Release v2.4.3

Release v2.4.2
Update database initialization to use db() shortcut and expand tools table with 100+ tools
2026-11-07 17:33:33 -10:00 · 2025-12-26 01:01:30 +00:00 · 2025-12-25 00:29:49 +00:00 · 2025-12-25 00:24:48 +00:00 · 2025-12-24 15:00:45 +00:00 · 2025-12-24 08:02:48 +00:00
172 changed files with 29163 additions and 343 deletions
@@ -261,6 +261,12 @@ npm install praisonai
 | ↳ 100+ LLM Support | [Example](examples/python/providers/openai/openai_gpt4_example.py) | [📖](https://docs.praison.ai/models) |
 | ↳ Callback Agents | [Example](examples/python/general/advanced-callback-systems.py) | [📖](https://docs.praison.ai/features/callbacks) |
 | ↳ Hooks | [Example](#9-hooks) | [📖](https://docs.praison.ai/features/hooks) |
+| ↳ Shadow Git Checkpoints | [Example](#10-shadow-git-checkpoints) | [📖](https://docs.praison.ai/features/checkpoints) |
+| ↳ Background Tasks | [Example](examples/background/basic_background.py) | [📖](https://docs.praison.ai/features/background-tasks) |
+| ↳ Policy Engine | [Example](examples/policy/basic_policy.py) | [📖](https://docs.praison.ai/features/policy-engine) |
+| ↳ Thinking Budgets | [Example](examples/thinking/basic_thinking.py) | [📖](https://docs.praison.ai/features/thinking-budgets) |
+| ↳ Output Styles | [Example](examples/output/basic_output.py) | [📖](https://docs.praison.ai/features/output-styles) |
+| ↳ Context Compaction | [Example](examples/compaction/basic_compaction.py) | [📖](https://docs.praison.ai/features/context-compaction) |
 | **📊 Monitoring & Management** | | |
 | ↳ Sessions Management | [Example](examples/python/sessions/comprehensive-session-management.py) | [📖](https://docs.praison.ai/features/sessions) |
 | ↳ Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/docs/cli/session) |
@@ -278,6 +284,12 @@ npm install praisonai
 | ↳ Git Integration | [Example](examples/python/cli/git_integration_example.py) | [📖](https://docs.praison.ai/docs/cli/git-integration) |
 | ↳ Sandbox Execution | [Example](examples/python/cli/sandbox_execution_example.py) | [📖](https://docs.praison.ai/docs/cli/sandbox-execution) |
 | ↳ CLI Compare | [Example](examples/compare/cli_compare_basic.py) | [📖](https://docs.praison.ai/docs/cli/compare) |
+| ↳ Profile/Benchmark | [Example](#profile-benchmark) | [📖](https://docs.praison.ai/docs/cli/profile) |
+| ↳ Auto Mode | [Example](#auto-mode) | [📖](https://docs.praison.ai/docs/cli/auto) |
+| ↳ Init | [Example](#init) | [📖](https://docs.praison.ai/docs/cli/init) |
+| ↳ File Input | [Example](#file-input) | [📖](https://docs.praison.ai/docs/cli/file-input) |
+| ↳ Final Agent | [Example](#final-agent) | [📖](https://docs.praison.ai/docs/cli/final-agent) |
+| ↳ Max Tokens | [Example](#max-tokens) | [📖](https://docs.praison.ai/docs/cli/max-tokens) |
 | **🧪 Evaluation** | | |
 | ↳ Accuracy Evaluation | [Example](examples/eval/accuracy_example.py) | [📖](https://docs.praison.ai/docs/cli/eval) |
 | ↳ Performance Evaluation | [Example](examples/eval/performance_example.py) | [📖](https://docs.praison.ai/docs/cli/eval) |
@@ -857,21 +869,258 @@ callbacks:

 ### 9. Hooks

-Configure in `.praison/hooks.json`:
+Intercept and modify agent behavior at various lifecycle points:

 ```python
-from praisonaiagents.memory import HooksManager
+from praisonaiagents.hooks import (
+    HookRegistry, HookRunner, HookEvent, HookResult,
+    BeforeToolInput
+)

-hooks = HooksManager()
+# Create a hook registry
+registry = HookRegistry()

-# Register Python hooks
-hooks.register("pre_write_code", lambda ctx: print(f"Writing {ctx['file']}"))
+# Log all tool calls
+@registry.on(HookEvent.BEFORE_TOOL)
+def log_tools(event_data: BeforeToolInput) -> HookResult:
+    print(f"Tool: {event_data.tool_name}")
+    return HookResult.allow()
+
+# Block dangerous operations
+@registry.on(HookEvent.BEFORE_TOOL)
+def security_check(event_data: BeforeToolInput) -> HookResult:
+    if "delete" in event_data.tool_name.lower():
+        return HookResult.deny("Delete operations blocked")
+    return HookResult.allow()

 # Execute hooks
-result = hooks.execute("pre_write_code", {"file": "main.py"})
+runner = HookRunner(registry)
 ```

-### 10. Field Names Reference (A-I-G-S)
+**CLI Commands:**
+```bash
+praisonai hooks list                    # List registered hooks
+praisonai hooks test before_tool        # Test hooks for an event
+praisonai hooks run "echo test"         # Run a command hook
+praisonai hooks validate hooks.json     # Validate configuration
+```
+
+
+### 10. Shadow Git Checkpoints
+
+File-level undo/restore using shadow git:
+
+```python
+from praisonaiagents.checkpoints import CheckpointService
+
+service = CheckpointService(workspace_dir="./my_project")
+await service.initialize()
+
+# Save checkpoint before changes
+result = await service.save("Before refactoring")
+
+# Make changes...
+
+# Restore if needed
+await service.restore(result.checkpoint.id)
+
+# View diff
+diff = await service.diff()
+```
+
+**CLI Commands:**
+```bash
+praisonai checkpoint save "Before changes"  # Save checkpoint
+praisonai checkpoint list                   # List checkpoints
+praisonai checkpoint diff                   # Show changes
+praisonai checkpoint restore abc123         # Restore to checkpoint
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/checkpoints)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/checkpoint)
+- [💻 Example](examples/checkpoints/basic_checkpoints.py)
+
+---
+
+### 11. Background Tasks
+
+Run agent tasks asynchronously without blocking:
+
+```python
+import asyncio
+from praisonaiagents.background import BackgroundRunner, BackgroundConfig
+
+async def main():
+    config = BackgroundConfig(max_concurrent_tasks=3)
+    runner = BackgroundRunner(config=config)
+    
+    async def my_task(name: str) -> str:
+        await asyncio.sleep(2)
+        return f"Task {name} completed"
+    
+    task = await runner.submit(my_task, args=("example",), name="my_task")
+    await task.wait(timeout=10.0)
+    print(task.result)
+
+asyncio.run(main())
+```
+
+**CLI Commands:**
+```bash
+praisonai background list          # List running tasks
+praisonai background status <id>   # Check task status
+praisonai background cancel <id>   # Cancel a task
+praisonai background clear         # Clear completed tasks
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/background-tasks)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/background)
+- [💻 Example](examples/background/basic_background.py)
+
+---
+
+### 12. Policy Engine
+
+Control what agents can and cannot do with policy-based execution:
+
+```python
+from praisonaiagents.policy import (
+    PolicyEngine, Policy, PolicyRule, PolicyAction
+)
+
+engine = PolicyEngine()
+
+policy = Policy(
+    name="no_delete",
+    rules=[
+        PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*",
+            reason="Delete operations blocked"
+        )
+    ]
+)
+engine.add_policy(policy)
+
+result = engine.check("tool:delete_file", {})
+print(f"Allowed: {result.allowed}")
+```
+
+**CLI Commands:**
+```bash
+praisonai policy list                  # List policies
+praisonai policy check "tool:name"     # Check if allowed
+praisonai policy init                  # Create template
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/policy-engine)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/policy)
+- [💻 Example](examples/policy/basic_policy.py)
+
+---
+
+### 13. Thinking Budgets
+
+Configure token budgets for extended thinking:
+
+```python
+from praisonaiagents.thinking import ThinkingBudget, ThinkingTracker
+
+# Use predefined levels
+budget = ThinkingBudget.high()  # 16,000 tokens
+
+# Track usage
+tracker = ThinkingTracker()
+session = tracker.start_session(budget_tokens=16000)
+tracker.end_session(session, tokens_used=12000)
+
+summary = tracker.get_summary()
+print(f"Utilization: {summary['average_utilization']:.1%}")
+```
+
+**CLI Commands:**
+```bash
+praisonai thinking status      # Show current budget
+praisonai thinking set high    # Set budget level
+praisonai thinking stats       # Show usage statistics
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/thinking-budgets)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/thinking)
+- [💻 Example](examples/thinking/basic_thinking.py)
+
+---
+
+### 14. Output Styles
+
+Configure how agents format their responses:
+
+```python
+from praisonaiagents.output import OutputStyle, OutputFormatter
+
+# Use preset styles
+style = OutputStyle.concise()
+formatter = OutputFormatter(style)
+
+# Format output
+text = "# Hello\n\nThis is **bold** text."
+plain = formatter.format(text)
+print(plain)
+```
+
+**CLI Commands:**
+```bash
+praisonai output status        # Show current style
+praisonai output set concise   # Set output style
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/output-styles)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/output-style)
+- [💻 Example](examples/output/basic_output.py)
+
+---
+
+### 15. Context Compaction
+
+Automatically manage context window size:
+
+```python
+from praisonaiagents.compaction import (
+    ContextCompactor, CompactionStrategy
+)
+
+compactor = ContextCompactor(
+    max_tokens=4000,
+    strategy=CompactionStrategy.SLIDING,
+    preserve_recent=3
+)
+
+messages = [...]  # Your conversation history
+compacted, result = compactor.compact(messages)
+
+print(f"Compression: {result.compression_ratio:.1%}")
+```
+
+**CLI Commands:**
+```bash
+praisonai compaction status        # Show settings
+praisonai compaction set sliding   # Set strategy
+praisonai compaction stats         # Show statistics
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/context-compaction)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/compaction)
+- [💻 Example](examples/compaction/basic_compaction.py)
+
+---
+
+### 16. Field Names Reference (A-I-G-S)

 PraisonAI accepts both old (agents.yaml) and new (workflow.yaml) field names. Use the **canonical names** for new projects:

@@ -905,7 +1154,7 @@ steps:                         # Define steps (not 'tasks')

 > **Note:** The parser accepts both old and new names. Run `praisonai workflow validate <file.yaml>` to see suggestions for canonical names.

-### 11. Extended agents.yaml with Workflow Patterns
+### 12. Extended agents.yaml with Workflow Patterns

 **Feature Parity:** Both `agents.yaml` and `workflow.yaml` now support the same features:
 - All workflow patterns (route, parallel, loop, repeat)
@@ -981,6 +1230,124 @@ Run with the same simple command:
 praisonai agents.yaml
 ```

+### 12. MCP (Model Context Protocol)
+
+PraisonAI supports MCP Protocol Revision 2025-11-25 with multiple transports.
+
+#### MCP Client (Consume MCP Servers)
+```python
+from praisonaiagents import Agent, MCP
+
+# stdio - Local NPX/Python servers
+agent = Agent(tools=MCP("npx @modelcontextprotocol/server-memory"))
+
+# Streamable HTTP - Production servers
+agent = Agent(tools=MCP("https://api.example.com/mcp"))
+
+# WebSocket - Real-time bidirectional
+agent = Agent(tools=MCP("wss://api.example.com/mcp", auth_token="token"))
+
+# SSE (Legacy) - Backward compatibility
+agent = Agent(tools=MCP("http://localhost:8080/sse"))
+
+# With environment variables
+agent = Agent(
+    tools=MCP(
+        command="npx",
+        args=["-y", "@modelcontextprotocol/server-brave-search"],
+        env={"BRAVE_API_KEY": "your-key"}
+    )
+)
+
+# Multiple MCP servers + regular functions
+def my_custom_tool(query: str) -> str:
+    """Custom tool function."""
+    return f"Result: {query}"
+
+agent = Agent(
+    name="MultiToolAgent",
+    instructions="Agent with multiple MCP servers",
+    tools=[
+        MCP("uvx mcp-server-time"),                    # Time tools
+        MCP("npx @modelcontextprotocol/server-memory"), # Memory tools
+        my_custom_tool                                  # Regular function
+    ]
+)
+```
+
+#### MCP Server (Expose Tools as MCP Server)
+
+Expose your Python functions as MCP tools for Claude Desktop, Cursor, and other MCP clients:
+
+```python
+from praisonaiagents.mcp import ToolsMCPServer
+
+def search_web(query: str, max_results: int = 5) -> dict:
+    """Search the web for information."""
+    return {"results": [f"Result for {query}"]}
+
+def calculate(expression: str) -> dict:
+    """Evaluate a mathematical expression."""
+    return {"result": eval(expression)}
+
+# Create and run MCP server
+server = ToolsMCPServer(name="my-tools")
+server.register_tools([search_web, calculate])
+server.run()  # stdio for Claude Desktop
+# server.run_sse(host="0.0.0.0", port=8080)  # SSE for web clients
+```
+
+#### MCP Features
+| Feature | Description |
+|---------|-------------|
+| Session Management | Automatic Mcp-Session-Id handling |
+| Protocol Versioning | Mcp-Protocol-Version header |
+| Resumability | SSE stream recovery via Last-Event-ID |
+| Security | Origin validation, DNS rebinding prevention |
+| WebSocket | Auto-reconnect with exponential backoff |
+
+### 13. A2A (Agent2Agent Protocol)
+
+PraisonAI supports the [A2A Protocol](https://a2a-protocol.org) for agent-to-agent communication, enabling your agents to be discovered and collaborate with other AI agents.
+
+#### A2A Server (Expose Agent as A2A Server)
+```python
+from praisonaiagents import Agent, A2A
+from fastapi import FastAPI
+
+# Create an agent with tools
+def search_web(query: str) -> str:
+    """Search the web for information."""
+    return f"Results for: {query}"
+
+agent = Agent(
+    name="Research Assistant",
+    role="Research Analyst",
+    goal="Help users research topics",
+    tools=[search_web]
+)
+
+# Expose as A2A Server
+a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
+
+app = FastAPI()
+app.include_router(a2a.get_router())
+
+# Run: uvicorn app:app --reload
+# Agent Card: GET /.well-known/agent.json
+# Status: GET /status
+```
+
+#### A2A Features
+| Feature | Description |
+|---------|-------------|
+| Agent Card | JSON metadata for agent discovery |
+| Skills Extraction | Auto-generate skills from tools |
+| Task Management | Stateful task lifecycle |
+| Streaming | SSE streaming for real-time updates |
+
+> **Documentation**: [docs.praison.ai/a2a](https://docs.praison.ai/a2a) | **Examples**: [examples/python/a2a](https://github.com/MervinPraison/PraisonAI/tree/main/examples/python/a2a)
+
 ---

 ## 🎯 CLI / No-Code Interface
@@ -1730,124 +2097,6 @@ agent = Agent(
 | Web Fetch | Anthropic |
 | Prompt Caching | OpenAI (auto), Anthropic, Bedrock, Deepseek |

-## MCP (Model Context Protocol)
-
-PraisonAI supports MCP Protocol Revision 2025-11-25 with multiple transports.
-
-### MCP Client (Consume MCP Servers)
-```python
-from praisonaiagents import Agent, MCP
-
-# stdio - Local NPX/Python servers
-agent = Agent(tools=MCP("npx @modelcontextprotocol/server-memory"))
-
-# Streamable HTTP - Production servers
-agent = Agent(tools=MCP("https://api.example.com/mcp"))
-
-# WebSocket - Real-time bidirectional
-agent = Agent(tools=MCP("wss://api.example.com/mcp", auth_token="token"))
-
-# SSE (Legacy) - Backward compatibility
-agent = Agent(tools=MCP("http://localhost:8080/sse"))
-
-# With environment variables
-agent = Agent(
-    tools=MCP(
-        command="npx",
-        args=["-y", "@modelcontextprotocol/server-brave-search"],
-        env={"BRAVE_API_KEY": "your-key"}
-    )
-)
-
-# Multiple MCP servers + regular functions
-def my_custom_tool(query: str) -> str:
-    """Custom tool function."""
-    return f"Result: {query}"
-
-agent = Agent(
-    name="MultiToolAgent",
-    instructions="Agent with multiple MCP servers",
-    tools=[
-        MCP("uvx mcp-server-time"),                    # Time tools
-        MCP("npx @modelcontextprotocol/server-memory"), # Memory tools
-        my_custom_tool                                  # Regular function
-    ]
-)
-```
-
-### MCP Server (Expose Tools as MCP Server)
-
-Expose your Python functions as MCP tools for Claude Desktop, Cursor, and other MCP clients:
-
-```python
-from praisonaiagents.mcp import ToolsMCPServer
-
-def search_web(query: str, max_results: int = 5) -> dict:
-    """Search the web for information."""
-    return {"results": [f"Result for {query}"]}
-
-def calculate(expression: str) -> dict:
-    """Evaluate a mathematical expression."""
-    return {"result": eval(expression)}
-
-# Create and run MCP server
-server = ToolsMCPServer(name="my-tools")
-server.register_tools([search_web, calculate])
-server.run()  # stdio for Claude Desktop
-# server.run_sse(host="0.0.0.0", port=8080)  # SSE for web clients
-```
-
-### MCP Features
-| Feature | Description |
-|---------|-------------|
-| Session Management | Automatic Mcp-Session-Id handling |
-| Protocol Versioning | Mcp-Protocol-Version header |
-| Resumability | SSE stream recovery via Last-Event-ID |
-| Security | Origin validation, DNS rebinding prevention |
-| WebSocket | Auto-reconnect with exponential backoff |
-
-## A2A (Agent2Agent Protocol)
-
-PraisonAI supports the [A2A Protocol](https://a2a-protocol.org) for agent-to-agent communication, enabling your agents to be discovered and collaborate with other AI agents.
-
-### A2A Server (Expose Agent as A2A Server)
-```python
-from praisonaiagents import Agent, A2A
-from fastapi import FastAPI
-
-# Create an agent with tools
-def search_web(query: str) -> str:
-    """Search the web for information."""
-    return f"Results for: {query}"
-
-agent = Agent(
-    name="Research Assistant",
-    role="Research Analyst",
-    goal="Help users research topics",
-    tools=[search_web]
-)
-
-# Expose as A2A Server
-a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
-
-app = FastAPI()
-app.include_router(a2a.get_router())
-
-# Run: uvicorn app:app --reload
-# Agent Card: GET /.well-known/agent.json
-# Status: GET /status
-```
-
-### A2A Features
-| Feature | Description |
-|---------|-------------|
-| Agent Card | JSON metadata for agent discovery |
-| Skills Extraction | Auto-generate skills from tools |
-| Task Management | Stateful task lifecycle |
-| Streaming | SSE streaming for real-time updates |
-
-> **Documentation**: [docs.praison.ai/a2a](https://docs.praison.ai/a2a) | **Examples**: [examples/python/a2a](https://github.com/MervinPraison/PraisonAI/tree/main/examples/python/a2a)
-
 ## CLI Features

 | Feature | Docs |
@@ -2475,6 +2724,103 @@ PraisonAI provides zero-dependency persistent memory for agents. For detailed ex

 ---

+## 💾 Persistence (Databases)
+
+Enable automatic conversation persistence with 2 lines of code:
+
+```python
+from praisonaiagents import Agent, db
+
+agent = Agent(
+    name="Assistant",
+    db=db(database_url="postgresql://localhost/mydb"),  # db(...) shortcut
+    session_id="my-session"  # Optional: defaults to per-hour ID (YYYYMMDDHH)
+)
+agent.chat("Hello!")  # Auto-persists messages, runs, traces
+```
+
+### Persistence CLI Commands
+
+| Command | Description |
+|---------|-------------|
+| `praisonai persistence doctor` | Validate DB connectivity |
+| `praisonai persistence run` | Run agent with persistence |
+| `praisonai persistence resume` | Resume existing session |
+| `praisonai persistence export` | Export session to JSONL |
+| `praisonai persistence import` | Import session from JSONL |
+| `praisonai persistence migrate` | Apply schema migrations |
+| `praisonai persistence status` | Show schema status |
+
+### Databases Table
+
+| Database | Store Type | Install | Example | Docs |
+|----------|------------|---------|---------|------|
+| PostgreSQL | Conversation | `pip install "praisonai[tools]"` | [simple_db_agent.py](examples/persistence/simple_db_agent.py) | [docs](https://docs.praison.ai/docs/databases/postgres) |
+| MySQL | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| SQLite | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| SingleStore | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Supabase | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| SurrealDB | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Qdrant | Knowledge | `pip install "praisonai[tools]"` | [knowledge_qdrant.py](examples/persistence/knowledge_qdrant.py) | [docs](https://docs.praison.ai/docs/databases/qdrant) |
+| ChromaDB | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Pinecone | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Weaviate | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| LanceDB | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Milvus | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| PGVector | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Redis Vector | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Cassandra | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| ClickHouse | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Redis | State | `pip install "praisonai[tools]"` | [state_redis.py](examples/persistence/state_redis.py) | [docs](https://docs.praison.ai/docs/databases/redis) |
+| MongoDB | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| DynamoDB | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Firestore | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Upstash | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Memory | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+
+---
+
+## 🔧 Tools Table
+
+Install all tools with: `pip install "praisonai[tools]"`
+
+| Tool | Category | Import | Docs |
+|------|----------|--------|------|
+| Tavily | Web Search | `from praisonai_tools import TavilyTool` | [docs](https://docs.praison.ai/docs/tools/external/tavily) |
+| DuckDuckGo | Web Search | `from praisonai_tools import DuckDuckGoTool` | [docs](https://docs.praison.ai/docs/tools/external/duckduckgo) |
+| Exa | Web Search | `from praisonai_tools import ExaTool` | [docs](https://docs.praison.ai/docs/tools/external/exa) |
+| Serper | Web Search | `from praisonai_tools import SerperTool` | [docs](https://docs.praison.ai/docs/tools/external/serper) |
+| Jina | Web Reader | `from praisonai_tools import JinaTool` | [docs](https://docs.praison.ai/docs/tools/external/jina) |
+| Firecrawl | Web Scraping | `from praisonai_tools import FirecrawlTool` | [docs](https://docs.praison.ai/docs/tools/external/firecrawl) |
+| Crawl4AI | Web Scraping | `from praisonai_tools import Crawl4AITool` | [docs](https://docs.praison.ai/docs/tools/external/crawl4ai) |
+| Wikipedia | Knowledge | `from praisonai_tools import WikipediaTool` | [docs](https://docs.praison.ai/docs/tools/external/wikipedia) |
+| ArXiv | Research | `from praisonai_tools import ArxivTool` | [docs](https://docs.praison.ai/docs/tools/external/arxiv) |
+| HackerNews | News | `from praisonai_tools import HackerNewsTool` | [docs](https://docs.praison.ai/docs/tools/external/hackernews) |
+| YouTube | Media | `from praisonai_tools import YouTubeTool` | [docs](https://docs.praison.ai/docs/tools/external/youtube) |
+| Weather | Data | `from praisonai_tools import WeatherTool` | [docs](https://docs.praison.ai/docs/tools/external/weather) |
+| PostgreSQL | Database | `from praisonai_tools import PostgresTool` | [docs](https://docs.praison.ai/docs/tools/external/postgres) |
+| MySQL | Database | `from praisonai_tools import MySQLTool` | [docs](https://docs.praison.ai/docs/tools/external/mysql) |
+| SQLite | Database | `from praisonai_tools import SQLiteTool` | [docs](https://docs.praison.ai/docs/tools/external/sqlite) |
+| MongoDB | Database | `from praisonai_tools import MongoDBTool` | [docs](https://docs.praison.ai/docs/tools/external/mongodb) |
+| Redis | Database | `from praisonai_tools import RedisTool` | [docs](https://docs.praison.ai/docs/tools/external/redis) |
+| Qdrant | Vector DB | `from praisonai_tools import QdrantTool` | [docs](https://docs.praison.ai/docs/tools/external/qdrant) |
+| GitHub | DevOps | `from praisonai_tools import GitHubTool` | [docs](https://docs.praison.ai/docs/tools/external/github) |
+| Slack | Communication | `from praisonai_tools import SlackTool` | [docs](https://docs.praison.ai/docs/tools/external/slack) |
+| Discord | Communication | `from praisonai_tools import DiscordTool` | [docs](https://docs.praison.ai/docs/tools/external/discord) |
+| Telegram | Communication | `from praisonai_tools import TelegramTool` | [docs](https://docs.praison.ai/docs/tools/external/telegram) |
+| Email | Communication | `from praisonai_tools import EmailTool` | [docs](https://docs.praison.ai/docs/tools/external/email) |
+| Notion | Productivity | `from praisonai_tools import NotionTool` | [docs](https://docs.praison.ai/docs/tools/external/notion) |
+| File | File System | `from praisonai_tools import FileTool` | [docs](https://docs.praison.ai/docs/tools/external/file) |
+| Shell | System | `from praisonai_tools import ShellTool` | [docs](https://docs.praison.ai/docs/tools/external/shell) |
+| Python | Code | `from praisonai_tools import PythonTool` | [docs](https://docs.praison.ai/docs/tools/external/python) |
+| JSON | Data | `from praisonai_tools import JSONTool` | [docs](https://docs.praison.ai/docs/tools/external/json) |
+| CSV | Data | `from praisonai_tools import CSVTool` | [docs](https://docs.praison.ai/docs/tools/external/csv) |
+| Calculator | Math | `from praisonai_tools import CalculatorTool` | [docs](https://docs.praison.ai/docs/tools/external/calculator) |
+
+> See [full tools documentation](https://docs.praison.ai/docs/tools/tools) for all 100+ available tools.
+
+---
+
 ## 🎓 Video Tutorials

 Learn PraisonAI through our comprehensive video series:
@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
    praisonai_tools \
-    "praisonai>=2.3.80" \
+    "praisonai>=2.4.3" \
    "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>=2.3.80" \
+    "praisonai>=2.4.3" \
    "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>=2.3.80" \
+    "praisonai>=2.4.3" \
    "praisonai[ui]" \
    "praisonai[crewai]"

@@ -0,0 +1,92 @@
+#!/usr/bin/env python3
+"""
+Basic Background Tasks Example for PraisonAI Agents.
+
+This example demonstrates how to use the background task system to:
+1. Run tasks asynchronously
+2. Track task progress
+3. Cancel running tasks
+4. Handle task completion
+
+Usage:
+    python basic_background.py
+"""
+
+import asyncio
+import time
+
+from praisonaiagents.background import BackgroundRunner, BackgroundConfig, TaskStatus
+
+
+async def main():
+    print("=" * 60)
+    print("Background Tasks Demo")
+    print("=" * 60)
+    
+    # Create a background runner with config
+    config = BackgroundConfig(max_concurrent_tasks=3)
+    runner = BackgroundRunner(config=config)
+    
+    # Define some example tasks
+    def slow_task(duration: float, name: str) -> str:
+        """A slow task that simulates work."""
+        print(f"  🔄 Task '{name}' starting (will take {duration}s)")
+        time.sleep(duration)
+        return f"Task '{name}' completed after {duration}s"
+    
+    async def async_task(duration: float, name: str) -> str:
+        """An async task that simulates work."""
+        print(f"  🔄 Async task '{name}' starting (will take {duration}s)")
+        await asyncio.sleep(duration)
+        return f"Async task '{name}' completed after {duration}s"
+    
+    # Submit tasks
+    print("\n--- Submitting Tasks ---")
+    
+    task1 = await runner.submit(slow_task, args=(1.0, "quick-job"), name="task1")
+    print(f"✅ Submitted task 1: {task1.id[:8]}")
+    
+    task2 = await runner.submit(slow_task, args=(2.0, "medium-job"), name="task2")
+    print(f"✅ Submitted task 2: {task2.id[:8]}")
+    
+    task3 = await runner.submit(async_task, args=(1.5, "async-job"), name="task3")
+    print(f"✅ Submitted async task 3: {task3.id[:8]}")
+    
+    # List all tasks
+    print("\n--- Task Status ---")
+    for task in runner.tasks:
+        print(f"  [{task.id[:8]}] {task.status.value}")
+    
+    # Wait for task 1 to complete
+    print("\n--- Waiting for Task 1 ---")
+    await task1.wait(timeout=5.0)
+    print(f"✅ Task 1 result: {task1.result}")
+    
+    # Check status of all tasks
+    print("\n--- Updated Task Status ---")
+    for task in [task1, task2, task3]:
+        status = "✅" if task.status == TaskStatus.COMPLETED else "🔄"
+        print(f"  {status} [{task.id[:8]}] {task.status.value}")
+    
+    # Wait for all remaining tasks
+    print("\n--- Waiting for All Tasks ---")
+    await task2.wait(timeout=10.0)
+    await task3.wait(timeout=10.0)
+    
+    # Final status
+    print("\n--- Final Results ---")
+    for task in [task1, task2, task3]:
+        if task.result:
+            print(f"  ✅ {task.result}")
+    
+    # Cleanup
+    runner.clear_completed()
+    print("\n✅ Cleared completed tasks")
+    
+    print("\n" + "=" * 60)
+    print("Demo Complete!")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,110 @@
+#!/usr/bin/env python3
+"""
+Basic Checkpoints Example for PraisonAI Agents.
+
+This example demonstrates how to use the shadow git checkpointing system to:
+1. Save checkpoints before making changes
+2. List available checkpoints
+3. View diffs between checkpoints
+4. Restore to a previous checkpoint
+
+Usage:
+    python basic_checkpoints.py
+"""
+
+import asyncio
+import tempfile
+from pathlib import Path
+
+from praisonaiagents.checkpoints import CheckpointService
+
+
+async def main():
+    # Create a temporary workspace for demonstration
+    with tempfile.TemporaryDirectory() as workspace:
+        print("=" * 60)
+        print("Shadow Git Checkpointing Demo")
+        print("=" * 60)
+        print(f"\nWorkspace: {workspace}")
+        
+        # Create some initial files
+        test_file = Path(workspace) / "example.py"
+        test_file.write_text("# Initial content\nprint('Hello, World!')\n")
+        print(f"\n✅ Created initial file: {test_file.name}")
+        
+        # Initialize the checkpoint service
+        service = CheckpointService(workspace_dir=workspace)
+        
+        try:
+            # Initialize the shadow git repository
+            print("\n--- Initializing Checkpoint Service ---")
+            await service.initialize()
+            print("✅ Shadow git repository initialized")
+            
+            # Save first checkpoint
+            print("\n--- Saving Checkpoint 1: Initial State ---")
+            result1 = await service.save("Initial state")
+            print(f"✅ Checkpoint saved: {result1.checkpoint.id[:8]}")
+            print(f"   Message: {result1.checkpoint.message}")
+            
+            # Make some changes
+            print("\n--- Making Changes ---")
+            test_file.write_text("# Modified content\nprint('Hello, PraisonAI!')\nprint('Checkpoints are awesome!')\n")
+            print("✅ Modified example.py")
+            
+            # Create a new file
+            new_file = Path(workspace) / "utils.py"
+            new_file.write_text("def helper():\n    return 'I help!'\n")
+            print("✅ Created utils.py")
+            
+            # Save second checkpoint
+            print("\n--- Saving Checkpoint 2: After Changes ---")
+            result2 = await service.save("Added features")
+            print(f"✅ Checkpoint saved: {result2.checkpoint.id[:8]}")
+            
+            # List all checkpoints
+            print("\n--- Listing All Checkpoints ---")
+            checkpoints = await service.list_checkpoints()
+            for i, cp in enumerate(checkpoints, 1):
+                print(f"  {i}. [{cp.id[:8]}] {cp.message} ({cp.timestamp})")
+            
+            # Show diff
+            print("\n--- Current Diff (uncommitted changes) ---")
+            diff = await service.diff()
+            if diff.files:
+                for f in diff.files:
+                    print(f"  {f.status}: {f.path}")
+            else:
+                print("  No uncommitted changes")
+            
+            # Make more changes to show diff
+            test_file.write_text("# Even more changes\nprint('This will be reverted')\n")
+            print("\n✅ Made more changes to example.py")
+            
+            diff = await service.diff()
+            print("\n--- New Diff ---")
+            if diff.files:
+                for f in diff.files:
+                    print(f"  {f.status}: {f.path}")
+            
+            # Restore to checkpoint 2
+            print(f"\n--- Restoring to Checkpoint: {result2.checkpoint.id[:8]} ---")
+            await service.restore(result2.checkpoint.id)
+            print("✅ Restored successfully!")
+            
+            # Verify restoration
+            content = test_file.read_text()
+            print(f"\n--- Verified Content After Restore ---")
+            print(content)
+            
+        except Exception as e:
+            print(f"\n❌ Error: {e}")
+            raise
+        
+        print("\n" + "=" * 60)
+        print("Demo Complete!")
+        print("=" * 60)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,93 @@
+# Persistence CLI Commands
+
+## Quick Reference
+
+```bash
+# Check database connectivity
+praisonai persistence doctor \
+  --conversation-url postgresql://localhost:5432/praisonai \
+  --state-url redis://localhost:6379
+
+# Run agent with persistence
+praisonai persistence run \
+  --conversation-url postgresql://localhost:5432/praisonai \
+  --session-id my-session
+
+# Resume a session
+praisonai persistence resume \
+  --conversation-url postgresql://localhost:5432/praisonai \
+  --session-id my-session
+
+# Export session to file
+praisonai persistence export \
+  --conversation-url postgresql://localhost:5432/praisonai \
+  --session-id my-session \
+  --output session_backup.jsonl
+
+# Import session from file
+praisonai persistence import \
+  --conversation-url postgresql://localhost:5432/praisonai \
+  --file session_backup.jsonl
+
+# Check schema status
+praisonai persistence status \
+  --conversation-url postgresql://localhost:5432/praisonai \
+  --state-url redis://localhost:6379
+
+# Apply migrations
+praisonai persistence migrate \
+  --conversation-url postgresql://localhost:5432/praisonai \
+  --state-url redis://localhost:6379
+```
+
+## Environment Variables
+
+Instead of CLI flags, you can use environment variables:
+
+```bash
+export PRAISON_CONVERSATION_URL=postgresql://localhost:5432/praisonai
+export PRAISON_STATE_URL=redis://localhost:6379
+export PRAISON_KNOWLEDGE_URL=http://localhost:6333
+
+# Then run without URL flags
+praisonai persistence doctor
+praisonai persistence status
+```
+
+## Docker Setup
+
+```bash
+# Start all services
+docker run -d --name praison-postgres \
+  -e POSTGRES_PASSWORD=praison123 \
+  -e POSTGRES_DB=praisonai \
+  -p 5432:5432 postgres:16
+
+docker run -d --name praison-redis \
+  -p 6379:6379 redis:7
+
+docker run -d --name praison-qdrant \
+  -p 6333:6333 -p 6334:6334 qdrant/qdrant
+
+# Verify
+docker ps
+```
+
+## Example Workflow
+
+```bash
+# 1. Start services
+docker-compose up -d
+
+# 2. Check connectivity
+praisonai persistence doctor
+
+# 3. Run agent
+praisonai persistence run --session-id demo-session
+
+# 4. Export for backup
+praisonai persistence export --session-id demo-session --output backup.jsonl
+
+# 5. Import to another environment
+praisonai persistence import --file backup.jsonl
+```
@@ -0,0 +1,124 @@
+# PraisonAI Persistence CLI - End-to-End Guide
+
+This guide demonstrates the CLI commands for database persistence.
+
+## Prerequisites
+
+```bash
+pip install "praisonai[tools]"
+
+# Start Docker containers
+docker run -d --name praison-postgres -p 5432:5432 \
+    -e POSTGRES_PASSWORD=praison123 \
+    -e POSTGRES_DB=praisonai \
+    postgres:16
+
+docker run -d --name praison-qdrant -p 6333:6333 qdrant/qdrant
+docker run -d --name praison-redis -p 6379:6379 redis:7
+```
+
+## 1. Doctor Command - Validate Connectivity
+
+```bash
+# Check all stores
+praisonai persistence doctor \
+    --conversation-url "postgresql://postgres:praison123@localhost:5432/praisonai" \
+    --knowledge-url "http://localhost:6333" \
+    --state-url "redis://localhost:6379"
+```
+
+**Expected Output:**
+```
+==================================================
+PraisonAI Persistence Doctor
+==================================================
+
+[Conversation Store] Testing: postgresql://postgres:****@localhost:5432/praisonai
+  ✅ Connected (postgres)
+
+[Knowledge Store] Testing: http://localhost:6333
+  ✅ Connected (qdrant)
+
+[State Store] Testing: redis://localhost:6379
+  ✅ Connected (redis)
+
+==================================================
+Results: 3/3 stores connected successfully
+==================================================
+```
+
+## 2. Run Command - Execute Agent with Persistence
+
+```bash
+# Run agent with persistence (dry-run first)
+praisonai persistence run \
+    --session-id "cli-demo-001" \
+    --conversation-url "postgresql://postgres:praison123@localhost:5432/praisonai" \
+    --dry-run \
+    "Hello, my name is Bob"
+
+# Actually run it
+praisonai persistence run \
+    --session-id "cli-demo-001" \
+    --conversation-url "postgresql://postgres:praison123@localhost:5432/praisonai" \
+    "Hello, my name is Bob"
+```
+
+**Expected Output:**
+```
+[Session: cli-demo-001]
+Agent: Hello Bob! Nice to meet you. How can I help you today?
+```
+
+## 3. Resume Command - Continue a Session
+
+```bash
+# Show history
+praisonai persistence resume \
+    --session-id "cli-demo-001" \
+    --conversation-url "postgresql://postgres:praison123@localhost:5432/praisonai" \
+    --show-history
+
+# Continue conversation
+praisonai persistence resume \
+    --session-id "cli-demo-001" \
+    --conversation-url "postgresql://postgres:praison123@localhost:5432/praisonai" \
+    --continue "What's my name?"
+```
+
+**Expected Output:**
+```
+[Session: cli-demo-001]
+Messages in history: 2
+
+--- Conversation History ---
+[USER] Hello, my name is Bob
+[ASSISTANT] Hello Bob! Nice to meet you...
+--- End History ---
+
+Agent: Your name is Bob!
+```
+
+## Environment Variables
+
+Instead of passing URLs on command line, use environment variables:
+
+```bash
+export PRAISON_CONVERSATION_URL="postgresql://postgres:praison123@localhost:5432/praisonai"
+export PRAISON_KNOWLEDGE_URL="http://localhost:6333"
+export PRAISON_STATE_URL="redis://localhost:6379"
+export OPENAI_API_KEY="your-key"
+
+# Now commands are simpler
+praisonai persistence doctor --all
+praisonai persistence run --session-id "my-session" "Hello!"
+```
+
+## Full CLI Reference
+
+```
+praisonai persistence --help
+praisonai persistence doctor --help
+praisonai persistence run --help
+praisonai persistence resume --help
+```
@@ -0,0 +1,146 @@
+#!/usr/bin/env python3
+"""
+Basic Context Compaction Example for PraisonAI Agents.
+
+This example demonstrates how to use context compaction to:
+1. Manage conversation context length
+2. Use different compaction strategies
+3. Track compaction results
+4. Preserve important messages
+
+Usage:
+    python basic_compaction.py
+"""
+
+from praisonaiagents.compaction import (
+    ContextCompactor, CompactionConfig, CompactionStrategy, CompactionResult
+)
+
+
+def main():
+    print("=" * 60)
+    print("Context Compaction Demo")
+    print("=" * 60)
+    
+    # ==========================================================================
+    # Sample Messages
+    # ==========================================================================
+    messages = [
+        {"role": "system", "content": "You are a helpful AI assistant."},
+        {"role": "user", "content": "Hello! Can you help me with Python?"},
+        {"role": "assistant", "content": "Of course! I'd be happy to help you with Python. What would you like to know?"},
+        {"role": "user", "content": "How do I read a file in Python?"},
+        {"role": "assistant", "content": "To read a file in Python, you can use the built-in open() function. Here's an example:\n\nwith open('filename.txt', 'r') as f:\n    content = f.read()\n\nThis opens the file, reads its content, and automatically closes it."},
+        {"role": "user", "content": "What about writing to a file?"},
+        {"role": "assistant", "content": "To write to a file, use the 'w' mode:\n\nwith open('filename.txt', 'w') as f:\n    f.write('Hello, World!')\n\nUse 'a' mode to append instead of overwriting."},
+        {"role": "user", "content": "Can you explain list comprehensions?"},
+        {"role": "assistant", "content": "List comprehensions are a concise way to create lists. Instead of:\n\nresult = []\nfor x in range(10):\n    result.append(x * 2)\n\nYou can write:\n\nresult = [x * 2 for x in range(10)]"},
+    ]
+    
+    print(f"\n--- Original Messages ---")
+    print(f"  Message count: {len(messages)}")
+    
+    # ==========================================================================
+    # Basic Compaction
+    # ==========================================================================
+    print("\n--- Basic Compaction (Truncate Strategy) ---")
+    
+    compactor = ContextCompactor(
+        max_tokens=50,  # Low limit to trigger compaction
+        strategy=CompactionStrategy.TRUNCATE,
+        preserve_system=True,
+        preserve_recent=2
+    )
+    
+    # Check stats before
+    stats = compactor.get_stats(messages)
+    print(f"  Total tokens: {stats['total_tokens']}")
+    print(f"  Max tokens: {stats['max_tokens']}")
+    print(f"  Needs compaction: {stats['needs_compaction']}")
+    
+    # Compact
+    compacted, result = compactor.compact(messages)
+    
+    print(f"\n  After compaction:")
+    print(f"    Messages: {len(messages)} -> {len(compacted)}")
+    print(f"    Tokens: {result.original_tokens} -> {result.compacted_tokens}")
+    print(f"    Saved: {result.tokens_saved} tokens")
+    print(f"    Compression: {result.compression_ratio:.1%}")
+    
+    # ==========================================================================
+    # Sliding Window Strategy
+    # ==========================================================================
+    print("\n--- Sliding Window Strategy ---")
+    
+    compactor = ContextCompactor(
+        max_tokens=50,
+        strategy=CompactionStrategy.SLIDING,
+        preserve_system=True,
+        preserve_recent=3
+    )
+    
+    compacted, result = compactor.compact(messages)
+    
+    print(f"  Messages kept: {result.messages_kept}")
+    print(f"  Messages removed: {result.messages_removed}")
+    print(f"  Strategy: {result.strategy_used.value}")
+    
+    # ==========================================================================
+    # Summarize Strategy
+    # ==========================================================================
+    print("\n--- Summarize Strategy ---")
+    
+    compactor = ContextCompactor(
+        max_tokens=50,
+        strategy=CompactionStrategy.SUMMARIZE,
+        preserve_system=True,
+        preserve_recent=2
+    )
+    
+    compacted, result = compactor.compact(messages)
+    
+    print(f"  Messages kept: {result.messages_kept}")
+    print(f"  Strategy: {result.strategy_used.value}")
+    
+    # Show what messages remain
+    print(f"\n  Remaining message roles:")
+    for msg in compacted:
+        role = msg.get("role", "unknown")
+        content_preview = msg.get("content", "")[:50]
+        print(f"    [{role}] {content_preview}...")
+    
+    # ==========================================================================
+    # No Compaction Needed
+    # ==========================================================================
+    print("\n--- No Compaction Needed ---")
+    
+    compactor = ContextCompactor(
+        max_tokens=10000,  # High limit
+        strategy=CompactionStrategy.TRUNCATE
+    )
+    
+    compacted, result = compactor.compact(messages)
+    
+    print(f"  Was compacted: {result.was_compacted}")
+    print(f"  Messages unchanged: {len(compacted) == len(messages)}")
+    
+    # ==========================================================================
+    # Result Serialization
+    # ==========================================================================
+    print("\n--- Result Serialization ---")
+    
+    compactor = ContextCompactor(max_tokens=50)
+    _, result = compactor.compact(messages)
+    
+    data = result.to_dict()
+    print(f"  Original tokens: {data['original_tokens']}")
+    print(f"  Compacted tokens: {data['compacted_tokens']}")
+    print(f"  Compression ratio: {data['compression_ratio']:.2f}")
+    
+    print("\n" + "=" * 60)
+    print("Demo Complete!")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,142 @@
+#!/usr/bin/env python3
+"""
+Basic Hooks Example for PraisonAI Agents.
+
+This example demonstrates how to use the hooks system to:
+1. Log tool calls before execution
+2. Block dangerous operations
+3. Add context to agent responses
+4. Monitor session lifecycle
+
+Usage:
+    python basic_hooks.py
+"""
+
+import asyncio
+from praisonaiagents import Agent
+from praisonaiagents.hooks import (
+    HookRegistry, HookRunner, HookEvent, HookResult,
+    BeforeToolInput, AfterToolInput
+)
+
+
+def main():
+    # Create a hook registry
+    registry = HookRegistry()
+    
+    # ==========================================================================
+    # Hook 1: Log all tool calls
+    # ==========================================================================
+    @registry.on(HookEvent.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}")
+        print(f"   Input: {event_data.tool_input}")
+        return HookResult.allow()
+    
+    # ==========================================================================
+    # Hook 2: Block dangerous file operations (using function logic)
+    # ==========================================================================
+    @registry.on(HookEvent.BEFORE_TOOL)
+    def block_delete_operations(event_data: BeforeToolInput) -> HookResult:
+        """Block any delete or remove operations."""
+        dangerous_keywords = ['delete', 'remove', 'rm', 'unlink']
+        tool_lower = event_data.tool_name.lower()
+        
+        if any(kw in tool_lower for kw in dangerous_keywords):
+            print(f"\n🚫 [BLOCKED] Dangerous operation: {event_data.tool_name}")
+            return HookResult.deny(
+                f"Operation '{event_data.tool_name}' is blocked by security policy"
+            )
+        return HookResult.allow()
+    
+    # ==========================================================================
+    # Hook 3: Require confirmation for write operations
+    # ==========================================================================
+    @registry.on(HookEvent.BEFORE_TOOL)
+    def confirm_write_operations(event_data: BeforeToolInput) -> HookResult:
+        """Request confirmation for write operations."""
+        write_keywords = ['write', 'save', 'create', 'update']
+        tool_lower = event_data.tool_name.lower()
+        
+        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)
+    def log_tool_completion(event_data: AfterToolInput) -> HookResult:
+        """Log tool completion with timing."""
+        print(f"\n✅ [DONE] Tool: {event_data.tool_name}")
+        print(f"   Duration: {event_data.execution_time_ms:.2f}ms")
+        if event_data.tool_error:
+            print(f"   Error: {event_data.tool_error}")
+        return HookResult.allow()
+    
+    # ==========================================================================
+    # Test the hooks
+    # ==========================================================================
+    print("=" * 60)
+    print("Testing Hooks System")
+    print("=" * 60)
+    
+    runner = HookRunner(registry)
+    
+    # Test 1: Normal tool call (should be logged and allowed)
+    print("\n--- Test 1: Normal read operation ---")
+    input1 = BeforeToolInput(
+        session_id="test",
+        cwd="/tmp",
+        event_name="before_tool",
+        timestamp="2024-01-01T00:00:00",
+        tool_name="read_file",
+        tool_input={"path": "/tmp/test.txt"}
+    )
+    results = asyncio.run(runner.execute(HookEvent.BEFORE_TOOL, input1))
+    print(f"Result: {'ALLOWED' if not HookRunner.is_blocked(results) else 'BLOCKED'}")
+    
+    # Test 2: Delete operation (should be blocked)
+    print("\n--- Test 2: Delete operation ---")
+    input2 = BeforeToolInput(
+        session_id="test",
+        cwd="/tmp",
+        event_name="before_tool",
+        timestamp="2024-01-01T00:00:00",
+        tool_name="delete_file",
+        tool_input={"path": "/important/data.txt"}
+    )
+    results = asyncio.run(runner.execute(HookEvent.BEFORE_TOOL, input2))
+    print(f"Result: {'ALLOWED' if not HookRunner.is_blocked(results) else 'BLOCKED'}")
+    if HookRunner.is_blocked(results):
+        print(f"Reason: {HookRunner.get_blocking_reason(results)}")
+    
+    # Test 3: Write operation (should be confirmed)
+    print("\n--- Test 3: Write operation ---")
+    input3 = BeforeToolInput(
+        session_id="test",
+        cwd="/tmp",
+        event_name="before_tool",
+        timestamp="2024-01-01T00:00:00",
+        tool_name="write_file",
+        tool_input={"path": "/tmp/output.txt", "content": "Hello"}
+    )
+    results = asyncio.run(runner.execute(HookEvent.BEFORE_TOOL, input3))
+    print(f"Result: {'ALLOWED' if not HookRunner.is_blocked(results) else 'BLOCKED'}")
+    
+    # Show registered hooks
+    print("\n" + "=" * 60)
+    print("Registered Hooks:")
+    print("=" * 60)
+    for event, hooks in registry.list_hooks().items():
+        print(f"\n{event}:")
+        for hook in hooks:
+            print(f"  - {hook['name']} (matcher: {hook['matcher'] or '*'})")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,122 @@
+"""
+Multi-Agent Persistence Example
+
+Demonstrates how multiple agents can share or isolate conversation
+history using the persistence layer.
+"""
+
+from praisonai.persistence.factory import create_conversation_store, create_state_store
+from praisonai.persistence.conversation.base import ConversationSession, ConversationMessage
+import uuid
+
+
+def main():
+    # Create stores
+    conv_store = create_conversation_store("sqlite", path=":memory:")
+    state_store = create_state_store("memory")
+    
+    print("=== Multi-Agent Persistence Demo ===\n")
+    
+    # Scenario 1: Shared session (agents collaborate)
+    print("--- Scenario 1: Shared Session ---")
+    shared_session_id = f"shared-{uuid.uuid4().hex[:8]}"
+    
+    session = ConversationSession(
+        session_id=shared_session_id,
+        user_id="user-123",
+        name="Shared Conversation"
+    )
+    conv_store.create_session(session)
+    
+    # Agent 1 (Researcher) adds context
+    conv_store.add_message(shared_session_id, ConversationMessage(
+        role="assistant",
+        content="[Researcher] I found relevant information about the topic.",
+        metadata={"agent_id": "researcher", "agent_role": "research"}
+    ))
+    
+    # Agent 2 (Writer) uses the context
+    conv_store.add_message(shared_session_id, ConversationMessage(
+        role="assistant", 
+        content="[Writer] Based on the research, here's a summary...",
+        metadata={"agent_id": "writer", "agent_role": "writing"}
+    ))
+    
+    # Agent 3 (Editor) reviews
+    conv_store.add_message(shared_session_id, ConversationMessage(
+        role="assistant",
+        content="[Editor] I've reviewed and polished the content.",
+        metadata={"agent_id": "editor", "agent_role": "editing"}
+    ))
+    
+    messages = conv_store.get_messages(shared_session_id)
+    print(f"Shared session has {len(messages)} messages from different agents")
+    for msg in messages:
+        agent = msg.metadata.get("agent_id", "unknown") if msg.metadata else "unknown"
+        print(f"  - {agent}: {msg.content[:50]}...")
+    
+    # Scenario 2: Isolated sessions (agents work independently)
+    print("\n--- Scenario 2: Isolated Sessions ---")
+    
+    agent_sessions = {}
+    for agent_name in ["planner", "executor", "validator"]:
+        session_id = f"{agent_name}-{uuid.uuid4().hex[:8]}"
+        agent_sessions[agent_name] = session_id
+        
+        conv_store.create_session(ConversationSession(
+            session_id=session_id,
+            agent_id=agent_name,
+            name=f"{agent_name.title()} Session"
+        ))
+        
+        # Each agent has its own conversation
+        conv_store.add_message(session_id, ConversationMessage(
+            role="user",
+            content=f"Task for {agent_name}"
+        ))
+        conv_store.add_message(session_id, ConversationMessage(
+            role="assistant",
+            content=f"[{agent_name.title()}] Processing task..."
+        ))
+    
+    print("Created isolated sessions for each agent:")
+    for agent, sid in agent_sessions.items():
+        msgs = conv_store.get_messages(sid)
+        print(f"  - {agent}: {len(msgs)} messages")
+    
+    # Scenario 3: Shared state across agents
+    print("\n--- Scenario 3: Shared State ---")
+    
+    # Agents share state for coordination
+    state_store.set("workflow:status", {"phase": "research", "progress": 0})
+    state_store.set("workflow:context", {"topic": "AI Agents", "deadline": "2024-12-31"})
+    
+    # Agent 1 updates progress
+    state = state_store.get("workflow:status")
+    state["progress"] = 33
+    state["phase"] = "writing"
+    state_store.set("workflow:status", state)
+    print(f"Agent 1 updated state: {state}")
+    
+    # Agent 2 reads and updates
+    state = state_store.get("workflow:status")
+    state["progress"] = 66
+    state["phase"] = "editing"
+    state_store.set("workflow:status", state)
+    print(f"Agent 2 updated state: {state}")
+    
+    # Agent 3 completes
+    state = state_store.get("workflow:status")
+    state["progress"] = 100
+    state["phase"] = "complete"
+    state_store.set("workflow:status", state)
+    print(f"Agent 3 completed: {state}")
+    
+    # Cleanup
+    conv_store.close()
+    state_store.close()
+    print("\n✅ Multi-agent persistence demo complete!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,16 @@
+"""Multi-Agent Shared Session Demo"""
+from praisonaiagents import Agent
+from praisonai.persistence import create_conversation_store
+
+store = create_conversation_store("sqlite", path="/tmp/multi_agent.db")
+
+agent1 = Agent(name="Researcher", llm="gpt-4o-mini", db=store, session_id="shared-session")
+agent2 = Agent(name="Writer", llm="gpt-4o-mini", db=store, session_id="shared-session")
+
+r1 = agent1.chat("Research topic: AI in healthcare. Key finding: reduces diagnosis time by 50%")
+print(f"Researcher: {r1[:50]}...")
+
+r2 = agent2.chat("Based on the research, what was the key finding?")
+print(f"Writer: {r2[:50]}...")
+assert "50" in r2 or "diagnosis" in r2.lower(), "Writer should see Researcher's context"
+print("PASSED: Multi-agent shared session works")
@@ -0,0 +1,48 @@
+"""
+Basic Observability Usage Example
+
+This example demonstrates how to use the observability module
+with PraisonAI agents.
+
+Usage:
+    # Set your provider's API key first
+    export LANGFUSE_PUBLIC_KEY=pk-lf-xxx
+    export LANGFUSE_SECRET_KEY=sk-lf-xxx
+    
+    python basic_usage.py
+"""
+
+from praisonai_tools.observability import obs
+from praisonaiagents import Agent
+
+# Initialize observability (auto-detects provider from env vars)
+obs.init()
+
+# Or specify a provider explicitly
+# obs.init(provider="langfuse", project_name="my-project")
+
+# Create an agent
+agent = Agent(
+    instructions="You are a helpful assistant.",
+    model="gpt-4o-mini",
+)
+
+# Use trace context manager for complete workflow tracing
+with obs.trace("chat-session", session_id="user-123"):
+    # Use span context manager for individual operations
+    with obs.span("user-query", kind=obs.SpanKind.AGENT):
+        response = agent.chat("What is the capital of France?")
+        print(response)
+
+# Log LLM calls manually if needed
+obs.log_llm_call(
+    model="gpt-4o-mini",
+    input_messages="What is 2+2?",
+    output="4",
+    input_tokens=10,
+    output_tokens=1,
+)
+
+# Check diagnostics
+print("\nDiagnostics:")
+print(obs.doctor())
@@ -0,0 +1,48 @@
+"""
+Langfuse Integration Example
+
+This example shows how to use Langfuse for LLM observability.
+
+Setup:
+    1. Sign up at https://langfuse.com/
+    2. Get your API keys from the project settings
+    3. Set environment variables:
+       export LANGFUSE_PUBLIC_KEY=pk-lf-xxx
+       export LANGFUSE_SECRET_KEY=sk-lf-xxx
+    4. Install dependencies:
+       pip install opentelemetry-sdk opentelemetry-exporter-otlp
+
+Usage:
+    python langfuse_example.py
+"""
+
+import os
+from praisonai_tools.observability import obs
+from praisonaiagents import Agent
+
+# Initialize Langfuse
+success = obs.init(
+    provider="langfuse",
+    project_name="praisonai-demo",
+)
+
+if not success:
+    print("Failed to initialize Langfuse. Check your API keys.")
+    print("Required: LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY")
+    exit(1)
+
+print("Langfuse initialized successfully!")
+print(f"View traces at: https://cloud.langfuse.com/")
+
+# Create agent
+agent = Agent(
+    instructions="You are a helpful coding assistant.",
+    model="gpt-4o-mini",
+)
+
+# Run with tracing
+with obs.trace("coding-session", user_id="developer-1"):
+    response = agent.chat("Write a Python function to calculate fibonacci numbers")
+    print(response)
+
+print("\nCheck Langfuse dashboard for traces!")
@@ -0,0 +1,22 @@
+"""MLflow Local Observability Demo (no API key needed)"""
+import mlflow
+import time
+
+mlflow.set_tracking_uri("file:///tmp/mlflow_demo")
+mlflow.set_experiment("praisonai-demo")
+
+with mlflow.start_run(run_name="agent-trace"):
+    mlflow.log_param("agent_name", "Assistant")
+    mlflow.log_param("model", "gpt-4o-mini")
+    
+    # Simulate agent work
+    start = time.time()
+    time.sleep(0.1)
+    latency = time.time() - start
+    
+    mlflow.log_metric("latency_ms", latency * 1000)
+    mlflow.log_metric("tokens_used", 150)
+    
+    print(f"Logged run to MLflow: latency={latency*1000:.1f}ms")
+
+print("PASSED: MLflow local observability works")
@@ -0,0 +1,53 @@
+"""
+Multi-Agent Tracing Example
+
+This example shows how to trace multi-agent workflows with
+parent/child span relationships.
+
+Usage:
+    # Set your provider's API key
+    export LANGFUSE_PUBLIC_KEY=pk-lf-xxx
+    export LANGFUSE_SECRET_KEY=sk-lf-xxx
+    
+    python multi_agent_tracing.py
+"""
+
+from praisonai_tools.observability import obs
+from praisonai_tools.observability.base import SpanKind
+from praisonaiagents import Agent, PraisonAIAgents
+
+# Initialize observability
+obs.init()
+
+# Create agents
+researcher = Agent(
+    name="Researcher",
+    instructions="You research topics and provide detailed information.",
+    model="gpt-4o-mini",
+)
+
+writer = Agent(
+    name="Writer", 
+    instructions="You write clear, engaging content based on research.",
+    model="gpt-4o-mini",
+)
+
+# Trace the multi-agent workflow
+with obs.trace("content-creation", metadata={"workflow": "research-write"}):
+    
+    # Research phase
+    with obs.span("research-phase", kind=SpanKind.AGENT) as research_span:
+        research_span.attributes["agent"] = "Researcher"
+        research_result = researcher.chat("Research the benefits of AI in healthcare")
+    
+    # Writing phase  
+    with obs.span("writing-phase", kind=SpanKind.AGENT) as write_span:
+        write_span.attributes["agent"] = "Writer"
+        write_span.attributes["input_length"] = len(str(research_result))
+        final_content = writer.chat(f"Write a blog post based on: {research_result}")
+
+print("Final Content:")
+print(final_content)
+
+# Check trace info
+print("\nDiagnostics:", obs.doctor())
@@ -0,0 +1,79 @@
+"""
+Qdrant Knowledge Store Example for PraisonAI.
+
+Demonstrates vector insert + search through the knowledge store.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Docker Setup:
+    docker run -d --name praison-qdrant -p 6333:6333 qdrant/qdrant
+
+Run:
+    python knowledge_qdrant.py
+
+Expected Output:
+    === Qdrant Knowledge Store Demo ===
+    Created collection: demo_knowledge
+    Inserted 3 documents
+    Search results: 2 documents found
+"""
+
+from praisonai.persistence.factory import create_knowledge_store
+from praisonai.persistence.knowledge.base import KnowledgeDocument
+import random
+
+# Create Qdrant knowledge store
+store = create_knowledge_store("qdrant", url="http://localhost:6333")
+
+collection_name = "demo_knowledge"
+dimension = 384  # Embedding dimension
+
+# Create collection
+print("=== Qdrant Knowledge Store Demo ===")
+if store.collection_exists(collection_name):
+    store.delete_collection(collection_name)
+
+store.create_collection(collection_name, dimension=dimension)
+print(f"Created collection: {collection_name}")
+
+# Create sample documents with embeddings
+random.seed(42)
+documents = [
+    KnowledgeDocument(
+        id="doc-1",
+        content="Python is a versatile programming language used for web development, data science, and AI.",
+        embedding=[random.random() for _ in range(dimension)],
+        metadata={"category": "programming", "language": "python"}
+    ),
+    KnowledgeDocument(
+        id="doc-2", 
+        content="Machine learning enables computers to learn patterns from data without explicit programming.",
+        embedding=[random.random() for _ in range(dimension)],
+        metadata={"category": "ai", "topic": "ml"}
+    ),
+    KnowledgeDocument(
+        id="doc-3",
+        content="PostgreSQL is a powerful open-source relational database system.",
+        embedding=[random.random() for _ in range(dimension)],
+        metadata={"category": "database", "type": "sql"}
+    ),
+]
+
+# Insert documents
+ids = store.insert(collection_name, documents)
+print(f"Inserted {len(ids)} documents")
+
+# Search for similar documents
+query_embedding = [random.random() for _ in range(dimension)]
+results = store.search(collection_name, query_embedding, limit=2)
+print(f"Search results: {len(results)} documents found")
+
+for doc in results:
+    print(f"  - {doc.id}: {doc.content[:50]}...")
+
+# Cleanup
+store.delete_collection(collection_name)
+store.close()
+
+print("\n=== Demo Complete ===")
@@ -0,0 +1,43 @@
+"""
+Minimal Agent with Database Persistence
+
+This is the simplest way to add persistence to your agent.
+Messages, runs, and traces are automatically saved.
+
+Run:
+    python minimal_agent_db.py
+
+Expected output:
+    - Agent responds to your question
+    - Data is persisted to PostgreSQL
+    - Session can be resumed later with same session_id
+"""
+
+from praisonaiagents import Agent, db
+
+# Create database connection (PostgreSQL + Redis)
+my_db = db(
+    database_url="postgresql://postgres:praison123@localhost:5432/praisonai",
+    state_url="redis://localhost:6379"  # Optional: for state/tracing
+)
+
+# Create agent with persistence
+agent = Agent(
+    name="Assistant",
+    instructions="You are a helpful assistant. Be concise.",
+    db=my_db,
+    # session_id is optional - defaults to per-hour ID (YYYYMMDDHH-hash)
+    # Set explicitly for session continuity across runs:
+    session_id="my-persistent-session"
+)
+
+# Chat - messages are automatically persisted
+response = agent.chat("What is the capital of France?")
+print(f"Response: {response}")
+
+# Verify persistence
+data = my_db.export_session("my-persistent-session")
+print(f"\nMessages stored: {len(data.get('messages', []))}")
+
+# Clean up
+my_db.close()
@@ -0,0 +1,61 @@
+"""
+PostgreSQL with Runs and Traces
+
+Demonstrates full persistence with run tracking and tracing.
+
+Run:
+    python postgres_runs_traces.py
+
+Expected output:
+    - Agent responds with tool usage
+    - Runs and traces are persisted
+    - Export shows full session data
+"""
+
+from praisonaiagents import Agent, db
+
+def get_weather(city: str) -> str:
+    """Get weather for a city."""
+    return f"Weather in {city}: Sunny, 72°F"
+
+# Create database with PostgreSQL + Redis
+my_db = db(
+    database_url="postgresql://postgres:praison123@localhost:5432/praisonai",
+    state_url="redis://localhost:6379"
+)
+
+# Create agent with tools
+agent = Agent(
+    name="WeatherBot",
+    instructions="You help with weather. Use the get_weather tool when asked.",
+    tools=[get_weather],
+    db=my_db,
+    session_id="weather-session-001"
+)
+
+# First chat - triggers run tracking
+print("=== First Question ===")
+response1 = agent.chat("What's the weather in Tokyo?")
+print(f"Response: {response1}\n")
+
+# Second chat - same session, new run
+print("=== Second Question ===")
+response2 = agent.chat("How about New York?")
+print(f"Response: {response2}\n")
+
+# Export session data
+print("=== Session Data ===")
+data = my_db.export_session("weather-session-001")
+print(f"Session ID: {data.get('session_id')}")
+print(f"Messages: {len(data.get('messages', []))}")
+print(f"Agent: {data.get('agent_name')}")
+
+# Show messages
+print("\n=== Messages ===")
+for msg in data.get('messages', []):
+    role = msg.get('role', 'unknown')
+    content = msg.get('content', '')[:60]
+    print(f"  [{role}] {content}...")
+
+my_db.close()
+print("\n✅ Done")
@@ -0,0 +1,83 @@
+"""
+Redis State Store
+
+Use Redis for state management, tracing, and caching.
+
+Run:
+    python redis_state.py
+
+Expected output:
+    - State operations (set/get/delete)
+    - Tracing operations
+"""
+
+from praisonaiagents import db
+
+# Create Redis-only database (for state/tracing)
+redis_db = db.RedisDB(host="localhost", port=6379)
+
+print("=== Redis State Store ===")
+
+# Test state operations
+print("\n1. State Operations:")
+redis_db._init_stores()  # Initialize stores
+
+# Set a value
+redis_db._state_store.set("user:123:preferences", {
+    "theme": "dark",
+    "language": "en"
+})
+print("   Set user preferences")
+
+# Get the value
+prefs = redis_db._state_store.get("user:123:preferences")
+print(f"   Got preferences: {prefs}")
+
+# Set with TTL (expires in 60 seconds)
+redis_db._state_store.set("temp:token", "abc123", ttl=60)
+print("   Set temporary token (60s TTL)")
+
+# Delete
+redis_db._state_store.delete("user:123:preferences")
+print("   Deleted preferences")
+
+# Test tracing
+print("\n2. Tracing Operations:")
+
+# Start a trace
+trace_id = "trace-example-001"
+redis_db.on_trace_start(
+    trace_id=trace_id,
+    session_id="example-session",
+    agent_name="ExampleAgent",
+    metadata={"purpose": "demo"}
+)
+print(f"   Started trace: {trace_id}")
+
+# Add spans
+span_id = "span-llm-001"
+redis_db.on_span_start(
+    span_id=span_id,
+    trace_id=trace_id,
+    name="llm_call",
+    attributes={"model": "gpt-4", "temperature": 0.7}
+)
+print(f"   Started span: {span_id}")
+
+redis_db.on_span_end(
+    span_id=span_id,
+    status="ok",
+    attributes={"tokens": 150, "latency_ms": 450}
+)
+print(f"   Ended span: {span_id}")
+
+# End trace
+redis_db.on_trace_end(
+    trace_id=trace_id,
+    status="ok",
+    metadata={"total_spans": 1}
+)
+print(f"   Ended trace: {trace_id}")
+
+redis_db.close()
+print("\n✅ Done")
@@ -0,0 +1,66 @@
+"""
+Session Resume Example
+
+Demonstrates how to resume a conversation from a previous session.
+
+Run:
+    python session_resume.py
+
+Expected output:
+    - First run: Creates new session
+    - Second run: Resumes with history
+"""
+
+from praisonaiagents import Agent, db
+
+# Create database
+my_db = db(
+    database_url="postgresql://postgres:praison123@localhost:5432/praisonai",
+    state_url="redis://localhost:6379"
+)
+
+SESSION_ID = "resume-demo-session"
+
+# Create agent with explicit session_id
+agent = Agent(
+    name="MemoryBot",
+    instructions="You remember our conversation. Be helpful and concise.",
+    db=my_db,
+    session_id=SESSION_ID
+)
+
+# Check if this is a new or resumed session
+data = my_db.export_session(SESSION_ID)
+existing_messages = len(data.get('messages', []))
+
+if existing_messages == 0:
+    print("=== NEW SESSION ===")
+    print("This is a new conversation.\n")
+    
+    response = agent.chat("My name is Alice and I love Python programming.")
+    print(f"Response: {response}\n")
+    
+    response = agent.chat("What's my favorite programming language?")
+    print(f"Response: {response}\n")
+else:
+    print(f"=== RESUMED SESSION ({existing_messages} previous messages) ===")
+    print("Continuing previous conversation.\n")
+    
+    # Show previous messages
+    print("Previous messages:")
+    for msg in data.get('messages', [])[:4]:
+        role = msg.get('role', 'unknown')
+        content = msg.get('content', '')[:60]
+        print(f"  [{role}] {content}...")
+    print()
+    
+    # Continue conversation
+    response = agent.chat("What's my name and what do I like?")
+    print(f"Response: {response}\n")
+
+# Show final state
+final_data = my_db.export_session(SESSION_ID)
+print(f"Total messages now: {len(final_data.get('messages', []))}")
+
+my_db.close()
+print("✅ Done")
@@ -0,0 +1,63 @@
+"""
+Simple Database Persistence Example for PraisonAI Agents.
+
+This example shows how to enable automatic conversation persistence
+with just 2 lines of code.
+
+Requirements:
+    pip install "praisonai[tools]"
+    
+Docker Setup:
+    docker run -d --name praison-postgres -p 5432:5432 \
+        -e POSTGRES_PASSWORD=praison123 \
+        -e POSTGRES_DB=praisonai \
+        postgres:16
+
+Environment:
+    export OPENAI_API_KEY=your-key
+
+Run:
+    python simple_agent_postgres.py
+
+Expected Output:
+    === First Run ===
+    Agent: Nice to meet you, Alice! Python is a great choice...
+    Session ID: demo-session-001
+    Messages persisted: 2
+"""
+
+from praisonaiagents import Agent
+from praisonai.db import PostgresDB
+
+# Create database adapter
+db = PostgresDB(
+    host="localhost",
+    port=5432,
+    database="praisonai",
+    user="postgres",
+    password="praison123"
+)
+
+# Create agent with persistence enabled
+agent = Agent(
+    name="Assistant",
+    instructions="You are a helpful assistant. Keep responses brief.",
+    db=db,
+    session_id="demo-session-001",  # Same session_id = resume conversation
+    verbose=False
+)
+
+# Chat with persistence
+print("=== First Run ===")
+response = agent.chat("My name is Alice and I love Python programming.")
+print(f"Agent: {response}\n")
+
+# Show session info
+print(f"Session ID: {agent.session_id}")
+print(f"Messages in history: {len(agent.chat_history)}")
+
+# Close DB connection
+db.close()
+
+print("\n=== Session persisted! ===")
+print("Run again with same session_id to resume.")
@@ -0,0 +1,41 @@
+"""
+SQLite Local Database
+
+Use SQLite for simple local persistence without external services.
+
+Run:
+    python sqlite_local.py
+
+Expected output:
+    - Agent responds
+    - Data persisted to local SQLite file
+"""
+
+from praisonaiagents import Agent, db
+import tempfile
+import os
+
+# Create SQLite database (local file)
+db_path = os.path.join(tempfile.gettempdir(), "my_agent.db")
+my_db = db.SQLiteDB(path=db_path)
+
+print(f"Database: {db_path}")
+
+# Create agent
+agent = Agent(
+    name="LocalBot",
+    instructions="You are a helpful assistant.",
+    db=my_db,
+    session_id="local-session"
+)
+
+# Chat
+response = agent.chat("Hello! What can you help me with?")
+print(f"Response: {response}")
+
+# Verify
+data = my_db.export_session("local-session")
+print(f"\nMessages stored: {len(data.get('messages', []))}")
+
+my_db.close()
+print("✅ Done")
@@ -0,0 +1,67 @@
+"""
+Redis State Store Example for PraisonAI.
+
+Demonstrates set/get/delete + TTL operations.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Docker Setup:
+    docker run -d --name praison-redis -p 6379:6379 redis:7
+
+Run:
+    python state_redis.py
+
+Expected Output:
+    === Redis State Store Demo ===
+    Set key: session:user123:preferences
+    Get value: {'theme': 'dark', 'language': 'en'}
+    TTL remaining: 3600 seconds
+    Hash operations: {'name': 'Alice', 'role': 'admin'}
+"""
+
+from praisonai.persistence.factory import create_state_store
+
+# Create Redis state store
+store = create_state_store("redis", url="redis://localhost:6379")
+
+print("=== Redis State Store Demo ===")
+
+# Basic set/get
+key = "session:user123:preferences"
+value = {"theme": "dark", "language": "en", "notifications": True}
+
+store.set(key, value)
+print(f"Set key: {key}")
+
+retrieved = store.get(key)
+print(f"Get value: {retrieved}")
+
+# Set with TTL (expires in 1 hour)
+ttl_key = "session:user123:token"
+store.set(ttl_key, "abc123xyz", ttl=3600)
+remaining = store.ttl(ttl_key)
+print(f"TTL remaining: {remaining} seconds")
+
+# Hash operations (for structured data)
+hash_key = "user:123:profile"
+store.hset(hash_key, "name", "Alice")
+store.hset(hash_key, "role", "admin")
+store.hset(hash_key, "last_login", "2024-12-24")
+
+profile = store.hgetall(hash_key)
+print(f"Hash operations: {profile}")
+
+# Check existence
+exists = store.exists(key)
+print(f"Key exists: {exists}")
+
+# Delete keys
+store.delete(key)
+store.delete(ttl_key)
+store.delete(hash_key)
+print("Cleaned up test keys")
+
+store.close()
+
+print("\n=== Demo Complete ===")
@@ -0,0 +1,142 @@
+#!/usr/bin/env python3
+"""
+Basic Policy Engine Example for PraisonAI Agents.
+
+This example demonstrates how to use the policy engine to:
+1. Create policies with rules
+2. Check if actions are allowed
+3. Block dangerous operations
+4. Use convenience policy creators
+
+Usage:
+    python basic_policy.py
+"""
+
+from praisonaiagents.policy import (
+    PolicyEngine, Policy, PolicyRule, PolicyAction, PolicyConfig,
+    create_deny_tools_policy, create_read_only_policy
+)
+
+
+def main():
+    print("=" * 60)
+    print("Policy Engine Demo")
+    print("=" * 60)
+    
+    # Create a policy engine
+    engine = PolicyEngine()
+    
+    # ==========================================================================
+    # Policy 1: Block dangerous tools
+    # ==========================================================================
+    print("\n--- Creating Policies ---")
+    
+    dangerous_tools_policy = Policy(
+        name="block_dangerous",
+        description="Block dangerous file operations",
+        rules=[
+            PolicyRule(
+                action=PolicyAction.DENY,
+                resource="tool:delete_*",
+                reason="Delete operations are blocked",
+                name="deny_delete"
+            ),
+            PolicyRule(
+                action=PolicyAction.DENY,
+                resource="tool:rm_*",
+                reason="Remove operations are blocked",
+                name="deny_rm"
+            ),
+        ],
+        priority=100
+    )
+    engine.add_policy(dangerous_tools_policy)
+    print(f"✅ Added policy: {dangerous_tools_policy.name}")
+    
+    # ==========================================================================
+    # Policy 2: Allow read operations
+    # ==========================================================================
+    read_policy = Policy(
+        name="allow_read",
+        description="Allow read operations",
+        rules=[
+            PolicyRule(
+                action=PolicyAction.ALLOW,
+                resource="tool:read_*",
+                name="allow_read"
+            ),
+            PolicyRule(
+                action=PolicyAction.ALLOW,
+                resource="tool:list_*",
+                name="allow_list"
+            ),
+        ]
+    )
+    engine.add_policy(read_policy)
+    print(f"✅ Added policy: {read_policy.name}")
+    
+    # ==========================================================================
+    # Test policy checks
+    # ==========================================================================
+    print("\n--- Testing Policy Checks ---")
+    
+    test_cases = [
+        ("tool:read_file", "Reading a file"),
+        ("tool:list_directory", "Listing directory"),
+        ("tool:delete_file", "Deleting a file"),
+        ("tool:rm_directory", "Removing directory"),
+        ("tool:write_file", "Writing a file"),
+    ]
+    
+    for resource, description in test_cases:
+        result = engine.check(resource, {})
+        status = "✅ ALLOWED" if result.allowed else "🚫 DENIED"
+        reason = f" ({result.reason})" if result.reason else ""
+        print(f"  {status}: {description}{reason}")
+    
+    # ==========================================================================
+    # Using convenience functions
+    # ==========================================================================
+    print("\n--- Using Convenience Functions ---")
+    
+    # Create a read-only policy
+    read_only = create_read_only_policy()
+    print(f"✅ Created read-only policy with {len(read_only.rules)} rules")
+    
+    # Create a deny tools policy
+    deny_tools = create_deny_tools_policy(
+        ["execute_*", "shell_*", "system_*"],
+        reason="System commands are blocked"
+    )
+    print(f"✅ Created deny-tools policy with {len(deny_tools.rules)} rules")
+    
+    # ==========================================================================
+    # Strict mode example
+    # ==========================================================================
+    print("\n--- Strict Mode Example ---")
+    
+    strict_engine = PolicyEngine(PolicyConfig(strict_mode=True))
+    
+    # In strict mode, unknown resources are denied
+    result = strict_engine.check("tool:unknown_operation", {})
+    print(f"  Unknown operation in strict mode: {'DENIED' if not result.allowed else 'ALLOWED'}")
+    
+    # ==========================================================================
+    # Policy serialization
+    # ==========================================================================
+    print("\n--- Policy Serialization ---")
+    
+    policy_dict = dangerous_tools_policy.to_dict()
+    print(f"  Serialized policy: {policy_dict['name']} with {len(policy_dict['rules'])} rules")
+    
+    # Recreate from dict
+    restored = Policy.from_dict(policy_dict)
+    print(f"  Restored policy: {restored.name}")
+    
+    print("\n" + "=" * 60)
+    print("Demo Complete!")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,69 @@
+#!/usr/bin/env python3
+"""Run all examples and collect PASS/SKIP/FAIL results."""
+import subprocess
+import sys
+import os
+from pathlib import Path
+
+EXAMPLES_DIR = Path(__file__).parent
+RESULTS = []
+
+def run_example(path: Path) -> tuple:
+    """Run an example and return (name, status, reason)."""
+    name = f"{path.parent.name}/{path.name}"
+    try:
+        result = subprocess.run(
+            [sys.executable, str(path)],
+            capture_output=True,
+            text=True,
+            timeout=60,
+            env={**os.environ, "PYTHONPATH": str(EXAMPLES_DIR.parent / "src")}
+        )
+        output = result.stdout + result.stderr
+        if "PASSED" in output:
+            return (name, "PASS", "")
+        elif "SKIPPED" in output:
+            return (name, "SKIP", output.split("SKIPPED:")[-1].strip()[:50])
+        elif result.returncode != 0:
+            error = output.strip().split("\n")[-1][:80]
+            return (name, "FAIL", error)
+        else:
+            return (name, "PASS", "")
+    except subprocess.TimeoutExpired:
+        return (name, "FAIL", "Timeout")
+    except Exception as e:
+        return (name, "FAIL", str(e)[:50])
+
+def main():
+    print("=" * 70)
+    print("EXAMPLE RUNNER - PASS/SKIP/FAIL SUMMARY")
+    print("=" * 70)
+    
+    # Find all example files
+    examples = []
+    for subdir in ["db", "vector", "observability", "multi_agent", "workflows"]:
+        subpath = EXAMPLES_DIR / subdir
+        if subpath.exists():
+            examples.extend(sorted(subpath.glob("*_wow.py")))
+    
+    print(f"\nFound {len(examples)} examples to run\n")
+    
+    for ex in examples:
+        name, status, reason = run_example(ex)
+        RESULTS.append((name, status, reason))
+        icon = {"PASS": "✅", "SKIP": "⏭️", "FAIL": "❌"}.get(status, "?")
+        reason_str = f" ({reason})" if reason else ""
+        print(f"{icon} {status:4} | {name:45} {reason_str}")
+    
+    # Summary
+    print("\n" + "=" * 70)
+    passed = sum(1 for _, s, _ in RESULTS if s == "PASS")
+    skipped = sum(1 for _, s, _ in RESULTS if s == "SKIP")
+    failed = sum(1 for _, s, _ in RESULTS if s == "FAIL")
+    print(f"SUMMARY: {passed} PASS | {skipped} SKIP | {failed} FAIL | {len(RESULTS)} TOTAL")
+    print("=" * 70)
+    
+    return 0 if failed == 0 else 1
+
+if __name__ == "__main__":
+    sys.exit(main())
@@ -0,0 +1,94 @@
+#!/usr/bin/env python3
+"""
+Example: Creating Skills with PraisonAI CLI
+
+This example demonstrates how to create Agent Skills using the CLI.
+"""
+
+import subprocess
+import tempfile
+import os
+from pathlib import Path
+
+
+def example_create_skill_with_template():
+    """Create a skill using template mode (no API key required)."""
+    print("=" * 60)
+    print("Example 1: Create skill with template")
+    print("=" * 60)
+    
+    with tempfile.TemporaryDirectory() as tmpdir:
+        result = subprocess.run([
+            "praisonai", "skills", "create",
+            "--name", "my-template-skill",
+            "--description", "A skill for processing text files",
+            "--author", "example-team",
+            "--license", "MIT",
+            "--template",
+            "--output-dir", tmpdir
+        ], capture_output=True, text=True)
+        
+        print(result.stdout)
+        if result.returncode == 0:
+            skill_md = Path(tmpdir) / "my-template-skill" / "SKILL.md"
+            print(f"\nGenerated SKILL.md:\n{skill_md.read_text()[:500]}...")
+        else:
+            print(f"Error: {result.stderr}")
+
+
+def example_create_skill_with_ai():
+    """Create a skill using AI generation (requires API key)."""
+    print("\n" + "=" * 60)
+    print("Example 2: Create skill with AI generation")
+    print("=" * 60)
+    
+    if not os.environ.get("OPENAI_API_KEY"):
+        print("Skipping: OPENAI_API_KEY not set")
+        return
+    
+    with tempfile.TemporaryDirectory() as tmpdir:
+        result = subprocess.run([
+            "praisonai", "skills", "create",
+            "--name", "csv-analyzer",
+            "--description", "Analyze CSV files and generate statistical reports",
+            "--output-dir", tmpdir
+        ], capture_output=True, text=True)
+        
+        print(result.stdout)
+        if result.returncode == 0:
+            skill_md = Path(tmpdir) / "csv-analyzer" / "SKILL.md"
+            print(f"\nGenerated SKILL.md:\n{skill_md.read_text()[:800]}...")
+            
+            # Check if script was generated
+            script_path = Path(tmpdir) / "csv-analyzer" / "scripts" / "skill.py"
+            if script_path.exists():
+                print(f"\nGenerated skill.py:\n{script_path.read_text()[:500]}...")
+
+
+def example_create_skill_with_script():
+    """Create a skill with auto-generated Python script."""
+    print("\n" + "=" * 60)
+    print("Example 3: Create skill with script")
+    print("=" * 60)
+    
+    with tempfile.TemporaryDirectory() as tmpdir:
+        result = subprocess.run([
+            "praisonai", "skills", "create",
+            "--name", "data-processor",
+            "--description", "Process and transform data files",
+            "--template",
+            "--script",
+            "--output-dir", tmpdir
+        ], capture_output=True, text=True)
+        
+        print(result.stdout)
+        if result.returncode == 0:
+            script_path = Path(tmpdir) / "data-processor" / "scripts" / "skill.py"
+            if script_path.exists():
+                print(f"\nGenerated skill.py:\n{script_path.read_text()}")
+
+
+if __name__ == "__main__":
+    example_create_skill_with_template()
+    example_create_skill_with_ai()
+    example_create_skill_with_script()
@@ -0,0 +1,137 @@
+#!/usr/bin/env python3
+"""
+Example: Multi-Agent CLI Usage
+
+This example demonstrates how to use the praisonai agents command
+to define and run multiple agents from the command line.
+"""
+
+import subprocess
+import os
+
+
+def example_single_agent():
+    """Run a single agent with a simple task."""
+    print("=" * 60)
+    print("Example 1: Single Agent")
+    print("=" * 60)
+    
+    result = subprocess.run([
+        "praisonai", "agents", "run",
+        "--agent", "assistant:Helper",
+        "--task", "What is the capital of France?"
+    ], capture_output=True, text=True)
+    
+    print(result.stdout)
+    if result.returncode != 0:
+        print(f"Error: {result.stderr}")
+
+
+def example_agent_with_tools():
+    """Run an agent with tools."""
+    print("\n" + "=" * 60)
+    print("Example 2: Agent with Tools")
+    print("=" * 60)
+    
+    result = subprocess.run([
+        "praisonai", "agents", "run",
+        "--agent", "researcher:Research Analyst:internet_search",
+        "--task", "Find the latest news about renewable energy"
+    ], capture_output=True, text=True)
+    
+    print(result.stdout)
+
+
+def example_multiple_agents_sequential():
+    """Run multiple agents in sequential mode."""
+    print("\n" + "=" * 60)
+    print("Example 3: Multiple Agents (Sequential)")
+    print("=" * 60)
+    
+    result = subprocess.run([
+        "praisonai", "agents", "run",
+        "--agent", "researcher:Research Analyst:internet_search",
+        "--agent", "writer:Content Writer:write_file",
+        "--task", "Research AI trends and write a brief summary"
+    ], capture_output=True, text=True)
+    
+    print(result.stdout)
+
+
+def example_multiple_agents_parallel():
+    """Run multiple agents in parallel mode."""
+    print("\n" + "=" * 60)
+    print("Example 4: Multiple Agents (Parallel)")
+    print("=" * 60)
+    
+    result = subprocess.run([
+        "praisonai", "agents", "run",
+        "--agent", "analyst1:Market Analyst",
+        "--agent", "analyst2:Tech Analyst",
+        "--process", "parallel",
+        "--task", "Analyze the current state of AI industry"
+    ], capture_output=True, text=True)
+    
+    print(result.stdout)
+
+
+def example_with_custom_llm():
+    """Run agents with a custom LLM model."""
+    print("\n" + "=" * 60)
+    print("Example 5: Custom LLM Model")
+    print("=" * 60)
+    
+    result = subprocess.run([
+        "praisonai", "agents", "run",
+        "--agent", "coder:Developer:execute_command",
+        "--llm", "gpt-4o-mini",
+        "--task", "Write a simple hello world Python script"
+    ], capture_output=True, text=True)
+    
+    print(result.stdout)
+
+
+def example_with_instructions():
+    """Run agents with additional instructions."""
+    print("\n" + "=" * 60)
+    print("Example 6: With Additional Instructions")
+    print("=" * 60)
+    
+    result = subprocess.run([
+        "praisonai", "agents", "run",
+        "--agent", "analyst:Data Analyst",
+        "--instructions", "Be concise and provide only key insights",
+        "--task", "Explain the benefits of using AI in healthcare"
+    ], capture_output=True, text=True)
+    
+    print(result.stdout)
+
+
+def example_list_tools():
+    """List available tools for agents."""
+    print("\n" + "=" * 60)
+    print("Example 7: List Available Tools")
+    print("=" * 60)
+    
+    result = subprocess.run([
+        "praisonai", "agents", "list"
+    ], capture_output=True, text=True)
+    
+    print(result.stdout)
+
+
+if __name__ == "__main__":
+    # Check for API key
+    if not os.environ.get("OPENAI_API_KEY"):
+        print("Warning: OPENAI_API_KEY not set. Some examples may fail.")
+        print()
+    
+    # Run examples
+    example_list_tools()
+    example_single_agent()
+    # Uncomment to run more examples:
+    # example_agent_with_tools()
+    # example_multiple_agents_sequential()
+    # example_multiple_agents_parallel()
+    # example_with_custom_llm()
+    # example_with_instructions()
@@ -0,0 +1,137 @@
+#!/usr/bin/env python3
+"""
+Basic Thinking Budgets Example for PraisonAI Agents.
+
+This example demonstrates how to use thinking budgets to:
+1. Configure token budgets for extended thinking
+2. Use predefined budget levels
+3. Track thinking usage
+4. Adapt budgets based on complexity
+
+Usage:
+    python basic_thinking.py
+"""
+
+from praisonaiagents.thinking import (
+    ThinkingBudget, ThinkingConfig, ThinkingUsage, ThinkingTracker
+)
+from praisonaiagents.thinking.budget import BudgetLevel
+
+
+def main():
+    print("=" * 60)
+    print("Thinking Budgets Demo")
+    print("=" * 60)
+    
+    # ==========================================================================
+    # Budget Levels
+    # ==========================================================================
+    print("\n--- Budget Levels ---")
+    
+    levels = [
+        ("Minimal", ThinkingBudget.minimal()),
+        ("Low", ThinkingBudget.low()),
+        ("Medium", ThinkingBudget.medium()),
+        ("High", ThinkingBudget.high()),
+        ("Maximum", ThinkingBudget.maximum()),
+    ]
+    
+    for name, budget in levels:
+        print(f"  {name}: {budget.max_tokens:,} tokens")
+    
+    # ==========================================================================
+    # Custom Budget
+    # ==========================================================================
+    print("\n--- Custom Budget ---")
+    
+    custom_budget = ThinkingBudget(
+        max_tokens=12000,
+        min_tokens=2000,
+        adaptive=True,
+        max_time_seconds=120.0
+    )
+    print(f"  Max tokens: {custom_budget.max_tokens:,}")
+    print(f"  Min tokens: {custom_budget.min_tokens:,}")
+    print(f"  Adaptive: {custom_budget.adaptive}")
+    print(f"  Time limit: {custom_budget.max_time_seconds}s")
+    
+    # ==========================================================================
+    # Complexity-Based Scaling
+    # ==========================================================================
+    print("\n--- Complexity-Based Token Allocation ---")
+    
+    budget = ThinkingBudget(
+        max_tokens=16000,
+        min_tokens=2000,
+        adaptive=True
+    )
+    
+    complexities = [0.0, 0.25, 0.5, 0.75, 1.0]
+    for complexity in complexities:
+        tokens = budget.get_tokens_for_complexity(complexity)
+        bar = "█" * int(tokens / 1000)
+        print(f"  Complexity {complexity:.2f}: {tokens:,} tokens {bar}")
+    
+    # ==========================================================================
+    # Usage Tracking
+    # ==========================================================================
+    print("\n--- Usage Tracking ---")
+    
+    usage = ThinkingUsage(
+        budget_tokens=8000,
+        tokens_used=5000,
+        time_seconds=30.0,
+        budget_time=60.0
+    )
+    
+    print(f"  Tokens used: {usage.tokens_used:,} / {usage.budget_tokens:,}")
+    print(f"  Tokens remaining: {usage.tokens_remaining:,}")
+    print(f"  Utilization: {usage.token_utilization:.1%}")
+    print(f"  Over budget: {usage.is_over_budget}")
+    print(f"  Time remaining: {usage.time_remaining}s")
+    
+    # ==========================================================================
+    # Session Tracking
+    # ==========================================================================
+    print("\n--- Session Tracking ---")
+    
+    tracker = ThinkingTracker()
+    
+    # Simulate multiple thinking sessions
+    sessions = [
+        (8000, 4000, 20.0),
+        (8000, 6000, 35.0),
+        (16000, 12000, 60.0),
+        (8000, 9000, 45.0),  # Over budget
+    ]
+    
+    for budget_tokens, tokens_used, time_seconds in sessions:
+        session = tracker.start_session(budget_tokens=budget_tokens)
+        tracker.end_session(session, tokens_used=tokens_used, time_seconds=time_seconds)
+    
+    summary = tracker.get_summary()
+    print(f"  Total sessions: {summary['session_count']}")
+    print(f"  Total tokens used: {summary['total_tokens_used']:,}")
+    print(f"  Average tokens/session: {summary['average_tokens_per_session']:,.0f}")
+    print(f"  Average utilization: {summary['average_utilization']:.1%}")
+    print(f"  Over-budget sessions: {summary['over_budget_count']}")
+    
+    # ==========================================================================
+    # Serialization
+    # ==========================================================================
+    print("\n--- Serialization ---")
+    
+    budget = ThinkingBudget.from_level(BudgetLevel.HIGH)
+    data = budget.to_dict()
+    print(f"  Serialized: level={data['level']}, max_tokens={data['max_tokens']}")
+    
+    restored = ThinkingBudget.from_dict(data)
+    print(f"  Restored: {restored.max_tokens:,} tokens")
+    
+    print("\n" + "=" * 60)
+    print("Demo Complete!")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,44 @@
+"""ArXiv Tool Example.
+
+This example demonstrates how to use the ArXiv tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Usage:
+    python tool.py
+
+Note: No API key required!
+"""
+
+from praisonai_tools import ArxivTool
+
+
+def main():
+    # Initialize ArXiv tool (no API key needed)
+    arxiv = ArxivTool()
+    
+    # Example 1: Search ArXiv
+    print("=" * 60)
+    print("Example 1: Search ArXiv")
+    print("=" * 60)
+    
+    results = arxiv.search("transformer neural networks", max_results=3)
+    
+    if results and "error" in results[0]:
+        print(f"Error: {results[0]['error']}")
+    else:
+        print(f"Found {len(results)} papers:")
+        for paper in results:
+            print(f"\n  Title: {paper.get('title', 'N/A')[:60]}...")
+            authors = paper.get('authors', [])
+            if authors:
+                print(f"  Authors: {', '.join(authors[:2])}...")
+            print(f"  Published: {paper.get('published', 'N/A')}")
+            print(f"  PDF: {paper.get('pdf_url', 'N/A')}")
+    
+    print("\n✅ ArXiv tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,53 @@
+"""Calculator Tool Example.
+
+This example demonstrates how to use the Calculator tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Usage:
+    python tool.py
+
+Note: No API key required!
+"""
+
+from praisonai_tools import CalculatorTool
+
+
+def main():
+    # Initialize Calculator tool
+    calc = CalculatorTool()
+    
+    # Example 1: Basic arithmetic
+    print("=" * 60)
+    print("Example 1: Basic Arithmetic")
+    print("=" * 60)
+    
+    expressions = [
+        "2 + 2",
+        "10 * 5",
+        "100 / 4",
+        "2 ** 10",
+        "(10 + 5) * 2 - 3"
+    ]
+    
+    for expr in expressions:
+        result = calc.evaluate(expr)
+        print(f"  {expr} = {result.get('result', result)}")
+    
+    # Example 2: Percentage calculation
+    print("\n" + "=" * 60)
+    print("Example 2: Percentage Calculation")
+    print("=" * 60)
+    
+    result = calc.evaluate("250 * 0.15")
+    print(f"  15% of 250 = {result.get('result', result)}")
+    
+    result = calc.evaluate("1000 * (1 + 0.05) ** 3")
+    print(f"  $1000 at 5% for 3 years = ${result.get('result', 0):.2f}")
+    
+    print("\n✅ Calculator tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,75 @@
+"""DuckDuckGo Search Tool Example.
+
+This example demonstrates how to use the DuckDuckGo search tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Usage:
+    python tool.py
+
+Note: No API key required!
+"""
+
+from praisonai_tools import DuckDuckGoTool
+
+
+def main():
+    # Initialize DuckDuckGo tool (no API key needed)
+    ddg = DuckDuckGoTool()
+    
+    # Example 1: Web search
+    print("=" * 60)
+    print("Example 1: Web Search")
+    print("=" * 60)
+    
+    results = ddg.search("Python programming best practices", max_results=3)
+    
+    if results and "error" in results[0]:
+        print(f"Error: {results[0]['error']}")
+    else:
+        print(f"Found {len(results)} results:")
+        for r in results:
+            print(f"  - {r['title']}")
+            print(f"    URL: {r['url']}")
+            print(f"    Snippet: {r['snippet'][:100]}...")
+            print()
+    
+    # Example 2: News search
+    print("=" * 60)
+    print("Example 2: News Search")
+    print("=" * 60)
+    
+    news = ddg.news("artificial intelligence", max_results=3)
+    
+    if news and "error" in news[0]:
+        print(f"Error: {news[0]['error']}")
+    else:
+        print(f"Found {len(news)} news articles:")
+        for n in news:
+            print(f"  - {n['title']}")
+            print(f"    Source: {n.get('source', 'N/A')}")
+            print(f"    Date: {n.get('date', 'N/A')}")
+            print()
+    
+    # Example 3: Image search
+    print("=" * 60)
+    print("Example 3: Image Search")
+    print("=" * 60)
+    
+    images = ddg.images("sunset landscape", max_results=3)
+    
+    if images and "error" in images[0]:
+        print(f"Error: {images[0]['error']}")
+    else:
+        print(f"Found {len(images)} images:")
+        for img in images:
+            print(f"  - {img['title']}")
+            print(f"    Image URL: {img['image_url'][:60]}...")
+            print()
+    
+    print("✅ DuckDuckGo tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,48 @@
+"""Exa Search Tool Example.
+
+This example demonstrates how to use the Exa search tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+    export EXA_API_KEY=your_api_key
+
+Usage:
+    python tool.py
+"""
+
+import os
+from praisonai_tools import ExaTool
+
+
+def main():
+    # Check for API key
+    if not os.getenv("EXA_API_KEY"):
+        print("Error: EXA_API_KEY environment variable not set")
+        print("Get your API key from https://exa.ai/")
+        return
+    
+    # Initialize Exa tool
+    exa = ExaTool()
+    
+    # Example 1: Neural search
+    print("=" * 60)
+    print("Example 1: Neural Search")
+    print("=" * 60)
+    
+    results = exa.search("best practices for Python development", num_results=3)
+    
+    if results and "error" in results[0]:
+        print(f"Error: {results[0]['error']}")
+    else:
+        print(f"Found {len(results)} results:")
+        for r in results:
+            print(f"  - {r.get('title', 'N/A')[:50]}...")
+            print(f"    URL: {r.get('url', 'N/A')[:60]}...")
+            print(f"    Score: {r.get('score', 'N/A')}")
+            print()
+    
+    print("✅ Exa tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,45 @@
+"""Firecrawl Tool Example.
+
+This example demonstrates how to use the Firecrawl tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+    export FIRECRAWL_API_KEY=your_api_key
+
+Usage:
+    python tool.py
+"""
+
+import os
+from praisonai_tools import FirecrawlTool
+
+
+def main():
+    # Check for API key
+    if not os.getenv("FIRECRAWL_API_KEY"):
+        print("Error: FIRECRAWL_API_KEY environment variable not set")
+        print("Get your API key from https://firecrawl.dev/")
+        return
+    
+    # Initialize Firecrawl tool
+    firecrawl = FirecrawlTool()
+    
+    # Example 1: Scrape a page
+    print("=" * 60)
+    print("Example 1: Scrape a Page")
+    print("=" * 60)
+    
+    result = firecrawl.scrape("https://example.com")
+    
+    if "error" in result:
+        print(f"Error: {result['error']}")
+    else:
+        print(f"URL: {result.get('url', 'N/A')}")
+        markdown = result.get('markdown', '')
+        print(f"Content preview: {markdown[:300]}...")
+    
+    print("\n✅ Firecrawl tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,42 @@
+"""Hacker News Tool Example.
+
+This example demonstrates how to use the Hacker News tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Usage:
+    python tool.py
+
+Note: No API key required!
+"""
+
+from praisonai_tools import HackerNewsTool
+
+
+def main():
+    # Initialize Hacker News tool
+    hn = HackerNewsTool()
+    
+    # Example 1: Get top stories
+    print("=" * 60)
+    print("Example 1: Top Stories")
+    print("=" * 60)
+    
+    stories = hn.get_top_stories(limit=5)
+    
+    if stories and "error" in stories[0]:
+        print(f"Error: {stories[0]['error']}")
+    else:
+        print(f"Found {len(stories)} top stories:")
+        for story in stories:
+            print(f"  - {story.get('title', 'N/A')[:50]}...")
+            print(f"    Score: {story.get('score', 'N/A')} | Comments: {story.get('descendants', 'N/A')}")
+            print(f"    URL: {story.get('url', 'N/A')[:60]}...")
+            print()
+    
+    print("✅ Hacker News tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,40 @@
+"""Jina Reader Tool Example.
+
+This example demonstrates how to use the Jina Reader tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Usage:
+    python tool.py
+
+Note: Works without API key (with rate limits)
+"""
+
+from praisonai_tools import JinaTool
+
+
+def main():
+    # Initialize Jina tool (works without API key)
+    jina = JinaTool()
+    
+    # Example 1: Read a URL
+    print("=" * 60)
+    print("Example 1: Read URL Content")
+    print("=" * 60)
+    
+    result = jina.read("https://example.com")
+    
+    if "error" in result:
+        print(f"Error: {result['error']}")
+    else:
+        print(f"URL: {result.get('url', 'N/A')}")
+        print(f"Title: {result.get('title', 'N/A')}")
+        content = result.get('content', '')
+        print(f"Content preview: {content[:300]}...")
+    
+    print("\n✅ Jina tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,56 @@
+"""PostgreSQL Tool Example.
+
+This example demonstrates how to use the PostgreSQL tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+    Docker: docker run -d --name postgres -e POSTGRES_PASSWORD=praison123 -e POSTGRES_DB=praisonai -p 5432:5432 postgres:16
+
+Usage:
+    python tool.py
+"""
+
+from praisonai_tools import PostgresTool
+
+
+def main():
+    # Initialize PostgreSQL tool
+    pg = PostgresTool(
+        host="localhost",
+        port=5432,
+        database="praisonai",
+        user="postgres",
+        password="praison123"
+    )
+    
+    # Example 1: List tables
+    print("=" * 60)
+    print("Example 1: List Tables")
+    print("=" * 60)
+    
+    tables = pg.list_tables()
+    
+    if isinstance(tables, dict) and "error" in tables:
+        print(f"Error: {tables['error']}")
+    else:
+        print(f"Found {len(tables)} tables:")
+        for t in tables[:10]:
+            print(f"  - {t.get('table_name', t)}")
+    
+    # Example 2: Query
+    print("\n" + "=" * 60)
+    print("Example 2: Execute Query")
+    print("=" * 60)
+    
+    result = pg.query("SELECT version()")
+    
+    if isinstance(result, dict) and "error" in result:
+        print(f"Error: {result['error']}")
+    else:
+        print(f"PostgreSQL version: {result}")
+    
+    print("\n✅ PostgreSQL tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,47 @@
+"""Serper Tool Example.
+
+This example demonstrates how to use the Serper (Google Search) tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+    export SERPER_API_KEY=your_api_key
+
+Usage:
+    python tool.py
+"""
+
+import os
+from praisonai_tools import SerperTool
+
+
+def main():
+    # Check for API key
+    if not os.getenv("SERPER_API_KEY"):
+        print("Error: SERPER_API_KEY environment variable not set")
+        print("Get your API key from https://serper.dev/")
+        return
+    
+    # Initialize Serper tool
+    serper = SerperTool()
+    
+    # Example 1: Web search
+    print("=" * 60)
+    print("Example 1: Google Web Search")
+    print("=" * 60)
+    
+    results = serper.search("Python programming tutorials", max_results=3)
+    
+    if results and "error" in results[0]:
+        print(f"Error: {results[0]['error']}")
+    else:
+        print(f"Found {len(results)} results:")
+        for r in results:
+            print(f"  - {r.get('title', 'N/A')[:50]}...")
+            print(f"    URL: {r.get('link', 'N/A')[:60]}...")
+            print()
+    
+    print("✅ Serper tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,57 @@
+"""Tavily Search Tool Example.
+
+This example demonstrates how to use the Tavily search tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+    export TAVILY_API_KEY=your_api_key
+
+Usage:
+    python tool.py
+"""
+
+import os
+from praisonai_tools import TavilyTool
+
+def main():
+    # Check for API key
+    if not os.getenv("TAVILY_API_KEY"):
+        print("Error: TAVILY_API_KEY environment variable not set")
+        print("Get your API key from https://tavily.com/")
+        return
+    
+    # Initialize Tavily tool
+    tavily = TavilyTool()
+    
+    # Example 1: Basic search
+    print("=" * 60)
+    print("Example 1: Basic Search")
+    print("=" * 60)
+    
+    results = tavily.search("What is quantum computing?", max_results=3)
+    
+    if "error" in results:
+        print(f"Error: {results['error']}")
+    else:
+        print(f"Query: {results.get('query')}")
+        if "answer" in results:
+            print(f"\nAI Answer: {results['answer'][:200]}...")
+        print(f"\nResults ({len(results.get('results', []))}):")
+        for r in results.get("results", []):
+            print(f"  - {r['title']}")
+            print(f"    URL: {r['url']}")
+            print(f"    Score: {r.get('score', 'N/A')}")
+    
+    # Example 2: Search context for RAG
+    print("\n" + "=" * 60)
+    print("Example 2: Search Context (for RAG)")
+    print("=" * 60)
+    
+    context = tavily.search_context("Python best practices 2024")
+    print(f"Context (first 300 chars): {context[:300]}...")
+    
+    print("\n✅ Tavily tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,69 @@
+"""Wikipedia Tool Example.
+
+This example demonstrates how to use the Wikipedia tool with PraisonAI agents.
+
+Requirements:
+    pip install "praisonai[tools]"
+
+Usage:
+    python tool.py
+
+Note: No API key required!
+"""
+
+from praisonai_tools import WikipediaTool
+
+
+def main():
+    # Initialize Wikipedia tool (no API key needed)
+    wiki = WikipediaTool()
+    
+    # Example 1: Search Wikipedia
+    print("=" * 60)
+    print("Example 1: Search Wikipedia")
+    print("=" * 60)
+    
+    results = wiki.search("Python programming", max_results=5)
+    
+    if results and "error" in results[0]:
+        print(f"Error: {results[0]['error']}")
+    else:
+        print(f"Found {len(results)} results:")
+        for r in results:
+            print(f"  - {r['title']}")
+    
+    # Example 2: Get page summary
+    print("\n" + "=" * 60)
+    print("Example 2: Get Page Summary")
+    print("=" * 60)
+    
+    summary = wiki.summary("Artificial intelligence", sentences=3)
+    
+    if "error" in summary:
+        print(f"Error: {summary['error']}")
+    else:
+        print(f"Title: {summary['title']}")
+        print(f"Summary: {summary['summary'][:300]}...")
+    
+    # Example 3: Get full page
+    print("\n" + "=" * 60)
+    print("Example 3: Get Full Page")
+    print("=" * 60)
+    
+    page = wiki.get_page("Machine learning")
+    
+    if "error" in page:
+        print(f"Error: {page['error']}")
+        if "options" in page:
+            print(f"Options: {page['options'][:5]}")
+    else:
+        print(f"Title: {page['title']}")
+        print(f"URL: {page['url']}")
+        print(f"Categories: {page['categories'][:3]}")
+        print(f"Content preview: {page['content'][:200]}...")
+    
+    print("\n✅ Wikipedia tool working correctly!")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,21 @@
+"""ChromaDB Vector Store - Basic Test"""
+import sys
+sys.path.insert(0, 'src/praisonai')
+from praisonai.persistence import create_knowledge_store
+from praisonai.persistence.knowledge.base import KnowledgeDocument
+
+store = create_knowledge_store("chroma", path="/tmp/chroma_demo")
+try:
+    store.delete_collection("demo")
+except Exception:
+    pass
+store.create_collection("demo", dimension=1536)
+docs = [
+    KnowledgeDocument(id="1", content="Python is a programming language", embedding=[0.1]*1536),
+    KnowledgeDocument(id="2", content="JavaScript runs in browsers", embedding=[0.2]*1536)
+]
+store.insert("demo", docs)
+results = store.search("demo", query_embedding=[0.1]*1536, limit=1)
+print(f"Found: {len(results)} results")
+assert len(results) >= 1
+print("PASSED: ChromaDB vector store")
@@ -0,0 +1,20 @@
+"""LanceDB Vector Store - Basic Test"""
+import sys
+sys.path.insert(0, 'src/praisonai')
+try:
+    from praisonai.persistence import create_knowledge_store
+    from praisonai.persistence.knowledge.base import KnowledgeDocument
+    
+    store = create_knowledge_store("lancedb", path="/tmp/lancedb_demo")
+    store.create_collection("demo", dimension=1536)
+    docs = [
+        KnowledgeDocument(id="doc1", content="The Eiffel Tower is in Paris", embedding=[0.1]*1536),
+        KnowledgeDocument(id="doc2", content="The Statue of Liberty is in New York", embedding=[0.2]*1536)
+    ]
+    store.insert("demo", docs)
+    results = store.search("demo", query_embedding=[0.1]*1536, limit=1)
+    print(f"Found: {len(results)} results")
+    assert len(results) >= 1
+    print("PASSED: LanceDB vector store")
+except ImportError as e:
+    print(f"SKIPPED: LanceDB - {e}")
@@ -0,0 +1,23 @@
+"""PGVector Knowledge Store - Basic Test (requires Docker)"""
+import sys
+import os
+sys.path.insert(0, 'src/praisonai')
+from praisonai.persistence import create_knowledge_store
+from praisonai.persistence.knowledge.base import KnowledgeDocument
+
+# Docker: docker run -d --name pgvector -e POSTGRES_PASSWORD=postgres -p 5433:5432 pgvector/pgvector:pg16
+url = os.getenv("PGVECTOR_URL", "postgresql://postgres:postgres@localhost:5433/postgres")
+try:
+    store = create_knowledge_store("pgvector", url=url)
+    store.create_collection("demo", dimension=1536)
+    docs = [
+        KnowledgeDocument(id="1", content="Kubernetes orchestrates containers", embedding=[0.1]*1536),
+        KnowledgeDocument(id="2", content="Docker packages applications", embedding=[0.2]*1536)
+    ]
+    store.insert("demo", docs)
+    results = store.search("demo", query_embedding=[0.1]*1536, limit=1)
+    print(f"Found: {len(results)} results")
+    assert len(results) >= 1
+    print("PASSED: PGVector vector store")
+except Exception as e:
+    print(f"SKIPPED: PGVector - {e}")
@@ -0,0 +1,23 @@
+"""Qdrant Vector Store - Basic Test (requires Docker)"""
+import sys, os
+sys.path.insert(0, 'src/praisonai')
+from praisonai.persistence import create_knowledge_store
+from praisonai.persistence.knowledge.base import KnowledgeDocument
+
+# Docker: docker run -d --name qdrant -p 6333:6333 qdrant/qdrant
+url = os.getenv("QDRANT_URL", "http://localhost:6333")
+store = create_knowledge_store("qdrant", url=url)
+try:
+    store.delete_collection("demo")
+except Exception:
+    pass
+store.create_collection("demo", dimension=1536)
+docs = [
+    KnowledgeDocument(id="1", content="Machine learning is AI", embedding=[0.1]*1536),
+    KnowledgeDocument(id="2", content="Deep learning uses neural nets", embedding=[0.2]*1536)
+]
+store.insert("demo", docs)
+results = store.search("demo", query_embedding=[0.1]*1536, limit=1)
+print(f"Found: {len(results)} results")
+assert len(results) >= 1
+print("PASSED: Qdrant vector store")
@@ -54,6 +54,8 @@ except ImportError:
    MCP = None
 from .session import Session
 from .memory.memory import Memory
+from .db import db
+from .obs import obs
 # Workflows - import from dedicated workflows module
 from .workflows import (
    Workflow, WorkflowStep, WorkflowContext, StepResult,
@@ -257,6 +259,8 @@ __all__ = [
    'AutoAgents',
    'Session',
    'Memory',
+    'db',
+    'obs',
    'display_interaction',
    'display_self_reflection',
    'display_instruction',
@@ -252,7 +252,9 @@ class Agent:
        history_in_context: Optional[int] = None,
        auto_save: Optional[str] = None,
        skills: Optional[List[str]] = None,
-        skills_dirs: Optional[List[str]] = None
+        skills_dirs: Optional[List[str]] = None,
+        db: Optional[Any] = None,
+        session_id: Optional[str] = None
    ):
        """Initialize an Agent instance.

@@ -615,6 +617,11 @@ Your Goal: {self.goal}
        self._skill_manager = None  # Lazy loaded
        self._skills_initialized = False

+        # Database persistence (lazy - no imports until used)
+        self._db = db
+        self._session_id = session_id
+        self._db_initialized = False
+
    @property
    def console(self):
        """Lazily initialize Rich Console only when needed."""
@@ -651,8 +658,45 @@ Your Goal: {self.goal}
                self._skill_manager.discover(self._skills_dirs, include_defaults=False)
            
            self._skills_initialized = True
+            
+            # Auto-add skill execution tools if not already present
+            self._add_skill_tools()
        return self._skill_manager
    
+    def _add_skill_tools(self):
+        """Add tools required for skill execution (read_file, run_skill_script).
+        
+        Uses lazy imports from praisonaiagents.tools to avoid performance impact
+        when skills are not used.
+        """
+        # Check if tools already include required capabilities
+        tool_names = set()
+        for tool in self.tools:
+            if callable(tool) and hasattr(tool, '__name__'):
+                tool_names.add(tool.__name__)
+            elif hasattr(tool, 'name'):
+                tool_names.add(tool.name)
+        
+        # Add read_file if not present
+        if 'read_file' not in tool_names:
+            try:
+                from ..tools import read_file
+                self.tools.append(read_file)
+                logging.debug("Added read_file tool for skill support")
+            except ImportError:
+                logging.warning("Could not import read_file tool for skills")
+        
+        # Add run_skill_script from skill_tools module
+        if 'run_skill_script' not in tool_names:
+            try:
+                from ..tools.skill_tools import create_skill_tools
+                # Create skill tools with current working directory
+                skill_tools = create_skill_tools()
+                self.tools.append(skill_tools.run_skill_script)
+                logging.debug("Added run_skill_script tool for skill support")
+            except ImportError as e:
+                logging.warning(f"Could not import skill_tools: {e}")
+    
    def get_skills_prompt(self) -> str:
        """Get the XML prompt for available skills.
        
@@ -1321,6 +1365,13 @@ Your Goal: {self.goal}"""
                if self.verbose:
                    self._display_memory_info()
        
+        # Add skills prompt if skills are configured
+        if self._skills or self._skills_dirs:
+            skills_prompt = self.get_skills_prompt()
+            if skills_prompt:
+                system_prompt += f"\n\n## Available Skills\n{skills_prompt}"
+                system_prompt += "\n\nWhen a skill is relevant to the task, read its SKILL.md file to get detailed instructions. If the skill has scripts in its scripts/ directory, you can execute them using the execute_code or run_script tool."
+        
        # Add tool usage instructions if tools are available
        # Use provided tools or fall back to self.tools
        tools_to_use = tools if tools is not None else self.tools
@@ -1913,7 +1964,108 @@ Your Goal: {self.goal}"""
        #         expand=False
        #     )

+    def _init_db_session(self):
+        """Initialize DB session if db adapter is provided (lazy, first chat only)."""
+        if self._db is None or self._db_initialized:
+            return
+        
+        # Generate session_id if not provided: default to per-hour ID (YYYYMMDDHH-agentname)
+        if self._session_id is None:
+            import hashlib
+            from datetime import datetime, timezone
+            # Per-hour session ID: YYYYMMDDHH (UTC) + agent name hash for uniqueness
+            hour_str = datetime.now(timezone.utc).strftime("%Y%m%d%H")
+            agent_hash = hashlib.md5(self.name.encode()).hexdigest()[:6]
+            self._session_id = f"{hour_str}-{agent_hash}"
+        
+        # Call db adapter's on_agent_start to get previous messages
+        try:
+            history = self._db.on_agent_start(
+                agent_name=self.name,
+                session_id=self._session_id,
+                user_id=self.user_id,
+                metadata={"role": self.role, "goal": self.goal}
+            )
+            
+            # Restore chat history from previous session
+            if history:
+                for msg in history:
+                    self.chat_history.append({
+                        "role": msg.role,
+                        "content": msg.content
+                    })
+                logging.info(f"Resumed session {self._session_id} with {len(history)} messages")
+        except Exception as e:
+            logging.warning(f"Failed to initialize DB session: {e}")
+        
+        self._db_initialized = True
+        self._current_run_id = None  # Track current run
+
+    def _start_run(self, input_content: str):
+        """Start a new run (turn) for persistence tracking."""
+        if self._db is None:
+            return
+        
+        import uuid
+        self._current_run_id = f"run-{uuid.uuid4().hex[:12]}"
+        
+        try:
+            if hasattr(self._db, 'on_run_start'):
+                self._db.on_run_start(
+                    session_id=self._session_id,
+                    run_id=self._current_run_id,
+                    input_content=input_content,
+                    metadata={"agent_name": self.name}
+                )
+        except Exception as e:
+            logging.warning(f"Failed to start run: {e}")
+
+    def _end_run(self, output_content: str, status: str = "completed", metrics: dict = None):
+        """End the current run (turn)."""
+        if self._db is None or self._current_run_id is None:
+            return
+        
+        try:
+            if hasattr(self._db, 'on_run_end'):
+                self._db.on_run_end(
+                    session_id=self._session_id,
+                    run_id=self._current_run_id,
+                    output_content=output_content,
+                    status=status,
+                    metrics=metrics or {},
+                    metadata={"agent_name": self.name}
+                )
+        except Exception as e:
+            logging.warning(f"Failed to end run: {e}")
+        
+        self._current_run_id = None
+
+    def _persist_message(self, role: str, content: str):
+        """Persist a message to the DB if adapter is provided."""
+        if self._db is None:
+            return
+        
+        try:
+            if role == "user":
+                self._db.on_user_message(self._session_id, content)
+            elif role == "assistant":
+                self._db.on_agent_message(self._session_id, content)
+        except Exception as e:
+            logging.warning(f"Failed to persist message: {e}")
+
+    @property
+    def session_id(self) -> Optional[str]:
+        """Get the current session ID."""
+        return self._session_id
+
    def chat(self, 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):
+        # Initialize DB session on first chat (lazy)
+        self._init_db_session()
+        
+        # Start a new run for this chat turn
+        prompt_str = prompt if isinstance(prompt, str) else str(prompt)
+        self._start_run(prompt_str)
+        
        # Reset the final display flag for each new conversation
        self._final_display_shown = False
        
@@ -2010,6 +2162,8 @@ Your Goal: {self.goal}"""
                        self.chat_history[-1].get("content") == normalized_content):
                    # Add user message to chat history BEFORE LLM call so handoffs can access it
                    self.chat_history.append({"role": "user", "content": normalized_content})
+                    # Persist user message to DB
+                    self._persist_message("user", normalized_content)
                
                try:
                    # Pass everything to LLM class
@@ -2039,6 +2193,8 @@ Your Goal: {self.goal}"""
                    )

                    self.chat_history.append({"role": "assistant", "content": response_text})
+                    # Persist assistant message to DB
+                    self._persist_message("assistant", response_text)

                    # Log completion time if in debug mode
                    if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
@@ -2083,6 +2239,8 @@ Your Goal: {self.goal}"""
                    self.chat_history[-1].get("content") == normalized_content):
                # Add user message to chat history BEFORE LLM call so handoffs can access it
                self.chat_history.append({"role": "user", "content": normalized_content})
+                # Persist user message to DB (OpenAI path)
+                self._persist_message("user", normalized_content)

            reflection_count = 0
            start_time = time.time()
@@ -2122,6 +2280,8 @@ Your Goal: {self.goal}"""
                            # Add to chat history and return raw response
                            # User message already added before LLM call via _build_messages
                            self.chat_history.append({"role": "assistant", "content": response_text})
+                            # Persist assistant message to DB
+                            self._persist_message("assistant", response_text)
                            # Apply guardrail validation even for JSON output
                            try:
                                validated_response = self._apply_guardrail_with_retry(response_text, original_prompt, temperature, tools, task_name, task_description, task_id)
@@ -2137,6 +2297,8 @@ Your Goal: {self.goal}"""
                        if not self.self_reflect:
                            # User message already added before LLM call via _build_messages
                            self.chat_history.append({"role": "assistant", "content": response_text})
+                            # Persist assistant message to DB (non-reflect path)
+                            self._persist_message("assistant", response_text)
                            if self.verbose:
                                logging.debug(f"Agent {self.name} final response: {response_text}")
                            # Return only reasoning content if reasoning_steps is True
@@ -2225,11 +2387,13 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                                    validated_response = self._apply_guardrail_with_retry(response_text, original_prompt, temperature, tools, task_name, task_description, task_id)
                                    # Execute callback after validation
                                    self._execute_callback_and_display(original_prompt, validated_response, time.time() - start_time, task_name, task_description, task_id)
+                                    self._end_run(validated_response, "completed", {"duration_ms": (time.time() - start_time) * 1000})
                                    return validated_response
                                except Exception as e:
                                    logging.error(f"Agent {self.name}: Guardrail validation failed after reflection: {e}")
                                    # Rollback chat history on guardrail failure
                                    self.chat_history = self.chat_history[:chat_history_length]
+                                    self._end_run(None, "error", {"error": str(e)})
                                    return None

                            # Check if we've hit max reflections
@@ -0,0 +1,64 @@
+"""
+Background Agents Module for PraisonAI Agents.
+
+Provides the ability to run agents in the background, allowing:
+- Long-running tasks without blocking
+- Task queuing and management
+- Progress monitoring and notifications
+- Graceful cancellation
+
+Zero Performance Impact:
+- All imports are lazy loaded via __getattr__
+- Background processing only when explicitly started
+- No overhead when not in use
+
+Usage:
+    from praisonaiagents.background import BackgroundRunner, BackgroundTask
+    
+    # Create a background runner
+    runner = BackgroundRunner()
+    
+    # Submit a task
+    task = runner.submit(
+        agent=my_agent,
+        prompt="Research AI trends",
+        callback=on_complete
+    )
+    
+    # Check status
+    print(task.status)  # "running", "completed", "failed"
+    
+    # Wait for completion
+    result = await task.wait()
+"""
+
+__all__ = [
+    # Core classes
+    "BackgroundRunner",
+    "BackgroundTask",
+    # Status enum
+    "TaskStatus",
+    # Configuration
+    "BackgroundConfig",
+]
+
+
+def __getattr__(name: str):
+    """Lazy load module components to avoid import overhead."""
+    if name == "BackgroundRunner":
+        from .runner import BackgroundRunner
+        return BackgroundRunner
+    
+    if name == "BackgroundTask":
+        from .task import BackgroundTask
+        return BackgroundTask
+    
+    if name == "TaskStatus":
+        from .task import TaskStatus
+        return TaskStatus
+    
+    if name == "BackgroundConfig":
+        from .config import BackgroundConfig
+        return BackgroundConfig
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -0,0 +1,17 @@
+"""
+Background Configuration for PraisonAI Agents.
+"""
+
+from dataclasses import dataclass, field
+from typing import Optional
+
+
+@dataclass
+class BackgroundConfig:
+    """Configuration for background task execution."""
+    max_concurrent_tasks: int = 5
+    default_timeout: Optional[float] = None  # None = no timeout
+    auto_cleanup: bool = True  # Auto-remove completed tasks
+    cleanup_delay: float = 300.0  # Seconds to keep completed tasks
+    enable_notifications: bool = True
+    log_progress: bool = True
@@ -0,0 +1,314 @@
+"""
+Background Runner for PraisonAI Agents.
+
+Manages background task execution.
+"""
+
+import asyncio
+import logging
+from typing import Optional, List, Dict, Any, Callable, Union
+from datetime import datetime
+
+from .task import BackgroundTask, TaskStatus
+from .config import BackgroundConfig
+
+logger = logging.getLogger(__name__)
+
+
+class BackgroundRunner:
+    """
+    Manages background task execution.
+    
+    Provides:
+    - Task submission and queuing
+    - Concurrent execution management
+    - Progress monitoring
+    - Task cancellation
+    
+    Example:
+        runner = BackgroundRunner()
+        
+        # Submit a task
+        task = await runner.submit(
+            func=my_agent.start,
+            args=("Research AI trends",),
+            name="research_task"
+        )
+        
+        # Check status
+        print(task.status)
+        
+        # Wait for result
+        result = await task.wait()
+    """
+    
+    def __init__(self, config: Optional[BackgroundConfig] = None):
+        """
+        Initialize the background runner.
+        
+        Args:
+            config: Configuration for background execution
+        """
+        self.config = config or BackgroundConfig()
+        self._tasks: Dict[str, BackgroundTask] = {}
+        self._semaphore = asyncio.Semaphore(self.config.max_concurrent_tasks)
+        self._running = False
+        self._cleanup_task: Optional[asyncio.Task] = None
+    
+    @property
+    def tasks(self) -> List[BackgroundTask]:
+        """Get all tasks."""
+        return list(self._tasks.values())
+    
+    @property
+    def running_tasks(self) -> List[BackgroundTask]:
+        """Get currently running tasks."""
+        return [t for t in self._tasks.values() if t.is_running]
+    
+    @property
+    def pending_tasks(self) -> List[BackgroundTask]:
+        """Get pending tasks."""
+        return [t for t in self._tasks.values() if t.status == TaskStatus.PENDING]
+    
+    async def submit(
+        self,
+        func: Callable,
+        args: tuple = (),
+        kwargs: Optional[Dict[str, Any]] = None,
+        name: Optional[str] = None,
+        timeout: Optional[float] = None,
+        on_complete: Optional[Callable[[BackgroundTask], None]] = None,
+        on_progress: Optional[Callable[[BackgroundTask], None]] = None
+    ) -> BackgroundTask:
+        """
+        Submit a task for background execution.
+        
+        Args:
+            func: Function to execute (can be sync or async)
+            args: Positional arguments for the function
+            kwargs: Keyword arguments for the function
+            name: Optional task name
+            timeout: Optional timeout in seconds
+            on_complete: Callback when task completes
+            on_progress: Callback for progress updates
+            
+        Returns:
+            BackgroundTask object for tracking
+        """
+        kwargs = kwargs or {}
+        
+        task = BackgroundTask(
+            name=name or func.__name__,
+            metadata={
+                "func_name": func.__name__,
+                "timeout": timeout or self.config.default_timeout
+            }
+        )
+        
+        self._tasks[task.id] = task
+        
+        # Create the execution coroutine
+        async def execute():
+            async with self._semaphore:
+                task.start()
+                logger.info(f"Background task started: {task.name} ({task.id})")
+                
+                try:
+                    # Check if function is async
+                    if asyncio.iscoroutinefunction(func):
+                        result = await asyncio.wait_for(
+                            func(*args, **kwargs),
+                            timeout=timeout or self.config.default_timeout
+                        )
+                    else:
+                        # Run sync function in thread pool
+                        loop = asyncio.get_event_loop()
+                        result = await asyncio.wait_for(
+                            loop.run_in_executor(None, lambda: func(*args, **kwargs)),
+                            timeout=timeout or self.config.default_timeout
+                        )
+                    
+                    task.complete(result)
+                    logger.info(f"Background task completed: {task.name} ({task.id})")
+                    
+                    if on_complete:
+                        try:
+                            on_complete(task)
+                        except Exception as e:
+                            logger.warning(f"on_complete callback error: {e}")
+                    
+                    return result
+                    
+                except asyncio.TimeoutError:
+                    task.fail(f"Task timed out after {timeout}s")
+                    logger.warning(f"Background task timed out: {task.name}")
+                    
+                except asyncio.CancelledError:
+                    task.cancel()
+                    logger.info(f"Background task cancelled: {task.name}")
+                    raise
+                    
+                except Exception as e:
+                    task.fail(str(e))
+                    logger.error(f"Background task failed: {task.name} - {e}")
+                    
+                    if on_complete:
+                        try:
+                            on_complete(task)
+                        except Exception as cb_error:
+                            logger.warning(f"on_complete callback error: {cb_error}")
+        
+        # Create and store the future
+        task._future = asyncio.create_task(execute())
+        
+        return task
+    
+    async def submit_agent(
+        self,
+        agent: Any,
+        prompt: str,
+        name: Optional[str] = None,
+        timeout: Optional[float] = None,
+        on_complete: Optional[Callable[[BackgroundTask], None]] = None
+    ) -> BackgroundTask:
+        """
+        Submit an agent task for background execution.
+        
+        Args:
+            agent: Agent instance to run
+            prompt: Prompt to send to the agent
+            name: Optional task name
+            timeout: Optional timeout in seconds
+            on_complete: Callback when task completes
+            
+        Returns:
+            BackgroundTask object for tracking
+        """
+        task_name = name or f"agent_{getattr(agent, 'name', 'unknown')}"
+        
+        # Determine the method to call
+        if hasattr(agent, 'start'):
+            func = agent.start
+        elif hasattr(agent, 'chat'):
+            func = agent.chat
+        elif hasattr(agent, 'run'):
+            func = agent.run
+        else:
+            raise ValueError("Agent must have start(), chat(), or run() method")
+        
+        return await self.submit(
+            func=func,
+            args=(prompt,),
+            name=task_name,
+            timeout=timeout,
+            on_complete=on_complete
+        )
+    
+    def get_task(self, task_id: str) -> Optional[BackgroundTask]:
+        """Get a task by ID."""
+        return self._tasks.get(task_id)
+    
+    async def cancel_task(self, task_id: str) -> bool:
+        """
+        Cancel a task.
+        
+        Args:
+            task_id: ID of task to cancel
+            
+        Returns:
+            True if cancelled, False if not found or already completed
+        """
+        task = self._tasks.get(task_id)
+        if task is None:
+            return False
+        
+        if task.is_completed:
+            return False
+        
+        task.cancel()
+        
+        if task._future and not task._future.done():
+            task._future.cancel()
+        
+        return True
+    
+    async def cancel_all(self):
+        """Cancel all running tasks."""
+        for task in self.running_tasks:
+            await self.cancel_task(task.id)
+    
+    async def wait_all(self, timeout: Optional[float] = None) -> List[BackgroundTask]:
+        """
+        Wait for all tasks to complete.
+        
+        Args:
+            timeout: Maximum time to wait
+            
+        Returns:
+            List of completed tasks
+        """
+        futures = [t._future for t in self._tasks.values() if t._future]
+        
+        if not futures:
+            return list(self._tasks.values())
+        
+        try:
+            await asyncio.wait_for(
+                asyncio.gather(*futures, return_exceptions=True),
+                timeout=timeout
+            )
+        except asyncio.TimeoutError:
+            pass
+        
+        return list(self._tasks.values())
+    
+    def clear_completed(self):
+        """Remove completed tasks from tracking."""
+        completed_ids = [
+            task_id for task_id, task in self._tasks.items()
+            if task.is_completed
+        ]
+        for task_id in completed_ids:
+            del self._tasks[task_id]
+    
+    def list_tasks(self, status: Optional[TaskStatus] = None) -> List[Dict[str, Any]]:
+        """
+        List tasks with optional status filter.
+        
+        Args:
+            status: Optional status to filter by
+            
+        Returns:
+            List of task dictionaries
+        """
+        tasks = self._tasks.values()
+        
+        if status:
+            tasks = [t for t in tasks if t.status == status]
+        
+        return [t.to_dict() for t in tasks]
+    
+    async def start_cleanup_loop(self):
+        """Start the automatic cleanup loop."""
+        if self._cleanup_task is not None:
+            return
+        
+        async def cleanup_loop():
+            while True:
+                await asyncio.sleep(self.config.cleanup_delay)
+                if self.config.auto_cleanup:
+                    self.clear_completed()
+        
+        self._cleanup_task = asyncio.create_task(cleanup_loop())
+    
+    async def stop(self):
+        """Stop the runner and cancel all tasks."""
+        await self.cancel_all()
+        
+        if self._cleanup_task:
+            self._cleanup_task.cancel()
+            try:
+                await self._cleanup_task
+            except asyncio.CancelledError:
+                pass
+            self._cleanup_task = None
@@ -0,0 +1,154 @@
+"""
+Background Task for PraisonAI Agents.
+
+Represents a task running in the background.
+"""
+
+import uuid
+import asyncio
+import logging
+from enum import Enum
+from dataclasses import dataclass, field
+from typing import Optional, Any, Callable, Dict
+from datetime import datetime
+
+logger = logging.getLogger(__name__)
+
+
+class TaskStatus(str, Enum):
+    """Status of a background task."""
+    PENDING = "pending"
+    RUNNING = "running"
+    COMPLETED = "completed"
+    FAILED = "failed"
+    CANCELLED = "cancelled"
+
+
+@dataclass
+class BackgroundTask:
+    """
+    Represents a background task.
+    
+    Tracks the status, progress, and result of a task running
+    in the background.
+    """
+    id: str = field(default_factory=lambda: str(uuid.uuid4())[:8])
+    name: str = ""
+    status: TaskStatus = TaskStatus.PENDING
+    progress: float = 0.0  # 0.0 to 1.0
+    result: Any = None
+    error: Optional[str] = None
+    created_at: datetime = field(default_factory=datetime.now)
+    started_at: Optional[datetime] = None
+    completed_at: Optional[datetime] = None
+    metadata: Dict[str, Any] = field(default_factory=dict)
+    
+    # Internal
+    _future: Optional[asyncio.Future] = field(default=None, repr=False)
+    _cancel_event: Optional[asyncio.Event] = field(default=None, repr=False)
+    
+    def __post_init__(self):
+        self._cancel_event = asyncio.Event()
+    
+    @property
+    def is_running(self) -> bool:
+        """Check if task is currently running."""
+        return self.status == TaskStatus.RUNNING
+    
+    @property
+    def is_completed(self) -> bool:
+        """Check if task has completed (success or failure)."""
+        return self.status in (TaskStatus.COMPLETED, TaskStatus.FAILED, TaskStatus.CANCELLED)
+    
+    @property
+    def is_successful(self) -> bool:
+        """Check if task completed successfully."""
+        return self.status == TaskStatus.COMPLETED
+    
+    @property
+    def duration_seconds(self) -> Optional[float]:
+        """Get task duration in seconds."""
+        if self.started_at is None:
+            return None
+        end_time = self.completed_at or datetime.now()
+        return (end_time - self.started_at).total_seconds()
+    
+    def start(self):
+        """Mark task as started."""
+        self.status = TaskStatus.RUNNING
+        self.started_at = datetime.now()
+    
+    def complete(self, result: Any = None):
+        """Mark task as completed."""
+        self.status = TaskStatus.COMPLETED
+        self.result = result
+        self.progress = 1.0
+        self.completed_at = datetime.now()
+    
+    def fail(self, error: str):
+        """Mark task as failed."""
+        self.status = TaskStatus.FAILED
+        self.error = error
+        self.completed_at = datetime.now()
+    
+    def cancel(self):
+        """Request task cancellation."""
+        if self._cancel_event:
+            self._cancel_event.set()
+        self.status = TaskStatus.CANCELLED
+        self.completed_at = datetime.now()
+    
+    def update_progress(self, progress: float, message: Optional[str] = None):
+        """Update task progress."""
+        self.progress = min(max(progress, 0.0), 1.0)
+        if message:
+            self.metadata["last_message"] = message
+    
+    async def wait(self, timeout: Optional[float] = None) -> Any:
+        """
+        Wait for task completion.
+        
+        Args:
+            timeout: Maximum time to wait in seconds
+            
+        Returns:
+            Task result
+            
+        Raises:
+            asyncio.TimeoutError: If timeout exceeded
+            RuntimeError: If task failed
+        """
+        if self._future is None:
+            if self.is_completed:
+                if self.status == TaskStatus.FAILED:
+                    raise RuntimeError(self.error)
+                return self.result
+            raise RuntimeError("Task has no associated future")
+        
+        try:
+            result = await asyncio.wait_for(self._future, timeout=timeout)
+            return result
+        except asyncio.TimeoutError:
+            raise
+        except Exception as e:
+            raise RuntimeError(str(e))
+    
+    def should_cancel(self) -> bool:
+        """Check if cancellation was requested."""
+        return self._cancel_event is not None and self._cancel_event.is_set()
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "id": self.id,
+            "name": self.name,
+            "status": self.status.value,
+            "progress": self.progress,
+            "result": str(self.result) if self.result else None,
+            "error": self.error,
+            "created_at": self.created_at.isoformat(),
+            "started_at": self.started_at.isoformat() if self.started_at else None,
+            "completed_at": self.completed_at.isoformat() if self.completed_at else None,
+            "duration_seconds": self.duration_seconds,
+            "metadata": self.metadata
+        }
@@ -0,0 +1,65 @@
+"""
+Checkpoints Module for PraisonAI Agents.
+
+Provides file-level checkpointing using a shadow git repository to track
+and restore file changes made by agents. This enables:
+
+- Automatic checkpointing before file modifications
+- Rewind to any previous checkpoint
+- Diff between checkpoints
+- Restore files and conversation state together
+
+Zero Performance Impact:
+- All imports are lazy loaded via __getattr__
+- Checkpoints only created when enabled
+- No overhead when checkpoints are disabled
+
+Usage:
+    from praisonaiagents.checkpoints import CheckpointService
+    
+    # Create checkpoint service
+    service = CheckpointService(
+        workspace_dir="/path/to/project",
+        storage_dir="~/.praison/checkpoints"
+    )
+    
+    # Initialize shadow git
+    await service.initialize()
+    
+    # Save a checkpoint
+    checkpoint_id = await service.save("Before refactoring")
+    
+    # Restore to a checkpoint
+    await service.restore(checkpoint_id)
+    
+    # Get diff between checkpoints
+    diff = await service.diff(from_id, to_id)
+"""
+
+__all__ = [
+    # Core service
+    "CheckpointService",
+    # Data types
+    "Checkpoint",
+    "CheckpointDiff",
+    "CheckpointConfig",
+    # Events
+    "CheckpointEvent",
+]
+
+
+def __getattr__(name: str):
+    """Lazy load module components to avoid import overhead."""
+    if name == "CheckpointService":
+        from .service import CheckpointService
+        return CheckpointService
+    
+    if name in ("Checkpoint", "CheckpointDiff", "CheckpointConfig"):
+        from .types import Checkpoint, CheckpointDiff, CheckpointConfig
+        return locals()[name]
+    
+    if name == "CheckpointEvent":
+        from .types import CheckpointEvent
+        return CheckpointEvent
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -0,0 +1,497 @@
+"""
+Checkpoint Service for PraisonAI Agents.
+
+Implements shadow git repository for file-level checkpointing.
+"""
+
+import os
+import asyncio
+import logging
+import shutil
+from typing import Optional, List, Dict, Any, Callable
+from datetime import datetime
+from pathlib import Path
+
+from .types import (
+    CheckpointConfig, Checkpoint, CheckpointDiff, FileDiff,
+    CheckpointResult, CheckpointEvent
+)
+
+logger = logging.getLogger(__name__)
+
+# Protected paths that should never be checkpointed
+PROTECTED_PATHS = [
+    os.path.expanduser("~"),
+    os.path.expanduser("~/Desktop"),
+    os.path.expanduser("~/Documents"),
+    os.path.expanduser("~/Downloads"),
+    "/",
+    "/tmp",
+    "/var",
+    "/etc",
+]
+
+
+class CheckpointService:
+    """
+    Shadow Git Checkpoint Service.
+    
+    Uses a separate git repository to track file changes in the workspace,
+    enabling checkpoint creation, restoration, and diffing without
+    interfering with the workspace's own git repository.
+    
+    Example:
+        service = CheckpointService(
+            workspace_dir="/path/to/project",
+            storage_dir="~/.praison/checkpoints"
+        )
+        
+        await service.initialize()
+        
+        # Save checkpoint before making changes
+        result = await service.save("Before refactoring")
+        
+        # Make changes...
+        
+        # Restore if needed
+        await service.restore(result.checkpoint.id)
+    """
+    
+    def __init__(
+        self,
+        workspace_dir: str,
+        storage_dir: Optional[str] = None,
+        enabled: bool = True,
+        auto_checkpoint: bool = True,
+        max_checkpoints: int = 100
+    ):
+        """
+        Initialize the checkpoint service.
+        
+        Args:
+            workspace_dir: Directory to track
+            storage_dir: Where to store checkpoint data
+            enabled: Whether checkpoints are enabled
+            auto_checkpoint: Auto-checkpoint before file modifications
+            max_checkpoints: Maximum checkpoints to keep
+        """
+        self.config = CheckpointConfig(
+            workspace_dir=workspace_dir,
+            storage_dir=storage_dir,
+            enabled=enabled,
+            auto_checkpoint=auto_checkpoint,
+            max_checkpoints=max_checkpoints
+        )
+        
+        self._initialized = False
+        self._checkpoints: List[Checkpoint] = []
+        self._event_handlers: Dict[CheckpointEvent, List[Callable]] = {
+            event: [] for event in CheckpointEvent
+        }
+    
+    @property
+    def workspace_dir(self) -> str:
+        """Get the workspace directory."""
+        return self.config.workspace_dir
+    
+    @property
+    def checkpoint_dir(self) -> str:
+        """Get the checkpoint storage directory."""
+        return self.config.get_checkpoint_dir()
+    
+    @property
+    def git_dir(self) -> str:
+        """Get the shadow git directory."""
+        return os.path.join(self.checkpoint_dir, ".git")
+    
+    @property
+    def is_initialized(self) -> bool:
+        """Check if the service is initialized."""
+        return self._initialized
+    
+    def on(self, event: CheckpointEvent, handler: Callable):
+        """Register an event handler."""
+        self._event_handlers[event].append(handler)
+    
+    def _emit(self, event: CheckpointEvent, data: Any = None):
+        """Emit an event to all handlers."""
+        for handler in self._event_handlers[event]:
+            try:
+                handler(data)
+            except Exception as e:
+                logger.warning(f"Event handler error: {e}")
+    
+    async def initialize(self) -> bool:
+        """
+        Initialize the shadow git repository.
+        
+        Returns:
+            True if initialization succeeded
+        """
+        if not self.config.enabled:
+            return False
+        
+        # Check for protected paths
+        workspace_real = os.path.realpath(self.config.workspace_dir)
+        for protected in PROTECTED_PATHS:
+            if workspace_real == os.path.realpath(protected):
+                logger.warning(f"Cannot checkpoint protected path: {workspace_real}")
+                return False
+        
+        # Check if workspace exists
+        if not os.path.isdir(self.config.workspace_dir):
+            logger.error(f"Workspace does not exist: {self.config.workspace_dir}")
+            return False
+        
+        # Create checkpoint directory
+        os.makedirs(self.checkpoint_dir, exist_ok=True)
+        
+        # Initialize shadow git if needed
+        if not os.path.exists(self.git_dir):
+            success = await self._init_shadow_git()
+            if not success:
+                return False
+        
+        # Load existing checkpoints
+        await self._load_checkpoints()
+        
+        self._initialized = True
+        self._emit(CheckpointEvent.INITIALIZED, {"workspace": self.config.workspace_dir})
+        
+        return True
+    
+    async def _init_shadow_git(self) -> bool:
+        """Initialize the shadow git repository."""
+        try:
+            # Initialize git repo
+            await self._run_git("init")
+            
+            # Configure git
+            await self._run_git("config", "user.name", "PraisonAI Checkpoints")
+            await self._run_git("config", "user.email", "[email protected]")
+            
+            # Set worktree to workspace
+            await self._run_git("config", "core.worktree", self.config.workspace_dir)
+            
+            # Create exclude file
+            exclude_dir = os.path.join(self.git_dir, "info")
+            os.makedirs(exclude_dir, exist_ok=True)
+            
+            exclude_file = os.path.join(exclude_dir, "exclude")
+            with open(exclude_file, "w") as f:
+                for pattern in self.config.exclude_patterns:
+                    f.write(f"{pattern}\n")
+                
+                # Also exclude the checkpoint directory itself
+                f.write(f"{self.checkpoint_dir}\n")
+            
+            # Create initial empty commit
+            await self._run_git("commit", "--allow-empty", "-m", "Initial checkpoint")
+            
+            logger.info(f"Initialized shadow git at {self.checkpoint_dir}")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Failed to initialize shadow git: {e}")
+            return False
+    
+    async def _run_git(self, *args: str) -> str:
+        """Run a git command in the shadow repository."""
+        env = self._get_sanitized_env()
+        
+        cmd = ["git", f"--git-dir={self.git_dir}", f"--work-tree={self.config.workspace_dir}"]
+        cmd.extend(args)
+        
+        process = await asyncio.create_subprocess_exec(
+            *cmd,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.PIPE,
+            env=env,
+            cwd=self.config.workspace_dir
+        )
+        
+        stdout, stderr = await process.communicate()
+        
+        if process.returncode != 0:
+            error_msg = stderr.decode().strip()
+            raise RuntimeError(f"Git command failed: {' '.join(args)}\n{error_msg}")
+        
+        return stdout.decode().strip()
+    
+    def _get_sanitized_env(self) -> Dict[str, str]:
+        """Get environment with git variables sanitized."""
+        env = os.environ.copy()
+        
+        # Remove git environment variables that could interfere
+        git_vars = [
+            "GIT_DIR", "GIT_WORK_TREE", "GIT_INDEX_FILE",
+            "GIT_OBJECT_DIRECTORY", "GIT_ALTERNATE_OBJECT_DIRECTORIES"
+        ]
+        for var in git_vars:
+            env.pop(var, None)
+        
+        return env
+    
+    async def save(self, message: str, allow_empty: bool = False) -> CheckpointResult:
+        """
+        Save a checkpoint.
+        
+        Args:
+            message: Checkpoint message
+            allow_empty: Allow checkpoint even if no changes
+            
+        Returns:
+            CheckpointResult with the created checkpoint
+        """
+        if not self._initialized:
+            return CheckpointResult.fail("Service not initialized")
+        
+        try:
+            # Stage all changes
+            await self._run_git("add", "-A")
+            
+            # Check if there are changes
+            try:
+                await self._run_git("diff", "--cached", "--quiet")
+                has_changes = False
+            except RuntimeError:
+                has_changes = True
+            
+            if not has_changes and not allow_empty:
+                return CheckpointResult.fail("No changes to checkpoint")
+            
+            # Create commit
+            commit_args = ["commit", "-m", message]
+            if allow_empty:
+                commit_args.append("--allow-empty")
+            
+            await self._run_git(*commit_args)
+            
+            # Get commit info
+            commit_hash = await self._run_git("rev-parse", "HEAD")
+            timestamp = await self._run_git("log", "-1", "--format=%aI")
+            
+            checkpoint = Checkpoint(
+                id=commit_hash,
+                short_id=commit_hash[:8],
+                message=message,
+                timestamp=datetime.fromisoformat(timestamp)
+            )
+            
+            self._checkpoints.append(checkpoint)
+            
+            # Prune old checkpoints if needed
+            await self._prune_checkpoints()
+            
+            self._emit(CheckpointEvent.CHECKPOINT_CREATED, checkpoint)
+            logger.info(f"Created checkpoint: {checkpoint.short_id} - {message}")
+            
+            return CheckpointResult.ok(checkpoint)
+            
+        except Exception as e:
+            error_msg = str(e)
+            self._emit(CheckpointEvent.ERROR, {"error": error_msg})
+            return CheckpointResult.fail(error_msg)
+    
+    async def restore(self, checkpoint_id: str) -> CheckpointResult:
+        """
+        Restore workspace to a checkpoint.
+        
+        Args:
+            checkpoint_id: Checkpoint ID (commit hash) to restore
+            
+        Returns:
+            CheckpointResult indicating success/failure
+        """
+        if not self._initialized:
+            return CheckpointResult.fail("Service not initialized")
+        
+        try:
+            # Clean untracked files
+            await self._run_git("clean", "-f", "-d")
+            
+            # Reset to checkpoint
+            await self._run_git("reset", "--hard", checkpoint_id)
+            
+            # Get checkpoint info
+            message = await self._run_git("log", "-1", "--format=%s", checkpoint_id)
+            timestamp = await self._run_git("log", "-1", "--format=%aI", checkpoint_id)
+            
+            checkpoint = Checkpoint(
+                id=checkpoint_id,
+                short_id=checkpoint_id[:8],
+                message=message,
+                timestamp=datetime.fromisoformat(timestamp)
+            )
+            
+            self._emit(CheckpointEvent.CHECKPOINT_RESTORED, checkpoint)
+            logger.info(f"Restored to checkpoint: {checkpoint.short_id}")
+            
+            return CheckpointResult.ok(checkpoint)
+            
+        except Exception as e:
+            error_msg = str(e)
+            self._emit(CheckpointEvent.ERROR, {"error": error_msg})
+            return CheckpointResult.fail(error_msg)
+    
+    async def diff(
+        self,
+        from_id: Optional[str] = None,
+        to_id: Optional[str] = None
+    ) -> CheckpointDiff:
+        """
+        Get diff between checkpoints.
+        
+        Args:
+            from_id: Starting checkpoint (default: previous checkpoint)
+            to_id: Ending checkpoint (default: current working directory)
+            
+        Returns:
+            CheckpointDiff with file changes
+        """
+        if not self._initialized:
+            return CheckpointDiff(from_checkpoint="", to_checkpoint="", files=[])
+        
+        try:
+            # Default from_id to HEAD~1
+            if from_id is None:
+                try:
+                    from_id = await self._run_git("rev-parse", "HEAD~1")
+                except RuntimeError:
+                    from_id = await self._run_git("rev-parse", "HEAD")
+            
+            # Build diff command
+            if to_id:
+                diff_output = await self._run_git(
+                    "diff", "--stat", "--numstat", from_id, to_id
+                )
+            else:
+                # Diff against working directory
+                await self._run_git("add", "-A")  # Stage to include untracked
+                diff_output = await self._run_git(
+                    "diff", "--stat", "--numstat", "--cached", from_id
+                )
+            
+            # Parse diff output
+            files = self._parse_diff_output(diff_output)
+            
+            return CheckpointDiff(
+                from_checkpoint=from_id[:8] if from_id else "",
+                to_checkpoint=to_id[:8] if to_id else None,
+                files=files
+            )
+            
+        except Exception as e:
+            logger.error(f"Failed to get diff: {e}")
+            return CheckpointDiff(from_checkpoint="", to_checkpoint="", files=[])
+    
+    def _parse_diff_output(self, output: str) -> List[FileDiff]:
+        """Parse git diff --numstat output."""
+        files = []
+        
+        for line in output.strip().split("\n"):
+            if not line or "\t" not in line:
+                continue
+            
+            parts = line.split("\t")
+            if len(parts) >= 3:
+                try:
+                    additions = int(parts[0]) if parts[0] != "-" else 0
+                    deletions = int(parts[1]) if parts[1] != "-" else 0
+                    path = parts[2]
+                    
+                    # Determine status
+                    if additions > 0 and deletions == 0:
+                        status = "added"
+                    elif additions == 0 and deletions > 0:
+                        status = "deleted"
+                    else:
+                        status = "modified"
+                    
+                    files.append(FileDiff(
+                        path=path,
+                        absolute_path=os.path.join(self.config.workspace_dir, path),
+                        status=status,
+                        additions=additions,
+                        deletions=deletions
+                    ))
+                except ValueError:
+                    continue
+        
+        return files
+    
+    async def list_checkpoints(self, limit: int = 50) -> List[Checkpoint]:
+        """
+        List all checkpoints.
+        
+        Args:
+            limit: Maximum number of checkpoints to return
+            
+        Returns:
+            List of checkpoints, newest first
+        """
+        if not self._initialized:
+            return []
+        
+        try:
+            # Get commit log
+            log_output = await self._run_git(
+                "log", f"-{limit}", "--format=%H|%s|%aI"
+            )
+            
+            checkpoints = []
+            for line in log_output.strip().split("\n"):
+                if not line or "|" not in line:
+                    continue
+                
+                parts = line.split("|", 2)
+                if len(parts) >= 3:
+                    checkpoints.append(Checkpoint(
+                        id=parts[0],
+                        short_id=parts[0][:8],
+                        message=parts[1],
+                        timestamp=datetime.fromisoformat(parts[2])
+                    ))
+            
+            return checkpoints
+            
+        except Exception as e:
+            logger.error(f"Failed to list checkpoints: {e}")
+            return []
+    
+    async def _load_checkpoints(self):
+        """Load existing checkpoints from git log."""
+        self._checkpoints = await self.list_checkpoints()
+    
+    async def _prune_checkpoints(self):
+        """Prune old checkpoints if over limit."""
+        if len(self._checkpoints) <= self.config.max_checkpoints:
+            return
+        
+        # Keep only the most recent checkpoints
+        # Note: This doesn't actually delete git history, just our tracking
+        self._checkpoints = self._checkpoints[:self.config.max_checkpoints]
+    
+    async def get_checkpoint(self, checkpoint_id: str) -> Optional[Checkpoint]:
+        """Get a specific checkpoint by ID."""
+        for cp in self._checkpoints:
+            if cp.id.startswith(checkpoint_id) or cp.short_id == checkpoint_id:
+                return cp
+        return None
+    
+    async def cleanup(self):
+        """Clean up the checkpoint service."""
+        # Nothing to clean up currently
+        self._initialized = False
+    
+    async def delete_all(self) -> bool:
+        """Delete all checkpoint data for this workspace."""
+        try:
+            if os.path.exists(self.checkpoint_dir):
+                shutil.rmtree(self.checkpoint_dir)
+            self._checkpoints = []
+            self._initialized = False
+            return True
+        except Exception as e:
+            logger.error(f"Failed to delete checkpoints: {e}")
+            return False
@@ -0,0 +1,158 @@
+"""
+Checkpoint Types for PraisonAI Agents.
+
+Defines the core types, enums, and dataclasses for the checkpoint system.
+"""
+
+import os
+from enum import Enum
+from dataclasses import dataclass, field
+from typing import Optional, Dict, Any, List
+from datetime import datetime
+from pathlib import Path
+
+
+class CheckpointEvent(str, Enum):
+    """Events emitted by the checkpoint service."""
+    INITIALIZED = "initialized"
+    CHECKPOINT_CREATED = "checkpoint_created"
+    CHECKPOINT_RESTORED = "checkpoint_restored"
+    ERROR = "error"
+
+
+@dataclass
+class CheckpointConfig:
+    """Configuration for the checkpoint service."""
+    workspace_dir: str
+    storage_dir: Optional[str] = None
+    enabled: bool = True
+    auto_checkpoint: bool = True  # Auto-checkpoint before file modifications
+    max_checkpoints: int = 100  # Maximum checkpoints to keep
+    exclude_patterns: List[str] = field(default_factory=lambda: [
+        ".git",
+        ".praison",
+        "__pycache__",
+        "*.pyc",
+        ".env",
+        "node_modules",
+        ".venv",
+        "venv",
+        "*.log"
+    ])
+    
+    def __post_init__(self):
+        # Expand paths
+        self.workspace_dir = os.path.expanduser(self.workspace_dir)
+        if self.storage_dir:
+            self.storage_dir = os.path.expanduser(self.storage_dir)
+        else:
+            # Default storage in user's home directory
+            self.storage_dir = os.path.expanduser("~/.praison/checkpoints")
+    
+    def get_checkpoint_dir(self) -> str:
+        """Get the checkpoint directory for this workspace."""
+        # Hash the workspace path to create a unique directory
+        import hashlib
+        workspace_hash = hashlib.sha256(
+            self.workspace_dir.encode()
+        ).hexdigest()[:12]
+        return os.path.join(self.storage_dir, workspace_hash)
+
+
+@dataclass
+class Checkpoint:
+    """Represents a single checkpoint."""
+    id: str  # Git commit hash
+    short_id: str  # Short hash (8 chars)
+    message: str
+    timestamp: datetime
+    files_changed: int = 0
+    insertions: int = 0
+    deletions: int = 0
+    
+    @classmethod
+    def from_git_commit(cls, commit_hash: str, message: str, timestamp: str) -> "Checkpoint":
+        """Create a Checkpoint from git commit info."""
+        return cls(
+            id=commit_hash,
+            short_id=commit_hash[:8],
+            message=message,
+            timestamp=datetime.fromisoformat(timestamp) if isinstance(timestamp, str) else timestamp
+        )
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "id": self.id,
+            "short_id": self.short_id,
+            "message": self.message,
+            "timestamp": self.timestamp.isoformat(),
+            "files_changed": self.files_changed,
+            "insertions": self.insertions,
+            "deletions": self.deletions
+        }
+
+
+@dataclass
+class FileDiff:
+    """Represents a diff for a single file."""
+    path: str
+    absolute_path: str
+    status: str  # added, modified, deleted
+    additions: int = 0
+    deletions: int = 0
+    before_content: Optional[str] = None
+    after_content: Optional[str] = None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "path": self.path,
+            "absolute_path": self.absolute_path,
+            "status": self.status,
+            "additions": self.additions,
+            "deletions": self.deletions
+        }
+
+
+@dataclass
+class CheckpointDiff:
+    """Represents a diff between two checkpoints."""
+    from_checkpoint: str
+    to_checkpoint: Optional[str]  # None means current working directory
+    files: List[FileDiff] = field(default_factory=list)
+    total_additions: int = 0
+    total_deletions: int = 0
+    
+    def __post_init__(self):
+        # Calculate totals
+        self.total_additions = sum(f.additions for f in self.files)
+        self.total_deletions = sum(f.deletions for f in self.files)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "from_checkpoint": self.from_checkpoint,
+            "to_checkpoint": self.to_checkpoint,
+            "files": [f.to_dict() for f in self.files],
+            "total_additions": self.total_additions,
+            "total_deletions": self.total_deletions
+        }
+
+
+@dataclass
+class CheckpointResult:
+    """Result of a checkpoint operation."""
+    success: bool
+    checkpoint: Optional[Checkpoint] = None
+    error: Optional[str] = None
+    
+    @classmethod
+    def ok(cls, checkpoint: Checkpoint) -> "CheckpointResult":
+        """Create a successful result."""
+        return cls(success=True, checkpoint=checkpoint)
+    
+    @classmethod
+    def fail(cls, error: str) -> "CheckpointResult":
+        """Create a failed result."""
+        return cls(success=False, error=error)
@@ -0,0 +1,57 @@
+"""
+Auto Context Compaction Module for PraisonAI Agents.
+
+Provides automatic context management for long conversations:
+- Message summarization
+- Context window management
+- Token counting and limits
+- Intelligent message pruning
+
+Zero Performance Impact:
+- All imports are lazy loaded via __getattr__
+- Compaction only runs when needed
+- No overhead when context is within limits
+
+Usage:
+    from praisonaiagents.compaction import ContextCompactor, CompactionConfig
+    
+    # Create a compactor
+    compactor = ContextCompactor(
+        max_tokens=8000,
+        strategy="summarize"
+    )
+    
+    # Compact messages when needed
+    compacted = compactor.compact(messages)
+"""
+
+__all__ = [
+    # Core classes
+    "ContextCompactor",
+    "CompactionConfig",
+    # Strategies
+    "CompactionStrategy",
+    # Results
+    "CompactionResult",
+]
+
+
+def __getattr__(name: str):
+    """Lazy load module components to avoid import overhead."""
+    if name == "ContextCompactor":
+        from .compactor import ContextCompactor
+        return ContextCompactor
+    
+    if name == "CompactionConfig":
+        from .config import CompactionConfig
+        return CompactionConfig
+    
+    if name == "CompactionStrategy":
+        from .strategy import CompactionStrategy
+        return CompactionStrategy
+    
+    if name == "CompactionResult":
+        from .result import CompactionResult
+        return CompactionResult
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -0,0 +1,237 @@
+"""
+Context Compactor for PraisonAI Agents.
+
+Manages context window by compacting messages when needed.
+"""
+
+from typing import List, Dict, Any, Optional
+
+from .config import CompactionConfig
+from .strategy import CompactionStrategy
+from .result import CompactionResult
+
+
+class ContextCompactor:
+    """
+    Compacts conversation context to fit within token limits.
+    
+    Example:
+        compactor = ContextCompactor(max_tokens=8000)
+        
+        # Check if compaction needed
+        if compactor.needs_compaction(messages):
+            result = compactor.compact(messages)
+            messages = result.messages
+    """
+    
+    def __init__(
+        self,
+        max_tokens: int = 8000,
+        target_tokens: Optional[int] = None,
+        strategy: CompactionStrategy = CompactionStrategy.TRUNCATE,
+        preserve_system: bool = True,
+        preserve_recent: int = 5
+    ):
+        """
+        Initialize the compactor.
+        
+        Args:
+            max_tokens: Maximum tokens before compaction
+            target_tokens: Target tokens after compaction
+            strategy: Compaction strategy to use
+            preserve_system: Keep system messages
+            preserve_recent: Number of recent messages to preserve
+        """
+        self.max_tokens = max_tokens
+        self.target_tokens = target_tokens or int(max_tokens * 0.75)
+        self.strategy = strategy
+        self.preserve_system = preserve_system
+        self.preserve_recent = preserve_recent
+    
+    def estimate_tokens(self, text: str) -> int:
+        """Estimate token count for text."""
+        # Rough estimate: ~4 chars per token
+        return len(text) // 4
+    
+    def count_message_tokens(self, message: Dict[str, Any]) -> int:
+        """Count tokens in a message."""
+        content = message.get("content", "")
+        if isinstance(content, str):
+            return self.estimate_tokens(content)
+        elif isinstance(content, list):
+            # Handle multi-part content
+            total = 0
+            for part in content:
+                if isinstance(part, dict):
+                    total += self.estimate_tokens(str(part.get("text", "")))
+                else:
+                    total += self.estimate_tokens(str(part))
+            return total
+        return 0
+    
+    def count_total_tokens(self, messages: List[Dict[str, Any]]) -> int:
+        """Count total tokens in messages."""
+        return sum(self.count_message_tokens(m) for m in messages)
+    
+    def needs_compaction(self, messages: List[Dict[str, Any]]) -> bool:
+        """Check if messages need compaction."""
+        return self.count_total_tokens(messages) > self.max_tokens
+    
+    def compact(
+        self,
+        messages: List[Dict[str, Any]]
+    ) -> tuple[List[Dict[str, Any]], CompactionResult]:
+        """
+        Compact messages to fit within token limit.
+        
+        Args:
+            messages: List of messages to compact
+            
+        Returns:
+            Tuple of (compacted messages, result)
+        """
+        original_tokens = self.count_total_tokens(messages)
+        
+        if original_tokens <= self.max_tokens:
+            return messages, CompactionResult(
+                original_tokens=original_tokens,
+                compacted_tokens=original_tokens,
+                messages_removed=0,
+                messages_kept=len(messages),
+                strategy_used=self.strategy
+            )
+        
+        if self.strategy == CompactionStrategy.TRUNCATE:
+            compacted = self._truncate(messages)
+        elif self.strategy == CompactionStrategy.SLIDING:
+            compacted = self._sliding_window(messages)
+        elif self.strategy == CompactionStrategy.SUMMARIZE:
+            compacted = self._summarize(messages)
+        elif self.strategy == CompactionStrategy.SMART:
+            compacted = self._smart_compact(messages)
+        else:
+            compacted = self._truncate(messages)
+        
+        compacted_tokens = self.count_total_tokens(compacted)
+        
+        result = CompactionResult(
+            original_tokens=original_tokens,
+            compacted_tokens=compacted_tokens,
+            messages_removed=len(messages) - len(compacted),
+            messages_kept=len(compacted),
+            strategy_used=self.strategy
+        )
+        
+        return compacted, result
+    
+    def _truncate(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """Truncate oldest messages."""
+        result = []
+        
+        # Separate system and non-system messages
+        system_msgs = []
+        other_msgs = []
+        
+        for msg in messages:
+            if self.preserve_system and msg.get("role") == "system":
+                system_msgs.append(msg)
+            else:
+                other_msgs.append(msg)
+        
+        # Always keep system messages
+        result.extend(system_msgs)
+        
+        # Keep recent messages
+        recent = other_msgs[-self.preserve_recent:] if other_msgs else []
+        
+        # Add recent messages
+        result.extend(recent)
+        
+        # If still over limit, truncate more
+        while self.count_total_tokens(result) > self.target_tokens and len(result) > 1:
+            # Remove oldest non-system message
+            for i, msg in enumerate(result):
+                if msg.get("role") != "system":
+                    result.pop(i)
+                    break
+        
+        return result
+    
+    def _sliding_window(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """Keep a sliding window of recent messages."""
+        result = []
+        
+        # Keep system messages
+        for msg in messages:
+            if self.preserve_system and msg.get("role") == "system":
+                result.append(msg)
+        
+        # Add messages from end until we hit target
+        non_system = [m for m in messages if m.get("role") != "system"]
+        
+        for msg in reversed(non_system):
+            if self.count_total_tokens(result + [msg]) <= self.target_tokens:
+                result.insert(len([m for m in result if m.get("role") == "system"]), msg)
+            else:
+                break
+        
+        # Ensure messages are in order
+        system_msgs = [m for m in result if m.get("role") == "system"]
+        other_msgs = [m for m in result if m.get("role") != "system"]
+        
+        return system_msgs + other_msgs
+    
+    def _summarize(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """Summarize old messages (simplified version)."""
+        result = []
+        
+        # Keep system messages
+        system_msgs = [m for m in messages if m.get("role") == "system"]
+        other_msgs = [m for m in messages if m.get("role") != "system"]
+        
+        result.extend(system_msgs)
+        
+        # Keep recent messages
+        recent = other_msgs[-self.preserve_recent:]
+        
+        # Summarize older messages
+        older = other_msgs[:-self.preserve_recent] if len(other_msgs) > self.preserve_recent else []
+        
+        if older:
+            # Create a simple summary
+            summary_parts = []
+            for msg in older:
+                role = msg.get("role", "unknown")
+                content = msg.get("content", "")
+                if isinstance(content, str) and content:
+                    # Take first 100 chars
+                    summary_parts.append(f"{role}: {content[:100]}...")
+            
+            if summary_parts:
+                summary = "[Previous conversation summary]\n" + "\n".join(summary_parts[:5])
+                result.append({
+                    "role": "system",
+                    "content": summary
+                })
+        
+        result.extend(recent)
+        
+        return result
+    
+    def _smart_compact(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """Smart compaction based on message importance."""
+        # For now, use sliding window as base
+        return self._sliding_window(messages)
+    
+    def get_stats(self, messages: List[Dict[str, Any]]) -> Dict[str, Any]:
+        """Get statistics about messages."""
+        total_tokens = self.count_total_tokens(messages)
+        
+        return {
+            "message_count": len(messages),
+            "total_tokens": total_tokens,
+            "max_tokens": self.max_tokens,
+            "target_tokens": self.target_tokens,
+            "needs_compaction": total_tokens > self.max_tokens,
+            "utilization": total_tokens / self.max_tokens if self.max_tokens > 0 else 0
+        }
@@ -0,0 +1,17 @@
+"""
+Compaction Configuration for PraisonAI Agents.
+"""
+
+from dataclasses import dataclass
+from typing import Optional
+
+
+@dataclass
+class CompactionConfig:
+    """Configuration for context compaction."""
+    enabled: bool = True
+    max_tokens: int = 8000
+    target_tokens: int = 6000  # Target after compaction
+    preserve_system: bool = True  # Always keep system messages
+    preserve_recent: int = 5  # Keep last N messages
+    auto_compact: bool = True  # Automatically compact when needed
@@ -0,0 +1,49 @@
+"""
+Compaction Result for PraisonAI Agents.
+"""
+
+from dataclasses import dataclass, field
+from typing import List, Dict, Any
+
+from .strategy import CompactionStrategy
+
+
+@dataclass
+class CompactionResult:
+    """Result of a compaction operation."""
+    original_tokens: int
+    compacted_tokens: int
+    messages_removed: int
+    messages_kept: int
+    strategy_used: CompactionStrategy
+    summary: str = ""
+    
+    @property
+    def tokens_saved(self) -> int:
+        """Get number of tokens saved."""
+        return self.original_tokens - self.compacted_tokens
+    
+    @property
+    def compression_ratio(self) -> float:
+        """Get compression ratio."""
+        if self.original_tokens == 0:
+            return 0.0
+        return self.compacted_tokens / self.original_tokens
+    
+    @property
+    def was_compacted(self) -> bool:
+        """Check if compaction occurred."""
+        return self.messages_removed > 0 or self.tokens_saved > 0
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "original_tokens": self.original_tokens,
+            "compacted_tokens": self.compacted_tokens,
+            "tokens_saved": self.tokens_saved,
+            "messages_removed": self.messages_removed,
+            "messages_kept": self.messages_kept,
+            "strategy_used": self.strategy_used.value,
+            "compression_ratio": self.compression_ratio,
+            "summary": self.summary
+        }
@@ -0,0 +1,13 @@
+"""
+Compaction Strategies for PraisonAI Agents.
+"""
+
+from enum import Enum
+
+
+class CompactionStrategy(str, Enum):
+    """Strategy for compacting context."""
+    TRUNCATE = "truncate"      # Remove oldest messages
+    SUMMARIZE = "summarize"    # Summarize old messages
+    SLIDING = "sliding"        # Sliding window of recent messages
+    SMART = "smart"            # Intelligent selection based on relevance
@@ -0,0 +1,97 @@
+"""
+Hooks Module for PraisonAI Agents.
+
+Provides a powerful hook system for intercepting and modifying agent behavior
+at various lifecycle points. Unlike callbacks (which are for UI events),
+hooks can intercept, modify, or block tool execution.
+
+Features:
+- Event-based hook system (BeforeTool, AfterTool, BeforeAgent, etc.)
+- Shell command hooks for external integrations
+- Python function hooks for in-process customization
+- Matcher patterns for selective hook execution
+- Sequential and parallel hook execution
+- Decision outcomes (allow, deny, block, ask)
+
+Zero Performance Impact:
+- All imports are lazy loaded via __getattr__
+- Hooks only execute when registered
+- No overhead when hooks are disabled
+
+Usage:
+    from praisonaiagents.hooks import HookRegistry, HookEvent
+    
+    # Register a Python function hook
+    registry = HookRegistry()
+    
+    @registry.on(HookEvent.BEFORE_TOOL)
+    def my_hook(event_data):
+        if event_data.tool_name == "dangerous_tool":
+            return HookResult(decision="deny", reason="Tool blocked by policy")
+        return HookResult(decision="allow")
+    
+    # Register a shell command hook
+    registry.register_command_hook(
+        event=HookEvent.BEFORE_TOOL,
+        command="python /path/to/validator.py",
+        matcher="write_*"  # Only match tools starting with write_
+    )
+    
+    # Use with Agent
+    agent = Agent(
+        name="MyAgent",
+        hooks=registry
+    )
+"""
+
+__all__ = [
+    # Core types
+    "HookEvent",
+    "HookDecision",
+    "HookResult",
+    "HookInput",
+    "HookOutput",
+    # Hook definitions
+    "HookDefinition",
+    "CommandHook",
+    "FunctionHook",
+    # Registry and runner
+    "HookRegistry",
+    "HookRunner",
+    # Event-specific inputs
+    "BeforeToolInput",
+    "AfterToolInput",
+    "BeforeAgentInput",
+    "AfterAgentInput",
+    "SessionStartInput",
+    "SessionEndInput",
+]
+
+
+def __getattr__(name: str):
+    """Lazy load module components to avoid import overhead."""
+    if name in ("HookEvent", "HookDecision", "HookResult", "HookInput", "HookOutput"):
+        from .types import HookEvent, HookDecision, HookResult, HookInput, HookOutput
+        return locals()[name]
+    
+    if name in ("HookDefinition", "CommandHook", "FunctionHook"):
+        from .types import HookDefinition, CommandHook, FunctionHook
+        return locals()[name]
+    
+    if name == "HookRegistry":
+        from .registry import HookRegistry
+        return HookRegistry
+    
+    if name == "HookRunner":
+        from .runner import HookRunner
+        return HookRunner
+    
+    if name in ("BeforeToolInput", "AfterToolInput", "BeforeAgentInput", 
+                "AfterAgentInput", "SessionStartInput", "SessionEndInput"):
+        from .events import (
+            BeforeToolInput, AfterToolInput, BeforeAgentInput,
+            AfterAgentInput, SessionStartInput, SessionEndInput
+        )
+        return locals()[name]
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -0,0 +1,195 @@
+"""
+Event-specific input types for the hook system.
+
+Each event type has its own input class with relevant fields.
+"""
+
+from dataclasses import dataclass, field
+from typing import Optional, Dict, Any, List
+from .types import HookInput
+
+
+@dataclass
+class BeforeToolInput(HookInput):
+    """Input for BeforeTool hooks."""
+    tool_name: str = ""
+    tool_input: Dict[str, Any] = field(default_factory=dict)
+    tool_description: Optional[str] = None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "tool_name": self.tool_name,
+            "tool_input": self.tool_input,
+            "tool_description": self.tool_description
+        })
+        return base
+
+
+@dataclass
+class AfterToolInput(HookInput):
+    """Input for AfterTool hooks."""
+    tool_name: str = ""
+    tool_input: Dict[str, Any] = field(default_factory=dict)
+    tool_output: Any = None
+    tool_error: Optional[str] = None
+    execution_time_ms: float = 0.0
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "tool_name": self.tool_name,
+            "tool_input": self.tool_input,
+            "tool_output": str(self.tool_output) if self.tool_output else None,
+            "tool_error": self.tool_error,
+            "execution_time_ms": self.execution_time_ms
+        })
+        return base
+
+
+@dataclass
+class BeforeAgentInput(HookInput):
+    """Input for BeforeAgent hooks."""
+    prompt: str = ""
+    conversation_history: List[Dict[str, Any]] = field(default_factory=list)
+    tools_available: List[str] = field(default_factory=list)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "prompt": self.prompt,
+            "conversation_history_length": len(self.conversation_history),
+            "tools_available": self.tools_available
+        })
+        return base
+
+
+@dataclass
+class AfterAgentInput(HookInput):
+    """Input for AfterAgent hooks."""
+    prompt: str = ""
+    response: str = ""
+    tools_used: List[str] = field(default_factory=list)
+    total_tokens: int = 0
+    execution_time_ms: float = 0.0
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "prompt": self.prompt,
+            "response": self.response[:500] if self.response else "",  # Truncate for JSON
+            "tools_used": self.tools_used,
+            "total_tokens": self.total_tokens,
+            "execution_time_ms": self.execution_time_ms
+        })
+        return base
+
+
+@dataclass
+class SessionStartInput(HookInput):
+    """Input for SessionStart hooks."""
+    source: str = "startup"  # startup, resume, clear
+    session_name: Optional[str] = None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "source": self.source,
+            "session_name": self.session_name
+        })
+        return base
+
+
+@dataclass
+class SessionEndInput(HookInput):
+    """Input for SessionEnd hooks."""
+    reason: str = "exit"  # exit, clear, logout, error
+    total_turns: int = 0
+    total_tokens: int = 0
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "reason": self.reason,
+            "total_turns": self.total_turns,
+            "total_tokens": self.total_tokens
+        })
+        return base
+
+
+@dataclass
+class BeforeLLMInput(HookInput):
+    """Input for BeforeLLM hooks."""
+    messages: List[Dict[str, Any]] = field(default_factory=list)
+    model: str = ""
+    temperature: Optional[float] = None
+    max_tokens: Optional[int] = None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "messages_count": len(self.messages),
+            "model": self.model,
+            "temperature": self.temperature,
+            "max_tokens": self.max_tokens
+        })
+        return base
+
+
+@dataclass
+class AfterLLMInput(HookInput):
+    """Input for AfterLLM hooks."""
+    messages: List[Dict[str, Any]] = field(default_factory=list)
+    response: str = ""
+    model: str = ""
+    tokens_used: int = 0
+    latency_ms: float = 0.0
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "messages_count": len(self.messages),
+            "response_length": len(self.response),
+            "model": self.model,
+            "tokens_used": self.tokens_used,
+            "latency_ms": self.latency_ms
+        })
+        return base
+
+
+@dataclass
+class OnErrorInput(HookInput):
+    """Input for OnError hooks."""
+    error_type: str = ""
+    error_message: str = ""
+    stack_trace: Optional[str] = None
+    context: Dict[str, Any] = field(default_factory=dict)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "error_type": self.error_type,
+            "error_message": self.error_message,
+            "stack_trace": self.stack_trace,
+            "context": self.context
+        })
+        return base
+
+
+@dataclass
+class OnRetryInput(HookInput):
+    """Input for OnRetry hooks."""
+    retry_count: int = 0
+    max_retries: int = 3
+    error_message: str = ""
+    operation: str = ""  # tool_call, llm_request, etc.
+    
+    def to_dict(self) -> Dict[str, Any]:
+        base = super().to_dict()
+        base.update({
+            "retry_count": self.retry_count,
+            "max_retries": self.max_retries,
+            "error_message": self.error_message,
+            "operation": self.operation
+        })
+        return base
@@ -0,0 +1,336 @@
+"""
+Hook Registry for PraisonAI Agents.
+
+Manages registration and lookup of hooks for different events.
+"""
+
+import logging
+from typing import Dict, List, Optional, Callable, Union
+from functools import wraps
+
+from .types import (
+    HookEvent, HookDefinition, CommandHook, FunctionHook,
+    HookInput, HookResult
+)
+
+logger = logging.getLogger(__name__)
+
+
+class HookRegistry:
+    """
+    Registry for managing hooks.
+    
+    Provides methods to register, unregister, and lookup hooks
+    for different events.
+    
+    Example:
+        registry = HookRegistry()
+        
+        # Register a function hook using decorator
+        @registry.on(HookEvent.BEFORE_TOOL)
+        def validate_tool(event_data):
+            if event_data.tool_name == "dangerous":
+                return HookResult.deny("Tool is dangerous")
+            return HookResult.allow()
+        
+        # Register a command hook
+        registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command="python /path/to/validator.py",
+            matcher="write_*"
+        )
+    """
+    
+    def __init__(self, enabled: bool = True):
+        """
+        Initialize the hook registry.
+        
+        Args:
+            enabled: Whether hooks are enabled globally
+        """
+        self._hooks: Dict[HookEvent, List[HookDefinition]] = {
+            event: [] for event in HookEvent
+        }
+        self._enabled = enabled
+        self._global_timeout = 60.0
+    
+    @property
+    def enabled(self) -> bool:
+        """Check if hooks are enabled."""
+        return self._enabled
+    
+    @enabled.setter
+    def enabled(self, value: bool):
+        """Enable or disable hooks."""
+        self._enabled = value
+    
+    def register(self, hook: HookDefinition) -> str:
+        """
+        Register a hook definition.
+        
+        Args:
+            hook: The hook definition to register
+            
+        Returns:
+            The hook ID
+        """
+        self._hooks[hook.event].append(hook)
+        logger.debug(f"Registered hook '{hook.name}' for event '{hook.event.value}'")
+        return hook.id
+    
+    def register_function(
+        self,
+        event: HookEvent,
+        func: Callable[[HookInput], HookResult],
+        matcher: Optional[str] = None,
+        name: Optional[str] = None,
+        description: Optional[str] = None,
+        sequential: bool = False,
+        timeout: float = 60.0,
+        is_async: bool = False
+    ) -> str:
+        """
+        Register a Python function as a hook.
+        
+        Args:
+            event: The event to hook
+            func: The function to call
+            matcher: Optional regex pattern to match targets
+            name: Optional name for the hook
+            description: Optional description
+            sequential: Whether to run sequentially
+            timeout: Timeout in seconds
+            is_async: Whether the function is async
+            
+        Returns:
+            The hook ID
+        """
+        hook = FunctionHook(
+            event=event,
+            func=func,
+            matcher=matcher,
+            name=name or func.__name__,
+            description=description,
+            sequential=sequential,
+            timeout=timeout,
+            is_async=is_async
+        )
+        return self.register(hook)
+    
+    def register_command(
+        self,
+        event: HookEvent,
+        command: str,
+        matcher: Optional[str] = None,
+        name: Optional[str] = None,
+        description: Optional[str] = None,
+        sequential: bool = False,
+        timeout: float = 60.0,
+        env: Optional[Dict[str, str]] = None,
+        shell: bool = True
+    ) -> str:
+        """
+        Register a shell command as a hook.
+        
+        Args:
+            event: The event to hook
+            command: The shell command to execute
+            matcher: Optional regex pattern to match targets
+            name: Optional name for the hook
+            description: Optional description
+            sequential: Whether to run sequentially
+            timeout: Timeout in seconds
+            env: Additional environment variables
+            shell: Whether to run in shell mode
+            
+        Returns:
+            The hook ID
+        """
+        hook = CommandHook(
+            event=event,
+            command=command,
+            matcher=matcher,
+            name=name,
+            description=description,
+            sequential=sequential,
+            timeout=timeout,
+            env=env or {},
+            shell=shell
+        )
+        return self.register(hook)
+    
+    def on(
+        self,
+        event: HookEvent,
+        matcher: Optional[str] = None,
+        sequential: bool = False,
+        timeout: float = 60.0
+    ) -> Callable:
+        """
+        Decorator to register a function as a hook.
+        
+        Args:
+            event: The event to hook
+            matcher: Optional regex pattern to match targets
+            sequential: Whether to run sequentially
+            timeout: Timeout in seconds
+            
+        Returns:
+            Decorator function
+            
+        Example:
+            @registry.on(HookEvent.BEFORE_TOOL)
+            def my_hook(event_data):
+                return HookResult.allow()
+        """
+        def decorator(func: Callable[[HookInput], HookResult]) -> Callable:
+            import asyncio
+            is_async = asyncio.iscoroutinefunction(func)
+            
+            self.register_function(
+                event=event,
+                func=func,
+                matcher=matcher,
+                sequential=sequential,
+                timeout=timeout,
+                is_async=is_async
+            )
+            
+            @wraps(func)
+            def wrapper(*args, **kwargs):
+                return func(*args, **kwargs)
+            
+            return wrapper
+        
+        return decorator
+    
+    def unregister(self, hook_id: str) -> bool:
+        """
+        Unregister a hook by ID.
+        
+        Args:
+            hook_id: The hook ID to unregister
+            
+        Returns:
+            True if found and removed, False otherwise
+        """
+        for event in HookEvent:
+            for i, hook in enumerate(self._hooks[event]):
+                if hook.id == hook_id:
+                    self._hooks[event].pop(i)
+                    logger.debug(f"Unregistered hook '{hook_id}'")
+                    return True
+        return False
+    
+    def get_hooks(
+        self,
+        event: HookEvent,
+        target: Optional[str] = None
+    ) -> List[HookDefinition]:
+        """
+        Get all hooks for an event, optionally filtered by target.
+        
+        Args:
+            event: The event to get hooks for
+            target: Optional target to filter by (e.g., tool name)
+            
+        Returns:
+            List of matching hook definitions
+        """
+        if not self._enabled:
+            return []
+        
+        hooks = self._hooks.get(event, [])
+        
+        if target is None:
+            return [h for h in hooks if h.enabled]
+        
+        return [h for h in hooks if h.enabled and h.matches(target)]
+    
+    def has_hooks(self, event: HookEvent) -> bool:
+        """Check if there are any hooks registered for an event."""
+        return bool(self.get_hooks(event))
+    
+    def clear(self, event: Optional[HookEvent] = None):
+        """
+        Clear all hooks or hooks for a specific event.
+        
+        Args:
+            event: Optional event to clear hooks for
+        """
+        if event is None:
+            for e in HookEvent:
+                self._hooks[e] = []
+        else:
+            self._hooks[event] = []
+    
+    def list_hooks(self) -> Dict[str, List[Dict]]:
+        """
+        List all registered hooks.
+        
+        Returns:
+            Dictionary mapping event names to hook info
+        """
+        result = {}
+        for event in HookEvent:
+            hooks = self._hooks[event]
+            if hooks:
+                result[event.value] = [
+                    {
+                        "id": h.id,
+                        "name": h.name,
+                        "type": "command" if isinstance(h, CommandHook) else "function",
+                        "matcher": h.matcher,
+                        "enabled": h.enabled,
+                        "sequential": h.sequential
+                    }
+                    for h in hooks
+                ]
+        return result
+    
+    def enable_hook(self, hook_id: str) -> bool:
+        """Enable a specific hook."""
+        for event in HookEvent:
+            for hook in self._hooks[event]:
+                if hook.id == hook_id:
+                    hook.enabled = True
+                    return True
+        return False
+    
+    def disable_hook(self, hook_id: str) -> bool:
+        """Disable a specific hook."""
+        for event in HookEvent:
+            for hook in self._hooks[event]:
+                if hook.id == hook_id:
+                    hook.enabled = False
+                    return True
+        return False
+    
+    def set_global_timeout(self, timeout: float):
+        """Set the global timeout for all hooks."""
+        self._global_timeout = timeout
+    
+    def __len__(self) -> int:
+        """Get total number of registered hooks."""
+        return sum(len(hooks) for hooks in self._hooks.values())
+    
+    def __repr__(self) -> str:
+        return f"HookRegistry(enabled={self._enabled}, hooks={len(self)})"
+
+
+# Global default registry
+_default_registry: Optional[HookRegistry] = None
+
+
+def get_default_registry() -> HookRegistry:
+    """Get the default global hook registry."""
+    global _default_registry
+    if _default_registry is None:
+        _default_registry = HookRegistry()
+    return _default_registry
+
+
+def set_default_registry(registry: HookRegistry):
+    """Set the default global hook registry."""
+    global _default_registry
+    _default_registry = registry
@@ -0,0 +1,450 @@
+"""
+Hook Runner for PraisonAI Agents.
+
+Executes hooks registered in the registry, supporting both
+Python functions and shell commands.
+"""
+
+import os
+import json
+import time
+import asyncio
+import logging
+import subprocess
+from typing import List, Optional, Dict, Any
+
+from .types import (
+    HookEvent, HookDefinition, CommandHook, FunctionHook,
+    HookInput, HookResult, HookExecutionResult
+)
+from .registry import HookRegistry
+
+logger = logging.getLogger(__name__)
+
+# Exit codes for command hooks
+EXIT_CODE_SUCCESS = 0
+EXIT_CODE_BLOCKING_ERROR = 2
+EXIT_CODE_NON_BLOCKING_ERROR = 1
+
+
+class HookRunner:
+    """
+    Executes hooks from a registry.
+    
+    Supports:
+    - Python function hooks (sync and async)
+    - Shell command hooks
+    - Sequential and parallel execution
+    - Timeout handling
+    - Result aggregation
+    
+    Example:
+        registry = HookRegistry()
+        runner = HookRunner(registry)
+        
+        # Execute hooks for an event
+        results = await runner.execute(
+            event=HookEvent.BEFORE_TOOL,
+            input_data=BeforeToolInput(
+                tool_name="write_file",
+                tool_input={"path": "/tmp/test.txt"}
+            )
+        )
+        
+        # Check if any hook blocked
+        if runner.is_blocked(results):
+            print("Tool execution blocked by hook")
+    """
+    
+    def __init__(
+        self,
+        registry: Optional[HookRegistry] = None,
+        default_timeout: float = 60.0,
+        cwd: Optional[str] = None
+    ):
+        """
+        Initialize the hook runner.
+        
+        Args:
+            registry: Hook registry to use
+            default_timeout: Default timeout for hooks
+            cwd: Working directory for command hooks
+        """
+        self._registry = registry or HookRegistry()
+        self._default_timeout = default_timeout
+        self._cwd = cwd or os.getcwd()
+    
+    @property
+    def registry(self) -> HookRegistry:
+        """Get the hook registry."""
+        return self._registry
+    
+    async def execute(
+        self,
+        event: HookEvent,
+        input_data: HookInput,
+        target: Optional[str] = None
+    ) -> List[HookExecutionResult]:
+        """
+        Execute all hooks for an event.
+        
+        Args:
+            event: The event to execute hooks for
+            input_data: Input data for the hooks
+            target: Optional target to filter hooks (e.g., tool name)
+            
+        Returns:
+            List of execution results
+        """
+        hooks = self._registry.get_hooks(event, target)
+        
+        if not hooks:
+            return []
+        
+        # Separate sequential and parallel hooks
+        sequential_hooks = [h for h in hooks if h.sequential]
+        parallel_hooks = [h for h in hooks if not h.sequential]
+        
+        results = []
+        
+        # Execute parallel hooks first
+        if parallel_hooks:
+            parallel_results = await self._execute_parallel(
+                parallel_hooks, event, input_data
+            )
+            results.extend(parallel_results)
+        
+        # Execute sequential hooks
+        if sequential_hooks:
+            sequential_results = await self._execute_sequential(
+                sequential_hooks, event, input_data
+            )
+            results.extend(sequential_results)
+        
+        return results
+    
+    def execute_sync(
+        self,
+        event: HookEvent,
+        input_data: HookInput,
+        target: Optional[str] = None
+    ) -> List[HookExecutionResult]:
+        """
+        Synchronous version of execute.
+        
+        Args:
+            event: The event to execute hooks for
+            input_data: Input data for the hooks
+            target: Optional target to filter hooks
+            
+        Returns:
+            List of execution results
+        """
+        try:
+            loop = asyncio.get_running_loop()
+            # If we're in an async context, create a task
+            future = asyncio.ensure_future(self.execute(event, input_data, target))
+            return loop.run_until_complete(future)
+        except RuntimeError:
+            # No event loop running, create one
+            return asyncio.run(self.execute(event, input_data, target))
+    
+    async def _execute_parallel(
+        self,
+        hooks: List[HookDefinition],
+        event: HookEvent,
+        input_data: HookInput
+    ) -> List[HookExecutionResult]:
+        """Execute hooks in parallel."""
+        tasks = [
+            self._execute_single(hook, event, input_data)
+            for hook in hooks
+        ]
+        return await asyncio.gather(*tasks)
+    
+    async def _execute_sequential(
+        self,
+        hooks: List[HookDefinition],
+        event: HookEvent,
+        input_data: HookInput
+    ) -> List[HookExecutionResult]:
+        """Execute hooks sequentially, passing modified input to next hook."""
+        results = []
+        current_input = input_data
+        
+        for hook in hooks:
+            result = await self._execute_single(hook, event, current_input)
+            results.append(result)
+            
+            # If hook modified the input, use it for next hook
+            if result.success and result.output and result.output.modified_input:
+                # Update input with modifications
+                for key, value in result.output.modified_input.items():
+                    if hasattr(current_input, key):
+                        setattr(current_input, key, value)
+            
+            # Stop if hook blocked
+            if result.output and result.output.is_denied():
+                break
+        
+        return results
+    
+    async def _execute_single(
+        self,
+        hook: HookDefinition,
+        event: HookEvent,
+        input_data: HookInput
+    ) -> HookExecutionResult:
+        """Execute a single hook."""
+        start_time = time.time()
+        
+        try:
+            if isinstance(hook, CommandHook):
+                return await self._execute_command_hook(hook, event, input_data, start_time)
+            elif isinstance(hook, FunctionHook):
+                return await self._execute_function_hook(hook, event, input_data, start_time)
+            else:
+                raise ValueError(f"Unknown hook type: {type(hook)}")
+        except Exception as e:
+            duration = (time.time() - start_time) * 1000
+            logger.warning(f"Hook '{hook.name}' failed: {e}")
+            return HookExecutionResult(
+                hook_id=hook.id,
+                hook_name=hook.name or "unknown",
+                event=event,
+                success=False,
+                error=str(e),
+                duration_ms=duration
+            )
+    
+    async def _execute_command_hook(
+        self,
+        hook: CommandHook,
+        event: HookEvent,
+        input_data: HookInput,
+        start_time: float
+    ) -> HookExecutionResult:
+        """Execute a command hook."""
+        timeout = hook.timeout or self._default_timeout
+        
+        # Prepare environment
+        env = os.environ.copy()
+        env.update(hook.env)
+        env["PRAISON_PROJECT_DIR"] = self._cwd
+        env["PRAISON_EVENT"] = event.value
+        
+        # Expand command variables
+        command = self._expand_command(hook.command, input_data)
+        
+        try:
+            # Create subprocess
+            process = await asyncio.create_subprocess_shell(
+                command,
+                stdin=asyncio.subprocess.PIPE,
+                stdout=asyncio.subprocess.PIPE,
+                stderr=asyncio.subprocess.PIPE,
+                env=env,
+                cwd=self._cwd
+            )
+            
+            # Send input as JSON
+            input_json = json.dumps(input_data.to_dict()).encode()
+            
+            try:
+                stdout, stderr = await asyncio.wait_for(
+                    process.communicate(input=input_json),
+                    timeout=timeout
+                )
+            except asyncio.TimeoutError:
+                process.kill()
+                await process.wait()
+                duration = (time.time() - start_time) * 1000
+                return HookExecutionResult(
+                    hook_id=hook.id,
+                    hook_name=hook.name or "unknown",
+                    event=event,
+                    success=False,
+                    error=f"Hook timed out after {timeout}s",
+                    duration_ms=duration
+                )
+            
+            duration = (time.time() - start_time) * 1000
+            exit_code = process.returncode
+            stdout_str = stdout.decode() if stdout else ""
+            stderr_str = stderr.decode() if stderr else ""
+            
+            # Parse output
+            output = self._parse_command_output(stdout_str, stderr_str, exit_code)
+            
+            return HookExecutionResult(
+                hook_id=hook.id,
+                hook_name=hook.name or "unknown",
+                event=event,
+                success=exit_code == EXIT_CODE_SUCCESS,
+                output=output,
+                stdout=stdout_str,
+                stderr=stderr_str,
+                exit_code=exit_code,
+                duration_ms=duration
+            )
+            
+        except Exception as e:
+            duration = (time.time() - start_time) * 1000
+            return HookExecutionResult(
+                hook_id=hook.id,
+                hook_name=hook.name or "unknown",
+                event=event,
+                success=False,
+                error=str(e),
+                duration_ms=duration
+            )
+    
+    async def _execute_function_hook(
+        self,
+        hook: FunctionHook,
+        event: HookEvent,
+        input_data: HookInput,
+        start_time: float
+    ) -> HookExecutionResult:
+        """Execute a function hook."""
+        if hook.func is None:
+            duration = (time.time() - start_time) * 1000
+            return HookExecutionResult(
+                hook_id=hook.id,
+                hook_name=hook.name or "unknown",
+                event=event,
+                success=False,
+                error="Hook function is None",
+                duration_ms=duration
+            )
+        
+        timeout = hook.timeout or self._default_timeout
+        
+        try:
+            if hook.is_async:
+                # Execute async function with timeout
+                result = await asyncio.wait_for(
+                    hook.func(input_data),
+                    timeout=timeout
+                )
+            else:
+                # Execute sync function in thread pool with timeout
+                loop = asyncio.get_event_loop()
+                result = await asyncio.wait_for(
+                    loop.run_in_executor(None, hook.func, input_data),
+                    timeout=timeout
+                )
+            
+            duration = (time.time() - start_time) * 1000
+            
+            # Normalize result
+            if result is None:
+                result = HookResult.allow()
+            elif not isinstance(result, HookResult):
+                result = HookResult.allow()
+            
+            return HookExecutionResult(
+                hook_id=hook.id,
+                hook_name=hook.name or "unknown",
+                event=event,
+                success=True,
+                output=result,
+                duration_ms=duration
+            )
+            
+        except asyncio.TimeoutError:
+            duration = (time.time() - start_time) * 1000
+            return HookExecutionResult(
+                hook_id=hook.id,
+                hook_name=hook.name or "unknown",
+                event=event,
+                success=False,
+                error=f"Hook timed out after {timeout}s",
+                duration_ms=duration
+            )
+        except Exception as e:
+            duration = (time.time() - start_time) * 1000
+            return HookExecutionResult(
+                hook_id=hook.id,
+                hook_name=hook.name or "unknown",
+                event=event,
+                success=False,
+                error=str(e),
+                duration_ms=duration
+            )
+    
+    def _expand_command(self, command: str, input_data: HookInput) -> str:
+        """Expand variables in command string."""
+        return command.replace(
+            "$PRAISON_PROJECT_DIR", self._cwd
+        ).replace(
+            "$PRAISON_CWD", input_data.cwd
+        )
+    
+    def _parse_command_output(
+        self,
+        stdout: str,
+        stderr: str,
+        exit_code: int
+    ) -> HookResult:
+        """Parse command output into HookResult."""
+        # Try to parse JSON from stdout
+        if stdout.strip():
+            try:
+                data = json.loads(stdout.strip())
+                
+                # Handle double-encoded JSON
+                if isinstance(data, str):
+                    data = json.loads(data)
+                
+                return HookResult(
+                    decision=data.get("decision", "allow"),
+                    reason=data.get("reason"),
+                    modified_input=data.get("modified_input"),
+                    additional_context=data.get("additional_context"),
+                    suppress_output=data.get("suppress_output", False)
+                )
+            except json.JSONDecodeError:
+                pass
+        
+        # Convert exit code to decision
+        if exit_code == EXIT_CODE_SUCCESS:
+            return HookResult(
+                decision="allow",
+                additional_context=stdout.strip() if stdout.strip() else None
+            )
+        elif exit_code == EXIT_CODE_BLOCKING_ERROR:
+            return HookResult(
+                decision="deny",
+                reason=stderr.strip() or stdout.strip() or "Blocked by hook"
+            )
+        else:
+            return HookResult(
+                decision="allow",
+                additional_context=f"Warning: {stderr.strip() or stdout.strip()}"
+            )
+    
+    @staticmethod
+    def is_blocked(results: List[HookExecutionResult]) -> bool:
+        """Check if any hook blocked execution."""
+        for result in results:
+            if result.output and result.output.is_denied():
+                return True
+        return False
+    
+    @staticmethod
+    def get_blocking_reason(results: List[HookExecutionResult]) -> Optional[str]:
+        """Get the reason for blocking from results."""
+        for result in results:
+            if result.output and result.output.is_denied():
+                return result.output.reason
+        return None
+    
+    @staticmethod
+    def aggregate_context(results: List[HookExecutionResult]) -> Optional[str]:
+        """Aggregate additional context from all results."""
+        contexts = []
+        for result in results:
+            if result.output and result.output.additional_context:
+                contexts.append(result.output.additional_context)
+        return "\n".join(contexts) if contexts else None
@@ -0,0 +1,197 @@
+"""
+Hook Types for PraisonAI Agents.
+
+Defines the core types, enums, and dataclasses for the hook system.
+"""
+
+import uuid
+from enum import Enum
+from dataclasses import dataclass, field
+from typing import Optional, Dict, Any, List, Callable, Union, Literal
+
+
+class HookEvent(str, Enum):
+    """Event names for the hook system."""
+    BEFORE_TOOL = "before_tool"
+    AFTER_TOOL = "after_tool"
+    BEFORE_AGENT = "before_agent"
+    AFTER_AGENT = "after_agent"
+    SESSION_START = "session_start"
+    SESSION_END = "session_end"
+    BEFORE_LLM = "before_llm"
+    AFTER_LLM = "after_llm"
+    ON_ERROR = "on_error"
+    ON_RETRY = "on_retry"
+
+
+# Decision types for hook outputs
+HookDecision = Literal["allow", "deny", "block", "ask", None]
+
+
+@dataclass
+class HookInput:
+    """Base hook input - common fields for all events."""
+    session_id: str
+    cwd: str
+    event_name: str
+    timestamp: str
+    agent_name: Optional[str] = None
+    extra: Dict[str, Any] = field(default_factory=dict)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary for JSON serialization."""
+        return {
+            "session_id": self.session_id,
+            "cwd": self.cwd,
+            "event_name": self.event_name,
+            "timestamp": self.timestamp,
+            "agent_name": self.agent_name,
+            **self.extra
+        }
+
+
+@dataclass
+class HookOutput:
+    """Base hook output - common fields for all events."""
+    proceed: bool = True
+    stop_reason: Optional[str] = None
+    suppress_output: bool = False
+    system_message: Optional[str] = None
+    decision: HookDecision = None
+    reason: Optional[str] = None
+    modified_data: Optional[Dict[str, Any]] = None
+    
+    def is_blocking(self) -> bool:
+        """Check if this output represents a blocking decision."""
+        return self.decision in ("block", "deny")
+    
+    def should_stop(self) -> bool:
+        """Check if execution should stop."""
+        return not self.proceed
+    
+    def get_reason(self) -> str:
+        """Get the effective reason for blocking or stopping."""
+        return self.reason or self.stop_reason or "No reason provided"
+
+
+@dataclass
+class HookResult:
+    """Result from a hook execution."""
+    decision: HookDecision = "allow"
+    reason: Optional[str] = None
+    modified_input: Optional[Dict[str, Any]] = None
+    additional_context: Optional[str] = None
+    suppress_output: bool = False
+    
+    @classmethod
+    def allow(cls, reason: Optional[str] = None) -> "HookResult":
+        """Create an allow result."""
+        return cls(decision="allow", reason=reason)
+    
+    @classmethod
+    def deny(cls, reason: str) -> "HookResult":
+        """Create a deny result."""
+        return cls(decision="deny", reason=reason)
+    
+    @classmethod
+    def block(cls, reason: str) -> "HookResult":
+        """Create a block result."""
+        return cls(decision="block", reason=reason)
+    
+    @classmethod
+    def ask(cls, reason: str) -> "HookResult":
+        """Create an ask result (requires user confirmation)."""
+        return cls(decision="ask", reason=reason)
+    
+    def is_allowed(self) -> bool:
+        """Check if the result allows execution."""
+        return self.decision in ("allow", None)
+    
+    def is_denied(self) -> bool:
+        """Check if the result denies execution."""
+        return self.decision in ("deny", "block")
+
+
+@dataclass
+class HookDefinition:
+    """Hook definition with matcher and configuration."""
+    id: str = field(default_factory=lambda: str(uuid.uuid4())[:8])
+    event: HookEvent = HookEvent.BEFORE_TOOL
+    matcher: Optional[str] = None  # Regex pattern to match tool names
+    sequential: bool = False  # Execute hooks sequentially vs parallel
+    enabled: bool = True
+    name: Optional[str] = None
+    description: Optional[str] = None
+    timeout: float = 60.0  # Timeout in seconds
+    
+    def matches(self, target: str) -> bool:
+        """Check if this hook matches the target (tool name, etc.)."""
+        if self.matcher is None:
+            return True
+        
+        import re
+        try:
+            return bool(re.match(self.matcher, target))
+        except re.error:
+            # Invalid regex, fall back to simple string match
+            return self.matcher in target
+
+
+@dataclass
+class CommandHook(HookDefinition):
+    """Hook that executes a shell command."""
+    command: str = ""
+    shell: bool = True
+    env: Dict[str, str] = field(default_factory=dict)
+    
+    def __post_init__(self):
+        if not self.name:
+            self.name = f"command_hook_{self.id}"
+
+
+@dataclass
+class FunctionHook(HookDefinition):
+    """Hook that executes a Python function."""
+    func: Optional[Callable[[HookInput], HookResult]] = None
+    is_async: bool = False
+    
+    def __post_init__(self):
+        if not self.name and self.func:
+            self.name = self.func.__name__
+        elif not self.name:
+            self.name = f"function_hook_{self.id}"
+
+
+@dataclass
+class HookExecutionResult:
+    """Result of executing a single hook."""
+    hook_id: str
+    hook_name: str
+    event: HookEvent
+    success: bool
+    output: Optional[HookResult] = None
+    stdout: Optional[str] = None
+    stderr: Optional[str] = None
+    exit_code: Optional[int] = None
+    duration_ms: float = 0.0
+    error: Optional[str] = None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "hook_id": self.hook_id,
+            "hook_name": self.hook_name,
+            "event": self.event.value,
+            "success": self.success,
+            "output": self.output.__dict__ if self.output else None,
+            "stdout": self.stdout,
+            "stderr": self.stderr,
+            "exit_code": self.exit_code,
+            "duration_ms": self.duration_ms,
+            "error": self.error
+        }
+
+
+# Type alias for hook functions
+HookFunction = Callable[[HookInput], Union[HookResult, None]]
+AsyncHookFunction = Callable[[HookInput], Any]  # Returns Awaitable[HookResult]
@@ -0,0 +1,65 @@
+"""
+LSP Integration Module for PraisonAI Agents.
+
+Provides Language Server Protocol integration for code intelligence:
+- Diagnostics (errors, warnings)
+- Code completion suggestions
+- Go to definition
+- Find references
+- Hover information
+
+Zero Performance Impact:
+- All imports are lazy loaded via __getattr__
+- LSP client only initialized when needed
+- No overhead when not in use
+
+Usage:
+    from praisonaiagents.lsp import LSPClient
+    
+    # Create client for a language
+    client = LSPClient(language="python")
+    
+    # Start the language server
+    await client.start()
+    
+    # Get diagnostics for a file
+    diagnostics = await client.get_diagnostics("/path/to/file.py")
+    
+    # Get completions at a position
+    completions = await client.get_completions("/path/to/file.py", line=10, character=5)
+"""
+
+__all__ = [
+    # Core client
+    "LSPClient",
+    # Data types
+    "Diagnostic",
+    "DiagnosticSeverity",
+    "CompletionItem",
+    "Location",
+    "Position",
+    "Range",
+    # Configuration
+    "LSPConfig",
+]
+
+
+def __getattr__(name: str):
+    """Lazy load module components to avoid import overhead."""
+    if name == "LSPClient":
+        from .client import LSPClient
+        return LSPClient
+    
+    if name in ("Diagnostic", "DiagnosticSeverity", "CompletionItem", 
+                "Location", "Position", "Range"):
+        from .types import (
+            Diagnostic, DiagnosticSeverity, CompletionItem,
+            Location, Position, Range
+        )
+        return locals()[name]
+    
+    if name == "LSPConfig":
+        from .config import LSPConfig
+        return LSPConfig
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -0,0 +1,489 @@
+"""
+LSP Client for PraisonAI Agents.
+
+Provides Language Server Protocol client implementation.
+"""
+
+import os
+import json
+import asyncio
+import logging
+from typing import Optional, List, Dict, Any
+from pathlib import Path
+
+from .types import (
+    Diagnostic, DiagnosticSeverity, CompletionItem, Location,
+    Position, Range, TextDocumentItem, TextDocumentIdentifier,
+    TextDocumentPositionParams
+)
+from .config import LSPConfig
+
+logger = logging.getLogger(__name__)
+
+
+class LSPClient:
+    """
+    Language Server Protocol client.
+    
+    Communicates with language servers to provide code intelligence
+    features like diagnostics, completions, and navigation.
+    
+    Example:
+        client = LSPClient(language="python")
+        await client.start()
+        
+        # Get diagnostics
+        diagnostics = await client.get_diagnostics("/path/to/file.py")
+        
+        # Get completions
+        completions = await client.get_completions(
+            "/path/to/file.py", line=10, character=5
+        )
+        
+        await client.stop()
+    """
+    
+    def __init__(
+        self,
+        language: str,
+        command: Optional[str] = None,
+        args: Optional[List[str]] = None,
+        root_uri: Optional[str] = None
+    ):
+        """
+        Initialize the LSP client.
+        
+        Args:
+            language: Programming language (python, javascript, etc.)
+            command: Language server command (uses default if not specified)
+            args: Command arguments
+            root_uri: Workspace root URI
+        """
+        self.config = LSPConfig(
+            language=language,
+            command=command,
+            args=args or [],
+            root_uri=root_uri
+        )
+        
+        self._process: Optional[asyncio.subprocess.Process] = None
+        self._request_id = 0
+        self._pending_requests: Dict[int, asyncio.Future] = {}
+        self._diagnostics: Dict[str, List[Diagnostic]] = {}
+        self._initialized = False
+        self._reader_task: Optional[asyncio.Task] = None
+    
+    @property
+    def is_running(self) -> bool:
+        """Check if the language server is running."""
+        return self._process is not None and self._process.returncode is None
+    
+    async def start(self) -> bool:
+        """
+        Start the language server.
+        
+        Returns:
+            True if started successfully
+        """
+        if self.is_running:
+            return True
+        
+        try:
+            cmd = [self.config.command] + self.config.args
+            
+            self._process = await asyncio.create_subprocess_exec(
+                *cmd,
+                stdin=asyncio.subprocess.PIPE,
+                stdout=asyncio.subprocess.PIPE,
+                stderr=asyncio.subprocess.PIPE
+            )
+            
+            # Start reader task
+            self._reader_task = asyncio.create_task(self._read_responses())
+            
+            # Initialize the server
+            root_uri = self.config.root_uri or f"file://{os.getcwd()}"
+            
+            result = await self._send_request("initialize", {
+                "processId": os.getpid(),
+                "rootUri": root_uri,
+                "capabilities": {
+                    "textDocument": {
+                        "completion": {"completionItem": {"snippetSupport": True}},
+                        "hover": {},
+                        "definition": {},
+                        "references": {},
+                        "publishDiagnostics": {}
+                    }
+                },
+                "initializationOptions": self.config.initialization_options
+            })
+            
+            if result:
+                await self._send_notification("initialized", {})
+                self._initialized = True
+                logger.info(f"LSP server started: {self.config.command}")
+                return True
+            
+            return False
+            
+        except FileNotFoundError:
+            logger.error(f"Language server not found: {self.config.command}")
+            return False
+        except Exception as e:
+            logger.error(f"Failed to start LSP server: {e}")
+            return False
+    
+    async def stop(self):
+        """Stop the language server."""
+        if not self.is_running:
+            return
+        
+        try:
+            await self._send_request("shutdown", None)
+            await self._send_notification("exit", None)
+        except Exception:
+            pass
+        
+        if self._reader_task:
+            self._reader_task.cancel()
+            try:
+                await self._reader_task
+            except asyncio.CancelledError:
+                pass
+        
+        if self._process:
+            self._process.terminate()
+            try:
+                await asyncio.wait_for(self._process.wait(), timeout=5.0)
+            except asyncio.TimeoutError:
+                self._process.kill()
+        
+        self._process = None
+        self._initialized = False
+    
+    async def open_document(self, file_path: str, text: Optional[str] = None) -> bool:
+        """
+        Open a document in the language server.
+        
+        Args:
+            file_path: Path to the file
+            text: File content (reads from disk if not provided)
+            
+        Returns:
+            True if successful
+        """
+        if not self._initialized:
+            return False
+        
+        if text is None:
+            try:
+                with open(file_path, "r") as f:
+                    text = f.read()
+            except Exception as e:
+                logger.error(f"Failed to read file: {e}")
+                return False
+        
+        uri = f"file://{os.path.abspath(file_path)}"
+        
+        await self._send_notification("textDocument/didOpen", {
+            "textDocument": TextDocumentItem(
+                uri=uri,
+                language_id=self.config.language,
+                version=1,
+                text=text
+            ).to_dict()
+        })
+        
+        return True
+    
+    async def close_document(self, file_path: str):
+        """Close a document in the language server."""
+        if not self._initialized:
+            return
+        
+        uri = f"file://{os.path.abspath(file_path)}"
+        
+        await self._send_notification("textDocument/didClose", {
+            "textDocument": TextDocumentIdentifier(uri=uri).to_dict()
+        })
+    
+    async def get_diagnostics(self, file_path: str) -> List[Diagnostic]:
+        """
+        Get diagnostics for a file.
+        
+        Args:
+            file_path: Path to the file
+            
+        Returns:
+            List of diagnostics
+        """
+        uri = f"file://{os.path.abspath(file_path)}"
+        return self._diagnostics.get(uri, [])
+    
+    async def get_completions(
+        self,
+        file_path: str,
+        line: int,
+        character: int
+    ) -> List[CompletionItem]:
+        """
+        Get completions at a position.
+        
+        Args:
+            file_path: Path to the file
+            line: Line number (0-indexed)
+            character: Character position (0-indexed)
+            
+        Returns:
+            List of completion items
+        """
+        if not self._initialized:
+            return []
+        
+        uri = f"file://{os.path.abspath(file_path)}"
+        
+        result = await self._send_request("textDocument/completion", {
+            "textDocument": {"uri": uri},
+            "position": {"line": line, "character": character}
+        })
+        
+        if result is None:
+            return []
+        
+        items = result.get("items", result) if isinstance(result, dict) else result
+        
+        return [
+            CompletionItem.from_dict(item)
+            for item in (items if isinstance(items, list) else [])
+        ]
+    
+    async def get_definition(
+        self,
+        file_path: str,
+        line: int,
+        character: int
+    ) -> List[Location]:
+        """
+        Get definition location(s) for a symbol.
+        
+        Args:
+            file_path: Path to the file
+            line: Line number (0-indexed)
+            character: Character position (0-indexed)
+            
+        Returns:
+            List of locations
+        """
+        if not self._initialized:
+            return []
+        
+        uri = f"file://{os.path.abspath(file_path)}"
+        
+        result = await self._send_request("textDocument/definition", {
+            "textDocument": {"uri": uri},
+            "position": {"line": line, "character": character}
+        })
+        
+        if result is None:
+            return []
+        
+        if isinstance(result, dict):
+            return [Location.from_dict(result)]
+        elif isinstance(result, list):
+            return [Location.from_dict(loc) for loc in result]
+        
+        return []
+    
+    async def get_references(
+        self,
+        file_path: str,
+        line: int,
+        character: int,
+        include_declaration: bool = True
+    ) -> List[Location]:
+        """
+        Get references to a symbol.
+        
+        Args:
+            file_path: Path to the file
+            line: Line number (0-indexed)
+            character: Character position (0-indexed)
+            include_declaration: Include the declaration in results
+            
+        Returns:
+            List of locations
+        """
+        if not self._initialized:
+            return []
+        
+        uri = f"file://{os.path.abspath(file_path)}"
+        
+        result = await self._send_request("textDocument/references", {
+            "textDocument": {"uri": uri},
+            "position": {"line": line, "character": character},
+            "context": {"includeDeclaration": include_declaration}
+        })
+        
+        if result is None:
+            return []
+        
+        return [Location.from_dict(loc) for loc in result]
+    
+    async def get_hover(
+        self,
+        file_path: str,
+        line: int,
+        character: int
+    ) -> Optional[str]:
+        """
+        Get hover information for a position.
+        
+        Args:
+            file_path: Path to the file
+            line: Line number (0-indexed)
+            character: Character position (0-indexed)
+            
+        Returns:
+            Hover content as string
+        """
+        if not self._initialized:
+            return None
+        
+        uri = f"file://{os.path.abspath(file_path)}"
+        
+        result = await self._send_request("textDocument/hover", {
+            "textDocument": {"uri": uri},
+            "position": {"line": line, "character": character}
+        })
+        
+        if result is None:
+            return None
+        
+        contents = result.get("contents")
+        if isinstance(contents, str):
+            return contents
+        elif isinstance(contents, dict):
+            return contents.get("value", str(contents))
+        elif isinstance(contents, list):
+            return "\n".join(
+                c.get("value", str(c)) if isinstance(c, dict) else str(c)
+                for c in contents
+            )
+        
+        return None
+    
+    async def _send_request(self, method: str, params: Any) -> Any:
+        """Send a request and wait for response."""
+        if not self.is_running:
+            return None
+        
+        self._request_id += 1
+        request_id = self._request_id
+        
+        message = {
+            "jsonrpc": "2.0",
+            "id": request_id,
+            "method": method,
+            "params": params
+        }
+        
+        future = asyncio.get_event_loop().create_future()
+        self._pending_requests[request_id] = future
+        
+        await self._send_message(message)
+        
+        try:
+            result = await asyncio.wait_for(future, timeout=self.config.timeout)
+            return result
+        except asyncio.TimeoutError:
+            logger.warning(f"Request timed out: {method}")
+            self._pending_requests.pop(request_id, None)
+            return None
+    
+    async def _send_notification(self, method: str, params: Any):
+        """Send a notification (no response expected)."""
+        if not self.is_running:
+            return
+        
+        message = {
+            "jsonrpc": "2.0",
+            "method": method,
+            "params": params
+        }
+        
+        await self._send_message(message)
+    
+    async def _send_message(self, message: Dict[str, Any]):
+        """Send a JSON-RPC message."""
+        if self._process is None or self._process.stdin is None:
+            return
+        
+        content = json.dumps(message)
+        header = f"Content-Length: {len(content)}\r\n\r\n"
+        
+        self._process.stdin.write(header.encode() + content.encode())
+        await self._process.stdin.drain()
+    
+    async def _read_responses(self):
+        """Read responses from the language server."""
+        if self._process is None or self._process.stdout is None:
+            return
+        
+        try:
+            while True:
+                # Read header
+                header = b""
+                while b"\r\n\r\n" not in header:
+                    chunk = await self._process.stdout.read(1)
+                    if not chunk:
+                        return
+                    header += chunk
+                
+                # Parse content length
+                content_length = 0
+                for line in header.decode().split("\r\n"):
+                    if line.startswith("Content-Length:"):
+                        content_length = int(line.split(":")[1].strip())
+                        break
+                
+                if content_length == 0:
+                    continue
+                
+                # Read content
+                content = await self._process.stdout.read(content_length)
+                message = json.loads(content.decode())
+                
+                await self._handle_message(message)
+                
+        except asyncio.CancelledError:
+            raise
+        except Exception as e:
+            logger.error(f"Error reading LSP response: {e}")
+    
+    async def _handle_message(self, message: Dict[str, Any]):
+        """Handle an incoming message."""
+        if "id" in message:
+            # Response to a request
+            request_id = message["id"]
+            if request_id in self._pending_requests:
+                future = self._pending_requests.pop(request_id)
+                if "error" in message:
+                    future.set_exception(
+                        RuntimeError(message["error"].get("message", "Unknown error"))
+                    )
+                else:
+                    future.set_result(message.get("result"))
+        
+        elif "method" in message:
+            # Notification from server
+            method = message["method"]
+            params = message.get("params", {})
+            
+            if method == "textDocument/publishDiagnostics":
+                uri = params.get("uri", "")
+                diagnostics = [
+                    Diagnostic.from_dict(d)
+                    for d in params.get("diagnostics", [])
+                ]
+                self._diagnostics[uri] = diagnostics
@@ -0,0 +1,52 @@
+"""
+LSP Configuration for PraisonAI Agents.
+"""
+
+from dataclasses import dataclass, field
+from typing import Optional, Dict, List
+
+
+# Default language server commands
+DEFAULT_SERVERS = {
+    "python": {
+        "command": "pylsp",
+        "args": [],
+    },
+    "javascript": {
+        "command": "typescript-language-server",
+        "args": ["--stdio"],
+    },
+    "typescript": {
+        "command": "typescript-language-server",
+        "args": ["--stdio"],
+    },
+    "rust": {
+        "command": "rust-analyzer",
+        "args": [],
+    },
+    "go": {
+        "command": "gopls",
+        "args": [],
+    },
+}
+
+
+@dataclass
+class LSPConfig:
+    """Configuration for LSP client."""
+    language: str
+    command: Optional[str] = None
+    args: List[str] = field(default_factory=list)
+    root_uri: Optional[str] = None
+    initialization_options: Dict = field(default_factory=dict)
+    timeout: float = 30.0
+    
+    def __post_init__(self):
+        # Use default server if not specified
+        if self.command is None:
+            if self.language in DEFAULT_SERVERS:
+                server = DEFAULT_SERVERS[self.language]
+                self.command = server["command"]
+                self.args = server["args"]
+            else:
+                raise ValueError(f"No default server for language: {self.language}")
@@ -0,0 +1,162 @@
+"""
+LSP Types for PraisonAI Agents.
+
+Defines the core types for Language Server Protocol integration.
+"""
+
+from enum import IntEnum
+from dataclasses import dataclass, field
+from typing import Optional, List, Dict, Any
+
+
+class DiagnosticSeverity(IntEnum):
+    """Severity of a diagnostic."""
+    ERROR = 1
+    WARNING = 2
+    INFORMATION = 3
+    HINT = 4
+
+
+@dataclass
+class Position:
+    """Position in a text document (0-indexed)."""
+    line: int
+    character: int
+    
+    def to_dict(self) -> Dict[str, int]:
+        return {"line": self.line, "character": self.character}
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, int]) -> "Position":
+        return cls(line=data["line"], character=data["character"])
+
+
+@dataclass
+class Range:
+    """Range in a text document."""
+    start: Position
+    end: Position
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {"start": self.start.to_dict(), "end": self.end.to_dict()}
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "Range":
+        return cls(
+            start=Position.from_dict(data["start"]),
+            end=Position.from_dict(data["end"])
+        )
+
+
+@dataclass
+class Location:
+    """Location in a document."""
+    uri: str
+    range: Range
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {"uri": self.uri, "range": self.range.to_dict()}
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "Location":
+        return cls(uri=data["uri"], range=Range.from_dict(data["range"]))
+
+
+@dataclass
+class Diagnostic:
+    """Represents a diagnostic (error, warning, etc.)."""
+    range: Range
+    message: str
+    severity: DiagnosticSeverity = DiagnosticSeverity.ERROR
+    code: Optional[str] = None
+    source: Optional[str] = None
+    related_information: List[Dict[str, Any]] = field(default_factory=list)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "range": self.range.to_dict(),
+            "message": self.message,
+            "severity": self.severity.value,
+            "code": self.code,
+            "source": self.source
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "Diagnostic":
+        return cls(
+            range=Range.from_dict(data["range"]),
+            message=data["message"],
+            severity=DiagnosticSeverity(data.get("severity", 1)),
+            code=data.get("code"),
+            source=data.get("source")
+        )
+
+
+@dataclass
+class CompletionItem:
+    """Represents a completion item."""
+    label: str
+    kind: int = 1  # Text
+    detail: Optional[str] = None
+    documentation: Optional[str] = None
+    insert_text: Optional[str] = None
+    sort_text: Optional[str] = None
+    filter_text: Optional[str] = None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "label": self.label,
+            "kind": self.kind,
+            "detail": self.detail,
+            "documentation": self.documentation,
+            "insertText": self.insert_text
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "CompletionItem":
+        return cls(
+            label=data["label"],
+            kind=data.get("kind", 1),
+            detail=data.get("detail"),
+            documentation=data.get("documentation"),
+            insert_text=data.get("insertText")
+        )
+
+
+@dataclass
+class TextDocumentItem:
+    """Represents a text document."""
+    uri: str
+    language_id: str
+    version: int
+    text: str
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "uri": self.uri,
+            "languageId": self.language_id,
+            "version": self.version,
+            "text": self.text
+        }
+
+
+@dataclass
+class TextDocumentIdentifier:
+    """Identifies a text document."""
+    uri: str
+    
+    def to_dict(self) -> Dict[str, str]:
+        return {"uri": self.uri}
+
+
+@dataclass
+class TextDocumentPositionParams:
+    """Parameters for text document position requests."""
+    text_document: TextDocumentIdentifier
+    position: Position
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "textDocument": self.text_document.to_dict(),
+            "position": self.position.to_dict()
+        }
@@ -0,0 +1,240 @@
+"""
+Observability interface for PraisonAI Agents.
+
+This module provides the protocol and types for observability/tracing.
+Implementations are provided by the wrapper layer (praisonai_tools.observability).
+
+Usage (simplest - recommended):
+    from praisonaiagents import Agent, obs
+    
+    agent = Agent(
+        name="Assistant",
+        observability=obs.auto(),  # Auto-detect from env vars
+    )
+    agent.chat("Hello!")  # Auto-traces to configured provider
+
+Alternative (explicit provider):
+    observability=obs.langfuse()     # Langfuse
+    observability=obs.langsmith()    # LangSmith
+    observability=obs.agentops()     # AgentOps
+    observability=obs.arize()        # Arize Phoenix
+    observability=obs.datadog()      # Datadog
+"""
+
+from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
+from dataclasses import dataclass, field
+import time
+
+
+@dataclass
+class Span:
+    """Represents a span in a trace."""
+    span_id: str
+    trace_id: str
+    name: str
+    parent_span_id: Optional[str] = None
+    start_time: float = field(default_factory=time.time)
+    end_time: Optional[float] = None
+    attributes: Dict[str, Any] = field(default_factory=dict)
+    status: str = "ok"
+
+
+@dataclass
+class Trace:
+    """Represents a complete trace."""
+    trace_id: str
+    session_id: Optional[str] = None
+    agent_name: Optional[str] = None
+    user_id: Optional[str] = None
+    start_time: float = field(default_factory=time.time)
+    end_time: Optional[float] = None
+    spans: List[Span] = field(default_factory=list)
+    metadata: Dict[str, Any] = field(default_factory=dict)
+    status: str = "ok"
+
+
+@runtime_checkable
+class ObservabilityAdapter(Protocol):
+    """Protocol for observability adapters."""
+    
+    def on_trace_start(
+        self,
+        trace_id: str,
+        session_id: Optional[str] = None,
+        agent_name: Optional[str] = None,
+        user_id: Optional[str] = None,
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> None:
+        """Called when a trace starts."""
+        ...
+    
+    def on_trace_end(
+        self,
+        trace_id: str,
+        status: str = "ok",
+        metadata: Optional[Dict[str, Any]] = None,
+    ) -> None:
+        """Called when a trace ends."""
+        ...
+    
+    def on_span_start(
+        self,
+        span_id: str,
+        trace_id: str,
+        name: str,
+        parent_span_id: Optional[str] = None,
+        attributes: Optional[Dict[str, Any]] = None,
+    ) -> None:
+        """Called when a span starts."""
+        ...
+    
+    def on_span_end(
+        self,
+        span_id: str,
+        status: str = "ok",
+        attributes: Optional[Dict[str, Any]] = None,
+    ) -> None:
+        """Called when a span ends."""
+        ...
+    
+    def on_llm_call(
+        self,
+        span_id: str,
+        model: str,
+        messages: List[Dict[str, Any]],
+        response: Optional[str] = None,
+        tokens: Optional[Dict[str, int]] = None,
+        latency_ms: Optional[float] = None,
+    ) -> None:
+        """Called when an LLM call is made."""
+        ...
+    
+    def on_tool_call(
+        self,
+        span_id: str,
+        tool_name: str,
+        args: Dict[str, Any],
+        result: Any,
+        latency_ms: Optional[float] = None,
+    ) -> None:
+        """Called when a tool is invoked."""
+        ...
+    
+    def flush(self) -> None:
+        """Flush any pending data."""
+        ...
+    
+    def close(self) -> None:
+        """Close the adapter and release resources."""
+        ...
+
+
+class _LazyObsModule:
+    """
+    Lazy proxy for observability backends.
+    
+    Allows `from praisonaiagents import obs` without importing heavy deps.
+    Actual provider classes are loaded only when accessed.
+    """
+    
+    _PROVIDERS = {
+        "langfuse": "praisonai_tools.observability.providers.langfuse_provider",
+        "langsmith": "praisonai_tools.observability.providers.langsmith_provider",
+        "agentops": "praisonai_tools.observability.providers.agentops_provider",
+        "arize": "praisonai_tools.observability.providers.arize_phoenix_provider",
+        "phoenix": "praisonai_tools.observability.providers.arize_phoenix_provider",
+        "datadog": "praisonai_tools.observability.providers.datadog_provider",
+        "mlflow": "praisonai_tools.observability.providers.mlflow_provider",
+        "openlit": "praisonai_tools.observability.providers.openlit_provider",
+        "opik": "praisonai_tools.observability.providers.opik_provider",
+        "portkey": "praisonai_tools.observability.providers.portkey_provider",
+        "traceloop": "praisonai_tools.observability.providers.traceloop_provider",
+        "weave": "praisonai_tools.observability.providers.weave_provider",
+        "braintrust": "praisonai_tools.observability.providers.braintrust_provider",
+        "langtrace": "praisonai_tools.observability.providers.langtrace_provider",
+        "langwatch": "praisonai_tools.observability.providers.langwatch_provider",
+        "maxim": "praisonai_tools.observability.providers.maxim_provider",
+    }
+    
+    def __getattr__(self, name: str):
+        if name in self._PROVIDERS:
+            return self._create_provider_factory(name)
+        raise AttributeError(f"module 'obs' has no attribute {name!r}")
+    
+    def _create_provider_factory(self, provider_name: str):
+        """Create a factory function for a provider."""
+        def factory(**kwargs):
+            try:
+                import importlib
+                module = importlib.import_module(self._PROVIDERS[provider_name])
+                # Get the provider class (naming convention: XxxProvider)
+                class_name = f"{provider_name.title().replace('_', '')}Provider"
+                provider_cls = getattr(module, class_name, None)
+                if provider_cls:
+                    return provider_cls(**kwargs)
+                # Fallback: try to find any class ending with Provider
+                for attr_name in dir(module):
+                    if attr_name.endswith("Provider"):
+                        return getattr(module, attr_name)(**kwargs)
+                raise AttributeError(f"No provider class found in {module}")
+            except ImportError as e:
+                raise ImportError(
+                    f"Observability provider '{provider_name}' requires praisonai-tools. "
+                    f"Install with: pip install praisonai-tools\n"
+                    f"Original error: {e}"
+                ) from e
+        return factory
+    
+    def auto(self, **kwargs):
+        """
+        Auto-detect observability provider from environment variables.
+        
+        Checks for common env vars like LANGFUSE_PUBLIC_KEY, LANGSMITH_API_KEY, etc.
+        Returns None if no provider is detected.
+        """
+        import os
+        
+        # Check for common provider env vars
+        provider_env_map = {
+            "LANGFUSE_PUBLIC_KEY": "langfuse",
+            "LANGSMITH_API_KEY": "langsmith",
+            "AGENTOPS_API_KEY": "agentops",
+            "ARIZE_API_KEY": "arize",
+            "DATADOG_API_KEY": "datadog",
+            "MLFLOW_TRACKING_URI": "mlflow",
+            "OPENLIT_API_KEY": "openlit",
+            "OPIK_API_KEY": "opik",
+            "PORTKEY_API_KEY": "portkey",
+            "TRACELOOP_API_KEY": "traceloop",
+            "WANDB_API_KEY": "weave",
+            "BRAINTRUST_API_KEY": "braintrust",
+        }
+        
+        for env_var, provider in provider_env_map.items():
+            if os.getenv(env_var):
+                return self._create_provider_factory(provider)(**kwargs)
+        
+        return None
+    
+    def __repr__(self):
+        return "<module 'praisonaiagents.obs' (lazy observability backends)>"
+    
+    def __call__(self, provider: str = "auto", **kwargs):
+        """
+        Shortcut: obs("langfuse") or obs() for auto-detection.
+        """
+        if provider == "auto":
+            return self.auto(**kwargs)
+        return self._create_provider_factory(provider)(**kwargs)
+
+
+# Singleton lazy module instance
+obs = _LazyObsModule()
+
+
+__all__ = [
+    "ObservabilityAdapter",
+    "Span",
+    "Trace",
+    "obs",
+]
@@ -0,0 +1,77 @@
+"""
+Exec Policy Engine for PraisonAI Agents.
+
+Provides policy-based execution control:
+- Define rules for what agents can/cannot do
+- Tool execution policies
+- Resource access control
+- Rate limiting and quotas
+
+Zero Performance Impact:
+- All imports are lazy loaded via __getattr__
+- Policies only evaluated when enabled
+- No overhead when no policies defined
+
+Usage:
+    from praisonaiagents.policy import PolicyEngine, Policy, PolicyRule
+    
+    # Create a policy engine
+    engine = PolicyEngine()
+    
+    # Add a policy
+    policy = Policy(
+        name="no_delete",
+        rules=[
+            PolicyRule(
+                action="deny",
+                resource="tool:delete_*",
+                reason="Delete operations are not allowed"
+            )
+        ]
+    )
+    engine.add_policy(policy)
+    
+    # Check if action is allowed
+    result = engine.check("tool:delete_file", context={})
+"""
+
+__all__ = [
+    # Core classes
+    "PolicyEngine",
+    "Policy",
+    "PolicyRule",
+    # Result types
+    "PolicyResult",
+    "PolicyAction",
+    # Configuration
+    "PolicyConfig",
+    # Convenience functions
+    "create_deny_tools_policy",
+    "create_allow_tools_policy",
+    "create_read_only_policy",
+]
+
+
+def __getattr__(name: str):
+    """Lazy load module components to avoid import overhead."""
+    if name == "PolicyEngine":
+        from .engine import PolicyEngine
+        return PolicyEngine
+    
+    if name in ("Policy", "PolicyRule"):
+        from .policy import Policy, PolicyRule
+        return locals()[name]
+    
+    if name in ("PolicyResult", "PolicyAction"):
+        from .types import PolicyResult, PolicyAction
+        return locals()[name]
+    
+    if name == "PolicyConfig":
+        from .config import PolicyConfig
+        return PolicyConfig
+    
+    if name in ("create_deny_tools_policy", "create_allow_tools_policy", "create_read_only_policy"):
+        from .engine import create_deny_tools_policy, create_allow_tools_policy, create_read_only_policy
+        return locals()[name]
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -0,0 +1,15 @@
+"""
+Policy Configuration for PraisonAI Agents.
+"""
+
+from dataclasses import dataclass, field
+from typing import Optional, List
+
+
+@dataclass
+class PolicyConfig:
+    """Configuration for the policy engine."""
+    enabled: bool = True
+    default_action: str = "allow"  # Default action when no policy matches
+    log_decisions: bool = True
+    strict_mode: bool = False  # If True, deny when no policy matches
@@ -0,0 +1,307 @@
+"""
+Policy Engine for PraisonAI Agents.
+
+Manages and evaluates policies for execution control.
+"""
+
+import logging
+from typing import Optional, List, Dict, Any
+
+from .types import PolicyAction, PolicyResult
+from .policy import Policy, PolicyRule
+from .config import PolicyConfig
+
+logger = logging.getLogger(__name__)
+
+
+class PolicyEngine:
+    """
+    Policy Engine for execution control.
+    
+    Manages policies and evaluates them against resources
+    to determine what actions are allowed.
+    
+    Example:
+        engine = PolicyEngine()
+        
+        # Add a policy to block delete operations
+        engine.add_policy(Policy(
+            name="no_delete",
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.DENY,
+                    resource="tool:delete_*",
+                    reason="Delete operations are not allowed"
+                )
+            ]
+        ))
+        
+        # Check if action is allowed
+        result = engine.check("tool:delete_file", {})
+        if not result.allowed:
+            print(f"Denied: {result.reason}")
+    """
+    
+    def __init__(self, config: Optional[PolicyConfig] = None):
+        """
+        Initialize the policy engine.
+        
+        Args:
+            config: Engine configuration
+        """
+        self.config = config or PolicyConfig()
+        self._policies: Dict[str, Policy] = {}
+    
+    @property
+    def policies(self) -> List[Policy]:
+        """Get all policies sorted by priority."""
+        return sorted(
+            self._policies.values(),
+            key=lambda p: p.priority,
+            reverse=True
+        )
+    
+    def add_policy(self, policy: Policy):
+        """
+        Add a policy to the engine.
+        
+        Args:
+            policy: Policy to add
+        """
+        self._policies[policy.name] = policy
+        logger.debug(f"Added policy: {policy.name}")
+    
+    def remove_policy(self, name: str) -> bool:
+        """
+        Remove a policy by name.
+        
+        Args:
+            name: Policy name
+            
+        Returns:
+            True if removed, False if not found
+        """
+        if name in self._policies:
+            del self._policies[name]
+            logger.debug(f"Removed policy: {name}")
+            return True
+        return False
+    
+    def get_policy(self, name: str) -> Optional[Policy]:
+        """Get a policy by name."""
+        return self._policies.get(name)
+    
+    def enable_policy(self, name: str) -> bool:
+        """Enable a policy."""
+        policy = self._policies.get(name)
+        if policy:
+            policy.enabled = True
+            return True
+        return False
+    
+    def disable_policy(self, name: str) -> bool:
+        """Disable a policy."""
+        policy = self._policies.get(name)
+        if policy:
+            policy.enabled = False
+            return True
+        return False
+    
+    def check(
+        self,
+        resource: str,
+        context: Optional[Dict[str, Any]] = None
+    ) -> PolicyResult:
+        """
+        Check if an action is allowed.
+        
+        Args:
+            resource: Resource identifier (e.g., "tool:read_file")
+            context: Additional context for policy evaluation
+            
+        Returns:
+            PolicyResult indicating if action is allowed
+        """
+        if not self.config.enabled:
+            return PolicyResult.allow("Policy engine disabled")
+        
+        context = context or {}
+        
+        # Evaluate policies in priority order
+        for policy in self.policies:
+            result = policy.evaluate(resource, context)
+            if result is not None:
+                if self.config.log_decisions:
+                    logger.info(
+                        f"Policy decision: {result.action.value} for {resource} "
+                        f"(policy: {result.policy_name}, reason: {result.reason})"
+                    )
+                return result
+        
+        # No policy matched - use default action
+        if self.config.strict_mode:
+            return PolicyResult.deny(
+                "No policy matched and strict mode is enabled"
+            )
+        
+        return PolicyResult.allow("No policy matched")
+    
+    def check_tool(
+        self,
+        tool_name: str,
+        tool_input: Optional[Dict[str, Any]] = None
+    ) -> PolicyResult:
+        """
+        Check if a tool execution is allowed.
+        
+        Args:
+            tool_name: Name of the tool
+            tool_input: Tool input parameters
+            
+        Returns:
+            PolicyResult
+        """
+        return self.check(
+            f"tool:{tool_name}",
+            {"tool_name": tool_name, "tool_input": tool_input or {}}
+        )
+    
+    def check_file(
+        self,
+        operation: str,
+        file_path: str
+    ) -> PolicyResult:
+        """
+        Check if a file operation is allowed.
+        
+        Args:
+            operation: Operation type (read, write, delete)
+            file_path: Path to the file
+            
+        Returns:
+            PolicyResult
+        """
+        return self.check(
+            f"file:{operation}",
+            {"operation": operation, "file_path": file_path}
+        )
+    
+    def clear(self):
+        """Remove all policies."""
+        self._policies.clear()
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert engine state to dictionary."""
+        return {
+            "config": {
+                "enabled": self.config.enabled,
+                "default_action": self.config.default_action,
+                "strict_mode": self.config.strict_mode
+            },
+            "policies": [p.to_dict() for p in self.policies]
+        }
+    
+    def load_from_dict(self, data: Dict[str, Any]):
+        """Load policies from a dictionary."""
+        for policy_data in data.get("policies", []):
+            policy = Policy.from_dict(policy_data)
+            self.add_policy(policy)
+
+
+# Convenience functions for common policies
+
+def create_deny_tools_policy(
+    tool_patterns: List[str],
+    name: str = "deny_tools",
+    reason: str = "Tool not allowed"
+) -> Policy:
+    """
+    Create a policy that denies specific tools.
+    
+    Args:
+        tool_patterns: List of tool name patterns to deny
+        name: Policy name
+        reason: Reason for denial
+        
+    Returns:
+        Policy
+    """
+    rules = [
+        PolicyRule(
+            action=PolicyAction.DENY,
+            resource=f"tool:{pattern}",
+            reason=reason,
+            name=f"deny_{pattern}"
+        )
+        for pattern in tool_patterns
+    ]
+    
+    return Policy(name=name, rules=rules)
+
+
+def create_allow_tools_policy(
+    tool_patterns: List[str],
+    name: str = "allow_tools"
+) -> Policy:
+    """
+    Create a policy that allows specific tools.
+    
+    Args:
+        tool_patterns: List of tool name patterns to allow
+        name: Policy name
+        
+    Returns:
+        Policy
+    """
+    rules = [
+        PolicyRule(
+            action=PolicyAction.ALLOW,
+            resource=f"tool:{pattern}",
+            name=f"allow_{pattern}"
+        )
+        for pattern in tool_patterns
+    ]
+    
+    return Policy(name=name, rules=rules, priority=10)
+
+
+def create_read_only_policy(name: str = "read_only") -> Policy:
+    """
+    Create a read-only policy that denies write operations.
+    
+    Args:
+        name: Policy name
+        
+    Returns:
+        Policy
+    """
+    return Policy(
+        name=name,
+        rules=[
+            PolicyRule(
+                action=PolicyAction.DENY,
+                resource="file:write",
+                reason="Write operations not allowed in read-only mode",
+                name="deny_write"
+            ),
+            PolicyRule(
+                action=PolicyAction.DENY,
+                resource="file:delete",
+                reason="Delete operations not allowed in read-only mode",
+                name="deny_delete"
+            ),
+            PolicyRule(
+                action=PolicyAction.DENY,
+                resource="tool:*_write*",
+                reason="Write tools not allowed in read-only mode",
+                name="deny_write_tools"
+            ),
+            PolicyRule(
+                action=PolicyAction.DENY,
+                resource="tool:*_delete*",
+                reason="Delete tools not allowed in read-only mode",
+                name="deny_delete_tools"
+            ),
+        ],
+        priority=100
+    )
@@ -0,0 +1,174 @@
+"""
+Policy and PolicyRule for PraisonAI Agents.
+
+Defines policies and rules for execution control.
+"""
+
+import re
+import fnmatch
+from dataclasses import dataclass, field
+from typing import Optional, Dict, Any, List, Callable
+
+from .types import PolicyAction, PolicyResult
+
+
+@dataclass
+class PolicyRule:
+    """
+    A single rule within a policy.
+    
+    Rules match against resources and contexts to determine
+    what action to take.
+    """
+    action: PolicyAction
+    resource: Optional[str] = None  # Pattern to match (supports wildcards)
+    condition: Optional[Callable[[Dict[str, Any]], bool]] = None
+    reason: Optional[str] = None
+    name: Optional[str] = None
+    priority: int = 0  # Higher priority rules are evaluated first
+    
+    def matches(self, resource: str, context: Dict[str, Any]) -> bool:
+        """
+        Check if this rule matches the given resource and context.
+        
+        Args:
+            resource: Resource identifier (e.g., "tool:read_file")
+            context: Additional context for the check
+            
+        Returns:
+            True if the rule matches
+        """
+        # Check resource pattern
+        if self.resource:
+            if not self._match_pattern(self.resource, resource):
+                return False
+        
+        # Check condition
+        if self.condition:
+            try:
+                if not self.condition(context):
+                    return False
+            except Exception:
+                return False
+        
+        return True
+    
+    def _match_pattern(self, pattern: str, value: str) -> bool:
+        """Match a pattern against a value (supports wildcards)."""
+        # Convert glob pattern to regex
+        if "*" in pattern or "?" in pattern:
+            return fnmatch.fnmatch(value, pattern)
+        return pattern == value
+    
+    def evaluate(self, resource: str, context: Dict[str, Any]) -> Optional[PolicyResult]:
+        """
+        Evaluate this rule against a resource.
+        
+        Args:
+            resource: Resource identifier
+            context: Additional context
+            
+        Returns:
+            PolicyResult if rule matches, None otherwise
+        """
+        if not self.matches(resource, context):
+            return None
+        
+        return PolicyResult(
+            allowed=self.action in (PolicyAction.ALLOW, PolicyAction.LOG),
+            action=self.action,
+            rule_name=self.name,
+            reason=self.reason
+        )
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "action": self.action.value,
+            "resource": self.resource,
+            "reason": self.reason,
+            "name": self.name,
+            "priority": self.priority
+        }
+
+
+@dataclass
+class Policy:
+    """
+    A collection of rules that define execution policy.
+    
+    Policies are evaluated in order, with higher priority rules
+    taking precedence.
+    """
+    name: str
+    rules: List[PolicyRule] = field(default_factory=list)
+    description: Optional[str] = None
+    enabled: bool = True
+    priority: int = 0  # Higher priority policies are evaluated first
+    
+    def add_rule(self, rule: PolicyRule):
+        """Add a rule to this policy."""
+        self.rules.append(rule)
+        # Sort by priority (descending)
+        self.rules.sort(key=lambda r: r.priority, reverse=True)
+    
+    def remove_rule(self, rule_name: str) -> bool:
+        """Remove a rule by name."""
+        for i, rule in enumerate(self.rules):
+            if rule.name == rule_name:
+                self.rules.pop(i)
+                return True
+        return False
+    
+    def evaluate(self, resource: str, context: Dict[str, Any]) -> Optional[PolicyResult]:
+        """
+        Evaluate this policy against a resource.
+        
+        Args:
+            resource: Resource identifier
+            context: Additional context
+            
+        Returns:
+            PolicyResult if any rule matches, None otherwise
+        """
+        if not self.enabled:
+            return None
+        
+        for rule in self.rules:
+            result = rule.evaluate(resource, context)
+            if result is not None:
+                result.policy_name = self.name
+                return result
+        
+        return None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "name": self.name,
+            "description": self.description,
+            "enabled": self.enabled,
+            "priority": self.priority,
+            "rules": [r.to_dict() for r in self.rules]
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "Policy":
+        """Create a policy from a dictionary."""
+        rules = []
+        for rule_data in data.get("rules", []):
+            rules.append(PolicyRule(
+                action=PolicyAction(rule_data["action"]),
+                resource=rule_data.get("resource"),
+                reason=rule_data.get("reason"),
+                name=rule_data.get("name"),
+                priority=rule_data.get("priority", 0)
+            ))
+        
+        return cls(
+            name=data["name"],
+            rules=rules,
+            description=data.get("description"),
+            enabled=data.get("enabled", True),
+            priority=data.get("priority", 0)
+        )
@@ -0,0 +1,60 @@
+"""
+Policy Types for PraisonAI Agents.
+
+Defines the core types for the policy engine.
+"""
+
+from enum import Enum
+from dataclasses import dataclass, field
+from typing import Optional, Dict, Any, List
+
+
+class PolicyAction(str, Enum):
+    """Action to take when a policy matches."""
+    ALLOW = "allow"
+    DENY = "deny"
+    ASK = "ask"  # Require user confirmation
+    LOG = "log"  # Allow but log the action
+    RATE_LIMIT = "rate_limit"
+
+
+@dataclass
+class PolicyResult:
+    """Result of a policy check."""
+    allowed: bool
+    action: PolicyAction
+    policy_name: Optional[str] = None
+    rule_name: Optional[str] = None
+    reason: Optional[str] = None
+    metadata: Dict[str, Any] = field(default_factory=dict)
+    
+    @classmethod
+    def allow(cls, reason: Optional[str] = None) -> "PolicyResult":
+        """Create an allow result."""
+        return cls(allowed=True, action=PolicyAction.ALLOW, reason=reason)
+    
+    @classmethod
+    def deny(cls, reason: str, policy_name: Optional[str] = None) -> "PolicyResult":
+        """Create a deny result."""
+        return cls(
+            allowed=False,
+            action=PolicyAction.DENY,
+            policy_name=policy_name,
+            reason=reason
+        )
+    
+    @classmethod
+    def ask(cls, reason: str) -> "PolicyResult":
+        """Create an ask result (requires confirmation)."""
+        return cls(allowed=False, action=PolicyAction.ASK, reason=reason)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "allowed": self.allowed,
+            "action": self.action.value,
+            "policy_name": self.policy_name,
+            "rule_name": self.rule_name,
+            "reason": self.reason,
+            "metadata": self.metadata
+        }
@@ -28,20 +28,31 @@ def format_skill_for_prompt(skill: SkillMetadata) -> str:
  </skill>"""


-def generate_skills_xml(skills: List[SkillMetadata]) -> str:
+def generate_skills_xml(skills: List[SkillMetadata], working_directory: str = None) -> str:
    """Generate XML block for available skills.

    Args:
        skills: List of SkillMetadata instances
+        working_directory: Current working directory for path resolution

    Returns:
        XML string with <available_skills> block
    """
+    import os
+    cwd = working_directory or os.getcwd()
+    
    if not skills:
-        return "<available_skills>\n</available_skills>"
+        return f"""<available_skills>
+  <working_directory>{html.escape(cwd)}</working_directory>
+  <note>When using run_skill_script, pass file paths relative to the working directory or as absolute paths. The tool will resolve relative paths automatically.</note>
+</available_skills>"""

    skill_entries = "\n".join(format_skill_for_prompt(s) for s in skills)
-    return f"<available_skills>\n{skill_entries}\n</available_skills>"
+    return f"""<available_skills>
+  <working_directory>{html.escape(cwd)}</working_directory>
+  <note>When using run_skill_script, pass file paths relative to the working directory or as absolute paths. The tool will resolve relative paths automatically.</note>
+{skill_entries}
+</available_skills>"""


 def to_prompt(skill_dirs: List[Path]) -> str:
@@ -0,0 +1,60 @@
+"""
+Extended Thinking Budgets Module for PraisonAI Agents.
+
+Provides configurable thinking budgets for LLM reasoning:
+- Token budgets for extended thinking
+- Time budgets for reasoning
+- Adaptive budget allocation
+- Budget tracking and reporting
+
+Zero Performance Impact:
+- All imports are lazy loaded via __getattr__
+- Budgets only applied when configured
+- No overhead when not in use
+
+Usage:
+    from praisonaiagents.thinking import ThinkingBudget, ThinkingConfig
+    
+    # Create a thinking budget
+    budget = ThinkingBudget(
+        max_tokens=16000,
+        max_time_seconds=60,
+        adaptive=True
+    )
+    
+    # Apply to agent
+    agent = Agent(
+        instructions="...",
+        thinking_budget=budget
+    )
+"""
+
+__all__ = [
+    # Core classes
+    "ThinkingBudget",
+    "ThinkingConfig",
+    # Tracking
+    "ThinkingUsage",
+    "ThinkingTracker",
+]
+
+
+def __getattr__(name: str):
+    """Lazy load module components to avoid import overhead."""
+    if name == "ThinkingBudget":
+        from .budget import ThinkingBudget
+        return ThinkingBudget
+    
+    if name == "ThinkingConfig":
+        from .config import ThinkingConfig
+        return ThinkingConfig
+    
+    if name == "ThinkingUsage":
+        from .tracker import ThinkingUsage
+        return ThinkingUsage
+    
+    if name == "ThinkingTracker":
+        from .tracker import ThinkingTracker
+        return ThinkingTracker
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@@ -0,0 +1,131 @@
+"""
+Thinking Budget for PraisonAI Agents.
+
+Defines budget constraints for extended thinking.
+"""
+
+from dataclasses import dataclass, field
+from typing import Optional, Dict, Any
+from enum import Enum
+
+
+class BudgetLevel(str, Enum):
+    """Predefined budget levels."""
+    MINIMAL = "minimal"      # 2000 tokens
+    LOW = "low"              # 4000 tokens
+    MEDIUM = "medium"        # 8000 tokens
+    HIGH = "high"            # 16000 tokens
+    MAXIMUM = "maximum"      # 32000 tokens
+
+
+# Token allocations for each level
+BUDGET_TOKENS = {
+    BudgetLevel.MINIMAL: 2000,
+    BudgetLevel.LOW: 4000,
+    BudgetLevel.MEDIUM: 8000,
+    BudgetLevel.HIGH: 16000,
+    BudgetLevel.MAXIMUM: 32000,
+}
+
+
+@dataclass
+class ThinkingBudget:
+    """
+    Budget constraints for extended thinking.
+    
+    Controls how much thinking/reasoning the LLM can do
+    before producing a response.
+    """
+    max_tokens: int = 8000
+    max_time_seconds: Optional[float] = None
+    adaptive: bool = True
+    level: Optional[BudgetLevel] = None
+    
+    # Adaptive settings
+    min_tokens: int = 1000
+    complexity_multiplier: float = 1.0
+    
+    def __post_init__(self):
+        # If level is specified, use its token allocation
+        if self.level:
+            self.max_tokens = BUDGET_TOKENS.get(self.level, self.max_tokens)
+    
+    @classmethod
+    def from_level(cls, level: BudgetLevel, **kwargs) -> "ThinkingBudget":
+        """Create a budget from a predefined level."""
+        return cls(
+            max_tokens=BUDGET_TOKENS[level],
+            level=level,
+            **kwargs
+        )
+    
+    @classmethod
+    def minimal(cls) -> "ThinkingBudget":
+        """Create a minimal budget."""
+        return cls.from_level(BudgetLevel.MINIMAL)
+    
+    @classmethod
+    def low(cls) -> "ThinkingBudget":
+        """Create a low budget."""
+        return cls.from_level(BudgetLevel.LOW)
+    
+    @classmethod
+    def medium(cls) -> "ThinkingBudget":
+        """Create a medium budget."""
+        return cls.from_level(BudgetLevel.MEDIUM)
+    
+    @classmethod
+    def high(cls) -> "ThinkingBudget":
+        """Create a high budget."""
+        return cls.from_level(BudgetLevel.HIGH)
+    
+    @classmethod
+    def maximum(cls) -> "ThinkingBudget":
+        """Create a maximum budget."""
+        return cls.from_level(BudgetLevel.MAXIMUM)
+    
+    def get_tokens_for_complexity(self, complexity: float) -> int:
+        """
+        Get token budget based on task complexity.
+        
+        Args:
+            complexity: Complexity score (0.0 to 1.0)
+            
+        Returns:
+            Adjusted token budget
+        """
+        if not self.adaptive:
+            return self.max_tokens
+        
+        # Scale between min and max based on complexity
+        range_tokens = self.max_tokens - self.min_tokens
+        adjusted = self.min_tokens + int(range_tokens * complexity * self.complexity_multiplier)
+        
+        return min(adjusted, self.max_tokens)
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "max_tokens": self.max_tokens,
+            "max_time_seconds": self.max_time_seconds,
+            "adaptive": self.adaptive,
+            "level": self.level.value if self.level else None,
+            "min_tokens": self.min_tokens,
+            "complexity_multiplier": self.complexity_multiplier
+        }
+    
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "ThinkingBudget":
+        """Create from dictionary."""
+        level = None
+        if data.get("level"):
+            level = BudgetLevel(data["level"])
+        
+        return cls(
+            max_tokens=data.get("max_tokens", 8000),
+            max_time_seconds=data.get("max_time_seconds"),
+            adaptive=data.get("adaptive", True),
+            level=level,
+            min_tokens=data.get("min_tokens", 1000),
+            complexity_multiplier=data.get("complexity_multiplier", 1.0)
+        )
@@ -0,0 +1,17 @@
+"""
+Thinking Configuration for PraisonAI Agents.
+"""
+
+from dataclasses import dataclass
+from typing import Optional
+
+
+@dataclass
+class ThinkingConfig:
+    """Configuration for extended thinking."""
+    enabled: bool = True
+    default_budget_tokens: int = 8000
+    max_budget_tokens: int = 32000
+    default_time_seconds: Optional[float] = None
+    adaptive: bool = True  # Adjust budget based on task complexity
+    log_thinking: bool = False  # Log thinking process
@@ -0,0 +1,173 @@
+"""
+Thinking Tracker for PraisonAI Agents.
+
+Tracks thinking usage and provides reporting.
+"""
+
+from dataclasses import dataclass, field
+from typing import Optional, Dict, Any, List
+from datetime import datetime
+
+
+@dataclass
+class ThinkingUsage:
+    """Usage statistics for a single thinking session."""
+    tokens_used: int = 0
+    time_seconds: float = 0.0
+    budget_tokens: int = 0
+    budget_time: Optional[float] = None
+    complexity: float = 0.5
+    started_at: Optional[datetime] = None
+    ended_at: Optional[datetime] = None
+    
+    @property
+    def tokens_remaining(self) -> int:
+        """Get remaining token budget."""
+        return max(0, self.budget_tokens - self.tokens_used)
+    
+    @property
+    def time_remaining(self) -> Optional[float]:
+        """Get remaining time budget."""
+        if self.budget_time is None:
+            return None
+        return max(0.0, self.budget_time - self.time_seconds)
+    
+    @property
+    def token_utilization(self) -> float:
+        """Get token utilization percentage."""
+        if self.budget_tokens == 0:
+            return 0.0
+        return self.tokens_used / self.budget_tokens
+    
+    @property
+    def is_over_budget(self) -> bool:
+        """Check if over token budget."""
+        return self.tokens_used > self.budget_tokens
+    
+    @property
+    def is_over_time(self) -> bool:
+        """Check if over time budget."""
+        if self.budget_time is None:
+            return False
+        return self.time_seconds > self.budget_time
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert to dictionary."""
+        return {
+            "tokens_used": self.tokens_used,
+            "time_seconds": self.time_seconds,
+            "budget_tokens": self.budget_tokens,
+            "budget_time": self.budget_time,
+            "complexity": self.complexity,
+            "tokens_remaining": self.tokens_remaining,
+            "token_utilization": self.token_utilization,
+            "is_over_budget": self.is_over_budget
+        }
+
+
+@dataclass
+class ThinkingTracker:
+    """
+    Tracks thinking usage across multiple sessions.
+    
+    Provides aggregate statistics and reporting.
+    """
+    sessions: List[ThinkingUsage] = field(default_factory=list)
+    total_tokens_used: int = 0
+    total_time_seconds: float = 0.0
+    
+    def start_session(
+        self,
+        budget_tokens: int,
+        budget_time: Optional[float] = None,
+        complexity: float = 0.5
+    ) -> ThinkingUsage:
+        """
+        Start a new thinking session.
+        
+        Args:
+            budget_tokens: Token budget for this session
+            budget_time: Optional time budget
+            complexity: Task complexity (0.0 to 1.0)
+            
+        Returns:
+            ThinkingUsage for tracking
+        """
+        usage = ThinkingUsage(
+            budget_tokens=budget_tokens,
+            budget_time=budget_time,
+            complexity=complexity,
+            started_at=datetime.now()
+        )
+        self.sessions.append(usage)
+        return usage
+    
+    def end_session(
+        self,
+        usage: ThinkingUsage,
+        tokens_used: int,
+        time_seconds: float
+    ):
+        """
+        End a thinking session.
+        
+        Args:
+            usage: The usage object from start_session
+            tokens_used: Actual tokens used
+            time_seconds: Actual time taken
+        """
+        usage.tokens_used = tokens_used
+        usage.time_seconds = time_seconds
+        usage.ended_at = datetime.now()
+        
+        self.total_tokens_used += tokens_used
+        self.total_time_seconds += time_seconds
+    
+    @property
+    def session_count(self) -> int:
+        """Get number of sessions."""
+        return len(self.sessions)
+    
+    @property
+    def average_tokens_per_session(self) -> float:
+        """Get average tokens per session."""
+        if not self.sessions:
+            return 0.0
+        return self.total_tokens_used / len(self.sessions)
+    
+    @property
+    def average_time_per_session(self) -> float:
+        """Get average time per session."""
+        if not self.sessions:
+            return 0.0
+        return self.total_time_seconds / len(self.sessions)
+    
+    @property
+    def average_utilization(self) -> float:
+        """Get average budget utilization."""
+        if not self.sessions:
+            return 0.0
+        return sum(s.token_utilization for s in self.sessions) / len(self.sessions)
+    
+    @property
+    def over_budget_count(self) -> int:
+        """Get number of sessions that went over budget."""
+        return sum(1 for s in self.sessions if s.is_over_budget)
+    
+    def get_summary(self) -> Dict[str, Any]:
+        """Get summary statistics."""
+        return {
+            "session_count": self.session_count,
+            "total_tokens_used": self.total_tokens_used,
+            "total_time_seconds": self.total_time_seconds,
+            "average_tokens_per_session": self.average_tokens_per_session,
+            "average_time_per_session": self.average_time_per_session,
+            "average_utilization": self.average_utilization,
+            "over_budget_count": self.over_budget_count
+        }
+    
+    def clear(self):
+        """Clear all tracking data."""
+        self.sessions.clear()
+        self.total_tokens_used = 0
+        self.total_time_seconds = 0.0
@@ -222,6 +222,14 @@ TOOL_MAPPINGS = {
    # Unified Web Search (auto-fallback across providers)
    'search_web': ('.web_search', None),
    'get_available_providers': ('.web_search', None),
+    
+    # Skill Tools (for Agent Skills script execution)
+    'run_skill_script': ('.skill_tools', None),
+    'read_skill_file': ('.skill_tools', None),
+    'list_skill_scripts': ('.skill_tools', None),
+    'create_skill_tools': ('.skill_tools', None),
+    'SkillTools': ('.skill_tools', 'SkillTools'),
+    'skill_tools': ('.skill_tools', None),
 }

 _instances = {}  # Cache for class instances
@@ -259,11 +267,12 @@ def __getattr__(name: str) -> Any:
            'exa_search_async', 'exa_search_contents_async', 'exa_answer_async',
            'crawl4ai', 'crawl4ai_many', 'crawl4ai_extract', 'crawl4ai_llm_extract',
            'crawl4ai_sync', 'crawl4ai_extract_sync',
-            'search_web', 'get_available_providers'
+            'search_web', 'get_available_providers',
+            'run_skill_script', 'read_skill_file', 'list_skill_scripts', 'create_skill_tools'
        ]:
            return getattr(module, name)
        if name in ['file_tools', 'pandas_tools', 'wikipedia_tools',
-                   'newspaper_tools', 'arxiv_tools', 'spider_tools', 'duckdb_tools', 'mongodb_tools', 'csv_tools', 'json_tools', 'excel_tools', 'xml_tools', 'yaml_tools', 'calculator_tools', 'python_tools', 'shell_tools', 'cot_tools', 'tavily_tools', 'youdotcom_tools', 'exa_tools', 'crawl4ai_tools']:
+                   'newspaper_tools', 'arxiv_tools', 'spider_tools', 'duckdb_tools', 'mongodb_tools', 'csv_tools', 'json_tools', 'excel_tools', 'xml_tools', 'yaml_tools', 'calculator_tools', 'python_tools', 'shell_tools', 'cot_tools', 'tavily_tools', 'youdotcom_tools', 'exa_tools', 'crawl4ai_tools', 'skill_tools']:
            return module  # Returns the callable module
        return getattr(module, name)
    else:
@@ -0,0 +1,280 @@
+"""Tools for executing Agent Skills scripts.
+
+This module provides tools for running scripts bundled with Agent Skills.
+Skills are modular packages that extend agent capabilities through SKILL.md
+files and optional scripts.
+
+Usage:
+    from praisonaiagents.tools import run_skill_script
+    result = run_skill_script("./my-skill/scripts/skill.py", "./data.csv")
+"""
+
+import subprocess
+import os
+import logging
+
+
+class SkillTools:
+    """Tools for executing Agent Skills scripts."""
+    
+    def __init__(self, working_directory: str = None):
+        """Initialize SkillTools.
+        
+        Args:
+            working_directory: Base directory for resolving relative paths.
+                              Defaults to current working directory.
+        """
+        self._working_directory = working_directory or os.getcwd()
+    
+    @property
+    def working_directory(self) -> str:
+        """Get the working directory for path resolution."""
+        return self._working_directory
+    
+    @working_directory.setter
+    def working_directory(self, value: str):
+        """Set the working directory for path resolution."""
+        self._working_directory = value
+    
+    def run_skill_script(
+        self,
+        script_path: str,
+        args: str = "",
+        timeout: int = 60
+    ) -> str:
+        """
+        Execute a skill script from a skill's scripts/ directory.
+        
+        Args:
+            script_path: Path to the script file (e.g., ./csv-analyzer/scripts/skill.py)
+            args: Arguments to pass to the script (e.g., file path to analyze)
+            timeout: Maximum execution time in seconds (default: 60)
+            
+        Returns:
+            The output from running the script, or error message if failed
+        """
+        try:
+            # Resolve the script path
+            script_path = os.path.expanduser(script_path)
+            if not os.path.isabs(script_path):
+                script_path = os.path.join(self._working_directory, script_path)
+            script_path = os.path.abspath(script_path)
+            
+            if not os.path.exists(script_path):
+                return f"Error: Script not found at {script_path}"
+            
+            # Resolve args paths relative to working directory
+            resolved_args = []
+            if args:
+                for arg in args.split():
+                    # Skip flags
+                    if arg.startswith('-'):
+                        resolved_args.append(arg)
+                        continue
+                    
+                    # Try to resolve as a path relative to working directory
+                    potential_path = os.path.join(self._working_directory, arg)
+                    if os.path.exists(potential_path):
+                        resolved_args.append(os.path.abspath(potential_path))
+                    elif os.path.isabs(arg) and os.path.exists(arg):
+                        # Already absolute and exists
+                        resolved_args.append(arg)
+                    else:
+                        # Keep original arg if path doesn't exist
+                        resolved_args.append(arg)
+            
+            # Determine how to run the script based on extension
+            ext = os.path.splitext(script_path)[1].lower()
+            
+            if ext == '.py':
+                cmd = ['python', script_path] + resolved_args
+            elif ext == '.sh':
+                cmd = ['bash', script_path] + resolved_args
+            elif ext == '.js':
+                cmd = ['node', script_path] + resolved_args
+            else:
+                # Try to run directly
+                cmd = [script_path] + resolved_args
+            
+            logging.debug(f"Running skill script: {' '.join(cmd)}")
+            
+            result = subprocess.run(
+                cmd,
+                capture_output=True,
+                text=True,
+                timeout=timeout,
+                cwd=self._working_directory
+            )
+            
+            output = result.stdout
+            if result.stderr:
+                output += f"\nStderr: {result.stderr}"
+            if result.returncode != 0:
+                output += f"\nExit code: {result.returncode}"
+            
+            return output if output else "Script executed successfully (no output)"
+            
+        except subprocess.TimeoutExpired:
+            return f"Error: Script execution timed out after {timeout} seconds"
+        except FileNotFoundError as e:
+            return f"Error: Could not find interpreter or script: {str(e)}"
+        except PermissionError as e:
+            return f"Error: Permission denied: {str(e)}"
+        except Exception as e:
+            return f"Error executing script: {str(e)}"
+    
+    def read_skill_file(
+        self,
+        skill_path: str,
+        file_path: str,
+        encoding: str = 'utf-8'
+    ) -> str:
+        """
+        Read a file from a skill directory.
+        
+        Args:
+            skill_path: Path to the skill directory (e.g., ./csv-analyzer)
+            file_path: Relative path within the skill (e.g., SKILL.md, scripts/skill.py)
+            encoding: File encoding (default: utf-8)
+            
+        Returns:
+            File contents or error message
+        """
+        try:
+            # Resolve skill path
+            skill_path = os.path.expanduser(skill_path)
+            if not os.path.isabs(skill_path):
+                skill_path = os.path.join(self._working_directory, skill_path)
+            skill_path = os.path.abspath(skill_path)
+            
+            if not os.path.exists(skill_path):
+                return f"Error: Skill directory not found at {skill_path}"
+            
+            if not os.path.isdir(skill_path):
+                return f"Error: {skill_path} is not a directory"
+            
+            # Resolve file path within skill
+            full_path = os.path.join(skill_path, file_path)
+            full_path = os.path.abspath(full_path)
+            
+            # Security check: ensure file is within skill directory
+            if not full_path.startswith(skill_path):
+                return f"Error: Path traversal detected - {file_path} is outside skill directory"
+            
+            if not os.path.exists(full_path):
+                return f"Error: File not found at {full_path}"
+            
+            with open(full_path, 'r', encoding=encoding) as f:
+                return f.read()
+                
+        except UnicodeDecodeError as e:
+            return f"Error: Could not decode file with {encoding} encoding: {str(e)}"
+        except PermissionError as e:
+            return f"Error: Permission denied reading file: {str(e)}"
+        except Exception as e:
+            return f"Error reading skill file: {str(e)}"
+    
+    def list_skill_scripts(self, skill_path: str) -> str:
+        """
+        List available scripts in a skill's scripts/ directory.
+        
+        Args:
+            skill_path: Path to the skill directory
+            
+        Returns:
+            JSON string with list of scripts or error message
+        """
+        import json
+        
+        try:
+            # Resolve skill path
+            skill_path = os.path.expanduser(skill_path)
+            if not os.path.isabs(skill_path):
+                skill_path = os.path.join(self._working_directory, skill_path)
+            skill_path = os.path.abspath(skill_path)
+            
+            if not os.path.exists(skill_path):
+                return f"Error: Skill directory not found at {skill_path}"
+            
+            scripts_dir = os.path.join(skill_path, "scripts")
+            if not os.path.exists(scripts_dir):
+                return json.dumps({"scripts": [], "message": "No scripts/ directory found"})
+            
+            scripts = []
+            for item in os.listdir(scripts_dir):
+                item_path = os.path.join(scripts_dir, item)
+                if os.path.isfile(item_path):
+                    ext = os.path.splitext(item)[1].lower()
+                    if ext in ['.py', '.sh', '.js', '.rb', '.pl']:
+                        scripts.append({
+                            "name": item,
+                            "path": os.path.join("scripts", item),
+                            "type": ext[1:]  # Remove the dot
+                        })
+            
+            return json.dumps({"scripts": scripts}, indent=2)
+            
+        except Exception as e:
+            return f"Error listing skill scripts: {str(e)}"
+
+
+# Create default instance for direct function access
+_skill_tools = SkillTools()
+
+def run_skill_script(script_path: str, args: str = "", timeout: int = 60) -> str:
+    """
+    Execute a skill script from a skill's scripts/ directory.
+    
+    Args:
+        script_path: Path to the script file (e.g., ./csv-analyzer/scripts/script.py)
+        args: Arguments to pass to the script (e.g., file path to analyze)
+        timeout: Maximum execution time in seconds (default: 60)
+        
+    Returns:
+        The output from running the script, or error message if failed
+    """
+    return _skill_tools.run_skill_script(script_path, args, timeout)
+
+
+def read_skill_file(skill_path: str, file_path: str, encoding: str = 'utf-8') -> str:
+    """
+    Read a file from a skill directory.
+    
+    Args:
+        skill_path: Path to the skill directory (e.g., ./csv-analyzer)
+        file_path: Relative path within the skill (e.g., SKILL.md, scripts/script.py)
+        encoding: File encoding (default: utf-8)
+        
+    Returns:
+        File contents or error message
+    """
+    return _skill_tools.read_skill_file(skill_path, file_path, encoding)
+
+
+def list_skill_scripts(skill_path: str) -> str:
+    """
+    List available scripts in a skill's scripts/ directory.
+    
+    Args:
+        skill_path: Path to the skill directory
+        
+    Returns:
+        JSON string with list of scripts or error message
+    """
+    return _skill_tools.list_skill_scripts(skill_path)
+
+
+def create_skill_tools(working_directory: str = None) -> SkillTools:
+    """
+    Create a SkillTools instance with a specific working directory.
+    
+    This is useful when you need to resolve paths relative to a specific
+    directory rather than the current working directory.
+    
+    Args:
+        working_directory: Base directory for resolving relative paths
+        
+    Returns:
+        SkillTools instance
+    """
+    return SkillTools(working_directory)
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"

 [project]
 name = "praisonaiagents"
-version = "0.1.24"
+version = "0.2.2"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 readme = "README.md"
 requires-python = ">=3.10"
@@ -0,0 +1 @@
+"""Unit tests for background module."""
@@ -0,0 +1,401 @@
+"""
+Unit tests for the Background module.
+
+Tests cover:
+- BackgroundTask creation and status management
+- BackgroundRunner task submission
+- Task cancellation and timeout
+- Concurrent execution
+"""
+
+import pytest
+import asyncio
+from datetime import datetime
+
+from praisonaiagents.background.task import BackgroundTask, TaskStatus
+from praisonaiagents.background.config import BackgroundConfig
+from praisonaiagents.background.runner import BackgroundRunner
+
+
+# =============================================================================
+# BackgroundTask Tests
+# =============================================================================
+
+class TestBackgroundTask:
+    """Tests for BackgroundTask class."""
+    
+    def test_task_creation(self):
+        """Test creating a task."""
+        task = BackgroundTask(name="test_task")
+        assert task.name == "test_task"
+        assert task.status == TaskStatus.PENDING
+        assert task.progress == 0.0
+        assert not task.is_running
+        assert not task.is_completed
+    
+    def test_task_start(self):
+        """Test starting a task."""
+        task = BackgroundTask(name="test")
+        task.start()
+        
+        assert task.status == TaskStatus.RUNNING
+        assert task.is_running
+        assert task.started_at is not None
+    
+    def test_task_complete(self):
+        """Test completing a task."""
+        task = BackgroundTask(name="test")
+        task.start()
+        task.complete(result="success")
+        
+        assert task.status == TaskStatus.COMPLETED
+        assert task.is_completed
+        assert task.is_successful
+        assert task.result == "success"
+        assert task.progress == 1.0
+        assert task.completed_at is not None
+    
+    def test_task_fail(self):
+        """Test failing a task."""
+        task = BackgroundTask(name="test")
+        task.start()
+        task.fail("Something went wrong")
+        
+        assert task.status == TaskStatus.FAILED
+        assert task.is_completed
+        assert not task.is_successful
+        assert task.error == "Something went wrong"
+    
+    def test_task_cancel(self):
+        """Test cancelling a task."""
+        task = BackgroundTask(name="test")
+        task.start()
+        task.cancel()
+        
+        assert task.status == TaskStatus.CANCELLED
+        assert task.is_completed
+        assert task.should_cancel()
+    
+    def test_task_progress(self):
+        """Test updating task progress."""
+        task = BackgroundTask(name="test")
+        task.start()
+        
+        task.update_progress(0.5, "Halfway done")
+        
+        assert task.progress == 0.5
+        assert task.metadata.get("last_message") == "Halfway done"
+    
+    def test_task_progress_bounds(self):
+        """Test that progress is bounded."""
+        task = BackgroundTask(name="test")
+        
+        task.update_progress(-0.5)
+        assert task.progress == 0.0
+        
+        task.update_progress(1.5)
+        assert task.progress == 1.0
+    
+    def test_task_duration(self):
+        """Test task duration calculation."""
+        task = BackgroundTask(name="test")
+        
+        assert task.duration_seconds is None
+        
+        task.start()
+        assert task.duration_seconds is not None
+        assert task.duration_seconds >= 0
+    
+    def test_task_to_dict(self):
+        """Test task serialization."""
+        task = BackgroundTask(name="test")
+        task.start()
+        task.complete("result")
+        
+        data = task.to_dict()
+        
+        assert data["name"] == "test"
+        assert data["status"] == "completed"
+        assert data["result"] == "result"
+        assert "created_at" in data
+        assert "started_at" in data
+        assert "completed_at" in data
+
+
+# =============================================================================
+# BackgroundConfig Tests
+# =============================================================================
+
+class TestBackgroundConfig:
+    """Tests for BackgroundConfig class."""
+    
+    def test_config_defaults(self):
+        """Test default configuration."""
+        config = BackgroundConfig()
+        
+        assert config.max_concurrent_tasks == 5
+        assert config.default_timeout is None
+        assert config.auto_cleanup
+        assert config.cleanup_delay == 300.0
+    
+    def test_config_custom(self):
+        """Test custom configuration."""
+        config = BackgroundConfig(
+            max_concurrent_tasks=10,
+            default_timeout=60.0,
+            auto_cleanup=False
+        )
+        
+        assert config.max_concurrent_tasks == 10
+        assert config.default_timeout == 60.0
+        assert not config.auto_cleanup
+
+
+# =============================================================================
+# BackgroundRunner Tests
+# =============================================================================
+
+class TestBackgroundRunner:
+    """Tests for BackgroundRunner class."""
+    
+    @pytest.fixture
+    def runner(self):
+        """Create a test runner."""
+        return BackgroundRunner()
+    
+    @pytest.mark.asyncio
+    async def test_submit_sync_function(self, runner):
+        """Test submitting a sync function."""
+        def sync_func(x):
+            return x * 2
+        
+        task = await runner.submit(func=sync_func, args=(5,), name="double")
+        result = await task.wait(timeout=5.0)
+        
+        assert result == 10
+        assert task.is_successful
+    
+    @pytest.mark.asyncio
+    async def test_submit_async_function(self, runner):
+        """Test submitting an async function."""
+        async def async_func(x):
+            await asyncio.sleep(0.1)
+            return x * 3
+        
+        task = await runner.submit(func=async_func, args=(5,), name="triple")
+        result = await task.wait(timeout=5.0)
+        
+        assert result == 15
+        assert task.is_successful
+    
+    @pytest.mark.asyncio
+    async def test_submit_with_kwargs(self, runner):
+        """Test submitting with keyword arguments."""
+        def func_with_kwargs(a, b=10):
+            return a + b
+        
+        task = await runner.submit(
+            func=func_with_kwargs,
+            args=(5,),
+            kwargs={"b": 20}
+        )
+        result = await task.wait(timeout=5.0)
+        
+        assert result == 25
+    
+    @pytest.mark.asyncio
+    async def test_task_timeout(self, runner):
+        """Test task timeout."""
+        async def slow_func():
+            await asyncio.sleep(10)
+            return "done"
+        
+        task = await runner.submit(func=slow_func, timeout=0.1)
+        
+        await asyncio.sleep(0.3)
+        
+        assert task.status == TaskStatus.FAILED
+        assert "timed out" in task.error
+    
+    @pytest.mark.asyncio
+    async def test_task_failure(self, runner):
+        """Test task that raises exception."""
+        def failing_func():
+            raise ValueError("Test error")
+        
+        task = await runner.submit(func=failing_func)
+        
+        await asyncio.sleep(0.1)
+        
+        assert task.status == TaskStatus.FAILED
+        assert "Test error" in task.error
+    
+    @pytest.mark.asyncio
+    async def test_cancel_task(self, runner):
+        """Test cancelling a task."""
+        async def long_running():
+            await asyncio.sleep(10)
+            return "done"
+        
+        task = await runner.submit(func=long_running)
+        
+        await asyncio.sleep(0.1)
+        result = await runner.cancel_task(task.id)
+        
+        assert result
+        assert task.status == TaskStatus.CANCELLED
+    
+    @pytest.mark.asyncio
+    async def test_get_task(self, runner):
+        """Test getting a task by ID."""
+        task = await runner.submit(func=lambda: "test")
+        
+        retrieved = runner.get_task(task.id)
+        
+        assert retrieved is not None
+        assert retrieved.id == task.id
+    
+    @pytest.mark.asyncio
+    async def test_list_tasks(self, runner):
+        """Test listing tasks."""
+        await runner.submit(func=lambda: "a", name="task_a")
+        await runner.submit(func=lambda: "b", name="task_b")
+        
+        await asyncio.sleep(0.2)
+        
+        tasks = runner.list_tasks()
+        
+        assert len(tasks) == 2
+    
+    @pytest.mark.asyncio
+    async def test_list_tasks_by_status(self, runner):
+        """Test listing tasks filtered by status."""
+        await runner.submit(func=lambda: "a")
+        await runner.submit(func=lambda: "b")
+        
+        await asyncio.sleep(0.2)
+        
+        completed = runner.list_tasks(status=TaskStatus.COMPLETED)
+        
+        assert len(completed) == 2
+    
+    @pytest.mark.asyncio
+    async def test_clear_completed(self, runner):
+        """Test clearing completed tasks."""
+        await runner.submit(func=lambda: "a")
+        await runner.submit(func=lambda: "b")
+        
+        await asyncio.sleep(0.2)
+        
+        assert len(runner.tasks) == 2
+        
+        runner.clear_completed()
+        
+        assert len(runner.tasks) == 0
+    
+    @pytest.mark.asyncio
+    async def test_on_complete_callback(self, runner):
+        """Test on_complete callback."""
+        callback_called = []
+        
+        def on_complete(task):
+            callback_called.append(task.id)
+        
+        task = await runner.submit(
+            func=lambda: "result",
+            on_complete=on_complete
+        )
+        
+        await task.wait(timeout=5.0)
+        
+        assert task.id in callback_called
+    
+    @pytest.mark.asyncio
+    async def test_concurrent_execution(self, runner):
+        """Test concurrent task execution."""
+        results = []
+        
+        async def task_func(n):
+            await asyncio.sleep(0.1)
+            results.append(n)
+            return n
+        
+        tasks = []
+        for i in range(3):
+            task = await runner.submit(func=task_func, args=(i,))
+            tasks.append(task)
+        
+        await runner.wait_all(timeout=5.0)
+        
+        assert len(results) == 3
+        assert all(t.is_successful for t in tasks)
+    
+    @pytest.mark.asyncio
+    async def test_max_concurrent_limit(self):
+        """Test max concurrent tasks limit."""
+        config = BackgroundConfig(max_concurrent_tasks=2)
+        runner = BackgroundRunner(config=config)
+        
+        execution_times = []
+        
+        async def tracked_func(n):
+            execution_times.append((n, "start", asyncio.get_event_loop().time()))
+            await asyncio.sleep(0.2)
+            execution_times.append((n, "end", asyncio.get_event_loop().time()))
+            return n
+        
+        tasks = []
+        for i in range(4):
+            task = await runner.submit(func=tracked_func, args=(i,))
+            tasks.append(task)
+        
+        await runner.wait_all(timeout=5.0)
+        
+        # All tasks should complete
+        assert all(t.is_successful for t in tasks)
+    
+    @pytest.mark.asyncio
+    async def test_wait_all(self, runner):
+        """Test waiting for all tasks."""
+        async def slow_func(n):
+            await asyncio.sleep(0.1 * n)
+            return n
+        
+        for i in range(1, 4):
+            await runner.submit(func=slow_func, args=(i,))
+        
+        tasks = await runner.wait_all(timeout=5.0)
+        
+        assert len(tasks) == 3
+        assert all(t.is_completed for t in tasks)
+    
+    @pytest.mark.asyncio
+    async def test_cancel_all(self, runner):
+        """Test cancelling all tasks."""
+        async def long_func():
+            await asyncio.sleep(10)
+        
+        for _ in range(3):
+            await runner.submit(func=long_func)
+        
+        await asyncio.sleep(0.1)
+        await runner.cancel_all()
+        
+        assert all(t.status == TaskStatus.CANCELLED for t in runner.tasks)
+    
+    @pytest.mark.asyncio
+    async def test_stop_runner(self, runner):
+        """Test stopping the runner."""
+        async def long_func():
+            await asyncio.sleep(10)
+        
+        await runner.submit(func=long_func)
+        await asyncio.sleep(0.1)
+        
+        await runner.stop()
+        
+        assert all(t.status == TaskStatus.CANCELLED for t in runner.tasks)
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -0,0 +1 @@
+"""Unit tests for checkpoints module."""
@@ -0,0 +1,417 @@
+"""
+Unit tests for the Checkpoints module.
+
+Tests cover:
+- CheckpointConfig creation and validation
+- Checkpoint data types
+- CheckpointService initialization
+- Save, restore, and diff operations
+"""
+
+import pytest
+import asyncio
+import os
+import tempfile
+import shutil
+from datetime import datetime
+
+from praisonaiagents.checkpoints.types import (
+    CheckpointConfig, Checkpoint, CheckpointDiff, FileDiff,
+    CheckpointResult, CheckpointEvent
+)
+from praisonaiagents.checkpoints.service import CheckpointService
+
+
+# =============================================================================
+# CheckpointConfig Tests
+# =============================================================================
+
+class TestCheckpointConfig:
+    """Tests for CheckpointConfig class."""
+    
+    def test_config_creation(self):
+        """Test creating a config."""
+        config = CheckpointConfig(workspace_dir="/tmp/test")
+        assert config.workspace_dir == "/tmp/test"
+        assert config.enabled
+        assert config.auto_checkpoint
+        assert config.max_checkpoints == 100
+    
+    def test_config_expands_paths(self):
+        """Test that paths are expanded."""
+        config = CheckpointConfig(
+            workspace_dir="~/test",
+            storage_dir="~/.praison/checkpoints"
+        )
+        assert not config.workspace_dir.startswith("~")
+        assert not config.storage_dir.startswith("~")
+    
+    def test_config_default_storage(self):
+        """Test default storage directory."""
+        config = CheckpointConfig(workspace_dir="/tmp/test")
+        assert ".praison/checkpoints" in config.storage_dir
+    
+    def test_config_exclude_patterns(self):
+        """Test default exclude patterns."""
+        config = CheckpointConfig(workspace_dir="/tmp/test")
+        assert ".git" in config.exclude_patterns
+        assert "__pycache__" in config.exclude_patterns
+        assert "node_modules" in config.exclude_patterns
+    
+    def test_get_checkpoint_dir(self):
+        """Test checkpoint directory generation."""
+        config = CheckpointConfig(workspace_dir="/tmp/test")
+        checkpoint_dir = config.get_checkpoint_dir()
+        assert config.storage_dir in checkpoint_dir
+        # Should be a hash-based subdirectory
+        assert len(os.path.basename(checkpoint_dir)) == 12
+
+
+# =============================================================================
+# Checkpoint Data Type Tests
+# =============================================================================
+
+class TestCheckpointTypes:
+    """Tests for checkpoint data types."""
+    
+    def test_checkpoint_creation(self):
+        """Test creating a checkpoint."""
+        checkpoint = Checkpoint(
+            id="abc123def456",
+            short_id="abc123de",
+            message="Test checkpoint",
+            timestamp=datetime.now()
+        )
+        assert checkpoint.id == "abc123def456"
+        assert checkpoint.short_id == "abc123de"
+        assert checkpoint.message == "Test checkpoint"
+    
+    def test_checkpoint_from_git_commit(self):
+        """Test creating checkpoint from git commit."""
+        checkpoint = Checkpoint.from_git_commit(
+            commit_hash="abc123def456789",
+            message="Test message",
+            timestamp="2024-01-01T00:00:00"
+        )
+        assert checkpoint.id == "abc123def456789"
+        assert checkpoint.short_id == "abc123de"
+        assert checkpoint.message == "Test message"
+    
+    def test_checkpoint_to_dict(self):
+        """Test checkpoint serialization."""
+        checkpoint = Checkpoint(
+            id="abc123",
+            short_id="abc1",
+            message="Test",
+            timestamp=datetime(2024, 1, 1)
+        )
+        data = checkpoint.to_dict()
+        assert data["id"] == "abc123"
+        assert data["message"] == "Test"
+        assert "timestamp" in data
+    
+    def test_file_diff(self):
+        """Test FileDiff creation."""
+        diff = FileDiff(
+            path="test.py",
+            absolute_path="/tmp/test.py",
+            status="modified",
+            additions=10,
+            deletions=5
+        )
+        assert diff.path == "test.py"
+        assert diff.status == "modified"
+        assert diff.additions == 10
+    
+    def test_checkpoint_diff(self):
+        """Test CheckpointDiff creation."""
+        files = [
+            FileDiff("a.py", "/tmp/a.py", "added", 10, 0),
+            FileDiff("b.py", "/tmp/b.py", "modified", 5, 3)
+        ]
+        diff = CheckpointDiff(
+            from_checkpoint="abc123",
+            to_checkpoint="def456",
+            files=files
+        )
+        assert diff.total_additions == 15
+        assert diff.total_deletions == 3
+    
+    def test_checkpoint_result_ok(self):
+        """Test successful checkpoint result."""
+        checkpoint = Checkpoint(
+            id="abc123",
+            short_id="abc1",
+            message="Test",
+            timestamp=datetime.now()
+        )
+        result = CheckpointResult.ok(checkpoint)
+        assert result.success
+        assert result.checkpoint == checkpoint
+        assert result.error is None
+    
+    def test_checkpoint_result_fail(self):
+        """Test failed checkpoint result."""
+        result = CheckpointResult.fail("Something went wrong")
+        assert not result.success
+        assert result.checkpoint is None
+        assert result.error == "Something went wrong"
+
+
+# =============================================================================
+# CheckpointService Tests
+# =============================================================================
+
+class TestCheckpointService:
+    """Tests for CheckpointService class."""
+    
+    @pytest.fixture
+    def temp_workspace(self):
+        """Create a temporary workspace directory."""
+        workspace = tempfile.mkdtemp(prefix="praison_test_")
+        yield workspace
+        # Cleanup
+        if os.path.exists(workspace):
+            shutil.rmtree(workspace)
+    
+    @pytest.fixture
+    def temp_storage(self):
+        """Create a temporary storage directory."""
+        storage = tempfile.mkdtemp(prefix="praison_checkpoints_")
+        yield storage
+        # Cleanup
+        if os.path.exists(storage):
+            shutil.rmtree(storage)
+    
+    def test_service_creation(self, temp_workspace, temp_storage):
+        """Test creating a checkpoint service."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        assert service.workspace_dir == temp_workspace
+        assert not service.is_initialized
+    
+    @pytest.mark.asyncio
+    async def test_service_initialize(self, temp_workspace, temp_storage):
+        """Test initializing the service."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        
+        result = await service.initialize()
+        
+        assert result
+        assert service.is_initialized
+        assert os.path.exists(service.git_dir)
+    
+    @pytest.mark.asyncio
+    async def test_service_save_checkpoint(self, temp_workspace, temp_storage):
+        """Test saving a checkpoint."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        # Create a file
+        test_file = os.path.join(temp_workspace, "test.txt")
+        with open(test_file, "w") as f:
+            f.write("Hello, World!")
+        
+        # Save checkpoint
+        result = await service.save("First checkpoint")
+        
+        assert result.success
+        assert result.checkpoint is not None
+        assert result.checkpoint.message == "First checkpoint"
+    
+    @pytest.mark.asyncio
+    async def test_service_save_no_changes(self, temp_workspace, temp_storage):
+        """Test saving checkpoint with no changes."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        # Try to save without changes
+        result = await service.save("Empty checkpoint")
+        
+        assert not result.success
+        assert "No changes" in result.error
+    
+    @pytest.mark.asyncio
+    async def test_service_save_allow_empty(self, temp_workspace, temp_storage):
+        """Test saving empty checkpoint when allowed."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        # Save empty checkpoint
+        result = await service.save("Empty checkpoint", allow_empty=True)
+        
+        assert result.success
+    
+    @pytest.mark.asyncio
+    async def test_service_restore(self, temp_workspace, temp_storage):
+        """Test restoring to a checkpoint."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        # Create initial file
+        test_file = os.path.join(temp_workspace, "test.txt")
+        with open(test_file, "w") as f:
+            f.write("Version 1")
+        
+        # Save checkpoint
+        result1 = await service.save("Version 1")
+        checkpoint_id = result1.checkpoint.id
+        
+        # Modify file
+        with open(test_file, "w") as f:
+            f.write("Version 2")
+        
+        # Restore to checkpoint
+        result = await service.restore(checkpoint_id)
+        
+        assert result.success
+        
+        # Verify file content
+        with open(test_file, "r") as f:
+            content = f.read()
+        assert content == "Version 1"
+    
+    @pytest.mark.asyncio
+    async def test_service_list_checkpoints(self, temp_workspace, temp_storage):
+        """Test listing checkpoints."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        # Create some checkpoints
+        test_file = os.path.join(temp_workspace, "test.txt")
+        
+        with open(test_file, "w") as f:
+            f.write("v1")
+        await service.save("Checkpoint 1")
+        
+        with open(test_file, "w") as f:
+            f.write("v2")
+        await service.save("Checkpoint 2")
+        
+        # List checkpoints
+        checkpoints = await service.list_checkpoints()
+        
+        # Should have initial + 2 checkpoints
+        assert len(checkpoints) >= 2
+    
+    @pytest.mark.asyncio
+    async def test_service_diff(self, temp_workspace, temp_storage):
+        """Test getting diff between checkpoints."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        # Create file and checkpoint
+        test_file = os.path.join(temp_workspace, "test.txt")
+        with open(test_file, "w") as f:
+            f.write("Hello")
+        await service.save("Initial")
+        
+        # Modify file
+        with open(test_file, "w") as f:
+            f.write("Hello World")
+        
+        # Get diff
+        diff = await service.diff()
+        
+        assert diff.from_checkpoint != ""
+        assert len(diff.files) > 0
+    
+    @pytest.mark.asyncio
+    async def test_service_protected_path(self, temp_storage):
+        """Test that protected paths are rejected."""
+        service = CheckpointService(
+            workspace_dir=os.path.expanduser("~"),
+            storage_dir=temp_storage
+        )
+        
+        result = await service.initialize()
+        
+        assert not result
+        assert not service.is_initialized
+    
+    @pytest.mark.asyncio
+    async def test_service_event_handlers(self, temp_workspace, temp_storage):
+        """Test event handlers."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        
+        events_received = []
+        
+        def on_initialized(data):
+            events_received.append(("initialized", data))
+        
+        def on_checkpoint(data):
+            events_received.append(("checkpoint", data))
+        
+        service.on(CheckpointEvent.INITIALIZED, on_initialized)
+        service.on(CheckpointEvent.CHECKPOINT_CREATED, on_checkpoint)
+        
+        await service.initialize()
+        
+        test_file = os.path.join(temp_workspace, "test.txt")
+        with open(test_file, "w") as f:
+            f.write("test")
+        await service.save("Test")
+        
+        assert len(events_received) == 2
+        assert events_received[0][0] == "initialized"
+        assert events_received[1][0] == "checkpoint"
+    
+    @pytest.mark.asyncio
+    async def test_service_cleanup(self, temp_workspace, temp_storage):
+        """Test service cleanup."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        await service.cleanup()
+        
+        assert not service.is_initialized
+    
+    @pytest.mark.asyncio
+    async def test_service_delete_all(self, temp_workspace, temp_storage):
+        """Test deleting all checkpoints."""
+        service = CheckpointService(
+            workspace_dir=temp_workspace,
+            storage_dir=temp_storage
+        )
+        await service.initialize()
+        
+        checkpoint_dir = service.checkpoint_dir
+        assert os.path.exists(checkpoint_dir)
+        
+        result = await service.delete_all()
+        
+        assert result
+        assert not os.path.exists(checkpoint_dir)
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -0,0 +1 @@
+"""Unit tests for compaction module."""
@@ -0,0 +1,314 @@
+"""
+Unit tests for the Compaction module.
+
+Tests cover:
+- CompactionConfig settings
+- CompactionStrategy enum
+- CompactionResult properties
+- ContextCompactor operations
+"""
+
+import pytest
+
+from praisonaiagents.compaction.config import CompactionConfig
+from praisonaiagents.compaction.strategy import CompactionStrategy
+from praisonaiagents.compaction.result import CompactionResult
+from praisonaiagents.compaction.compactor import ContextCompactor
+
+
+# =============================================================================
+# CompactionConfig Tests
+# =============================================================================
+
+class TestCompactionConfig:
+    """Tests for CompactionConfig class."""
+    
+    def test_config_defaults(self):
+        """Test default configuration."""
+        config = CompactionConfig()
+        
+        assert config.enabled
+        assert config.max_tokens == 8000
+        assert config.target_tokens == 6000
+        assert config.preserve_system
+        assert config.preserve_recent == 5
+    
+    def test_config_custom(self):
+        """Test custom configuration."""
+        config = CompactionConfig(
+            enabled=False,
+            max_tokens=16000,
+            preserve_recent=10
+        )
+        
+        assert not config.enabled
+        assert config.max_tokens == 16000
+        assert config.preserve_recent == 10
+
+
+# =============================================================================
+# CompactionStrategy Tests
+# =============================================================================
+
+class TestCompactionStrategy:
+    """Tests for CompactionStrategy enum."""
+    
+    def test_strategy_values(self):
+        """Test strategy enum values."""
+        assert CompactionStrategy.TRUNCATE.value == "truncate"
+        assert CompactionStrategy.SUMMARIZE.value == "summarize"
+        assert CompactionStrategy.SLIDING.value == "sliding"
+        assert CompactionStrategy.SMART.value == "smart"
+    
+    def test_strategy_from_string(self):
+        """Test creating strategy from string."""
+        strategy = CompactionStrategy("truncate")
+        assert strategy == CompactionStrategy.TRUNCATE
+
+
+# =============================================================================
+# CompactionResult Tests
+# =============================================================================
+
+class TestCompactionResult:
+    """Tests for CompactionResult class."""
+    
+    def test_result_creation(self):
+        """Test creating a result."""
+        result = CompactionResult(
+            original_tokens=10000,
+            compacted_tokens=6000,
+            messages_removed=5,
+            messages_kept=10,
+            strategy_used=CompactionStrategy.TRUNCATE
+        )
+        
+        assert result.original_tokens == 10000
+        assert result.compacted_tokens == 6000
+    
+    def test_result_tokens_saved(self):
+        """Test tokens saved calculation."""
+        result = CompactionResult(
+            original_tokens=10000,
+            compacted_tokens=6000,
+            messages_removed=5,
+            messages_kept=10,
+            strategy_used=CompactionStrategy.TRUNCATE
+        )
+        
+        assert result.tokens_saved == 4000
+    
+    def test_result_compression_ratio(self):
+        """Test compression ratio calculation."""
+        result = CompactionResult(
+            original_tokens=10000,
+            compacted_tokens=5000,
+            messages_removed=5,
+            messages_kept=10,
+            strategy_used=CompactionStrategy.TRUNCATE
+        )
+        
+        assert result.compression_ratio == 0.5
+    
+    def test_result_was_compacted(self):
+        """Test was_compacted property."""
+        result = CompactionResult(
+            original_tokens=10000,
+            compacted_tokens=6000,
+            messages_removed=5,
+            messages_kept=10,
+            strategy_used=CompactionStrategy.TRUNCATE
+        )
+        
+        assert result.was_compacted
+    
+    def test_result_not_compacted(self):
+        """Test when not compacted."""
+        result = CompactionResult(
+            original_tokens=5000,
+            compacted_tokens=5000,
+            messages_removed=0,
+            messages_kept=10,
+            strategy_used=CompactionStrategy.TRUNCATE
+        )
+        
+        assert not result.was_compacted
+    
+    def test_result_to_dict(self):
+        """Test result serialization."""
+        result = CompactionResult(
+            original_tokens=10000,
+            compacted_tokens=6000,
+            messages_removed=5,
+            messages_kept=10,
+            strategy_used=CompactionStrategy.TRUNCATE
+        )
+        data = result.to_dict()
+        
+        assert data["original_tokens"] == 10000
+        assert data["tokens_saved"] == 4000
+        assert data["strategy_used"] == "truncate"
+
+
+# =============================================================================
+# ContextCompactor Tests
+# =============================================================================
+
+class TestContextCompactor:
+    """Tests for ContextCompactor class."""
+    
+    @pytest.fixture
+    def compactor(self):
+        """Create a test compactor."""
+        return ContextCompactor(max_tokens=100, preserve_recent=2)
+    
+    @pytest.fixture
+    def messages(self):
+        """Create test messages."""
+        return [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": "Hello, how are you?"},
+            {"role": "assistant", "content": "I'm doing well, thank you!"},
+            {"role": "user", "content": "What's the weather like?"},
+            {"role": "assistant", "content": "I don't have access to weather data."},
+        ]
+    
+    def test_compactor_creation(self, compactor):
+        """Test creating a compactor."""
+        assert compactor.max_tokens == 100
+        assert compactor.preserve_recent == 2
+    
+    def test_compactor_estimate_tokens(self, compactor):
+        """Test token estimation."""
+        text = "Hello world"  # 11 chars
+        tokens = compactor.estimate_tokens(text)
+        
+        assert tokens == 2  # 11 // 4
+    
+    def test_compactor_count_message_tokens(self, compactor):
+        """Test message token counting."""
+        message = {"role": "user", "content": "Hello world"}
+        tokens = compactor.count_message_tokens(message)
+        
+        assert tokens == 2
+    
+    def test_compactor_count_total_tokens(self, compactor, messages):
+        """Test total token counting."""
+        tokens = compactor.count_total_tokens(messages)
+        
+        assert tokens > 0
+    
+    def test_compactor_needs_compaction_true(self):
+        """Test needs_compaction when over limit."""
+        # Create compactor with very low limit
+        compactor = ContextCompactor(max_tokens=10, preserve_recent=2)
+        messages = [
+            {"role": "user", "content": "This is a very long message that should exceed the token limit."},
+            {"role": "assistant", "content": "This is another long response that adds more tokens."},
+        ]
+        
+        needs = compactor.needs_compaction(messages)
+        
+        assert needs
+    
+    def test_compactor_needs_compaction_false(self):
+        """Test needs_compaction when under limit."""
+        compactor = ContextCompactor(max_tokens=10000)
+        messages = [{"role": "user", "content": "Hi"}]
+        
+        needs = compactor.needs_compaction(messages)
+        
+        assert not needs
+    
+    def test_compactor_compact_not_needed(self):
+        """Test compact when not needed."""
+        compactor = ContextCompactor(max_tokens=10000)
+        messages = [{"role": "user", "content": "Hi"}]
+        
+        compacted, result = compactor.compact(messages)
+        
+        assert len(compacted) == len(messages)
+        assert not result.was_compacted
+    
+    def test_compactor_compact_truncate(self):
+        """Test truncate strategy."""
+        compactor = ContextCompactor(max_tokens=10, preserve_recent=1)
+        compactor.strategy = CompactionStrategy.TRUNCATE
+        messages = [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "user", "content": "This is a very long message that should exceed the token limit."},
+            {"role": "assistant", "content": "This is another long response."},
+            {"role": "user", "content": "More content here."},
+        ]
+        
+        compacted, result = compactor.compact(messages)
+        
+        assert len(compacted) < len(messages)
+        assert result.was_compacted
+        assert result.strategy_used == CompactionStrategy.TRUNCATE
+    
+    def test_compactor_compact_sliding(self, compactor, messages):
+        """Test sliding window strategy."""
+        compactor.strategy = CompactionStrategy.SLIDING
+        
+        compacted, result = compactor.compact(messages)
+        
+        assert result.strategy_used == CompactionStrategy.SLIDING
+    
+    def test_compactor_compact_summarize(self, compactor, messages):
+        """Test summarize strategy."""
+        compactor.strategy = CompactionStrategy.SUMMARIZE
+        
+        compacted, result = compactor.compact(messages)
+        
+        assert result.strategy_used == CompactionStrategy.SUMMARIZE
+    
+    def test_compactor_compact_smart(self, compactor, messages):
+        """Test smart strategy."""
+        compactor.strategy = CompactionStrategy.SMART
+        
+        compacted, result = compactor.compact(messages)
+        
+        assert result.strategy_used == CompactionStrategy.SMART
+    
+    def test_compactor_preserves_system(self, compactor, messages):
+        """Test that system messages are preserved."""
+        compacted, _ = compactor.compact(messages)
+        
+        system_msgs = [m for m in compacted if m.get("role") == "system"]
+        assert len(system_msgs) >= 1
+    
+    def test_compactor_preserves_recent(self, compactor, messages):
+        """Test that recent messages are preserved."""
+        compacted, _ = compactor.compact(messages)
+        
+        # Should have at least preserve_recent messages
+        non_system = [m for m in compacted if m.get("role") != "system"]
+        assert len(non_system) >= min(compactor.preserve_recent, len(messages) - 1)
+    
+    def test_compactor_get_stats(self, compactor, messages):
+        """Test get_stats method."""
+        stats = compactor.get_stats(messages)
+        
+        assert "message_count" in stats
+        assert "total_tokens" in stats
+        assert "needs_compaction" in stats
+        assert stats["message_count"] == len(messages)
+    
+    def test_compactor_multipart_content(self, compactor):
+        """Test handling multipart content."""
+        message = {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Hello"},
+                {"type": "text", "text": "World"}
+            ]
+        }
+        
+        tokens = compactor.count_message_tokens(message)
+        
+        assert tokens > 0
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -0,0 +1 @@
+"""Unit tests for hooks module."""
@@ -0,0 +1,717 @@
+"""
+Unit tests for the Hooks module.
+
+Tests cover:
+- HookRegistry registration and lookup
+- HookRunner execution (function and command hooks)
+- Event types and inputs
+- Decision handling (allow, deny, block)
+"""
+
+import pytest
+import asyncio
+import json
+import os
+import tempfile
+from datetime import datetime
+from unittest.mock import MagicMock, AsyncMock, patch
+
+# Import hook types
+from praisonaiagents.hooks.types import (
+    HookEvent, HookResult, HookInput, HookOutput,
+    HookDefinition, CommandHook, FunctionHook, HookExecutionResult
+)
+from praisonaiagents.hooks.events import (
+    BeforeToolInput, AfterToolInput, BeforeAgentInput,
+    AfterAgentInput, SessionStartInput, SessionEndInput
+)
+from praisonaiagents.hooks.registry import HookRegistry, get_default_registry
+from praisonaiagents.hooks.runner import HookRunner
+
+
+# =============================================================================
+# HookResult Tests
+# =============================================================================
+
+class TestHookResult:
+    """Tests for HookResult class."""
+    
+    def test_allow_result(self):
+        """Test creating an allow result."""
+        result = HookResult.allow("Allowed by policy")
+        assert result.decision == "allow"
+        assert result.reason == "Allowed by policy"
+        assert result.is_allowed()
+        assert not result.is_denied()
+    
+    def test_deny_result(self):
+        """Test creating a deny result."""
+        result = HookResult.deny("Blocked by policy")
+        assert result.decision == "deny"
+        assert result.reason == "Blocked by policy"
+        assert not result.is_allowed()
+        assert result.is_denied()
+    
+    def test_block_result(self):
+        """Test creating a block result."""
+        result = HookResult.block("Security violation")
+        assert result.decision == "block"
+        assert result.reason == "Security violation"
+        assert result.is_denied()
+    
+    def test_ask_result(self):
+        """Test creating an ask result."""
+        result = HookResult.ask("Requires confirmation")
+        assert result.decision == "ask"
+        assert result.reason == "Requires confirmation"
+    
+    def test_default_result(self):
+        """Test default result is allow."""
+        result = HookResult()
+        assert result.decision == "allow"
+        assert result.is_allowed()
+
+
+# =============================================================================
+# HookDefinition Tests
+# =============================================================================
+
+class TestHookDefinition:
+    """Tests for HookDefinition class."""
+    
+    def test_definition_creation(self):
+        """Test creating a hook definition."""
+        hook = HookDefinition(
+            event=HookEvent.BEFORE_TOOL,
+            name="test_hook",
+            matcher="write_*"
+        )
+        assert hook.event == HookEvent.BEFORE_TOOL
+        assert hook.name == "test_hook"
+        assert hook.matcher == "write_*"
+        assert hook.enabled
+    
+    def test_matcher_regex(self):
+        """Test regex matching."""
+        hook = HookDefinition(matcher="write_.*")
+        assert hook.matches("write_file")
+        assert hook.matches("write_data")
+        assert not hook.matches("read_file")
+    
+    def test_matcher_none(self):
+        """Test that None matcher matches everything."""
+        hook = HookDefinition(matcher=None)
+        assert hook.matches("anything")
+        assert hook.matches("write_file")
+    
+    def test_command_hook(self):
+        """Test CommandHook creation."""
+        hook = CommandHook(
+            event=HookEvent.BEFORE_TOOL,
+            command="python validator.py",
+            env={"API_KEY": "test"}
+        )
+        assert hook.command == "python validator.py"
+        assert hook.env == {"API_KEY": "test"}
+        assert hook.shell
+    
+    def test_function_hook(self):
+        """Test FunctionHook creation."""
+        def my_hook(data):
+            return HookResult.allow()
+        
+        hook = FunctionHook(
+            event=HookEvent.BEFORE_TOOL,
+            func=my_hook
+        )
+        assert hook.func == my_hook
+        assert hook.name == "my_hook"
+
+
+# =============================================================================
+# HookRegistry Tests
+# =============================================================================
+
+class TestHookRegistry:
+    """Tests for HookRegistry class."""
+    
+    def test_registry_creation(self):
+        """Test creating a registry."""
+        registry = HookRegistry()
+        assert registry.enabled
+        assert len(registry) == 0
+    
+    def test_register_function(self):
+        """Test registering a function hook."""
+        registry = HookRegistry()
+        
+        def my_hook(data):
+            return HookResult.allow()
+        
+        hook_id = registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=my_hook,
+            name="my_hook"
+        )
+        
+        assert hook_id is not None
+        assert len(registry) == 1
+        
+        hooks = registry.get_hooks(HookEvent.BEFORE_TOOL)
+        assert len(hooks) == 1
+        assert hooks[0].name == "my_hook"
+    
+    def test_register_command(self):
+        """Test registering a command hook."""
+        registry = HookRegistry()
+        
+        hook_id = registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command="python validator.py",
+            name="validator"
+        )
+        
+        assert hook_id is not None
+        hooks = registry.get_hooks(HookEvent.BEFORE_TOOL)
+        assert len(hooks) == 1
+        assert isinstance(hooks[0], CommandHook)
+    
+    def test_decorator_registration(self):
+        """Test decorator-based registration."""
+        registry = HookRegistry()
+        
+        @registry.on(HookEvent.BEFORE_TOOL)
+        def validate_tool(data):
+            return HookResult.allow()
+        
+        hooks = registry.get_hooks(HookEvent.BEFORE_TOOL)
+        assert len(hooks) == 1
+        assert hooks[0].name == "validate_tool"
+    
+    def test_unregister(self):
+        """Test unregistering a hook."""
+        registry = HookRegistry()
+        
+        hook_id = registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command="echo test"
+        )
+        
+        assert len(registry) == 1
+        assert registry.unregister(hook_id)
+        assert len(registry) == 0
+    
+    def test_get_hooks_with_matcher(self):
+        """Test getting hooks filtered by target."""
+        registry = HookRegistry()
+        
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=lambda d: HookResult.allow(),
+            matcher="write_.*",
+            name="write_hook"
+        )
+        
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=lambda d: HookResult.allow(),
+            matcher="read_.*",
+            name="read_hook"
+        )
+        
+        write_hooks = registry.get_hooks(HookEvent.BEFORE_TOOL, "write_file")
+        assert len(write_hooks) == 1
+        assert write_hooks[0].name == "write_hook"
+        
+        read_hooks = registry.get_hooks(HookEvent.BEFORE_TOOL, "read_file")
+        assert len(read_hooks) == 1
+        assert read_hooks[0].name == "read_hook"
+    
+    def test_disable_enable_hook(self):
+        """Test disabling and enabling hooks."""
+        registry = HookRegistry()
+        
+        hook_id = registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command="echo test"
+        )
+        
+        assert len(registry.get_hooks(HookEvent.BEFORE_TOOL)) == 1
+        
+        registry.disable_hook(hook_id)
+        assert len(registry.get_hooks(HookEvent.BEFORE_TOOL)) == 0
+        
+        registry.enable_hook(hook_id)
+        assert len(registry.get_hooks(HookEvent.BEFORE_TOOL)) == 1
+    
+    def test_clear_hooks(self):
+        """Test clearing hooks."""
+        registry = HookRegistry()
+        
+        registry.register_command(HookEvent.BEFORE_TOOL, "echo 1")
+        registry.register_command(HookEvent.AFTER_TOOL, "echo 2")
+        
+        assert len(registry) == 2
+        
+        registry.clear(HookEvent.BEFORE_TOOL)
+        assert len(registry) == 1
+        
+        registry.clear()
+        assert len(registry) == 0
+    
+    def test_list_hooks(self):
+        """Test listing all hooks."""
+        registry = HookRegistry()
+        
+        registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command="echo test",
+            name="test_hook"
+        )
+        
+        hooks_list = registry.list_hooks()
+        assert "before_tool" in hooks_list
+        assert len(hooks_list["before_tool"]) == 1
+        assert hooks_list["before_tool"][0]["name"] == "test_hook"
+
+
+# =============================================================================
+# Event Input Tests
+# =============================================================================
+
+class TestEventInputs:
+    """Tests for event-specific input classes."""
+    
+    def test_before_tool_input(self):
+        """Test BeforeToolInput."""
+        input_data = BeforeToolInput(
+            session_id="test-session",
+            cwd="/tmp",
+            event_name="before_tool",
+            timestamp="2024-01-01T00:00:00",
+            tool_name="write_file",
+            tool_input={"path": "/tmp/test.txt", "content": "hello"}
+        )
+        
+        assert input_data.tool_name == "write_file"
+        assert input_data.tool_input["path"] == "/tmp/test.txt"
+        
+        data_dict = input_data.to_dict()
+        assert data_dict["tool_name"] == "write_file"
+    
+    def test_after_tool_input(self):
+        """Test AfterToolInput."""
+        input_data = AfterToolInput(
+            session_id="test-session",
+            cwd="/tmp",
+            event_name="after_tool",
+            timestamp="2024-01-01T00:00:00",
+            tool_name="write_file",
+            tool_output="File written successfully",
+            execution_time_ms=100.5
+        )
+        
+        assert input_data.tool_output == "File written successfully"
+        assert input_data.execution_time_ms == 100.5
+    
+    def test_before_agent_input(self):
+        """Test BeforeAgentInput."""
+        input_data = BeforeAgentInput(
+            session_id="test-session",
+            cwd="/tmp",
+            event_name="before_agent",
+            timestamp="2024-01-01T00:00:00",
+            prompt="Write a file",
+            tools_available=["write_file", "read_file"]
+        )
+        
+        assert input_data.prompt == "Write a file"
+        assert "write_file" in input_data.tools_available
+    
+    def test_session_start_input(self):
+        """Test SessionStartInput."""
+        input_data = SessionStartInput(
+            session_id="test-session",
+            cwd="/tmp",
+            event_name="session_start",
+            timestamp="2024-01-01T00:00:00",
+            source="startup"
+        )
+        
+        assert input_data.source == "startup"
+
+
+# =============================================================================
+# HookRunner Tests
+# =============================================================================
+
+class TestHookRunner:
+    """Tests for HookRunner class."""
+    
+    def _create_sample_input(self):
+        """Create sample input data."""
+        return BeforeToolInput(
+            session_id="test-session",
+            cwd="/tmp",
+            event_name="before_tool",
+            timestamp="2024-01-01T00:00:00",
+            tool_name="write_file",
+            tool_input={"path": "/tmp/test.txt"}
+        )
+    
+    @pytest.mark.asyncio
+    async def test_execute_function_hook_allow(self):
+        """Test executing a function hook that allows."""
+        registry = HookRegistry()
+        
+        def allow_hook(data):
+            return HookResult.allow("Allowed")
+        
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=allow_hook
+        )
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert results[0].success
+        assert results[0].output.is_allowed()
+    
+    @pytest.mark.asyncio
+    async def test_execute_function_hook_deny(self):
+        """Test executing a function hook that denies."""
+        registry = HookRegistry()
+        
+        def deny_hook(data):
+            return HookResult.deny("Not allowed")
+        
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=deny_hook
+        )
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert results[0].success
+        assert results[0].output.is_denied()
+        assert HookRunner.is_blocked(results)
+    
+    @pytest.mark.asyncio
+    async def test_execute_async_function_hook(self):
+        """Test executing an async function hook."""
+        registry = HookRegistry()
+        
+        async def async_hook(data):
+            await asyncio.sleep(0.01)
+            return HookResult.allow("Async allowed")
+        
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=async_hook,
+            is_async=True
+        )
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert results[0].success
+    
+    @pytest.mark.asyncio
+    async def test_execute_multiple_hooks_parallel(self):
+        """Test executing multiple hooks in parallel."""
+        registry = HookRegistry()
+        call_order = []
+        
+        def hook1(data):
+            call_order.append(1)
+            return HookResult.allow()
+        
+        def hook2(data):
+            call_order.append(2)
+            return HookResult.allow()
+        
+        registry.register_function(HookEvent.BEFORE_TOOL, hook1, sequential=False)
+        registry.register_function(HookEvent.BEFORE_TOOL, hook2, sequential=False)
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 2
+        assert all(r.success for r in results)
+    
+    @pytest.mark.asyncio
+    async def test_execute_sequential_hooks(self):
+        """Test executing hooks sequentially."""
+        registry = HookRegistry()
+        call_order = []
+        
+        def hook1(data):
+            call_order.append(1)
+            return HookResult.allow()
+        
+        def hook2(data):
+            call_order.append(2)
+            return HookResult.allow()
+        
+        registry.register_function(HookEvent.BEFORE_TOOL, hook1, sequential=True)
+        registry.register_function(HookEvent.BEFORE_TOOL, hook2, sequential=True)
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 2
+        assert call_order == [1, 2]
+    
+    @pytest.mark.asyncio
+    async def test_sequential_stops_on_deny(self):
+        """Test that sequential execution stops on deny."""
+        registry = HookRegistry()
+        call_order = []
+        
+        def hook1(data):
+            call_order.append(1)
+            return HookResult.deny("Blocked")
+        
+        def hook2(data):
+            call_order.append(2)
+            return HookResult.allow()
+        
+        registry.register_function(HookEvent.BEFORE_TOOL, hook1, sequential=True)
+        registry.register_function(HookEvent.BEFORE_TOOL, hook2, sequential=True)
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1  # Only first hook executed
+        assert call_order == [1]
+        assert HookRunner.is_blocked(results)
+    
+    @pytest.mark.asyncio
+    async def test_hook_timeout(self):
+        """Test hook timeout handling."""
+        registry = HookRegistry()
+        
+        async def slow_hook(data):
+            await asyncio.sleep(10)  # Very slow
+            return HookResult.allow()
+        
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=slow_hook,
+            is_async=True,
+            timeout=0.1  # 100ms timeout
+        )
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert not results[0].success
+        assert "timed out" in results[0].error
+    
+    @pytest.mark.asyncio
+    async def test_hook_exception_handling(self):
+        """Test hook exception handling."""
+        registry = HookRegistry()
+        
+        def failing_hook(data):
+            raise ValueError("Hook failed")
+        
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=failing_hook
+        )
+        
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert not results[0].success
+        assert "Hook failed" in results[0].error
+    
+    @pytest.mark.asyncio
+    async def test_no_hooks_returns_empty(self):
+        """Test that no hooks returns empty list."""
+        registry = HookRegistry()
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        assert results == []
+    
+    @pytest.mark.asyncio
+    async def test_disabled_registry(self):
+        """Test that disabled registry returns no hooks."""
+        registry = HookRegistry()
+        registry.register_function(
+            event=HookEvent.BEFORE_TOOL,
+            func=lambda d: HookResult.allow()
+        )
+        
+        registry.enabled = False
+        runner = HookRunner(registry)
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert results == []
+    
+    def test_is_blocked_helper(self):
+        """Test is_blocked helper method."""
+        allow_result = HookExecutionResult(
+            hook_id="1",
+            hook_name="test",
+            event=HookEvent.BEFORE_TOOL,
+            success=True,
+            output=HookResult.allow()
+        )
+        
+        deny_result = HookExecutionResult(
+            hook_id="2",
+            hook_name="test",
+            event=HookEvent.BEFORE_TOOL,
+            success=True,
+            output=HookResult.deny("Blocked")
+        )
+        
+        assert not HookRunner.is_blocked([allow_result])
+        assert HookRunner.is_blocked([deny_result])
+        assert HookRunner.is_blocked([allow_result, deny_result])
+    
+    def test_get_blocking_reason(self):
+        """Test get_blocking_reason helper method."""
+        deny_result = HookExecutionResult(
+            hook_id="1",
+            hook_name="test",
+            event=HookEvent.BEFORE_TOOL,
+            success=True,
+            output=HookResult.deny("Security violation")
+        )
+        
+        reason = HookRunner.get_blocking_reason([deny_result])
+        assert reason == "Security violation"
+    
+    def test_aggregate_context(self):
+        """Test aggregate_context helper method."""
+        result1 = HookExecutionResult(
+            hook_id="1",
+            hook_name="test1",
+            event=HookEvent.BEFORE_TOOL,
+            success=True,
+            output=HookResult(additional_context="Context 1")
+        )
+        
+        result2 = HookExecutionResult(
+            hook_id="2",
+            hook_name="test2",
+            event=HookEvent.BEFORE_TOOL,
+            success=True,
+            output=HookResult(additional_context="Context 2")
+        )
+        
+        context = HookRunner.aggregate_context([result1, result2])
+        assert "Context 1" in context
+        assert "Context 2" in context
+
+
+# =============================================================================
+# Command Hook Tests
+# =============================================================================
+
+class TestCommandHooks:
+    """Tests for command hook execution."""
+    
+    def _create_sample_input(self):
+        return BeforeToolInput(
+            session_id="test-session",
+            cwd="/tmp",
+            event_name="before_tool",
+            timestamp="2024-01-01T00:00:00",
+            tool_name="write_file",
+            tool_input={"path": "/tmp/test.txt"}
+        )
+    
+    @pytest.mark.asyncio
+    async def test_command_hook_success(self):
+        """Test successful command hook execution."""
+        registry = HookRegistry()
+        registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command='echo \'{"decision": "allow"}\'',
+            name="allow_hook"
+        )
+        
+        runner = HookRunner(registry, cwd="/tmp")
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert results[0].success
+        assert results[0].output.decision == "allow"
+    
+    @pytest.mark.asyncio
+    async def test_command_hook_deny(self):
+        """Test command hook that denies."""
+        registry = HookRegistry()
+        registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command='echo \'{"decision": "deny", "reason": "Blocked"}\''
+        )
+        
+        runner = HookRunner(registry, cwd="/tmp")
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert results[0].output.decision == "deny"
+        assert results[0].output.reason == "Blocked"
+    
+    @pytest.mark.asyncio
+    async def test_command_hook_exit_code_2(self):
+        """Test command hook with blocking exit code."""
+        registry = HookRegistry()
+        registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command="exit 2"
+        )
+        
+        runner = HookRunner(registry, cwd="/tmp")
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert results[0].exit_code == 2
+        assert results[0].output.decision == "deny"
+    
+    @pytest.mark.asyncio
+    async def test_command_hook_timeout(self):
+        """Test command hook timeout."""
+        registry = HookRegistry()
+        registry.register_command(
+            event=HookEvent.BEFORE_TOOL,
+            command="sleep 10",
+            timeout=0.1
+        )
+        
+        runner = HookRunner(registry, cwd="/tmp")
+        sample_input = self._create_sample_input()
+        results = await runner.execute(HookEvent.BEFORE_TOOL, sample_input)
+        
+        assert len(results) == 1
+        assert not results[0].success
+        assert "timed out" in results[0].error
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -0,0 +1 @@
+"""Unit tests for LSP module."""
@@ -0,0 +1,327 @@
+"""
+Unit tests for the LSP module.
+
+Tests cover:
+- LSP types (Position, Range, Diagnostic, etc.)
+- LSPConfig creation and defaults
+- LSPClient initialization
+"""
+
+import pytest
+from praisonaiagents.lsp.types import (
+    Position, Range, Location, Diagnostic, DiagnosticSeverity,
+    CompletionItem, TextDocumentItem, TextDocumentIdentifier
+)
+from praisonaiagents.lsp.config import LSPConfig, DEFAULT_SERVERS
+from praisonaiagents.lsp.client import LSPClient
+
+
+# =============================================================================
+# Position Tests
+# =============================================================================
+
+class TestPosition:
+    """Tests for Position class."""
+    
+    def test_position_creation(self):
+        """Test creating a position."""
+        pos = Position(line=10, character=5)
+        assert pos.line == 10
+        assert pos.character == 5
+    
+    def test_position_to_dict(self):
+        """Test position serialization."""
+        pos = Position(line=10, character=5)
+        data = pos.to_dict()
+        assert data == {"line": 10, "character": 5}
+    
+    def test_position_from_dict(self):
+        """Test position deserialization."""
+        pos = Position.from_dict({"line": 10, "character": 5})
+        assert pos.line == 10
+        assert pos.character == 5
+
+
+# =============================================================================
+# Range Tests
+# =============================================================================
+
+class TestRange:
+    """Tests for Range class."""
+    
+    def test_range_creation(self):
+        """Test creating a range."""
+        start = Position(line=0, character=0)
+        end = Position(line=10, character=20)
+        r = Range(start=start, end=end)
+        
+        assert r.start.line == 0
+        assert r.end.line == 10
+    
+    def test_range_to_dict(self):
+        """Test range serialization."""
+        r = Range(
+            start=Position(0, 0),
+            end=Position(10, 20)
+        )
+        data = r.to_dict()
+        
+        assert data["start"]["line"] == 0
+        assert data["end"]["line"] == 10
+    
+    def test_range_from_dict(self):
+        """Test range deserialization."""
+        r = Range.from_dict({
+            "start": {"line": 0, "character": 0},
+            "end": {"line": 10, "character": 20}
+        })
+        
+        assert r.start.line == 0
+        assert r.end.character == 20
+
+
+# =============================================================================
+# Location Tests
+# =============================================================================
+
+class TestLocation:
+    """Tests for Location class."""
+    
+    def test_location_creation(self):
+        """Test creating a location."""
+        loc = Location(
+            uri="file:///test.py",
+            range=Range(Position(0, 0), Position(10, 0))
+        )
+        
+        assert loc.uri == "file:///test.py"
+        assert loc.range.start.line == 0
+    
+    def test_location_to_dict(self):
+        """Test location serialization."""
+        loc = Location(
+            uri="file:///test.py",
+            range=Range(Position(0, 0), Position(10, 0))
+        )
+        data = loc.to_dict()
+        
+        assert data["uri"] == "file:///test.py"
+        assert "range" in data
+
+
+# =============================================================================
+# Diagnostic Tests
+# =============================================================================
+
+class TestDiagnostic:
+    """Tests for Diagnostic class."""
+    
+    def test_diagnostic_creation(self):
+        """Test creating a diagnostic."""
+        diag = Diagnostic(
+            range=Range(Position(5, 0), Position(5, 10)),
+            message="Undefined variable 'x'",
+            severity=DiagnosticSeverity.ERROR
+        )
+        
+        assert diag.message == "Undefined variable 'x'"
+        assert diag.severity == DiagnosticSeverity.ERROR
+    
+    def test_diagnostic_default_severity(self):
+        """Test default severity is ERROR."""
+        diag = Diagnostic(
+            range=Range(Position(0, 0), Position(0, 10)),
+            message="Test"
+        )
+        
+        assert diag.severity == DiagnosticSeverity.ERROR
+    
+    def test_diagnostic_to_dict(self):
+        """Test diagnostic serialization."""
+        diag = Diagnostic(
+            range=Range(Position(5, 0), Position(5, 10)),
+            message="Test error",
+            severity=DiagnosticSeverity.WARNING,
+            code="W001",
+            source="test"
+        )
+        data = diag.to_dict()
+        
+        assert data["message"] == "Test error"
+        assert data["severity"] == 2  # WARNING
+        assert data["code"] == "W001"
+        assert data["source"] == "test"
+    
+    def test_diagnostic_from_dict(self):
+        """Test diagnostic deserialization."""
+        diag = Diagnostic.from_dict({
+            "range": {
+                "start": {"line": 5, "character": 0},
+                "end": {"line": 5, "character": 10}
+            },
+            "message": "Test error",
+            "severity": 2,
+            "code": "W001"
+        })
+        
+        assert diag.message == "Test error"
+        assert diag.severity == DiagnosticSeverity.WARNING
+        assert diag.code == "W001"
+
+
+# =============================================================================
+# CompletionItem Tests
+# =============================================================================
+
+class TestCompletionItem:
+    """Tests for CompletionItem class."""
+    
+    def test_completion_creation(self):
+        """Test creating a completion item."""
+        item = CompletionItem(
+            label="print",
+            kind=3,  # Function
+            detail="Built-in function"
+        )
+        
+        assert item.label == "print"
+        assert item.kind == 3
+        assert item.detail == "Built-in function"
+    
+    def test_completion_to_dict(self):
+        """Test completion serialization."""
+        item = CompletionItem(
+            label="print",
+            kind=3,
+            detail="Built-in function",
+            insert_text="print($1)"
+        )
+        data = item.to_dict()
+        
+        assert data["label"] == "print"
+        assert data["insertText"] == "print($1)"
+    
+    def test_completion_from_dict(self):
+        """Test completion deserialization."""
+        item = CompletionItem.from_dict({
+            "label": "print",
+            "kind": 3,
+            "detail": "Built-in function",
+            "insertText": "print($1)"
+        })
+        
+        assert item.label == "print"
+        assert item.insert_text == "print($1)"
+
+
+# =============================================================================
+# TextDocument Tests
+# =============================================================================
+
+class TestTextDocumentTypes:
+    """Tests for text document types."""
+    
+    def test_text_document_item(self):
+        """Test TextDocumentItem."""
+        doc = TextDocumentItem(
+            uri="file:///test.py",
+            language_id="python",
+            version=1,
+            text="print('hello')"
+        )
+        data = doc.to_dict()
+        
+        assert data["uri"] == "file:///test.py"
+        assert data["languageId"] == "python"
+        assert data["version"] == 1
+    
+    def test_text_document_identifier(self):
+        """Test TextDocumentIdentifier."""
+        doc = TextDocumentIdentifier(uri="file:///test.py")
+        data = doc.to_dict()
+        
+        assert data["uri"] == "file:///test.py"
+
+
+# =============================================================================
+# LSPConfig Tests
+# =============================================================================
+
+class TestLSPConfig:
+    """Tests for LSPConfig class."""
+    
+    def test_config_with_defaults(self):
+        """Test config with default server."""
+        config = LSPConfig(language="python")
+        
+        assert config.language == "python"
+        assert config.command == "pylsp"
+        assert config.args == []
+    
+    def test_config_custom_command(self):
+        """Test config with custom command."""
+        config = LSPConfig(
+            language="python",
+            command="pyright-langserver",
+            args=["--stdio"]
+        )
+        
+        assert config.command == "pyright-langserver"
+        assert config.args == ["--stdio"]
+    
+    def test_config_unknown_language(self):
+        """Test config with unknown language raises error."""
+        with pytest.raises(ValueError):
+            LSPConfig(language="unknown_language")
+    
+    def test_default_servers_exist(self):
+        """Test that default servers are defined."""
+        assert "python" in DEFAULT_SERVERS
+        assert "javascript" in DEFAULT_SERVERS
+        assert "typescript" in DEFAULT_SERVERS
+
+
+# =============================================================================
+# LSPClient Tests
+# =============================================================================
+
+class TestLSPClient:
+    """Tests for LSPClient class."""
+    
+    def test_client_creation(self):
+        """Test creating a client."""
+        client = LSPClient(language="python")
+        
+        assert client.config.language == "python"
+        assert not client.is_running
+    
+    def test_client_custom_command(self):
+        """Test client with custom command."""
+        client = LSPClient(
+            language="python",
+            command="custom-server",
+            args=["--mode", "stdio"]
+        )
+        
+        assert client.config.command == "custom-server"
+        assert client.config.args == ["--mode", "stdio"]
+    
+    def test_client_root_uri(self):
+        """Test client with root URI."""
+        client = LSPClient(
+            language="python",
+            root_uri="file:///workspace"
+        )
+        
+        assert client.config.root_uri == "file:///workspace"
+    
+    def test_client_not_running_initially(self):
+        """Test client is not running initially."""
+        client = LSPClient(language="python")
+        
+        assert not client.is_running
+        assert not client._initialized
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -0,0 +1 @@
+"""Unit tests for policy module."""
@@ -0,0 +1,508 @@
+"""
+Unit tests for the Policy module.
+
+Tests cover:
+- PolicyResult creation
+- PolicyRule matching and evaluation
+- Policy evaluation
+- PolicyEngine management and checks
+"""
+
+import pytest
+
+from praisonaiagents.policy.types import PolicyAction, PolicyResult
+from praisonaiagents.policy.policy import Policy, PolicyRule
+from praisonaiagents.policy.config import PolicyConfig
+from praisonaiagents.policy.engine import (
+    PolicyEngine, create_deny_tools_policy,
+    create_allow_tools_policy, create_read_only_policy
+)
+
+
+# =============================================================================
+# PolicyResult Tests
+# =============================================================================
+
+class TestPolicyResult:
+    """Tests for PolicyResult class."""
+    
+    def test_result_creation(self):
+        """Test creating a result."""
+        result = PolicyResult(
+            allowed=True,
+            action=PolicyAction.ALLOW,
+            reason="Test"
+        )
+        assert result.allowed
+        assert result.action == PolicyAction.ALLOW
+    
+    def test_result_allow(self):
+        """Test allow factory method."""
+        result = PolicyResult.allow("Allowed")
+        assert result.allowed
+        assert result.action == PolicyAction.ALLOW
+        assert result.reason == "Allowed"
+    
+    def test_result_deny(self):
+        """Test deny factory method."""
+        result = PolicyResult.deny("Not allowed", "test_policy")
+        assert not result.allowed
+        assert result.action == PolicyAction.DENY
+        assert result.reason == "Not allowed"
+        assert result.policy_name == "test_policy"
+    
+    def test_result_ask(self):
+        """Test ask factory method."""
+        result = PolicyResult.ask("Confirm action")
+        assert not result.allowed
+        assert result.action == PolicyAction.ASK
+    
+    def test_result_to_dict(self):
+        """Test result serialization."""
+        result = PolicyResult(
+            allowed=False,
+            action=PolicyAction.DENY,
+            policy_name="test",
+            reason="Test reason"
+        )
+        data = result.to_dict()
+        
+        assert data["allowed"] is False
+        assert data["action"] == "deny"
+        assert data["policy_name"] == "test"
+
+
+# =============================================================================
+# PolicyRule Tests
+# =============================================================================
+
+class TestPolicyRule:
+    """Tests for PolicyRule class."""
+    
+    def test_rule_creation(self):
+        """Test creating a rule."""
+        rule = PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*",
+            reason="No delete"
+        )
+        assert rule.action == PolicyAction.DENY
+        assert rule.resource == "tool:delete_*"
+    
+    def test_rule_exact_match(self):
+        """Test exact resource matching."""
+        rule = PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_file"
+        )
+        
+        assert rule.matches("tool:delete_file", {})
+        assert not rule.matches("tool:read_file", {})
+    
+    def test_rule_wildcard_match(self):
+        """Test wildcard resource matching."""
+        rule = PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*"
+        )
+        
+        assert rule.matches("tool:delete_file", {})
+        assert rule.matches("tool:delete_directory", {})
+        assert not rule.matches("tool:read_file", {})
+    
+    def test_rule_condition(self):
+        """Test rule with condition."""
+        rule = PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:*",
+            condition=lambda ctx: ctx.get("dangerous", False)
+        )
+        
+        assert rule.matches("tool:test", {"dangerous": True})
+        assert not rule.matches("tool:test", {"dangerous": False})
+        assert not rule.matches("tool:test", {})
+    
+    def test_rule_evaluate_match(self):
+        """Test rule evaluation when matching."""
+        rule = PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*",
+            reason="No delete",
+            name="deny_delete"
+        )
+        
+        result = rule.evaluate("tool:delete_file", {})
+        
+        assert result is not None
+        assert not result.allowed
+        assert result.action == PolicyAction.DENY
+        assert result.reason == "No delete"
+    
+    def test_rule_evaluate_no_match(self):
+        """Test rule evaluation when not matching."""
+        rule = PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*"
+        )
+        
+        result = rule.evaluate("tool:read_file", {})
+        
+        assert result is None
+    
+    def test_rule_to_dict(self):
+        """Test rule serialization."""
+        rule = PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:test",
+            reason="Test",
+            name="test_rule",
+            priority=10
+        )
+        data = rule.to_dict()
+        
+        assert data["action"] == "deny"
+        assert data["resource"] == "tool:test"
+        assert data["priority"] == 10
+
+
+# =============================================================================
+# Policy Tests
+# =============================================================================
+
+class TestPolicy:
+    """Tests for Policy class."""
+    
+    def test_policy_creation(self):
+        """Test creating a policy."""
+        policy = Policy(
+            name="test_policy",
+            description="Test policy"
+        )
+        assert policy.name == "test_policy"
+        assert policy.enabled
+    
+    def test_policy_add_rule(self):
+        """Test adding rules to a policy."""
+        policy = Policy(name="test")
+        
+        policy.add_rule(PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*"
+        ))
+        
+        assert len(policy.rules) == 1
+    
+    def test_policy_remove_rule(self):
+        """Test removing rules from a policy."""
+        policy = Policy(name="test")
+        policy.add_rule(PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*",
+            name="deny_delete"
+        ))
+        
+        result = policy.remove_rule("deny_delete")
+        
+        assert result
+        assert len(policy.rules) == 0
+    
+    def test_policy_evaluate_match(self):
+        """Test policy evaluation when rule matches."""
+        policy = Policy(
+            name="test",
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.DENY,
+                    resource="tool:delete_*",
+                    reason="No delete"
+                )
+            ]
+        )
+        
+        result = policy.evaluate("tool:delete_file", {})
+        
+        assert result is not None
+        assert not result.allowed
+        assert result.policy_name == "test"
+    
+    def test_policy_evaluate_no_match(self):
+        """Test policy evaluation when no rule matches."""
+        policy = Policy(
+            name="test",
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.DENY,
+                    resource="tool:delete_*"
+                )
+            ]
+        )
+        
+        result = policy.evaluate("tool:read_file", {})
+        
+        assert result is None
+    
+    def test_policy_disabled(self):
+        """Test disabled policy."""
+        policy = Policy(
+            name="test",
+            enabled=False,
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.DENY,
+                    resource="tool:*"
+                )
+            ]
+        )
+        
+        result = policy.evaluate("tool:delete_file", {})
+        
+        assert result is None
+    
+    def test_policy_to_dict(self):
+        """Test policy serialization."""
+        policy = Policy(
+            name="test",
+            description="Test policy",
+            rules=[
+                PolicyRule(action=PolicyAction.DENY, resource="tool:*")
+            ]
+        )
+        data = policy.to_dict()
+        
+        assert data["name"] == "test"
+        assert len(data["rules"]) == 1
+    
+    def test_policy_from_dict(self):
+        """Test policy deserialization."""
+        data = {
+            "name": "test",
+            "description": "Test",
+            "rules": [
+                {"action": "deny", "resource": "tool:delete_*"}
+            ]
+        }
+        
+        policy = Policy.from_dict(data)
+        
+        assert policy.name == "test"
+        assert len(policy.rules) == 1
+        assert policy.rules[0].action == PolicyAction.DENY
+
+
+# =============================================================================
+# PolicyConfig Tests
+# =============================================================================
+
+class TestPolicyConfig:
+    """Tests for PolicyConfig class."""
+    
+    def test_config_defaults(self):
+        """Test default configuration."""
+        config = PolicyConfig()
+        
+        assert config.enabled
+        assert config.default_action == "allow"
+        assert not config.strict_mode
+    
+    def test_config_custom(self):
+        """Test custom configuration."""
+        config = PolicyConfig(
+            enabled=False,
+            strict_mode=True
+        )
+        
+        assert not config.enabled
+        assert config.strict_mode
+
+
+# =============================================================================
+# PolicyEngine Tests
+# =============================================================================
+
+class TestPolicyEngine:
+    """Tests for PolicyEngine class."""
+    
+    @pytest.fixture
+    def engine(self):
+        """Create a test engine."""
+        return PolicyEngine()
+    
+    def test_engine_creation(self, engine):
+        """Test creating an engine."""
+        assert engine.config.enabled
+        assert len(engine.policies) == 0
+    
+    def test_engine_add_policy(self, engine):
+        """Test adding a policy."""
+        policy = Policy(name="test")
+        engine.add_policy(policy)
+        
+        assert len(engine.policies) == 1
+        assert engine.get_policy("test") is not None
+    
+    def test_engine_remove_policy(self, engine):
+        """Test removing a policy."""
+        engine.add_policy(Policy(name="test"))
+        
+        result = engine.remove_policy("test")
+        
+        assert result
+        assert len(engine.policies) == 0
+    
+    def test_engine_check_allow(self, engine):
+        """Test check that allows."""
+        engine.add_policy(Policy(
+            name="allow_read",
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.ALLOW,
+                    resource="tool:read_*"
+                )
+            ]
+        ))
+        
+        result = engine.check("tool:read_file", {})
+        
+        assert result.allowed
+    
+    def test_engine_check_deny(self, engine):
+        """Test check that denies."""
+        engine.add_policy(Policy(
+            name="deny_delete",
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.DENY,
+                    resource="tool:delete_*",
+                    reason="No delete"
+                )
+            ]
+        ))
+        
+        result = engine.check("tool:delete_file", {})
+        
+        assert not result.allowed
+        assert result.reason == "No delete"
+    
+    def test_engine_check_no_match(self, engine):
+        """Test check with no matching policy."""
+        result = engine.check("tool:anything", {})
+        
+        assert result.allowed  # Default is allow
+    
+    def test_engine_strict_mode(self):
+        """Test strict mode denies when no match."""
+        engine = PolicyEngine(PolicyConfig(strict_mode=True))
+        
+        result = engine.check("tool:anything", {})
+        
+        assert not result.allowed
+    
+    def test_engine_disabled(self):
+        """Test disabled engine allows everything."""
+        engine = PolicyEngine(PolicyConfig(enabled=False))
+        engine.add_policy(Policy(
+            name="deny_all",
+            rules=[PolicyRule(action=PolicyAction.DENY, resource="*")]
+        ))
+        
+        result = engine.check("tool:anything", {})
+        
+        assert result.allowed
+    
+    def test_engine_check_tool(self, engine):
+        """Test check_tool helper."""
+        engine.add_policy(Policy(
+            name="deny_delete",
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.DENY,
+                    resource="tool:delete_file"
+                )
+            ]
+        ))
+        
+        result = engine.check_tool("delete_file")
+        
+        assert not result.allowed
+    
+    def test_engine_check_file(self, engine):
+        """Test check_file helper."""
+        engine.add_policy(Policy(
+            name="deny_write",
+            rules=[
+                PolicyRule(
+                    action=PolicyAction.DENY,
+                    resource="file:write"
+                )
+            ]
+        ))
+        
+        result = engine.check_file("write", "/path/to/file")
+        
+        assert not result.allowed
+    
+    def test_engine_enable_disable_policy(self, engine):
+        """Test enabling/disabling policies."""
+        engine.add_policy(Policy(name="test"))
+        
+        engine.disable_policy("test")
+        assert not engine.get_policy("test").enabled
+        
+        engine.enable_policy("test")
+        assert engine.get_policy("test").enabled
+    
+    def test_engine_clear(self, engine):
+        """Test clearing all policies."""
+        engine.add_policy(Policy(name="test1"))
+        engine.add_policy(Policy(name="test2"))
+        
+        engine.clear()
+        
+        assert len(engine.policies) == 0
+    
+    def test_engine_to_dict(self, engine):
+        """Test engine serialization."""
+        engine.add_policy(Policy(name="test"))
+        
+        data = engine.to_dict()
+        
+        assert "config" in data
+        assert "policies" in data
+        assert len(data["policies"]) == 1
+
+
+# =============================================================================
+# Convenience Function Tests
+# =============================================================================
+
+class TestConvenienceFunctions:
+    """Tests for convenience policy creation functions."""
+    
+    def test_create_deny_tools_policy(self):
+        """Test creating deny tools policy."""
+        policy = create_deny_tools_policy(
+            ["delete_*", "write_*"],
+            reason="Not allowed"
+        )
+        
+        assert policy.name == "deny_tools"
+        assert len(policy.rules) == 2
+    
+    def test_create_allow_tools_policy(self):
+        """Test creating allow tools policy."""
+        policy = create_allow_tools_policy(["read_*", "list_*"])
+        
+        assert policy.name == "allow_tools"
+        assert len(policy.rules) == 2
+    
+    def test_create_read_only_policy(self):
+        """Test creating read-only policy."""
+        policy = create_read_only_policy()
+        
+        assert policy.name == "read_only"
+        assert len(policy.rules) >= 2
+        assert policy.priority == 100
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -0,0 +1 @@
+"""Unit tests for thinking module."""
@@ -0,0 +1,355 @@
+"""
+Unit tests for the Thinking module.
+
+Tests cover:
+- ThinkingBudget creation and levels
+- ThinkingConfig settings
+- ThinkingUsage tracking
+- ThinkingTracker aggregation
+"""
+
+import pytest
+
+from praisonaiagents.thinking.budget import ThinkingBudget, BudgetLevel, BUDGET_TOKENS
+from praisonaiagents.thinking.config import ThinkingConfig
+from praisonaiagents.thinking.tracker import ThinkingUsage, ThinkingTracker
+
+
+# =============================================================================
+# ThinkingBudget Tests
+# =============================================================================
+
+class TestThinkingBudget:
+    """Tests for ThinkingBudget class."""
+    
+    def test_budget_creation(self):
+        """Test creating a budget."""
+        budget = ThinkingBudget(max_tokens=10000)
+        assert budget.max_tokens == 10000
+        assert budget.adaptive
+    
+    def test_budget_from_level(self):
+        """Test creating budget from level."""
+        budget = ThinkingBudget.from_level(BudgetLevel.HIGH)
+        assert budget.max_tokens == BUDGET_TOKENS[BudgetLevel.HIGH]
+        assert budget.level == BudgetLevel.HIGH
+    
+    def test_budget_minimal(self):
+        """Test minimal budget."""
+        budget = ThinkingBudget.minimal()
+        assert budget.max_tokens == 2000
+    
+    def test_budget_low(self):
+        """Test low budget."""
+        budget = ThinkingBudget.low()
+        assert budget.max_tokens == 4000
+    
+    def test_budget_medium(self):
+        """Test medium budget."""
+        budget = ThinkingBudget.medium()
+        assert budget.max_tokens == 8000
+    
+    def test_budget_high(self):
+        """Test high budget."""
+        budget = ThinkingBudget.high()
+        assert budget.max_tokens == 16000
+    
+    def test_budget_maximum(self):
+        """Test maximum budget."""
+        budget = ThinkingBudget.maximum()
+        assert budget.max_tokens == 32000
+    
+    def test_budget_complexity_scaling(self):
+        """Test complexity-based token scaling."""
+        budget = ThinkingBudget(
+            max_tokens=10000,
+            min_tokens=2000,
+            adaptive=True
+        )
+        
+        # Low complexity
+        tokens_low = budget.get_tokens_for_complexity(0.0)
+        assert tokens_low == 2000
+        
+        # High complexity
+        tokens_high = budget.get_tokens_for_complexity(1.0)
+        assert tokens_high == 10000
+        
+        # Medium complexity
+        tokens_mid = budget.get_tokens_for_complexity(0.5)
+        assert 2000 < tokens_mid < 10000
+    
+    def test_budget_non_adaptive(self):
+        """Test non-adaptive budget."""
+        budget = ThinkingBudget(
+            max_tokens=10000,
+            adaptive=False
+        )
+        
+        # Should always return max_tokens
+        assert budget.get_tokens_for_complexity(0.0) == 10000
+        assert budget.get_tokens_for_complexity(1.0) == 10000
+    
+    def test_budget_to_dict(self):
+        """Test budget serialization."""
+        budget = ThinkingBudget(
+            max_tokens=8000,
+            max_time_seconds=60.0,
+            adaptive=True
+        )
+        data = budget.to_dict()
+        
+        assert data["max_tokens"] == 8000
+        assert data["max_time_seconds"] == 60.0
+        assert data["adaptive"]
+    
+    def test_budget_from_dict(self):
+        """Test budget deserialization."""
+        data = {
+            "max_tokens": 16000,
+            "max_time_seconds": 120.0,
+            "adaptive": False,
+            "level": "high"
+        }
+        
+        budget = ThinkingBudget.from_dict(data)
+        
+        assert budget.max_tokens == 16000
+        assert budget.max_time_seconds == 120.0
+        assert not budget.adaptive
+        assert budget.level == BudgetLevel.HIGH
+
+
+# =============================================================================
+# ThinkingConfig Tests
+# =============================================================================
+
+class TestThinkingConfig:
+    """Tests for ThinkingConfig class."""
+    
+    def test_config_defaults(self):
+        """Test default configuration."""
+        config = ThinkingConfig()
+        
+        assert config.enabled
+        assert config.default_budget_tokens == 8000
+        assert config.max_budget_tokens == 32000
+        assert config.adaptive
+    
+    def test_config_custom(self):
+        """Test custom configuration."""
+        config = ThinkingConfig(
+            enabled=False,
+            default_budget_tokens=4000,
+            adaptive=False
+        )
+        
+        assert not config.enabled
+        assert config.default_budget_tokens == 4000
+        assert not config.adaptive
+
+
+# =============================================================================
+# ThinkingUsage Tests
+# =============================================================================
+
+class TestThinkingUsage:
+    """Tests for ThinkingUsage class."""
+    
+    def test_usage_creation(self):
+        """Test creating usage."""
+        usage = ThinkingUsage(
+            budget_tokens=8000,
+            tokens_used=4000
+        )
+        
+        assert usage.budget_tokens == 8000
+        assert usage.tokens_used == 4000
+    
+    def test_usage_tokens_remaining(self):
+        """Test tokens remaining calculation."""
+        usage = ThinkingUsage(
+            budget_tokens=8000,
+            tokens_used=3000
+        )
+        
+        assert usage.tokens_remaining == 5000
+    
+    def test_usage_tokens_remaining_over_budget(self):
+        """Test tokens remaining when over budget."""
+        usage = ThinkingUsage(
+            budget_tokens=8000,
+            tokens_used=10000
+        )
+        
+        assert usage.tokens_remaining == 0
+    
+    def test_usage_time_remaining(self):
+        """Test time remaining calculation."""
+        usage = ThinkingUsage(
+            budget_time=60.0,
+            time_seconds=20.0
+        )
+        
+        assert usage.time_remaining == 40.0
+    
+    def test_usage_time_remaining_no_budget(self):
+        """Test time remaining with no budget."""
+        usage = ThinkingUsage()
+        
+        assert usage.time_remaining is None
+    
+    def test_usage_token_utilization(self):
+        """Test token utilization calculation."""
+        usage = ThinkingUsage(
+            budget_tokens=8000,
+            tokens_used=4000
+        )
+        
+        assert usage.token_utilization == 0.5
+    
+    def test_usage_is_over_budget(self):
+        """Test over budget detection."""
+        usage = ThinkingUsage(
+            budget_tokens=8000,
+            tokens_used=10000
+        )
+        
+        assert usage.is_over_budget
+    
+    def test_usage_is_not_over_budget(self):
+        """Test not over budget."""
+        usage = ThinkingUsage(
+            budget_tokens=8000,
+            tokens_used=4000
+        )
+        
+        assert not usage.is_over_budget
+    
+    def test_usage_is_over_time(self):
+        """Test over time detection."""
+        usage = ThinkingUsage(
+            budget_time=60.0,
+            time_seconds=90.0
+        )
+        
+        assert usage.is_over_time
+    
+    def test_usage_to_dict(self):
+        """Test usage serialization."""
+        usage = ThinkingUsage(
+            budget_tokens=8000,
+            tokens_used=4000,
+            time_seconds=30.0
+        )
+        data = usage.to_dict()
+        
+        assert data["budget_tokens"] == 8000
+        assert data["tokens_used"] == 4000
+        assert data["token_utilization"] == 0.5
+
+
+# =============================================================================
+# ThinkingTracker Tests
+# =============================================================================
+
+class TestThinkingTracker:
+    """Tests for ThinkingTracker class."""
+    
+    @pytest.fixture
+    def tracker(self):
+        """Create a test tracker."""
+        return ThinkingTracker()
+    
+    def test_tracker_creation(self, tracker):
+        """Test creating a tracker."""
+        assert tracker.session_count == 0
+        assert tracker.total_tokens_used == 0
+    
+    def test_tracker_start_session(self, tracker):
+        """Test starting a session."""
+        usage = tracker.start_session(
+            budget_tokens=8000,
+            complexity=0.7
+        )
+        
+        assert usage.budget_tokens == 8000
+        assert usage.complexity == 0.7
+        assert tracker.session_count == 1
+    
+    def test_tracker_end_session(self, tracker):
+        """Test ending a session."""
+        usage = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage, tokens_used=5000, time_seconds=30.0)
+        
+        assert usage.tokens_used == 5000
+        assert usage.time_seconds == 30.0
+        assert tracker.total_tokens_used == 5000
+        assert tracker.total_time_seconds == 30.0
+    
+    def test_tracker_multiple_sessions(self, tracker):
+        """Test multiple sessions."""
+        usage1 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage1, tokens_used=4000, time_seconds=20.0)
+        
+        usage2 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage2, tokens_used=6000, time_seconds=40.0)
+        
+        assert tracker.session_count == 2
+        assert tracker.total_tokens_used == 10000
+        assert tracker.total_time_seconds == 60.0
+    
+    def test_tracker_average_tokens(self, tracker):
+        """Test average tokens calculation."""
+        usage1 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage1, tokens_used=4000, time_seconds=20.0)
+        
+        usage2 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage2, tokens_used=6000, time_seconds=40.0)
+        
+        assert tracker.average_tokens_per_session == 5000
+    
+    def test_tracker_average_time(self, tracker):
+        """Test average time calculation."""
+        usage1 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage1, tokens_used=4000, time_seconds=20.0)
+        
+        usage2 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage2, tokens_used=6000, time_seconds=40.0)
+        
+        assert tracker.average_time_per_session == 30.0
+    
+    def test_tracker_over_budget_count(self, tracker):
+        """Test over budget counting."""
+        usage1 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage1, tokens_used=4000, time_seconds=20.0)
+        
+        usage2 = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage2, tokens_used=10000, time_seconds=40.0)
+        
+        assert tracker.over_budget_count == 1
+    
+    def test_tracker_get_summary(self, tracker):
+        """Test summary generation."""
+        usage = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage, tokens_used=4000, time_seconds=20.0)
+        
+        summary = tracker.get_summary()
+        
+        assert summary["session_count"] == 1
+        assert summary["total_tokens_used"] == 4000
+        assert "average_utilization" in summary
+    
+    def test_tracker_clear(self, tracker):
+        """Test clearing tracker."""
+        usage = tracker.start_session(budget_tokens=8000)
+        tracker.end_session(usage, tokens_used=4000, time_seconds=20.0)
+        
+        tracker.clear()
+        
+        assert tracker.session_count == 0
+        assert tracker.total_tokens_used == 0
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
@@ -2422,7 +2422,7 @@ wheels = [

 [[package]]
 name = "praisonaiagents"
-version = "0.1.24"
+version = "0.2.2"
 source = { editable = "." }
 dependencies = [
    { name = "aiohttp" },
@@ -261,6 +261,12 @@ npm install praisonai
 | ↳ 100+ LLM Support | [Example](examples/python/providers/openai/openai_gpt4_example.py) | [📖](https://docs.praison.ai/models) |
 | ↳ Callback Agents | [Example](examples/python/general/advanced-callback-systems.py) | [📖](https://docs.praison.ai/features/callbacks) |
 | ↳ Hooks | [Example](#9-hooks) | [📖](https://docs.praison.ai/features/hooks) |
+| ↳ Shadow Git Checkpoints | [Example](#10-shadow-git-checkpoints) | [📖](https://docs.praison.ai/features/checkpoints) |
+| ↳ Background Tasks | [Example](examples/background/basic_background.py) | [📖](https://docs.praison.ai/features/background-tasks) |
+| ↳ Policy Engine | [Example](examples/policy/basic_policy.py) | [📖](https://docs.praison.ai/features/policy-engine) |
+| ↳ Thinking Budgets | [Example](examples/thinking/basic_thinking.py) | [📖](https://docs.praison.ai/features/thinking-budgets) |
+| ↳ Output Styles | [Example](examples/output/basic_output.py) | [📖](https://docs.praison.ai/features/output-styles) |
+| ↳ Context Compaction | [Example](examples/compaction/basic_compaction.py) | [📖](https://docs.praison.ai/features/context-compaction) |
 | **📊 Monitoring & Management** | | |
 | ↳ Sessions Management | [Example](examples/python/sessions/comprehensive-session-management.py) | [📖](https://docs.praison.ai/features/sessions) |
 | ↳ Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/docs/cli/session) |
@@ -278,6 +284,12 @@ npm install praisonai
 | ↳ Git Integration | [Example](examples/python/cli/git_integration_example.py) | [📖](https://docs.praison.ai/docs/cli/git-integration) |
 | ↳ Sandbox Execution | [Example](examples/python/cli/sandbox_execution_example.py) | [📖](https://docs.praison.ai/docs/cli/sandbox-execution) |
 | ↳ CLI Compare | [Example](examples/compare/cli_compare_basic.py) | [📖](https://docs.praison.ai/docs/cli/compare) |
+| ↳ Profile/Benchmark | [Example](#profile-benchmark) | [📖](https://docs.praison.ai/docs/cli/profile) |
+| ↳ Auto Mode | [Example](#auto-mode) | [📖](https://docs.praison.ai/docs/cli/auto) |
+| ↳ Init | [Example](#init) | [📖](https://docs.praison.ai/docs/cli/init) |
+| ↳ File Input | [Example](#file-input) | [📖](https://docs.praison.ai/docs/cli/file-input) |
+| ↳ Final Agent | [Example](#final-agent) | [📖](https://docs.praison.ai/docs/cli/final-agent) |
+| ↳ Max Tokens | [Example](#max-tokens) | [📖](https://docs.praison.ai/docs/cli/max-tokens) |
 | **🧪 Evaluation** | | |
 | ↳ Accuracy Evaluation | [Example](examples/eval/accuracy_example.py) | [📖](https://docs.praison.ai/docs/cli/eval) |
 | ↳ Performance Evaluation | [Example](examples/eval/performance_example.py) | [📖](https://docs.praison.ai/docs/cli/eval) |
@@ -857,21 +869,258 @@ callbacks:

 ### 9. Hooks

-Configure in `.praison/hooks.json`:
+Intercept and modify agent behavior at various lifecycle points:

 ```python
-from praisonaiagents.memory import HooksManager
+from praisonaiagents.hooks import (
+    HookRegistry, HookRunner, HookEvent, HookResult,
+    BeforeToolInput
+)

-hooks = HooksManager()
+# Create a hook registry
+registry = HookRegistry()

-# Register Python hooks
-hooks.register("pre_write_code", lambda ctx: print(f"Writing {ctx['file']}"))
+# Log all tool calls
+@registry.on(HookEvent.BEFORE_TOOL)
+def log_tools(event_data: BeforeToolInput) -> HookResult:
+    print(f"Tool: {event_data.tool_name}")
+    return HookResult.allow()
+
+# Block dangerous operations
+@registry.on(HookEvent.BEFORE_TOOL)
+def security_check(event_data: BeforeToolInput) -> HookResult:
+    if "delete" in event_data.tool_name.lower():
+        return HookResult.deny("Delete operations blocked")
+    return HookResult.allow()

 # Execute hooks
-result = hooks.execute("pre_write_code", {"file": "main.py"})
+runner = HookRunner(registry)
 ```

-### 10. Field Names Reference (A-I-G-S)
+**CLI Commands:**
+```bash
+praisonai hooks list                    # List registered hooks
+praisonai hooks test before_tool        # Test hooks for an event
+praisonai hooks run "echo test"         # Run a command hook
+praisonai hooks validate hooks.json     # Validate configuration
+```
+
+
+### 10. Shadow Git Checkpoints
+
+File-level undo/restore using shadow git:
+
+```python
+from praisonaiagents.checkpoints import CheckpointService
+
+service = CheckpointService(workspace_dir="./my_project")
+await service.initialize()
+
+# Save checkpoint before changes
+result = await service.save("Before refactoring")
+
+# Make changes...
+
+# Restore if needed
+await service.restore(result.checkpoint.id)
+
+# View diff
+diff = await service.diff()
+```
+
+**CLI Commands:**
+```bash
+praisonai checkpoint save "Before changes"  # Save checkpoint
+praisonai checkpoint list                   # List checkpoints
+praisonai checkpoint diff                   # Show changes
+praisonai checkpoint restore abc123         # Restore to checkpoint
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/checkpoints)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/checkpoint)
+- [💻 Example](examples/checkpoints/basic_checkpoints.py)
+
+---
+
+### 11. Background Tasks
+
+Run agent tasks asynchronously without blocking:
+
+```python
+import asyncio
+from praisonaiagents.background import BackgroundRunner, BackgroundConfig
+
+async def main():
+    config = BackgroundConfig(max_concurrent_tasks=3)
+    runner = BackgroundRunner(config=config)
+    
+    async def my_task(name: str) -> str:
+        await asyncio.sleep(2)
+        return f"Task {name} completed"
+    
+    task = await runner.submit(my_task, args=("example",), name="my_task")
+    await task.wait(timeout=10.0)
+    print(task.result)
+
+asyncio.run(main())
+```
+
+**CLI Commands:**
+```bash
+praisonai background list          # List running tasks
+praisonai background status <id>   # Check task status
+praisonai background cancel <id>   # Cancel a task
+praisonai background clear         # Clear completed tasks
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/background-tasks)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/background)
+- [💻 Example](examples/background/basic_background.py)
+
+---
+
+### 12. Policy Engine
+
+Control what agents can and cannot do with policy-based execution:
+
+```python
+from praisonaiagents.policy import (
+    PolicyEngine, Policy, PolicyRule, PolicyAction
+)
+
+engine = PolicyEngine()
+
+policy = Policy(
+    name="no_delete",
+    rules=[
+        PolicyRule(
+            action=PolicyAction.DENY,
+            resource="tool:delete_*",
+            reason="Delete operations blocked"
+        )
+    ]
+)
+engine.add_policy(policy)
+
+result = engine.check("tool:delete_file", {})
+print(f"Allowed: {result.allowed}")
+```
+
+**CLI Commands:**
+```bash
+praisonai policy list                  # List policies
+praisonai policy check "tool:name"     # Check if allowed
+praisonai policy init                  # Create template
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/policy-engine)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/policy)
+- [💻 Example](examples/policy/basic_policy.py)
+
+---
+
+### 13. Thinking Budgets
+
+Configure token budgets for extended thinking:
+
+```python
+from praisonaiagents.thinking import ThinkingBudget, ThinkingTracker
+
+# Use predefined levels
+budget = ThinkingBudget.high()  # 16,000 tokens
+
+# Track usage
+tracker = ThinkingTracker()
+session = tracker.start_session(budget_tokens=16000)
+tracker.end_session(session, tokens_used=12000)
+
+summary = tracker.get_summary()
+print(f"Utilization: {summary['average_utilization']:.1%}")
+```
+
+**CLI Commands:**
+```bash
+praisonai thinking status      # Show current budget
+praisonai thinking set high    # Set budget level
+praisonai thinking stats       # Show usage statistics
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/thinking-budgets)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/thinking)
+- [💻 Example](examples/thinking/basic_thinking.py)
+
+---
+
+### 14. Output Styles
+
+Configure how agents format their responses:
+
+```python
+from praisonaiagents.output import OutputStyle, OutputFormatter
+
+# Use preset styles
+style = OutputStyle.concise()
+formatter = OutputFormatter(style)
+
+# Format output
+text = "# Hello\n\nThis is **bold** text."
+plain = formatter.format(text)
+print(plain)
+```
+
+**CLI Commands:**
+```bash
+praisonai output status        # Show current style
+praisonai output set concise   # Set output style
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/output-styles)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/output-style)
+- [💻 Example](examples/output/basic_output.py)
+
+---
+
+### 15. Context Compaction
+
+Automatically manage context window size:
+
+```python
+from praisonaiagents.compaction import (
+    ContextCompactor, CompactionStrategy
+)
+
+compactor = ContextCompactor(
+    max_tokens=4000,
+    strategy=CompactionStrategy.SLIDING,
+    preserve_recent=3
+)
+
+messages = [...]  # Your conversation history
+compacted, result = compactor.compact(messages)
+
+print(f"Compression: {result.compression_ratio:.1%}")
+```
+
+**CLI Commands:**
+```bash
+praisonai compaction status        # Show settings
+praisonai compaction set sliding   # Set strategy
+praisonai compaction stats         # Show statistics
+```
+
+**Links:**
+- [📖 Coding Docs](https://docs.praison.ai/features/context-compaction)
+- [📖 CLI Docs](https://docs.praison.ai/docs/cli/compaction)
+- [💻 Example](examples/compaction/basic_compaction.py)
+
+---
+
+### 16. Field Names Reference (A-I-G-S)

 PraisonAI accepts both old (agents.yaml) and new (workflow.yaml) field names. Use the **canonical names** for new projects:

@@ -905,7 +1154,7 @@ steps:                         # Define steps (not 'tasks')

 > **Note:** The parser accepts both old and new names. Run `praisonai workflow validate <file.yaml>` to see suggestions for canonical names.

-### 11. Extended agents.yaml with Workflow Patterns
+### 12. Extended agents.yaml with Workflow Patterns

 **Feature Parity:** Both `agents.yaml` and `workflow.yaml` now support the same features:
 - All workflow patterns (route, parallel, loop, repeat)
@@ -981,6 +1230,124 @@ Run with the same simple command:
 praisonai agents.yaml
 ```

+### 12. MCP (Model Context Protocol)
+
+PraisonAI supports MCP Protocol Revision 2025-11-25 with multiple transports.
+
+#### MCP Client (Consume MCP Servers)
+```python
+from praisonaiagents import Agent, MCP
+
+# stdio - Local NPX/Python servers
+agent = Agent(tools=MCP("npx @modelcontextprotocol/server-memory"))
+
+# Streamable HTTP - Production servers
+agent = Agent(tools=MCP("https://api.example.com/mcp"))
+
+# WebSocket - Real-time bidirectional
+agent = Agent(tools=MCP("wss://api.example.com/mcp", auth_token="token"))
+
+# SSE (Legacy) - Backward compatibility
+agent = Agent(tools=MCP("http://localhost:8080/sse"))
+
+# With environment variables
+agent = Agent(
+    tools=MCP(
+        command="npx",
+        args=["-y", "@modelcontextprotocol/server-brave-search"],
+        env={"BRAVE_API_KEY": "your-key"}
+    )
+)
+
+# Multiple MCP servers + regular functions
+def my_custom_tool(query: str) -> str:
+    """Custom tool function."""
+    return f"Result: {query}"
+
+agent = Agent(
+    name="MultiToolAgent",
+    instructions="Agent with multiple MCP servers",
+    tools=[
+        MCP("uvx mcp-server-time"),                    # Time tools
+        MCP("npx @modelcontextprotocol/server-memory"), # Memory tools
+        my_custom_tool                                  # Regular function
+    ]
+)
+```
+
+#### MCP Server (Expose Tools as MCP Server)
+
+Expose your Python functions as MCP tools for Claude Desktop, Cursor, and other MCP clients:
+
+```python
+from praisonaiagents.mcp import ToolsMCPServer
+
+def search_web(query: str, max_results: int = 5) -> dict:
+    """Search the web for information."""
+    return {"results": [f"Result for {query}"]}
+
+def calculate(expression: str) -> dict:
+    """Evaluate a mathematical expression."""
+    return {"result": eval(expression)}
+
+# Create and run MCP server
+server = ToolsMCPServer(name="my-tools")
+server.register_tools([search_web, calculate])
+server.run()  # stdio for Claude Desktop
+# server.run_sse(host="0.0.0.0", port=8080)  # SSE for web clients
+```
+
+#### MCP Features
+| Feature | Description |
+|---------|-------------|
+| Session Management | Automatic Mcp-Session-Id handling |
+| Protocol Versioning | Mcp-Protocol-Version header |
+| Resumability | SSE stream recovery via Last-Event-ID |
+| Security | Origin validation, DNS rebinding prevention |
+| WebSocket | Auto-reconnect with exponential backoff |
+
+### 13. A2A (Agent2Agent Protocol)
+
+PraisonAI supports the [A2A Protocol](https://a2a-protocol.org) for agent-to-agent communication, enabling your agents to be discovered and collaborate with other AI agents.
+
+#### A2A Server (Expose Agent as A2A Server)
+```python
+from praisonaiagents import Agent, A2A
+from fastapi import FastAPI
+
+# Create an agent with tools
+def search_web(query: str) -> str:
+    """Search the web for information."""
+    return f"Results for: {query}"
+
+agent = Agent(
+    name="Research Assistant",
+    role="Research Analyst",
+    goal="Help users research topics",
+    tools=[search_web]
+)
+
+# Expose as A2A Server
+a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
+
+app = FastAPI()
+app.include_router(a2a.get_router())
+
+# Run: uvicorn app:app --reload
+# Agent Card: GET /.well-known/agent.json
+# Status: GET /status
+```
+
+#### A2A Features
+| Feature | Description |
+|---------|-------------|
+| Agent Card | JSON metadata for agent discovery |
+| Skills Extraction | Auto-generate skills from tools |
+| Task Management | Stateful task lifecycle |
+| Streaming | SSE streaming for real-time updates |
+
+> **Documentation**: [docs.praison.ai/a2a](https://docs.praison.ai/a2a) | **Examples**: [examples/python/a2a](https://github.com/MervinPraison/PraisonAI/tree/main/examples/python/a2a)
+
 ---

 ## 🎯 CLI / No-Code Interface
@@ -1730,124 +2097,6 @@ agent = Agent(
 | Web Fetch | Anthropic |
 | Prompt Caching | OpenAI (auto), Anthropic, Bedrock, Deepseek |

-## MCP (Model Context Protocol)
-
-PraisonAI supports MCP Protocol Revision 2025-11-25 with multiple transports.
-
-### MCP Client (Consume MCP Servers)
-```python
-from praisonaiagents import Agent, MCP
-
-# stdio - Local NPX/Python servers
-agent = Agent(tools=MCP("npx @modelcontextprotocol/server-memory"))
-
-# Streamable HTTP - Production servers
-agent = Agent(tools=MCP("https://api.example.com/mcp"))
-
-# WebSocket - Real-time bidirectional
-agent = Agent(tools=MCP("wss://api.example.com/mcp", auth_token="token"))
-
-# SSE (Legacy) - Backward compatibility
-agent = Agent(tools=MCP("http://localhost:8080/sse"))
-
-# With environment variables
-agent = Agent(
-    tools=MCP(
-        command="npx",
-        args=["-y", "@modelcontextprotocol/server-brave-search"],
-        env={"BRAVE_API_KEY": "your-key"}
-    )
-)
-
-# Multiple MCP servers + regular functions
-def my_custom_tool(query: str) -> str:
-    """Custom tool function."""
-    return f"Result: {query}"
-
-agent = Agent(
-    name="MultiToolAgent",
-    instructions="Agent with multiple MCP servers",
-    tools=[
-        MCP("uvx mcp-server-time"),                    # Time tools
-        MCP("npx @modelcontextprotocol/server-memory"), # Memory tools
-        my_custom_tool                                  # Regular function
-    ]
-)
-```
-
-### MCP Server (Expose Tools as MCP Server)
-
-Expose your Python functions as MCP tools for Claude Desktop, Cursor, and other MCP clients:
-
-```python
-from praisonaiagents.mcp import ToolsMCPServer
-
-def search_web(query: str, max_results: int = 5) -> dict:
-    """Search the web for information."""
-    return {"results": [f"Result for {query}"]}
-
-def calculate(expression: str) -> dict:
-    """Evaluate a mathematical expression."""
-    return {"result": eval(expression)}
-
-# Create and run MCP server
-server = ToolsMCPServer(name="my-tools")
-server.register_tools([search_web, calculate])
-server.run()  # stdio for Claude Desktop
-# server.run_sse(host="0.0.0.0", port=8080)  # SSE for web clients
-```
-
-### MCP Features
-| Feature | Description |
-|---------|-------------|
-| Session Management | Automatic Mcp-Session-Id handling |
-| Protocol Versioning | Mcp-Protocol-Version header |
-| Resumability | SSE stream recovery via Last-Event-ID |
-| Security | Origin validation, DNS rebinding prevention |
-| WebSocket | Auto-reconnect with exponential backoff |
-
-## A2A (Agent2Agent Protocol)
-
-PraisonAI supports the [A2A Protocol](https://a2a-protocol.org) for agent-to-agent communication, enabling your agents to be discovered and collaborate with other AI agents.
-
-### A2A Server (Expose Agent as A2A Server)
-```python
-from praisonaiagents import Agent, A2A
-from fastapi import FastAPI
-
-# Create an agent with tools
-def search_web(query: str) -> str:
-    """Search the web for information."""
-    return f"Results for: {query}"
-
-agent = Agent(
-    name="Research Assistant",
-    role="Research Analyst",
-    goal="Help users research topics",
-    tools=[search_web]
-)
-
-# Expose as A2A Server
-a2a = A2A(agent=agent, url="http://localhost:8000/a2a")
-
-app = FastAPI()
-app.include_router(a2a.get_router())
-
-# Run: uvicorn app:app --reload
-# Agent Card: GET /.well-known/agent.json
-# Status: GET /status
-```
-
-### A2A Features
-| Feature | Description |
-|---------|-------------|
-| Agent Card | JSON metadata for agent discovery |
-| Skills Extraction | Auto-generate skills from tools |
-| Task Management | Stateful task lifecycle |
-| Streaming | SSE streaming for real-time updates |
-
-> **Documentation**: [docs.praison.ai/a2a](https://docs.praison.ai/a2a) | **Examples**: [examples/python/a2a](https://github.com/MervinPraison/PraisonAI/tree/main/examples/python/a2a)
-
 ## CLI Features

 | Feature | Docs |
@@ -2475,6 +2724,103 @@ PraisonAI provides zero-dependency persistent memory for agents. For detailed ex

 ---

+## 💾 Persistence (Databases)
+
+Enable automatic conversation persistence with 2 lines of code:
+
+```python
+from praisonaiagents import Agent, db
+
+agent = Agent(
+    name="Assistant",
+    db=db(database_url="postgresql://localhost/mydb"),  # db(...) shortcut
+    session_id="my-session"  # Optional: defaults to per-hour ID (YYYYMMDDHH)
+)
+agent.chat("Hello!")  # Auto-persists messages, runs, traces
+```
+
+### Persistence CLI Commands
+
+| Command | Description |
+|---------|-------------|
+| `praisonai persistence doctor` | Validate DB connectivity |
+| `praisonai persistence run` | Run agent with persistence |
+| `praisonai persistence resume` | Resume existing session |
+| `praisonai persistence export` | Export session to JSONL |
+| `praisonai persistence import` | Import session from JSONL |
+| `praisonai persistence migrate` | Apply schema migrations |
+| `praisonai persistence status` | Show schema status |
+
+### Databases Table
+
+| Database | Store Type | Install | Example | Docs |
+|----------|------------|---------|---------|------|
+| PostgreSQL | Conversation | `pip install "praisonai[tools]"` | [simple_db_agent.py](examples/persistence/simple_db_agent.py) | [docs](https://docs.praison.ai/docs/databases/postgres) |
+| MySQL | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| SQLite | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| SingleStore | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Supabase | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| SurrealDB | Conversation | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Qdrant | Knowledge | `pip install "praisonai[tools]"` | [knowledge_qdrant.py](examples/persistence/knowledge_qdrant.py) | [docs](https://docs.praison.ai/docs/databases/qdrant) |
+| ChromaDB | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Pinecone | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Weaviate | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| LanceDB | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Milvus | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| PGVector | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Redis Vector | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Cassandra | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| ClickHouse | Knowledge | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Redis | State | `pip install "praisonai[tools]"` | [state_redis.py](examples/persistence/state_redis.py) | [docs](https://docs.praison.ai/docs/databases/redis) |
+| MongoDB | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| DynamoDB | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Firestore | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Upstash | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+| Memory | State | `pip install "praisonai[tools]"` | - | [docs](https://docs.praison.ai/docs/databases/overview) |
+
+---
+
+## 🔧 Tools Table
+
+Install all tools with: `pip install "praisonai[tools]"`
+
+| Tool | Category | Import | Docs |
+|------|----------|--------|------|
+| Tavily | Web Search | `from praisonai_tools import TavilyTool` | [docs](https://docs.praison.ai/docs/tools/external/tavily) |
+| DuckDuckGo | Web Search | `from praisonai_tools import DuckDuckGoTool` | [docs](https://docs.praison.ai/docs/tools/external/duckduckgo) |
+| Exa | Web Search | `from praisonai_tools import ExaTool` | [docs](https://docs.praison.ai/docs/tools/external/exa) |
+| Serper | Web Search | `from praisonai_tools import SerperTool` | [docs](https://docs.praison.ai/docs/tools/external/serper) |
+| Jina | Web Reader | `from praisonai_tools import JinaTool` | [docs](https://docs.praison.ai/docs/tools/external/jina) |
+| Firecrawl | Web Scraping | `from praisonai_tools import FirecrawlTool` | [docs](https://docs.praison.ai/docs/tools/external/firecrawl) |
+| Crawl4AI | Web Scraping | `from praisonai_tools import Crawl4AITool` | [docs](https://docs.praison.ai/docs/tools/external/crawl4ai) |
+| Wikipedia | Knowledge | `from praisonai_tools import WikipediaTool` | [docs](https://docs.praison.ai/docs/tools/external/wikipedia) |
+| ArXiv | Research | `from praisonai_tools import ArxivTool` | [docs](https://docs.praison.ai/docs/tools/external/arxiv) |
+| HackerNews | News | `from praisonai_tools import HackerNewsTool` | [docs](https://docs.praison.ai/docs/tools/external/hackernews) |
+| YouTube | Media | `from praisonai_tools import YouTubeTool` | [docs](https://docs.praison.ai/docs/tools/external/youtube) |
+| Weather | Data | `from praisonai_tools import WeatherTool` | [docs](https://docs.praison.ai/docs/tools/external/weather) |
+| PostgreSQL | Database | `from praisonai_tools import PostgresTool` | [docs](https://docs.praison.ai/docs/tools/external/postgres) |
+| MySQL | Database | `from praisonai_tools import MySQLTool` | [docs](https://docs.praison.ai/docs/tools/external/mysql) |
+| SQLite | Database | `from praisonai_tools import SQLiteTool` | [docs](https://docs.praison.ai/docs/tools/external/sqlite) |
+| MongoDB | Database | `from praisonai_tools import MongoDBTool` | [docs](https://docs.praison.ai/docs/tools/external/mongodb) |
+| Redis | Database | `from praisonai_tools import RedisTool` | [docs](https://docs.praison.ai/docs/tools/external/redis) |
+| Qdrant | Vector DB | `from praisonai_tools import QdrantTool` | [docs](https://docs.praison.ai/docs/tools/external/qdrant) |
+| GitHub | DevOps | `from praisonai_tools import GitHubTool` | [docs](https://docs.praison.ai/docs/tools/external/github) |
+| Slack | Communication | `from praisonai_tools import SlackTool` | [docs](https://docs.praison.ai/docs/tools/external/slack) |
+| Discord | Communication | `from praisonai_tools import DiscordTool` | [docs](https://docs.praison.ai/docs/tools/external/discord) |
+| Telegram | Communication | `from praisonai_tools import TelegramTool` | [docs](https://docs.praison.ai/docs/tools/external/telegram) |
+| Email | Communication | `from praisonai_tools import EmailTool` | [docs](https://docs.praison.ai/docs/tools/external/email) |
+| Notion | Productivity | `from praisonai_tools import NotionTool` | [docs](https://docs.praison.ai/docs/tools/external/notion) |
+| File | File System | `from praisonai_tools import FileTool` | [docs](https://docs.praison.ai/docs/tools/external/file) |
+| Shell | System | `from praisonai_tools import ShellTool` | [docs](https://docs.praison.ai/docs/tools/external/shell) |
+| Python | Code | `from praisonai_tools import PythonTool` | [docs](https://docs.praison.ai/docs/tools/external/python) |
+| JSON | Data | `from praisonai_tools import JSONTool` | [docs](https://docs.praison.ai/docs/tools/external/json) |
+| CSV | Data | `from praisonai_tools import CSVTool` | [docs](https://docs.praison.ai/docs/tools/external/csv) |
+| Calculator | Math | `from praisonai_tools import CalculatorTool` | [docs](https://docs.praison.ai/docs/tools/external/calculator) |
+
+> See [full tools documentation](https://docs.praison.ai/docs/tools/tools) for all 100+ available tools.
+
+---
+
 ## 🎓 Video Tutorials

 Learn PraisonAI through our comprehensive video series:
@@ -3,8 +3,8 @@ class Praisonai < Formula
  
    desc "AI tools for various AI applications"
    homepage "https://github.com/MervinPraison/PraisonAI"
-    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.80.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.80.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.4.3.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.4.3.tar.gz | shasum -a 256`.split.first
    license "MIT"
  
    depends_on "[email protected]"
@@ -62,7 +62,7 @@ except ImportError:
 logging.basicConfig(level=os.environ.get('LOGLEVEL', 'INFO').upper(), format='%(asctime)s - %(levelname)s - %(message)s')

 # =============================================================================
-# Available Tools List (shared between generators)
+# Available Tools List (shared between generators) - Legacy for praisonai_tools
 # =============================================================================
 AVAILABLE_TOOLS = [
    "CodeDocsSearchTool", "CSVSearchTool", "DirectorySearchTool", "DOCXSearchTool",
@@ -72,6 +72,206 @@ AVAILABLE_TOOLS = [
    "YoutubeChannelSearchTool", "YoutubeVideoSearchTool"
 ]

+# =============================================================================
+# Enhanced Tool Discovery from praisonaiagents.tools
+# =============================================================================
+
+# Tool categories with their tools from praisonaiagents.tools
+TOOL_CATEGORIES = {
+    'web_search': [
+        'internet_search', 'duckduckgo', 'tavily_search', 'exa_search',
+        'search_web', 'ydc_search', 'searxng_search'
+    ],
+    'web_scraping': [
+        'scrape_page', 'extract_links', 'crawl', 'extract_text',
+        'crawl4ai', 'crawl4ai_extract', 'get_article'
+    ],
+    'file_operations': [
+        'read_file', 'write_file', 'list_files', 'get_file_info',
+        'copy_file', 'move_file', 'delete_file'
+    ],
+    'code_execution': [
+        'execute_command', 'execute_code', 'analyze_code', 'format_code'
+    ],
+    'data_processing': [
+        'read_csv', 'write_csv', 'analyze_csv', 'read_json', 'write_json',
+        'read_excel', 'write_excel', 'read_yaml', 'write_yaml', 'read_xml'
+    ],
+    'research': [
+        'search_arxiv', 'get_arxiv_paper', 'wiki_search', 'wiki_summary',
+        'get_news_sources', 'get_trending_topics'
+    ],
+    'finance': [
+        'get_stock_price', 'get_stock_info', 'get_historical_data'
+    ],
+    'math': [
+        'evaluate', 'solve_equation', 'convert_units', 'calculate_statistics'
+    ],
+    'database': [
+        'query', 'create_table', 'load_data', 'find_documents', 'vector_search'
+    ]
+}
+
+# Keywords that map to tool categories
+TASK_KEYWORD_TO_TOOLS = {
+    # Web search keywords
+    'search': 'web_search',
+    'find': 'web_search',
+    'look up': 'web_search',
+    'google': 'web_search',
+    'internet': 'web_search',
+    'online': 'web_search',
+    'web': 'web_search',
+    
+    # Web scraping keywords
+    'scrape': 'web_scraping',
+    'crawl': 'web_scraping',
+    'extract from website': 'web_scraping',
+    'get from url': 'web_scraping',
+    'fetch page': 'web_scraping',
+    
+    # File operation keywords
+    'read file': 'file_operations',
+    'write file': 'file_operations',
+    'save': 'file_operations',
+    'load': 'file_operations',
+    'open file': 'file_operations',
+    'create file': 'file_operations',
+    
+    # Code execution keywords
+    'execute': 'code_execution',
+    'run code': 'code_execution',
+    'python': 'code_execution',
+    'script': 'code_execution',
+    'command': 'code_execution',
+    'shell': 'code_execution',
+    
+    # Data processing keywords
+    'csv': 'data_processing',
+    'excel': 'data_processing',
+    'json': 'data_processing',
+    'yaml': 'data_processing',
+    'xml': 'data_processing',
+    'data': 'data_processing',
+    'spreadsheet': 'data_processing',
+    
+    # Research keywords
+    'research': 'research',
+    'paper': 'research',
+    'arxiv': 'research',
+    'wikipedia': 'research',
+    'academic': 'research',
+    'news': 'research',
+    
+    # Finance keywords
+    'stock': 'finance',
+    'price': 'finance',
+    'market': 'finance',
+    'financial': 'finance',
+    'trading': 'finance',
+    
+    # Math keywords
+    'calculate': 'math',
+    'math': 'math',
+    'equation': 'math',
+    'compute': 'math',
+    'statistics': 'math',
+    
+    # Database keywords
+    'database': 'database',
+    'sql': 'database',
+    'query': 'database',
+    'mongodb': 'database',
+    'vector': 'database'
+}
+
+
+def get_all_available_tools() -> Dict[str, List[str]]:
+    """
+    Get all available tools organized by category.
+    
+    Returns:
+        Dict mapping category names to lists of tool names
+    """
+    return TOOL_CATEGORIES.copy()
+
+
+def get_tools_for_task(task_description: str) -> List[str]:
+    """
+    Analyze a task description and return appropriate tools.
+    
+    Args:
+        task_description: The task to analyze
+        
+    Returns:
+        List of tool names appropriate for the task
+    """
+    task_lower = task_description.lower()
+    matched_categories = set()
+    
+    # Match keywords to categories
+    for keyword, category in TASK_KEYWORD_TO_TOOLS.items():
+        if keyword in task_lower:
+            matched_categories.add(category)
+    
+    # Collect tools from matched categories
+    tools = []
+    for category in matched_categories:
+        if category in TOOL_CATEGORIES:
+            tools.extend(TOOL_CATEGORIES[category])
+    
+    # Always include core tools for flexibility
+    core_tools = ['read_file', 'write_file', 'execute_command']
+    for tool in core_tools:
+        if tool not in tools:
+            tools.append(tool)
+    
+    # Remove duplicates while preserving order
+    seen = set()
+    unique_tools = []
+    for tool in tools:
+        if tool not in seen:
+            seen.add(tool)
+            unique_tools.append(tool)
+    
+    return unique_tools
+
+
+def recommend_agent_count(task_description: str) -> int:
+    """
+    Recommend the optimal number of agents based on task complexity.
+    
+    Args:
+        task_description: The task to analyze
+        
+    Returns:
+        Recommended number of agents (1-4)
+    """
+    complexity = BaseAutoGenerator.analyze_complexity(task_description)
+    
+    if complexity == 'simple':
+        return 1
+    elif complexity == 'moderate':
+        return 2
+    else:  # complex
+        # Count distinct aspects of the task
+        task_lower = task_description.lower()
+        aspects = 0
+        
+        aspect_keywords = [
+            ['research', 'search', 'find', 'gather'],
+            ['analyze', 'evaluate', 'assess', 'review'],
+            ['write', 'create', 'generate', 'produce'],
+            ['edit', 'refine', 'improve', 'polish'],
+            ['coordinate', 'manage', 'orchestrate', 'delegate']
+        ]
+        
+        for keyword_group in aspect_keywords:
+            if any(kw in task_lower for kw in keyword_group):
+                aspects += 1
+        
+        return min(max(aspects, 2), 4)  # Between 2 and 4 agents
+
 # =============================================================================
 # Base Generator Class (DRY - shared functionality)
 # =============================================================================
@@ -458,9 +658,19 @@ Tools are not available for {framework}. To use tools, install:
        
        return merged_data

+    def discover_tools_for_topic(self) -> List[str]:
+        """
+        Discover appropriate tools for the topic using intelligent matching.
+        
+        Returns:
+            List of tool names appropriate for this topic
+        """
+        return get_tools_for_task(self.topic)
+    
    def get_user_content(self):
        """
        Generates a prompt for the OpenAI API to generate a team structure.
+        Uses intelligent tool discovery based on task analysis.

        Args:
            None
@@ -484,42 +694,68 @@ Tools are not available for {framework}. To use tools, install:
        
        workflow_guidance = pattern_guidance.get(self.pattern, pattern_guidance["sequential"])
        
+        # Get recommended tools based on task analysis
+        recommended_tools = self.discover_tools_for_topic()
+        recommended_agent_count = recommend_agent_count(self.topic)
+        complexity = self.analyze_complexity(self.topic)
+        
+        # Build comprehensive tool list with categories
+        all_tools_by_category = []
+        for category, tools in TOOL_CATEGORIES.items():
+            all_tools_by_category.append(f"  {category}: {', '.join(tools)}")
+        tools_reference = "\n".join(all_tools_by_category)
+        
+        # Also include legacy tools for backward compatibility
+        legacy_tools = ", ".join(AVAILABLE_TOOLS)
+        
        user_content = f"""Analyze and generate a team structure for: "{self.topic}"

-STEP 1: TASK COMPLEXITY ANALYSIS
-First, analyze the task complexity:
- Is this a simple task that 1-2 agents could handle?
- Does it require multiple specialized perspectives?
- Are there clear sequential dependencies between steps?
+TASK COMPLEXITY ANALYSIS (Pre-computed):
+- Complexity: {complexity}
+- Recommended agents: {recommended_agent_count}
+- Recommended tools based on task keywords: {', '.join(recommended_tools)}
+
+STEP 1: VALIDATE TASK ANALYSIS
+Review the pre-computed analysis above. Adjust if needed based on your understanding.

 STEP 2: DETERMINE OPTIMAL TEAM SIZE
-Based on your analysis, create the minimum number of agents needed:
- Simple tasks: 1-2 agents
- Moderate tasks: 2-3 agents  
- Complex tasks: 3-4 agents (maximum)
+Based on complexity analysis:
+- Simple tasks: 1-2 agents (single focused agent or simple pair)
+- Moderate tasks: 2-3 agents (researcher + executor pattern)
+- Complex tasks: 3-4 agents (specialized team)

-IMPORTANT: Only create agents that provide meaningful specialization. Avoid unnecessary complexity.
+Recommended for this task: {recommended_agent_count} agent(s)
+
+IMPORTANT: Avoid unnecessary complexity. Only add agents if there is meaningful specialization.
+Each agent must have a distinct, non-overlapping responsibility.

 STEP 3: DESIGN THE TEAM (Pattern: {self.pattern})
 {workflow_guidance}
+
 Each agent should have:
- A clear, distinct role
+- A clear, distinct role with meaningful specialization
 - A specific goal
 - Relevant backstory
 - 1 focused task with clear description and expected output
- Appropriate tools (only if needed)
+- Appropriate tools from the recommended list

-Available Tools: CodeDocsSearchTool, CSVSearchTool, DirectorySearchTool, DOCXSearchTool, DirectoryReadTool, FileReadTool, TXTSearchTool, JSONSearchTool, MDXSearchTool, PDFSearchTool, RagTool, ScrapeElementFromWebsiteTool, ScrapeWebsiteTool, WebsiteSearchTool, XMLSearchTool, YoutubeChannelSearchTool, YoutubeVideoSearchTool.
-Only use these tools if the task requires them. Use empty list [] if no tools needed.
+AVAILABLE TOOLS BY CATEGORY:
+{tools_reference}

-Example structure (2 agents for a writing task):
+LEGACY TOOLS (for backward compatibility):
+{legacy_tools}
+
+RECOMMENDED TOOLS FOR THIS TASK: {', '.join(recommended_tools)}
+Prioritize using the recommended tools. Only add others if specifically needed.
+
+Example structure (2 agents for a research + writing task):
 {{
  "roles": {{
    "researcher": {{
      "role": "Research Analyst",
      "goal": "Gather comprehensive information on the topic",
      "backstory": "Expert researcher skilled at finding and synthesizing information.",
-      "tools": ["WebsiteSearchTool"],
+      "tools": ["internet_search", "read_file"],
      "tasks": {{
        "research_task": {{
          "description": "Research key information about the topic and compile findings.",
@@ -531,7 +767,7 @@ Example structure (2 agents for a writing task):
      "role": "Content Writer",
      "goal": "Create polished final content",
      "backstory": "Skilled writer who transforms research into engaging content.",
-      "tools": [],
+      "tools": ["write_file"],
      "tasks": {{
        "writing_task": {{
          "description": "Write the final content based on research findings.",
@@ -543,6 +779,7 @@ Example structure (2 agents for a writing task):
 }}

 Now generate the optimal team structure for: {self.topic}
+Use the recommended tools: {', '.join(recommended_tools)}
 """
        return user_content

@@ -29,6 +29,9 @@ Features:
 - at_mentions: @ mention autocomplete for files and directories
 - compare: CLI command comparison feature
 - eval: Agent evaluation framework (accuracy, performance, reliability, criteria)
+- hooks: Hook system for intercepting and modifying agent behavior
+- checkpoints: Shadow git checkpointing for file-level undo/restore
+- background: Background agent task execution and management
 """

 # Type hints available for IDE support
@@ -71,6 +74,12 @@ __all__ = [
    'CompareHandler',
    # Agent Skills
    'SkillsHandler',
+    # Hooks
+    'HooksHandler',
+    # Checkpoints
+    'CheckpointsHandler',
+    # Background
+    'BackgroundHandler',
 ]

 def __getattr__(name):
@@ -170,4 +179,13 @@ def __getattr__(name):
    elif name == 'SkillsHandler':
        from .skills import SkillsHandler
        return SkillsHandler
+    elif name == 'HooksHandler':
+        from .hooks import HooksHandler
+        return HooksHandler
+    elif name == 'CheckpointsHandler':
+        from .checkpoints import CheckpointsHandler
+        return CheckpointsHandler
+    elif name == 'BackgroundHandler':
+        from .background import BackgroundHandler
+        return BackgroundHandler
    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
Author	SHA1	Message	Date
Mervin Praison	aba2265e5e	Release v2.4.3	2025-12-26 01:01:30 +00:00
Mervin Praison	ebb9b24bff	Release v2.4.2	2025-12-25 00:29:49 +00:00
Mervin Praison	759ef2c655	Update database initialization to use db() shortcut and expand tools table with 100+ tools	2025-12-25 00:24:48 +00:00
Mervin Praison	cb4318f6e8	Release v2.4.1	2025-12-24 15:00:45 +00:00
Mervin Praison	d9bb869d5e	Add documentation for 6 new features: Shadow Git Checkpoints, Background Tasks, Policy Engine, Thinking Budgets, Output Styles, and Context Compaction	2025-12-24 08:02:48 +00:00
Mervin Praison	34b6aeb76b	Release v2.4.0	2025-12-24 07:47:53 +00:00
Mervin Praison	078b7801e1	Add 'response' field to workflow API for consistency with single-agent endpoint	2025-12-23 17:50:07 +00:00
Mervin Praison	a970e849b4	Release v2.3.87	2025-12-23 16:08:35 +00:00
Mervin Praison	8e68f4e71c	Release v2.3.86	2025-12-23 15:23:31 +00:00
Mervin Praison	308758cdc2	Release v2.3.85	2025-12-23 15:07:46 +00:00
Mervin Praison	f8fa61b082	Release v2.3.84	2025-12-23 14:57:15 +00:00
Mervin Praison	955d236924	Release v2.3.84	2025-12-23 13:20:08 +00:00
Mervin Praison	d9d63c3a13	Release v2.3.83	2025-12-23 13:06:42 +00:00
Mervin Praison	5bee6eb470	Release v2.3.83	2025-12-23 11:42:47 +00:00
Mervin Praison	7cb1676b7c	Release v2.3.82	2025-12-23 09:41:09 +00:00
Mervin Praison	e2e9c3f9ee	Release v2.3.81	2025-12-23 08:11:31 +00:00