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app/agent_factory.py

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+import logging
+from typing import Optional, List, Callable, Dict, Any, Union
+
+from google.adk.agents.llm_agent import LlmAgent, Agent
+from google.adk.models.lite_llm import LiteLlm
+from google.adk.planners import BuiltInPlanner
+from google.adk.code_executors import BuiltInCodeExecutor
+from google.genai import types
+
+from app.config import settings
+from app.models import AgentConfig, LLMConfig, GenerationConfig
+from app.services.tool_service import get_tool_service
+
+from app.tools import TOOL_REGISTRY
+
+
+
+logger = logging.getLogger(__name__)
+
+
+# ==========================
+# 🏭 Agent Factory
+# ==========================
+
+def _create_llm_model(
+    model_name: str, 
+    llm_config: Optional[LLMConfig] = None
+) -> Union[str, LiteLlm]:
+    """
+    Create the LLM model instance or return model identifier string.
+    
+    Logic:
+    1. If model name implies Gemini (official Google model), return the string directly.
+       ADK's LlmAgent handles 'gemini-...' strings using the native google-genai SDK.
+    2. For other models (GPT, Claude, etc.), wrap in LiteLlm adapter.
+    """
+    # Normalize comparison
+    name_lower = model_name.lower()
+    
+    # Check if likely native Gemini (no provider prefix)
+    # Exclude obvious proxy prefixes that require LiteLLM (e.g. openai/gemini...)
+    provider_prefixes = ["openai/", "azure/", "anthropic/", "bedrock/", "mistral/"]
+    has_provider_prefix = any(p in name_lower for p in provider_prefixes)
+    
+    is_gemini = "gemini" in name_lower and not has_provider_prefix
+    
+    # Check if custom configuration forces a specific path
+    # If API Base is provided and distinct from default Google, usually implies using LiteLLM/Proxy 
+    # even for Gemini models (e.g. via OpenAI-compatible endpoint).
+    has_custom_base = llm_config and llm_config.api_base and "googleapis.com" not in llm_config.api_base
+    
+    if is_gemini and not has_custom_base:
+        logger.info(f"Using Native Gemini Model: {model_name}")
+        return model_name
+    
+    # Fallback / Non-Gemini -> Use LiteLLM
+    api_key = (llm_config.api_key if llm_config and llm_config.api_key else settings.LLM_API_KEY)
+    api_base = (llm_config.api_base if llm_config and llm_config.api_base else settings.LLM_API_BASE)
+    
+    logger.info(f"Using LiteLLM for: {model_name} (Base: {api_base})")
+    return LiteLlm(
+        model=model_name,
+        api_base=api_base,
+        api_key=api_key
+    )
+
+
+def create_agent(config: AgentConfig) -> Agent:
+    """
+    Create a fully configured ADK Agent based on the provided AgentConfig.
+    """
+    logger.info(f"Creating Agent: {config.name} ({config.model})")
+    
+    # 1. Model Initialization
+    # Returns either a str (for native Gemini) or LiteLlm object
+    llm = _create_llm_model(config.model, config.llm_config)
+    
+    # 2. Tools Selection
+    selected_tools = []
+    tool_service = get_tool_service()
+    
+    for tool_name in config.tools:
+        # A. Check Legacy/Hardcoded Registry
+        if tool_name in TOOL_REGISTRY:
+            selected_tools.append(TOOL_REGISTRY[tool_name])
+            continue
+            
+        # B. Check Local Tools (tools/ folder)
+        local_tool = tool_service.load_local_tool(tool_name)
+        if local_tool:
+            selected_tools.append(local_tool)
+            continue
+            
+        # C. Check MCP Servers
+        mcp_tool = tool_service.get_mcp_toolset(tool_name)
+        if mcp_tool:
+            selected_tools.append(mcp_tool)
+            continue
+            
+        logger.warning(f"Tool '{tool_name}' not found (checked Registry, Local, MCP). Skipping.")
+            
+    # 3. Code Execution
+    code_executor = None
+    if config.enable_code_execution:
+        logger.info("Enabling BuiltInCodeExecutor")
+        code_executor = BuiltInCodeExecutor()
+
+    # 4. Planner / Thinking
+    # Only applicable for models that support it (mostly Gemini)
+    planner = None
+    if config.thinking_config:
+        logger.info(f"Enabling BuiltInPlanner with budget {config.thinking_config.thinking_budget}")
+        t_config = types.ThinkingConfig(
+            include_thoughts=config.thinking_config.include_thoughts,
+            thinking_budget=config.thinking_config.thinking_budget
+        )
+        planner = BuiltInPlanner(thinking_config=t_config)
+
+    # 5. Generation Config
+    gen_config = None
+    if config.generation_config:
+        g_params = {}
+        if config.generation_config.temperature is not None:
+            g_params["temperature"] = config.generation_config.temperature
+        if config.generation_config.max_output_tokens is not None:
+            g_params["max_output_tokens"] = config.generation_config.max_output_tokens
+        if config.generation_config.top_p is not None:
+            g_params["top_p"] = config.generation_config.top_p
+            
+        if g_params:
+            gen_config = types.GenerateContentConfig(**g_params)
+
+    # 6. Assemble LlmAgent
+    return LlmAgent(
+        name=config.name,
+        model=llm, 
+        description=config.description or "",
+        instruction=config.instruction,
+        tools=selected_tools,
+        code_executor=code_executor,
+        planner=planner,
+        generate_content_config=gen_config
+    )

app/config.py

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+from pydantic_settings import BaseSettings
+from functools import lru_cache
+
+
+class Settings(BaseSettings):
+    """Application settings loaded from environment variables."""
+    
+    # Database Configuration
+    DATABASE_URL: str = "postgresql+asyncpg://myuser:mypassword@127.0.0.1:5432/mydatabase"
+    
+    # LLM API Configuration
+    LLM_API_KEY: str
+    LLM_API_BASE: str = "https://api.openai.com/v1"
+    LLM_DEFAULT_MODEL: str = "openai/gpt-4o"
+    
+    # App Configuration
+    DEFAULT_APP_NAME: str = "adk_chat_app"
+
+    class Config:
+        env_file = ".env"
+        extra = "ignore"
+
+
+@lru_cache
+def get_settings() -> Settings:
+    """Get cached settings instance."""
+    return Settings()
+
+
+settings = get_settings()

app/main.py

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+import json
+import logging
+from typing import AsyncGenerator
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI, HTTPException, Depends
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import StreamingResponse
+
+from google.adk.runners import Runner
+from google.adk.agents.run_config import RunConfig, StreamingMode
+from google.genai import types
+
+from app.config import settings
+
+from app.services import (
+    get_session_service, 
+    init_session_service, 
+    close_session_service
+)
+from app.agent_factory import create_agent
+
+# Routers
+from app.routers.agents import router as agents_router
+from app.routers.sessions import router as sessions_router
+from app.routers.tools import router as tools_router
+
+
+# --- Logging Configuration ---
+
+# --- Logging Configuration ---
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+)
+logger = logging.getLogger(__name__)
+
+
+# --- Application Lifespan ---
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """Application lifespan manager for startup/shutdown events."""
+    logger.info("Starting up ADK Chat Backend...")
+    await init_session_service()
+    logger.info("Application started successfully")
+    yield
+    logger.info("Shutting down ADK Chat Backend...")
+    await close_session_service()
+    logger.info("Application shutdown complete")
+
+
+app = FastAPI(
+    title="ADK Enterprise Chat Backend",
+    description="LLM Chat backend powered by Google ADK with PostgreSQL persistence",
+    version="2.0.0",
+    lifespan=lifespan
+)
+
+
+# --- CORS Configuration ---
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+# --- Register Routers ---
+app.include_router(agents_router)
+app.include_router(sessions_router)
+app.include_router(tools_router)
+
+
+# --- Helper ---
+def get_streaming_mode(mode_str: str) -> StreamingMode:
+    return StreamingMode.SSE if mode_str.lower() == "sse" else StreamingMode.NONE
+
+
+

app/models.py

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+from pydantic import BaseModel, Field
+from typing import List, Optional, Any
+
+
+from typing import List, Optional, Any, Dict, Literal, Union
+
+# --- MCP Tool Configuration Models ---
+
+class StdioConfig(BaseModel):
+    """Configuration for Stdio-based MCP server."""
+    command: str = Field(..., description="Executable command (e.g., 'npx', 'python')")
+    args: List[str] = Field(default_factory=list, description="Command arguments")
+    env: Optional[Dict[str, str]] = Field(None, description="Environment variables")
+
+class SSEConfig(BaseModel):
+    """Configuration for SSE-based MCP server."""
+    url: str = Field(..., description="Server URL (e.g., 'http://localhost:8000/sse')")
+
+class MCPServerConfig(BaseModel):
+    """Configuration for an MCP Server connection."""
+    name: str = Field(..., description="Unique name for the toolset")
+    type: Literal["stdio", "sse"] = Field("stdio", description="Connection type")
+    stdio_config: Optional[StdioConfig] = Field(None, description="Stdio configuration")
+    sse_config: Optional[SSEConfig] = Field(None, description="SSE configuration")
+    tool_filter: Optional[List[str]] = Field(None, description="Optional whitelist of tools to enable")
+
+# --- LLM Configuration Models ---
+
+class LLMConfig(BaseModel):
+    """Custom LLM API configuration for per-request override."""
+    api_key: Optional[str] = Field(None, description="API key for the LLM service")
+    api_base: Optional[str] = Field(None, description="Base URL for the LLM API")
+    model: Optional[str] = Field(None, description="Model name (e.g., 'openai/gpt-4o')")
+
+
+class GenerationConfig(BaseModel):
+    """LLM generation parameters for fine-tuning responses."""
+    temperature: Optional[float] = Field(None, ge=0.0, le=2.0, description="Randomness (0.0-2.0)")
+    max_output_tokens: Optional[int] = Field(None, gt=0, description="Max response length")
+    top_p: Optional[float] = Field(None, ge=0.0, le=1.0, description="Nucleus sampling")
+    top_k: Optional[int] = Field(None, gt=0, description="Top-k sampling")
+
+
+# --- Request Models ---
+
+class CreateSessionRequest(BaseModel):
+    """Request to create a new chat session."""
+    user_id: str
+    app_name: Optional[str] = None
+
+
+
+class ThinkingConfigModel(BaseModel):
+    """Configuration for BuiltInPlanner thinking features."""
+    include_thoughts: bool = Field(True, description="Whether to include internal thoughts in the response")
+    thinking_budget: int = Field(1024, gt=0, description="Token budget for thinking")
+
+
+class AgentConfig(BaseModel):
+    """Comprehensive configuration for creating an ADK Agent."""
+    name: str = Field(..., description="Unique name for the agent")
+    description: Optional[str] = Field(None, description="Description of agent capabilities")
+    model: str = Field(..., description="Model identifier (e.g., 'gemini-2.5-flash')")
+    instruction: str = Field(..., description="System instruction / persona for the agent")
+    tools: List[str] = Field(default_factory=list, description="List of tool names to enable")
+    enable_code_execution: bool = Field(False, description="Enable built-in code executor")
+    
+    thinking_config: Optional[ThinkingConfigModel] = Field(None, description="Configuration for reasoning/planning")
+    
+    # Nested configurations
+    llm_config: Optional[LLMConfig] = Field(None, description="Custom LLM API connection details")
+    generation_config: Optional[GenerationConfig] = Field(None, description="Generation parameters")
+
+
+
+class AgentDefinition(AgentConfig):
+    """Persisted Agent definition with unique ID."""
+    id: str = Field(..., description="Unique identifier for the agent")
+    created_at: float = Field(default_factory=lambda: __import__("time").time(), description="Creation timestamp")
+    updated_at: float = Field(default_factory=lambda: __import__("time").time(), description="Last update timestamp")
+
+
+class ChatTurnRequest(BaseModel):
+    """Request for a single chat turn with a specific agent."""
+    agent_id: str = Field(..., description="ID of the agent to use for this turn")
+    message: str = Field(..., description="User message content")
+    # Optional overrides for this specific turn
+    streaming_mode: Optional[str] = Field("sse", description="Streaming mode: 'sse', 'none'")
+
+
+class ChatRequest(BaseModel):
+    """
+    LEGACY: Request for chat completion. 
+    Used by the old /chat/stream endpoint.
+    """
+    session_id: str
+    user_id: str
+    message: str
+    app_name: Optional[str] = None
+    
+    agent_config: Optional[AgentConfig] = Field(None, description="Ephemeral agent config")
+    max_llm_calls: Optional[int] = Field(500, gt=0)
+    streaming_mode: Optional[str] = "sse"
+
+
+class SessionResponse(BaseModel):
+    """Response for session operations."""
+    id: str
+    app_name: str
+    user_id: str
+    updated_at: Any = None
+
+
+class HistoryEvent(BaseModel):
+    """A single event in chat history."""
+    type: str
+    role: str
+    content: str
+    agent_name: Optional[str] = None
+    timestamp: Optional[Any] = None
+    invocation_id: Optional[str] = None
+
+
+class SessionDetailResponse(SessionResponse):
+    """Session details including chat history."""
+    history: List[HistoryEvent] = []
+    events_count: int = 0
+    created_at: Any = None

app/routers/agents.py

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+from fastapi import APIRouter, HTTPException, Depends
+from typing import List
+
+from app.models import AgentConfig, AgentDefinition
+from app.services.agent_service import get_agent_service, AgentService
+
+# Initialize Router
+router = APIRouter(
+    prefix="/agents",
+    tags=["Agents"]
+)
+
+# ==========================
+# 🤖 Agent Management API
+# ==========================
+
+@router.post("", response_model=AgentDefinition)
+async def create_agent_def(
+    config: AgentConfig,
+    service: AgentService = Depends(get_agent_service)
+):
+    """Create a new Agent definition."""
+    return service.create_agent(config)
+
+
+@router.get("", response_model=List[AgentDefinition])
+async def list_agents(
+    service: AgentService = Depends(get_agent_service)
+):
+    """List all available Agents."""
+    return service.list_agents()
+
+
+@router.get("/{agent_id}", response_model=AgentDefinition)
+async def get_agent_def(
+    agent_id: str,
+    service: AgentService = Depends(get_agent_service)
+):
+    """Get specific Agent definition."""
+    agent = service.get_agent(agent_id)
+    if not agent:
+        raise HTTPException(status_code=404, detail="Agent not found")
+    return agent
+
+
+@router.put("/{agent_id}", response_model=AgentDefinition)
+async def update_agent_def(
+    agent_id: str,
+    config: AgentConfig,
+    service: AgentService = Depends(get_agent_service)
+):
+    """Update an Agent definition."""
+    agent = service.update_agent(agent_id, config)
+    if not agent:
+        raise HTTPException(status_code=404, detail="Agent not found")
+    return agent
+
+
+@router.delete("/{agent_id}")
+async def delete_agent_def(
+    agent_id: str,
+    service: AgentService = Depends(get_agent_service)
+):
+    """Delete an Agent definition."""
+    success = service.delete_agent(agent_id)
+    if not success:
+        raise HTTPException(status_code=404, detail="Agent not found")
+    return {"status": "deleted", "agent_id": agent_id}

app/routers/sessions.py

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+from typing import List, AsyncGenerator
+import json
+import logging
+
+from fastapi import APIRouter, HTTPException, Depends
+from fastapi.responses import StreamingResponse
+
+from google.adk.runners import Runner
+from google.adk.agents.run_config import RunConfig, StreamingMode
+from google.genai import types
+
+from app.config import settings
+from app.models import (
+    CreateSessionRequest, 
+    ChatTurnRequest, 
+    SessionResponse, 
+    SessionDetailResponse, 
+    HistoryEvent, 
+    AgentConfig
+)
+from app.services import get_session_service
+from app.services.agent_service import get_agent_service, AgentService
+from app.agent_factory import create_agent
+
+# Initialize Router
+router = APIRouter(
+    prefix="/sessions",
+    tags=["Sessions"]
+)
+
+logger = logging.getLogger(__name__)
+
+
+# --- Helper ---
+def get_streaming_mode(mode_str: str) -> StreamingMode:
+    """Convert string streaming mode to StreamingMode enum."""
+    mode_map = {
+        "none": StreamingMode.NONE,
+        "sse": StreamingMode.SSE,
+        "bidi": StreamingMode.BIDI,
+    }
+    return mode_map.get(mode_str.lower(), StreamingMode.SSE)
+
+
+# ==========================
+# 📋 Session CRUD
+# ==========================
+
+@router.post("", response_model=SessionResponse)
+async def create_session(
+    req: CreateSessionRequest,
+    service=Depends(get_session_service)
+):
+    """Create a new chat session."""
+    app_name = req.app_name or settings.DEFAULT_APP_NAME
+    session = await service.create_session(app_name=app_name, user_id=req.user_id)
+    return SessionResponse(
+        id=session.id,
+        app_name=session.app_name,
+        user_id=session.user_id,
+        updated_at=getattr(session, 'last_update_time', getattr(session, 'updated_at', None))
+    )
+
+
+@router.get("", response_model=List[SessionResponse])
+async def list_sessions(
+    user_id: str, 
+    app_name: str = None,
+    service=Depends(get_session_service)
+):
+    """List all sessions for a user."""
+    app_name = app_name or settings.DEFAULT_APP_NAME
+    response = await service.list_sessions(app_name=app_name, user_id=user_id)
+    
+    return [
+        SessionResponse(
+            id=s.id, 
+            app_name=s.app_name, 
+            user_id=s.user_id, 
+            updated_at=getattr(s, 'last_update_time', getattr(s, 'updated_at', None))
+        ) for s in response.sessions
+    ]
+
+
+@router.get("/{session_id}", response_model=SessionDetailResponse)
+async def get_session_history(
+    session_id: str,
+    user_id: str,
+    app_name: str = None,
+    service=Depends(get_session_service)
+):
+    """Get session details and chat history."""
+    app_name = app_name or settings.DEFAULT_APP_NAME
+    session = await service.get_session(
+        app_name=app_name, 
+        user_id=user_id, 
+        session_id=session_id
+    )
+    if not session:
+        raise HTTPException(status_code=404, detail="Session not found")
+
+    # Convert history events
+    history_events = []
+    events = getattr(session, 'events', [])
+    
+    # Filter events based on Rewind actions
+    # ADK preserves all events in the log. We must retroactively remove rewound events for the view.
+    valid_events = []
+    for e in events:
+        # Check for rewind action
+        actions = getattr(e, 'actions', None)
+        rewind_target_id = getattr(actions, 'rewind_before_invocation_id', None) if actions else None
+        
+        if rewind_target_id:
+            # Find the index where the truncated invocation began
+            truncate_idx = -1
+            for i, ve in enumerate(valid_events):
+                if getattr(ve, 'invocation_id', None) == rewind_target_id:
+                    truncate_idx = i
+                    break
+            
+            if truncate_idx != -1:
+                logger.debug(f"Rewinding history to before {rewind_target_id}")
+                valid_events = valid_events[:truncate_idx]
+        else:
+            valid_events.append(e)
+
+    for e in valid_events:
+        content_str = ""
+        if hasattr(e, 'content') and e.content:
+            if isinstance(e.content, str):
+                content_str = e.content
+            elif hasattr(e.content, 'parts'):
+                parts = e.content.parts
+                for part in parts:
+                    if hasattr(part, 'text') and part.text:
+                        content_str += part.text
+        
+        # Determine basic role (user vs model)
+        # ADK usually sets author to the agent name or "user"
+        author = getattr(e, 'author', 'unknown')
+        role = "user" if author == "user" else "model"
+        
+        # Agent Name is the specific author if it's a model response
+        agent_name = author if role == "model" else None
+        
+        # Extract timestamp
+        timestamp = getattr(e, 'timestamp', getattr(e, 'created_at', None))
+        invocation_id = getattr(e, 'invocation_id', None)
+        
+        history_events.append(HistoryEvent(
+            type="message",
+            role=role,
+            agent_name=agent_name,
+            content=content_str,
+            timestamp=timestamp,
+            invocation_id=invocation_id
+        ))
+
+    return SessionDetailResponse(
+        id=session.id,
+        app_name=session.app_name,
+        user_id=session.user_id,
+        updated_at=getattr(session, 'last_update_time', getattr(session, 'updated_at', None)),
+        created_at=getattr(session, 'created_at', getattr(session, 'create_time', None)),
+        history=history_events,
+        events_count=len(history_events)
+    )
+
+
+@router.delete("/{session_id}")
+async def delete_session(
+    session_id: str,
+    user_id: str,
+    app_name: str = None,
+    service=Depends(get_session_service)
+):
+    """Delete a session."""
+    app_name = app_name or settings.DEFAULT_APP_NAME
+    await service.delete_session(app_name=app_name, user_id=user_id, session_id=session_id)
+    return {"status": "deleted", "session_id": session_id}
+
+
+@router.post("/{session_id}/rewind")
+async def rewind_session_state(
+    session_id: str,
+    user_id: str,
+    invocation_id: str,
+    app_name: str = None,
+    session_service=Depends(get_session_service),
+    agent_service: AgentService = Depends(get_agent_service)
+):
+    """
+    Rewind session state to before a specific invocation.
+    Undoes changes from the specified invocation and subsequent ones.
+    """
+    app_name = app_name or settings.DEFAULT_APP_NAME
+    
+    # 1. Need a Runner instance to perform rewind.
+    # The Runner requires an agent, but for rewind (session/log operation),
+    # the specific agent configuration might not be critical if default is used,
+    # assuming session persistence is agent-agnostic.
+    # We'll use the default assistant to initialize the runner.
+    agent_def = agent_service.get_agent("default-assistant")
+    if not agent_def:
+         # Fallback if default deleted
+        agent_def = AgentConfig(
+            name="rewinder",
+            model=settings.LLM_DEFAULT_MODEL,
+            instruction="",
+            tools=[]
+        )
+    
+    agent = create_agent(agent_def)
+    
+    runner = Runner(
+        agent=agent,
+        app_name=app_name,
+        session_service=session_service
+    )
+    
+    try:
+        await runner.rewind_async(
+            user_id=user_id, 
+            session_id=session_id, 
+            rewind_before_invocation_id=invocation_id
+        )
+        return {"status": "success", "rewound_before": invocation_id}
+    except Exception as e:
+        logger.error(f"Rewind failed: {e}")
+        # ADK might raise specific errors, generic catch for now
+        raise HTTPException(status_code=500, detail=f"Rewind failed: {str(e)}")
+
+
+# ==========================
+# 💬 Session Chat
+# ==========================
+
+@router.post("/{session_id}/chat")
+async def chat_with_agent(
+    session_id: str,
+    req: ChatTurnRequest,
+    user_id: str,
+    app_name: str = None,
+    session_service=Depends(get_session_service),
+    agent_service: AgentService = Depends(get_agent_service)
+):
+    """
+    Chat with a specific Agent in a Session.
+    Decoupled: Agent is loaded from AgentService, Session is loaded from SessionService.
+    """
+    app_name = app_name or settings.DEFAULT_APP_NAME
+    
+    # 1. Load Session
+    session = await session_service.get_session(
+        app_name=app_name, 
+        user_id=user_id, 
+        session_id=session_id
+    )
+    if not session:
+        raise HTTPException(status_code=404, detail="Session not found")
+
+    # 2. Get Agent Definition
+    agent_def = agent_service.get_agent(req.agent_id)
+    if not agent_def:
+        raise HTTPException(status_code=404, detail=f"Agent '{req.agent_id}' not found")
+
+    # 3. Create Runtime Agent
+    agent = create_agent(agent_def)
+
+    # 4. Preparation for Run
+    streaming_mode = get_streaming_mode(req.streaming_mode or "sse")
+    run_config = RunConfig(
+        streaming_mode=streaming_mode,
+        max_llm_calls=500, # or configurable
+    )
+    
+    runner = Runner(
+        agent=agent,
+        app_name=app_name,
+        session_service=session_service
+    )
+
+    # 5. Stream Generator
+    async def event_generator() -> AsyncGenerator[str, None]:
+        new_msg = types.Content(
+            role="user", 
+            parts=[types.Part(text=req.message)]
+        )
+        try:
+            async for event in runner.run_async(
+                session_id=session.id,
+                user_id=user_id,
+                new_message=new_msg,
+                run_config=run_config,
+            ):
+                if event.content:
+                    text_content = ""
+                    if hasattr(event.content, 'parts'):
+                        for part in event.content.parts:
+                            if hasattr(part, 'text') and part.text:
+                                text_content += part.text
+                    elif isinstance(event.content, str):
+                        text_content = event.content
+
+                    if text_content:
+                        payload = {"type": "content", "text": text_content, "role": "model"}
+                        yield f"data: {json.dumps(payload)}\n\n"
+            
+            yield f"data: {json.dumps({'type': 'done'})}\n\n"
+            
+        except Exception as e:
+            logger.exception("Error during agent chat stream")
+            err_payload = {"type": "error", "text": str(e)}
+            yield f"data: {json.dumps(err_payload)}\n\n"
+
+    return StreamingResponse(event_generator(), media_type="text/event-stream")

app/routers/tools.py

@@ -0,0 +1,43 @@
+
+from fastapi import APIRouter, Depends, HTTPException
+from typing import List, Dict
+
+from app.services.tool_service import ToolService, get_tool_service
+from app.models import MCPServerConfig
+
+router = APIRouter(prefix="/tools", tags=["tools"])
+
+@router.get("/local")
+async def list_local_tools(
+    service: ToolService = Depends(get_tool_service)
+) -> List[str]:
+    """List available local tools (scan 'tools/' directory)."""
+    return service.get_local_tools()
+
+@router.get("/mcp", response_model=List[MCPServerConfig])
+async def list_mcp_servers(
+    service: ToolService = Depends(get_tool_service)
+):
+    """List configured MCP servers."""
+    return service.list_mcp_servers()
+
+@router.post("/mcp", response_model=MCPServerConfig)
+async def add_mcp_server(
+    config: MCPServerConfig,
+    service: ToolService = Depends(get_tool_service)
+):
+    """Register a new MCP server configuration."""
+    # Check if exists? Overwrite behavior is default in dict
+    service.add_mcp_server(config)
+    return config
+
+@router.delete("/mcp/{name}")
+async def remove_mcp_server(
+    name: str,
+    service: ToolService = Depends(get_tool_service)
+):
+    """Remove a configured MCP server."""
+    deleted = service.remove_mcp_server(name)
+    if not deleted:
+        raise HTTPException(status_code=404, detail=f"MCP Server '{name}' not found")
+    return {"status": "deleted", "name": name}

app/services/__init__.py

@@ -0,0 +1,5 @@
+from .session_service import (
+    init_session_service,
+    close_session_service,
+    get_session_service
+)

app/services/agent_service.py

@@ -0,0 +1,89 @@
+import uuid
+import time
+from typing import Dict, List, Optional
+import logging
+
+from app.config import settings
+from app.models import AgentConfig, AgentDefinition
+
+logger = logging.getLogger(__name__)
+
+class AgentService:
+    """
+    Service for managing Agent Definitions.
+    Currently uses in-memory storage. 
+    Can be extended to support Database storage.
+    """
+    def __init__(self):
+        # In-memory store: {agent_id: AgentDefinition}
+        self._store: Dict[str, AgentDefinition] = {}
+        
+        # Populate with a default agent for convenience
+        self._create_default_agent()
+
+    def _create_default_agent(self):
+        default_id = "default-assistant"
+        if default_id not in self._store:
+            self._store[default_id] = AgentDefinition(
+                id=default_id,
+                name="Assistant",
+                description="A helpful default AI assistant",
+                model=settings.LLM_DEFAULT_MODEL,
+                instruction="You are a helpful assistant.",
+                tools=[],
+                created_at=time.time(),
+                updated_at=time.time()
+            )
+
+    def create_agent(self, config: AgentConfig) -> AgentDefinition:
+        """Create and store a new agent definition."""
+        agent_id = str(uuid.uuid4())
+        definition = AgentDefinition(
+            id=agent_id,
+            **config.model_dump(),
+            created_at=time.time(),
+            updated_at=time.time()
+        )
+        self._store[agent_id] = definition
+        logger.info(f"Created new agent definition: {agent_id}")
+        return definition
+
+    def get_agent(self, agent_id: str) -> Optional[AgentDefinition]:
+        """Retrieve an agent definition by ID."""
+        return self._store.get(agent_id)
+
+    def update_agent(self, agent_id: str, config: AgentConfig) -> Optional[AgentDefinition]:
+        """Update an existing agent definition."""
+        if agent_id not in self._store:
+            return None
+        
+        # Preserve original creation time and ID
+        original = self._store[agent_id]
+        updated = AgentDefinition(
+            id=agent_id,
+            **config.model_dump(),
+            created_at=original.created_at,
+            updated_at=time.time()
+        )
+        self._store[agent_id] = updated
+        logger.info(f"Updated agent definition: {agent_id}")
+        return updated
+
+    def list_agents(self) -> List[AgentDefinition]:
+        """List all stored agents."""
+        return list(self._store.values())
+
+    def delete_agent(self, agent_id: str) -> bool:
+        """Delete an agent definition."""
+        if agent_id in self._store:
+            del self._store[agent_id]
+            logger.info(f"Deleted agent definition: {agent_id}")
+            return True
+        return False
+
+
+# Singleton instance
+_agent_service = AgentService()
+
+def get_agent_service() -> AgentService:
+    return _agent_service

app/services/session_service.py

@@ -0,0 +1,40 @@
+import logging
+from google.adk.sessions import DatabaseSessionService
+from app.config import settings
+
+logger = logging.getLogger(__name__)
+
+# Global service instance
+_session_service: DatabaseSessionService | None = None
+
+
+async def init_session_service() -> None:
+    """Initialize the database session service on application startup."""
+    global _session_service
+    if _session_service is None:
+        logger.info(f"Initializing DatabaseSessionService with {settings.DATABASE_URL}...")
+        _session_service = DatabaseSessionService(db_url=settings.DATABASE_URL)
+        logger.info("DatabaseSessionService initialized successfully")
+
+
+async def close_session_service() -> None:
+    """Cleanup session service resources on application shutdown."""
+    global _session_service
+    if _session_service:
+        _session_service = None
+        logger.info("DatabaseSessionService closed")
+
+
+def get_session_service() -> DatabaseSessionService:
+    """
+    Get the session service instance for dependency injection.
+    
+    Raises:
+        RuntimeError: If service is not initialized.
+    """
+    if _session_service is None:
+        raise RuntimeError("Session service not initialized. Application may not have started properly.")
+    return _session_service
+
+
+

app/services/tool_service.py

@@ -0,0 +1,146 @@
+
+import os
+import logging
+import importlib.util
+import inspect
+from typing import List, Dict, Optional, Any, Callable
+from pathlib import Path
+
+# ADK imports
+from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset
+from google.adk.tools.mcp_tool.mcp_session_manager import (
+    StreamableHTTPServerParams, 
+    StdioConnectionParams, 
+    StdioServerParameters
+)
+
+from app.models import MCPServerConfig
+
+logger = logging.getLogger(__name__)
+
+class ToolService:
+    """
+    Service for managing available tools (Local and MCP).
+    """
+    def __init__(self, tools_dir: str = "tools"):
+        self.tools_dir = Path(tools_dir)
+        self._mcp_registry: Dict[str, MCPServerConfig] = {}
+        
+        # Ensure tools directory exists
+        if not self.tools_dir.exists():
+            self.tools_dir.mkdir(parents=True, exist_ok=True)
+            
+    # --- Local Tools Scanning ---
+    
+    def get_local_tools(self) -> List[str]:
+        """
+        Scan the 'tools/' directory for valid tool implementations.
+        Returns a list of tool names (folder names).
+        """
+        tools = []
+        if not self.tools_dir.exists():
+            return []
+            
+        for item in self.tools_dir.iterdir():
+            if item.is_dir():
+                # Check if it has a valid entry point
+                if (item / "tool.py").exists() or (item / "main.py").exists():
+                    tools.append(item.name)
+        return tools
+
+    def load_local_tool(self, tool_name: str) -> Optional[Callable]:
+        """
+        Dynamically load a local tool by name.
+        Expects a function named 'tool' or the directory name in tool.py/main.py.
+        """
+        tool_path = self.tools_dir / tool_name
+        
+        # Try finding the module
+        module_file = None
+        if (tool_path / "tool.py").exists():
+            module_file = tool_path / "tool.py"
+        elif (tool_path / "main.py").exists():
+            module_file = tool_path / "main.py"
+            
+        if not module_file:
+            logger.warning(f"Tool implementation not found for {tool_name}")
+            return None
+            
+        try:
+            spec = importlib.util.spec_from_file_location(f"tools.{tool_name}", module_file)
+            if spec and spec.loader:
+                module = importlib.util.module_from_spec(spec)
+                spec.loader.exec_module(module)
+                
+                # Look for a callable object named 'tool' or scan for functions
+                if hasattr(module, "tool") and callable(module.tool):
+                    return module.tool
+                
+                # Heuristic: Find first function that looks like a tool?
+                # For now, require 'tool' export or function with same name as folder
+                if hasattr(module, tool_name) and callable(getattr(module, tool_name)):
+                    return getattr(module, tool_name)
+                    
+                logger.warning(f"No callable 'tool' or '{tool_name}' found in {module_file}")
+        except Exception as e:
+            logger.error(f"Failed to load tool {tool_name}: {e}")
+            
+        return None
+
+    # --- MCP Registry ---
+
+    def list_mcp_servers(self) -> List[MCPServerConfig]:
+        """Return all configured MCP servers."""
+        return list(self._mcp_registry.values())
+        
+    def add_mcp_server(self, config: MCPServerConfig):
+        """Register a new MCP server."""
+        self._mcp_registry[config.name] = config
+        logger.info(f"Registered MCP Server: {config.name}")
+        
+    def remove_mcp_server(self, name: str) -> bool:
+        """Remove an MCP server by name."""
+        if name in self._mcp_registry:
+            del self._mcp_registry[name]
+            logger.info(f"Removed MCP Server: {name}")
+            return True
+        return False
+        
+    def get_mcp_toolset(self, name: str) -> Optional[MCPToolset]:
+        """
+        Create an ADK MCPToolset instance from the configuration.
+        """
+        config = self._mcp_registry.get(name)
+        if not config:
+            return None
+            
+        try:
+            if config.type == "sse":
+                if not config.sse_config:
+                    raise ValueError("Missing SSE config")
+                params = StreamableHTTPServerParams(url=config.sse_config.url)
+                return MCPToolset(connection_params=params)
+                
+            elif config.type == "stdio":
+                if not config.stdio_config:
+                    raise ValueError("Missing Stdio config")
+                
+                server_params = StdioServerParameters(
+                    command=config.stdio_config.command,
+                    args=config.stdio_config.args,
+                    env=config.stdio_config.env
+                )
+                params = StdioConnectionParams(server_params=server_params)
+                return MCPToolset(connection_params=params, tool_filter=config.tool_filter)
+                
+        except Exception as e:
+            logger.error(f"Failed to create MCP Toolset '{name}': {e}")
+            return None
+            
+        return None
+
+# Singleton instance
+_tool_service = ToolService()
+
+def get_tool_service() -> ToolService:
+    return _tool_service

app/tools.py

@@ -0,0 +1,29 @@
+import logging
+from typing import Dict, Callable, Any
+
+logger = logging.getLogger(__name__)
+
+def dummy_tool(query: str) -> dict:
+    """
+    Dummy Tool: A placeholder tool for demonstration.
+    
+    Args:
+        query: Any string input.
+        
+    Returns:
+        A mock structured response.
+    """
+    logger.info(f"[Tool] dummy_tool called with: {query}")
+    return {
+        "status": "success", 
+        "message": f"Processed query: {query}", 
+        "data": "dummy_value"
+    }
+
+# ==========================
+# 🛠️ Tool Registry
+# ==========================
+# Map tool names to their function implementation
+TOOL_REGISTRY: Dict[str, Callable] = {
+    "dummy_tool": dummy_tool,
+}