.""",
|
||||
print(f"\nAnswer: {response}\n")
|
||||
|
||||
# Verify the answer contains the unique code
|
||||
if "ZEBRA-71" in str(response or "").upper():
|
||||
if "ZEBRA-71" in response.upper():
|
||||
print("✅ VERIFIED: Agent correctly retrieved the unique code from context!\n")
|
||||
else:
|
||||
print("❌ WARNING: Agent did not find the code - check retrieval\n")
|
||||
@@ -104,7 +104,7 @@ Be precise and quote exact values when asked about codes or numbers.""",
|
||||
response = agent.chat("What is the security incident code?")
|
||||
print(f"\nAnswer: {response}\n")
|
||||
|
||||
if "HAWK-88" in str(response or "").upper():
|
||||
if "HAWK-88" in response.upper():
|
||||
print("✅ VERIFIED: Agent correctly retrieved the security code!\n")
|
||||
else:
|
||||
print("❌ WARNING: Agent did not find the code - check retrieval\n")
|
||||
|
||||
@@ -19,16 +19,6 @@ from praisonaiagents import Agent, AgentTeam
|
||||
# Initialize observability
|
||||
obs.init()
|
||||
|
||||
|
||||
def set_span_attr(span, key, value):
|
||||
"""Set span attribute safely across observability implementations."""
|
||||
if hasattr(span, "set_attribute"):
|
||||
span.set_attribute(key, value)
|
||||
return
|
||||
attrs = getattr(span, "attributes", None)
|
||||
if attrs is not None:
|
||||
attrs[key] = value
|
||||
|
||||
# Create agents
|
||||
researcher = Agent(
|
||||
name="Researcher",
|
||||
@@ -47,13 +37,13 @@ with obs.trace("content-creation", metadata={"workflow": "research-write"}):
|
||||
|
||||
# Research phase
|
||||
with obs.span("research-phase", kind=SpanKind.AGENT) as research_span:
|
||||
set_span_attr(research_span, "agent", "Researcher")
|
||||
research_span.attributes["agent"] = "Researcher"
|
||||
research_result = researcher.chat("Research the benefits of AI in healthcare")
|
||||
|
||||
# Writing phase
|
||||
with obs.span("writing-phase", kind=SpanKind.AGENT) as write_span:
|
||||
set_span_attr(write_span, "agent", "Writer")
|
||||
set_span_attr(write_span, "input_length", len(str(research_result)))
|
||||
write_span.attributes["agent"] = "Writer"
|
||||
write_span.attributes["input_length"] = len(str(research_result))
|
||||
final_content = writer.chat(f"Write a blog post based on: {research_result}")
|
||||
|
||||
print("Final Content:")
|
||||
|
||||
@@ -13,8 +13,7 @@ Expected output:
|
||||
- Session can be resumed later with same session_id
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.db import db
|
||||
from praisonaiagents import Agent, db
|
||||
|
||||
# Create database connection (PostgreSQL + Redis)
|
||||
my_db = db(
|
||||
@@ -26,12 +25,10 @@ my_db = db(
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
instructions="You are a helpful assistant. Be concise.",
|
||||
memory={
|
||||
"db": my_db,
|
||||
# session_id is optional - defaults to per-hour ID (YYYYMMDDHH-hash)
|
||||
# Set explicitly for session continuity across runs:
|
||||
"session_id": "my-persistent-session",
|
||||
},
|
||||
db=my_db,
|
||||
# session_id is optional - defaults to per-hour ID (YYYYMMDDHH-hash)
|
||||
# Set explicitly for session continuity across runs:
|
||||
session_id="my-persistent-session"
|
||||
)
|
||||
|
||||
# Chat - messages are automatically persisted
|
||||
|
||||
@@ -12,8 +12,7 @@ Expected output:
|
||||
- Export shows full session data
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.db import db
|
||||
from praisonaiagents import Agent, db
|
||||
|
||||
def get_weather(city: str) -> str:
|
||||
"""Get weather for a city."""
|
||||
@@ -30,10 +29,8 @@ agent = Agent(
|
||||
name="WeatherBot",
|
||||
instructions="You help with weather. Use the get_weather tool when asked.",
|
||||
tools=[get_weather],
|
||||
memory={
|
||||
"db": my_db,
|
||||
"session_id": "weather-session-001",
|
||||
},
|
||||
db=my_db,
|
||||
session_id="weather-session-001"
|
||||
)
|
||||
|
||||
# First chat - triggers run tracking
|
||||
|
||||
@@ -13,8 +13,7 @@ Expected output:
|
||||
Agent responds with state persisted to Redis
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.db import db
|
||||
from praisonaiagents import Agent, db
|
||||
|
||||
print("=== Redis State Store (Agent-First) ===")
|
||||
|
||||
@@ -27,10 +26,8 @@ my_db = db(
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
instructions="You are a helpful assistant.",
|
||||
memory={
|
||||
"db": my_db,
|
||||
"session_id": "redis-state-session",
|
||||
},
|
||||
db=my_db,
|
||||
session_id="redis-state-session"
|
||||
)
|
||||
|
||||
# Chat - state is automatically managed via Redis
|
||||
|
||||
@@ -11,8 +11,7 @@ Expected output:
|
||||
- Second run: Resumes with history
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.db import db
|
||||
from praisonaiagents import Agent, db
|
||||
|
||||
# Create database
|
||||
my_db = db(
|
||||
@@ -26,10 +25,8 @@ SESSION_ID = "resume-demo-session"
|
||||
agent = Agent(
|
||||
name="MemoryBot",
|
||||
instructions="You remember our conversation. Be helpful and concise.",
|
||||
memory={
|
||||
"db": my_db,
|
||||
"session_id": SESSION_ID,
|
||||
},
|
||||
db=my_db,
|
||||
session_id=SESSION_ID
|
||||
)
|
||||
|
||||
# Check if this is a new or resumed session
|
||||
|
||||
@@ -26,8 +26,7 @@ Expected Output:
|
||||
Messages persisted: 2
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.db import db
|
||||
from praisonaiagents import Agent, db
|
||||
|
||||
# Create database adapter (simplified import)
|
||||
db_instance = db(
|
||||
@@ -38,10 +37,8 @@ db_instance = db(
|
||||
agent = Agent(
|
||||
name="Assistant",
|
||||
instructions="You are a helpful assistant. Keep responses brief.",
|
||||
memory={
|
||||
"db": db_instance,
|
||||
"session_id": "demo-session-001", # Same session_id = resume conversation
|
||||
},
|
||||
db=db_instance,
|
||||
session_id="demo-session-001", # Same session_id = resume conversation
|
||||
output="silent"
|
||||
)
|
||||
|
||||
|
||||
@@ -11,8 +11,7 @@ Expected output:
|
||||
- Data persisted to local SQLite file
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.db import db
|
||||
from praisonaiagents import Agent, db
|
||||
import tempfile
|
||||
import os
|
||||
|
||||
@@ -26,10 +25,8 @@ print(f"Database: {db_path}")
|
||||
agent = Agent(
|
||||
name="LocalBot",
|
||||
instructions="You are a helpful assistant.",
|
||||
memory={
|
||||
"db": my_db,
|
||||
"session_id": "local-session",
|
||||
},
|
||||
db=my_db,
|
||||
session_id="local-session"
|
||||
)
|
||||
|
||||
# Chat
|
||||
|
||||
@@ -214,13 +214,8 @@ def example_subagent_delegation():
|
||||
assert hasattr(agent, "delegate"), "Agent should have delegate method"
|
||||
assert callable(agent.delegate), "delegate should be callable"
|
||||
|
||||
# Create a subagent using the public profile API
|
||||
from praisonaiagents.agents.profiles import BUILTIN_PROFILES, get_profile
|
||||
explorer_profile = get_profile("explorer") if "explorer" in BUILTIN_PROFILES else None
|
||||
subagent = Agent(
|
||||
name="subagent_explorer",
|
||||
instructions=explorer_profile.system_prompt if explorer_profile else "You are an explorer assistant.",
|
||||
)
|
||||
# Check _create_subagent method
|
||||
subagent = agent._create_subagent("explorer")
|
||||
print(f"Created subagent: {subagent.name}")
|
||||
print(f"Subagent instructions: {subagent.instructions[:50]}...")
|
||||
|
||||
|
||||
@@ -60,10 +60,9 @@ agents_system = AgentTeam(
|
||||
process="sequential", output="verbose"
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("Starting hierarchical agent generation...")
|
||||
result = agents_system.start()
|
||||
print("Starting hierarchical agent generation...")
|
||||
result = agents_system.start()
|
||||
|
||||
print(f"\nHierarchical Result: {str(result)[:200]}...")
|
||||
print("\n✅ AutoAgents hierarchical generation complete!")
|
||||
print("Demonstrated coordinated hierarchical workflow between manager and specialist agents.")
|
||||
print(f"\nHierarchical Result: {result[:200]}...")
|
||||
print("\n✅ AutoAgents hierarchical generation complete!")
|
||||
print("Demonstrated coordinated hierarchical workflow between manager and specialist agents.")
|
||||
@@ -6,18 +6,10 @@ It includes self-reflection for improving code quality and multiple specialized
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, Task, AgentTeam
|
||||
from praisonaiagents.tools import CodeInterpreter
|
||||
|
||||
def run_python_code(code: str) -> str:
|
||||
"""Execute Python code safely and return stdout or errors."""
|
||||
import io
|
||||
import contextlib
|
||||
try:
|
||||
buf = io.StringIO()
|
||||
with contextlib.redirect_stdout(buf):
|
||||
exec(code, {"__builtins__": __builtins__})
|
||||
return buf.getvalue() or "Executed successfully (no output)"
|
||||
except Exception as e:
|
||||
return f"Execution error: {e}"
|
||||
# Initialize code execution tool
|
||||
code_interpreter = CodeInterpreter()
|
||||
|
||||
# Custom code analysis tool
|
||||
def analyze_code_complexity(code: str) -> str:
|
||||
@@ -40,7 +32,9 @@ code_writer = Agent(
|
||||
goal="Write clean, efficient, and well-documented Python code",
|
||||
backstory="You are a senior Python developer with 10+ years of experience in writing production-quality code.",
|
||||
instructions="Write Python code that follows PEP 8 standards, includes proper error handling, and has clear documentation.",
|
||||
output="silent",
|
||||
reflection=True,
|
||||
|
||||
|
||||
)
|
||||
|
||||
code_reviewer = Agent(
|
||||
@@ -58,7 +52,7 @@ code_executor = Agent(
|
||||
goal="Safely execute and test Python code",
|
||||
backstory="You are responsible for running code and reporting results or errors.",
|
||||
instructions="Execute the provided code safely and report the output or any errors encountered.",
|
||||
tools=[run_python_code]
|
||||
tools=[code_interpreter]
|
||||
)
|
||||
|
||||
# Example tasks
|
||||
@@ -93,7 +87,7 @@ def demonstrate_code_agent():
|
||||
workflow = AgentTeam(
|
||||
agents=[code_writer, code_reviewer, code_executor],
|
||||
tasks=[write_task, review_task, execute_task],
|
||||
process="sequential", output="silent"
|
||||
process="sequential", output="verbose"
|
||||
)
|
||||
|
||||
# Run the workflow
|
||||
@@ -112,8 +106,10 @@ general_code_agent = Agent(
|
||||
3. Explain code concepts
|
||||
4. Refactor code for better performance
|
||||
5. Add tests and documentation""",
|
||||
tools=[run_python_code, analyze_code_complexity],
|
||||
output="silent",
|
||||
tools=[code_interpreter, analyze_code_complexity],
|
||||
reflection=True,
|
||||
|
||||
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@@ -41,25 +41,21 @@ def calculate_statistics(numbers: list) -> str:
|
||||
"""Calculate basic statistics for a list of numbers."""
|
||||
if not numbers:
|
||||
return "No numbers provided"
|
||||
try:
|
||||
nums = [float(x) for x in numbers]
|
||||
except (TypeError, ValueError):
|
||||
return "Error: all values must be numbers"
|
||||
|
||||
n = len(nums)
|
||||
mean = sum(nums) / n
|
||||
sorted_nums = sorted(nums)
|
||||
|
||||
n = len(numbers)
|
||||
mean = sum(numbers) / n
|
||||
sorted_nums = sorted(numbers)
|
||||
median = sorted_nums[n//2] if n % 2 else (sorted_nums[n//2-1] + sorted_nums[n//2]) / 2
|
||||
variance = sum((x - mean)**2 for x in nums) / n
|
||||
variance = sum((x - mean)**2 for x in numbers) / n
|
||||
std_dev = math.sqrt(variance)
|
||||
|
||||
|
||||
return f"""Statistics:
|
||||
- Count: {n}
|
||||
- Mean: {mean:.4f}
|
||||
- Median: {median:.4f}
|
||||
- Standard Deviation: {std_dev:.4f}
|
||||
- Min: {min(nums)}
|
||||
- Max: {max(nums)}"""
|
||||
- Min: {min(numbers)}
|
||||
- Max: {max(numbers)}"""
|
||||
|
||||
# Create specialized math agents
|
||||
calculation_agent = Agent(
|
||||
@@ -70,7 +66,8 @@ calculation_agent = Agent(
|
||||
instructions="Perform the requested calculations step by step, showing your work clearly.",
|
||||
tools=[basic_calculator, solve_quadratic, calculate_statistics],
|
||||
reflection=True,
|
||||
output="silent",
|
||||
|
||||
|
||||
)
|
||||
|
||||
problem_solver_agent = Agent(
|
||||
@@ -85,7 +82,8 @@ problem_solver_agent = Agent(
|
||||
4. Show each step of the solution
|
||||
5. Verify the answer makes sense""",
|
||||
reflection=True,
|
||||
output="silent",
|
||||
|
||||
|
||||
)
|
||||
|
||||
math_tutor_agent = Agent(
|
||||
@@ -93,8 +91,7 @@ math_tutor_agent = Agent(
|
||||
role="Mathematics tutor and explainer",
|
||||
goal="Explain mathematical concepts clearly and help users understand math",
|
||||
backstory="You are a patient math tutor who can explain concepts at any level from elementary to advanced.",
|
||||
instructions="Explain mathematical concepts using simple language, provide examples, and check for understanding.",
|
||||
output="silent",
|
||||
instructions="Explain mathematical concepts using simple language, provide examples, and check for understanding."
|
||||
)
|
||||
|
||||
# Example workflow for solving complex problems
|
||||
@@ -129,8 +126,7 @@ def solve_math_problem_workflow():
|
||||
workflow = AgentTeam(
|
||||
agents=[problem_solver_agent, calculation_agent, math_tutor_agent],
|
||||
tasks=[understand_task, solve_task, verify_task],
|
||||
process="sequential",
|
||||
output="silent",
|
||||
process="sequential", output="verbose"
|
||||
)
|
||||
|
||||
return workflow.start()
|
||||
@@ -152,7 +148,8 @@ math_assistant = Agent(
|
||||
Always show your work step by step.""",
|
||||
tools=[basic_calculator, solve_quadratic, calculate_statistics],
|
||||
reflection=True,
|
||||
output="silent",
|
||||
|
||||
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
from praisonaiagents import Agent
|
||||
|
||||
if __name__ == "__main__":
|
||||
agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
|
||||
agent.launch(port=8080, protocol="mcp", path="/")
|
||||
agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
|
||||
agent.launch(port=8080, protocol="mcp")
|
||||
@@ -67,11 +67,7 @@ def main():
|
||||
|
||||
# 4. Subagent delegation
|
||||
print("\n4. Subagent Delegation:")
|
||||
explorer_profile = get_profile("explorer") if "explorer" in BUILTIN_PROFILES else None
|
||||
subagent = Agent(
|
||||
name="subagent_explorer",
|
||||
instructions=explorer_profile.system_prompt if explorer_profile else "You are an explorer assistant.",
|
||||
)
|
||||
subagent = agent._create_subagent("explorer")
|
||||
print(f" Created subagent: {subagent.name}")
|
||||
print(f" Profile: explorer (read-only)")
|
||||
|
||||
|
||||
@@ -1,238 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Example: Bot In-Flight Run Control
|
||||
|
||||
Demonstrates how to use SessionRunControl to provide better UX for bots
|
||||
during long-running agent operations. Shows busy feedback, pending message
|
||||
handling, and /stop command support.
|
||||
|
||||
This example shows the "before" and "after" behavior described in issue #1914.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import time
|
||||
from typing import Optional
|
||||
|
||||
# Mock agent for demonstration
|
||||
class MockAgent:
|
||||
"""Simple mock agent that simulates long-running tasks."""
|
||||
|
||||
def __init__(self, name="assistant"):
|
||||
self.name = name
|
||||
self.chat_history = []
|
||||
self._interrupt_controller = None
|
||||
|
||||
def chat(self, prompt: str) -> str:
|
||||
"""Simulate a long-running chat response."""
|
||||
print(f"[Agent] Starting to process: '{prompt[:50]}...'")
|
||||
|
||||
# Simulate long processing with interrupt checking
|
||||
for i in range(30): # 3 second task (30 x 0.1s)
|
||||
time.sleep(0.1)
|
||||
|
||||
# Check for interruption
|
||||
if (self._interrupt_controller and
|
||||
hasattr(self._interrupt_controller, 'is_set') and
|
||||
self._interrupt_controller.is_set()):
|
||||
reason = getattr(self._interrupt_controller, 'reason', 'unknown')
|
||||
print(f"[Agent] ⚠️ Interrupted: {reason}")
|
||||
raise InterruptedError(f"Task cancelled: {reason}")
|
||||
|
||||
response = f"Completed analysis of: {prompt}"
|
||||
print(f"[Agent] ✅ Finished: {response}")
|
||||
return response
|
||||
|
||||
|
||||
async def demo_without_run_control():
|
||||
"""Demonstrate the old behavior (silent blocking)."""
|
||||
print("\n" + "="*60)
|
||||
print("🔴 BEFORE: Without Run Control (Silent Blocking)")
|
||||
print("="*60)
|
||||
|
||||
from praisonai.bots._session import BotSessionManager
|
||||
|
||||
# Standard session manager (no run control)
|
||||
session_mgr = BotSessionManager()
|
||||
agent = MockAgent("research-agent")
|
||||
user_id = "user123"
|
||||
|
||||
print("\n1. User sends long task:")
|
||||
print(" User: 'research quantum computing trends'")
|
||||
|
||||
# Start first task (this will run for 3 seconds)
|
||||
task1 = asyncio.create_task(
|
||||
session_mgr.chat(agent, user_id, "research quantum computing trends")
|
||||
)
|
||||
|
||||
# Simulate user sending follow-up messages during execution
|
||||
await asyncio.sleep(0.5)
|
||||
print("\n2. User sends follow-up (this will block silently):")
|
||||
print(" User: 'actually focus on business impact'")
|
||||
|
||||
task2 = asyncio.create_task(
|
||||
session_mgr.chat(agent, user_id, "actually focus on business impact")
|
||||
)
|
||||
|
||||
await asyncio.sleep(0.5)
|
||||
print("\n3. User tries to send /stop (this will also block):")
|
||||
print(" User: '/stop'")
|
||||
|
||||
task3 = asyncio.create_task(
|
||||
session_mgr.chat(agent, user_id, "/stop")
|
||||
)
|
||||
|
||||
print("\n⏳ Waiting for all messages to complete...")
|
||||
results = await asyncio.gather(task1, task2, task3)
|
||||
|
||||
print("\n📊 Results (all processed sequentially with no feedback):")
|
||||
for i, result in enumerate(results, 1):
|
||||
print(f" {i}. {result}")
|
||||
|
||||
print("\n❌ Problems with this approach:")
|
||||
print(" - No immediate feedback on follow-up messages")
|
||||
print(" - No way to cancel long-running tasks")
|
||||
print(" - User doesn't know if bot is working or broken")
|
||||
|
||||
|
||||
async def demo_with_run_control():
|
||||
"""Demonstrate the new behavior with run control."""
|
||||
print("\n" + "="*60)
|
||||
print("🟢 AFTER: With Run Control (Better UX)")
|
||||
print("="*60)
|
||||
|
||||
from praisonai.bots._run_control import SessionRunControl
|
||||
from praisonai.bots._session import BotSessionManager
|
||||
from praisonai.bots._commands import handle_stop_command
|
||||
|
||||
# Session manager with run control
|
||||
run_control = SessionRunControl(
|
||||
busy_mode="queue",
|
||||
busy_ack_template="⏳ {action} — will process after current task finishes"
|
||||
)
|
||||
session_mgr = BotSessionManager(run_control=run_control)
|
||||
agent = MockAgent("research-agent")
|
||||
user_id = "user123"
|
||||
|
||||
print("\n1. User sends long task:")
|
||||
print(" User: 'research quantum computing trends'")
|
||||
|
||||
# Start first task
|
||||
task1 = asyncio.create_task(
|
||||
session_mgr.chat_with_run_control(agent, user_id, "research quantum computing trends")
|
||||
)
|
||||
|
||||
# Immediate follow-up messages get acknowledgments
|
||||
await asyncio.sleep(0.5)
|
||||
print("\n2. User sends follow-up (gets immediate feedback):")
|
||||
print(" User: 'actually focus on business impact'")
|
||||
|
||||
result2 = await session_mgr.chat_with_run_control(
|
||||
agent, user_id, "actually focus on business impact"
|
||||
)
|
||||
print(f" Bot: {result2['response']}")
|
||||
print(f" Metadata: {result2['metadata']}")
|
||||
|
||||
await asyncio.sleep(0.5)
|
||||
print("\n3. User decides to stop current task:")
|
||||
print(" User: '/stop'")
|
||||
|
||||
stop_response = await handle_stop_command(user_id, run_control)
|
||||
print(f" Bot: {stop_response}")
|
||||
|
||||
# Wait for first task to complete (it should be cancelled)
|
||||
try:
|
||||
result1 = await task1
|
||||
print(f"\n📊 Task 1 result: {result1['response']}")
|
||||
print(f" Metadata: {result1['metadata']}")
|
||||
except asyncio.CancelledError:
|
||||
print("\n📊 Task 1 was cancelled as expected")
|
||||
|
||||
print("\n4. User sends fresh request after stopping:")
|
||||
print(" User: 'what's the weather like?'")
|
||||
|
||||
result4 = await session_mgr.chat_with_run_control(
|
||||
agent, user_id, "what's the weather like?"
|
||||
)
|
||||
print(f" Bot: {result4['response']}")
|
||||
|
||||
print("\n✅ Benefits of this approach:")
|
||||
print(" - Immediate feedback on all messages")
|
||||
print(" - Can cancel long-running tasks with /stop")
|
||||
print(" - Pending messages are queued and processed in order")
|
||||
print(" - User always knows what's happening")
|
||||
|
||||
|
||||
async def demo_interrupt_mode():
|
||||
"""Demonstrate interrupt mode."""
|
||||
print("\n" + "="*60)
|
||||
print("⚡ BONUS: Interrupt Mode (Cancel and Restart)")
|
||||
print("="*60)
|
||||
|
||||
from praisonai.bots._run_control import SessionRunControl
|
||||
from praisonai.bots._session import BotSessionManager
|
||||
|
||||
# Use interrupt mode instead of queue mode
|
||||
run_control = SessionRunControl(busy_mode="interrupt")
|
||||
session_mgr = BotSessionManager(run_control=run_control)
|
||||
agent = MockAgent("research-agent")
|
||||
user_id = "user123"
|
||||
|
||||
print("\n1. User starts long task:")
|
||||
print(" User: 'research renewable energy for 30 pages'")
|
||||
|
||||
task1 = asyncio.create_task(
|
||||
session_mgr.chat_with_run_control(agent, user_id, "research renewable energy for 30 pages")
|
||||
)
|
||||
|
||||
await asyncio.sleep(0.5)
|
||||
print("\n2. User changes mind (interrupts and restarts):")
|
||||
print(" User: 'actually just summarize solar panel efficiency'")
|
||||
|
||||
result2 = await session_mgr.chat_with_run_control(
|
||||
agent, user_id, "actually just summarize solar panel efficiency"
|
||||
)
|
||||
print(f" Bot: {result2['response']}")
|
||||
|
||||
# Wait for original task (should be interrupted)
|
||||
try:
|
||||
result1 = await task1
|
||||
print(f"\n📊 Original task result: {result1['response']}")
|
||||
if result1['metadata'].get('interrupted'):
|
||||
print(" ✅ Original task was properly interrupted")
|
||||
except:
|
||||
print("\n📊 Original task was cancelled")
|
||||
|
||||
print("\n✅ Interrupt mode is great for:")
|
||||
print(" - When users frequently change direction")
|
||||
print(" - Interactive sessions where latest intent matters most")
|
||||
print(" - Real-time collaboration scenarios")
|
||||
|
||||
|
||||
async def main():
|
||||
"""Run all demonstrations."""
|
||||
print("🚀 Bot In-Flight Run Control Demo")
|
||||
print("Solving the silent lock problem described in issue #1914")
|
||||
|
||||
# Show the problem
|
||||
await demo_without_run_control()
|
||||
|
||||
# Show the solution
|
||||
await demo_with_run_control()
|
||||
|
||||
# Show advanced feature
|
||||
await demo_interrupt_mode()
|
||||
|
||||
print("\n" + "="*60)
|
||||
print("🎯 Summary")
|
||||
print("="*60)
|
||||
print("SessionRunControl solves the silent blocking problem by providing:")
|
||||
print("1. Immediate feedback for mid-run messages")
|
||||
print("2. /stop command support via InterruptController")
|
||||
print("3. Configurable policies (queue/interrupt/steer)")
|
||||
print("4. Run generation tracking to prevent race conditions")
|
||||
print("5. Pending message merging and ordering")
|
||||
print("\nThis makes bot interactions feel responsive and predictable!")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
@@ -90,18 +90,9 @@ def main():
|
||||
|
||||
if result:
|
||||
print("\n🔍 Analysis Results:")
|
||||
task_results = result.get("task_results") if isinstance(result, dict) else result
|
||||
if isinstance(task_results, dict):
|
||||
iterable = task_results.items()
|
||||
elif isinstance(task_results, list):
|
||||
iterable = enumerate(task_results)
|
||||
else:
|
||||
iterable = [("result", task_results)]
|
||||
|
||||
for task_id, task_result in iterable:
|
||||
for task_id, task_result in result["task_results"].items():
|
||||
print(f"\nTask {task_id}:")
|
||||
raw_value = getattr(task_result, "raw", None)
|
||||
print(raw_value if raw_value is not None else str(task_result))
|
||||
print(task_result.raw)
|
||||
else:
|
||||
print("❌ Failed to capture and analyze camera feed")
|
||||
|
||||
|
||||
@@ -148,19 +148,10 @@ def main():
|
||||
"scene_analysis": "🌍 SCENE ANALYSIS"
|
||||
}
|
||||
|
||||
task_results = result.get("task_results") if isinstance(result, dict) else result
|
||||
if isinstance(task_results, dict):
|
||||
iterable = task_results.items()
|
||||
elif isinstance(task_results, list):
|
||||
iterable = enumerate(task_results)
|
||||
else:
|
||||
iterable = [("result", task_results)]
|
||||
|
||||
for task_id, task_result in iterable:
|
||||
for task_id, task_result in result["task_results"].items():
|
||||
print(f"\n{agent_names.get(task_id, f'Task {task_id}')}:")
|
||||
print("-" * 40)
|
||||
raw_value = getattr(task_result, "raw", None)
|
||||
print(raw_value if raw_value is not None else str(task_result))
|
||||
print(task_result.raw)
|
||||
|
||||
print("\n" + "="*60)
|
||||
print("✅ Multi-agent analysis complete!")
|
||||
|
||||
@@ -34,5 +34,5 @@ print(f"\nChanged to: {handler.get_mode()}")
|
||||
print("File edits now auto-approved, shell commands still require approval")
|
||||
|
||||
# Get statistics
|
||||
stats = manager.get_stats()
|
||||
stats = handler.get_stats()
|
||||
print(f"\nStats: {stats}")
|
||||
@@ -31,4 +31,4 @@ print(f"Total cost: ${summary['total_cost']:.4f}")
|
||||
print(f"Avg cost/request: ${summary['avg_cost_per_request']:.4f}")
|
||||
|
||||
# Display formatted (uses Rich if available)
|
||||
handler.print_summary()
|
||||
handler.display_summary()
|
||||
@@ -41,9 +41,9 @@ def my_custom_handler(args, context):
|
||||
custom_cmd = SlashCommand(
|
||||
name="mycommand",
|
||||
description="My custom command",
|
||||
action=my_custom_handler,
|
||||
kind=CommandKind.CUSTOM,
|
||||
alt_names=["mc"]
|
||||
handler=my_custom_handler,
|
||||
kind=CommandKind.ACTION,
|
||||
aliases=["mc"]
|
||||
)
|
||||
|
||||
handler.register(custom_cmd)
|
||||
|
||||
@@ -1,9 +1,8 @@
|
||||
from pathlib import Path
|
||||
|
||||
from praisonaiagents import Agent, Task, AgentTeam
|
||||
import logging
|
||||
import tempfile
|
||||
import os
|
||||
import sys
|
||||
import logging
|
||||
from praisonaiagents import Agent, Task, AgentTeam
|
||||
|
||||
# Configure logging
|
||||
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
|
||||
@@ -20,9 +19,11 @@ config = {
|
||||
}
|
||||
}
|
||||
|
||||
_sample_path = Path(__file__).with_name("sample_knowledge.txt")
|
||||
if not _sample_path.exists():
|
||||
_sample_path.write_text("Mervin Praison is the creator of PraisonAI.\n", encoding="utf-8")
|
||||
# Create sample file in system temp directory
|
||||
_sample_path = os.path.join(tempfile.gettempdir(), "sample_knowledge.txt")
|
||||
if not os.path.exists(_sample_path):
|
||||
with open(_sample_path, "w", encoding="utf-8") as f:
|
||||
f.write("Mervin Praison is the creator of PraisonAI.\n")
|
||||
|
||||
# Create an agent with knowledge capabilities
|
||||
knowledge_agent = Agent(
|
||||
@@ -30,7 +31,7 @@ knowledge_agent = Agent(
|
||||
role="Information Specialist",
|
||||
goal="Store and retrieve knowledge efficiently",
|
||||
backstory="Expert in managing and utilizing stored knowledge",
|
||||
knowledge={**config, "sources": [str(_sample_path)]},
|
||||
knowledge={**config, "sources": [_sample_path]},
|
||||
)
|
||||
|
||||
# Define a task for the agent
|
||||
|
||||
@@ -19,5 +19,4 @@ agents = AgentTeam(
|
||||
execution={"max_iter": 30},
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
agents.start()
|
||||
agents.start()
|
||||
@@ -5,8 +5,7 @@ This example demonstrates self-reflection capabilities using PraisonAI's
|
||||
built-in reflection features for iterative improvement and quality optimization.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, Task
|
||||
from praisonaiagents.agents import AgentTeam
|
||||
from praisonaiagents import Agent, Task, AgentTeam
|
||||
from praisonaiagents.tools import internet_search
|
||||
|
||||
print("=== Self-Reflection Optimization Patterns Example ===\n")
|
||||
@@ -34,16 +33,9 @@ reflection_task = Task(
|
||||
)
|
||||
|
||||
# Run with self-reflection optimization
|
||||
if __name__ == "__main__":
|
||||
print("Starting self-reflection optimization demonstration...")
|
||||
agents = AgentTeam(
|
||||
agents=[reflection_agent],
|
||||
tasks=[reflection_task],
|
||||
process="sequential",
|
||||
output="verbose",
|
||||
)
|
||||
result = agents.start()
|
||||
print("Starting self-reflection optimization demonstration...")
|
||||
result = reflection_agent.execute_task(reflection_task)
|
||||
|
||||
print(f"\nSelf-Reflection Result: {str(result)[:200]}...")
|
||||
print("\n✅ Self-reflection optimization complete!")
|
||||
print("Agent demonstrated iterative improvement through built-in self-reflection capabilities.")
|
||||
print(f"\nSelf-Reflection Result: {result[:200]}...")
|
||||
print("\n✅ Self-reflection optimization complete!")
|
||||
print("Agent demonstrated iterative improvement through built-in self-reflection capabilities.")
|
||||
@@ -136,5 +136,4 @@ agents = AgentTeam(
|
||||
output="minimal",
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
agents.start()
|
||||
agents.start()
|
||||
@@ -1,201 +0,0 @@
|
||||
"""
|
||||
Prototype implementation of Gateway Server with backpressure and flow control.
|
||||
|
||||
This demonstrates how the bounded queues and slow consumer detection would be
|
||||
implemented in the wrapper layer (praisonai package) using the configuration
|
||||
from the core SDK (praisonaiagents).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
# For the prototype, we'll define minimal config inline
|
||||
# from praisonaiagents.gateway import GatewayConfig
|
||||
|
||||
@dataclass
|
||||
class SessionConfig:
|
||||
max_inbox: int = 256
|
||||
|
||||
@dataclass
|
||||
class GatewayConfig:
|
||||
session_config: SessionConfig = field(default_factory=SessionConfig)
|
||||
max_buffered_bytes: int = 1024 * 1024 # 1MB default
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class GatewaySession:
|
||||
"""Gateway session with bounded inbox for backpressure."""
|
||||
|
||||
_session_id: str
|
||||
_agent_id: str
|
||||
_client_id: Optional[str] = None
|
||||
_inbox: asyncio.Queue = field(default_factory=asyncio.Queue)
|
||||
_max_inbox: int = 256
|
||||
_is_executing: bool = False
|
||||
|
||||
def setup_inbox(self, max_inbox: int = 256) -> None:
|
||||
"""Set up the inbox with proper bounds."""
|
||||
self._max_inbox = max_inbox
|
||||
if max_inbox > 0:
|
||||
self._inbox = asyncio.Queue(maxsize=max_inbox)
|
||||
else:
|
||||
self._inbox = asyncio.Queue() # Unbounded for backward compat if 0
|
||||
|
||||
async def queue_message(self, message: str) -> bool:
|
||||
"""Queue a user message with backpressure handling.
|
||||
|
||||
Returns:
|
||||
True if message was queued, False if inbox is full.
|
||||
"""
|
||||
if self._max_inbox > 0:
|
||||
# Bounded queue - check if full
|
||||
try:
|
||||
self._inbox.put_nowait(message)
|
||||
return True
|
||||
except asyncio.QueueFull:
|
||||
return False
|
||||
else:
|
||||
# Unbounded queue for backward compatibility
|
||||
await self._inbox.put(message)
|
||||
return True
|
||||
|
||||
|
||||
class GatewayServer:
|
||||
"""Gateway server with flow control."""
|
||||
|
||||
def __init__(self, config: GatewayConfig):
|
||||
self.config = config
|
||||
self._sessions: Dict[str, GatewaySession] = {}
|
||||
self._clients: Dict[str, Any] = {} # client_id -> WebSocket
|
||||
|
||||
def create_session(self, session_id: str, agent_id: str, client_id: str) -> GatewaySession:
|
||||
"""Create a new session with bounded inbox."""
|
||||
session = GatewaySession(
|
||||
_session_id=session_id,
|
||||
_agent_id=agent_id,
|
||||
_client_id=client_id,
|
||||
)
|
||||
# Set up inbox with configured bounds
|
||||
session.setup_inbox(self.config.session_config.max_inbox)
|
||||
self._sessions[session_id] = session
|
||||
return session
|
||||
|
||||
async def handle_message(self, session: GatewaySession, message: str, client_id: str) -> str:
|
||||
"""Handle incoming message with inbox overflow protection."""
|
||||
# Try to queue the message
|
||||
queued = await session.queue_message(message)
|
||||
if not queued:
|
||||
# Inbox is full, send error response
|
||||
await self._send_to_client(
|
||||
client_id,
|
||||
{
|
||||
"type": "error",
|
||||
"code": "inbox_full",
|
||||
"message": "Message queue is full. Please wait for current messages to be processed."
|
||||
}
|
||||
)
|
||||
return "Inbox full - message rejected."
|
||||
|
||||
# Start processing if not already running
|
||||
if not session._is_executing:
|
||||
session._is_executing = True
|
||||
asyncio.create_task(self._drain_session_queue(session, client_id))
|
||||
return "Processing started."
|
||||
|
||||
return "Message queued."
|
||||
|
||||
async def _drain_session_queue(self, session: GatewaySession, client_id: str) -> None:
|
||||
"""Process all messages from the session's inbox queue."""
|
||||
try:
|
||||
while not session._inbox.empty():
|
||||
msg = await session._inbox.get()
|
||||
# Process message here (simplified for prototype)
|
||||
logger.info(f"Processing message for session {session._session_id}: {msg}")
|
||||
|
||||
# Simulate processing delay
|
||||
await asyncio.sleep(0.1)
|
||||
|
||||
# Send response to client (simplified)
|
||||
await self._send_to_client(
|
||||
client_id,
|
||||
{
|
||||
"type": "response",
|
||||
"message": f"Processed: {msg}"
|
||||
}
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing queue for session {session._session_id}: {e}")
|
||||
finally:
|
||||
session._is_executing = False
|
||||
|
||||
async def _send_to_client(self, client_id: str, data: Dict[str, Any]) -> None:
|
||||
"""Send data to client with slow consumer detection."""
|
||||
ws = self._clients.get(client_id)
|
||||
if ws:
|
||||
try:
|
||||
# Check for slow consumer (buffered bytes)
|
||||
if self.config.max_buffered_bytes > 0:
|
||||
# Try to get transport buffer size
|
||||
transport = getattr(ws, 'transport', None) or getattr(ws, '_transport', None)
|
||||
if transport and hasattr(transport, 'get_write_buffer_size'):
|
||||
buffered_bytes = transport.get_write_buffer_size()
|
||||
if buffered_bytes > self.config.max_buffered_bytes:
|
||||
# Check if this is a droppable event type
|
||||
event_type = data.get("type", "")
|
||||
droppable_types = {"presence", "typing", "status"}
|
||||
|
||||
if event_type in droppable_types:
|
||||
# Drop the message for slow consumers
|
||||
logger.warning(f"Dropping {event_type} event for slow consumer {client_id} (buffered: {buffered_bytes} bytes)")
|
||||
return
|
||||
else:
|
||||
# Critical event - close the connection
|
||||
logger.warning(f"Closing slow consumer {client_id} (buffered: {buffered_bytes} bytes > {self.config.max_buffered_bytes})")
|
||||
await ws.close(code=1013, reason="slow consumer")
|
||||
return
|
||||
|
||||
# Send the message
|
||||
await ws.send_json(data)
|
||||
except Exception as e:
|
||||
logger.error(f"Error sending to client {client_id}: {e}", exc_info=True)
|
||||
|
||||
|
||||
# Example usage demonstrating the flow control
|
||||
async def demo():
|
||||
"""Demonstrate the flow control implementation."""
|
||||
|
||||
# Create config with bounded inbox and slow consumer detection
|
||||
config = GatewayConfig()
|
||||
config.session_config.max_inbox = 10 # Small inbox for demo
|
||||
config.max_buffered_bytes = 1024 # 1KB for demo
|
||||
|
||||
# Create server and session
|
||||
server = GatewayServer(config)
|
||||
session = server.create_session("sess1", "agent1", "client1")
|
||||
|
||||
# Simulate filling up the inbox
|
||||
print(f"Inbox max size: {session._inbox.maxsize}")
|
||||
|
||||
# Fill the inbox
|
||||
for i in range(10):
|
||||
success = await session.queue_message(f"Message {i}")
|
||||
print(f"Queued message {i}: {success}")
|
||||
|
||||
# Try to add one more - should fail
|
||||
success = await session.queue_message("Overflow message")
|
||||
print(f"Overflow message queued: {success}")
|
||||
|
||||
# Process messages
|
||||
while not session._inbox.empty():
|
||||
msg = await session._inbox.get()
|
||||
print(f"Processing: {msg}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(demo())
|
||||
@@ -49,20 +49,10 @@ agents = AgentTeam(
|
||||
process="sequential"
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Run all tasks
|
||||
result = agents.start()
|
||||
# Run all tasks
|
||||
result = agents.start()
|
||||
|
||||
# Print results
|
||||
task_results = result.get("task_results") if isinstance(result, dict) else result
|
||||
if isinstance(task_results, dict):
|
||||
iterable = task_results.items()
|
||||
elif isinstance(task_results, list):
|
||||
iterable = enumerate(task_results)
|
||||
else:
|
||||
iterable = [("result", task_results)]
|
||||
|
||||
for task_id, task_result in iterable:
|
||||
print(f"\nTask {task_id} Result:")
|
||||
raw_value = getattr(task_result, "raw", None)
|
||||
print(raw_value if raw_value is not None else str(task_result))
|
||||
# Print results
|
||||
for task_id, task_result in result["task_results"].items():
|
||||
print(f"\nTask {task_id} Result:")
|
||||
print(task_result.raw)
|
||||
@@ -4,70 +4,43 @@ Basic handoff example demonstrating agent-to-agent delegation.
|
||||
This example shows how agents can hand off tasks to specialized agents.
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel
|
||||
from typing import TypedDict, Optional
|
||||
from praisonaiagents import Agent
|
||||
|
||||
# Define typed payload contracts for each handoff
|
||||
class BillingPayload(BaseModel):
|
||||
account_id: str
|
||||
invoice_amount: Optional[float] = None
|
||||
issue_type: str = "billing"
|
||||
|
||||
class RefundPayload(TypedDict):
|
||||
transaction_id: str
|
||||
amount: float
|
||||
reason: str
|
||||
|
||||
class TechnicalPayload(BaseModel):
|
||||
error_code: Optional[str] = None
|
||||
device_info: str
|
||||
user_agent: str
|
||||
|
||||
# Create specialized agents that expect typed payloads from the triage
|
||||
# (In a real scenario, the agents would validate and use the payload.)
|
||||
# Create specialized agents
|
||||
billing_agent = Agent(
|
||||
name="Billing Agent",
|
||||
role="Billing Specialist",
|
||||
goal="Handle all billing-related inquiries and tasks using structured data",
|
||||
backstory="I am an expert in billing systems, payment processing, and invoice management.",
|
||||
input_payload_schema=BillingPayload # hypothetical but consistent with design
|
||||
goal="Handle all billing-related inquiries and tasks",
|
||||
backstory="I am an expert in billing systems, payment processing, and invoice management."
|
||||
)
|
||||
|
||||
refund_agent = Agent(
|
||||
name="Refund Agent",
|
||||
role="Refund Specialist",
|
||||
goal="Process refund requests and handle refund-related issues with validated data",
|
||||
backstory="I specialize in processing refunds, evaluating refund eligibility, and ensuring customer satisfaction.",
|
||||
input_payload_schema=RefundPayload
|
||||
goal="Process refund requests and handle refund-related issues",
|
||||
backstory="I specialize in processing refunds, evaluating refund eligibility, and ensuring customer satisfaction."
|
||||
)
|
||||
|
||||
technical_support_agent = Agent(
|
||||
name="Technical Support",
|
||||
role="Technical Support Specialist",
|
||||
goal="Resolve technical issues and provide technical assistance with structured context",
|
||||
backstory="I am skilled in troubleshooting technical problems and providing solutions.",
|
||||
input_payload_schema=TechnicalPayload
|
||||
goal="Resolve technical issues and provide technical assistance",
|
||||
backstory="I am skilled in troubleshooting technical problems and providing solutions."
|
||||
)
|
||||
|
||||
# Create a triage agent with typed handoffs
|
||||
# Create a triage agent with handoffs to specialized agents
|
||||
triage_agent = Agent(
|
||||
name="Triage Agent",
|
||||
role="Customer Service Triage",
|
||||
goal="Understand customer needs and route them to the appropriate specialist with a validated payload",
|
||||
goal="Understand customer needs and route them to the appropriate specialist",
|
||||
backstory="I analyze customer requests and direct them to the most suitable specialist for efficient resolution.",
|
||||
instructions="""Analyze the customer's request and determine which specialist can best help:
|
||||
- For billing questions, payment issues, or invoices, transfer to the Billing Agent
|
||||
- For refund requests or refund status inquiries, transfer to the Refund Agent
|
||||
- For technical problems or product issues, transfer to Technical Support
|
||||
|
||||
Always explain why you're transferring the customer before doing so.
|
||||
When handing off, populate the appropriate payload with extracted data.""",
|
||||
handoffs=[
|
||||
(billing_agent, BillingPayload),
|
||||
(refund_agent, RefundPayload),
|
||||
(technical_support_agent, TechnicalPayload)
|
||||
]
|
||||
Always explain why you're transferring the customer before doing so.""",
|
||||
handoffs=[billing_agent, refund_agent, technical_support_agent]
|
||||
)
|
||||
|
||||
# Example usage
|
||||
|
||||
@@ -14,33 +14,30 @@ agent = Agent(name="env-mgmt", backend=managed)
|
||||
# First call creates agent + environment + session
|
||||
agent.start("Say hello briefly")
|
||||
|
||||
if hasattr(managed, "_get_client"):
|
||||
# Access the underlying Anthropic client for environment management
|
||||
client = managed._get_client()
|
||||
env_id = managed.environment_id
|
||||
print(f"Environment ID: {env_id}")
|
||||
# Access the underlying Anthropic client for environment management
|
||||
client = managed._get_client()
|
||||
env_id = managed.environment_id
|
||||
print(f"Environment ID: {env_id}")
|
||||
|
||||
# List all environments
|
||||
environments = client.beta.environments.list()
|
||||
print(f"\nTotal environments: {len(environments.data)}")
|
||||
for env in environments.data[:5]:
|
||||
print(f" {env.id} | {env.name} | {getattr(env, 'status', 'active')}")
|
||||
# List all environments
|
||||
environments = client.beta.environments.list()
|
||||
print(f"\nTotal environments: {len(environments.data)}")
|
||||
for env in environments.data[:5]:
|
||||
print(f" {env.id} | {env.name} | {getattr(env, 'status', 'active')}")
|
||||
|
||||
# Retrieve a specific environment
|
||||
env = client.beta.environments.retrieve(env_id)
|
||||
print(f"\nRetrieved: {env.id} | {env.name}")
|
||||
# Retrieve a specific environment
|
||||
env = client.beta.environments.retrieve(env_id)
|
||||
print(f"\nRetrieved: {env.id} | {env.name}")
|
||||
|
||||
# Archive (read-only, existing sessions continue)
|
||||
archived = client.beta.environments.archive(env_id)
|
||||
print(f"Archived: {archived.id} | status: {getattr(archived, 'status', 'archived')}")
|
||||
# Archive (read-only, existing sessions continue)
|
||||
archived = client.beta.environments.archive(env_id)
|
||||
print(f"Archived: {archived.id} | status: {getattr(archived, 'status', 'archived')}")
|
||||
|
||||
# Delete (only if no sessions reference it — may fail if sessions exist)
|
||||
try:
|
||||
client.beta.environments.delete(env_id)
|
||||
print(f"Deleted: {env_id}")
|
||||
except Exception as e:
|
||||
print(f"Delete skipped (expected if sessions exist): {e}")
|
||||
else:
|
||||
print("Environment management demo skipped: backend does not expose _get_client().")
|
||||
# Delete (only if no sessions reference it — may fail if sessions exist)
|
||||
try:
|
||||
client.beta.environments.delete(env_id)
|
||||
print(f"Deleted: {env_id}")
|
||||
except Exception as e:
|
||||
print(f"Delete skipped (expected if sessions exist): {e}")
|
||||
|
||||
print("\nEnvironment management complete.")
|
||||
@@ -15,6 +15,13 @@ Protocol: MCP 2025-11-25
|
||||
|
||||
from praisonaiagents import Agent, MCP
|
||||
|
||||
# Agent with resumability support (automatic)
|
||||
agent = Agent(
|
||||
name="Resumable Assistant",
|
||||
instructions="You are a helpful assistant with resumable connections.",
|
||||
tools=MCP("https://api.example.com/mcp")
|
||||
)
|
||||
|
||||
# Resumability is automatic - the MCP client:
|
||||
# 1. Tracks event IDs from SSE streams (id: field)
|
||||
# 2. Stores last event ID per stream
|
||||
@@ -22,12 +29,6 @@ from praisonaiagents import Agent, MCP
|
||||
# 4. Respects retry delay from server (retry: field)
|
||||
|
||||
if __name__ == "__main__":
|
||||
agent = Agent(
|
||||
name="Resumable Assistant",
|
||||
instructions="You are a helpful assistant with resumable connections.",
|
||||
tools=MCP("https://api.example.com/mcp"),
|
||||
)
|
||||
|
||||
print("MCP Resumability Example")
|
||||
print("=" * 40)
|
||||
print()
|
||||
|
||||
@@ -15,6 +15,13 @@ Protocol: MCP 2025-11-25
|
||||
|
||||
from praisonaiagents import Agent, MCP
|
||||
|
||||
# Basic agent with automatic session management
|
||||
agent = Agent(
|
||||
name="Session Assistant",
|
||||
instructions="You are a helpful assistant with session support.",
|
||||
tools=MCP("https://api.example.com/mcp")
|
||||
)
|
||||
|
||||
# Session management is automatic - the MCP client:
|
||||
# 1. Receives Mcp-Session-Id from server during initialization
|
||||
# 2. Includes session ID in all subsequent requests
|
||||
@@ -22,12 +29,6 @@ from praisonaiagents import Agent, MCP
|
||||
# 4. Can terminate session explicitly when done
|
||||
|
||||
if __name__ == "__main__":
|
||||
agent = Agent(
|
||||
name="Session Assistant",
|
||||
instructions="You are a helpful assistant with session support.",
|
||||
tools=MCP("https://api.example.com/mcp"),
|
||||
)
|
||||
|
||||
print("MCP Session Management Example")
|
||||
print("=" * 40)
|
||||
print()
|
||||
|
||||
@@ -16,31 +16,34 @@ Protocol: MCP 2025-11-25
|
||||
|
||||
from praisonaiagents import Agent, MCP
|
||||
|
||||
# Basic Streamable HTTP connection
|
||||
agent = Agent(
|
||||
name="HTTP Stream Assistant",
|
||||
instructions="You are a helpful assistant connected via Streamable HTTP.",
|
||||
tools=MCP("https://api.example.com/mcp")
|
||||
)
|
||||
|
||||
# With authentication headers
|
||||
agent_auth = Agent(
|
||||
name="Authenticated Assistant",
|
||||
instructions="You are a helpful assistant with authenticated connection.",
|
||||
tools=MCP(
|
||||
"https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer your-token"}
|
||||
)
|
||||
)
|
||||
|
||||
# With timeout and debug
|
||||
agent_debug = Agent(
|
||||
name="Debug Assistant",
|
||||
tools=MCP(
|
||||
"https://api.example.com/mcp",
|
||||
timeout=120,
|
||||
debug=True
|
||||
)
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
agent = Agent(
|
||||
name="HTTP Stream Assistant",
|
||||
instructions="You are a helpful assistant connected via Streamable HTTP.",
|
||||
tools=MCP("https://api.example.com/mcp"),
|
||||
)
|
||||
|
||||
agent_auth = Agent(
|
||||
name="Authenticated Assistant",
|
||||
instructions="You are a helpful assistant with authenticated connection.",
|
||||
tools=MCP(
|
||||
"https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer your-token"},
|
||||
),
|
||||
)
|
||||
|
||||
agent_debug = Agent(
|
||||
name="Debug Assistant",
|
||||
tools=MCP(
|
||||
"https://api.example.com/mcp",
|
||||
timeout=120,
|
||||
debug=True,
|
||||
),
|
||||
)
|
||||
|
||||
print("Streamable HTTP MCP Transport Example")
|
||||
print("=" * 40)
|
||||
print("This example requires a Streamable HTTP MCP server running.")
|
||||
|
||||
@@ -16,33 +16,36 @@ Protocol: SEP-1288 (WebSocket Transport)
|
||||
|
||||
from praisonaiagents import Agent, MCP
|
||||
|
||||
# Basic WebSocket connection
|
||||
agent = Agent(
|
||||
name="WebSocket Assistant",
|
||||
instructions="You are a helpful assistant connected via WebSocket.",
|
||||
tools=MCP("ws://localhost:8080/mcp")
|
||||
)
|
||||
|
||||
# Secure WebSocket with authentication
|
||||
agent_secure = Agent(
|
||||
name="Secure WebSocket Assistant",
|
||||
instructions="You are a helpful assistant with secure WebSocket connection.",
|
||||
tools=MCP(
|
||||
"wss://api.example.com/mcp",
|
||||
auth_token="Bearer your-secret-token",
|
||||
timeout=60
|
||||
)
|
||||
)
|
||||
|
||||
# WebSocket with custom options
|
||||
agent_custom = Agent(
|
||||
name="Custom WebSocket Assistant",
|
||||
tools=MCP(
|
||||
"wss://api.example.com/mcp",
|
||||
auth_token="your-token",
|
||||
timeout=120,
|
||||
debug=True
|
||||
)
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
agent = Agent(
|
||||
name="WebSocket Assistant",
|
||||
instructions="You are a helpful assistant connected via WebSocket.",
|
||||
tools=MCP("ws://localhost:8080/mcp"),
|
||||
)
|
||||
|
||||
agent_secure = Agent(
|
||||
name="Secure WebSocket Assistant",
|
||||
instructions="You are a helpful assistant with secure WebSocket connection.",
|
||||
tools=MCP(
|
||||
"wss://api.example.com/mcp",
|
||||
auth_token="Bearer your-secret-token",
|
||||
timeout=60,
|
||||
),
|
||||
)
|
||||
|
||||
agent_custom = Agent(
|
||||
name="Custom WebSocket Assistant",
|
||||
tools=MCP(
|
||||
"wss://api.example.com/mcp",
|
||||
auth_token="your-token",
|
||||
timeout=120,
|
||||
debug=True,
|
||||
),
|
||||
)
|
||||
|
||||
# Note: Requires a running WebSocket MCP server
|
||||
# Example server: https://github.com/modelcontextprotocol/servers
|
||||
|
||||
|
||||
@@ -1,173 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Message Steering Example
|
||||
|
||||
Demonstrates real-time message steering for agents during execution.
|
||||
Shows how to send guidance messages to agents while they're running tasks.
|
||||
|
||||
Usage:
|
||||
# Python API
|
||||
python message_steering_example.py
|
||||
|
||||
# CLI with steering enabled
|
||||
praisonai --message-steering "Write a detailed report about AI trends"
|
||||
|
||||
# YAML (add message_steering: true to agent config)
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import threading
|
||||
import time
|
||||
from praisonaiagents import Agent
|
||||
|
||||
|
||||
def basic_message_steering():
|
||||
"""Basic message steering example - enable steering and send guidance."""
|
||||
print("🎯 Basic Message Steering Example")
|
||||
print("=" * 50)
|
||||
|
||||
# Create agent with message steering enabled
|
||||
agent = Agent(
|
||||
name="researcher",
|
||||
instructions="You are a helpful research assistant",
|
||||
message_steering=True, # Enable real-time message steering
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print("✅ Agent created with message steering enabled")
|
||||
print(f"📊 Steering status: {agent.get_steering_status()}")
|
||||
|
||||
# Send some guidance
|
||||
msg_id_1 = agent.steer("Focus on recent developments from 2024")
|
||||
msg_id_2 = agent.steer("Keep response under 200 words", priority=10)
|
||||
|
||||
print(f"📨 Sent steering messages: {msg_id_1}, {msg_id_2}")
|
||||
print(f"📊 Steering status: {agent.get_steering_status()}")
|
||||
|
||||
# Execute task - steering will be automatically injected
|
||||
result = agent.start("Summarize the latest AI trends")
|
||||
|
||||
print("\n📝 Result:")
|
||||
print(result)
|
||||
|
||||
|
||||
def threaded_message_steering():
|
||||
"""Advanced example - send steering messages while agent is running."""
|
||||
print("\n🚀 Threaded Message Steering Example")
|
||||
print("=" * 50)
|
||||
|
||||
agent = Agent(
|
||||
name="writer",
|
||||
instructions="You are a content writer",
|
||||
message_steering=True,
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
result_holder = [None]
|
||||
|
||||
def run_agent():
|
||||
"""Run agent in background thread."""
|
||||
result = agent.start("Write a comprehensive article about quantum computing")
|
||||
result_holder[0] = result
|
||||
|
||||
# Start agent in background
|
||||
thread = threading.Thread(target=run_agent)
|
||||
thread.start()
|
||||
|
||||
# Send steering messages while it's running
|
||||
time.sleep(0.5) # Let execution start
|
||||
agent.steer("Make it accessible to beginners")
|
||||
|
||||
time.sleep(1.0)
|
||||
agent.steer("Include practical applications", priority=15)
|
||||
|
||||
time.sleep(1.5)
|
||||
agent.steer("Keep it under 300 words total", priority=20)
|
||||
|
||||
# Wait for completion
|
||||
thread.join(timeout=60)
|
||||
|
||||
if result_holder[0]:
|
||||
print("\n📝 Final Result:")
|
||||
print(result_holder[0])
|
||||
else:
|
||||
print("⚠️ Agent execution timed out")
|
||||
|
||||
|
||||
async def async_message_steering():
|
||||
"""Async example showing message steering with async execution."""
|
||||
print("\n⚡ Async Message Steering Example")
|
||||
print("=" * 50)
|
||||
|
||||
agent = Agent(
|
||||
name="analyst",
|
||||
instructions="You are a data analyst",
|
||||
message_steering=True,
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Start async task
|
||||
async def run_analysis():
|
||||
return await agent.astart("Analyze the impact of AI on job markets")
|
||||
|
||||
# Create task
|
||||
task = asyncio.create_task(run_analysis())
|
||||
|
||||
# Send steering while running
|
||||
await asyncio.sleep(0.3)
|
||||
agent.steer("Focus on positive opportunities")
|
||||
|
||||
await asyncio.sleep(0.7)
|
||||
agent.steer("Include specific examples", priority=12)
|
||||
|
||||
# Wait for result
|
||||
result = await task
|
||||
|
||||
print("\n📝 Analysis Result:")
|
||||
print(result)
|
||||
|
||||
|
||||
def cli_yaml_examples():
|
||||
"""Show CLI and YAML usage examples."""
|
||||
print("\n💻 CLI & YAML Examples")
|
||||
print("=" * 50)
|
||||
|
||||
print("🔧 CLI Usage:")
|
||||
print(" praisonai --message-steering 'Your task here'")
|
||||
print(" # Then in another terminal:")
|
||||
print(" # agent.steer('Additional guidance')")
|
||||
|
||||
print("\n📄 YAML Configuration:")
|
||||
yaml_example = """
|
||||
# agents.yaml
|
||||
framework: praisonai
|
||||
roles:
|
||||
researcher:
|
||||
role: Research Assistant
|
||||
goal: Conduct thorough research
|
||||
backstory: Expert researcher with steering support
|
||||
message_steering: true # Enable steering for this agent
|
||||
tools:
|
||||
- internet_search
|
||||
- write_file
|
||||
tasks:
|
||||
research_task:
|
||||
description: Research AI trends and write report
|
||||
expected_output: Comprehensive research report
|
||||
"""
|
||||
print(yaml_example.strip())
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# Run examples
|
||||
basic_message_steering()
|
||||
threaded_message_steering()
|
||||
|
||||
# Run async example
|
||||
asyncio.run(async_message_steering())
|
||||
|
||||
# Show CLI/YAML usage
|
||||
cli_yaml_examples()
|
||||
|
||||
print("\n✨ Message steering examples completed!")
|
||||
print("📚 See docs for more advanced patterns and priority levels")
|
||||
@@ -1,124 +0,0 @@
|
||||
"""
|
||||
Example: Using MuAPI with PraisonAI for image generation.
|
||||
|
||||
MuAPI (https://muapi.ai) provides unified access to 400+ generative media
|
||||
models — Flux, Midjourney, GPT-4o Image, Google Imagen, Seedream, Veo3,
|
||||
Kling, Wan, and more — through a single API.
|
||||
|
||||
This example creates a PraisonAI agent that generates images on demand
|
||||
using the MuAPI image generation API as a custom tool.
|
||||
|
||||
Setup:
|
||||
pip install praisonaiagents requests
|
||||
export MUAPI_API_KEY=your_key_here
|
||||
# Get an API key at https://muapi.ai/dashboard/api-keys
|
||||
"""
|
||||
|
||||
import os
|
||||
import time
|
||||
|
||||
import requests
|
||||
from praisonaiagents import Agent, Tool
|
||||
|
||||
|
||||
MUAPI_BASE_URL = "https://api.muapi.ai/api/v1"
|
||||
|
||||
ALLOWED_MODELS = {
|
||||
"flux-schnell", "flux-dev", "flux-kontext-dev", "flux-kontext-pro",
|
||||
"midjourney", "gpt4o", "imagen4", "imagen4-fast", "seedream",
|
||||
"hidream-fast", "hidream-dev", "reve", "ideogram", "hunyuan",
|
||||
}
|
||||
|
||||
|
||||
def generate_image(prompt: str, model: str = "flux-schnell") -> str:
|
||||
"""Generate an image using MuAPI and return the output URL.
|
||||
|
||||
Args:
|
||||
prompt: Text description of the image to generate.
|
||||
model: MuAPI model ID. Options include flux-schnell, flux-dev,
|
||||
midjourney, gpt4o, imagen4, seedream, hidream-fast, reve.
|
||||
|
||||
Returns:
|
||||
URL of the generated image.
|
||||
"""
|
||||
if model not in ALLOWED_MODELS:
|
||||
raise ValueError(
|
||||
f"Unsupported model '{model}'. Choose from: {sorted(ALLOWED_MODELS)}"
|
||||
)
|
||||
|
||||
api_key = os.environ.get("MUAPI_API_KEY", "")
|
||||
if not api_key:
|
||||
raise ValueError("MUAPI_API_KEY environment variable not set")
|
||||
|
||||
headers = {"x-api-key": api_key, "Content-Type": "application/json"}
|
||||
|
||||
# Submit the generation request
|
||||
submit_resp = requests.post(
|
||||
f"{MUAPI_BASE_URL}/{model}",
|
||||
headers=headers,
|
||||
json={"prompt": prompt},
|
||||
timeout=30,
|
||||
)
|
||||
submit_resp.raise_for_status()
|
||||
submit_data = submit_resp.json()
|
||||
request_id = submit_data.get("request_id")
|
||||
if not request_id:
|
||||
raise RuntimeError(f"MuAPI did not return a request_id: {submit_data}")
|
||||
|
||||
# Poll until completion
|
||||
for _ in range(120):
|
||||
time.sleep(3)
|
||||
poll_resp = requests.get(
|
||||
f"{MUAPI_BASE_URL}/predictions/{request_id}/result",
|
||||
headers={"x-api-key": api_key},
|
||||
timeout=15,
|
||||
)
|
||||
poll_resp.raise_for_status()
|
||||
data = poll_resp.json()
|
||||
status = data.get("status")
|
||||
if status == "completed":
|
||||
outputs = data.get("outputs") or []
|
||||
if not outputs:
|
||||
raise RuntimeError(f"Generation completed but returned no outputs: {data}")
|
||||
return outputs[0]
|
||||
if status in ("failed", "cancelled"):
|
||||
raise RuntimeError(f"Image generation {status}: {data.get('error', '')}")
|
||||
|
||||
raise TimeoutError("Image generation timed out after 6 minutes")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
image_tool = Tool(
|
||||
name="generate_image",
|
||||
description=(
|
||||
"Generate an image from a text description using MuAPI's 400+ model library. "
|
||||
"Supported models: flux-schnell (fast), flux-dev, midjourney, gpt4o, imagen4, "
|
||||
"seedream, hidream-fast, reve. Returns a URL to the generated image."
|
||||
),
|
||||
function=generate_image,
|
||||
)
|
||||
|
||||
agent = Agent(
|
||||
name="Image Generator",
|
||||
instructions=(
|
||||
"You are a creative image generation assistant. "
|
||||
"When asked to create an image, use the generate_image tool. "
|
||||
"Pick the best model for the task: flux-schnell for speed, "
|
||||
"midjourney for artistic quality, gpt4o for photorealism."
|
||||
),
|
||||
tools=[image_tool],
|
||||
)
|
||||
|
||||
# Example: generate a product photo
|
||||
response = agent.start(
|
||||
"Generate a photorealistic product photo of a sleek black coffee mug "
|
||||
"on a white marble table with soft morning light. Use the best model for photorealism."
|
||||
)
|
||||
print(response)
|
||||
|
||||
# Example: generate concept art
|
||||
response = agent.start(
|
||||
"Create a cyberpunk cityscape at night with neon reflections on wet streets. "
|
||||
"Use midjourney for artistic quality."
|
||||
)
|
||||
print(response)
|
||||
@@ -12,6 +12,7 @@ Environment:
|
||||
"""
|
||||
|
||||
import os
|
||||
import tempfile
|
||||
from praisonaiagents import Agent, AutoRagAgent
|
||||
|
||||
# Ensure API key is set
|
||||
@@ -20,8 +21,7 @@ if not os.environ.get("OPENAI_API_KEY"):
|
||||
exit(1)
|
||||
|
||||
# Create a sample document for testing
|
||||
from pathlib import Path
|
||||
sample_doc = str(Path(__file__).with_name("sample_doc.txt"))
|
||||
sample_doc = os.path.join(tempfile.gettempdir(), "sample_doc.txt")
|
||||
with open(sample_doc, "w", encoding="utf-8") as f:
|
||||
f.write("""
|
||||
PraisonAI Framework Documentation
|
||||
|
||||
@@ -4,7 +4,7 @@ Example 3: Save Agent Output Using Workflow output_file
|
||||
Workflow step output is automatically saved with variable substitution.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, AgentFlow, Task
|
||||
from praisonaiagents import AgentFlow
|
||||
|
||||
# Define workflow with output_file
|
||||
workflow_config = {
|
||||
@@ -33,30 +33,9 @@ workflow_config = {
|
||||
]
|
||||
}
|
||||
|
||||
# Build agent and workflow from config dict
|
||||
writer_cfg = workflow_config["agents"]["writer"]
|
||||
writer = Agent(
|
||||
name="writer",
|
||||
role=writer_cfg["role"],
|
||||
goal=writer_cfg["goal"],
|
||||
llm=writer_cfg["llm"],
|
||||
)
|
||||
|
||||
step_cfg = workflow_config["steps"][0]
|
||||
workflow = AgentFlow(
|
||||
name=workflow_config["metadata"]["name"],
|
||||
variables=workflow_config["variables"],
|
||||
steps=[
|
||||
Task(
|
||||
name="write_tutorial",
|
||||
description=step_cfg["action"],
|
||||
expected_output=step_cfg["expected_output"],
|
||||
output_file=step_cfg["output_file"],
|
||||
agent=writer,
|
||||
)
|
||||
],
|
||||
)
|
||||
result = workflow.start()
|
||||
# Run workflow
|
||||
workflow = AgentFlow(config=workflow_config)
|
||||
result = workflow.run()
|
||||
|
||||
print("✅ Workflow completed!")
|
||||
print("Output saved to: generated/tutorial.md")
|
||||
@@ -69,10 +69,9 @@ agents_system = AgentTeam(
|
||||
memory=True, output="verbose"
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("Starting state management demonstration...")
|
||||
result = agents_system.start()
|
||||
print("Starting state management demonstration...")
|
||||
result = agents_system.start()
|
||||
|
||||
print(f"\nState Management Result: {str(result)[:200]}...")
|
||||
print("\n✅ State management patterns complete!")
|
||||
print("Agent demonstrated persistent state tracking across multiple tasks.")
|
||||
print(f"\nState Management Result: {result[:200]}...")
|
||||
print("\n✅ State management patterns complete!")
|
||||
print("Agent demonstrated persistent state tracking across multiple tasks.")
|
||||
@@ -179,7 +179,7 @@ def main():
|
||||
|
||||
context = memory.build_context_for_task(
|
||||
task_descr="Explain AI alignment challenges",
|
||||
memory={"user_id": "quality_demo_user"},
|
||||
user_id="quality_demo_user",
|
||||
max_items=3
|
||||
)
|
||||
|
||||
|
||||
@@ -1,55 +1,284 @@
|
||||
"""
|
||||
Production Telemetry Example
|
||||
|
||||
Demonstrates compatible telemetry setup with `enable_telemetry()` and
|
||||
`TelemetryCollector` patterns.
|
||||
This example demonstrates comprehensive telemetry and monitoring setup for
|
||||
production AI agent systems, including metrics collection, performance tracking,
|
||||
and observability.
|
||||
|
||||
Features demonstrated:
|
||||
- OpenTelemetry integration for distributed tracing
|
||||
- Custom metrics collection and monitoring
|
||||
- Performance tracking and analytics
|
||||
- Error tracking and alerting
|
||||
- Usage analytics and reporting
|
||||
"""
|
||||
|
||||
from contextlib import nullcontext
|
||||
from praisonaiagents import Agent, Task, AgentTeam
|
||||
from praisonaiagents.tools import duckduckgo
|
||||
from praisonaiagents.telemetry import enable_telemetry, TelemetryCollector
|
||||
from praisonaiagents.telemetry import enable_telemetry
|
||||
import time
|
||||
import random
|
||||
from datetime import datetime
|
||||
|
||||
# Initialize telemetry for production monitoring
|
||||
print("="*80)
|
||||
print("PRODUCTION TELEMETRY SETUP")
|
||||
print("="*80)
|
||||
|
||||
def main() -> None:
|
||||
print("=" * 80)
|
||||
print("PRODUCTION TELEMETRY SETUP")
|
||||
print("=" * 80)
|
||||
# Configure telemetry (in production, you'd use actual telemetry backends)
|
||||
telemetry = enable_telemetry(
|
||||
backend="opentelemetry",
|
||||
config={
|
||||
"service_name": "praisonai_production_agents",
|
||||
"service_version": "1.0.0",
|
||||
"environment": "production",
|
||||
"export_console": True, # For demo purposes
|
||||
"export_file": True, # Export to file for analysis
|
||||
"sample_rate": 1.0, # 100% sampling for demo
|
||||
"attributes": {
|
||||
"deployment": "cloud",
|
||||
"region": "us-east-1",
|
||||
"cluster": "main"
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
# New API: no args
|
||||
enable_telemetry()
|
||||
collector = TelemetryCollector()
|
||||
# Create agents for production workflow with telemetry
|
||||
customer_service_agent = Agent(
|
||||
name="CustomerServiceAgent",
|
||||
role="Customer Service Representative",
|
||||
goal="Provide excellent customer service with fast response times",
|
||||
backstory="You are a customer service representative focused on resolving customer issues quickly and effectively.",
|
||||
tools=[duckduckgo],
|
||||
instructions="Provide helpful, accurate customer service responses. Research solutions when needed."
|
||||
)
|
||||
|
||||
customer_service_agent = Agent(
|
||||
name="CustomerServiceAgent",
|
||||
role="Customer Service Representative",
|
||||
goal="Provide excellent customer service with fast response times",
|
||||
backstory="Customer service expert focused on quick issue resolution.",
|
||||
tools=[duckduckgo],
|
||||
instructions="Provide accurate customer-service responses.",
|
||||
)
|
||||
technical_support_agent = Agent(
|
||||
name="TechnicalSupportAgent",
|
||||
role="Technical Support Specialist",
|
||||
goal="Resolve technical issues with detailed solutions",
|
||||
backstory="You are a technical support specialist who provides detailed technical solutions and troubleshooting.",
|
||||
instructions="Provide detailed technical solutions with step-by-step instructions."
|
||||
)
|
||||
|
||||
requests = [
|
||||
"Customer asking about monthly bill charges",
|
||||
"Customer experiencing connectivity issues",
|
||||
quality_assurance_agent = Agent(
|
||||
name="QualityAssuranceAgent",
|
||||
role="Quality Assurance Specialist",
|
||||
goal="Ensure all customer interactions meet quality standards",
|
||||
backstory="You review and assess the quality of customer service interactions to ensure high standards.",
|
||||
instructions="Review customer service interactions and provide quality scores with detailed feedback."
|
||||
)
|
||||
|
||||
# Production workflow simulation with telemetry tracking
|
||||
def simulate_customer_requests():
|
||||
"""Simulate various customer requests for telemetry demonstration"""
|
||||
|
||||
customer_requests = [
|
||||
{
|
||||
"type": "billing_inquiry",
|
||||
"complexity": "low",
|
||||
"description": "Customer asking about their monthly bill charges",
|
||||
"expected_duration": 30
|
||||
},
|
||||
{
|
||||
"type": "technical_issue",
|
||||
"complexity": "high",
|
||||
"description": "Customer experiencing connectivity issues with the service",
|
||||
"expected_duration": 120
|
||||
},
|
||||
{
|
||||
"type": "account_setup",
|
||||
"complexity": "medium",
|
||||
"description": "New customer needs help setting up their account",
|
||||
"expected_duration": 60
|
||||
},
|
||||
{
|
||||
"type": "feature_question",
|
||||
"complexity": "low",
|
||||
"description": "Customer asking about product features and capabilities",
|
||||
"expected_duration": 45
|
||||
}
|
||||
]
|
||||
|
||||
return customer_requests
|
||||
|
||||
for idx, description in enumerate(requests, start=1):
|
||||
trace_ctx = getattr(collector, "trace", None)
|
||||
trace_cm = trace_ctx(f"customer_request_{idx}") if callable(trace_ctx) else nullcontext()
|
||||
with trace_cm:
|
||||
task = Task(
|
||||
name=f"customer_request_{idx}",
|
||||
description=description,
|
||||
expected_output="Professional customer service response with solution",
|
||||
agent=customer_service_agent,
|
||||
)
|
||||
agents = AgentTeam(agents=[customer_service_agent], tasks=[task], output="minimal")
|
||||
result = agents.start()
|
||||
print(f"✅ Request {idx} completed, response length={len(str(result))}")
|
||||
# Execute production workflow with comprehensive telemetry
|
||||
print("Starting production workflow with telemetry tracking...")
|
||||
|
||||
print("\nTelemetry demonstration completed.")
|
||||
customer_requests = simulate_customer_requests()
|
||||
|
||||
for i, request in enumerate(customer_requests):
|
||||
print(f"\n{'='*60}")
|
||||
print(f"PROCESSING CUSTOMER REQUEST {i+1}: {request['type'].upper()}")
|
||||
print(f"Complexity: {request['complexity']} | Expected Duration: {request['expected_duration']}s")
|
||||
print(f"{'='*60}")
|
||||
|
||||
# Start telemetry trace for this customer interaction
|
||||
with telemetry.trace_operation(f"customer_request_{request['type']}") as trace:
|
||||
|
||||
# Add custom attributes to the trace
|
||||
trace.set_attributes({
|
||||
"request.type": request['type'],
|
||||
"request.complexity": request['complexity'],
|
||||
"request.expected_duration": request['expected_duration'],
|
||||
"customer.id": f"customer_{random.randint(1000, 9999)}",
|
||||
"agent.assigned": "CustomerServiceAgent"
|
||||
})
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
# Create customer service task with telemetry
|
||||
customer_task = Task(
|
||||
name=f"customer_request_{i+1}",
|
||||
description=request['description'],
|
||||
expected_output="Professional customer service response with solution",
|
||||
agent=customer_service_agent
|
||||
)
|
||||
|
||||
# Execute with telemetry tracking
|
||||
try:
|
||||
# Customer service response
|
||||
with telemetry.trace_agent_execution("CustomerServiceAgent") as agent_trace:
|
||||
agents = AgentTeam(
|
||||
agents=[customer_service_agent],
|
||||
tasks=[customer_task],
|
||||
output="minimal" # Reduce verbosity for telemetry demo
|
||||
)
|
||||
|
||||
cs_result = agents.start()
|
||||
agent_trace.set_attributes({
|
||||
"agent.response_length": len(str(cs_result)),
|
||||
"agent.tools_used": len(customer_service_agent.tools) if customer_service_agent.tools else 0
|
||||
})
|
||||
|
||||
# Technical support (if needed for high complexity)
|
||||
if request['complexity'] == 'high':
|
||||
with telemetry.trace_agent_execution("TechnicalSupportAgent") as tech_trace:
|
||||
tech_task = Task(
|
||||
name=f"technical_support_{i+1}",
|
||||
description=f"Provide detailed technical support for: {request['description']}",
|
||||
expected_output="Detailed technical solution with troubleshooting steps",
|
||||
agent=technical_support_agent,
|
||||
context=[customer_task]
|
||||
)
|
||||
|
||||
tech_agents = AgentTeam(
|
||||
agents=[technical_support_agent],
|
||||
tasks=[tech_task], output="minimal"
|
||||
)
|
||||
|
||||
tech_result = tech_agents.start()
|
||||
tech_trace.set_attributes({
|
||||
"agent.response_length": len(str(tech_result)),
|
||||
"agent.escalation": True
|
||||
})
|
||||
|
||||
# Quality assurance check
|
||||
with telemetry.trace_agent_execution("QualityAssuranceAgent") as qa_trace:
|
||||
qa_task = Task(
|
||||
name=f"quality_check_{i+1}",
|
||||
description=f"Review the quality of customer service provided for: {request['description']}",
|
||||
expected_output="Quality assessment score and feedback",
|
||||
agent=quality_assurance_agent
|
||||
)
|
||||
|
||||
qa_agents = AgentTeam(
|
||||
agents=[quality_assurance_agent],
|
||||
tasks=[qa_task], output="minimal"
|
||||
)
|
||||
|
||||
qa_result = qa_agents.start()
|
||||
|
||||
# Extract quality score (simulated)
|
||||
quality_score = random.uniform(0.8, 1.0) # Simulated score
|
||||
qa_trace.set_attributes({
|
||||
"qa.score": quality_score,
|
||||
"qa.passed": quality_score >= 0.85
|
||||
})
|
||||
|
||||
# Calculate performance metrics
|
||||
end_time = time.time()
|
||||
duration = end_time - start_time
|
||||
|
||||
# Record custom metrics
|
||||
telemetry.record_metric("request_duration", duration, {
|
||||
"request_type": request['type'],
|
||||
"complexity": request['complexity']
|
||||
})
|
||||
|
||||
telemetry.record_metric("request_success", 1, {
|
||||
"request_type": request['type']
|
||||
})
|
||||
|
||||
# Set final trace attributes
|
||||
trace.set_attributes({
|
||||
"request.duration_seconds": duration,
|
||||
"request.status": "completed",
|
||||
"request.quality_score": quality_score,
|
||||
"request.escalated": request['complexity'] == 'high'
|
||||
})
|
||||
|
||||
print(f"✅ Request completed successfully in {duration:.2f}s (Quality: {quality_score:.2f})")
|
||||
|
||||
except Exception as e:
|
||||
# Record error metrics
|
||||
telemetry.record_metric("request_error", 1, {
|
||||
"request_type": request['type'],
|
||||
"error_type": type(e).__name__
|
||||
})
|
||||
|
||||
trace.set_attributes({
|
||||
"request.status": "error",
|
||||
"request.error": str(e)
|
||||
})
|
||||
|
||||
print(f"❌ Request failed: {str(e)}")
|
||||
|
||||
# Add some delay between requests
|
||||
time.sleep(2)
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
# Generate telemetry summary
|
||||
print(f"\n{'='*80}")
|
||||
print("TELEMETRY SUMMARY AND ANALYTICS")
|
||||
print(f"{'='*80}")
|
||||
|
||||
# Simulated telemetry analytics (in production, this would come from your telemetry backend)
|
||||
print("📊 Performance Metrics:")
|
||||
print("- Total Requests Processed: 4")
|
||||
print("- Average Response Time: 3.2s")
|
||||
print("- Success Rate: 100%")
|
||||
print("- Quality Score Average: 0.91")
|
||||
print("- High Complexity Requests: 25%")
|
||||
|
||||
print("\n📈 Usage Analytics:")
|
||||
print("- Most Common Request Type: technical_issue")
|
||||
print("- Peak Performance Window: All requests within SLA")
|
||||
print("- Agent Utilization: CustomerService (100%), TechnicalSupport (25%), QA (100%)")
|
||||
|
||||
print("\n🔍 Observability Features Demonstrated:")
|
||||
print("- Distributed tracing across agent interactions")
|
||||
print("- Custom metrics for business KPIs")
|
||||
print("- Performance monitoring and SLA tracking")
|
||||
print("- Error tracking and alerting")
|
||||
print("- Quality assurance metrics")
|
||||
print("- User journey tracking")
|
||||
print("- Resource utilization monitoring")
|
||||
|
||||
print("\n⚙️ Production Monitoring Setup:")
|
||||
print("- OpenTelemetry integration for standardized observability")
|
||||
print("- Custom metrics for business-specific KPIs")
|
||||
print("- Trace correlation across multi-agent workflows")
|
||||
print("- Performance benchmarking against expected durations")
|
||||
print("- Quality scoring and automated validation")
|
||||
print("- Error categorization and alerting")
|
||||
|
||||
print(f"\n{'='*80}")
|
||||
print("TELEMETRY DEMONSTRATION COMPLETED")
|
||||
print(f"{'='*80}")
|
||||
print("This example demonstrated comprehensive production telemetry including:")
|
||||
print("- Request tracing and performance monitoring")
|
||||
print("- Custom business metrics collection")
|
||||
print("- Quality assurance tracking")
|
||||
print("- Error handling and alerting")
|
||||
print("- Multi-agent workflow observability")
|
||||
print("- Production-ready monitoring patterns")
|
||||
@@ -1,115 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
JIRA Agent Watch Example
|
||||
|
||||
This example demonstrates how to use the JIRA watch tools with PraisonAI agents.
|
||||
The agent can monitor JIRA issues and projects for changes, search for issues,
|
||||
and get detailed issue information.
|
||||
|
||||
Setup:
|
||||
1. Install JIRA library: pip install jira
|
||||
2. Set environment variables:
|
||||
- [email protected] (for cloud JIRA)
|
||||
- JIRA_API_TOKEN=your_api_token
|
||||
- Or use JIRA_USERNAME + JIRA_API_TOKEN for server JIRA
|
||||
|
||||
Usage:
|
||||
python jira_agent_example.py
|
||||
"""
|
||||
|
||||
import os
|
||||
from praisonaiagents import Agent
|
||||
from praisonaiagents.tools import jira_tools
|
||||
|
||||
|
||||
def main():
|
||||
"""Demonstrate JIRA agent watch capabilities."""
|
||||
|
||||
# Check if JIRA credentials are available
|
||||
jira_email = os.getenv('JIRA_EMAIL')
|
||||
jira_token = os.getenv('JIRA_API_TOKEN')
|
||||
jira_username = os.getenv('JIRA_USERNAME')
|
||||
|
||||
if not jira_token:
|
||||
print("❌ JIRA_API_TOKEN environment variable not set")
|
||||
print("Please set your JIRA API token:")
|
||||
print("export JIRA_API_TOKEN='your_token_here'")
|
||||
return
|
||||
|
||||
if not (jira_email or jira_username):
|
||||
print("❌ JIRA credentials incomplete")
|
||||
print("Please set either:")
|
||||
print("- JIRA_EMAIL (for cloud JIRA)")
|
||||
print("- JIRA_USERNAME (for server JIRA)")
|
||||
return
|
||||
|
||||
# Create agent with JIRA tools
|
||||
agent = Agent(
|
||||
name="JIRA Monitor Agent",
|
||||
instructions="""
|
||||
You are a JIRA monitoring agent. You can:
|
||||
|
||||
1. Watch specific JIRA issues for changes
|
||||
2. Monitor JIRA projects for new issues and updates
|
||||
3. Search for issues using JQL queries
|
||||
4. Get detailed information about specific issues
|
||||
|
||||
When using JIRA tools, always provide the full JIRA URL
|
||||
(e.g., https://yourcompany.atlassian.net).
|
||||
|
||||
Be helpful and provide clear summaries of JIRA activity.
|
||||
""",
|
||||
tools=jira_tools(), # Add all JIRA tools
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print("🎯 JIRA Agent Watch Example")
|
||||
print("=" * 50)
|
||||
print()
|
||||
print("Available JIRA tools:")
|
||||
print("- jira_watch_issue: Monitor a specific issue for changes")
|
||||
print("- jira_watch_project: Monitor a project for new/updated issues")
|
||||
print("- jira_get_issue_info: Get detailed info about an issue")
|
||||
print("- jira_search_issues: Search issues using JQL")
|
||||
print()
|
||||
|
||||
# Example interactions
|
||||
example_prompts = [
|
||||
"Get information about JIRA issue DEMO-1 from https://praisonai.atlassian.net",
|
||||
"Search for open issues in project DEMO from https://praisonai.atlassian.net using JQL: 'project = DEMO AND status = Open'",
|
||||
"Watch JIRA issue DEMO-1 from https://praisonai.atlassian.net for 2 minutes (check every 60 seconds, max 2 checks)",
|
||||
]
|
||||
|
||||
print("📝 Example prompts you can try:")
|
||||
for i, prompt in enumerate(example_prompts, 1):
|
||||
print(f"{i}. {prompt}")
|
||||
print()
|
||||
|
||||
# Interactive mode
|
||||
print("💬 Interactive JIRA Agent (type 'quit' to exit)")
|
||||
print("-" * 50)
|
||||
|
||||
while True:
|
||||
try:
|
||||
user_input = input("\n🧑 You: ").strip()
|
||||
|
||||
if user_input.lower() in ['quit', 'exit', 'q']:
|
||||
print("👋 Goodbye!")
|
||||
break
|
||||
|
||||
if not user_input:
|
||||
continue
|
||||
|
||||
print("🤖 Agent: ", end="", flush=True)
|
||||
response = agent.start(user_input)
|
||||
print(response)
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("\n👋 Goodbye!")
|
||||
break
|
||||
except Exception as e:
|
||||
print(f"❌ Error: {e}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -5,17 +5,11 @@ from dotenv import load_dotenv
|
||||
|
||||
load_dotenv()
|
||||
|
||||
serper_api_key = os.getenv("SERPER_API_KEY")
|
||||
if serper_api_key is not None:
|
||||
os.environ["SERPER_API_KEY"] = serper_api_key
|
||||
os.environ['SERPER_API_KEY'] = os.getenv('SERPER_API_KEY')
|
||||
|
||||
search = GoogleSerperAPIWrapper()
|
||||
|
||||
if __name__ == "__main__":
|
||||
if not serper_api_key:
|
||||
print("SERPER_API_KEY is not set. Skipping Google Serper example.")
|
||||
else:
|
||||
search = GoogleSerperAPIWrapper()
|
||||
data_agent = Agent(instructions="Suggest me top 5 most visited websites for Dosa Recipe", tools=[search])
|
||||
editor_agent = Agent(instructions="List out the websites with their url and a short description")
|
||||
agents = AgentTeam(agents=[data_agent, editor_agent])
|
||||
agents.start()
|
||||
data_agent = Agent(instructions="Suggest me top 5 most visited websites for Dosa Recipe", tools=[search])
|
||||
editor_agent = Agent(instructions="List out the websites with their url and a short description")
|
||||
agents = AgentTeam(agents=[data_agent, editor_agent])
|
||||
agents.start()
|
||||
@@ -1,227 +0,0 @@
|
||||
"""
|
||||
Named Toolsets Example
|
||||
|
||||
This example demonstrates how to use named toolsets to organize and reuse
|
||||
groups of tools across agents and workflows.
|
||||
|
||||
Toolsets provide:
|
||||
- Organized tool collections (web, research, development, etc.)
|
||||
- Progressive disclosure (safe → research → development)
|
||||
- Composable design (toolsets can include other toolsets)
|
||||
- YAML configuration support
|
||||
"""
|
||||
|
||||
import os
|
||||
from praisonaiagents import Agent, Task, AgentTeam
|
||||
from praisonaiagents.toolsets import (
|
||||
list_toolsets,
|
||||
resolve_toolset,
|
||||
register_toolset
|
||||
)
|
||||
|
||||
# Set up environment (replace with your actual API key)
|
||||
os.environ.setdefault("OPENAI_API_KEY", "your-openai-api-key-here")
|
||||
|
||||
|
||||
def demo_basic_toolsets():
|
||||
"""Demonstrate basic toolset functionality."""
|
||||
print("=== Basic Toolsets Demo ===")
|
||||
|
||||
# List available toolsets
|
||||
available_toolsets = list_toolsets()
|
||||
print(f"Available toolsets: {available_toolsets}")
|
||||
|
||||
# Show what tools are in each prebuilt toolset
|
||||
for toolset_name in ["safe", "web", "research"]:
|
||||
tools = resolve_toolset(toolset_name)
|
||||
print(f"\n{toolset_name.upper()} toolset contains: {tools}")
|
||||
|
||||
|
||||
def demo_agent_with_toolsets():
|
||||
"""Demonstrate agents using toolsets."""
|
||||
print("\n=== Agent with Toolsets Demo ===")
|
||||
|
||||
# Create a research agent with research toolset
|
||||
researcher = Agent(
|
||||
name="researcher",
|
||||
role="Research Specialist",
|
||||
goal="Research topics thoroughly using web tools",
|
||||
instructions="You are a research specialist with access to web search and file tools.",
|
||||
toolsets=["research"], # includes web tools + file tools
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print(f"Research agent has {len(researcher.tools)} tools available")
|
||||
print(f"Tools: {[getattr(t, '__name__', str(t)) for t in researcher.tools]}")
|
||||
|
||||
# Create a safe agent with minimal tools
|
||||
safe_agent = Agent(
|
||||
name="safe_assistant",
|
||||
role="Safe Assistant",
|
||||
goal="Help users safely without risky operations",
|
||||
instructions="You are a helpful assistant with access to only safe, read-only tools.",
|
||||
toolsets=["safe"],
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print(f"\nSafe agent has {len(safe_agent.tools)} tools available")
|
||||
print(f"Safe tools: {[getattr(t, '__name__', str(t)) for t in safe_agent.tools]}")
|
||||
|
||||
|
||||
def demo_custom_toolsets():
|
||||
"""Demonstrate creating and using custom toolsets."""
|
||||
print("\n=== Custom Toolsets Demo ===")
|
||||
|
||||
# Register a custom toolset for data analysis
|
||||
register_toolset(
|
||||
"data_analysis",
|
||||
tools=["read_file", "write_file"],
|
||||
includes=["safe"], # Include safe tools too
|
||||
description="Tools for data analysis workflows"
|
||||
)
|
||||
|
||||
# Create an agent with the custom toolset
|
||||
analyst = Agent(
|
||||
name="data_analyst",
|
||||
role="Data Analyst",
|
||||
goal="Analyze data files and generate reports",
|
||||
instructions="You specialize in data analysis. Read files, process data, and write reports.",
|
||||
toolsets=["data_analysis"],
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print(f"Data analyst has {len(analyst.tools)} tools available")
|
||||
print(f"Analysis tools: {[getattr(t, '__name__', str(t)) for t in analyst.tools]}")
|
||||
|
||||
|
||||
def demo_mixed_tools_and_toolsets():
|
||||
"""Demonstrate mixing explicit tools with toolsets."""
|
||||
print("\n=== Mixed Tools and Toolsets Demo ===")
|
||||
|
||||
# Create agent with both explicit tools and toolsets
|
||||
hybrid_agent = Agent(
|
||||
name="hybrid_assistant",
|
||||
role="Hybrid Assistant",
|
||||
goal="Assist with both research and custom tasks",
|
||||
instructions="You can research topics and perform custom analysis tasks.",
|
||||
tools=["write_file"], # Explicit tool
|
||||
toolsets=["research"], # Toolset with web + file tools
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print(f"Hybrid agent has {len(hybrid_agent.tools)} tools available")
|
||||
tool_names = [getattr(t, '__name__', str(t)) for t in hybrid_agent.tools]
|
||||
print(f"Hybrid tools: {tool_names}")
|
||||
|
||||
# Note: write_file might appear twice (once explicit, once from toolset)
|
||||
# The agent handles deduplication automatically
|
||||
|
||||
|
||||
def demo_multi_agent_with_toolsets():
|
||||
"""Demonstrate multi-agent workflows with different toolsets."""
|
||||
print("\n=== Multi-Agent with Toolsets Demo ===")
|
||||
|
||||
# Create agents with different toolsets for different roles
|
||||
researcher = Agent(
|
||||
name="researcher",
|
||||
role="Research Specialist",
|
||||
goal="Research topics and gather information",
|
||||
toolsets=["research"],
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
writer = Agent(
|
||||
name="writer",
|
||||
role="Content Writer",
|
||||
goal="Write content based on research",
|
||||
toolsets=["safe"], # Safe tools for writing
|
||||
llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
# Create tasks for each agent
|
||||
research_task = Task(
|
||||
name="research_task",
|
||||
description="Research the benefits of renewable energy",
|
||||
expected_output="A summary of key benefits of renewable energy",
|
||||
agent=researcher
|
||||
)
|
||||
|
||||
writing_task = Task(
|
||||
name="writing_task",
|
||||
description="Write a blog post about renewable energy based on the research",
|
||||
expected_output="A well-written blog post about renewable energy benefits",
|
||||
agent=writer
|
||||
)
|
||||
|
||||
# Create team with different toolsets per agent
|
||||
team = AgentTeam(
|
||||
agents=[researcher, writer],
|
||||
tasks=[research_task, writing_task],
|
||||
process="sequential"
|
||||
)
|
||||
|
||||
print(f"Team created with {len(team.agents)} agents using different toolsets")
|
||||
print(f"Research agent tools: {len(researcher.tools)}")
|
||||
print(f"Writer agent tools: {len(writer.tools)}")
|
||||
|
||||
|
||||
def demo_yaml_config():
|
||||
"""Show how toolsets work in YAML configuration."""
|
||||
print("\n=== YAML Configuration Example ===")
|
||||
|
||||
yaml_config = """
|
||||
# agents.yaml - Example using toolsets
|
||||
agents:
|
||||
researcher:
|
||||
role: Research Specialist
|
||||
goal: Research topics thoroughly
|
||||
toolsets:
|
||||
- research # Includes web search, file tools
|
||||
llm: gpt-4o-mini
|
||||
|
||||
analyst:
|
||||
role: Data Analyst
|
||||
goal: Analyze research data
|
||||
tools:
|
||||
- write_file # Explicit tool
|
||||
toolsets:
|
||||
- safe # Safe toolset
|
||||
llm: gpt-4o-mini
|
||||
|
||||
tasks:
|
||||
research_task:
|
||||
description: Research renewable energy trends
|
||||
agent: researcher
|
||||
expected_output: Research summary
|
||||
|
||||
analysis_task:
|
||||
description: Analyze the research data
|
||||
agent: analyst
|
||||
expected_output: Analysis report
|
||||
"""
|
||||
|
||||
print("Example YAML configuration with toolsets:")
|
||||
print(yaml_config)
|
||||
print("Use: praisonai run 'Research renewable energy' --toolset research")
|
||||
print("Or: praisonai chat --toolset web,files")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("🛠️ PraisonAI Named Toolsets Example")
|
||||
print("=" * 50)
|
||||
|
||||
# Run all demos
|
||||
demo_basic_toolsets()
|
||||
demo_agent_with_toolsets()
|
||||
demo_custom_toolsets()
|
||||
demo_mixed_tools_and_toolsets()
|
||||
demo_multi_agent_with_toolsets()
|
||||
demo_yaml_config()
|
||||
|
||||
print("\n✅ Toolsets example completed!")
|
||||
print("\n💡 Key Benefits:")
|
||||
print(" • Organized tool collections")
|
||||
print(" • Progressive disclosure (safe → research → development)")
|
||||
print(" • Reusable across agents and workflows")
|
||||
print(" • YAML configuration support")
|
||||
print(" • Composable design with includes")
|
||||
@@ -2,7 +2,6 @@ from praisonaiagents import Agent, Task, AgentTeam
|
||||
from pydantic import BaseModel
|
||||
from typing import List, Dict
|
||||
from gitingest import ingest
|
||||
import sys
|
||||
|
||||
class CodeMetrics(BaseModel):
|
||||
category: str
|
||||
@@ -61,10 +60,7 @@ def analyze_code(code_source: str) -> CodeAnalysisReport:
|
||||
Analyze code from directory path or GitHub URL
|
||||
"""
|
||||
# Ingest code content
|
||||
try:
|
||||
summary, tree, content = ingest(code_source)
|
||||
except Exception as exc:
|
||||
raise RuntimeError(f"Failed to ingest code source: {exc}") from exc
|
||||
summary, tree, content = ingest(code_source)
|
||||
|
||||
# Concatenate context into structured format
|
||||
context_text = f"""
|
||||
@@ -90,22 +86,10 @@ def analyze_code(code_source: str) -> CodeAnalysisReport:
|
||||
tasks=[code_analysis_task]
|
||||
)
|
||||
|
||||
result = agents.start(context_text)
|
||||
if result is None:
|
||||
raise RuntimeError("No analysis result returned by AgentTeam.start()")
|
||||
return result
|
||||
|
||||
|
||||
def main() -> None:
|
||||
# Example usage
|
||||
code_source = "https://github.com/openai/openai-python/tree/main/src/openai/cli/_api/chat" # GitHub URL or local directory
|
||||
try:
|
||||
result = analyze_code(code_source)
|
||||
except RuntimeError as exc:
|
||||
print(f"Code analysis failed: {exc}")
|
||||
sys.exit(1)
|
||||
print(result)
|
||||
|
||||
return agents.start(context_text)
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
# Example usage
|
||||
code_source = "https://github.com/openai/openai-python/tree/main/src/openai/cli/_api/chat" # GitHub URL or local directory
|
||||
result = analyze_code(code_source)
|
||||
print(result)
|
||||
@@ -77,44 +77,25 @@ agents = AgentTeam(
|
||||
process="sequential", output="verbose"
|
||||
)
|
||||
|
||||
|
||||
def _extract_pydantic_result(result_obj):
|
||||
"""Extract pydantic payload from AgentTeam.start() output shapes."""
|
||||
if hasattr(result_obj, "pydantic"):
|
||||
return result_obj.pydantic
|
||||
if isinstance(result_obj, dict):
|
||||
task_results = result_obj.get("task_results")
|
||||
if isinstance(task_results, dict):
|
||||
values = list(task_results.values())
|
||||
if values and hasattr(values[-1], "pydantic"):
|
||||
return values[-1].pydantic
|
||||
if isinstance(task_results, list) and task_results and hasattr(task_results[-1], "pydantic"):
|
||||
return task_results[-1].pydantic
|
||||
return None
|
||||
|
||||
|
||||
# Start the analysis
|
||||
result = agents.start()
|
||||
pydantic_result = _extract_pydantic_result(result)
|
||||
if pydantic_result is None:
|
||||
raise ValueError("Could not extract structured CVAnalysisReport from workflow result")
|
||||
|
||||
# Access the structured results
|
||||
print("\nCV Analysis Results:")
|
||||
print(f"\nOverall Score: {pydantic_result.overall_score}/100")
|
||||
print(f"\nOverall Score: {result.pydantic.overall_score}/100")
|
||||
print("\nKey Strengths:")
|
||||
for strength in pydantic_result.key_strengths:
|
||||
for strength in result.pydantic.key_strengths:
|
||||
print(f"- {strength}")
|
||||
|
||||
print("\nSkill Analysis:")
|
||||
print("\nTechnical Skills:")
|
||||
for skill in pydantic_result.skill_analysis.technical_skills:
|
||||
for skill in result.pydantic.skill_analysis.technical_skills:
|
||||
print(f"- {skill}")
|
||||
|
||||
print("\nExperience Highlights:")
|
||||
for achievement in pydantic_result.experience_analysis.key_achievements:
|
||||
for achievement in result.pydantic.experience_analysis.key_achievements:
|
||||
print(f"- {achievement}")
|
||||
|
||||
print("\nRecommendations:")
|
||||
for recommendation in pydantic_result.recommendations:
|
||||
for recommendation in result.pydantic.recommendations:
|
||||
print(f"- {recommendation}")
|
||||
@@ -100,8 +100,6 @@ def evaluate_project(video_path: str) -> ProjectEvaluation:
|
||||
evaluation_data = response
|
||||
|
||||
print(f"Debug - Parsed evaluation_data: {evaluation_data}")
|
||||
if not evaluation_data or not isinstance(evaluation_data, dict):
|
||||
raise ValueError("No structured evaluation data returned by agent")
|
||||
|
||||
# Create and return ProjectEvaluation instance
|
||||
return ProjectEvaluation(
|
||||
|
||||
@@ -1,11 +1,5 @@
|
||||
from praisonaiagents import VideoAgent
|
||||
import os
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if not os.getenv("AZURE_API_BASE"):
|
||||
print("AZURE_API_BASE is not configured. Skipping Azure video example.")
|
||||
else:
|
||||
agent = VideoAgent(llm="azure/sora-2")
|
||||
video = agent.generate("Mountain landscape")
|
||||
print(video.id)
|
||||
agent = VideoAgent(llm="azure/sora-2")
|
||||
video = agent.generate("Mountain landscape")
|
||||
print(video.id)
|
||||
@@ -5,7 +5,7 @@ Demonstrates using Agent instances directly as workflow steps.
|
||||
Each agent processes the input and passes output to the next agent.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, AgentFlow
|
||||
from praisonaiagents import Agent, Workflow
|
||||
|
||||
# Create agents with specific roles
|
||||
researcher = Agent(
|
||||
|
||||
@@ -6,7 +6,6 @@ with Agents for workflow monitoring and logging.
|
||||
"""
|
||||
|
||||
from praisonaiagents import Agent, Task, AgentTeam
|
||||
from praisonaiagents.config.feature_configs import MultiAgentHooksConfig
|
||||
|
||||
# Create an agent
|
||||
researcher = Agent(
|
||||
@@ -48,10 +47,8 @@ if __name__ == "__main__":
|
||||
agents=[researcher],
|
||||
tasks=[task1, task2],
|
||||
process="workflow",
|
||||
hooks=MultiAgentHooksConfig(
|
||||
on_task_start=on_start,
|
||||
on_task_complete=on_complete,
|
||||
),
|
||||
on_task_start=on_start,
|
||||
on_task_complete=on_complete,
|
||||
variables={"global_var": "shared_value"} # Global variables
|
||||
)
|
||||
|
||||
|
||||
@@ -6,6 +6,7 @@ to different next steps based on output content.
|
||||
"""
|
||||
|
||||
from praisonaiagents import AgentFlow, Task
|
||||
from praisonaiagents import AgentFlowManager
|
||||
|
||||
# Create a workflow with branching
|
||||
workflow = AgentFlow(
|
||||
@@ -35,9 +36,16 @@ workflow = AgentFlow(
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
result = workflow.run("", llm="gpt-4o-mini", verbose=True)
|
||||
# Create manager and register workflow
|
||||
manager = WorkflowManager()
|
||||
manager.workflows["Decision Workflow"] = workflow
|
||||
|
||||
# Execute - will branch to success_handler since 42 is positive
|
||||
result = manager.execute(
|
||||
"Decision Workflow",
|
||||
default_llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print("Workflow completed!")
|
||||
for step in result.get("steps", []):
|
||||
name = step.get("step", step.get("name", "unknown"))
|
||||
status = step.get("status", "completed")
|
||||
print(f" {name}: {status}")
|
||||
for step_result in result["results"]:
|
||||
print(f" {step_result['step']}: {step_result['status']}")
|
||||
@@ -54,13 +54,11 @@ workflow = AgentFlow(
|
||||
analyzer, # Always runs
|
||||
Task(
|
||||
name="tech_review",
|
||||
description="Review technical aspects when technical keywords are detected.",
|
||||
agent=tech_reviewer,
|
||||
should_run=is_technical # Only runs for technical content
|
||||
),
|
||||
Task(
|
||||
name="creative_enhance",
|
||||
description="Enhance narrative quality when creative keywords are detected.",
|
||||
agent=creative_enhancer,
|
||||
should_run=needs_creative # Only runs for creative content
|
||||
),
|
||||
|
||||
@@ -6,8 +6,9 @@ functions that return StepResult with stop_workflow=True.
|
||||
"""
|
||||
|
||||
from praisonaiagents import (
|
||||
AgentFlow, Task, WorkflowContext, StepResult
|
||||
Workflow, Task, WorkflowContext, StepResult
|
||||
)
|
||||
from praisonaiagents import AgentFlowManager
|
||||
|
||||
# Custom validator that can stop the workflow
|
||||
def validate_data(context: WorkflowContext) -> StepResult:
|
||||
@@ -49,13 +50,20 @@ workflow = AgentFlow(
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
manager = WorkflowManager()
|
||||
manager.workflows["Data Processing"] = workflow
|
||||
|
||||
# Test with invalid data (will stop early)
|
||||
print("=== Testing with invalid data ===")
|
||||
result = workflow.run("", llm="gpt-4o-mini", verbose=True)
|
||||
for step in result.get("steps", []):
|
||||
print(f" {step.get('step', 'step')}: {step.get('output', step.get('status'))}")
|
||||
|
||||
result = manager.execute("Data Processing", default_llm="gpt-4o-mini")
|
||||
|
||||
for step_result in result["results"]:
|
||||
print(f" {step_result['step']}: {step_result['output']}")
|
||||
|
||||
# Test with valid data (will complete)
|
||||
print("\n=== Testing with valid data ===")
|
||||
workflow.variables["data"] = {"value": 42}
|
||||
result = workflow.run("", llm="gpt-4o-mini", verbose=True)
|
||||
for step in result.get("steps", []):
|
||||
print(f" {step.get('step', 'step')}: {step.get('status', 'completed')}")
|
||||
result = manager.execute("Data Processing", default_llm="gpt-4o-mini")
|
||||
|
||||
for step_result in result["results"]:
|
||||
print(f" {step_result['step']}: {step_result['status']}")
|
||||
@@ -6,6 +6,7 @@ Each item is processed individually with the loop variable.
|
||||
"""
|
||||
|
||||
from praisonaiagents import AgentFlow, Task
|
||||
from praisonaiagents import AgentFlowManager
|
||||
|
||||
# Create a workflow with loop
|
||||
workflow = AgentFlow(
|
||||
@@ -29,12 +30,18 @@ workflow = AgentFlow(
|
||||
)
|
||||
|
||||
if __name__ == "__main__":
|
||||
result = workflow.run("", llm="gpt-4o-mini", verbose=True)
|
||||
# Create manager and register workflow
|
||||
manager = WorkflowManager()
|
||||
manager.workflows["Process Items"] = workflow
|
||||
|
||||
# Execute - will process each fruit in the list
|
||||
result = manager.execute(
|
||||
"Process Items",
|
||||
default_llm="gpt-4o-mini"
|
||||
)
|
||||
|
||||
print("Workflow completed!")
|
||||
for step in result.get("steps", []):
|
||||
name = step.get("step", step.get("name", "unknown"))
|
||||
status = step.get("status", "completed")
|
||||
print(f" {name}: {status}")
|
||||
out = step.get("output")
|
||||
if isinstance(out, list):
|
||||
print(f" Loop processed {len(out)} items")
|
||||
for step_result in result["results"]:
|
||||
print(f" {step_result['step']}: {step_result['status']}")
|
||||
if isinstance(step_result.get("output"), list):
|
||||
print(f" Loop processed {len(step_result['output'])} items")
|
||||
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