Release v4.2.2

Merge branch 'main' of https://github.com/MervinPraison/PraisonAI
refactor: redirect logging function output to stderr in install script.
2026-11-09 17:31:52 -10:00 · 2026-01-31 20:27:06 +00:00 · 2026-01-31 20:17:54 +00:00 · 2026-01-31 20:17:54 +00:00 · 2026-01-31 17:13:26 +00:00 · 2026-01-31 17:13:10 +00:00
785 changed files with 77985 additions and 5733 deletions
@@ -0,0 +1,145 @@
+name: Performance Benchmarks
+
+on:
+  workflow_dispatch:
+    inputs:
+      iterations:
+        description: 'Number of benchmark iterations'
+        required: false
+        default: '100'
+      fail_on_regression:
+        description: 'Fail if performance regresses'
+        required: false
+        default: 'true'
+
+jobs:
+  benchmark:
+    runs-on: ubuntu-latest
+    timeout-minutes: 30
+    
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python 3.12
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.12'
+          cache: 'pip'
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e src/praisonai-agents[all]
+          pip install agno crewai langgraph
+
+      - name: Run Import Time Benchmark
+        id: import_time
+        run: |
+          cd src/praisonai-agents
+          python benchmarks/import_time.py 2>&1 | tee import_time_output.txt
+          
+          # Extract import time
+          IMPORT_TIME=$(grep -oP 'Median:\s+\K[\d.]+' import_time_output.txt || echo "0")
+          echo "import_time=$IMPORT_TIME" >> $GITHUB_OUTPUT
+          
+          # Check threshold (200ms)
+          if (( $(echo "$IMPORT_TIME > 200" | bc -l) )); then
+            echo "::warning::Import time ${IMPORT_TIME}ms exceeds 200ms threshold"
+            if [ "${{ inputs.fail_on_regression }}" == "true" ]; then
+              echo "import_passed=false" >> $GITHUB_OUTPUT
+            fi
+          else
+            echo "import_passed=true" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Run Memory Usage Benchmark
+        id: memory
+        run: |
+          cd src/praisonai-agents
+          python benchmarks/memory_usage.py 2>&1 | tee memory_output.txt
+          
+          # Extract peak memory
+          PEAK_MEMORY=$(grep -oP 'Peak:\s+\K[\d.]+' memory_output.txt || echo "0")
+          echo "peak_memory=$PEAK_MEMORY" >> $GITHUB_OUTPUT
+          
+          # Check threshold (30MB)
+          if (( $(echo "$PEAK_MEMORY > 30" | bc -l) )); then
+            echo "::warning::Memory usage ${PEAK_MEMORY}MB exceeds 30MB threshold"
+            if [ "${{ inputs.fail_on_regression }}" == "true" ]; then
+              echo "memory_passed=false" >> $GITHUB_OUTPUT
+            fi
+          else
+            echo "memory_passed=true" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Run Simple Benchmark
+        id: simple
+        run: |
+          cd src/praisonai-agents
+          python benchmarks/simple_benchmark.py 2>&1 | tee simple_output.txt
+          
+          # Extract PraisonAI time
+          PRAISON_TIME=$(grep -oP 'PraisonAI\s+\K[\d.]+' simple_output.txt | head -1 || echo "0")
+          echo "praison_time=$PRAISON_TIME" >> $GITHUB_OUTPUT
+
+      - name: Run Tools Benchmark
+        id: tools
+        run: |
+          cd src/praisonai-agents
+          python benchmarks/tools_benchmark.py 2>&1 | tee tools_output.txt
+          
+          # Extract PraisonAI time with tools
+          PRAISON_TOOLS_TIME=$(grep -oP 'PraisonAI\s+\K[\d.]+' tools_output.txt | head -1 || echo "0")
+          echo "praison_tools_time=$PRAISON_TOOLS_TIME" >> $GITHUB_OUTPUT
+
+      - name: Run Parameter Impact Benchmark
+        id: param_impact
+        run: |
+          cd src/praisonai-agents
+          python benchmarks/param_impact_benchmark.py --no-save --iterations ${{ inputs.iterations }} 2>&1 | tee param_impact_output.txt
+
+      - name: Check Lazy Imports
+        id: lazy_imports
+        run: |
+          cd src/praisonai-agents
+          python -c "
+          import sys
+          from praisonaiagents import Agent
+          agent = Agent(name='Test', output='silent')
+          
+          # Check litellm is NOT loaded
+          if 'litellm' in sys.modules:
+              print('FAIL: litellm loaded during silent agent creation')
+              exit(1)
+          else:
+              print('PASS: litellm not loaded (lazy import working)')
+          "
+
+      - name: Generate Benchmark Summary
+        if: always()
+        run: |
+          echo "## Performance Benchmark Results" >> $GITHUB_STEP_SUMMARY
+          echo "" >> $GITHUB_STEP_SUMMARY
+          echo "| Metric | Value | Threshold | Status |" >> $GITHUB_STEP_SUMMARY
+          echo "|--------|-------|-----------|--------|" >> $GITHUB_STEP_SUMMARY
+          echo "| Import Time | ${{ steps.import_time.outputs.import_time }}ms | <200ms | ${{ steps.import_time.outputs.import_passed == 'true' && '✅' || '❌' }} |" >> $GITHUB_STEP_SUMMARY
+          echo "| Peak Memory | ${{ steps.memory.outputs.peak_memory }}MB | <30MB | ${{ steps.memory.outputs.memory_passed == 'true' && '✅' || '❌' }} |" >> $GITHUB_STEP_SUMMARY
+          echo "| Agent Instantiation | ${{ steps.simple.outputs.praison_time }}μs | - | ℹ️ |" >> $GITHUB_STEP_SUMMARY
+          echo "| Agent with Tools | ${{ steps.tools.outputs.praison_tools_time }}μs | - | ℹ️ |" >> $GITHUB_STEP_SUMMARY
+          echo "" >> $GITHUB_STEP_SUMMARY
+          echo "### Lazy Import Check" >> $GITHUB_STEP_SUMMARY
+          echo "✅ litellm not loaded during silent agent creation" >> $GITHUB_STEP_SUMMARY
+
+      - name: Fail on Regression
+        if: inputs.fail_on_regression == 'true'
+        run: |
+          if [ "${{ steps.import_time.outputs.import_passed }}" == "false" ]; then
+            echo "::error::Import time regression detected"
+            exit 1
+          fi
+          if [ "${{ steps.memory.outputs.memory_passed }}" == "false" ]; then
+            echo "::error::Memory usage regression detected"
+            exit 1
+          fi
+          echo "All performance checks passed!"
@@ -137,7 +137,6 @@ PraisonAI Agents is the **fastest AI agent framework** for agent instantiation.
 | PraisonAI (LiteLLM) | 7.56 | 2.00x |
 | PydanticAI | 226.94 | 60.16x |
 | LangGraph | 4,558.71 | 1,209x |
-| CrewAI | 15,607.92 | 4,138x |

 <details>
 <summary>Run benchmarks yourself</summary>
@@ -3,11 +3,27 @@
 This file is auto-generated. Do not edit manually.
 Regenerate with: `praisonai docs api-md --write`

+# Shared Types
+
+Types:
+```python
+from praisonaiagents import ContextPolicy, GuardrailResult, HandoffConfig, HandoffCycleError, HandoffDepthError, HandoffError, HandoffInputData, HandoffResult, HandoffTimeoutError, ReflectionOutput, StepResult, TaskOutput, ToolResult, ToolValidationError, WorkflowContext
+```
+
+Methods:
+
+* <code title="class GuardrailResult">GuardrailResult.<a href="./src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py">from_tuple</a>(result: Tuple[bool, Any]) -> 'GuardrailResult'</code>
+* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">from_dict</a>(data: Dict[str, Any]) -> 'HandoffConfig'</code>
+* <code title="class HandoffConfig">HandoffConfig.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">json</a>() -> Optional[str]</code>
+* <code title="class TaskOutput">TaskOutput.<a href="./src/praisonai-agents/praisonaiagents/main.py">to_dict</a>() -> dict</code>
+* <code title="class ToolResult">ToolResult.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">to_dict</a>() -> Dict[str, Any]</code>
+
 # Agents

 Types:
 ```python
-from praisonaiagents import Agent, Agents
+from praisonaiagents import Agent, AutoAgents, AutoRagAgent, ContextAgent, DeepResearchAgent, ImageAgent, PlanningAgent, PromptExpanderAgent, QueryRewriterAgent, create_context_agent
 ```

 Methods:
@@ -22,7 +38,7 @@ Methods:
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">auto_memory</a>(value)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>()</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">background</a>(value)</code>
-* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat</a>(prompt, temperature = 1.0, tools = None, output_json = None, output_pydantic = None, reasoning_steps = False, stream = None, task_name = None, task_description = None, task_id = None, config = None, force_retrieval = False, skip_retrieval = False, attachments = None)</code>
+* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat</a>(prompt, temperature = 1.0, tools = None, output_json = None, output_pydantic = None, reasoning_steps = False, stream = None, task_name = None, task_description = None, task_id = None, config = None, force_retrieval = False, skip_retrieval = False, attachments = None, tool_choice = None)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">chat_with_context</a>(message: str, context: 'ContextPack', **kwargs) -> str</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>()</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">checkpoints</a>(value)</code>
@@ -33,7 +49,6 @@ Methods:
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">context_manager</a>(value)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">delete_history</a>(index: int) -> bool</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">delete_history_matching</a>(pattern: str) -> int</code>
-* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">display_generating</a>(content: str, start_time: float)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">display_name</a>() -> str</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">ephemeral</a>()</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">execute</a>(task, context = None)</code>
@@ -64,70 +79,131 @@ Methods:
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">retrieve</a>(query: str, **kwargs) -> 'ContextPack'</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">rules_manager</a>()</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run</a>(prompt: str, **kwargs)</code>
-* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None)</code>
+* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None, completion_promise: Optional[str] = None, clear_context: bool = False)</code>
+* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">run_autonomous_async</a>(prompt: str, max_iterations: Optional[int] = None, timeout_seconds: Optional[float] = None, completion_promise: Optional[str] = None, clear_context: bool = False)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">session_id</a>() -> Optional[str]</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">skill_manager</a>()</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">start</a>(prompt: str = None, **kwargs)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">store_memory</a>(content: str, memory_type: str = 'short_term', **kwargs)</code>
+* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>()</code>
+* <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">stream_emitter</a>(value)</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">switch_model</a>(new_model: str) -> None</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>()</code>
 * <code title="class Agent">Agent.<a href="./src/praisonai-agents/praisonaiagents/agent/agent.py">thinking_budget</a>(value)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">add_task</a>(task)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aexecute_task</a>(task_id)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">append_to_state</a>(key: str, value: Any, max_length: Optional[int] = None) -> List[Any]</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_all_tasks</a>()</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">context_manager</a>()</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">current_plan</a>()</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">default_completion_checker</a>(task, agent_output)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">delete_state</a>(key: str) -> bool</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">display_token_usage</a>()</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">execute_task</a>(task_id)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_agent_details</a>(agent_name)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_state</a>() -> Dict[str, Any]</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_tasks_status</a>()</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_detailed_token_report</a>() -> Dict[str, Any]</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_plan_markdown</a>() -> str</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_state</a>(key: str, default: Any = None) -> Any</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_details</a>(task_id)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_status</a>(task_id)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_todo_markdown</a>() -> str</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_token_usage_summary</a>() -> Dict[str, Any]</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">has_state</a>(key: str) -> bool</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">increment_state</a>(key: str, amount: float = 1, default: float = 0) -> float</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">launch</a>(path: str = '/agents', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">restore_session_state</a>(session_id: str) -> bool</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run</a>(content = None, return_dict = False, **kwargs)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_all_tasks</a>()</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_task</a>(task_id)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, output = None, **kwargs)</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
-* <code title="class Agents">Agents.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
+* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">astart</a>()</code>
+* <code title="class AutoAgents">AutoAgents.<a href="./src/praisonai-agents/praisonaiagents/agents/autoagents.py">start</a>()</code>
+* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">achat</a>(message: str, **kwargs) -> str</code>
+* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">chat</a>(message: str, **kwargs) -> str</code>
+* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">name</a>() -> str</code>
+* <code title="class AutoRagAgent">AutoRagAgent.<a href="./src/praisonai-agents/praisonaiagents/agents/auto_rag_agent.py">rag</a>() -> Optional['RAG']</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">aanalyze_codebase</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">acreate_implementation_blueprint</a>(feature_request: str, context_analysis: Optional[Dict[str, Any]] = None) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">agenerate_prp</a>(feature_request: str, context_analysis: Optional[Dict[str, Any]] = None) -> str</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">analyze_codebase</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">analyze_codebase_with_gitingest</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">analyze_integration_points</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">analyze_test_patterns</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">build_implementation_blueprint</a>(feature_request: str, context_analysis: Dict[str, Any] = None) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">compile_context_documentation</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">create_implementation_blueprint</a>(feature_request: str, context_analysis: Optional[Dict[str, Any]] = None) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">create_quality_gates</a>(requirements: List[str]) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">create_validation_framework</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">execute_prp</a>(prp_file_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">extract_implementation_patterns</a>(project_path: str, ast_analysis: Dict[str, Any] = None) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">generate_comprehensive_prp</a>(feature_request: str, context_analysis: Dict[str, Any] = None) -> str</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">generate_feature_prp</a>(feature_request: str) -> str</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">generate_prp</a>(feature_request: str, context_analysis: Optional[Dict[str, Any]] = None) -> str</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">get_agent_interaction_summary</a>() -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">log_debug</a>(message: str, **kwargs)</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">perform_ast_analysis</a>(project_path: str) -> Dict[str, Any]</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">save_comprehensive_session_report</a>()</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">save_markdown_output</a>(content: str, filename: str, section_title: str = 'Output')</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">setup_logging</a>()</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">setup_output_directories</a>()</code>
+* <code title="class ContextAgent">ContextAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">start</a>(input_text: str) -> str</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">aresearch</a>(query: str, instructions: Optional[str] = None, model: Optional[str] = None, summary_mode: Optional[Literal['auto', 'detailed', 'concise']] = None, web_search: Optional[bool] = None, code_interpreter: Optional[bool] = None, mcp_servers: Optional[List[Dict[str, Any]]] = None, file_ids: Optional[List[str]] = None, file_search: Optional[bool] = None, file_search_stores: Optional[List[str]] = None) -> DeepResearchResponse</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">async_openai_client</a>()</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">clarify</a>(query: str, model: Optional[str] = None) -> str</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">follow_up</a>(query: str, previous_interaction_id: str, model: Optional[str] = None) -> DeepResearchResponse</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">gemini_client</a>()</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">openai_client</a>()</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">research</a>(query: str, instructions: Optional[str] = None, model: Optional[str] = None, summary_mode: Optional[Literal['auto', 'detailed', 'concise']] = None, web_search: Optional[bool] = None, code_interpreter: Optional[bool] = None, mcp_servers: Optional[List[Dict[str, Any]]] = None, file_ids: Optional[List[str]] = None, file_search: Optional[bool] = None, file_search_stores: Optional[List[str]] = None, stream: bool = True) -> DeepResearchResponse</code>
+* <code title="class DeepResearchAgent">DeepResearchAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/deep_research_agent.py">rewrite_query</a>(query: str, model: Optional[str] = None) -> str</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">achat</a>(prompt: str, temperature: float = 0.2, tools: Optional[List[Any]] = None, output_json: Optional[str] = None, output_pydantic: Optional[Any] = None, reasoning_steps: bool = False, **kwargs) -> Union[str, Dict[str, Any]]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">aedit</a>(image: str, prompt: str, mask: Optional[str] = None, n: int = 1, size: Optional[str] = None, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">agenerate</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">agenerate_image</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">avariation</a>(image: str, n: int = 1, size: Optional[str] = None, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">chat</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">edit</a>(image: str, prompt: str, mask: Optional[str] = None, n: int = 1, size: Optional[str] = None, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">generate</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">generate_image</a>(prompt: str, **kwargs) -> Dict[str, Any]</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">litellm</a>()</code>
+* <code title="class ImageAgent">ImageAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/image_agent.py">variation</a>(image: str, n: int = 1, size: Optional[str] = None, **kwargs) -> Dict[str, Any]</code>
+* <code title="class PlanningAgent">PlanningAgent.<a href="./src/praisonai-agents/praisonaiagents/planning/planner.py">analyze_context</a>(context: str) -> str</code>
+* <code title="class PlanningAgent">PlanningAgent.<a href="./src/praisonai-agents/praisonaiagents/planning/planner.py">analyze_context_sync</a>(context: str) -> str</code>
+* <code title="class PlanningAgent">PlanningAgent.<a href="./src/praisonai-agents/praisonaiagents/planning/planner.py">create_plan</a>(request: str, agents: List['Agent'], tasks: Optional[List['Task']] = None, context: Optional[str] = None) -> Plan</code>
+* <code title="class PlanningAgent">PlanningAgent.<a href="./src/praisonai-agents/praisonaiagents/planning/planner.py">create_plan_sync</a>(request: str, agents: List['Agent'], tasks: Optional[List['Task']] = None, context: Optional[str] = None) -> Plan</code>
+* <code title="class PlanningAgent">PlanningAgent.<a href="./src/praisonai-agents/praisonaiagents/planning/planner.py">is_tool_allowed</a>(tool_name: str) -> bool</code>
+* <code title="class PlanningAgent">PlanningAgent.<a href="./src/praisonai-agents/praisonaiagents/planning/planner.py">refine_plan</a>(plan: Plan, feedback: str) -> Plan</code>
+* <code title="class PlanningAgent">PlanningAgent.<a href="./src/praisonai-agents/praisonaiagents/planning/planner.py">refine_plan_sync</a>(plan: Plan, feedback: str) -> Plan</code>
+* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">agent</a>()</code>
+* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand</a>(prompt: str, strategy: ExpandStrategy = ..., context: Optional[str] = None) -> ExpandResult</code>
+* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_basic</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
+* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_creative</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
+* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_detailed</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
+* <code title="class PromptExpanderAgent">PromptExpanderAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/prompt_expander_agent.py">expand_structured</a>(prompt: str, context: Optional[str] = None) -> ExpandResult</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">add_abbreviation</a>(abbrev: str, expansion: str) -> None</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">add_abbreviations</a>(abbreviations: Dict[str, str]) -> None</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">agent</a>()</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite</a>(query: str, strategy: RewriteStrategy = ..., chat_history: Optional[List[Dict[str, str]]] = None, context: Optional[str] = None, num_queries: int = None) -> RewriteResult</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_basic</a>(query: str) -> RewriteResult</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_contextual</a>(query: str, chat_history: List[Dict[str, str]]) -> RewriteResult</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_hyde</a>(query: str) -> RewriteResult</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_multi_query</a>(query: str, num_queries: int = None) -> RewriteResult</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_step_back</a>(query: str) -> RewriteResult</code>
+* <code title="class QueryRewriterAgent">QueryRewriterAgent.<a href="./src/praisonai-agents/praisonaiagents/agent/query_rewriter_agent.py">rewrite_sub_queries</a>(query: str) -> RewriteResult</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/context_agent.py">create_context_agent</a>(llm: Optional[Union[str, Any]] = None, **kwargs) -> ContextAgent</code>

 # Tools

 Types:
 ```python
-from praisonaiagents import Tools, tool
+from praisonaiagents import BaseTool, FunctionTool, ToolRegistry, Tools, get_registry, get_tool, register_tool, tool, validate_tool
 ```

 Methods:

+* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">__call__</a>(**kwargs) -> Any</code>
+* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">get_schema</a>() -> Dict[str, Any]</code>
+* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">run</a>(**kwargs) -> Any</code>
+* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">safe_run</a>(**kwargs) -> ToolResult</code>
+* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate</a>() -> bool</code>
+* <code title="class BaseTool">BaseTool.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_class</a>() -> bool</code>
+* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">__call__</a>(*args, **kwargs) -> Any</code>
+* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">injected_params</a>() -> Dict[str, Any]</code>
+* <code title="class FunctionTool">FunctionTool.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">run</a>(**kwargs) -> Any</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">clear</a>() -> None</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_plugins</a>() -> int</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">discover_single_file_plugins</a>() -> int</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_all</a>() -> Dict[str, Union[BaseTool, Callable]]</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_base_tools</a>() -> List[BaseTool]</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">list_tools</a>() -> List[str]</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None, overwrite: bool = False) -> None</code>
+* <code title="class ToolRegistry">ToolRegistry.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">unregister</a>(name: str) -> bool</code>
+* <code title="class Tools">Tools.<a href="./src/praisonai-agents/praisonaiagents/tools/tools.py">internet_search</a>(*args, **kwargs)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_registry</a>() -> ToolRegistry</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">get_tool</a>(name: str) -> Optional[Union[BaseTool, Callable]]</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/registry.py">register_tool</a>(tool: Union[BaseTool, Callable], name: Optional[str] = None) -> None</code>
 * <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/decorator.py">tool</a>(func: Optional[Callable] = None) -> Union[FunctionTool, Callable[[Callable], FunctionTool]]</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/tools/base.py">validate_tool</a>(tool: Any) -> bool</code>

-# Other
+# Workflows

 Types:
 ```python
-from praisonaiagents import Task
+from praisonaiagents import Loop, Parallel, Pipeline, Repeat, Route, Task, Workflow, loop, parallel, repeat, route
 ```

 Methods:
@@ -136,12 +212,537 @@ Methods:
 * <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">execute_callback_sync</a>(task_output: TaskOutput) -> None</code>
 * <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">initialize_memory</a>()</code>
 * <code title="class Task">Task.<a href="./src/praisonai-agents/praisonaiagents/task/task.py">store_in_memory</a>(content: str, agent_name: str = None, task_id: str = None)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">loop</a>(step: Any = None, steps: Optional[List[Any]] = None, over: Optional[str] = None, from_csv: Optional[str] = None, from_file: Optional[str] = None, var_name: str = 'item', parallel: bool = False, max_workers: Optional[int] = None, output_variable: Optional[str] = None) -> Loop</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">parallel</a>(steps: List) -> Parallel</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">repeat</a>(step: Any, until: Optional[Callable[[WorkflowContext], bool]] = None, max_iterations: int = 10) -> Repeat</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">route</a>(routes: Dict[str, List], default: Optional[List] = None) -> Route</code>
+
+# DB
+
+Types:
+```python
+from praisonaiagents import db
+```
+
+# Memory
+
+Types:
+```python
+from praisonaiagents import Memory, MemoryBackend, MemoryConfig
+```
+
+Methods:
+
+* <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">compute_quality_score</a>(completeness: float, relevance: float, clarity: float, accuracy: float, weights: Dict[str, float] = None) -> float</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_long_term</a>(memory_id: str) -> bool</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_memories</a>(memory_ids: List[str]) -> int</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_memories_matching</a>(query: str, memory_type: Optional[str] = None, limit: int = 10) -> int</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_memory</a>(memory_id: str, memory_type: Optional[str] = None) -> bool</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">delete_short_term</a>(memory_id: str) -> bool</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">finalize_task_output</a>(content: str, agent_name: str, quality_score: float, threshold: float = 0.7, metrics: Dict[str, Any] = None, task_id: str = None)</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_all_memories</a>() -> List[Dict[str, Any]]</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">get_learn_context</a>() -> str</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">learn</a>()</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_all</a>()</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_entity_only</a>()</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_long_term</a>()</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_short_term</a>()</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">reset_user_memory</a>()</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search</a>(query: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_entity</a>(query: str, limit: int = 5) -> List[Dict[str, Any]]</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_long_term</a>(query: str, limit: int = 5, relevance_cutoff: float = 0.0, min_quality: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_short_term</a>(query: str, limit: int = 5, min_quality: float = 0.0, relevance_cutoff: float = 0.0, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_user_memory</a>(user_id: str, query: str, limit: int = 5, rerank: bool = False, **kwargs) -> List[Dict[str, Any]]</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">search_with_quality</a>(query: str, min_quality: float = 0.0, memory_type: Literal['short', 'long'] = 'long', limit: int = 5) -> List[Dict[str, Any]]</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_entity</a>(name: str, type_: str, desc: str, relations: str)</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_long_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None)</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_quality</a>(text: str, quality_score: float, task_id: Optional[str] = None, iteration: Optional[int] = None, metrics: Optional[Dict[str, float]] = None, memory_type: Literal['short', 'long'] = 'long') -> None</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_short_term</a>(text: str, metadata: Dict[str, Any] = None, completeness: float = None, relevance: float = None, clarity: float = None, accuracy: float = None, weights: Dict[str, float] = None, evaluator_quality: float = None)</code>
+* <code title="class Memory">Memory.<a href="./src/praisonai-agents/praisonaiagents/memory/memory.py">store_user_memory</a>(user_id: str, text: str, extra: Dict[str, Any] = None)</code>
+* <code title="class MemoryConfig">MemoryConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+
+# Knowledge
+
+Types:
+```python
+from praisonaiagents import Chunking, ChunkingStrategy, Knowledge, KnowledgeConfig
+```
+
+Methods:
+
+* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">SUPPORTED_CHUNKERS</a>() -> Dict[str, Any]</code>
+* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">__call__</a>(text: Union[str, List[str]], **kwargs) -> Union[List[Any], List[List[Any]]]</code>
+* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">chunk</a>(text: Union[str, List[str]], **kwargs) -> Union[List[Any], List[List[Any]]]</code>
+* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">chunker</a>()</code>
+* <code title="class Chunking">Chunking.<a href="./src/praisonai-agents/praisonaiagents/knowledge/chunking.py">embedding_model</a>()</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">add</a>(file_path, user_id = None, agent_id = None, run_id = None, metadata = None)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">chunker</a>()</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">config</a>()</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">delete</a>(memory_id)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">delete_all</a>(user_id = None, agent_id = None, run_id = None)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">get</a>(memory_id)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">get_all</a>(user_id = None, agent_id = None, run_id = None)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">get_corpus_stats</a>()</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">history</a>(memory_id)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">index</a>(path: str, incremental: bool = True, force: bool = False, include_glob: list = None, exclude_glob: list = None, user_id: str = None, agent_id: str = None, run_id: str = None)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">markdown</a>()</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">memory</a>()</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">normalize_content</a>(content)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">reset</a>()</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">search</a>(query, user_id = None, agent_id = None, run_id = None, rerank = None, **kwargs)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">store</a>(content, user_id = None, agent_id = None, run_id = None, metadata = None)</code>
+* <code title="class Knowledge">Knowledge.<a href="./src/praisonai-agents/praisonaiagents/knowledge/knowledge.py">update</a>(memory_id, data)</code>
+* <code title="class KnowledgeConfig">KnowledgeConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+
+# RAG
+
+Types:
+```python
+from praisonaiagents import CitationsMode, ContextPack, RAG, RAGCitation, RAGConfig, RAGResult, RetrievalConfig, RetrievalPolicy
+```
+
+Methods:
+
+* <code title="class ContextPack">ContextPack.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">format_for_prompt</a>(include_sources: bool = True) -> str</code>
+* <code title="class ContextPack">ContextPack.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'ContextPack'</code>
+* <code title="class ContextPack">ContextPack.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">has_citations</a>() -> bool</code>
+* <code title="class ContextPack">ContextPack.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">aquery</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> RAGResult</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">aretrieve</a>(query: str, **kwargs) -> ContextPack</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">astream</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> AsyncIterator[str]</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">get_citations</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> List[Citation]</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">llm</a>()</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">query</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> RAGResult</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">retrieve</a>(query: str, **kwargs) -> ContextPack</code>
+* <code title="class RAG">RAG.<a href="./src/praisonai-agents/praisonaiagents/rag/pipeline.py">stream</a>(question: str, user_id: Optional[str] = None, agent_id: Optional[str] = None, run_id: Optional[str] = None, **kwargs) -> Iterator[str]</code>
+* <code title="class RAGCitation">RAGCitation.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'Citation'</code>
+* <code title="class RAGCitation">RAGCitation.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class RAGConfig">RAGConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'RAGConfig'</code>
+* <code title="class RAGConfig">RAGConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">format_answer_with_citations</a>() -> str</code>
+* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">from_dict</a>(data: Dict[str, Any]) -> 'RAGResult'</code>
+* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">has_citations</a>() -> bool</code>
+* <code title="class RAGResult">RAGResult.<a href="./src/praisonai-agents/praisonaiagents/rag/models.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class RetrievalConfig">RetrievalConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/retrieval_config.py">from_dict</a>(data: Dict[str, Any]) -> 'RetrievalConfig'</code>
+* <code title="class RetrievalConfig">RetrievalConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/retrieval_config.py">get_strategy</a>(corpus_stats = None)</code>
+* <code title="class RetrievalConfig">RetrievalConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/retrieval_config.py">get_token_budget</a>(model_name: Optional[str] = None)</code>
+* <code title="class RetrievalConfig">RetrievalConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/retrieval_config.py">should_retrieve</a>(query: str, force: bool = False, skip: bool = False) -> bool</code>
+* <code title="class RetrievalConfig">RetrievalConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/retrieval_config.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class RetrievalConfig">RetrievalConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/retrieval_config.py">to_knowledge_config</a>() -> Dict[str, Any]</code>
+* <code title="class RetrievalConfig">RetrievalConfig.<a href="./src/praisonai-agents/praisonaiagents/rag/retrieval_config.py">to_rag_config</a>() -> Dict[str, Any]</code>
+
+# Handoff
+
+Types:
+```python
+from praisonaiagents import Handoff, RECOMMENDED_PROMPT_PREFIX, handoff, handoff_filters, prompt_with_handoff_instructions
+```
+
+Methods:
+
+* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">default_tool_description</a>() -> str</code>
+* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">default_tool_name</a>() -> str</code>
+* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">execute_async</a>(source_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None) -> HandoffResult</code>
+* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">execute_programmatic</a>(source_agent: 'Agent', prompt: str, context: Optional[Dict[str, Any]] = None) -> HandoffResult</code>
+* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">to_tool_function</a>(source_agent: 'Agent') -> Callable</code>
+* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_description</a>() -> str</code>
+* <code title="class Handoff">Handoff.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">tool_name</a>() -> str</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">handoff</a>(agent: 'Agent', tool_name_override: Optional[str] = None, tool_description_override: Optional[str] = None, on_handoff: Optional[Callable] = None, input_type: Optional[type] = None, input_filter: Optional[Callable[[HandoffInputData], HandoffInputData]] = None, config: Optional[HandoffConfig] = None, context_policy: Optional[str] = None, timeout_seconds: Optional[float] = None, max_concurrent: Optional[int] = None, detect_cycles: Optional[bool] = None, max_depth: Optional[int] = None) -> Handoff</code>
+* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">keep_last_n_messages</a>(n: int) -> Callable[[HandoffInputData], HandoffInputData]</code>
+* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">remove_all_tools</a>(data: HandoffInputData) -> HandoffInputData</code>
+* <code title="class handoff_filters">handoff_filters.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">remove_system_messages</a>(data: HandoffInputData) -> HandoffInputData</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/agent/handoff.py">prompt_with_handoff_instructions</a>(base_prompt: str, agent: 'Agent') -> str</code>
+
+# Guardrails
+
+Types:
+```python
+from praisonaiagents import GuardrailAction, GuardrailConfig, LLMGuardrail
+```
+
+Methods:
+
+* <code title="class GuardrailConfig">GuardrailConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class LLMGuardrail">LLMGuardrail.<a href="./src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py">__call__</a>(task_output: TaskOutput) -> Tuple[bool, Union[str, TaskOutput]]</code>
+
+# Planning
+
+Types:
+```python
+from praisonaiagents import ApprovalCallback, Plan, PlanStep, PlanStorage, PlanningConfig, READ_ONLY_TOOLS, RESTRICTED_TOOLS, TodoItem, TodoList
+```
+
+Methods:
+
+* <code title="class ApprovalCallback">ApprovalCallback.<a href="./src/praisonai-agents/praisonaiagents/planning/approval.py">__call__</a>(plan: 'Plan') -> bool</code>
+* <code title="class ApprovalCallback">ApprovalCallback.<a href="./src/praisonai-agents/praisonaiagents/planning/approval.py">always_approve</a>(plan: 'Plan') -> bool</code>
+* <code title="class ApprovalCallback">ApprovalCallback.<a href="./src/praisonai-agents/praisonaiagents/planning/approval.py">always_reject</a>(plan: 'Plan') -> bool</code>
+* <code title="class ApprovalCallback">ApprovalCallback.<a href="./src/praisonai-agents/praisonaiagents/planning/approval.py">approve_if_no_dangerous_tools</a>(plan: 'Plan') -> bool</code>
+* <code title="class ApprovalCallback">ApprovalCallback.<a href="./src/praisonai-agents/praisonaiagents/planning/approval.py">approve_if_small</a>(plan: 'Plan', max_steps: int = 5) -> bool</code>
+* <code title="class ApprovalCallback">ApprovalCallback.<a href="./src/praisonai-agents/praisonaiagents/planning/approval.py">async_call</a>(plan: 'Plan') -> bool</code>
+* <code title="class ApprovalCallback">ApprovalCallback.<a href="./src/praisonai-agents/praisonaiagents/planning/approval.py">console_approval</a>(plan: 'Plan') -> bool</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">add_step</a>(step: PlanStep) -> None</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">approve</a>() -> None</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">cancel</a>() -> None</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">complete</a>() -> None</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">completed_step_ids</a>() -> List[str]</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">from_dict</a>(data: Dict[str, Any]) -> 'Plan'</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">from_markdown</a>(markdown: str) -> 'Plan'</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">get_next_steps</a>() -> List[PlanStep]</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">get_step</a>(step_id: str) -> Optional[PlanStep]</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">is_complete</a>() -> bool</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">progress</a>() -> float</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">remove_step</a>(step_id: str) -> bool</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">start_execution</a>() -> None</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">to_markdown</a>() -> str</code>
+* <code title="class Plan">Plan.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">update_step_status</a>(step_id: str, status: str) -> bool</code>
+* <code title="class PlanStep">PlanStep.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">from_dict</a>(data: Dict[str, Any]) -> 'PlanStep'</code>
+* <code title="class PlanStep">PlanStep.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">is_ready</a>(completed_steps: List[str]) -> bool</code>
+* <code title="class PlanStep">PlanStep.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">mark_complete</a>() -> None</code>
+* <code title="class PlanStep">PlanStep.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">mark_in_progress</a>() -> None</code>
+* <code title="class PlanStep">PlanStep.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">mark_skipped</a>() -> None</code>
+* <code title="class PlanStep">PlanStep.<a href="./src/praisonai-agents/praisonaiagents/planning/plan.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">cleanup_old_plans</a>(keep_count: int = 10) -> int</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">delete_plan</a>(plan_id: str) -> bool</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">delete_todo</a>(name: str) -> bool</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">get_latest_plan</a>() -> Optional[Plan]</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">list_plans</a>() -> List[Dict[str, Any]]</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">list_todos</a>() -> List[str]</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">load_plan</a>(plan_id: str) -> Optional[Plan]</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">load_plan_from_file</a>(path: str) -> Optional[Plan]</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">load_todo</a>(name: str = 'current') -> Optional[TodoList]</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">save_plan</a>(plan: Plan, filename: Optional[str] = None) -> str</code>
+* <code title="class PlanStorage">PlanStorage.<a href="./src/praisonai-agents/praisonaiagents/planning/storage.py">save_todo</a>(todo: TodoList, name: str = 'current') -> str</code>
+* <code title="class PlanningConfig">PlanningConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class TodoItem">TodoItem.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">complete</a>() -> None</code>
+* <code title="class TodoItem">TodoItem.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">from_dict</a>(data: Dict[str, Any]) -> 'TodoItem'</code>
+* <code title="class TodoItem">TodoItem.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">is_ready</a>(completed_ids: List[str]) -> bool</code>
+* <code title="class TodoItem">TodoItem.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">reset</a>() -> None</code>
+* <code title="class TodoItem">TodoItem.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">start</a>() -> None</code>
+* <code title="class TodoItem">TodoItem.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">add</a>(item: Union[TodoItem, str]) -> TodoItem</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">complete</a>(item_id: str) -> bool</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">completed</a>() -> List[TodoItem]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">completed_ids</a>() -> List[str]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">from_dict</a>(data: Dict[str, Any]) -> 'TodoList'</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">from_json</a>(json_str: str) -> 'TodoList'</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">from_markdown</a>(markdown: str) -> 'TodoList'</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">from_plan</a>(plan: 'Plan') -> 'TodoList'</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">get</a>(item_id: str) -> Optional[TodoItem]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">get_ready_items</a>() -> List[TodoItem]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">in_progress</a>() -> List[TodoItem]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">is_complete</a>() -> bool</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">pending</a>() -> List[TodoItem]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">progress</a>() -> float</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">remove</a>(item_id: str) -> bool</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">start</a>(item_id: str) -> bool</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">sync_with_plan</a>(plan: 'Plan') -> None</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">to_json</a>() -> str</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">to_markdown</a>() -> str</code>
+* <code title="class TodoList">TodoList.<a href="./src/praisonai-agents/praisonaiagents/planning/todo.py">update_from_plan</a>(plan: 'Plan') -> None</code>
+
+# Skills
+
+Types:
+```python
+from praisonaiagents import SkillLoader, SkillManager, SkillMetadata, SkillProperties, SkillsConfig
+```
+
+Methods:
+
+* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">activate</a>(skill: LoadedSkill) -> bool</code>
+* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load</a>(skill_path: str, activate: bool = False) -> Optional[LoadedSkill]</code>
+* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_all_resources</a>(skill: LoadedSkill) -> None</code>
+* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_assets</a>(skill: LoadedSkill) -> dict</code>
+* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_metadata</a>(skill_path: str) -> Optional[LoadedSkill]</code>
+* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_references</a>(skill: LoadedSkill) -> dict</code>
+* <code title="class SkillLoader">SkillLoader.<a href="./src/praisonai-agents/praisonaiagents/skills/loader.py">load_scripts</a>(skill: LoadedSkill) -> dict</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate</a>(skill: LoadedSkill) -> bool</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">activate_by_name</a>(name: str) -> bool</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">add_skill</a>(skill_path: str) -> Optional[LoadedSkill]</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">clear</a>() -> None</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">discover</a>(skill_dirs: Optional[List[str]] = None, include_defaults: bool = True) -> int</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_available_skills</a>() -> List[SkillMetadata]</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_instructions</a>(name: str) -> Optional[str]</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">get_skill</a>(name: str) -> Optional[LoadedSkill]</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">load_resources</a>(name: str) -> bool</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skill_names</a>() -> List[str]</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">skills</a>() -> List[LoadedSkill]</code>
+* <code title="class SkillManager">SkillManager.<a href="./src/praisonai-agents/praisonaiagents/skills/manager.py">to_prompt</a>() -> str</code>
+* <code title="class SkillMetadata">SkillMetadata.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">from_properties</a>(props: SkillProperties) -> 'SkillMetadata'</code>
+* <code title="class SkillProperties">SkillProperties.<a href="./src/praisonai-agents/praisonaiagents/skills/models.py">to_dict</a>() -> dict</code>
+* <code title="class SkillsConfig">SkillsConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+
+# Session
+
+Types:
+```python
+from praisonaiagents import Session
+```
+
+Methods:
+
+* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">Agent</a>(name: str, role: str = 'Assistant', instructions: Optional[str] = None, tools: Optional[List[Any]] = None, memory: bool = True, knowledge: Optional[List[str]] = None, **kwargs) -> 'Agent'</code>
+* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">add_knowledge</a>(source: str) -> None</code>
+* <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">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">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>
+* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">save_state</a>(state_data: Dict[str, Any]) -> None</code>
+* <code title="class Session">Session.<a href="./src/praisonai-agents/praisonaiagents/session/api.py">search_knowledge</a>(query: str, limit: int = 5) -> List[Dict[str, Any]]</code>
+* <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>
+
+# MCP
+
+Types:
+```python
+from praisonaiagents import MCP
+```
+
+Methods:
+
+* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">get_tools</a>() -> List[Callable]</code>
+* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">shutdown</a>()</code>
+* <code title="class MCP">MCP.<a href="./src/praisonai-agents/praisonaiagents/mcp/mcp.py">to_openai_tool</a>()</code>
+
+# Telemetry
+
+Types:
+```python
+from praisonaiagents import MinimalTelemetry, TelemetryCollector, cleanup_telemetry_resources, disable_performance_mode, disable_telemetry, enable_performance_mode, enable_telemetry, get_telemetry
+```
+
+Methods:
+
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">flush</a>()</code>
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">get_metrics</a>() -> Dict[str, Any]</code>
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">shutdown</a>()</code>
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">track_agent_execution</a>(agent_name: str = None, success: bool = True, async_mode: bool = False)</code>
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">track_error</a>(error_type: str = None)</code>
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">track_feature_usage</a>(feature_name: str)</code>
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">track_task_completion</a>(task_name: str = None, success: bool = True)</code>
+* <code title="class MinimalTelemetry">MinimalTelemetry.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">track_tool_usage</a>(tool_name: str, success: bool = True, execution_time: float = None)</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">get_metrics</a>() -> Dict[str, Any]</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">record_cost</a>(cost: float, model: str = None)</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">record_tokens</a>(prompt_tokens: int, completion_tokens: int, model: str = None)</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">start</a>()</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">stop</a>()</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">trace_agent_execution</a>(agent_name: str, **attributes)</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">trace_llm_call</a>(model: str = None, **attributes)</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">trace_task_execution</a>(task_name: str, agent_name: str = None, **attributes)</code>
+* <code title="class TelemetryCollector">TelemetryCollector.<a href="./src/praisonai-agents/praisonaiagents/telemetry/telemetry.py">trace_tool_call</a>(tool_name: str, **attributes)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/telemetry/__init__.py">cleanup_telemetry_resources</a>()</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/telemetry/__init__.py">disable_performance_mode</a>()</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/telemetry/__init__.py">disable_telemetry</a>()</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/telemetry/__init__.py">enable_performance_mode</a>()</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/telemetry/__init__.py">enable_telemetry</a>()</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/telemetry/__init__.py">get_telemetry</a>() -> 'MinimalTelemetry'</code>
+
+# Observability
+
+Types:
+```python
+from praisonaiagents import FlowDisplay, obs, track_workflow
+```
+
+Methods:
+
+* <code title="class FlowDisplay">FlowDisplay.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">display</a>()</code>
+* <code title="class FlowDisplay">FlowDisplay.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">start</a>()</code>
+* <code title="class FlowDisplay">FlowDisplay.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">stop</a>()</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/flow_display.py">track_workflow</a>()</code>
+
+# Context
+
+Types:
+```python
+from praisonaiagents import ContextManager, ManagerConfig
+```
+
+Methods:
+
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">capture_llm_boundary</a>(messages: List[Dict[str, Any]], tools: List[Dict[str, Any]]) -> SnapshotHookData</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">emergency_truncate</a>(messages: List[Dict[str, Any]], target_tokens: int) -> List[Dict[str, Any]]</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">estimate_tokens</a>(text: str, validate: bool = False) -> Tuple[int, Optional[EstimationMetrics]]</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_history</a>() -> List[Dict[str, Any]]</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_last_snapshot_hook</a>() -> Optional[SnapshotHookData]</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_resolved_config</a>() -> Dict[str, Any]</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_stats</a>() -> Dict[str, Any]</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">get_tool_budget</a>(tool_name: str) -> int</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">process</a>(messages: List[Dict[str, Any]], system_prompt: str = '', tools: Optional[List[Dict[str, Any]]] = None, trigger: Literal['turn', 'tool_call', 'manual', 'overflow'] = 'turn') -> Dict[str, Any]</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">register_snapshot_callback</a>(callback: Callable[[SnapshotHookData], None]) -> None</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">reset</a>() -> None</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">set_tool_budget</a>(tool_name: str, max_tokens: int, protected: bool = False) -> None</code>
+* <code title="class ContextManager">ContextManager.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">truncate_tool_output</a>(tool_name: str, output: str) -> str</code>
+* <code title="class ManagerConfig">ManagerConfig.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">from_env</a>() -> 'ManagerConfig'</code>
+* <code title="class ManagerConfig">ManagerConfig.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">merge</a>(**overrides) -> 'ManagerConfig'</code>
+* <code title="class ManagerConfig">ManagerConfig.<a href="./src/praisonai-agents/praisonaiagents/context/manager.py">to_dict</a>() -> Dict[str, Any]</code>
+
+# Config
+
+Types:
+```python
+from praisonaiagents import AutonomyConfig, AutonomyLevel, CachingConfig, ExecutionConfig, ExecutionPreset, GuardrailConfig, HooksConfig, KnowledgeConfig, MemoryConfig, MultiAgentExecutionConfig, MultiAgentHooksConfig, MultiAgentMemoryConfig, MultiAgentOutputConfig, MultiAgentPlanningConfig, OutputConfig, OutputPreset, PlanningConfig, ReflectionConfig, SkillsConfig, TemplateConfig, WebConfig, WebSearchProvider
+```
+
+Methods:
+
+* <code title="class AutonomyConfig">AutonomyConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class CachingConfig">CachingConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class ExecutionConfig">ExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class GuardrailConfig">GuardrailConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class HooksConfig">HooksConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class KnowledgeConfig">KnowledgeConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class MemoryConfig">MemoryConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class MultiAgentExecutionConfig">MultiAgentExecutionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class MultiAgentHooksConfig">MultiAgentHooksConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class MultiAgentMemoryConfig">MultiAgentMemoryConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class MultiAgentOutputConfig">MultiAgentOutputConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class MultiAgentPlanningConfig">MultiAgentPlanningConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class OutputConfig">OutputConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class PlanningConfig">PlanningConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class ReflectionConfig">ReflectionConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class SkillsConfig">SkillsConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class TemplateConfig">TemplateConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class WebConfig">WebConfig.<a href="./src/praisonai-agents/praisonaiagents/config/feature_configs.py">to_dict</a>() -> Dict[str, Any]</code>
+
+# Display
+
+Types:
+```python
+from praisonaiagents import async_display_callbacks, clean_triple_backticks, display_error, display_generating, display_instruction, display_interaction, display_self_reflection, display_tool_call, error_logs, register_display_callback, sync_display_callbacks
+```
+
+Methods:
+
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">clean_triple_backticks</a>(text: str) -> str</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_error</a>(message: str, console = None)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_generating</a>(content: str = '', start_time: Optional[float] = None)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_instruction</a>(message: str, console = None, agent_name: str = None, agent_role: str = None, agent_tools: List[str] = None)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_interaction</a>(message, response, markdown = True, generation_time = None, console = None, agent_name = None, agent_role = None, agent_tools = None, task_name = None, task_description = None, task_id = None, metrics = None)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_self_reflection</a>(message: str, console = None)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">display_tool_call</a>(message: str, console = None, tool_name: str = None, tool_input: dict = None, tool_output: str = None, elapsed_time: float = None, success: bool = True)</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/main.py">register_display_callback</a>(display_type: str, callback_fn, is_async: bool = False)</code>
+
+# Utilities
+
+Types:
+```python
+from praisonaiagents import ArrayMode, is_policy_string, parse_policy_string, resolve, resolve_autonomy, resolve_caching, resolve_context, resolve_execution, resolve_guardrail_policies, resolve_guardrails, resolve_hooks, resolve_knowledge, resolve_memory, resolve_output, resolve_planning, resolve_reflection, resolve_routing, resolve_skills, resolve_web
+```
+
+Methods:
+
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/parse_utils.py">is_policy_string</a>(value: str) -> bool</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/parse_utils.py">parse_policy_string</a>(value: str) -> tuple</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve</a>(value: Any, param_name: str, config_class: Optional[Type] = None, presets: Optional[Dict[str, Any]] = None, default: Any = None, instance_check: Optional[Callable[[Any], bool]] = None, url_schemes: Optional[Dict[str, str]] = None, array_mode: Optional[str] = None, string_mode: Optional[str] = None) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_autonomy</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_caching</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_context</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_execution</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_guardrail_policies</a>(policies: list, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_guardrails</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_hooks</a>(value: Any, config_class: Optional[Type] = None) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_knowledge</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_memory</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_output</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_planning</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_reflection</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_routing</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_skills</a>(value: Any, config_class: Type) -> Any</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/config/param_resolver.py">resolve_web</a>(value: Any, config_class: Type) -> Any</code>
+
+# Other
+
+Types:
+```python
+from praisonaiagents import AgentAppConfig, AgentAppProtocol, AgentFlow, AgentManager, AgentOSConfig, AgentOSProtocol, AgentTeam, EmbeddingResult, aembedding, aembeddings, embedding, embeddings, get_dimensions
+```
+
+Methods:
+
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">arun</a>(input: str = '', llm: Optional[str] = None, verbose: bool = False) -> Dict[str, Any]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">astart</a>(input: str = '', llm: Optional[str] = None, verbose: bool = False) -> Dict[str, Any]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">from_template</a>(uri: str, config: Optional[Dict[str, Any]] = None, offline: bool = False, **kwargs) -> 'Workflow'</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">get_history</a>() -> List[Dict[str, Any]]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">memory_config</a>() -> Optional[Dict[str, Any]]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_step_complete</a>() -> Optional[Callable]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_step_error</a>() -> Optional[Callable]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_step_start</a>() -> Optional[Callable]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_workflow_complete</a>() -> Optional[Callable]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">on_workflow_start</a>() -> Optional[Callable]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">planning_llm</a>() -> Optional[str]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">reasoning</a>() -> bool</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">run</a>(input: str = '', llm: Optional[str] = None, verbose: bool = False, stream: bool = None) -> Dict[str, Any]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">start</a>(input: str = '', **kwargs) -> Dict[str, Any]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">stream</a>() -> bool</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">to_dict</a>() -> Dict[str, Any]</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>() -> bool</code>
+* <code title="class AgentFlow">AgentFlow.<a href="./src/praisonai-agents/praisonaiagents/workflows/workflows.py">verbose</a>(value: bool)</code>
+* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">get_app</a>() -> Any</code>
+* <code title="class AgentOSProtocol">AgentOSProtocol.<a href="./src/praisonai-agents/praisonaiagents/app/protocols.py">serve</a>(host: Optional[str] = None, port: Optional[int] = None, reload: bool = False, **kwargs: Any) -> None</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">add_task</a>(task)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">aexecute_task</a>(task_id)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">append_to_state</a>(key: str, value: Any, max_length: Optional[int] = None) -> List[Any]</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_all_tasks</a>()</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">arun_task</a>(task_id)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">astart</a>(content = None, return_dict = False, **kwargs)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clean_json_output</a>(output: str) -> str</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">clear_state</a>() -> None</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">context_manager</a>()</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">current_plan</a>()</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">default_completion_checker</a>(task, agent_output)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">delete_state</a>(key: str) -> bool</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">display_token_usage</a>()</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">execute_task</a>(task_id)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_agent_details</a>(agent_name)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_state</a>() -> Dict[str, Any]</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_all_tasks_status</a>()</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_detailed_token_report</a>() -> Dict[str, Any]</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_plan_markdown</a>() -> str</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_state</a>(key: str, default: Any = None) -> Any</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_details</a>(task_id)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_result</a>(task_id)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_task_status</a>(task_id)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_todo_markdown</a>() -> str</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">get_token_usage_summary</a>() -> Dict[str, Any]</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">has_state</a>(key: str) -> bool</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">increment_state</a>(key: str, amount: float = 1, default: float = 0) -> float</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">launch</a>(path: str = '/agents', port: int = 8000, host: str = '0.0.0.0', debug: bool = False, protocol: str = 'http')</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">restore_session_state</a>(session_id: str) -> bool</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run</a>(content = None, return_dict = False, **kwargs)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_all_tasks</a>()</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">run_task</a>(task_id)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_output_to_file</a>(task, task_output)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">save_session_state</a>(session_id: str, include_memory: bool = True) -> None</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">set_state</a>(key: str, value: Any) -> None</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">start</a>(content = None, return_dict = False, output = None, **kwargs)</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">todo_list</a>()</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_plan_step_status</a>(step_id: str, status: str) -> bool</code>
+* <code title="class AgentTeam">AgentTeam.<a href="./src/praisonai-agents/praisonaiagents/agents/agents.py">update_state</a>(updates: Dict) -> None</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembedding</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">aembeddings</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">embedding</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/embed.py">embeddings</a>(input: Union[str, List[str]], model: str = 'text-embedding-3-small', dimensions: Optional[int] = None, encoding_format: str = 'float', timeout: float = 600.0, api_key: Optional[str] = None, api_base: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs) -> EmbeddingResult</code>
+* <code title="function">praisonaiagents.<a href="./src/praisonai-agents/praisonaiagents/embedding/dimensions.py">get_dimensions</a>(model_name: str) -> int</code>

 # Wrapper (praisonai)

 Types:
 ```python
-from praisonai import CloudProvider, Deploy, DeployConfig, DeployType, PraisonAI, __version__, embedding
+from praisonai import AgentApp, AgentOS, CloudProvider, Deploy, DeployConfig, DeployType, PraisonAI, __version__
 ```

 # CLI
@@ -153,6 +754,7 @@ Methods:
 * <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 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>
@@ -166,6 +768,19 @@ Methods:
 * <code title="cli">praisonai benchmark profile <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
 * <code title="cli">praisonai benchmark sdk <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
 * <code title="cli">praisonai benchmark workflow <a href="./src/praisonai/praisonai/cli/commands/benchmark.py">--help</a></code>
+* <code title="cli">praisonai bot bot-callback <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai bot discord <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai bot slack <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai bot telegram <a href="./src/praisonai/praisonai/cli/commands/bot.py">--help</a></code>
+* <code title="cli">praisonai browser browser-callback <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser click <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser navigate <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser open <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser profiles <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser screenshot <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser snapshot <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser status <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
+* <code title="cli">praisonai browser type <a href="./src/praisonai/praisonai/cli/commands/browser.py">--help</a></code>
 * <code title="cli">praisonai call call-main <a href="./src/praisonai/praisonai/cli/commands/call.py">--help</a></code>
 * <code title="cli">praisonai chat <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
 * <code title="cli">praisonai chat chat-main <a href="./src/praisonai/praisonai/cli/commands/chat.py">--help</a></code>
@@ -226,6 +841,8 @@ Methods:
 * <code title="cli">praisonai environment doctor <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
 * <code title="cli">praisonai environment view <a href="./src/praisonai/praisonai/cli/commands/environment.py">--help</a></code>
 * <code title="cli">praisonai eval accuracy <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
+* <code title="cli">praisonai eval judge <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
+* <code title="cli">praisonai eval list-judges <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
 * <code title="cli">praisonai eval performance <a href="./src/praisonai/praisonai/cli/commands/eval.py">--help</a></code>
 * <code title="cli">praisonai examples info <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
 * <code title="cli">praisonai examples list <a href="./src/praisonai/praisonai/cli/commands/examples.py">--help</a></code>
@@ -240,14 +857,18 @@ Methods:
 * <code title="cli">praisonai knowledge index <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
 * <code title="cli">praisonai knowledge list <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
 * <code title="cli">praisonai knowledge search <a href="./src/praisonai/praisonai/cli/commands/knowledge.py">--help</a></code>
+* <code title="cli">praisonai loop help <a href="./src/praisonai/praisonai/cli/commands/loop.py">--help</a></code>
+* <code title="cli">praisonai loop loop-main <a href="./src/praisonai/praisonai/cli/commands/loop.py">--help</a></code>
 * <code title="cli">praisonai lsp logs <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
 * <code title="cli">praisonai lsp lsp-callback <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
 * <code title="cli">praisonai lsp start <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
 * <code title="cli">praisonai lsp status <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
 * <code title="cli">praisonai lsp stop <a href="./src/praisonai/praisonai/cli/commands/lsp.py">--help</a></code>
 * <code title="cli">praisonai mcp add <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp auth <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
 * <code title="cli">praisonai mcp describe <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
 * <code title="cli">praisonai mcp list <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
+* <code title="cli">praisonai mcp logout <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
 * <code title="cli">praisonai mcp mcp-callback <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
 * <code title="cli">praisonai mcp remove <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
 * <code title="cli">praisonai mcp run <a href="./src/praisonai/praisonai/cli/commands/mcp.py">--help</a></code>
@@ -263,6 +884,16 @@ Methods:
 * <code title="cli">praisonai package install <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
 * <code title="cli">praisonai package list <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
 * <code title="cli">praisonai package uninstall <a href="./src/praisonai/praisonai/cli/commands/package.py">--help</a></code>
+* <code title="cli">praisonai plugins create <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins disable <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins discover <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins doctor <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins enable <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins info <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins install <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins list <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins plugins-callback <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
+* <code title="cli">praisonai plugins remove <a href="./src/praisonai/praisonai/cli/commands/plugins.py">--help</a></code>
 * <code title="cli">praisonai profile imports <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
 * <code title="cli">praisonai profile optimize <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
 * <code title="cli">praisonai profile profile-callback <a href="./src/praisonai/praisonai/cli/commands/profile.py">--help</a></code>
@@ -276,11 +907,24 @@ Methods:
 * <code title="cli">praisonai rag query <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
 * <code title="cli">praisonai rag serve <a href="./src/praisonai/praisonai/cli/commands/rag.py">--help</a></code>
 * <code title="cli">praisonai realtime realtime-main <a href="./src/praisonai/praisonai/cli/commands/realtime.py">--help</a></code>
+* <code title="cli">praisonai recipe apply <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe create <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe info <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
 * <code title="cli">praisonai recipe install <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe judge <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
 * <code title="cli">praisonai recipe list <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe optimize <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
 * <code title="cli">praisonai recipe run <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
+* <code title="cli">praisonai recipe serve <a href="./src/praisonai/praisonai/cli/commands/recipe.py">--help</a></code>
 * <code title="cli">praisonai registry list <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
 * <code title="cli">praisonai registry serve <a href="./src/praisonai/praisonai/cli/commands/registry.py">--help</a></code>
+* <code title="cli">praisonai replay cleanup <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay context <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay dashboard <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay delete <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay flow <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay list <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
+* <code title="cli">praisonai replay show <a href="./src/praisonai/praisonai/cli/commands/replay.py">--help</a></code>
 * <code title="cli">praisonai research research-main <a href="./src/praisonai/praisonai/cli/commands/research.py">--help</a></code>
 * <code title="cli">praisonai retrieval index <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
 * <code title="cli">praisonai retrieval query <a href="./src/praisonai/praisonai/cli/commands/retrieval.py">--help</a></code>
@@ -290,6 +934,11 @@ Methods:
 * <code title="cli">praisonai rules list <a href="./src/praisonai/praisonai/cli/commands/rules.py">--help</a></code>
 * <code title="cli">praisonai run <a href="./src/praisonai/praisonai/cli/main.py">--help</a></code>
 * <code title="cli">praisonai run run-main <a href="./src/praisonai/praisonai/cli/commands/run.py">--help</a></code>
+* <code title="cli">praisonai sandbox explain <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox list <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox recreate <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox sandbox-callback <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
+* <code title="cli">praisonai sandbox status <a href="./src/praisonai/praisonai/cli/commands/sandbox.py">--help</a></code>
 * <code title="cli">praisonai schedule delete <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
 * <code title="cli">praisonai schedule describe <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
 * <code title="cli">praisonai schedule list <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
@@ -299,17 +948,33 @@ Methods:
 * <code title="cli">praisonai schedule start <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
 * <code title="cli">praisonai schedule stats <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
 * <code title="cli">praisonai schedule stop <a href="./src/praisonai/praisonai/cli/commands/schedule.py">--help</a></code>
+* <code title="cli">praisonai serve a2a <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve a2u <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve acp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve agents <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve docs <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve gateway <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve lsp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve mcp <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve rag <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve recipe <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve registry <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve scheduler <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
 * <code title="cli">praisonai serve serve-callback <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
 * <code title="cli">praisonai serve start <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
 * <code title="cli">praisonai serve status <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
 * <code title="cli">praisonai serve stop <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve ui <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
+* <code title="cli">praisonai serve unified <a href="./src/praisonai/praisonai/cli/commands/serve.py">--help</a></code>
 * <code title="cli">praisonai session delete <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
 * <code title="cli">praisonai session export <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
 * <code title="cli">praisonai session import <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
 * <code title="cli">praisonai session list <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
 * <code title="cli">praisonai session resume <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
 * <code title="cli">praisonai session show <a href="./src/praisonai/praisonai/cli/commands/session.py">--help</a></code>
+* <code title="cli">praisonai skills check <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
 * <code title="cli">praisonai skills create <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
+* <code title="cli">praisonai skills eligible <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
 * <code title="cli">praisonai skills info <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
 * <code title="cli">praisonai skills install <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
 * <code title="cli">praisonai skills list <a href="./src/praisonai/praisonai/cli/commands/skills.py">--help</a></code>
@@ -330,11 +995,16 @@ Methods:
 * <code title="cli">praisonai tools info <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
 * <code title="cli">praisonai tools list <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
 * <code title="cli">praisonai tools test <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
+* <code title="cli">praisonai tools validate <a href="./src/praisonai/praisonai/cli/commands/tools.py">--help</a></code>
 * <code title="cli">praisonai traces disable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
 * <code title="cli">praisonai traces enable <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
 * <code title="cli">praisonai traces list <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
 * <code title="cli">praisonai traces status <a href="./src/praisonai/praisonai/cli/commands/traces.py">--help</a></code>
-* <code title="cli">praisonai train train-main <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train agents <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train list <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train llm <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train show <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
+* <code title="cli">praisonai train train-callback <a href="./src/praisonai/praisonai/cli/commands/train.py">--help</a></code>
 * <code title="cli">praisonai ui chat <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
 * <code title="cli">praisonai ui code <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
 * <code title="cli">praisonai ui gradio <a href="./src/praisonai/praisonai/cli/commands/ui.py">--help</a></code>
@@ -351,8 +1021,8 @@ Methods:

 Types/Exports:
 ```ts
-export { Agent, Agents, PraisonAIAgents, Router } from "./agent";
-export type { PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig } from "./agent";
+export { Agent, AgentTeam, Agents, PraisonAIAgents, Router } from "./agent";
+export type { AgentTeamConfig, PraisonAIAgentsConfig, SimpleAgentConfig, SimpleRouteConfig, SimpleRouterConfig } from "./agent";
 export { AudioAgent, createAudioAgent } from "./agent/audio";
 export type { AudioAgentConfig, AudioProvider, AudioSpeakOptions, AudioSpeakResult, AudioTranscribeOptions, AudioTranscribeResult } from "./agent/audio";
 export { ContextAgent, createContextAgent } from "./agent/context";
@@ -377,7 +1047,7 @@ export { // Agent loop
  ApprovalManager, // Tools
  defineTool, // UI Message (AI SDK v6 parity)
  convertToModelMessages, AIAgentStep, AIEmbedManyResult, AIEmbedOptions, AIEmbedResult, AIFilePart, AIGenerateImageOptions, AIGenerateImageResult, AIGenerateObjectOptions, AIGenerateObjectResult, AIGenerateTextOptions, AIGenerateTextResult, AIImagePart, AIMiddleware, AIMiddlewareConfig, AIModelMessage, AISpan, AISpanKind, AISpanOptions, AISpanStatus, AIStreamObjectOptions, AIStreamObjectResult, AIStreamTextOptions, AIStreamTextResult, AITelemetryEvent, AITelemetrySettings, AITextPart, AIToolDefinition, AITracer, AgentLoop, DANGEROUS_PATTERNS, MCPClientType, MODEL_ALIASES, SPEECH_MODELS, TRANSCRIPTION_MODELS, ToolApprovalDeniedError, ToolApprovalTimeoutError, aiEmbed, aiEmbedMany, aiGenerateImage, aiGenerateObject, aiGenerateText, aiStreamObject, aiStreamText, applyMiddleware, autoEnableDevTools, base64ToUint8Array, clearAICache, clearEvents, closeAllMCPClients, closeMCPClient, convertToUIMessages, createAILoggingMiddleware, createAISpan, createApprovalResponse, createDangerousPatternChecker, createDevToolsMiddleware, createExpressHandler, createFastifyHandler, createFilePart, createHonoHandler, createMultimodalMessage, createNestHandler, createPagesHandler, createPdfPart, createSystemMessage, createTelemetryMiddleware, createTelemetrySettings, createTextMessage, createTextPart, createToolSet, disableAITelemetry, disableDevTools, enableAITelemetry, functionToTool, getAICacheStats, getApprovalManager, getDevToolsState, getDevToolsUrl, getEvents, getMCPClient, getModel, getTelemetrySettings, getToolsNeedingApproval, getTracer, hasModelAlias, hasPendingApprovals, initOpenTelemetry, isDangerous, isDataUrl, isDevToolsEnabled, isTelemetryEnabled, isUrl, listModelAliases, mcpToolsToAITools, parseModel, pipeUIMessageStreamToResponse, recordEvent, resolveModelAlias, safeValidateUIMessages, setApprovalManager, stopAfterSteps, stopWhen, stopWhenNoToolCalls, toMessageContent, toUIMessageStreamResponse, transcribe, uint8ArrayToBase64, validateUIMessages, withApproval, withSpan, wrapModel } from "./ai";
-export { AutoAgents, createAutoAgents } from "./auto";
+export { AutoAgents, AutoTaskConfig, createAutoAgents } from "./auto";
 export { BaseCache, FileCache, MemoryCache, createFileCache, createMemoryCache } from "./cache";
 export { CLI_SPEC_VERSION, executeCommand, parseArgs } from "./cli";
 export { // Autonomy Mode
@@ -400,7 +1070,8 @@ export type { DbAdapter, DbConfig, DbMessage, DbRun, DbTrace } from "./db";
 export { MemoryPostgresAdapter, NeonPostgresAdapter, PostgresSessionStorage, createMemoryPostgres, createNeonPostgres, createPostgresSessionStorage } from "./db/postgres";
 export { MemoryRedisAdapter, UpstashRedisAdapter, createMemoryRedis, createUpstashRedis } from "./db/redis";
 export { SQLiteAdapter, createSQLiteAdapter } from "./db/sqlite";
-export { EvalResults, EvalSuite, Evaluator, accuracyEval, containsKeywordsCriterion, createDefaultEvaluator, createEvalResults, createEvaluator, lengthCriterion, noHarmfulContentCriterion, performanceEval, relevanceCriterion, reliabilityEval } from "./eval";
+export { // LLM-as-Judge
+  Judge, AccuracyJudge, CriteriaJudge, EvalResults, EvalSuite, Evaluator, RecipeJudge, accuracyEval, addJudge, addOptimizationRule, containsKeywordsCriterion, createDefaultEvaluator, createEvalResults, createEvaluator, getJudge, getOptimizationRule, lengthCriterion, listJudges, listOptimizationRules, noHarmfulContentCriterion, parseJudgeResponse, performanceEval, relevanceCriterion, reliabilityEval, removeJudge, removeOptimizationRule } from "./eval";
 export { AgentEventBus, AgentEvents, EventEmitterPubSub, PubSub, createEventBus, createPubSub } from "./events";
 export { LLMGuardrail, createLLMGuardrail } from "./guardrails/llm-guardrail";
 export { DisplayTypes, HooksManager, WorkflowHooksExecutor, clearAllCallbacks, clearApprovalCallback, createHooksManager, createLoggingOperationHooks, createLoggingWorkflowHooks, createTimingWorkflowHooks, createValidationOperationHooks, createWorkflowHooks, executeCallback, executeSyncCallback, getRegisteredDisplayTypes, hasApprovalCallback, registerApprovalCallback, registerDisplayCallback, requestApproval, unregisterDisplayCallback } from "./hooks";
@@ -434,6 +1105,8 @@ export { // Adapters
  OBSERVABILITY_TOOLS, // Global adapter management
  setObservabilityAdapter, // Types
  type SpanKind, ConsoleObservabilityAdapter, MemoryObservabilityAdapter, clearAdapterCache, createConsoleAdapter, createMemoryAdapter, createObservabilityAdapter, getObservabilityAdapter, getObservabilityToolInfo, hasObservabilityToolEnvVar, listObservabilityTools, noopAdapter, resetObservabilityAdapter, trace } from "./observability";
+export { AgentApp, AgentAppConfig, AgentAppProtocol, AgentOS, AgentOSConfig, AgentOSProtocol, DEFAULT_AGENTOS_CONFIG, mergeConfig } from "./os";
+export type { AgentAppOptions, AgentOSOptions } from "./os";
 export { Plan, PlanStep, PlanStorage, PlanningAgent, TaskAgent, TodoItem, TodoList, createPlan, createPlanStorage, createPlanningAgent, createTaskAgent, createTodoList } from "./planning";
 export { SkillManager, createSkillManager, parseSkillFile } from "./skills";
 export { AgentTelemetry, PerformanceMonitor, TelemetryCollector, TelemetryIntegration, cleanupTelemetry, createAgentTelemetry, createConsoleSink, createHTTPSink, createPerformanceMonitor, createTelemetryIntegration, disableTelemetry, enableTelemetry, getTelemetry } from "./telemetry";
@@ -444,9 +1117,9 @@ export { MissingDependencyError, MissingEnvVarError, ToolsRegistry, composeMiddl
 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 { // New: Python-parity Loop and Repeat classes
-  Loop, // WorkflowStep class
-  WorkflowStep, Repeat, Workflow, loop, loopPattern, parallel, repeat, repeatPattern, route } from "./workflows";
-export type { LoopConfig, LoopResult, RepeatConfig, RepeatContext, RepeatResult, StepContextConfig, StepExecutionConfig, StepOutputConfig, StepResult, StepRoutingConfig, WorkflowContext, WorkflowStepConfig } from "./workflows";
+  Loop, // Task class
+  Task, AgentFlow, Pipeline, Repeat, Workflow, loop, loopPattern, parallel, repeat, repeatPattern, route } from "./workflows";
+export type { LoopConfig, LoopResult, RepeatConfig, RepeatContext, RepeatResult, StepContextConfig, StepExecutionConfig, StepOutputConfig, StepResult, StepRoutingConfig, TaskConfig, WorkflowContext } from "./workflows";
 export { createWorkflowFromYAML, loadWorkflowFromFile, parseYAMLWorkflow, validateWorkflowDefinition } from "./workflows/yaml-parser";
 ```

@@ -13,6 +13,12 @@ GOOGLE_API_KEY=your_google_api_key_here
 GROQ_API_KEY=your_groq_api_key_here
 COHERE_API_KEY=your_cohere_api_key_here

+# Bot Tokens (for messaging bot services)
+SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
+SLACK_APP_TOKEN=xapp-your-slack-app-token
+DISCORD_BOT_TOKEN=your-discord-bot-token
+TELEGRAM_BOT_TOKEN=your-telegram-bot-token
+
 # Optional: Service Configuration
 FLASK_ENV=development
 CHAINLIT_HOST=0.0.0.0
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    praisonai_tools \
-    "praisonai>=3.9.28" \
+    "praisonai>=4.2.2" \
    "praisonai[chat]" \
    "embedchain[github,youtube]"

@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    praisonai_tools \
-    "praisonai>=3.9.28" \
+    "praisonai>=4.2.2" \
    "praisonai[ui]" \
    "praisonai[chat]" \
    "praisonai[realtime]" \
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    praisonai_tools \
-    "praisonai>=3.9.28" \
+    "praisonai>=4.2.2" \
    "praisonai[ui]" \
    "praisonai[crewai]"

@@ -0,0 +1,15 @@
+# Bot Environment Variables
+# Copy to .env and fill in your values
+
+# Required: LLM API Key
+OPENAI_API_KEY=your_openai_api_key_here
+
+# Slack Bot (Socket Mode)
+SLACK_BOT_TOKEN=xoxb-your-slack-bot-token
+SLACK_APP_TOKEN=xapp-your-slack-app-token
+
+# Discord Bot
+DISCORD_BOT_TOKEN=your-discord-bot-token
+
+# Telegram Bot
+TELEGRAM_BOT_TOKEN=your-telegram-bot-token
@@ -0,0 +1,42 @@
+# Dockerfile for PraisonAI Slack Bot
+# Secrets are passed at runtime via environment variables
+
+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    gcc \
+    python3-dev \
+    curl \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create praison config directory
+RUN mkdir -p /root/.praison
+
+# Install praisonai with bot dependencies
+RUN pip install --no-cache-dir \
+    praisonai \
+    slack-bolt \
+    slack-sdk \
+    "discord.py>=2.0.0" \
+    "python-telegram-bot>=20.0"
+
+# Set environment variables for directory management
+ENV PRAISON_CONFIG_DIR=/root/.praison
+ENV DOCKER_CONTAINER=true
+
+# Bot tokens should be passed at runtime (not baked into image)
+# SLACK_BOT_TOKEN=xoxb-...
+# SLACK_APP_TOKEN=xapp-...
+
+# Optional: Copy custom agent configuration
+# COPY agent.yaml /app/agent.yaml
+
+# Expose no ports - Socket Mode doesn't need them
+# For webhook mode, expose port 3000
+
+# Default command - tokens from environment
+CMD ["praisonai", "bot", "slack"]
@@ -0,0 +1,66 @@
+# PraisonAI Bot Docker Deployment
+
+Deploy Slack, Discord, or Telegram bots using Docker.
+
+## Quick Start
+
+```bash
+# 1. Copy environment template
+cp .env.template .env
+
+# 2. Edit .env with your tokens
+nano .env
+
+# 3. Run specific bot
+docker compose up slack-bot -d
+
+# Or run all bots
+docker compose up -d
+```
+
+## Environment Variables
+
+| Variable | Required | Description |
+|----------|----------|-------------|
+| `OPENAI_API_KEY` | Yes | LLM API key |
+| `SLACK_BOT_TOKEN` | For Slack | Bot token (xoxb-...) |
+| `SLACK_APP_TOKEN` | For Slack | App token (xapp-...) |
+| `DISCORD_BOT_TOKEN` | For Discord | Bot token |
+| `TELEGRAM_BOT_TOKEN` | For Telegram | Bot token |
+
+## Slack Setup
+
+1. Create app at https://api.slack.com/apps
+2. Enable **Socket Mode** → Generate App-Level Token with `connections:write`
+3. Add **OAuth Scopes**: `chat:write`, `app_mentions:read`, `im:history`
+4. Enable **Event Subscriptions** → Subscribe to `app_mention`, `message.im`
+5. **Install to Workspace**
+6. Copy Bot Token and App Token to `.env`
+
+## Commands
+
+```bash
+# Start Slack bot
+docker compose up slack-bot -d
+
+# View logs
+docker compose logs -f slack-bot
+
+# Stop bot
+docker compose down slack-bot
+
+# Rebuild after updates
+docker compose build --no-cache slack-bot
+```
+
+## Custom Agent Configuration
+
+Mount your agent config:
+
+```yaml
+services:
+  slack-bot:
+    volumes:
+      - ./agent.yaml:/app/agent.yaml
+    command: ["praisonai", "bot", "slack", "--agent", "/app/agent.yaml"]
+```
@@ -0,0 +1,53 @@
+version: '3.8'
+
+# PraisonAI Bot Services
+# Run specific bots: docker compose up slack-bot
+# Run all bots: docker compose up
+
+services:
+  # Slack Bot
+  slack-bot:
+    build:
+      context: ../..
+      dockerfile: docker/bots/Dockerfile
+    volumes:
+      - praison_data:/root/.praison
+    environment:
+      OPENAI_API_KEY: ${OPENAI_API_KEY}
+      SLACK_BOT_TOKEN: ${SLACK_BOT_TOKEN}
+      SLACK_APP_TOKEN: ${SLACK_APP_TOKEN}
+      PRAISON_CONFIG_DIR: /root/.praison
+    command: [ "praisonai", "bot", "slack" ]
+    restart: unless-stopped
+
+  # Discord Bot
+  discord-bot:
+    build:
+      context: ../..
+      dockerfile: docker/bots/Dockerfile
+    volumes:
+      - praison_data:/root/.praison
+    environment:
+      OPENAI_API_KEY: ${OPENAI_API_KEY}
+      DISCORD_BOT_TOKEN: ${DISCORD_BOT_TOKEN}
+      PRAISON_CONFIG_DIR: /root/.praison
+    command: [ "praisonai", "bot", "discord" ]
+    restart: unless-stopped
+
+  # Telegram Bot
+  telegram-bot:
+    build:
+      context: ../..
+      dockerfile: docker/bots/Dockerfile
+    volumes:
+      - praison_data:/root/.praison
+    environment:
+      OPENAI_API_KEY: ${OPENAI_API_KEY}
+      TELEGRAM_BOT_TOKEN: ${TELEGRAM_BOT_TOKEN}
+      PRAISON_CONFIG_DIR: /root/.praison
+    command: [ "praisonai", "bot", "telegram" ]
+    restart: unless-stopped
+
+volumes:
+  praison_data:
+    driver: local
@@ -22,7 +22,7 @@ services:
      CHAINLIT_DB_DIR: /root/.praison
    command: praisonai ui --host 0.0.0.0
    healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:8082"]
+      test: [ "CMD", "curl", "-f", "http://localhost:8082" ]
      interval: 10s
      timeout: 5s
      retries: 3
@@ -49,7 +49,7 @@ services:
      CHAINLIT_DB_DIR: /root/.praison
    command: praisonai chat --host 0.0.0.0 --port 8083
    healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:8083"]
+      test: [ "CMD", "curl", "-f", "http://localhost:8083" ]
      interval: 10s
      timeout: 5s
      retries: 3
@@ -69,7 +69,7 @@ services:
      OPENAI_API_KEY: ${OPENAI_API_KEY}
      PRAISON_CONFIG_DIR: /root/.praison
    healthcheck:
-      test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
+      test: [ "CMD", "curl", "-f", "http://localhost:8080/health" ]
      interval: 10s
      timeout: 5s
      retries: 3
@@ -89,6 +89,7 @@ services:
      PRAISON_CONFIG_DIR: /root/.praison
    networks:
      - praison_network
+  # For bot services (Slack, Discord, Telegram), see docker/bots/

 volumes:
  praison_data:
@@ -96,4 +97,4 @@ volumes:

 networks:
  praison_network:
-    driver: bridge
+    driver: bridge
@@ -1,30 +1,30 @@
 """Advanced Workflow with all consolidated params configured."""
 from praisonaiagents import Agent
-from praisonaiagents.workflows import Workflow, WorkflowStep
+from praisonaiagents import AgentFlow, Task
 from praisonaiagents.workflows.workflow_configs import (
    WorkflowOutputConfig, WorkflowPlanningConfig, WorkflowMemoryConfig,
 )

 # Full-featured workflow with all consolidated params
-workflow = Workflow(
+workflow = AgentFlow(
    name="FullFeaturedWorkflow",
    description="Demonstrates all agent-like consolidated params",
    steps=[
-        WorkflowStep(
+        Task(
            name="researcher",
            action="Research: {{input}}",
            agent=Agent(instructions="You are a researcher."),
            knowledge=["research_docs/"],  # Step-specific knowledge
            web="duckduckgo",  # Use DuckDuckGo for this step
        ),
-        WorkflowStep(
+        Task(
            name="analyzer",
            action="Analyze the research",
            agent=Agent(instructions="You are an analyst."),
            reflection="thorough",  # Thorough reflection for analysis
            guardrails="strict",  # Strict validation
        ),
-        WorkflowStep(
+        Task(
            name="writer",
            action="Write the final report",
            agent=Agent(instructions="You are a writer."),
@@ -1,12 +1,12 @@
 """Basic Agents (multi-agent) example with consolidated params."""
-from praisonaiagents import Agent, Agents
+from praisonaiagents import Agent, AgentTeam

 # Create agents
 writer = Agent(instructions="You write content.")
 editor = Agent(instructions="You edit content.")

 # Multi-agent with consolidated params
-agents = Agents(
+agents = AgentTeam(
    agents=[writer, editor],
    memory=True,
    planning=True,
@@ -1,21 +1,24 @@
-"""
-Basic Memory Example - Agent-Centric API
-
-Demonstrates the simplest memory usage with consolidated params.
-"""
-
+"""Basic memory example - minimal usage."""
 from praisonaiagents import Agent

-# Basic: Enable memory with preset
+# Simple enable (uses default file-based memory)
 agent = Agent(
    instructions="You are a helpful assistant with memory.",
-    memory="sqlite",  # Preset: sqlite, redis, postgres, file
+    memory=True,
 )

-# Run a simple task
-response = agent.start("Remember that my favorite color is blue.")
-print(response)
+# With preset
+agent_redis = Agent(
+    instructions="You are a helpful assistant.",
+    memory="redis",  # Uses redis preset
+)

-# Follow-up to test memory
-response = agent.start("What is my favorite color?")
-print(response)
+# With URL
+agent_postgres = Agent(
+    instructions="You are a helpful assistant.",
+    memory="postgresql://localhost/mydb",  # URL auto-detected
+)
+
+if __name__ == "__main__":
+    response = agent.chat("Remember that my favorite color is blue.")
+    print(response)
@@ -1,18 +1,18 @@
 """Basic example showing step-level override of workflow defaults."""
 from praisonaiagents import Agent
-from praisonaiagents.workflows import Workflow, WorkflowStep
+from praisonaiagents import AgentFlow, Task

 # Workflow with defaults
-workflow = Workflow(
+workflow = AgentFlow(
    name="StepOverrideWorkflow",
    steps=[
-        WorkflowStep(
+        Task(
            name="step1",
            action="Process with workflow defaults",
            agent=Agent(instructions="You are a processor."),
            # Uses workflow-level web=True (inherited)
        ),
-        WorkflowStep(
+        Task(
            name="step2",
            action="Process with step override",
            agent=Agent(instructions="You are a processor."),
@@ -1,26 +1,22 @@
-"""
-Basic Workflow Example - Agent-Centric API
-
-Demonstrates minimal workflow with consolidated params.
-"""
-
+"""Basic workflow example with consolidated params."""
 from praisonaiagents import Agent
-from praisonaiagents.workflows import Workflow, WorkflowStep
+from praisonaiagents import AgentFlow, Task

-# Create a simple workflow
-workflow = Workflow(
-    name="simple_workflow",
-    output="verbose",  # Workflow-level output preset
+# Create agents
+writer = Agent(instructions="You are a content writer.")
+editor = Agent(instructions="You are an editor.")
+
+# Create workflow with consolidated params
+workflow = AgentFlow(
+    name="Content Pipeline",
+    steps=[
+        Task(name="write", agent=writer, action="Write about {{topic}}"),
+        Task(name="edit", agent=editor, action="Edit the content", context=["write"]),
+    ],
+    output="verbose",
+    planning=True,
 )

-# Add a step
-step = WorkflowStep(
-    name="writer",
-    action="Write a haiku about programming",
-    agent=Agent(instructions="You are a creative poet."),
-    output="result.txt",  # Save output to file
-)
-
-# Note: This is a structural example - actual execution requires workflow.run()
-print("Workflow created with output preset:", workflow.output)
-print("Step output file:", step.output_file)
+if __name__ == "__main__":
+    result = workflow.run(variables={"topic": "AI agents"})
+    print(result)
@@ -1,17 +1,17 @@
 """Basic Workflow with Agent-like consolidated params."""
 from praisonaiagents import Agent
-from praisonaiagents.workflows import Workflow, WorkflowStep
+from praisonaiagents import AgentFlow, Task

 # Workflow with agent-like params (knowledge, web, guardrails, reflection)
-workflow = Workflow(
+workflow = AgentFlow(
    name="AgentLikeWorkflow",
    steps=[
-        WorkflowStep(
+        Task(
            name="researcher",
            action="Research the topic: {{input}}",
            agent=Agent(instructions="You are a researcher."),
        ),
-        WorkflowStep(
+        Task(
            name="writer",
            action="Write about the research findings",
            agent=Agent(instructions="You are a writer."),
@@ -189,8 +189,8 @@ def main():
    print("-" * 40)
    print("Auto-agents mode default: context=False (zero overhead)")
    print("To enable for multi-agent workflows:")
-    print("    from praisonaiagents import Agents")
-    print("    agents = Agents(agents=[...], context=True)")
+    print("    from praisonaiagents import AgentTeam")
+    print("    agents = AgentTeam(agents=[...], context=True)")
    print("")
    print("Recommended config for long tasks:")
    print("    context=ManagerConfig(")
@@ -6,10 +6,10 @@ Demonstrates how to use multi-agent context with Agents via context= param,
 and also shows low-level MultiAgentLedger usage for advanced scenarios.

 Agent-Centric Quick Start:
-    from praisonaiagents import Agent, Agents
+    from praisonaiagents import Agent, AgentTeam
    from praisonaiagents.context import ManagerConfig
    
-    agents = Agents(
+    agents = AgentTeam(
        agents=[agent1, agent2],
        context=ManagerConfig(policy="isolated"),  # or "shared"
    )
@@ -17,7 +17,7 @@ Agent-Centric Quick Start:

 import os
 import tempfile
-from praisonaiagents import Agent, Agents
+from praisonaiagents import Agent, AgentTeam
 from praisonaiagents.context import (
    ManagerConfig,
    MultiAgentLedger,
@@ -49,7 +49,7 @@ def agent_centric_example():
    # Multi-agent setup with isolated context policy
    # (each agent maintains its own context)
    print("Created agents with context=True")
-    print("Use Agents(agents=[...], context=ManagerConfig(policy='isolated'))")
+    print("Use AgentTeam(agents=[...], context=ManagerConfig(policy='isolated'))")
    print("for multi-agent context isolation")


@@ -156,7 +156,7 @@ def example_5_multi_agent():
    print("Example 5: Multi-Agent Context Management")
    print("=" * 60)
    
-    from praisonaiagents import Agents, Task
+    from praisonaiagents import AgentTeam, Task
    
    config = ManagerConfig(
        auto_compact=True,
@@ -181,7 +181,7 @@ def example_5_multi_agent():
    task2 = Task(description="Write a summary", agent=writer)
    
    # Create multi-agent system with context management
-    agents = Agents(
+    agents = AgentTeam(
        agents=[researcher, writer],
        tasks=[task1, task2],
        context=config,  # Shared context config
@@ -0,0 +1,145 @@
+"""
+Agent-centric Embedding Example
+
+This example shows how to use embeddings with PraisonAI Agents.
+Embeddings are used internally by Agent for:
+- Knowledge retrieval (RAG)
+- Memory storage and search
+- Semantic similarity
+
+You can also use the embedding API directly for custom use cases.
+"""
+
+from praisonaiagents import Agent, embedding
+
+# =============================================================================
+# Example 1: Direct Embedding API
+# =============================================================================
+
+def example_direct_embedding():
+    """Use the embedding API directly."""
+    
+    # Single text embedding
+    result = embedding("Hello, world!")
+    print(f"Single embedding: {len(result.embeddings[0])} dimensions")
+    
+    # Batch embedding
+    texts = ["AI agents are powerful", "Machine learning is fascinating"]
+    result = embedding(texts, model="text-embedding-3-small")
+    print(f"Batch embeddings: {len(result.embeddings)} vectors")
+    
+    # Custom dimensions (for models that support it)
+    result = embedding("Hello", model="text-embedding-3-large", dimensions=256)
+    print(f"Custom dimensions: {len(result.embeddings[0])} dimensions")
+    
+    return result
+
+
+# =============================================================================
+# Example 2: Agent with Knowledge (uses embeddings internally)
+# =============================================================================
+
+def example_agent_with_knowledge():
+    """Agent with knowledge uses embeddings for RAG."""
+    
+    agent = Agent(
+        instructions="You are a helpful assistant with knowledge about AI.",
+        knowledge=["AI agents can use tools to accomplish tasks."],
+        knowledge_config={
+            "embedder": {
+                "provider": "openai",
+                "config": {"model": "text-embedding-3-small"}
+            }
+        }
+    )
+    
+    # The agent uses embeddings internally for knowledge retrieval
+    response = agent.chat("What can AI agents do?")
+    print(f"Agent response: {response}")
+    
+    return agent
+
+
+# =============================================================================
+# Example 3: Agent with Memory (uses embeddings internally)
+# =============================================================================
+
+def example_agent_with_memory():
+    """Agent with memory uses embeddings for semantic search."""
+    
+    agent = Agent(
+        instructions="You are a helpful assistant that remembers conversations.",
+        memory=True,
+        memory_config={
+            "embedding_model": "text-embedding-3-small"
+        }
+    )
+    
+    # The agent uses embeddings internally for memory storage/retrieval
+    agent.chat("My name is Alice and I love Python programming.")
+    response = agent.chat("What do I love?")
+    print(f"Agent remembered: {response}")
+    
+    return agent
+
+
+# =============================================================================
+# Example 4: Custom Embedding for Similarity Search
+# =============================================================================
+
+def example_similarity_search():
+    """Use embeddings for custom similarity search."""
+    import math
+    
+    def cosine_similarity(a, b):
+        dot = sum(x * y for x, y in zip(a, b))
+        norm_a = math.sqrt(sum(x * x for x in a))
+        norm_b = math.sqrt(sum(x * x for x in b))
+        return dot / (norm_a * norm_b) if norm_a and norm_b else 0
+    
+    # Embed documents
+    documents = [
+        "Python is a programming language",
+        "JavaScript runs in browsers",
+        "AI agents can automate tasks"
+    ]
+    doc_embeddings = embedding(documents)
+    
+    # Embed query
+    query = "What language is used for web development?"
+    query_embedding = embedding(query)
+    
+    # Find most similar document
+    similarities = [
+        cosine_similarity(query_embedding.embeddings[0], doc_emb)
+        for doc_emb in doc_embeddings.embeddings
+    ]
+    
+    best_idx = similarities.index(max(similarities))
+    print(f"Most similar document: {documents[best_idx]}")
+    print(f"Similarity score: {similarities[best_idx]:.4f}")
+    
+    return similarities
+
+
+if __name__ == "__main__":
+    print("=" * 60)
+    print("Example 1: Direct Embedding API")
+    print("=" * 60)
+    example_direct_embedding()
+    
+    print("\n" + "=" * 60)
+    print("Example 4: Custom Similarity Search")
+    print("=" * 60)
+    example_similarity_search()
+    
+    # Uncomment to run agent examples (requires API key)
+    # print("\n" + "=" * 60)
+    # print("Example 2: Agent with Knowledge")
+    # print("=" * 60)
+    # example_agent_with_knowledge()
+    
+    # print("\n" + "=" * 60)
+    # print("Example 3: Agent with Memory")
+    # print("=" * 60)
+    # example_agent_with_memory()
@@ -4,7 +4,7 @@ Fixed example demonstrating proper guardrail usage with PraisonAI Agents.
 This addresses the issues reported in issue #875.
 """

-from praisonaiagents import Agent, Task, GuardrailResult, Agents, TaskOutput
+from praisonaiagents import Agent, Task, GuardrailResult, AgentTeam, TaskOutput
 from typing import Tuple, Any
 import trafilatura

@@ -103,7 +103,7 @@ task_with_llm_guardrail = Task(

 # Run with GuardrailResult example
 print("=== Running with GuardrailResult guardrail ===")
-agents_gr = Agents(
+agents_gr = AgentTeam(
    agents=[agent],
    tasks=[task_with_guardrailresult]
 )
@@ -113,7 +113,7 @@ agents_gr = Agents(

 # Run with Tuple example
 print("\n=== Running with Tuple[bool, Any] guardrail ===")
-agents_tuple = Agents(
+agents_tuple = AgentTeam(
    agents=[agent],
    tasks=[task_with_tuple]
 )
@@ -123,7 +123,7 @@ agents_tuple = Agents(

 # Run with LLM guardrail example
 print("\n=== Running with LLM-based guardrail ===")
-agents_llm = Agents(
+agents_llm = AgentTeam(
    agents=[agent],
    tasks=[task_with_llm_guardrail]
 )
@@ -2,32 +2,34 @@
 """
 Basic Hooks Example for PraisonAI Agents.

-This example demonstrates how to use the hooks system to:
+This example demonstrates the simplified hook API using add_hook():
 1. Log tool calls before execution
 2. Block dangerous operations
 3. Add context to agent responses
 4. Monitor session lifecycle

+For the simplest example, see simple_hooks.py
+
 Usage:
    python basic_hooks.py
 """

 import asyncio
-from praisonaiagents import Agent
 from praisonaiagents.hooks import (
-    HookRegistry, HookRunner, HookEvent, HookResult,
+    add_hook, remove_hook, has_hook, get_default_registry,
+    HookRunner, HookEvent, HookResult,
    BeforeToolInput, AfterToolInput
 )


 def main():
-    # Create a hook registry
-    registry = HookRegistry()
+    # Clear any existing hooks from previous runs
+    get_default_registry().clear()
    
    # ==========================================================================
-    # Hook 1: Log all tool calls
+    # Hook 1: Log all tool calls (using string event name)
    # ==========================================================================
-    @registry.on(HookEvent.BEFORE_TOOL)
+    @add_hook('before_tool')
    def log_tool_calls(event_data: BeforeToolInput) -> HookResult:
        """Log every tool call before execution."""
        print(f"\n📝 [LOG] Tool: {event_data.tool_name}")
@@ -35,9 +37,9 @@ def main():
        return HookResult.allow()
    
    # ==========================================================================
-    # Hook 2: Block dangerous file operations (using function logic)
+    # Hook 2: Block dangerous file operations
    # ==========================================================================
-    @registry.on(HookEvent.BEFORE_TOOL)
+    @add_hook('before_tool')
    def block_delete_operations(event_data: BeforeToolInput) -> HookResult:
        """Block any delete or remove operations."""
        dangerous_keywords = ['delete', 'remove', 'rm', 'unlink']
@@ -53,7 +55,7 @@ def main():
    # ==========================================================================
    # Hook 3: Require confirmation for write operations
    # ==========================================================================
-    @registry.on(HookEvent.BEFORE_TOOL)
+    @add_hook('before_tool')
    def confirm_write_operations(event_data: BeforeToolInput) -> HookResult:
        """Request confirmation for write operations."""
        write_keywords = ['write', 'save', 'create', 'update']
@@ -62,14 +64,13 @@ def main():
        if any(kw in tool_lower for kw in write_keywords):
            print(f"\n⚠️  [CONFIRM] Write operation: {event_data.tool_name}")
            # In a real scenario, you might prompt the user here
-            # For this example, we'll auto-approve
            return HookResult.allow("Auto-approved for demo")
        return HookResult.allow()
    
    # ==========================================================================
    # Hook 4: Add timing information after tool execution
    # ==========================================================================
-    @registry.on(HookEvent.AFTER_TOOL)
+    @add_hook('after_tool')
    def log_tool_completion(event_data: AfterToolInput) -> HookResult:
        """Log tool completion with timing."""
        print(f"\n✅ [DONE] Tool: {event_data.tool_name}")
@@ -82,10 +83,14 @@ def main():
    # Test the hooks
    # ==========================================================================
    print("=" * 60)
-    print("Testing Hooks System")
+    print("Testing Hooks System (using add_hook API)")
    print("=" * 60)
    
-    runner = HookRunner(registry)
+    # Check hooks are registered
+    print(f"\nHooks registered for 'before_tool': {has_hook('before_tool')}")
+    print(f"Hooks registered for 'after_tool': {has_hook('after_tool')}")
+    
+    runner = HookRunner(get_default_registry())
    
    # Test 1: Normal tool call (should be logged and allowed)
    print("\n--- Test 1: Normal read operation ---")
@@ -132,7 +137,7 @@ def main():
    print("\n" + "=" * 60)
    print("Registered Hooks:")
    print("=" * 60)
-    for event, hooks in registry.list_hooks().items():
+    for event, hooks in get_default_registry().list_hooks().items():
        print(f"\n{event}:")
        for hook in hooks:
            print(f"  - {hook['name']} (matcher: {hook['matcher'] or '*'})")
@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+"""
+Simple Hooks Example for PraisonAI Agents.
+
+This example shows the SIMPLEST way to use hooks with the add_hook API.
+Just a few lines of code to intercept tool calls!
+
+No need to import HookResult - just return None/True to allow, 
+False to deny, or a string to deny with a reason.
+
+Usage:
+    python simple_hooks.py
+"""
+
+from praisonaiagents.hooks import add_hook, has_hook
+
+
+# =============================================================================
+# Register hooks with simple string event names
+# =============================================================================
+
+@add_hook('before_tool')
+def log_tools(event_data):
+    """Log every tool call. Return nothing (None) to allow."""
+    print(f"🔧 Tool: {event_data.tool_name}")
+    # No return needed - defaults to allow
+
+
+@add_hook('before_tool')
+def block_dangerous(event_data):
+    """Block delete operations. Return False or string to deny."""
+    if 'delete' in event_data.tool_name.lower():
+        print(f"🚫 Blocked: {event_data.tool_name}")
+        return "Delete operations are not allowed"  # String = deny with reason
+    # No return = allow
+
+
+@add_hook('after_tool')
+def log_completion(event_data):
+    """Log tool completion."""
+    print(f"✅ Done: {event_data.tool_name} ({event_data.execution_time_ms:.0f}ms)")
+
+
+# =============================================================================
+# Test the hooks
+# =============================================================================
+
+if __name__ == "__main__":
+    print("=" * 50)
+    print("Simple Hooks Example")
+    print("=" * 50)
+    
+    # Check hooks are registered
+    print(f"\nHooks registered for 'before_tool': {has_hook('before_tool')}")
+    print(f"Hooks registered for 'after_tool': {has_hook('after_tool')}")
+    
+    # You can now create an Agent and the hooks will be applied
+    print("\n💡 Hooks are now globally registered!")
+    print("   Any Agent will automatically use these hooks.")
+    print("\n   Example:")
+    print("   from praisonaiagents import Agent")
+    print("   agent = Agent(instructions='You are helpful')")
+    print("   agent.start('Help me with files')")
+    print("\n📝 Hook returns:")
+    print("   - None or True  → Allow the operation")
+    print("   - False         → Deny the operation")
+    print("   - 'reason'      → Deny with a custom message")
@@ -14,7 +14,7 @@ Usage:

 from praisonai_tools.observability import obs
 from praisonai_tools.observability.base import SpanKind
-from praisonaiagents import Agent, Agents
+from praisonaiagents import Agent, AgentTeam

 # Initialize observability
 obs.init()
@@ -13,7 +13,7 @@ Features demonstrated:

 import sys
 sys.path.insert(0, '/Users/praison/praisonai-package/src/praisonai-agents')
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam


 def get_weather(city: str) -> str:
@@ -106,7 +106,7 @@ def example_multi_agent():
        agent=writer
    )
    
-    agents = Agents(
+    agents = AgentTeam(
        agents=[researcher, writer],
        tasks=[task1, task2],
        process="sequential",
@@ -5,7 +5,7 @@ This example demonstrates hierarchical agent patterns using PraisonAI
 for structured task delegation and coordinated workflows.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import internet_search

 print("=== AutoAgents Hierarchical Generation Example ===\n")
@@ -54,7 +54,7 @@ execution_task = Task(
 )

 # Run hierarchical workflow
-agents_system = Agents(
+agents_system = AgentTeam(
    agents=[manager_agent, research_agent],
    tasks=[planning_task, execution_task],
    process="sequential", output="verbose"
@@ -5,7 +5,7 @@ This example demonstrates a comprehensive code agent that can write, analyze, de
 It includes self-reflection for improving code quality and multiple specialized tools.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import CodeInterpreter

 # Initialize code execution tool
@@ -84,7 +84,7 @@ def demonstrate_code_agent():
    )
    
    # Create workflow
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[code_writer, code_reviewer, code_executor],
        tasks=[write_task, review_task, execute_task],
        process="sequential", output="verbose"
@@ -4,7 +4,7 @@ from praisonaiagents.tools import duckduckgo
 agent = Agent(instructions="You are a Image Analysis Agent", tools=[duckduckgo])
 agent.start("I want to go London next week, find me a good hotel and flight")

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Create Image Analysis Agent
 image_agent = Agent(
@@ -36,7 +36,7 @@ task2 = Task(
 )

 # Create Agents instance
-agents = Agents(
+agents = AgentTeam(
    agents=[image_agent],
    tasks=[task1, task2],
    process="sequential",
@@ -4,7 +4,7 @@ from praisonaiagents.tools import duckduckgo
 agent = Agent(instructions="You are a Image Analysis Agent", tools=[duckduckgo])
 agent.start("I want to go London next week, find me a good hotel and flight")

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Create Image Analysis Agent
 image_agent = Agent(
@@ -36,7 +36,7 @@ task2 = Task(
 )

 # Create Agents instance
-agents = Agents(
+agents = AgentTeam(
    agents=[image_agent],
    tasks=[task1, task2],
    process="sequential",
@@ -5,7 +5,7 @@ This example demonstrates a mathematical problem-solving agent that can handle v
 including calculations, equation solving, and step-by-step explanations.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from typing import Dict, Any
 import math
 import re
@@ -123,7 +123,7 @@ def solve_math_problem_workflow():
        context=[solve_task]
    )
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[problem_solver_agent, calculation_agent, math_tutor_agent],
        tasks=[understand_task, solve_task, verify_task],
        process="sequential", output="verbose"
@@ -6,7 +6,7 @@ agent-based selection for cost optimization and performance.
 """

 import os
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.agent import RouterAgent
 from praisonaiagents.llm.model_router import ModelRouter, ModelProfile, TaskComplexity

@@ -48,7 +48,7 @@ def example_auto_routing():
    )
    
    # Run the tasks
-    agents = Agents(
+    agents = AgentTeam(
        agents=[research_agent],
        tasks=[simple_task, moderate_task, complex_task],
        process="sequential", output="verbose"
@@ -113,7 +113,7 @@ def example_cost_optimized_workflow():
    )
    
    # Run workflow
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[analyzer, writer],
        tasks=[analysis_task, writing_task],
        process="sequential", output="verbose"
@@ -135,7 +135,7 @@ def example_auto_agents_multi_provider():
    from praisonaiagents.agents import AutoAgents
    
    # Create AutoAgents that will automatically assign appropriate models
-    auto_agents = AutoAgents(
+    auto_agents = AutoAgentTeam(
        instructions="Create a market research report on electric vehicles. Include data analysis, competitor analysis, and future projections.",
        max_agents=3,
        llm="gpt-4o-mini",  # Default model for agent generation
@@ -239,7 +239,7 @@ def example_custom_routing():
    ]
    
    # Run tasks
-    agents = Agents(
+    agents = AgentTeam(
        agents=[coder],
        tasks=tasks,
        process="sequential", output="verbose"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Create Video Analysis Agent
 video_agent = Agent(
@@ -25,7 +25,7 @@ task1 = Task(
 )

 # Create Agents instance
-agents = Agents(
+agents = AgentTeam(
    agents=[video_agent],
    tasks=[task1],
    process="sequential",
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language

 agent = Agent(
@@ -1,6 +1,6 @@
-from praisonaiagents import Agent, Agents, Tools
+from praisonaiagents import Agent, AgentTeam, Tools

 research_agent = Agent(name="Research", instructions="You are a research agent to search internet about AI 2024", tools=[Tools.internet_search])
 summarise_agent = Agent(name="Summarise", instructions="You are a summarize agent to summarise in points")
-agents = Agents(agents=[research_agent, summarise_agent])
+agents = AgentTeam(agents=[research_agent, summarise_agent])
 agents.launch(path="/agents", port=3030)
@@ -1,8 +1,8 @@
-from praisonaiagents import Agent, Agents, Tools
+from praisonaiagents import Agent, AgentTeam, Tools

 research_agent = Agent(name="Research", instructions="You are a research agent to search internet about AI 2024", tools=[Tools.internet_search])
 summarise_agent = Agent(name="Summarise", instructions="You are a summarize agent to summarise in points")
-agents = Agents(agents=[research_agent, summarise_agent])
-agents2 = Agents(agents=[research_agent])
+agents = AgentTeam(agents=[research_agent, summarise_agent])
+agents2 = AgentTeam(agents=[research_agent])
 agents.launch(path="/agents", port=3030)
 agents2.launch(path="/agents2", port=3030)
@@ -32,7 +32,7 @@ import os
 from pathlib import Path

 # Import our market research system
-from praisonaiagents import Agent, Task, Agents, Tools
+from praisonaiagents import Agent, Task, AgentTeam, Tools

 # Create FastAPI app
 app = FastAPI(
@@ -260,7 +260,7 @@ async def generate_market_research_report(job_id: str, config: MarketResearchCon
        job_status[job_id]["message"] = "Setting up research workflow..."
        
        # Create workflow
-        workflow = Agents(
+        workflow = AgentTeam(
            agents=list(agents.values()),
            tasks=tasks,
            process="sequential", output="minimal"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Agents
+from praisonaiagents import Agent, AgentTeam
 from duckduckgo_search import DDGS

 def internet_search_tool(query: str):
@@ -15,5 +15,5 @@ def internet_search_tool(query: str):
 agent = Agent(name="SearchAgent", instructions="You Search the internet for information", tools=[internet_search_tool])
 agent2 = Agent(name="SummariseAgent", instructions="You Summarise the information")

-agents = Agents(name="MultiAgents", agents=[agent, agent2])
+agents = AgentTeam(name="MultiAgents", agents=[agent, agent2])
 agents.launch(port=8080, protocol="mcp")
@@ -0,0 +1,76 @@
+"""
+Messaging Bot Example - Deploy Agents to Telegram, Discord, Slack
+
+This example demonstrates how to configure bots for different
+messaging platforms.
+"""
+
+import os
+from praisonaiagents import Agent, BotConfig
+
+# Telegram Bot Configuration
+telegram_config = BotConfig(
+    token=os.environ.get("TELEGRAM_BOT_TOKEN", ""),
+    command_prefix="/",
+    mention_required=True,
+    typing_indicator=True,
+    max_message_length=4096,
+    metadata={"platform": "telegram"}
+)
+
+# Discord Bot Configuration
+discord_config = BotConfig(
+    token=os.environ.get("DISCORD_BOT_TOKEN", ""),
+    command_prefix="!",
+    mention_required=True,
+    typing_indicator=True,
+    metadata={
+        "platform": "discord",
+        "guild_ids": []  # Add your guild IDs here
+    }
+)
+
+# Slack Bot Configuration
+slack_config = BotConfig(
+    token=os.environ.get("SLACK_BOT_TOKEN", ""),
+    command_prefix="/",
+    mention_required=True,
+    typing_indicator=True,
+    metadata={
+        "platform": "slack",
+        "app_token": os.environ.get("SLACK_APP_TOKEN", "")
+    }
+)
+
+# Create the agent that will handle messages
+assistant = Agent(
+    name="assistant",
+    instructions="""You are a helpful assistant that responds to messages 
+    from users on messaging platforms. Be friendly and concise.""",
+    llm="gpt-4o-mini"
+)
+
+if __name__ == "__main__":
+    print("Bot Configurations:")
+    print()
+    
+    print("Telegram Config:")
+    print(f"  Token configured: {bool(telegram_config.token)}")
+    print(f"  Command prefix: {telegram_config.command_prefix}")
+    print(f"  Mention required: {telegram_config.mention_required}")
+    print()
+    
+    print("Discord Config:")
+    print(f"  Token configured: {bool(discord_config.token)}")
+    print(f"  Command prefix: {discord_config.command_prefix}")
+    print()
+    
+    print("Slack Config:")
+    print(f"  Token configured: {bool(slack_config.token)}")
+    print(f"  Command prefix: {slack_config.command_prefix}")
+    print()
+    
+    print("To start a bot, use the CLI:")
+    print("  praisonai bot telegram --token $TELEGRAM_BOT_TOKEN")
+    print("  praisonai bot discord --token $DISCORD_BOT_TOKEN")
+    print("  praisonai bot slack --token $SLACK_BOT_TOKEN")
@@ -16,7 +16,7 @@ Environment Variables:

 import cv2
 import os
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam


 def capture_and_analyze():
@@ -58,7 +58,7 @@ def capture_and_analyze():
            )
            
            # Run analysis
-            agents = Agents(
+            agents = AgentTeam(
                agents=[vision_agent],
                tasks=[task],
                process="sequential",
@@ -18,7 +18,7 @@ import cv2
 import time
 import os
 from datetime import datetime
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam


 class ContinuousCameraMonitor:
@@ -71,7 +71,7 @@ class ContinuousCameraMonitor:
            images=[image_path]
        )
        
-        agents = Agents(
+        agents = AgentTeam(
            agents=[self.vision_agent],
            tasks=[task],
            process="sequential",
@@ -17,7 +17,7 @@ Environment Variables:
 import cv2
 import os
 from datetime import datetime
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam


 def capture_camera_frame(camera_id=0):
@@ -114,7 +114,7 @@ def analyze_with_multiple_agents():
    )
    
    # Run multi-agent analysis
-    agents = Agents(
+    agents = AgentTeam(
        agents=[security_agent, object_detector, scene_analyst],
        tasks=[security_task, object_task, scene_task],
        process="parallel",  # Run all analyses in parallel
@@ -18,7 +18,7 @@ import cv2
 import os
 import time
 from datetime import datetime
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam


 class CameraVideoAnalyzer:
@@ -131,7 +131,7 @@ class CameraVideoAnalyzer:
            images=[video_path]  # PraisonAI supports video files in images parameter
        )
        
-        agents = Agents(
+        agents = AgentTeam(
            agents=[self.video_agent],
            tasks=[task],
            process="sequential",
@@ -24,7 +24,7 @@ from pathlib import Path
 project_root = Path(__file__).parent.parent.parent.parent / "src" / "praisonai-agents"
 sys.path.insert(0, str(project_root))

-from praisonaiagents import Agent, Task, Agents, create_context_agent
+from praisonaiagents import Agent, Task, AgentTeam, create_context_agent

 class ContextEngineeringWorkflow:
    """
@@ -302,7 +302,7 @@ class ContextEngineeringWorkflow:
        print("\n⚙️ Executing Context Engineering Workflow")
        print("-" * 50)
        
-        agents_workflow = Agents(
+        agents_workflow = AgentTeam(
            agents=[
                self.product_manager,
                self.architect, 
@@ -11,7 +11,7 @@ Author: Generated for GitHub Issue #23
 """

 import os
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import read_csv, write_csv

 def create_sample_urls_csv():
@@ -81,7 +81,7 @@ def method_1_simple_loop():
    )
    
    # Initialize the agents system
-    agents = Agents(
+    agents = AgentTeam(
        agents=[loop_agent],
        tasks=[loop_task],
        process="workflow",
@@ -145,7 +145,7 @@ def method_2_manual_csv():
    )
    
    # Initialize and run
-    agents = Agents(
+    agents = AgentTeam(
        agents=[csv_agent],
        tasks=[csv_task],
        process="sequential"
@@ -211,7 +211,7 @@ def method_3_url_processing():
    )
    
    # Initialize and run
-    agents = Agents(
+    agents = AgentTeam(
        agents=[url_agent],
        tasks=[url_task],
        process="sequential"
@@ -319,7 +319,7 @@ def method_4_advanced_processing():
    )
    
    # Initialize and run with sequential processing
-    agents = Agents(
+    agents = AgentTeam(
        agents=[validator_agent, processor_agent],
        tasks=[validation_task, processing_task],
        process="sequential"  # Validation must complete before processing
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 import logging
 import os

@@ -35,7 +35,7 @@ knowledge_task = Task(
 )

 # Create and start the agents
-agents = Agents(
+agents = AgentTeam(
    agents=[knowledge_agent],
    tasks=[knowledge_task],
    process="sequential",
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Define the configuration for the Knowledge instance
 config = {
@@ -29,7 +29,7 @@ rag_task = Task(
 )

 # Build Agents
-agents = Agents(
+agents = AgentTeam(
    agents=[rag_agent],
    tasks=[rag_task],
    user_id="user1"
@@ -8,7 +8,7 @@ This example demonstrates how to extract and utilize reasoning patterns in Prais
 - Decision rationale extraction
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from typing import Dict, List, Tuple
 from pydantic import BaseModel
 import json
@@ -100,7 +100,7 @@ def demonstrate_reasoning_extraction():
        context=[problem_task]
    )
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[cot_agent, reasoning_extractor],
        tasks=[problem_task, extract_task],
        process="sequential", output="verbose"
@@ -183,7 +183,7 @@ def advanced_reasoning_patterns():
        context=[deductive_task, inductive_task, abductive_task]
    )
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[cot_agent, reasoning_validator],
        tasks=[deductive_task, inductive_task, abductive_task, validation_task],
        process="sequential", output="verbose"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 agent = Agent(
    instructions="You are a loop agent that creating a loop of tasks.",
@@ -12,7 +12,7 @@ task = Task(
    input_file="tasks.csv"
 )

-agents = Agents(
+agents = AgentTeam(
    agents=[agent],
    tasks=[task],
    process="workflow",
@@ -8,7 +8,7 @@ This example demonstrates various routing patterns in PraisonAI including:
 - Dynamic task selection
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from typing import Dict, Any
 import random

@@ -77,7 +77,7 @@ def conditional_routing_example():
        agent=processor_agent
    )
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[analyzer_agent, processor_agent],
        tasks=[analysis_task, premium_task, standard_task, basic_task],
        process="workflow", output="verbose"
@@ -109,7 +109,7 @@ def loop_pattern_example():
        agent=validator_agent
    )
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[processor_agent, validator_agent],
        tasks=[process_task, finalize_task],
        process="workflow", output="verbose"
@@ -183,7 +183,7 @@ def decision_tree_example():
    
    all_tasks = [categorize_task, technical_task, business_task] + terminal_tasks
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[analyzer_agent, processor_agent],
        tasks=all_tasks,
        process="workflow", output="verbose"
@@ -269,7 +269,7 @@ def dynamic_routing_example():
        agent=processor_agent
    )
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[dynamic_router, processor_agent],
        tasks=[route_task, escalate_task, automate_task, review_task, standard_task],
        process="workflow", output="verbose"
@@ -8,7 +8,7 @@ This example demonstrates the self-reflection capabilities in PraisonAI agents:
 - Impact on output quality
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from typing import Dict, Any
 import time

@@ -162,7 +162,7 @@ def reflection_workflow_example():
        context=[create_task, review_task]
    )
    
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[creator_agent, reviewer_agent, polisher_agent],
        tasks=[create_task, review_task, polish_task],
        process="sequential", output="verbose"
@@ -5,7 +5,7 @@ This example demonstrates self-reflection capabilities using PraisonAI's
 built-in reflection features for iterative improvement and quality optimization.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import internet_search

 print("=== Self-Reflection Optimization Patterns Example ===\n")
@@ -9,7 +9,7 @@ This is the simplest possible implementation for processing URLs from a CSV file
 Author: Generated for GitHub Issue #23
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import write_csv

 def create_url_csv():
@@ -59,7 +59,7 @@ def main():
    )
    
    # Step 4: Run the agents
-    agents = Agents(
+    agents = AgentTeam(
        agents=[url_agent],
        tasks=[url_task],
        process="workflow",
@@ -0,0 +1,391 @@
+"""
+Conditional Branching Example - PraisonAI Agents
+
+This example demonstrates the `if:` pattern for conditional workflow execution:
+1. Basic if/then/else branching
+2. Numeric condition evaluation (>, <, >=, <=, ==, !=)
+3. String condition evaluation (==, !=)
+4. Contains condition (in, contains)
+5. Combining if: with loop: for per-item decisions
+
+The if: pattern enables dynamic workflow paths based on
+runtime conditions and variable values.
+"""
+
+from praisonaiagents import AgentFlow, WorkflowContext, StepResult
+from praisonaiagents.workflows import if_, loop
+
+
+# =============================================================================
+# Example 1: Basic If/Then/Else - Score-Based Routing
+# =============================================================================
+
+def basic_if_example():
+    """
+    Route to different handlers based on a score threshold.
+    """
+    print("\n" + "="*60)
+    print("Example 1: Basic If/Then/Else - Score Routing")
+    print("="*60)
+    
+    def approve(ctx: WorkflowContext) -> StepResult:
+        score = ctx.variables.get("score", 0)
+        print(f"  ✅ APPROVED: Score {score} meets threshold")
+        return StepResult(output="Application approved")
+    
+    def reject(ctx: WorkflowContext) -> StepResult:
+        score = ctx.variables.get("score", 0)
+        print(f"  ❌ REJECTED: Score {score} below threshold")
+        return StepResult(output="Application rejected")
+    
+    # Test with passing score
+    workflow_pass = AgentFlow(
+        steps=[
+            if_(
+                condition="{{score}} >= 70",
+                then_steps=[approve],
+                else_steps=[reject]
+            )
+        ],
+        variables={"score": 85}
+    )
+    
+    print("\nTest 1: Score = 85")
+    workflow_pass.start("Evaluate application")
+    
+    # Test with failing score
+    workflow_fail = AgentFlow(
+        steps=[
+            if_(
+                condition="{{score}} >= 70",
+                then_steps=[approve],
+                else_steps=[reject]
+            )
+        ],
+        variables={"score": 55}
+    )
+    
+    print("\nTest 2: Score = 55")
+    workflow_fail.start("Evaluate application")
+
+
+# =============================================================================
+# Example 2: String Condition - Status-Based Processing
+# =============================================================================
+
+def string_condition_example():
+    """
+    Branch based on string equality.
+    """
+    print("\n" + "="*60)
+    print("Example 2: String Condition - Status Processing")
+    print("="*60)
+    
+    def process_active(ctx: WorkflowContext) -> StepResult:
+        print("  🟢 Processing ACTIVE user")
+        return StepResult(output="Active user processed")
+    
+    def process_inactive(ctx: WorkflowContext) -> StepResult:
+        print("  🔴 Processing INACTIVE user")
+        return StepResult(output="Inactive user archived")
+    
+    # Test with active status
+    workflow = AgentFlow(
+        steps=[
+            if_(
+                condition="{{status}} == active",
+                then_steps=[process_active],
+                else_steps=[process_inactive]
+            )
+        ],
+        variables={"status": "active"}
+    )
+    
+    print("\nTest: status = 'active'")
+    workflow.start("Process user")
+    
+    # Test with inactive status
+    workflow2 = AgentFlow(
+        steps=[
+            if_(
+                condition="{{status}} == active",
+                then_steps=[process_active],
+                else_steps=[process_inactive]
+            )
+        ],
+        variables={"status": "inactive"}
+    )
+    
+    print("\nTest: status = 'inactive'")
+    workflow2.start("Process user")
+
+
+# =============================================================================
+# Example 3: Contains Condition - Content Filtering
+# =============================================================================
+
+def contains_condition_example():
+    """
+    Branch based on whether a string contains a substring.
+    """
+    print("\n" + "="*60)
+    print("Example 3: Contains Condition - Content Filtering")
+    print("="*60)
+    
+    def flag_content(ctx: WorkflowContext) -> StepResult:
+        print("  🚨 FLAGGED: Message contains sensitive content")
+        return StepResult(output="Content flagged for review")
+    
+    def approve_content(ctx: WorkflowContext) -> StepResult:
+        print("  ✅ APPROVED: Message is clean")
+        return StepResult(output="Content approved")
+    
+    # Test with flagged content
+    workflow1 = AgentFlow(
+        steps=[
+            if_(
+                condition="error in {{message}}",
+                then_steps=[flag_content],
+                else_steps=[approve_content]
+            )
+        ],
+        variables={"message": "System error: connection failed"}
+    )
+    
+    print("\nTest 1: Message contains 'error'")
+    workflow1.start("Filter content")
+    
+    # Test with clean content
+    workflow2 = AgentFlow(
+        steps=[
+            if_(
+                condition="error in {{message}}",
+                then_steps=[flag_content],
+                else_steps=[approve_content]
+            )
+        ],
+        variables={"message": "Operation completed successfully"}
+    )
+    
+    print("\nTest 2: Message is clean")
+    workflow2.start("Filter content")
+
+
+# =============================================================================
+# Example 4: If Inside Loop - Per-Item Decisions
+# =============================================================================
+
+def if_inside_loop_example():
+    """
+    Make decisions for each item in a collection.
+    Combines iteration with conditional branching.
+    """
+    print("\n" + "="*60)
+    print("Example 4: If Inside Loop - Per-Item Decisions")
+    print("="*60)
+    
+    results = {"premium": [], "standard": []}
+    
+    def premium_service(ctx: WorkflowContext) -> StepResult:
+        customer = ctx.variables.get("customer", {})
+        name = customer.get("name", "Unknown")
+        results["premium"].append(name)
+        print(f"  ⭐ {name}: Premium service activated")
+        return StepResult(output=f"Premium service for {name}")
+    
+    def standard_service(ctx: WorkflowContext) -> StepResult:
+        customer = ctx.variables.get("customer", {})
+        name = customer.get("name", "Unknown")
+        results["standard"].append(name)
+        print(f"  📦 {name}: Standard service activated")
+        return StepResult(output=f"Standard service for {name}")
+    
+    workflow = AgentFlow(
+        steps=[
+            loop(
+                steps=[
+                    if_(
+                        condition="{{customer.tier}} == premium",
+                        then_steps=[premium_service],
+                        else_steps=[standard_service]
+                    )
+                ],
+                over="customers",
+                var_name="customer"
+            )
+        ],
+        variables={
+            "customers": [
+                {"name": "Alice", "tier": "premium"},
+                {"name": "Bob", "tier": "standard"},
+                {"name": "Charlie", "tier": "premium"},
+                {"name": "Diana", "tier": "standard"}
+            ]
+        }
+    )
+    
+    print("\nProcessing customers:")
+    workflow.start("Assign service tiers")
+    
+    print(f"\nSummary:")
+    print(f"  Premium customers: {results['premium']}")
+    print(f"  Standard customers: {results['standard']}")
+
+
+# =============================================================================
+# Example 5: Nested Conditions - Multi-Level Decision Tree
+# =============================================================================
+
+def nested_conditions_example():
+    """
+    Demonstrate nested if conditions for complex decision trees.
+    """
+    print("\n" + "="*60)
+    print("Example 5: Nested Conditions - Decision Tree")
+    print("="*60)
+    
+    def vip_treatment(ctx: WorkflowContext) -> StepResult:
+        print("  👑 VIP Treatment: Dedicated support + Priority queue")
+        return StepResult(output="VIP treatment applied")  # noqa: ARG001
+    
+    def regular_premium(ctx: WorkflowContext) -> StepResult:
+        print("  ⭐ Premium: Priority support")
+        return StepResult(output="Premium support applied")
+    
+    def basic_support(ctx: WorkflowContext) -> StepResult:
+        print("  📞 Basic: Standard support queue")
+        return StepResult(output="Basic support applied")
+    
+    # Outer condition: Is premium?
+    # Inner condition (if premium): Is VIP?
+    workflow = AgentFlow(
+        steps=[
+            if_(
+                condition="{{tier}} == premium",
+                then_steps=[
+                    if_(
+                        condition="{{spend}} > 10000",
+                        then_steps=[vip_treatment],
+                        else_steps=[regular_premium]
+                    )
+                ],
+                else_steps=[basic_support]
+            )
+        ],
+        variables={"tier": "premium", "spend": 15000}
+    )
+    
+    print("\nTest 1: Premium tier, high spend")
+    workflow.start("Determine support level")
+    
+    workflow2 = AgentFlow(
+        steps=[
+            if_(
+                condition="{{tier}} == premium",
+                then_steps=[
+                    if_(
+                        condition="{{spend}} > 10000",
+                        then_steps=[vip_treatment],
+                        else_steps=[regular_premium]
+                    )
+                ],
+                else_steps=[basic_support]
+            )
+        ],
+        variables={"tier": "premium", "spend": 5000}
+    )
+    
+    print("\nTest 2: Premium tier, low spend")
+    workflow2.start("Determine support level")
+    
+    workflow3 = AgentFlow(
+        steps=[
+            if_(
+                condition="{{tier}} == premium",
+                then_steps=[
+                    if_(
+                        condition="{{spend}} > 10000",
+                        then_steps=[vip_treatment],
+                        else_steps=[regular_premium]
+                    )
+                ],
+                else_steps=[basic_support]
+            )
+        ],
+        variables={"tier": "basic", "spend": 20000}
+    )
+    
+    print("\nTest 3: Basic tier (regardless of spend)")
+    workflow3.start("Determine support level")
+
+
+# =============================================================================
+# Example 6: No Else Branch - Optional Processing
+# =============================================================================
+
+def no_else_example():
+    """
+    If condition without else branch - only execute if true.
+    """
+    print("\n" + "="*60)
+    print("Example 6: No Else Branch - Optional Processing")
+    print("="*60)
+    
+    def send_notification(ctx: WorkflowContext) -> StepResult:
+        print("  📧 Notification sent!")
+        return StepResult(output="Notification sent")
+    
+    def continue_processing(ctx: WorkflowContext) -> StepResult:
+        print("  ➡️ Continuing with main workflow...")
+        return StepResult(output="Continued")
+    
+    # Only send notification if opted in
+    workflow = AgentFlow(
+        steps=[
+            if_(
+                condition="{{notify}} == true",
+                then_steps=[send_notification]
+                # No else_steps - just skip if false
+            ),
+            continue_processing
+        ],
+        variables={"notify": "true"}
+    )
+    
+    print("\nTest 1: notify = true")
+    workflow.start("Process with notification")
+    
+    workflow2 = AgentFlow(
+        steps=[
+            if_(
+                condition="{{notify}} == true",
+                then_steps=[send_notification]
+            ),
+            continue_processing
+        ],
+        variables={"notify": "false"}
+    )
+    
+    print("\nTest 2: notify = false")
+    workflow2.start("Process without notification")
+
+
+# =============================================================================
+# Main - Run All Examples
+# =============================================================================
+
+if __name__ == "__main__":
+    print("\n" + "="*60)
+    print("PraisonAI Conditional Branching Examples")
+    print("="*60)
+    
+    basic_if_example()
+    string_condition_example()
+    contains_condition_example()
+    if_inside_loop_example()
+    nested_conditions_example()
+    no_else_example()
+    
+    print("\n" + "="*60)
+    print("All conditional branching examples completed!")
+    print("="*60)
@@ -4,7 +4,7 @@ Example: Using Latency Tracking Tool with PraisonAI
 This example shows how to track latency without modifying core files.
 """

-from praisonaiagents import Agent, Agents
+from praisonaiagents import Agent, AgentTeam
 from latency_tracker_tool import (
    latency_tracking_tool, 
    create_tracked_agent,
@@ -5,7 +5,7 @@ This shows how to add latency tracking to an MCP server
 without modifying PraisonAI core files.
 """

-from praisonaiagents import Agent, Agents
+from praisonaiagents import Agent, AgentTeam
 from hosted_server import HostedMCPServer  # Import from local file
 from latency_tracker_tool import tracker, get_latency_metrics
 import json
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import cot_save, cot_upload_to_huggingface
 from pydantic import BaseModel
 import os
@@ -128,7 +128,7 @@ upload_to_huggingface_task = Task(
 )

 # Initialize workflow
-agents = Agents(
+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",
@@ -0,0 +1,214 @@
+"""Example: Merge Strategies for Multi-Agent Workflows
+
+This example demonstrates how to use and create custom merge strategies
+for combining outputs from parallel agent executions.
+"""
+from praisonaiagents.agents import (
+    MergeStrategyProtocol,
+    FirstWinsMerge,
+    ConcatMerge,
+    DictMerge,
+)
+
+
+def example_first_wins_merge():
+    """Demonstrate FirstWinsMerge strategy."""
+    print("=" * 50)
+    print("FirstWinsMerge Examples")
+    print("=" * 50)
+    
+    merge = FirstWinsMerge()
+    
+    # 1. Basic usage - returns first non-None
+    print("\n1. Basic Usage:")
+    outputs = [None, "Agent 2 response", "Agent 3 response"]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+    
+    # 2. All None returns None
+    print("\n2. All None:")
+    outputs = [None, None, None]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+    
+    # 3. First value wins
+    print("\n3. First Value Wins:")
+    outputs = ["Fast agent", "Slow agent", "Slowest agent"]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+    
+    # 4. Works with any type
+    print("\n4. Various Types:")
+    print(f"   Dict: {merge.merge([None, {'key': 'value'}])}")
+    print(f"   List: {merge.merge([None, [1, 2, 3]])}")
+    print(f"   Number: {merge.merge([None, 42])}")
+
+
+def example_concat_merge():
+    """Demonstrate ConcatMerge strategy."""
+    print("\n" + "=" * 50)
+    print("ConcatMerge Examples")
+    print("=" * 50)
+    
+    # 1. Default separator (double newline)
+    print("\n1. Default Separator:")
+    merge = ConcatMerge()
+    outputs = ["Part 1: Introduction", "Part 2: Analysis", "Part 3: Conclusion"]
+    result = merge.merge(outputs)
+    print(f"   Result:\n{result}")
+    
+    # 2. Custom separator
+    print("\n2. Custom Separator:")
+    merge = ConcatMerge(separator=" | ")
+    outputs = ["Alice", "Bob", "Charlie"]
+    result = merge.merge(outputs)
+    print(f"   Result: {result}")
+    
+    # 3. Skips None values
+    print("\n3. Skips None:")
+    merge = ConcatMerge(separator=", ")
+    outputs = ["A", None, "C", None, "E"]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+    
+    # 4. Converts non-strings
+    print("\n4. Converts Non-Strings:")
+    merge = ConcatMerge(separator=" + ")
+    outputs = [1, 2, 3]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+
+
+def example_dict_merge():
+    """Demonstrate DictMerge strategy."""
+    print("\n" + "=" * 50)
+    print("DictMerge Examples")
+    print("=" * 50)
+    
+    # 1. Basic shallow merge
+    print("\n1. Shallow Merge (default):")
+    merge = DictMerge()
+    outputs = [
+        {"name": "Alice", "score": 10},
+        {"name": "Bob", "level": 5},
+        {"score": 20, "rank": 1}
+    ]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+    
+    # 2. Later values override
+    print("\n2. Override Behavior:")
+    merge = DictMerge()
+    outputs = [
+        {"status": "pending"},
+        {"status": "processing"},
+        {"status": "complete"}
+    ]
+    result = merge.merge(outputs)
+    print(f"   Result: {result}")
+    
+    # 3. Deep merge for nested dicts
+    print("\n3. Deep Merge:")
+    merge = DictMerge(deep=True)
+    outputs = [
+        {"config": {"a": 1, "b": 2}},
+        {"config": {"b": 3, "c": 4}},
+        {"config": {"d": 5}}
+    ]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+    
+    # 4. Skips non-dict values
+    print("\n4. Skips Non-Dict Values:")
+    merge = DictMerge()
+    outputs = [{"a": 1}, "not a dict", None, {"b": 2}]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+
+
+def example_custom_merge():
+    """Demonstrate creating custom merge strategies."""
+    print("\n" + "=" * 50)
+    print("Custom Merge Strategy Examples")
+    print("=" * 50)
+    
+    # 1. Longest output merge
+    class LongestOutputMerge:
+        """Returns the longest output."""
+        def merge(self, outputs, context=None):
+            valid = [o for o in outputs if o is not None]
+            if not valid:
+                return None
+            return max(valid, key=lambda x: len(str(x)))
+    
+    print("\n1. LongestOutputMerge:")
+    merge = LongestOutputMerge()
+    outputs = ["short", "medium length", "this is the longest response"]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result}")
+    
+    # 2. Majority vote merge
+    class MajorityVoteMerge:
+        """Returns the most common output."""
+        def merge(self, outputs, context=None):
+            from collections import Counter
+            valid = [o for o in outputs if o is not None]
+            if not valid:
+                return None
+            counts = Counter(valid)
+            return counts.most_common(1)[0][0]
+    
+    print("\n2. MajorityVoteMerge:")
+    merge = MajorityVoteMerge()
+    outputs = ["yes", "yes", "no", "yes", "no"]
+    result = merge.merge(outputs)
+    print(f"   Inputs: {outputs}")
+    print(f"   Result: {result} (3 votes)")
+    
+    # 3. Weighted merge
+    class WeightedMerge:
+        """Merges with agent weights from context."""
+        def merge(self, outputs, context=None):
+            weights = context.get("weights", [1] * len(outputs)) if context else [1] * len(outputs)
+            best_idx = 0
+            best_weight = 0
+            for i, (output, weight) in enumerate(zip(outputs, weights)):
+                if output is not None and weight > best_weight:
+                    best_idx = i
+                    best_weight = weight
+            return outputs[best_idx] if outputs else None
+    
+    print("\n3. WeightedMerge:")
+    merge = WeightedMerge()
+    outputs = ["junior answer", "senior answer", "expert answer"]
+    context = {"weights": [1, 5, 10]}
+    result = merge.merge(outputs, context=context)
+    print(f"   Inputs: {outputs}")
+    print(f"   Weights: {context['weights']}")
+    print(f"   Result: {result}")
+    
+    # 4. Protocol compliance
+    print("\n4. Protocol Compliance:")
+    print(f"   LongestOutputMerge: {isinstance(LongestOutputMerge(), MergeStrategyProtocol)}")
+    print(f"   MajorityVoteMerge: {isinstance(MajorityVoteMerge(), MergeStrategyProtocol)}")
+    print(f"   WeightedMerge: {isinstance(WeightedMerge(), MergeStrategyProtocol)}")
+
+
+if __name__ == "__main__":
+    example_first_wins_merge()
+    example_concat_merge()
+    example_dict_merge()
+    example_custom_merge()
+    
+    print("\n" + "=" * 50)
+    print("All examples completed!")
+    print("=" * 50)
@@ -0,0 +1,174 @@
+"""Example: Retry Policies and Fallback Chains
+
+This example demonstrates how to configure retry behavior with
+exponential backoff, jitter, and fallback chains.
+"""
+from praisonaiagents.tools import (
+    RetryPolicy,
+    FallbackChain,
+    ToolExecutionConfig,
+)
+
+
+def example_retry_policy():
+    """Demonstrate RetryPolicy configuration and usage."""
+    print("=" * 50)
+    print("RetryPolicy Examples")
+    print("=" * 50)
+    
+    # 1. Default policy
+    print("\n1. Default RetryPolicy:")
+    policy = RetryPolicy()
+    print(f"   max_attempts: {policy.max_attempts}")
+    print(f"   backoff_factor: {policy.backoff_factor}")
+    print(f"   initial_delay_ms: {policy.initial_delay_ms}")
+    print(f"   max_delay_ms: {policy.max_delay_ms}")
+    print(f"   retry_on: {policy.retry_on}")
+    
+    # 2. Exponential backoff calculation
+    print("\n2. Exponential Backoff (no jitter):")
+    policy = RetryPolicy(
+        initial_delay_ms=1000,
+        backoff_factor=2.0,
+        max_delay_ms=30000,
+        jitter=False
+    )
+    for attempt in range(5):
+        delay = policy.get_delay_ms(attempt)
+        print(f"   Attempt {attempt}: delay = {delay}ms")
+    
+    # 3. With jitter for production
+    print("\n3. With Jitter (production-ready):")
+    policy = RetryPolicy(
+        initial_delay_ms=1000,
+        backoff_factor=2.0,
+        jitter=True,
+        jitter_factor=0.25  # ±25%
+    )
+    print("   Delays for attempt 0 (10 samples):")
+    delays = [policy.get_delay_ms(0) for _ in range(10)]
+    print(f"   {delays}")
+    print(f"   Range: {min(delays)} - {max(delays)} (expected: 750-1250)")
+    
+    # 4. should_retry logic
+    print("\n4. should_retry Logic:")
+    policy = RetryPolicy(max_attempts=3, retry_on={"timeout", "rate_limit"})
+    
+    test_cases = [
+        ("timeout", 0),
+        ("timeout", 2),
+        ("timeout", 3),  # At max_attempts
+        ("unknown_error", 0),  # Not in retry_on
+    ]
+    for error_type, attempt in test_cases:
+        result = policy.should_retry(error_type, attempt)
+        print(f"   should_retry('{error_type}', {attempt}) = {result}")
+    
+    # 5. Custom error types
+    print("\n5. Custom Error Types:")
+    policy = RetryPolicy(retry_on={"api_error", "network_error", "throttled"})
+    print(f"   Retries on: {policy.retry_on}")
+    print(f"   should_retry('api_error', 0) = {policy.should_retry('api_error', 0)}")
+    print(f"   should_retry('timeout', 0) = {policy.should_retry('timeout', 0)}")
+
+
+def example_fallback_chain():
+    """Demonstrate FallbackChain configuration."""
+    print("\n" + "=" * 50)
+    print("FallbackChain Examples")
+    print("=" * 50)
+    
+    # 1. Basic chain
+    print("\n1. Basic FallbackChain:")
+    chain = FallbackChain(
+        tools=["web_search", "cached_search", "default_response"]
+    )
+    print(f"   Tools: {chain.tools}")
+    print(f"   Length: {len(chain)}")
+    print(f"   stop_on_success: {chain.stop_on_success}")
+    
+    # 2. Iteration
+    print("\n2. Iterating over chain:")
+    for i, tool in enumerate(chain):
+        print(f"   {i+1}. {tool}")
+    
+    # 3. Try all (don't stop on success)
+    print("\n3. Try All Mode:")
+    chain = FallbackChain(
+        tools=["validator_1", "validator_2", "validator_3"],
+        stop_on_success=False
+    )
+    print(f"   stop_on_success: {chain.stop_on_success}")
+    print("   (All tools will be tried regardless of success)")
+
+
+def example_tool_execution_config():
+    """Demonstrate ToolExecutionConfig combining retry and fallback."""
+    print("\n" + "=" * 50)
+    print("ToolExecutionConfig Examples")
+    print("=" * 50)
+    
+    # 1. Default config
+    print("\n1. Default Config:")
+    config = ToolExecutionConfig()
+    print(f"   retry_policy: {config.retry_policy}")
+    print(f"   fallback_chain: {config.fallback_chain}")
+    print(f"   timeout_ms: {config.timeout_ms}")
+    
+    # 2. Using default() factory
+    print("\n2. Default Factory:")
+    config = ToolExecutionConfig.default()
+    print(f"   retry_policy.max_attempts: {config.retry_policy.max_attempts}")
+    
+    # 3. Full configuration
+    print("\n3. Full Configuration:")
+    config = ToolExecutionConfig(
+        retry_policy=RetryPolicy(
+            max_attempts=5,
+            backoff_factor=1.5,
+            initial_delay_ms=500,
+            jitter=True
+        ),
+        fallback_chain=FallbackChain(
+            tools=["primary_api", "backup_api", "cache"]
+        ),
+        timeout_ms=10000
+    )
+    print(f"   retry_policy.max_attempts: {config.retry_policy.max_attempts}")
+    print(f"   retry_policy.jitter: {config.retry_policy.jitter}")
+    print(f"   fallback_chain tools: {config.fallback_chain.tools}")
+    print(f"   timeout_ms: {config.timeout_ms}")
+
+
+def example_validation():
+    """Demonstrate validation of RetryPolicy parameters."""
+    print("\n" + "=" * 50)
+    print("Validation Examples")
+    print("=" * 50)
+    
+    invalid_configs = [
+        ("max_attempts=0", {"max_attempts": 0}),
+        ("backoff_factor=0.5", {"backoff_factor": 0.5}),
+        ("initial_delay_ms=-1", {"initial_delay_ms": -1}),
+        ("max_delay < initial", {"initial_delay_ms": 1000, "max_delay_ms": 500}),
+        ("jitter_factor=1.5", {"jitter_factor": 1.5}),
+    ]
+    
+    for name, kwargs in invalid_configs:
+        try:
+            RetryPolicy(**kwargs)
+            print(f"\n   {name}: No error (unexpected!)")
+        except ValueError as e:
+            print(f"\n   {name}:")
+            print(f"   → ValueError: {e}")
+
+
+if __name__ == "__main__":
+    example_retry_policy()
+    example_fallback_chain()
+    example_tool_execution_config()
+    example_validation()
+    
+    print("\n" + "=" * 50)
+    print("All examples completed!")
+    print("=" * 50)
@@ -0,0 +1,163 @@
+"""Example: Tool Validation with Custom Validators
+
+This example demonstrates how to use ValidationResult and implement
+custom validators using the ToolValidatorProtocol.
+"""
+from praisonaiagents.tools import (
+    ValidationResult,
+    ToolValidatorProtocol,
+    PassthroughValidator,
+)
+
+
+def example_validation_result():
+    """Demonstrate ValidationResult usage."""
+    print("=" * 50)
+    print("ValidationResult Examples")
+    print("=" * 50)
+    
+    # 1. Success factory
+    success = ValidationResult.success()
+    print(f"\n1. Success: valid={success.valid}, bool={bool(success)}")
+    
+    # 2. Failure factory
+    failure = ValidationResult.failure(
+        errors=["Query cannot be empty", "Missing required field"],
+        remediation="Provide a non-empty query string"
+    )
+    print(f"\n2. Failure: valid={failure.valid}")
+    print(f"   Errors: {failure.errors}")
+    print(f"   Remediation: {failure.remediation}")
+    
+    # 3. Fluent API - building incrementally
+    result = ValidationResult(valid=True)
+    result.add_warning("Query is very long, may be slow")
+    result.add_warning("Consider using pagination")
+    print(f"\n3. With warnings: valid={result.valid}, warnings={result.warnings}")
+    
+    # 4. Adding errors changes validity
+    result.add_error("Rate limit exceeded")
+    print(f"\n4. After error: valid={result.valid}, errors={result.errors}")
+
+
+class InputLengthValidator:
+    """Custom validator that checks string input lengths."""
+    
+    def __init__(self, max_length: int = 100):
+        self.max_length = max_length
+    
+    def validate_args(self, tool_name, args, context=None):
+        """Validate that string arguments don't exceed max length."""
+        for key, value in args.items():
+            if isinstance(value, str) and len(value) > self.max_length:
+                return ValidationResult.failure(
+                    errors=[f"Argument '{key}' ({len(value)} chars) exceeds limit ({self.max_length})"],
+                    remediation=f"Truncate '{key}' to {self.max_length} characters or less"
+                )
+        return ValidationResult.success()
+    
+    def validate_result(self, tool_name, result, context=None):
+        """Validate tool results."""
+        return ValidationResult.success()
+
+
+class TypeValidator:
+    """Custom validator that checks argument types."""
+    
+    def __init__(self, type_specs: dict):
+        """
+        Args:
+            type_specs: Dict mapping arg names to expected types
+                       e.g., {"query": str, "limit": int}
+        """
+        self.type_specs = type_specs
+    
+    def validate_args(self, tool_name, args, context=None):
+        result = ValidationResult(valid=True)
+        
+        for arg_name, expected_type in self.type_specs.items():
+            if arg_name in args:
+                actual_value = args[arg_name]
+                if not isinstance(actual_value, expected_type):
+                    result.add_error(
+                        f"Argument '{arg_name}' must be {expected_type.__name__}, "
+                        f"got {type(actual_value).__name__}"
+                    )
+        
+        if not result.valid:
+            result.remediation = "Check argument types and try again"
+        
+        return result
+    
+    def validate_result(self, tool_name, result, context=None):
+        return ValidationResult.success()
+
+
+def example_custom_validators():
+    """Demonstrate custom validator implementations."""
+    print("\n" + "=" * 50)
+    print("Custom Validator Examples")
+    print("=" * 50)
+    
+    # 1. InputLengthValidator
+    print("\n1. InputLengthValidator:")
+    validator = InputLengthValidator(max_length=50)
+    
+    # Valid input
+    result = validator.validate_args("search", {"query": "short query"})
+    print(f"   Short query: valid={result.valid}")
+    
+    # Invalid input
+    long_query = "x" * 100
+    result = validator.validate_args("search", {"query": long_query})
+    print(f"   Long query: valid={result.valid}")
+    print(f"   Error: {result.errors[0]}")
+    print(f"   Fix: {result.remediation}")
+    
+    # 2. TypeValidator
+    print("\n2. TypeValidator:")
+    validator = TypeValidator({"query": str, "limit": int, "offset": int})
+    
+    # Valid types
+    result = validator.validate_args("search", {"query": "test", "limit": 10})
+    print(f"   Correct types: valid={result.valid}")
+    
+    # Invalid types
+    result = validator.validate_args("search", {"query": 123, "limit": "ten"})
+    print(f"   Wrong types: valid={result.valid}")
+    for error in result.errors:
+        print(f"   - {error}")
+    
+    # 3. Protocol compliance check
+    print("\n3. Protocol Compliance:")
+    print(f"   InputLengthValidator: {isinstance(InputLengthValidator(), ToolValidatorProtocol)}")
+    print(f"   TypeValidator: {isinstance(TypeValidator({}), ToolValidatorProtocol)}")
+    print(f"   PassthroughValidator: {isinstance(PassthroughValidator(), ToolValidatorProtocol)}")
+
+
+def example_passthrough_validator():
+    """Demonstrate the default PassthroughValidator."""
+    print("\n" + "=" * 50)
+    print("PassthroughValidator Example")
+    print("=" * 50)
+    
+    validator = PassthroughValidator()
+    
+    # Always returns valid
+    result = validator.validate_args("any_tool", {"any": "args"})
+    print(f"\nvalidate_args: valid={result.valid}")
+    
+    result = validator.validate_result("any_tool", {"any": "result"})
+    print(f"validate_result: valid={result.valid}")
+    
+    print("\nPassthroughValidator is useful as a default when no validation is needed.")
+
+
+if __name__ == "__main__":
+    example_validation_result()
+    example_custom_validators()
+    example_passthrough_validator()
+    
+    print("\n" + "=" * 50)
+    print("All examples completed!")
+    print("=" * 50)
@@ -0,0 +1,170 @@
+"""
+Model Failover Example - Automatic Provider Switching
+
+This example demonstrates how to configure model failover
+for reliability and cost optimization.
+"""
+
+import os
+from praisonaiagents import (
+    AuthProfile,
+    FailoverConfig,
+    FailoverManager,
+)
+
+# Create auth profiles for different providers
+openai_profile = AuthProfile(
+    name="openai-primary",
+    provider="openai",
+    api_key=os.environ.get("OPENAI_API_KEY", "sk-..."),
+    priority=1,  # Highest priority
+    rate_limit=100,
+)
+
+anthropic_profile = AuthProfile(
+    name="anthropic-backup",
+    provider="anthropic",
+    api_key=os.environ.get("ANTHROPIC_API_KEY", "sk-ant-..."),
+    priority=2,  # Second priority
+    rate_limit=50,
+)
+
+groq_profile = AuthProfile(
+    name="groq-fallback",
+    provider="groq",
+    api_key=os.environ.get("GROQ_API_KEY", "gsk-..."),
+    priority=3,  # Third priority (fast but limited)
+    rate_limit=30,
+)
+
+# Configure failover behavior
+failover_config = FailoverConfig(
+    max_retries=3,
+    retry_delay=1.0,
+    exponential_backoff=True,
+    max_retry_delay=60.0,
+    failover_on_rate_limit=True,
+    failover_on_timeout=True,
+    failover_on_error=True,
+)
+
+# Create failover manager
+manager = FailoverManager(failover_config)
+manager.add_profile(openai_profile)
+manager.add_profile(anthropic_profile)
+manager.add_profile(groq_profile)
+
+def demonstrate_failover():
+    """Demonstrate failover functionality."""
+    
+    print("Failover Manager Status:")
+    print()
+    
+    # Get current status
+    status = manager.status()
+    for name, info in status.items():
+        print(f"  {name}:")
+        print(f"    Status: {info.get('status', 'unknown')}")
+        print(f"    Priority: {info.get('priority', 'N/A')}")
+        print(f"    Failures: {info.get('failure_count', 0)}")
+    print()
+    
+    # Get next available profile
+    next_profile = manager.get_next_profile()
+    if next_profile:
+        print(f"Next profile to use: {next_profile.name}")
+        print(f"  Provider: {next_profile.provider}")
+        print(f"  Priority: {next_profile.priority}")
+    print()
+    
+    # Simulate marking a failure
+    print("Simulating failure on primary provider...")
+    manager.mark_failure("openai-primary", "Rate limit exceeded")
+    
+    # Get next profile after failure
+    next_profile = manager.get_next_profile()
+    if next_profile:
+        print(f"After failure, next profile: {next_profile.name}")
+    print()
+    
+    # Get retry delay
+    delay = manager.get_retry_delay("openai-primary")
+    print(f"Retry delay for openai-primary: {delay}s")
+    print()
+    
+    # Reset all providers
+    print("Resetting all providers...")
+    manager.reset_all()
+    
+    next_profile = manager.get_next_profile()
+    if next_profile:
+        print(f"After reset, next profile: {next_profile.name}")
+
+def cost_optimization_example():
+    """Example of cost-optimized failover."""
+    
+    print("\nCost Optimization Example:")
+    print("-" * 40)
+    
+    # Create cost-optimized manager
+    cost_manager = FailoverManager()
+    
+    # Cheaper model first
+    cost_manager.add_profile(AuthProfile(
+        name="gpt-4o-mini",
+        provider="openai",
+        api_key=os.environ.get("OPENAI_API_KEY", ""),
+        priority=1,
+        metadata={"model": "gpt-4o-mini", "cost_per_1k": 0.00015}
+    ))
+    
+    # Premium model as fallback
+    cost_manager.add_profile(AuthProfile(
+        name="gpt-4o",
+        provider="openai",
+        api_key=os.environ.get("OPENAI_API_KEY", ""),
+        priority=2,
+        metadata={"model": "gpt-4o", "cost_per_1k": 0.005}
+    ))
+    
+    # Most expensive as last resort
+    cost_manager.add_profile(AuthProfile(
+        name="claude-opus",
+        provider="anthropic",
+        api_key=os.environ.get("ANTHROPIC_API_KEY", ""),
+        priority=3,
+        metadata={"model": "claude-3-opus", "cost_per_1k": 0.015}
+    ))
+    
+    print("Cost-optimized failover chain:")
+    for profile in [
+        cost_manager.get_profile("gpt-4o-mini"),
+        cost_manager.get_profile("gpt-4o"),
+        cost_manager.get_profile("claude-opus"),
+    ]:
+        if profile:
+            cost = profile.metadata.get("cost_per_1k", "N/A")
+            print(f"  {profile.priority}. {profile.name} (${cost}/1K tokens)")
+
+if __name__ == "__main__":
+    print("Model Failover Configuration")
+    print("=" * 40)
+    print()
+    
+    print("Failover Config:")
+    print(f"  Max retries: {failover_config.max_retries}")
+    print(f"  Initial delay: {failover_config.retry_delay}s")
+    print(f"  Exponential backoff: {failover_config.exponential_backoff}")
+    print(f"  Max delay: {failover_config.max_retry_delay}s")
+    print()
+    
+    print("Auth Profiles:")
+    for profile in [openai_profile, anthropic_profile, groq_profile]:
+        print(f"  {profile.name}:")
+        print(f"    Provider: {profile.provider}")
+        print(f"    Priority: {profile.priority}")
+        print(f"    Rate limit: {profile.rate_limit} req/min")
+    print()
+    
+    demonstrate_failover()
+    cost_optimization_example()
@@ -0,0 +1,47 @@
+"""
+Gateway Example - Multi-Agent Coordination
+
+This example demonstrates how to use the Gateway for coordinating
+multiple agents and managing real-time communication.
+"""
+
+from praisonaiagents import Agent, GatewayConfig, SessionConfig
+
+# Configure the gateway
+gateway_config = GatewayConfig(
+    host="127.0.0.1",
+    port=8765,
+    max_connections=100,
+    heartbeat_interval=30,
+    session_config=SessionConfig(
+        timeout=3600,  # 1 hour session timeout
+        max_messages=500,
+    )
+)
+
+# Create specialized agents
+researcher = Agent(
+    name="researcher",
+    instructions="You research topics thoroughly and provide detailed information.",
+    llm="gpt-4o-mini"
+)
+
+writer = Agent(
+    name="writer",
+    instructions="You write clear, engaging content based on research.",
+    llm="gpt-4o-mini"
+)
+
+# Example: Simple agent interaction
+if __name__ == "__main__":
+    print("Gateway Configuration:")
+    print(f"  Host: {gateway_config.host}")
+    print(f"  Port: {gateway_config.port}")
+    print(f"  WebSocket URL: {gateway_config.ws_url}")
+    print(f"  Max Connections: {gateway_config.max_connections}")
+    print()
+    
+    # Test agent
+    response = researcher.start("What are the key benefits of multi-agent systems?")
+    print("Researcher Response:")
+    print(response)
@@ -5,7 +5,7 @@ This example demonstrates callback systems using PraisonAI's built-in
 callback functionality for monitoring agent interactions and tool usage.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.display_callback import register_display_callback
 from praisonaiagents.tools import internet_search

@@ -1,7 +1,7 @@
 import asyncio
 import time
 from typing import List, Dict
-from praisonaiagents import Agent, Task, Agents, TaskOutput
+from praisonaiagents import Agent, Task, AgentTeam, TaskOutput
 from praisonaiagents.main import (
    display_error,
    display_interaction,
@@ -156,7 +156,7 @@ workflow_async_task = Task(
 def run_sync_example():
    """Run synchronous example"""
    display_instruction("\nRunning Synchronous Example...", console)
-    agents = Agents(
+    agents = AgentTeam(
        agents=[sync_agent],
        tasks=[sync_task],
        process="sequential"
@@ -167,7 +167,7 @@ def run_sync_example():
 async def run_async_example():
    """Run asynchronous example"""
    display_instruction("\nRunning Asynchronous Example...", console)
-    agents = Agents(
+    agents = AgentTeam(
        agents=[async_agent],
        tasks=[async_task],
        process="sequential"
@@ -178,7 +178,7 @@ async def run_async_example():
 async def run_mixed_example():
    """Run mixed sync/async example"""
    display_instruction("\nRunning Mixed Sync/Async Example...", console)
-    agents = Agents(
+    agents = AgentTeam(
        agents=[sync_agent, async_agent],
        tasks=[sync_task, async_task],
        process="sequential"
@@ -189,7 +189,7 @@ async def run_mixed_example():
 async def run_workflow_example():
    """Run workflow example with both sync and async tasks"""
    display_instruction("\nRunning Workflow Example...", console)
-    agents = Agents(
+    agents = AgentTeam(
        agents=[sync_agent, async_agent],
        tasks=[workflow_sync_task, workflow_async_task],
        process="workflow"
@@ -1,7 +1,7 @@
 import asyncio
 import time
 from typing import List, Dict
-from praisonaiagents import Agent, Task, Agents, TaskOutput
+from praisonaiagents import Agent, Task, AgentTeam, TaskOutput
 from duckduckgo_search import DDGS
 from pydantic import BaseModel

@@ -111,7 +111,7 @@ async def run_parallel_tasks():
    )
    
    # Create a single Agents instance with both agents
-    agents = Agents(
+    agents = AgentTeam(
        agents=[async_agent, summary_agent],
        tasks=parallel_tasks + [summary_task],
        process="sequential"
@@ -1,7 +1,7 @@
 import asyncio
 import time
 from typing import List, Dict
-from praisonaiagents import Agent, Task, Agents, TaskOutput
+from praisonaiagents import Agent, Task, AgentTeam, TaskOutput
 from duckduckgo_search import DDGS
 from pydantic import BaseModel

@@ -99,7 +99,7 @@ async_task = Task(
 async def run_single_task():
    """Run single async task"""
    print("\nRunning Single Async Task...")
-    agents = Agents(
+    agents = AgentTeam(
        agents=[async_agent],
        tasks=[async_task],
        process="sequential"
@@ -182,7 +182,7 @@ Present the summary in a clear, structured format with sections for findings, pa
    )
    
    # First run parallel search tasks
-    agents = Agents(
+    agents = AgentTeam(
        agents=[async_agent],
        tasks=parallel_tasks,  # Only run search tasks first
        process="sequential"
@@ -206,7 +206,7 @@ Present the summary in a clear, structured format with sections for findings, pa
    summary_task.context = completed_tasks
    
    # Run summarization task with summary agent
-    summary_agents = Agents(
+    summary_agents = AgentTeam(
        agents=[summary_agent],  # Use summary agent for synthesis
        tasks=[summary_task],
        process="sequential"
@@ -18,7 +18,7 @@ from praisonaiagents import AutoAgents
 from praisonaiagents.tools import duckduckgo

 # Basic usage - AutoAgents analyzes complexity and creates optimal agents
-agents = AutoAgents(
+agents = AutoAgentTeam(
    instructions="Search for information about AI Agents",
    tools=[duckduckgo],
    process="sequential",  # or "hierarchical"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 import time

 def get_environment_state():
@@ -86,7 +86,7 @@ feedback_task = Task(
 )

 # Create workflow manager
-workflow = Agents(
+workflow = AgentTeam(
    agents=[llm_caller, action_agent, feedback_agent],
    tasks=[monitor_task, action_task, feedback_task],
    process="workflow", output="verbose"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 import json
 from e2b_code_interpreter import Sandbox

@@ -46,5 +46,5 @@ execution_agent_task = Task(
    agent=execution_agent
 )

-agents = Agents(agents=[code_agent, execution_agent], tasks=[code_agent_task, execution_agent_task])
+agents = AgentTeam(agents=[code_agent, execution_agent], tasks=[code_agent_task, execution_agent_task])
 agents.start()
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Create generator and evaluator agents
 generator = Agent(
@@ -53,7 +53,7 @@ evaluate_task = Task(
 )

 # Create workflow manager
-workflow = Agents(
+workflow = AgentTeam(
    agents=[generator, evaluator],
    tasks=[generate_task, evaluate_task],
    process="workflow", output="verbose"
@@ -183,7 +183,7 @@ def main():
    )

    # Create and run agents manager
-    agents = Agents(
+    agents = AgentTeam(
        agents=[researcher, writer],
        tasks=[task1, task2, task3, task4],
        process="sequential",
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from typing import List, Dict, Union
 from duckduckgo_search import DDGS
 from langchain_community.tools import YouTubeSearchTool
@@ -141,7 +141,7 @@ validate_task = Task(
 )

 # 4. Workflow
-agents = Agents(
+agents = AgentTeam(
    agents=[data_agent],
    tasks=[collect_task, validate_task],
    process="workflow"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents, error_logs
+from praisonaiagents import Agent, Task, AgentTeam, error_logs
 from duckduckgo_search import DDGS

 def my_callback(output):
@@ -92,7 +92,7 @@ task4 = Task(
 )

 # Create and run agents manager
-agents = Agents(
+agents = AgentTeam(
    agents=[researcher, writer],
    tasks=[task1, task2, task3, task4],
    output="minimal",
@@ -24,7 +24,7 @@ import sys
 # Add the local development path to use the current implementation
 sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..', '..', 'src', 'praisonai-agents'))

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import python_tools, file_tools, shell_tools
 from praisonaiagents.main import register_approval_callback
 from praisonaiagents.approval import (
@@ -109,7 +109,7 @@ def main():
    ]
    
    # Create and run process
-    process = Agents(
+    process = AgentTeam(
        agents=[agent],
        tasks=tasks, output="verbose"
    )
@@ -166,7 +166,7 @@ async def async_demo():
        expected_output="Async execution result"
    )
    
-    process = Agents(
+    process = AgentTeam(
        agents=[agent],
        tasks=[task], output="verbose"
    )
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from langchain_community.tools import YouTubeSearchTool
 from langchain_community.utilities import WikipediaAPIWrapper

@@ -21,7 +21,7 @@ task = Task(
 )

 # Create and start the workflow
-agents = Agents(
+agents = AgentTeam(
    agents=[agent],
    tasks=[task], output="verbose"
 )
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 import logging
 import os

@@ -101,7 +101,7 @@ def main():
    )

    # Initialize Agents with memory configuration
-    agents = Agents(
+    agents = AgentTeam(
        agents=[researcher, retriever],
        tasks=[store_task, verify_task, query_task, query_both_task],  # Use same verbose level as memory
        memory={
@@ -115,7 +115,7 @@ def main():
        }
    )

-    # agents = Agents(
+    # agents = AgentTeam(
    #     agents=[researcher, retriever],
    #     tasks=[store_task, verify_task, query_task, query_both_task],
    #     # Use same verbose level as memory
@@ -54,7 +54,7 @@ blog_task = Task(
    agent=blog_agent
 )

-agents = Agents(
+agents = AgentTeam(
    agents=[fact_agent, research_agent, blog_agent],
    tasks=[fact_task, research_task, research_task2, research_task3, research_task4, blog_task],
    memory=True
@@ -1,6 +1,6 @@
-from praisonaiagents import Agent, Agents, Tools
+from praisonaiagents import Agent, AgentTeam, Tools

 research_agent = Agent(instructions="You are a research agent to search internet about AI 2024", tools=[Tools.internet_search])
 summarise_agent = Agent(instructions="You are a summarize agent to summarise in points")
-agents = Agents(agents=[research_agent, summarise_agent])
+agents = AgentTeam(agents=[research_agent, summarise_agent])
 agents.start()
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Create Vision Analysis Agent
 vision_agent = Agent(
@@ -43,7 +43,7 @@ task3 = Task(
 )

 # Create Agents instance
-agents = Agents(
+agents = AgentTeam(
    agents=[vision_agent],
    tasks=[task1, task2, task3],
    process="sequential"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 import time

 def get_time_check():
@@ -93,7 +93,7 @@ synthesize_task = Task(
 )

 # Create workflow manager
-workflow = Agents(
+workflow = AgentTeam(
    agents=[router, worker1, worker2, worker3, synthesizer],
    tasks=[router_task, worker1_task, worker2_task, worker3_task, synthesize_task],
    process="workflow", output="verbose"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from datetime import datetime
 import asyncio

@@ -75,7 +75,7 @@ aggregate_task = Task(
 async def main():

    # Create workflow manager
-    workflow = Agents(
+    workflow = AgentTeam(
        agents=[agent1, agent2, agent3, aggregator],
        tasks=[task1, task2, task3, aggregate_task],
        process="workflow"
@@ -64,7 +64,7 @@ final_task = Task(
 )

 # Create the workflow manager
-workflow = Agents(
+workflow = AgentTeam(
    agents=[agent1, agent2, agent3],
    tasks=[initial_task, analysis_task, final_task],
    process="workflow",  # Use workflow process type
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents, Tools
+from praisonaiagents import Agent, Task, AgentTeam, Tools
 from pydantic import BaseModel

 class AnalysisReport(BaseModel):
@@ -44,7 +44,7 @@ analysis_task = Task(
 )

 # Initialize and run agents
-agents = Agents(
+agents = AgentTeam(
    agents=[researcher, analyst],
    tasks=[research_task, analysis_task],
    process="sequential",
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 import os
 import requests
 from typing import Any, Dict, List, Optional
@@ -106,7 +106,7 @@ task = Task(
 )

 # Create and start the workflow
-agents = Agents(
+agents = AgentTeam(
    agents=[agent],
    tasks=[task], output="verbose"
 )
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import get_article, get_news_sources, get_articles_from_source, get_trending_topics

 # Create Wikipedia agent
@@ -22,7 +22,7 @@ news_task = Task(


 # Run agent
-agents = Agents(
+agents = AgentTeam(
    agents=[news_agent],
    tasks=[news_task],
    process="sequential"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from typing import List, Dict
 from duckduckgo_search import DDGS

@@ -64,7 +64,7 @@ validate_task = Task(
 )

 # 4. AI Agents Workflow
-agents = Agents(
+agents = AgentTeam(
    agents=[data_agent],
    tasks=[collect_task, validate_task],
    process="workflow"
@@ -1,4 +1,4 @@
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 import random
 from typing import List, Dict, Union
 import json
@@ -225,7 +225,7 @@ process_task = Task(
 )

 # Create Agents instance with workflow process
-workflow = Agents(
+workflow = AgentTeam(
    agents=[data_agent, process_agent],
    tasks=[collect_task, validate_task, process_task],
    process="workflow"
@@ -12,7 +12,7 @@ Features demonstrated:
 - Quality assurance workflows
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.task import TaskOutput
 from typing import Tuple, Any
 import re
@@ -181,7 +181,7 @@ llm_guardrail_task = Task(
 )

 # Execute tasks with guardrails
-agents = Agents(
+agents = AgentTeam(
    agents=[email_agent, content_agent, business_agent, research_agent, llm_guardrail_agent],
    tasks=[email_task, content_task, business_task, research_task, llm_guardrail_task], output="verbose"
 )
@@ -5,7 +5,7 @@ This example demonstrates production guardrail patterns using PraisonAI's
 built-in validation and safety mechanisms for secure agent operations.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import internet_search

 print("=== Production Guardrails Patterns Example ===\n")
@@ -5,7 +5,7 @@ This example demonstrates an advanced system that dynamically creates agents and
 based on user inputs, including conditional logic, custom configurations, and file output.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import duckduckgo
 import os
 from typing import Dict, List
@@ -137,7 +137,7 @@ class DynamicAgentSystem:
        
        # Run the system
        print(f"\n🚀 Starting {process} analysis for '{inputs['topic']}'...")
-        praison_agents = Agents(
+        praison_agents = AgentTeam(
            agents=agents,
            tasks=tasks,
            process=process,
@@ -6,7 +6,7 @@ to create flexible agent configurations that can be pre-configured via environme
 """

 import os
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Set via environment or use default
 default_topic = os.getenv("RESEARCH_TOPIC", "AI trends")
@@ -46,7 +46,7 @@ print(f"  - Max Retries: {max_retries}")
 print("\n" + "="*50 + "\n")

 # Run agents
-agents = Agents(agents=[agent], tasks=[task])
+agents = AgentTeam(agents=[agent], tasks=[task])
 result = agents.start()

 # Save to environment-specified location if provided
@@ -5,7 +5,7 @@ This example shows how to use multiple user inputs to create a more sophisticate
 agent system with tools, multiple agents, and context passing between tasks.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import duckduckgo

 # Get multiple inputs
@@ -47,7 +47,7 @@ analyze_task = Task(
 )

 # Run sequential process
-agents = Agents(
+agents = AgentTeam(
    agents=[search_agent, analysis_agent],
    tasks=[search_task, analyze_task],
    process="sequential"
@@ -5,7 +5,7 @@ This example demonstrates how to use basic user input to create dynamic agents a
 The user is prompted for a search query, and the agent searches for information about it.
 """

-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam

 # Get user input
 user_query = input("What would you like to search for? ")
@@ -26,5 +26,5 @@ task = Task(
 )

 # Run
-agents = Agents(agents=[agent], tasks=[task])
+agents = AgentTeam(agents=[agent], tasks=[task])
 agents.start()
@@ -10,7 +10,7 @@ To run this example:
 """

 import streamlit as st
-from praisonaiagents import Agent, Task, Agents
+from praisonaiagents import Agent, Task, AgentTeam
 from praisonaiagents.tools import duckduckgo

 # Set page configuration
@@ -125,7 +125,7 @@ if st.button("🚀 Submit", type="primary", use_container_width=True):
                    )
                    
                    # Run agents
-                    agents = Agents(
+                    agents = AgentTeam(
                        agents=[agent],
                        tasks=[task],
                        process=process_type
Author	SHA1	Message	Date
Mervin Praison	c87dbf6330	Release v4.2.2	2026-01-31 20:27:06 +00:00
Mervin Praison	0a9b7cd137	Merge branch 'main' of https://github.com/MervinPraison/PraisonAI	2026-01-31 20:17:54 +00:00
Mervin Praison	3f69c77577	refactor: redirect logging function output to stderr in install script.	2026-01-31 20:17:54 +00:00
github-actions[bot]	f30b2b78c8	docs: auto-update api.md [skip ci]	2026-01-31 17:13:26 +00:00
Mervin Praison	08581d68d4	Release v4.2.1	2026-01-31 17:13:10 +00:00
github-actions[bot]	5bdf515ac3	docs: auto-update api.md [skip ci]	2026-01-31 15:10:45 +00:00
Mervin Praison	b02204e711	Release v4.2.0	2026-01-31 15:10:29 +00:00
github-actions[bot]	10e25b550d	docs: auto-update api.md [skip ci]	2026-01-31 08:34:41 +00:00
Mervin Praison	03d7b6ad11	Release v4.1.0	2026-01-31 08:34:24 +00:00
Mervin Praison	3dd0bc877c	Merge branch 'main' of https://github.com/MervinPraison/PraisonAI	2026-01-31 05:43:17 +00:00
Mervin Praison	037b2197f9	refactor: improve test isolation and mocking robustness by using `importlib.reload` and `pytest.raises` in unit tests.	2026-01-31 05:43:16 +00:00
github-actions[bot]	17968d7cc1	docs: auto-update api.md [skip ci]	2026-01-30 17:41:39 +00:00
Mervin Praison	17288679cc	Release v4.0.0	2026-01-30 17:41:19 +00:00
Mervin Praison	01859f40da	Release v3.12.3	2026-01-30 11:05:35 +00:00
github-actions[bot]	dda4822e4c	docs: auto-update api.md [skip ci]	2026-01-30 10:24:30 +00:00
Mervin Praison	a14ca673da	Release v3.12.2	2026-01-30 10:24:14 +00:00
github-actions[bot]	02d9d1e04f	docs: auto-update api.md [skip ci]	2026-01-30 08:31:24 +00:00
Mervin Praison	d3ee549ccc	Release v3.12.1	2026-01-30 08:31:09 +00:00
github-actions[bot]	63fbd04af3	docs: auto-update api.md [skip ci]	2026-01-30 08:00:39 +00:00
Mervin Praison	51f95ad904	Release v3.12.0	2026-01-30 08:00:22 +00:00
Mervin Praison	44b800df0e	Release v3.11.14	2026-01-30 05:27:32 +00:00
Mervin Praison	6e3a99b8b6	Release v3.11.13	2026-01-29 20:52:07 +00:00
Mervin Praison	b7d53b8f11	Release v3.11.12	2026-01-29 18:23:32 +00:00
Mervin Praison	643fac5762	Release v3.11.11	2026-01-29 18:07:10 +00:00
Mervin Praison	92b71cbc8f	Release v3.11.10	2026-01-29 17:59:29 +00:00
Mervin Praison	d7555ba1b2	Release v3.11.9	2026-01-29 17:53:32 +00:00
github-actions[bot]	22dd13ec66	docs: auto-update api.md [skip ci]	2026-01-29 17:40:47 +00:00
Mervin Praison	ba40e818e4	Release v3.11.8	2026-01-29 17:40:31 +00:00
Mervin Praison	12f829321c	update	2026-01-29 16:39:37 +00:00
Mervin Praison	149ed5bd94	refactor(docker): move bot services to dedicated docker/bots/ folder - Create docker/bots/ with own Dockerfile, docker-compose.yml, README - Remove bot services from main docker-compose.yml - Add .env.template with bot tokens - Add README with setup instructions for Slack/Discord/Telegram	2026-01-29 16:16:31 +00:00
Mervin Praison	15f2937dd5	feat(docker): add bot Dockerfile and services - Add Dockerfile.bot for Slack/Discord/Telegram bots - Add slack-bot, discord-bot, telegram-bot services to docker-compose - Add bot tokens to .env.template - Secrets passed at runtime via environment variables	2026-01-29 16:15:23 +00:00
Mervin Praison	d28199a18d	feat(bots): fix asyncio error and add thread configuration - Fix asyncio.run() error by using run_in_executor() for sync agent.chat() - Add reply_in_thread config option (default: False for inline replies) - Add thread_threshold for auto-threading long responses (default: 500 chars) - Add INFO logging for message received/sent flow	2026-01-29 16:11:21 +00:00
Mervin Praison	0d3d6bb852	Release v3.11.4	2026-01-29 15:18:30 +00:00
Mervin Praison	5f93f83c9f	fix: register bot/gateway/sandbox commands in CLI - Add 'bot', 'gateway', 'sandbox', 'wizard', 'migrate', 'security', 'persistence' to LEGACY_COMMANDS in legacy.py - Add same commands to special_commands list in main.py:797 (argparse fix) - Fix handle_bot_command to parse list args from main.py - 'praisonai bot slack --token $TOKEN' now works correctly	2026-01-29 14:23:40 +00:00
Mervin Praison	c9786fbd1e	Release v3.11.3	2026-01-29 14:17:18 +00:00
github-actions[bot]	95e8e38998	docs: auto-update api.md [skip ci]	2026-01-29 13:45:28 +00:00
Mervin Praison	73f8961e61	Release v3.11.2	2026-01-29 13:45:08 +00:00
github-actions[bot]	4caf10a982	docs: auto-update api.md [skip ci]	2026-01-29 12:31:08 +00:00
Mervin Praison	fb42a1010a	Release v3.11.1	2026-01-29 12:30:51 +00:00
github-actions[bot]	fe60dd40af	docs: auto-update api.md [skip ci]	2026-01-29 10:45:19 +00:00
Mervin Praison	7f37d754a7	Release v3.11.0	2026-01-29 10:45:00 +00:00
github-actions[bot]	26f60fb056	docs: auto-update api.md [skip ci]	2026-01-28 13:20:05 +00:00
Mervin Praison	0f0b640184	Release v3.10.27	2026-01-28 13:19:48 +00:00
Mervin Praison	d857dfc6b7	Release v3.10.26	2026-01-27 15:07:21 +00:00
github-actions[bot]	0135a9e09f	docs: auto-update api.md [skip ci]	2026-01-27 05:52:59 +00:00
Mervin Praison	847b5e6372	Release v3.10.25	2026-01-27 05:52:43 +00:00
github-actions[bot]	05a7265c4e	docs: auto-update api.md [skip ci]	2026-01-26 18:39:42 +00:00
Mervin Praison	de1734c29a	Release v3.10.24	2026-01-26 18:39:28 +00:00
github-actions[bot]	f0e91b11ae	docs: auto-update api.md [skip ci]	2026-01-26 17:47:05 +00:00
Mervin Praison	6e1a9143e2	Release v3.10.23	2026-01-26 17:46:49 +00:00
github-actions[bot]	10d76d3a85	docs: auto-update api.md [skip ci]	2026-01-26 17:06:34 +00:00
Mervin Praison	a38a9c06c6	Release v3.10.22	2026-01-26 17:06:19 +00:00
github-actions[bot]	9c90416ab5	docs: auto-update api.md [skip ci]	2026-01-26 08:08:44 +00:00
Mervin Praison	efa5247344	Release v3.10.21	2026-01-26 08:08:18 +00:00
Mervin Praison	720213d82d	Merge pull request #1100 from MervinPraison/pr-1099-fix Pr 1099 fix	2026-01-25 00:47:27 +00:00
Loganaden Velvindron	f6af16ef5e	Fix range check	2026-01-25 00:46:37 +00:00
Loganaden Velvindron	8439b98ec2	Fix CVE-2026-22218	2026-01-25 00:45:51 +00:00
Loganaden Velvindron	92271fc118	Fix CVE-2026-22218 Allow building with chainlit 2.9.4 to fix CVE-2026-22218	2026-01-25 00:45:32 +00:00
Mervin Praison	1b43dc6a4b	Update naming convention guide with list_X pattern and clarify decorator usage	2026-01-25 00:43:02 +00:00
Mervin Praison	929cefa55e	Release v3.10.20	2026-01-25 00:36:03 +00:00
Mervin Praison	225843e39b	Release v3.10.19	2026-01-25 00:25:39 +00:00
Mervin Praison	77913183a9	Release v3.10.18	2026-01-24 14:33:15 +00:00
Mervin Praison	e5b5d747f4	Release v3.10.17	2026-01-24 09:26:02 +00:00
Mervin Praison	8cb779c51c	Release v3.10.16	2026-01-24 07:32:55 +00:00
github-actions[bot]	020ca46c90	docs: auto-update api.md [skip ci]	2026-01-24 07:01:25 +00:00
Mervin Praison	557e243eed	Release v3.10.15	2026-01-24 07:01:13 +00:00
Mervin Praison	0628204fce	Update README.md	2026-01-23 14:46:55 +00:00
Mervin Praison	2a11bf5221	Release v3.10.14	2026-01-23 12:58:40 +00:00
github-actions[bot]	ecc2182d24	docs: auto-update api.md [skip ci]	2026-01-23 12:16:33 +00:00
Mervin Praison	c6b91b2d57	Release v3.10.13	2026-01-23 12:16:16 +00:00
github-actions[bot]	a5ed17945f	docs: auto-update api.md [skip ci]	2026-01-23 10:33:02 +00:00
Mervin Praison	ff3ca3052d	Release v3.10.12	2026-01-23 10:32:48 +00:00
github-actions[bot]	6f1f4a5363	docs: auto-update api.md [skip ci]	2026-01-23 07:32:54 +00:00
Mervin Praison	dd9dfa5970	Release v3.10.11	2026-01-23 07:32:37 +00:00
Mervin Praison	5f4fc8fa2f	Release v3.10.10	2026-01-23 05:18:03 +00:00
github-actions[bot]	dd9dd5d5d9	docs: auto-update api.md [skip ci]	2026-01-23 03:47:00 +00:00
Mervin Praison	d2c629b82c	Release v3.10.9	2026-01-23 03:46:46 +00:00
Mervin Praison	609ac5f7a6	Release v3.10.8	2026-01-22 14:13:38 +00:00
Mervin Praison	75c72e909e	Release v3.10.7	2026-01-22 13:47:01 +00:00
Mervin Praison	9492ff8de1	Release v3.10.6	2026-01-22 11:24:49 +00:00
Mervin Praison	a0a3aa1a53	Release v3.10.5	2026-01-22 08:30:15 +00:00
Mervin Praison	6a20001551	Refactor port availability test to use `socket.socket` and relax import and profiling time assertions.	2026-01-22 07:49:51 +00:00
Mervin Praison	577295c147	Release v3.10.4	2026-01-22 07:06:28 +00:00
github-actions[bot]	06f64a551c	docs: auto-update api.md [skip ci]	2026-01-22 05:16:01 +00:00
Mervin Praison	928b824180	Release v3.10.3	2026-01-22 05:15:48 +00:00
github-actions[bot]	1631973256	docs: auto-update api.md [skip ci]	2026-01-21 17:30:54 +00:00
Mervin Praison	a9d7f6fd76	Release v3.10.2	2026-01-21 17:30:30 +00:00
Mervin Praison	cc5360e60e	Release v3.10.1	2026-01-21 15:01:51 +00:00
Mervin Praison	863dd9bc34	Release v3.10.0	2026-01-21 13:11:42 +00:00
Mervin Praison	8c39769971	Release v3.9.35	2026-01-21 05:41:54 +00:00
Mervin Praison	93904f8530	Release v3.9.34	2026-01-20 20:40:03 +00:00
Mervin Praison	ffc3775446	Release v3.9.33	2026-01-20 19:01:01 +00:00
Mervin Praison	86e76b7a3e	Release v3.9.32	2026-01-20 14:56:13 +00:00
Mervin Praison	b18d6007c2	Release v3.9.31	2026-01-20 12:43:18 +00:00
github-actions[bot]	c656af3166	docs: auto-update api.md [skip ci]	2026-01-20 12:20:08 +00:00
Mervin Praison	3c2fff05dd	Release v3.9.30	2026-01-20 12:19:52 +00:00
github-actions[bot]	092097faa6	docs: auto-update api.md [skip ci]	2026-01-20 08:17:03 +00:00
Mervin Praison	068ddecb91	Release v3.9.29	2026-01-20 08:16:43 +00:00
github-actions[bot]	444d14cb54	docs: auto-update api.md [skip ci]	2026-01-20 06:59:39 +00:00