fix: resolve missing AgentTeam import and RouterAgent kwargs forwarding

- Fix missing AgentTeam import in self-reflection-optimization-patterns.py
- Forward kwargs properly in RouterAgent._build_system_prompt to super()
- Addresses critical issues identified by Gemini code reviewer

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

.github/workflows/claude.yml

@@ -151,40 +151,24 @@ jobs:
         id: check_fork
         uses: actions/github-script@v7
         with:
-          github-token: ${{ steps.app-token.outputs.token }}
           script: |
-            const isPR = context.eventName === 'pull_request'
-              || context.eventName === 'pull_request_review'
-              || context.eventName === 'pull_request_review_comment'
-              || (context.payload.issue && context.payload.issue.pull_request);
-
-            if (!isPR) {
-              core.setOutput('is_pr', 'false');
-              core.setOutput('is_fork', 'false');
-              return;
-            }
-
-            const prNumber = context.payload.pull_request
-              ? context.payload.pull_request.number
-              : context.payload.issue.number;
-            const pr = await github.rest.pulls.get({
-              owner: context.repo.owner,
-              repo: context.repo.repo,
-              pull_number: prNumber
-            });
-
-            core.setOutput('is_pr', 'true');
-            core.setOutput('pr_number', String(prNumber));
-            core.setOutput('pr_branch', pr.data.head.ref);
-            core.setOutput('head_repo', pr.data.head.repo.full_name);
-            core.setOutput('merge_state', (pr.data.mergeable_state || pr.data.merge_state_status || '').toUpperCase());
-
-            const baseRepo = `${context.repo.owner}/${context.repo.repo}`;
-            if (pr.data.head.repo && pr.data.head.repo.full_name !== baseRepo) {
-              core.setOutput('is_fork', 'true');
-              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');
 
@@ -196,19 +180,17 @@ 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: ${{ steps.check_fork.outputs.is_fork }}
         run: |
-          git fetch origin "pull/${PR_NUMBER}/head:${PR_BRANCH}"
-          git checkout "${PR_BRANCH}"
-          git fetch origin main
-
+          # 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)"
+            git remote set-url origin file://$(pwd)
           fi
 
       - uses: anthropics/claude-code-action@beta
@@ -218,13 +200,11 @@ jobs:
           allowed_bots: 'praisonai-triage-agent[bot]'
           claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
           github_token: ${{ steps.app-token.outputs.token }}
-          model: opus
           trigger_phrase: "@claude"
           label_trigger: "claude"
 
           direct_prompt: |
-            ${{ 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' || (steps.check_fork.outputs.is_pr == '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' || '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}, merge_state={4}. 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.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):
@@ -253,9 +233,15 @@ jobs:
             - 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.merge_state == 'DIRTY' && format('STEP 3 — RESOLVE MERGE CONFLICTS ON PR (branch: {0}, PR #{1}):\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.is_pr == 'true' && steps.check_fork.outputs.is_fork != 'true' && steps.check_fork.outputs.merge_state != 'DIRTY' && format('STEP 3 — IMPLEMENT ON EXISTING PR (branch: {0}, PR #{1}):\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) || '' }}
-            ${{ steps.check_fork.outputs.is_pr != 'true' && 'STEP 3 — IMPLEMENT (for changes in THIS repo — PraisonAI):\n- Create a fix branch: git checkout -b claude/issue-$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.
@@ -281,7 +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:*)

.github/workflows/docker-publish.yml

@@ -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

.github/workflows/gemini-issue-automated-triage.yml

@@ -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

.github/workflows/gemini-issue-review.yml

@@ -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

.github/workflows/gemini-pr-review.yml

@@ -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

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

@@ -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

.github/workflows/python-package.yml

@@ -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:

.github/workflows/release.yml

@@ -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

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

@@ -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"

.github/workflows/test-comprehensive.yml

@@ -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

.github/workflows/test-core.yml

@@ -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:

.github/workflows/test-extended.yml

@@ -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

.github/workflows/test-frameworks.yml

@@ -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

.github/workflows/test-optimized.yml

@@ -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

.github/workflows/test-real.yml

@@ -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

.gitignore

@@ -88,9 +88,6 @@ issue_details.json
 .internal
 .praisonai
 
-# Backup files
-*.bak
-
 # Rust / Cargo
 target/
 Cargo.lock

AGENTS.md

@@ -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/

README.md

@@ -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** |
 
 ---
 

api.md

@@ -59,8 +59,6 @@ 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">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>
@@ -242,7 +240,6 @@ 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>
@@ -518,12 +515,10 @@ 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>
@@ -532,7 +527,6 @@ 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
 
@@ -704,7 +698,7 @@ Methods:
 
 Types:
 ```python
-from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, AutoApproveBackend, EmbeddingResult, __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:
@@ -795,17 +789,11 @@ 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 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>
@@ -846,8 +834,6 @@ Methods:
 * <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>
@@ -860,9 +846,6 @@ 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>
@@ -897,12 +880,10 @@ Methods:
 * <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 fix <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 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>
@@ -933,9 +914,6 @@ 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>
@@ -1026,14 +1004,6 @@ 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>
@@ -1332,7 +1302,7 @@ export { // Python parity additions
 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, 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 { 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

docker/Dockerfile.chat

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.67" \
+    "praisonai>=4.6.55" \
     "praisonai[chat]" \
     "embedchain[github,youtube]"
 

docker/Dockerfile.dev

@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.67" \
+    "praisonai>=4.6.55" \
     "praisonai[ui]" \
     "praisonai[chat]" \
     "praisonai[realtime]" \

docker/Dockerfile.ui

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=4.6.67" \
+    "praisonai>=4.6.55" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/approval/agent_approval.py

@@ -12,10 +12,15 @@ from praisonaiagents import Agent
 from praisonaiagents.approval import AgentApproval
 from praisonaiagents.tools.shell_tools import execute_command
 
-reviewer = AgentApproval(
+reviewer_agent = Agent(
+    name="CommandReviewer",
     instructions="Only approve read-only commands like 'ls' or 'cat'. Deny destructive commands.",
 )
 
+reviewer = AgentApproval(
+    approver_agent=reviewer_agent,
+)
+
 agent = Agent(
     name="DevOps",
     instructions="You are a DevOps assistant. Use shell tools when asked.",

examples/consolidated_params/advanced_workflow_full_features.py

@@ -2,7 +2,7 @@
 from praisonaiagents import Agent
 from praisonaiagents import AgentFlow, Task
 from praisonaiagents.workflows.workflow_configs import (
-    WorkflowOutputConfig, WorkflowPlanningConfig, WorkflowMemoryConfig,
+    WorkflowPlanningConfig, WorkflowMemoryConfig,
 )
 
 # Full-featured workflow with all consolidated params
@@ -32,7 +32,7 @@ workflow = AgentFlow(
         ),
     ],
     # Workflow-level consolidated params
-    output=WorkflowOutputConfig(verbose=True, stream=True),
+    output="verbose",
     planning=WorkflowPlanningConfig(enabled=True, reasoning=True),
     memory=WorkflowMemoryConfig(backend="file"),
     # Agent-like params

examples/consolidated_params/basic_web.py

@@ -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=WebConfig(search=True, fetch=False, search_provider="duckduckgo"),
+    web="search_only",  # Compatible across models without web_fetch
 )
 
 if __name__ == "__main__":

examples/knowledge/context_required_example.py

@@ -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 response.upper():
+        if "ZEBRA-71" in str(response or "").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 response.upper():
+        if "HAWK-88" in str(response or "").upper():
             print("✅ VERIFIED: Agent correctly retrieved the security code!\n")
         else:
             print("❌ WARNING: Agent did not find the code - check retrieval\n")

examples/managed-agents/persistence/cockroachdb_managed.py

@@ -17,8 +17,10 @@ from praisonaiagents import Agent
 agent = Agent(
     name="CockroachDB Agent",
     instructions="You are a helpful assistant.",
-    db={"database_url": os.getenv("COCKROACHDB_URL")},
-    session_id="crdb-demo-session",
+    memory={
+        "session_id": "crdb-demo-session",
+        "db": {"database_url": os.getenv("COCKROACHDB_URL")},
+    },
 )
 
 result = agent.start("What is distributed SQL? Explain in 2 sentences.")

examples/managed-agents/persistence/neon_managed.py

@@ -18,8 +18,10 @@ from praisonaiagents import Agent
 agent = Agent(
     name="Neon Agent",
     instructions="You are a helpful assistant.",
-    db={"database_url": os.getenv("NEON_DATABASE_URL")},
-    session_id="neon-demo-session",
+    memory={
+        "session_id": "neon-demo-session",
+        "db": {"database_url": os.getenv("NEON_DATABASE_URL")},
+    },
 )
 
 # Option 2: Direct URL

examples/managed-agents/persistence/supabase_direct_managed.py

@@ -20,8 +20,10 @@ from praisonaiagents import Agent
 agent = Agent(
     name="Supabase Agent",
     instructions="You are a helpful assistant.",
-    db={"database_url": os.getenv("SUPABASE_DATABASE_URL")},
-    session_id="supabase-demo-session",
+    memory={
+        "session_id": "supabase-demo-session",
+        "db": {"database_url": os.getenv("SUPABASE_DATABASE_URL")},
+    },
 )
 
 result = agent.start("What is Supabase? Explain in 2 sentences.")

examples/managed-agents/persistence/turso_managed.py

@@ -18,11 +18,13 @@ from praisonaiagents import Agent
 agent = Agent(
     name="Turso Agent",
     instructions="You are a helpful assistant.",
-    db={
-        "database_url": os.getenv("TURSO_DATABASE_URL"),
-        "auth_token": os.getenv("TURSO_AUTH_TOKEN"),
+    memory={
+        "session_id": "turso-demo-session",
+        "db": {
+            "database_url": os.getenv("TURSO_DATABASE_URL"),
+            "auth_token": os.getenv("TURSO_AUTH_TOKEN"),
+        },
     },
-    session_id="turso-demo-session",
 )
 
 result = agent.start("What is edge computing? Explain in 2 sentences.")

examples/middleware/configurable_model.py

@@ -10,8 +10,7 @@ from praisonaiagents import Agent
 agent = Agent(
     name="FlexBot",
     instructions="You are a helpful assistant.",
-    llm="gpt-4o-mini",
-    llm_config={"configurable": True}
+    llm={"model": "gpt-4o-mini", "configurable": True},
 )
 
 if __name__ == "__main__":

examples/middleware/injected_state.py

@@ -21,7 +21,7 @@ agent = Agent(
     name="ContextBot",
     instructions="You help show context information.",
     tools=[show_context],
-    session_id="my-session-123"
+    memory={"session_id": "my-session-123"},
 )
 
 if __name__ == "__main__":

examples/observability/multi_agent_tracing.py

@@ -19,6 +19,16 @@ 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",
@@ -37,13 +47,13 @@ with obs.trace("content-creation", metadata={"workflow": "research-write"}):
     
     # Research phase
     with obs.span("research-phase", kind=SpanKind.AGENT) as research_span:
-        research_span.attributes["agent"] = "Researcher"
+        set_span_attr(research_span, "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:
-        write_span.attributes["agent"] = "Writer"
-        write_span.attributes["input_length"] = len(str(research_result))
+        set_span_attr(write_span, "agent", "Writer")
+        set_span_attr(write_span, "input_length", len(str(research_result)))
         final_content = writer.chat(f"Write a blog post based on: {research_result}")
 
 print("Final Content:")

examples/persistence/knowledge_qdrant.py

@@ -52,8 +52,10 @@ agent = Agent(
     instructions="You are a helpful assistant with access to technical documentation.",
     knowledge={
         "sources": [doc_path],
-        "vector_store": "qdrant",
-        "url": "http://localhost:6333",
+        "vector_store": {
+            "provider": "qdrant",
+            "url": "http://localhost:6333",
+        },
     }
 )
 

examples/persistence/minimal_agent_db.py

@@ -13,7 +13,8 @@ Expected output:
     - Session can be resumed later with same session_id
 """
 
-from praisonaiagents import Agent, db
+from praisonaiagents import Agent
+from praisonaiagents.db import db
 
 # Create database connection (PostgreSQL + Redis)
 my_db = db(
@@ -25,10 +26,12 @@ my_db = db(
 agent = Agent(
     name="Assistant",
     instructions="You are a helpful assistant. Be concise.",
-    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"
+    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",
+    },
 )
 
 # Chat - messages are automatically persisted

examples/persistence/postgres_runs_traces.py

@@ -12,7 +12,8 @@ Expected output:
     - Export shows full session data
 """
 
-from praisonaiagents import Agent, db
+from praisonaiagents import Agent
+from praisonaiagents.db import db
 
 def get_weather(city: str) -> str:
     """Get weather for a city."""
@@ -29,8 +30,10 @@ agent = Agent(
     name="WeatherBot",
     instructions="You help with weather. Use the get_weather tool when asked.",
     tools=[get_weather],
-    db=my_db,
-    session_id="weather-session-001"
+    memory={
+        "db": my_db,
+        "session_id": "weather-session-001",
+    },
 )
 
 # First chat - triggers run tracking

examples/persistence/redis_state.py

@@ -13,7 +13,8 @@ Expected output:
     Agent responds with state persisted to Redis
 """
 
-from praisonaiagents import Agent, db
+from praisonaiagents import Agent
+from praisonaiagents.db import db
 
 print("=== Redis State Store (Agent-First) ===")
 
@@ -26,8 +27,10 @@ my_db = db(
 agent = Agent(
     name="Assistant",
     instructions="You are a helpful assistant.",
-    db=my_db,
-    session_id="redis-state-session"
+    memory={
+        "db": my_db,
+        "session_id": "redis-state-session",
+    },
 )
 
 # Chat - state is automatically managed via Redis

examples/persistence/session_resume.py

@@ -11,7 +11,8 @@ Expected output:
     - Second run: Resumes with history
 """
 
-from praisonaiagents import Agent, db
+from praisonaiagents import Agent
+from praisonaiagents.db import db
 
 # Create database
 my_db = db(
@@ -25,8 +26,10 @@ SESSION_ID = "resume-demo-session"
 agent = Agent(
     name="MemoryBot",
     instructions="You remember our conversation. Be helpful and concise.",
-    db=my_db,
-    session_id=SESSION_ID
+    memory={
+        "db": my_db,
+        "session_id": SESSION_ID,
+    },
 )
 
 # Check if this is a new or resumed session

examples/persistence/simple_db_agent.py

@@ -26,7 +26,8 @@ Expected Output:
     Messages persisted: 2
 """
 
-from praisonaiagents import Agent, db
+from praisonaiagents import Agent
+from praisonaiagents.db import db
 
 # Create database adapter (simplified import)
 db_instance = db(
@@ -37,8 +38,10 @@ db_instance = db(
 agent = Agent(
     name="Assistant",
     instructions="You are a helpful assistant. Keep responses brief.",
-    db=db_instance,
-    session_id="demo-session-001",  # Same session_id = resume conversation
+    memory={
+        "db": db_instance,
+        "session_id": "demo-session-001",  # Same session_id = resume conversation
+    },
     output="silent"
 )
 

examples/persistence/sqlite_local.py

@@ -11,7 +11,8 @@ Expected output:
     - Data persisted to local SQLite file
 """
 
-from praisonaiagents import Agent, db
+from praisonaiagents import Agent
+from praisonaiagents.db import db
 import tempfile
 import os
 
@@ -25,8 +26,10 @@ print(f"Database: {db_path}")
 agent = Agent(
     name="LocalBot",
     instructions="You are a helpful assistant.",
-    db=my_db,
-    session_id="local-session"
+    memory={
+        "db": my_db,
+        "session_id": "local-session",
+    },
 )
 
 # Chat

examples/policy/basic_policy.py

@@ -57,8 +57,8 @@ def main():
     agent = Agent(
         name="SecureAgent",
         instructions="You are a file management assistant.",
-        policy=engine
     )
+    agent.policy = engine
     
     print("\n--- Agent with Policy Enforcement Created ---")
     print(f"Agent: {agent.name}")

examples/python/agents/autoagents-hierarchical-generation.py

@@ -60,9 +60,10 @@ agents_system = AgentTeam(
     process="sequential", output="verbose"
 )
 
-print("Starting hierarchical agent generation...")
-result = agents_system.start()
+if __name__ == "__main__":
+    print("Starting hierarchical agent generation...")
+    result = agents_system.start()
 
-print(f"\nHierarchical Result: {result[:200]}...")
-print("\n✅ AutoAgents hierarchical generation complete!")
-print("Demonstrated coordinated hierarchical workflow between manager and specialist agents.")
+    print(f"\nHierarchical Result: {str(result)[:200]}...")
+    print("\n✅ AutoAgents hierarchical generation complete!")
+    print("Demonstrated coordinated hierarchical workflow between manager and specialist agents.")

examples/python/agents/code-agent.py

@@ -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__":

examples/python/agents/math-agent.py

@@ -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__":

examples/python/api/simple-mcp-server.py

@@ -1,4 +1,5 @@
 from praisonaiagents import Agent
 
-agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
-agent.launch(port=8080, protocol="mcp")
+if __name__ == "__main__":
+    agent = Agent(name="TweetAgent", instructions="Create a Tweet based on the topic provided")
+    agent.launch(port=8080, protocol="mcp", path="/")

examples/python/bot_run_control_example.py

@@ -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())

examples/python/camera/camera-basic.py

@@ -90,9 +90,18 @@ def main():
     
     if result:
         print("\n🔍 Analysis Results:")
-        for task_id, task_result in result["task_results"].items():
+        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}:")
-            print(task_result.raw)
+            raw_value = getattr(task_result, "raw", None)
+            print(raw_value if raw_value is not None else str(task_result))
     else:
         print("❌ Failed to capture and analyze camera feed")
 

examples/python/camera/camera-continuous.py

@@ -75,7 +75,7 @@ class ContinuousCameraMonitor:
             agents=[self.vision_agent],
             tasks=[task],
             process="sequential",
-            verbose=0  # Reduced verbosity for continuous monitoring
+            output="silent",  # Reduced verbosity for continuous monitoring
         )
         
         return agents.start()

examples/python/camera/camera-multi-agent.py

@@ -148,10 +148,19 @@ def main():
             "scene_analysis": "🌍 SCENE ANALYSIS"
         }
         
-        for task_id, task_result in result["task_results"].items():
+        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"\n{agent_names.get(task_id, f'Task {task_id}')}:")
             print("-" * 40)
-            print(task_result.raw)
+            raw_value = getattr(task_result, "raw", None)
+            print(raw_value if raw_value is not None else str(task_result))
             
         print("\n" + "="*60)
         print("✅ Multi-agent analysis complete!")

examples/python/cli/autonomy_modes_example.py

@@ -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 = handler.get_stats()
+stats = manager.get_stats()
 print(f"\nStats: {stats}")

examples/python/cli/cost_tracking_example.py

@@ -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.display_summary()
+handler.print_summary()

examples/python/cli/slash_commands_example.py

@@ -41,9 +41,9 @@ def my_custom_handler(args, context):
 custom_cmd = SlashCommand(
     name="mycommand",
     description="My custom command",
-    handler=my_custom_handler,
-    kind=CommandKind.ACTION,
-    aliases=["mc"]
+    action=my_custom_handler,
+    kind=CommandKind.CUSTOM,
+    alt_names=["mc"]
 )
 
 handler.register(custom_cmd)

examples/python/concepts/repetitive-agents.py

@@ -16,7 +16,8 @@ agents = AgentTeam(
     agents=[agent],
     tasks=[task],
     process="workflow",
-    max_iter=30
+    execution={"max_iter": 30},
 )
 
-agents.start()
+if __name__ == "__main__":
+    agents.start()

examples/python/concepts/self-reflection-optimization-patterns.py

@@ -5,7 +5,8 @@ This example demonstrates self-reflection capabilities using PraisonAI's
 built-in reflection features for iterative improvement and quality optimization.
 """
 
-from praisonaiagents import Agent, Task, AgentTeam
+from praisonaiagents import Agent, Task
+from praisonaiagents.agents import AgentTeam
 from praisonaiagents.tools import internet_search
 
 print("=== Self-Reflection Optimization Patterns Example ===\n")
@@ -33,9 +34,16 @@ reflection_task = Task(
 )
 
 # Run with self-reflection optimization
-print("Starting self-reflection optimization demonstration...")
-result = reflection_agent.execute_task(reflection_task)
+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(f"\nSelf-Reflection Result: {result[:200]}...")
-print("\n✅ Self-reflection optimization complete!")
-print("Agent demonstrated iterative improvement through built-in self-reflection capabilities.")
+    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.")

examples/python/custom_tools/example_latency_tracking.py

@@ -61,7 +61,6 @@ def example_with_wrappers():
         role="Data Analyst",
         goal="Analyze data and provide insights",
         llm="gpt-4o-mini",
-        request_id="request_2"  # Unique request ID
     )
     
     # Operations are automatically tracked

examples/python/data/cot-agents.py

@@ -132,7 +132,9 @@ agents = AgentTeam(
     agents=[qa_generator, total_questions_evaluator, cot_generator, upload_to_huggingface],
     tasks=[generate_task, evaluate_total_questions_task, generate_cot_task, upload_to_huggingface_task],
     process="workflow",
-    max_iter=30, output="minimal"
+    execution={"max_iter": 30},
+    output="minimal",
 )
 
-agents.start()
+if __name__ == "__main__":
+    agents.start()

examples/python/failover_example.py

@@ -18,7 +18,7 @@ openai_profile = AuthProfile(
     provider="openai",
     api_key=os.environ.get("OPENAI_API_KEY", "sk-..."),
     priority=1,  # Highest priority
-    rate_limit=100,
+    rate_limit_rpm=100,
 )
 
 anthropic_profile = AuthProfile(
@@ -26,7 +26,7 @@ anthropic_profile = AuthProfile(
     provider="anthropic",
     api_key=os.environ.get("ANTHROPIC_API_KEY", "sk-ant-..."),
     priority=2,  # Second priority
-    rate_limit=50,
+    rate_limit_rpm=50,
 )
 
 groq_profile = AuthProfile(
@@ -34,7 +34,7 @@ groq_profile = AuthProfile(
     provider="groq",
     api_key=os.environ.get("GROQ_API_KEY", "gsk-..."),
     priority=3,  # Third priority (fast but limited)
-    rate_limit=30,
+    rate_limit_rpm=30,
 )
 
 # Configure failover behavior

examples/python/general/memory_example.py

@@ -105,13 +105,13 @@ def main():
         agents=[researcher, retriever],
         tasks=[store_task, verify_task, query_task, query_both_task],  # Use same verbose level as memory
         memory={
-            "backend": "sqlite",
             "embedder": {
                 "provider": "openai",
                 "config": {
                     "model": "text-embedding-3-small"
                 }
-            }
+            },
+            "config": {"provider": "sqlite"},
         }
     )
 

examples/python/general/multimodal.py

@@ -49,10 +49,20 @@ agents = AgentTeam(
     process="sequential"
 )
 
-# Run all tasks
-result = agents.start()
+if __name__ == "__main__":
+    # Run all tasks
+    result = agents.start()
 
-# Print results
-for task_id, task_result in result["task_results"].items():
-    print(f"\nTask {task_id} Result:")
-    print(task_result.raw)
+    # 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))

examples/python/guardrails/production-guardrails-patterns.py

@@ -6,6 +6,7 @@ built-in validation and safety mechanisms for secure agent operations.
 """
 
 from praisonaiagents import Agent, Task, AgentTeam
+from praisonaiagents.config.feature_configs import GuardrailConfig
 from praisonaiagents.tools import internet_search
 
 print("=== Production Guardrails Patterns Example ===\n")
@@ -38,8 +39,8 @@ production_agent = Agent(
     goal="Generate safe, compliant content for production use",
     backstory="Production-ready agent with built-in safety and compliance checks",
     tools=[internet_search],
-    guardrails=content_guardrail,
-    max_retries=3)
+    guardrails=GuardrailConfig(validator=content_guardrail, max_retries=3),
+)
 
 # Create secure task with validation
 secure_task = Task(

examples/python/linear_agent_example.py

@@ -40,7 +40,7 @@ agent = Agent(
         "execute_command"
     ],
     memory=True,
-    web_search=True,
+    web=True,
     auto_approve_tools=True,
 )
 

examples/python/managed-agents/19_manage_environments.py

@@ -14,30 +14,33 @@ agent = Agent(name="env-mgmt", backend=managed)
 # First call creates agent + environment + session
 agent.start("Say hello briefly")
 
-# Access the underlying Anthropic client for environment management
-client = managed._get_client()
-env_id = managed.environment_id
-print(f"Environment ID: {env_id}")
+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}")
 
-# 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}")
+    # 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().")
 
 print("\nEnvironment management complete.")

examples/python/mcp/mcp-resumability.py

@@ -15,13 +15,6 @@ 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
@@ -29,6 +22,12 @@ agent = Agent(
 # 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()

examples/python/mcp/mcp-session-management.py

@@ -15,13 +15,6 @@ 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
@@ -29,6 +22,12 @@ agent = Agent(
 # 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()

examples/python/mcp/streamable-http-mcp.py

@@ -16,34 +16,31 @@ 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.")

examples/python/mcp/websocket-mcp.py

@@ -16,36 +16,33 @@ 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
     

examples/python/memory/advanced-graph-memory-integration.py

@@ -12,8 +12,8 @@ print("=== Advanced Graph Memory Integration Example ===\n")
 
 # Configure simple graph memory
 memory_config = {
-    "provider": "mem0",
     "config": {
+        "provider": "mem0",
         "vector_store": {
             "provider": "chroma",
             "config": {

examples/python/memory/advanced-memory-search-optimization.py

@@ -12,8 +12,8 @@ print("=== Advanced Memory Search and Optimization Example ===\n")
 
 # Configure optimized memory settings
 memory_config = {
-    "provider": "mem0",
     "config": {
+        "provider": "mem0",
         "vector_store": {
             "provider": "chroma",
             "config": {

examples/python/memory/gemini-embedding-example.py

@@ -86,13 +86,13 @@ def main():
         agents=[researcher, retriever],
         tasks=[store_task, retrieve_task],
         memory={
-            "backend": "sqlite",
             "embedder": {
                 "provider": "gemini",
                 "config": {
                     "model": "text-embedding-004",
                 }
-            }
+            },
+            "config": {"provider": "sqlite"},
         }
     )
     

examples/python/models/deepseek/deepseek-rag-agents.py

@@ -30,7 +30,11 @@ config = {
 agent = Agent(
     name="Knowledge Agent",
     instructions="You answer questions based on the provided knowledge.",
-    knowledge={**config, "sources": ["kag-research-paper.pdf"]},
+    knowledge={
+        "sources": ["kag-research-paper.pdf"],
+        "vector_store": config["vector_store"],
+        "embedder": config["embedder"],
+    },
     memory={"user_id": "user1"},
     llm="deepseek-r1"
 )

examples/python/models/googlegemini/any-llm-agents-advanced.py

@@ -31,10 +31,9 @@ llm_config = {
 agent = Agent(
     instructions="You are a helpful Assistant specialized in scientific explanations. "
                 "Provide clear, accurate, and engaging responses.",
-    llm=llm_config,                  # Pass the detailed configuration
-    # Enable detailed output
-    markdown=True,                   # Format responses in markdown
-    reflection=True               # Enable self-reflection
+    llm=llm_config,
+    output={"markdown": True},
+    reflection=True,
 )
 
 # Test the agent

examples/python/mongodb/mongodb_memory_example.py

@@ -28,8 +28,8 @@ if not os.environ.get("OPENAI_API_KEY"):
 def main():
     # MongoDB memory configuration
     mongodb_memory_config = {
-        "provider": "mongodb",
         "config": {
+            "provider": "mongodb",
             "connection_string": "mongodb://localhost:27017/",  # Replace with your MongoDB connection string
             "database": "praisonai_memory",
             "use_vector_search": True,  # Enable Atlas Vector Search (requires MongoDB Atlas)

examples/python/save_output/03_workflow_output_file.py

@@ -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 AgentFlow
+from praisonaiagents import Agent, AgentFlow, Task
 
 # Define workflow with output_file
 workflow_config = {
@@ -33,9 +33,30 @@ workflow_config = {
     ]
 }
 
-# Run workflow
-workflow = AgentFlow(config=workflow_config)
-result = workflow.run()
+# 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()
 
 print("✅ Workflow completed!")
 print("Output saved to: generated/tutorial.md")

examples/python/session/session_persistence_example.py

@@ -28,7 +28,7 @@ def example_basic_persistence():
     agent = Agent(
         name="Assistant",
         instructions="You are a helpful assistant. Be very brief.",
-        session_id=session_id,
+        memory={"session_id": session_id},
         output="minimal",
     )
     
@@ -59,7 +59,7 @@ def example_session_restoration():
     agent1 = Agent(
         name="MemoryBot",
         instructions="You are a helpful assistant. Be very brief.",
-        session_id=session_id,
+        memory={"session_id": session_id},
         output="minimal",
     )
     
@@ -72,7 +72,7 @@ def example_session_restoration():
     agent2 = Agent(
         name="MemoryBot",
         instructions="You are a helpful assistant. Be very brief.",
-        session_id=session_id,
+        memory={"session_id": session_id},
         output="minimal",
     )
     

examples/python/stateful/advanced-state-management-patterns.py

@@ -69,9 +69,10 @@ agents_system = AgentTeam(
     memory=True, output="verbose"
 )
 
-print("Starting state management demonstration...")
-result = agents_system.start()
+if __name__ == "__main__":
+    print("Starting state management demonstration...")
+    result = agents_system.start()
 
-print(f"\nState Management Result: {result[:200]}...")
-print("\n✅ State management patterns complete!")
-print("Agent demonstrated persistent state tracking across multiple tasks.")
+    print(f"\nState Management Result: {str(result)[:200]}...")
+    print("\n✅ State management patterns complete!")
+    print("Agent demonstrated persistent state tracking across multiple tasks.")

examples/python/stateful/memory-quality-example.py

@@ -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
     )
     

examples/python/stateful/session-example.py

@@ -15,7 +15,7 @@ def main():
     # Create a session with persistent storage
     session = Session(
         session_id="demo_chat_001",
-        memory={"user_id": "demo_user"},
+        user_id="demo_user",
     )
     
     print(f"📝 Created session: {session}")

examples/python/telemetry/production-telemetry-example.py

@@ -1,284 +1,55 @@
 """
 Production Telemetry Example
 
-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
+Demonstrates compatible telemetry setup with `enable_telemetry()` and
+`TelemetryCollector` patterns.
 """
 
+from contextlib import nullcontext
 from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import duckduckgo
-from praisonaiagents.telemetry import enable_telemetry
-import time
-import random
-from datetime import datetime
+from praisonaiagents.telemetry import enable_telemetry, TelemetryCollector
 
-# Initialize telemetry for production monitoring
-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"
-        }
-    }
-)
+def main() -> None:
+    print("=" * 80)
+    print("PRODUCTION TELEMETRY SETUP")
+    print("=" * 80)
 
-# 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."
-)
+    # New API: no args
+    enable_telemetry()
+    collector = TelemetryCollector()
 
-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."
-)
+    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.",
+    )
 
-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
-        }
+    requests = [
+        "Customer asking about monthly bill charges",
+        "Customer experiencing connectivity issues",
     ]
-    
-    return customer_requests
 
-# Execute production workflow with comprehensive telemetry
-print("Starting production workflow with telemetry tracking...")
+    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))}")
 
-customer_requests = simulate_customer_requests()
+    print("\nTelemetry demonstration completed.")
 
-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)
 
-# 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")
+if __name__ == "__main__":
+    main()

examples/python/token-metrics/01_basic_token_tracking.py

@@ -14,7 +14,7 @@ def main():
         goal="Find information about a topic",
         backstory="You are an expert researcher who finds comprehensive information.",
         llm="gpt-4o-mini",  # Use a cost-effective model for examples
-        metrics=True  # 🎯 SIMPLIFIED: Just add this parameter!
+        output={"metrics": True}  # Token metrics via consolidated output config
     )
     
     # Create a simple task

examples/python/token-metrics/02_session_metrics.py

@@ -14,7 +14,7 @@ def main():
         goal="Analyze data and provide insights",
         backstory="You are an experienced data analyst with expertise in market research.",
         llm="gpt-4o-mini",
-        metrics=True  # 🎯 Enable metrics tracking
+        output={"metrics": True}
     )
     
     writer_agent = Agent(
@@ -23,7 +23,7 @@ def main():
         goal="Create well-structured content",
         backstory="You are a skilled technical writer who creates clear, engaging content.",
         llm="gpt-4o-mini",
-        metrics=True  # 🎯 Enable metrics tracking
+        output={"metrics": True}
     )
     
     # Create multiple tasks

examples/python/token-metrics/03_cost_estimation.py

@@ -14,7 +14,7 @@ def main():
         goal="Conduct comprehensive market research",
         backstory="You are a seasoned market researcher with 10+ years of experience.",
         llm="gpt-4o-mini",
-        metrics=True  # 🎯 Enable automatic metrics tracking
+        output={"metrics": True}
     )
     
     strategy_agent = Agent(
@@ -23,7 +23,7 @@ def main():
         goal="Develop actionable business strategies",
         backstory="You are a strategic consultant who translates research into business plans.",
         llm="gpt-4o-mini",
-        metrics=True  # 🎯 Enable automatic metrics tracking
+        output={"metrics": True}
     )
     
     # Create tasks that will generate substantial token usage

examples/python/tools/exa-tool/rag_examples/agentic_rag/rag_agent.py

@@ -22,7 +22,8 @@ rag_agent = Agent(
     
     You can use the internet_search function to search the web when needed.""",
     llm="gpt-4o",
-    markdown=True)
+    output={"markdown": True},
+)
 
 if __name__ == "__main__":
     print("🤖 Thai Recipe RAG Agent is ready!")

examples/python/tools/jira_agent_example.py

@@ -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:
-   - JIRA_EMAIL=your_email@example.com (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()

examples/python/tools/langchain/google-serper-search.py

@@ -5,11 +5,17 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
-os.environ['SERPER_API_KEY'] = os.getenv('SERPER_API_KEY')
+serper_api_key = os.getenv("SERPER_API_KEY")
+if serper_api_key is not None:
+    os.environ["SERPER_API_KEY"] = serper_api_key
 
-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()
+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()

examples/python/usecases/analysis/code-analysis-agents.py

@@ -2,6 +2,7 @@ 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
@@ -60,7 +61,10 @@ def analyze_code(code_source: str) -> CodeAnalysisReport:
     Analyze code from directory path or GitHub URL
     """
     # Ingest code content
-    summary, tree, content = ingest(code_source)
+    try:
+        summary, tree, content = ingest(code_source)
+    except Exception as exc:
+        raise RuntimeError(f"Failed to ingest code source: {exc}") from exc
     
     # Concatenate context into structured format
     context_text = f"""
@@ -86,10 +90,22 @@ def analyze_code(code_source: str) -> CodeAnalysisReport:
         tasks=[code_analysis_task]
     )
     
-    return agents.start(context_text)
+    result = agents.start(context_text)
+    if result is None:
+        raise RuntimeError("No analysis result returned by AgentTeam.start()")
+    return result
 
-if __name__ == "__main__":
+
+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
-    result = analyze_code(code_source)
-    print(result) 
+    try:
+        result = analyze_code(code_source)
+    except RuntimeError as exc:
+        print(f"Code analysis failed: {exc}")
+        sys.exit(1)
+    print(result) 
+
+
+if __name__ == "__main__":
+    main()

examples/python/usecases/analysis/cv-analysis.py

@@ -77,25 +77,44 @@ 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: {result.pydantic.overall_score}/100")
+print(f"\nOverall Score: {pydantic_result.overall_score}/100")
 print("\nKey Strengths:")
-for strength in result.pydantic.key_strengths:
+for strength in pydantic_result.key_strengths:
     print(f"- {strength}")
 
 print("\nSkill Analysis:")
 print("\nTechnical Skills:")
-for skill in result.pydantic.skill_analysis.technical_skills:
+for skill in pydantic_result.skill_analysis.technical_skills:
     print(f"- {skill}")
 
 print("\nExperience Highlights:")
-for achievement in result.pydantic.experience_analysis.key_achievements:
+for achievement in pydantic_result.experience_analysis.key_achievements:
     print(f"- {achievement}")
 
 print("\nRecommendations:")
-for recommendation in result.pydantic.recommendations:
+for recommendation in pydantic_result.recommendations:
     print(f"- {recommendation}")

examples/python/usecases/analysis/hackathon-judge-agent.py

@@ -100,6 +100,8 @@ 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(

examples/python/video/video_azure.py

@@ -1,5 +1,11 @@
 from praisonaiagents import VideoAgent
+import os
 
-agent = VideoAgent(llm="azure/sora-2")
-video = agent.generate("Mountain landscape")
-print(video.id)
+
+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)

examples/python/workflows/task_callbacks.py

@@ -6,6 +6,7 @@ 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(
@@ -47,8 +48,10 @@ if __name__ == "__main__":
         agents=[researcher],
         tasks=[task1, task2],
         process="workflow",
-        on_task_start=on_start,
-        on_task_complete=on_complete,
+        hooks=MultiAgentHooksConfig(
+            on_task_start=on_start,
+            on_task_complete=on_complete,
+        ),
         variables={"global_var": "shared_value"}  # Global variables
     )
     

examples/python/workflows/workflow_branching.py

@@ -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']}")

examples/python/workflows/workflow_conditional.py

@@ -54,13 +54,13 @@ workflow = AgentFlow(
         analyzer,  # Always runs
         Task(
             name="tech_review",
-            description="Review technical aspects of the content",
+            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 the creative aspects of the content",
+            description="Enhance narrative quality when creative keywords are detected.",
             agent=creative_enhancer,
             should_run=needs_creative  # Only runs for creative content
         ),

examples/python/workflows/workflow_early_stop.py

@@ -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']}")

examples/python/workflows/workflow_loops.py

@@ -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")

examples/python/workflows/workflow_mixed_steps.py

@@ -53,7 +53,7 @@ workflow = AgentFlow(
         # Step 4: Function - formats output
         format_output
     ],
-    llm="gpt-4o-mini"  # Used for action-based steps
+    llm="gpt-4o-mini",  # Used for action-based steps
 )
 
 if __name__ == "__main__":

examples/python/workflows/workflow_parallel.py

@@ -5,7 +5,7 @@ Demonstrates running multiple agents concurrently and
 combining their results with an aggregator agent.
 """
 
-from praisonaiagents import Agent, AgentFlow
+from praisonaiagents import Agent, Workflow
 from praisonaiagents.workflows import parallel
 
 # Create parallel research agents

examples/python/workflows/workflow_robustness.py

@@ -42,6 +42,7 @@ def main():
     
     # Create tasks with robustness features
     research_task = Task(
+        name="research",
         description="Research the latest trends in AI agents for 2025",
         expected_output="A summary of key AI agent trends",
         agent=researcher,
@@ -51,6 +52,7 @@ def main():
     
     # Optional enrichment step - workflow continues even if this fails
     enrich_task = Task(
+        name="enrich",
         description="Enrich the research with real-world examples",
         expected_output="Research with added examples",
         agent=enricher,
@@ -60,6 +62,7 @@ def main():
     )
     
     write_task = Task(
+        name="write",
         description="Write a brief summary based on the research",
         expected_output="A well-written summary paragraph",
         agent=writer,

examples/python/workflows/workflow_routing.py

@@ -5,7 +5,7 @@ Demonstrates decision-based routing where an agent classifier
 routes to specialized handler agents based on the request type.
 """
 
-from praisonaiagents import Agent, AgentFlow
+from praisonaiagents import Agent, Workflow
 from praisonaiagents.workflows import route
 
 # Create classifier agent

examples/retrieval/basic_retrieval.py

@@ -51,13 +51,15 @@ print("=" * 60)
 agent = Agent(
     name="Knowledge Agent",
     instructions="You are a helpful assistant that answers questions based on the provided knowledge. Be concise.",
-    knowledge=[".praison/test_docs/overview.txt"],
-    retrieval_config={
-        "policy": "always",      # Always retrieve for this demo
-        "top_k": 3,              # Get top 3 chunks
-        "citations": True,       # Include citations
-        "max_context_tokens": 2000,
-    }
+    knowledge={
+        "sources": [".praison/test_docs/overview.txt"],
+        "config": {
+            "policy": "always",
+            "top_k": 3,
+            "citations": True,
+            "max_context_tokens": 2000,
+        },
+    },
 )
 
 # Test 1: Basic chat with retrieval

examples/skills/basic_skill_usage.py

@@ -60,7 +60,7 @@ print("=" * 50)
 agent_with_discovery = Agent(
     name="Multi-Skill Agent",
     instructions="You are a versatile assistant with multiple skills.",
-    skills_dirs=["./"],  # Scan current directory for skill subdirectories
+    skills=["./"],  # Scan current directory for skill subdirectories
 )
 
 if agent_with_discovery.skill_manager:

examples/storage/storage_backends_example.py

@@ -190,7 +190,7 @@ def example_run_history_with_backend():
         
         # Use with RunHistory
         history = RunHistory(backend=backend)
-        runs = history.list()
+        runs = history.list_runs()
         
         print(f"RunHistory created with SQLite backend, {len(runs)} runs")
         print("Recipe runs will be stored in database instead of files")