ai-service/README.md

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+# AI Service
+
+Python AI Service for intelligent chat with RAG support.
+
+## Features
+
+- Multi-tenant isolation via X-Tenant-Id header
+- SSE streaming support via Accept: text/event-stream
+- RAG-powered responses with confidence scoring
+
+## Installation
+
+```bash
+pip install -e ".[dev]"
+```
+
+## Running
+
+```bash
+uvicorn app.main:app --host 0.0.0.0 --port 8080
+```
+
+## API Endpoints
+
+- `POST /ai/chat` - Generate AI reply
+- `GET /ai/health` - Health check

ai-service/app/__init__.py

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+"""
+AI Service - Python AI Middle Platform
+[AC-AISVC-01] FastAPI-based AI chat service with multi-tenant support.
+"""

ai-service/app/api/__init__.py

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+"""
+API module for AI Service.
+"""
+
+from app.api.chat import router as chat_router
+from app.api.health import router as health_router
+
+__all__ = ["chat_router", "health_router"]

ai-service/app/api/chat.py

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+"""
+Chat endpoint for AI Service.
+[AC-AISVC-01, AC-AISVC-02, AC-AISVC-06] Main chat endpoint with streaming/non-streaming modes.
+"""
+
+import logging
+from typing import Annotated, Any
+
+from fastapi import APIRouter, Depends, Header, Request
+from fastapi.responses import JSONResponse
+from sse_starlette.sse import EventSourceResponse
+
+from app.core.middleware import get_response_mode, is_sse_request
+from app.core.sse import create_error_event
+from app.core.tenant import get_tenant_id
+from app.models import ChatRequest, ChatResponse, ErrorResponse
+from app.services.orchestrator import OrchestratorService, get_orchestrator_service
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(tags=["AI Chat"])
+
+
+@router.post(
+    "/ai/chat",
+    operation_id="generateReply",
+    summary="Generate AI reply",
+    description="""
+    [AC-AISVC-01, AC-AISVC-02, AC-AISVC-06] Generate AI reply based on user message.
+    
+    Response mode is determined by Accept header:
+    - Accept: text/event-stream -> SSE streaming response
+    - Other -> JSON response
+    """,
+    responses={
+        200: {
+            "description": "Success - JSON or SSE stream",
+            "content": {
+                "application/json": {"schema": {"$ref": "#/components/schemas/ChatResponse"}},
+                "text/event-stream": {"schema": {"type": "string"}},
+            },
+        },
+        400: {"description": "Invalid request", "model": ErrorResponse},
+        500: {"description": "Internal error", "model": ErrorResponse},
+        503: {"description": "Service unavailable", "model": ErrorResponse},
+    },
+)
+async def generate_reply(
+    request: Request,
+    chat_request: ChatRequest,
+    accept: Annotated[str | None, Header()] = None,
+    orchestrator: OrchestratorService = Depends(get_orchestrator_service),
+) -> Any:
+    """
+    [AC-AISVC-06] Generate AI reply with automatic response mode switching.
+    
+    Based on Accept header:
+    - text/event-stream: Returns SSE stream with message/final/error events
+    - Other: Returns JSON ChatResponse
+    """
+    tenant_id = get_tenant_id()
+    if not tenant_id:
+        from app.core.exceptions import MissingTenantIdException
+        raise MissingTenantIdException()
+
+    logger.info(
+        f"[AC-AISVC-06] Processing chat request: tenant={tenant_id}, "
+        f"session={chat_request.session_id}, mode={get_response_mode(request)}"
+    )
+
+    if is_sse_request(request):
+        return await _handle_streaming_request(tenant_id, chat_request, orchestrator)
+    else:
+        return await _handle_json_request(tenant_id, chat_request, orchestrator)
+
+
+async def _handle_json_request(
+    tenant_id: str,
+    chat_request: ChatRequest,
+    orchestrator: OrchestratorService,
+) -> JSONResponse:
+    """
+    [AC-AISVC-02] Handle non-streaming JSON request.
+    Returns ChatResponse with reply, confidence, shouldTransfer.
+    """
+    logger.info(f"[AC-AISVC-02] Processing JSON request for tenant={tenant_id}")
+
+    try:
+        response = await orchestrator.generate(tenant_id, chat_request)
+        return JSONResponse(
+            content=response.model_dump(exclude_none=True, by_alias=True),
+        )
+    except Exception as e:
+        logger.error(f"[AC-AISVC-04] Error generating response: {e}")
+        from app.core.exceptions import AIServiceException, ErrorCode
+        if isinstance(e, AIServiceException):
+            raise e
+        from app.core.exceptions import AIServiceException
+        raise AIServiceException(
+            code=ErrorCode.INTERNAL_ERROR,
+            message=str(e),
+        )
+
+
+async def _handle_streaming_request(
+    tenant_id: str,
+    chat_request: ChatRequest,
+    orchestrator: OrchestratorService,
+) -> EventSourceResponse:
+    """
+    [AC-AISVC-06, AC-AISVC-07, AC-AISVC-08, AC-AISVC-09] Handle SSE streaming request.
+    Yields message events followed by final or error event.
+    """
+    logger.info(f"[AC-AISVC-06] Processing SSE request for tenant={tenant_id}")
+
+    async def event_generator():
+        try:
+            async for event in orchestrator.generate_stream(tenant_id, chat_request):
+                yield event
+        except Exception as e:
+            logger.error(f"[AC-AISVC-09] Streaming error: {e}")
+            yield create_error_event(
+                code="STREAMING_ERROR",
+                message=str(e),
+            )
+
+    return EventSourceResponse(event_generator(), ping=15)

ai-service/app/api/health.py

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+"""
+Health check endpoint.
+[AC-AISVC-20] Health check for service monitoring.
+"""
+
+from fastapi import APIRouter, status
+from fastapi.responses import JSONResponse
+
+router = APIRouter(tags=["Health"])
+
+
+@router.get(
+    "/ai/health",
+    operation_id="healthCheck",
+    summary="Health check",
+    description="[AC-AISVC-20] Check if AI service is healthy",
+    responses={
+        200: {"description": "Service is healthy"},
+        503: {"description": "Service is unhealthy"},
+    },
+)
+async def health_check() -> JSONResponse:
+    """
+    [AC-AISVC-20] Health check endpoint.
+    Returns 200 with status if healthy, 503 if not.
+    """
+    return JSONResponse(
+        status_code=status.HTTP_200_OK,
+        content={"status": "healthy"},
+    )

ai-service/app/core/__init__.py

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+"""
+Core module - Configuration, dependencies, and utilities.
+[AC-AISVC-01, AC-AISVC-10, AC-AISVC-11] Core infrastructure components.
+"""
+
+from app.core.config import Settings, get_settings
+from app.core.database import async_session_maker, get_session, init_db, close_db
+from app.core.qdrant_client import QdrantClient, get_qdrant_client
+
+__all__ = [
+    "Settings",
+    "get_settings",
+    "async_session_maker",
+    "get_session",
+    "init_db",
+    "close_db",
+    "QdrantClient",
+    "get_qdrant_client",
+]

ai-service/app/core/config.py

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+"""
+Configuration management for AI Service.
+[AC-AISVC-01] Centralized configuration with environment variable support.
+"""
+
+from functools import lru_cache
+
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+
+class Settings(BaseSettings):
+    model_config = SettingsConfigDict(env_prefix="AI_SERVICE_", env_file=".env", extra="ignore")
+
+    app_name: str = "AI Service"
+    app_version: str = "0.1.0"
+    debug: bool = False
+
+    host: str = "0.0.0.0"
+    port: int = 8080
+
+    request_timeout_seconds: int = 20
+    sse_ping_interval_seconds: int = 15
+
+    log_level: str = "INFO"
+
+    llm_provider: str = "openai"
+    llm_api_key: str = ""
+    llm_base_url: str = "https://api.openai.com/v1"
+    llm_model: str = "gpt-4o-mini"
+    llm_max_tokens: int = 2048
+    llm_temperature: float = 0.7
+    llm_timeout_seconds: int = 30
+    llm_max_retries: int = 3
+
+    database_url: str = "postgresql+asyncpg://postgres:postgres@localhost:5432/ai_service"
+    database_pool_size: int = 10
+    database_max_overflow: int = 20
+
+    qdrant_url: str = "http://localhost:6333"
+    qdrant_collection_prefix: str = "kb_"
+    qdrant_vector_size: int = 1536
+
+    rag_top_k: int = 5
+    rag_score_threshold: float = 0.7
+    rag_min_hits: int = 1
+    rag_max_evidence_tokens: int = 2000
+
+    confidence_threshold_low: float = 0.5
+    max_history_tokens: int = 4000
+
+
+@lru_cache
+def get_settings() -> Settings:
+    return Settings()

ai-service/app/core/database.py

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+"""
+Database client for AI Service.
+[AC-AISVC-11] PostgreSQL database with SQLModel for multi-tenant data isolation.
+"""
+
+import logging
+from typing import AsyncGenerator
+
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
+from sqlalchemy.pool import NullPool
+from sqlmodel import SQLModel
+
+from app.core.config import get_settings
+
+logger = logging.getLogger(__name__)
+
+settings = get_settings()
+
+engine = create_async_engine(
+    settings.database_url,
+    pool_size=settings.database_pool_size,
+    max_overflow=settings.database_max_overflow,
+    echo=settings.debug,
+    pool_pre_ping=True,
+)
+
+async_session_maker = async_sessionmaker(
+    engine,
+    class_=AsyncSession,
+    expire_on_commit=False,
+    autocommit=False,
+    autoflush=False,
+)
+
+
+async def init_db() -> None:
+    """
+    [AC-AISVC-11] Initialize database tables.
+    Creates all tables defined in SQLModel metadata.
+    """
+    async with engine.begin() as conn:
+        await conn.run_sync(SQLModel.metadata.create_all)
+    logger.info("[AC-AISVC-11] Database tables initialized")
+
+
+async def close_db() -> None:
+    """
+    Close database connections.
+    """
+    await engine.dispose()
+    logger.info("Database connections closed")
+
+
+async def get_session() -> AsyncGenerator[AsyncSession, None]:
+    """
+    [AC-AISVC-11] Dependency injection for database session.
+    Ensures proper session lifecycle management.
+    """
+    async with async_session_maker() as session:
+        try:
+            yield session
+            await session.commit()
+        except Exception:
+            await session.rollback()
+            raise
+        finally:
+            await session.close()

ai-service/app/core/exceptions.py

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+"""
+Exception handling for AI Service.
+[AC-AISVC-03, AC-AISVC-04, AC-AISVC-05] Structured error responses.
+"""
+
+from fastapi import HTTPException, Request, status
+from fastapi.responses import JSONResponse
+
+from app.models import ErrorCode, ErrorResponse
+
+
+class AIServiceException(Exception):
+    def __init__(
+        self,
+        code: ErrorCode,
+        message: str,
+        status_code: int = status.HTTP_500_INTERNAL_SERVER_ERROR,
+        details: list[dict] | None = None,
+    ):
+        self.code = code
+        self.message = message
+        self.status_code = status_code
+        self.details = details
+        super().__init__(message)
+
+
+class MissingTenantIdException(AIServiceException):
+    def __init__(self, message: str = "Missing required header: X-Tenant-Id"):
+        super().__init__(
+            code=ErrorCode.MISSING_TENANT_ID,
+            message=message,
+            status_code=status.HTTP_400_BAD_REQUEST,
+        )
+
+
+class InvalidRequestException(AIServiceException):
+    def __init__(self, message: str, details: list[dict] | None = None):
+        super().__init__(
+            code=ErrorCode.INVALID_REQUEST,
+            message=message,
+            status_code=status.HTTP_400_BAD_REQUEST,
+            details=details,
+        )
+
+
+class ServiceUnavailableException(AIServiceException):
+    def __init__(self, message: str = "Service temporarily unavailable"):
+        super().__init__(
+            code=ErrorCode.SERVICE_UNAVAILABLE,
+            message=message,
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+        )
+
+
+class TimeoutException(AIServiceException):
+    def __init__(self, message: str = "Request timeout"):
+        super().__init__(
+            code=ErrorCode.TIMEOUT,
+            message=message,
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+        )
+
+
+async def ai_service_exception_handler(request: Request, exc: AIServiceException) -> JSONResponse:
+    return JSONResponse(
+        status_code=exc.status_code,
+        content=ErrorResponse(
+            code=exc.code.value,
+            message=exc.message,
+            details=exc.details,
+        ).model_dump(exclude_none=True),
+    )
+
+
+async def http_exception_handler(request: Request, exc: HTTPException) -> JSONResponse:
+    if exc.status_code == status.HTTP_400_BAD_REQUEST:
+        code = ErrorCode.INVALID_REQUEST
+    elif exc.status_code == status.HTTP_503_SERVICE_UNAVAILABLE:
+        code = ErrorCode.SERVICE_UNAVAILABLE
+    else:
+        code = ErrorCode.INTERNAL_ERROR
+
+    return JSONResponse(
+        status_code=exc.status_code,
+        content=ErrorResponse(
+            code=code.value,
+            message=exc.detail or "An error occurred",
+        ).model_dump(exclude_none=True),
+    )
+
+
+async def generic_exception_handler(request: Request, exc: Exception) -> JSONResponse:
+    return JSONResponse(
+        status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+        content=ErrorResponse(
+            code=ErrorCode.INTERNAL_ERROR.value,
+            message="An unexpected error occurred",
+        ).model_dump(exclude_none=True),
+    )

ai-service/app/core/middleware.py

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+"""
+Middleware for AI Service.
+[AC-AISVC-10, AC-AISVC-12] X-Tenant-Id header validation and tenant context injection.
+"""
+
+import logging
+from typing import Callable
+
+from fastapi import Request, Response, status
+from fastapi.responses import JSONResponse
+from starlette.middleware.base import BaseHTTPMiddleware
+
+from app.core.exceptions import ErrorCode, ErrorResponse, MissingTenantIdException
+from app.core.tenant import clear_tenant_context, set_tenant_context
+
+logger = logging.getLogger(__name__)
+
+TENANT_ID_HEADER = "X-Tenant-Id"
+ACCEPT_HEADER = "Accept"
+SSE_CONTENT_TYPE = "text/event-stream"
+
+
+class TenantContextMiddleware(BaseHTTPMiddleware):
+    """
+    [AC-AISVC-10, AC-AISVC-12] Middleware to extract and validate X-Tenant-Id header.
+    Injects tenant context into request state for downstream processing.
+    """
+
+    async def dispatch(self, request: Request, call_next: Callable) -> Response:
+        clear_tenant_context()
+
+        if request.url.path == "/ai/health":
+            return await call_next(request)
+
+        tenant_id = request.headers.get(TENANT_ID_HEADER)
+
+        if not tenant_id or not tenant_id.strip():
+            logger.warning("[AC-AISVC-12] Missing or empty X-Tenant-Id header")
+            return JSONResponse(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                content=ErrorResponse(
+                    code=ErrorCode.MISSING_TENANT_ID.value,
+                    message="Missing required header: X-Tenant-Id",
+                ).model_dump(exclude_none=True),
+            )
+
+        set_tenant_context(tenant_id.strip())
+        request.state.tenant_id = tenant_id.strip()
+
+        logger.info(f"[AC-AISVC-10] Tenant context set: tenant_id={tenant_id.strip()}")
+
+        try:
+            response = await call_next(request)
+        finally:
+            clear_tenant_context()
+
+        return response
+
+
+def is_sse_request(request: Request) -> bool:
+    """
+    [AC-AISVC-06] Check if the request expects SSE streaming response.
+    Based on Accept header: text/event-stream indicates SSE mode.
+    """
+    accept_header = request.headers.get(ACCEPT_HEADER, "")
+    return SSE_CONTENT_TYPE in accept_header
+
+
+def get_response_mode(request: Request) -> str:
+    """
+    [AC-AISVC-06] Determine response mode based on Accept header.
+    Returns 'streaming' for SSE, 'json' for regular JSON response.
+    """
+    return "streaming" if is_sse_request(request) else "json"

ai-service/app/core/qdrant_client.py

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+"""
+Qdrant client for AI Service.
+[AC-AISVC-10] Vector database client with tenant-isolated collection management.
+"""
+
+import logging
+from typing import Any
+
+from qdrant_client import AsyncQdrantClient
+from qdrant_client.models import Distance, PointStruct, VectorParams
+
+from app.core.config import get_settings
+
+logger = logging.getLogger(__name__)
+
+settings = get_settings()
+
+
+class QdrantClient:
+    """
+    [AC-AISVC-10] Qdrant client with tenant-isolated collection management.
+    Collection naming: kb_{tenantId} for tenant isolation.
+    """
+
+    def __init__(self):
+        self._client: AsyncQdrantClient | None = None
+        self._collection_prefix = settings.qdrant_collection_prefix
+        self._vector_size = settings.qdrant_vector_size
+
+    async def get_client(self) -> AsyncQdrantClient:
+        """Get or create Qdrant client instance."""
+        if self._client is None:
+            self._client = AsyncQdrantClient(url=settings.qdrant_url)
+            logger.info(f"[AC-AISVC-10] Qdrant client initialized: {settings.qdrant_url}")
+        return self._client
+
+    async def close(self) -> None:
+        """Close Qdrant client connection."""
+        if self._client:
+            await self._client.close()
+            self._client = None
+            logger.info("Qdrant client connection closed")
+
+    def get_collection_name(self, tenant_id: str) -> str:
+        """
+        [AC-AISVC-10] Get collection name for a tenant.
+        Naming convention: kb_{tenantId}
+        """
+        return f"{self._collection_prefix}{tenant_id}"
+
+    async def ensure_collection_exists(self, tenant_id: str) -> bool:
+        """
+        [AC-AISVC-10] Ensure collection exists for tenant.
+        Note: MVP uses pre-provisioned collections, this is for development/testing.
+        """
+        client = await self.get_client()
+        collection_name = self.get_collection_name(tenant_id)
+
+        try:
+            collections = await client.get_collections()
+            exists = any(c.name == collection_name for c in collections.collections)
+
+            if not exists:
+                await client.create_collection(
+                    collection_name=collection_name,
+                    vectors_config=VectorParams(
+                        size=self._vector_size,
+                        distance=Distance.COSINE,
+                    ),
+                )
+                logger.info(
+                    f"[AC-AISVC-10] Created collection: {collection_name} for tenant={tenant_id}"
+                )
+            return True
+        except Exception as e:
+            logger.error(f"[AC-AISVC-10] Error ensuring collection: {e}")
+            return False
+
+    async def upsert_vectors(
+        self,
+        tenant_id: str,
+        points: list[PointStruct],
+    ) -> bool:
+        """
+        [AC-AISVC-10] Upsert vectors into tenant's collection.
+        """
+        client = await self.get_client()
+        collection_name = self.get_collection_name(tenant_id)
+
+        try:
+            await client.upsert(
+                collection_name=collection_name,
+                points=points,
+            )
+            logger.info(
+                f"[AC-AISVC-10] Upserted {len(points)} vectors for tenant={tenant_id}"
+            )
+            return True
+        except Exception as e:
+            logger.error(f"[AC-AISVC-10] Error upserting vectors: {e}")
+            return False
+
+    async def search(
+        self,
+        tenant_id: str,
+        query_vector: list[float],
+        limit: int = 5,
+        score_threshold: float | None = None,
+    ) -> list[dict[str, Any]]:
+        """
+        [AC-AISVC-10] Search vectors in tenant's collection.
+        Returns results with score >= score_threshold if specified.
+        """
+        client = await self.get_client()
+        collection_name = self.get_collection_name(tenant_id)
+
+        try:
+            results = await client.search(
+                collection_name=collection_name,
+                query_vector=query_vector,
+                limit=limit,
+                score_threshold=score_threshold,
+            )
+
+            hits = [
+                {
+                    "id": str(result.id),
+                    "score": result.score,
+                    "payload": result.payload or {},
+                }
+                for result in results
+            ]
+
+            logger.info(
+                f"[AC-AISVC-10] Search returned {len(hits)} results for tenant={tenant_id}"
+            )
+            return hits
+        except Exception as e:
+            logger.error(f"[AC-AISVC-10] Error searching vectors: {e}")
+            return []
+
+    async def delete_collection(self, tenant_id: str) -> bool:
+        """
+        [AC-AISVC-10] Delete tenant's collection.
+        Used when tenant is removed.
+        """
+        client = await self.get_client()
+        collection_name = self.get_collection_name(tenant_id)
+
+        try:
+            await client.delete_collection(collection_name=collection_name)
+            logger.info(f"[AC-AISVC-10] Deleted collection: {collection_name}")
+            return True
+        except Exception as e:
+            logger.error(f"[AC-AISVC-10] Error deleting collection: {e}")
+            return False
+
+
+_qdrant_client: QdrantClient | None = None
+
+
+async def get_qdrant_client() -> QdrantClient:
+    """Get or create Qdrant client instance."""
+    global _qdrant_client
+    if _qdrant_client is None:
+        _qdrant_client = QdrantClient()
+    return _qdrant_client
+
+
+async def close_qdrant_client() -> None:
+    """Close Qdrant client connection."""
+    global _qdrant_client
+    if _qdrant_client:
+        await _qdrant_client.close()
+        _qdrant_client = None

ai-service/app/core/sse.py

@@ -0,0 +1,170 @@
+"""
+SSE utilities for AI Service.
+[AC-AISVC-06, AC-AISVC-07, AC-AISVC-08, AC-AISVC-09] SSE event generation and state machine.
+"""
+
+import asyncio
+import json
+import logging
+from enum import Enum
+from typing import Any, AsyncGenerator
+
+from sse_starlette.sse import EventSourceResponse, ServerSentEvent
+
+from app.core.config import get_settings
+from app.models import SSEErrorEvent, SSEEventType, SSEFinalEvent, SSEMessageEvent
+
+logger = logging.getLogger(__name__)
+
+
+class SSEState(str, Enum):
+    INIT = "INIT"
+    STREAMING = "STREAMING"
+    FINAL_SENT = "FINAL_SENT"
+    ERROR_SENT = "ERROR_SENT"
+    CLOSED = "CLOSED"
+
+
+class SSEStateMachine:
+    """
+    [AC-AISVC-08, AC-AISVC-09] SSE state machine ensuring proper event sequence.
+    State transitions: INIT -> STREAMING -> FINAL_SENT/ERROR_SENT -> CLOSED
+    """
+
+    def __init__(self):
+        self._state = SSEState.INIT
+        self._lock = asyncio.Lock()
+
+    @property
+    def state(self) -> SSEState:
+        return self._state
+
+    async def transition_to_streaming(self) -> bool:
+        async with self._lock:
+            if self._state == SSEState.INIT:
+                self._state = SSEState.STREAMING
+                logger.debug(f"[AC-AISVC-07] SSE state transition: INIT -> STREAMING")
+                return True
+            return False
+
+    async def transition_to_final(self) -> bool:
+        async with self._lock:
+            if self._state == SSEState.STREAMING:
+                self._state = SSEState.FINAL_SENT
+                logger.debug(f"[AC-AISVC-08] SSE state transition: STREAMING -> FINAL_SENT")
+                return True
+            return False
+
+    async def transition_to_error(self) -> bool:
+        async with self._lock:
+            if self._state in (SSEState.INIT, SSEState.STREAMING):
+                self._state = SSEState.ERROR_SENT
+                logger.debug(f"[AC-AISVC-09] SSE state transition: {self._state} -> ERROR_SENT")
+                return True
+            return False
+
+    async def close(self) -> None:
+        async with self._lock:
+            self._state = SSEState.CLOSED
+            logger.debug("SSE state transition: -> CLOSED")
+
+    def can_send_message(self) -> bool:
+        return self._state == SSEState.STREAMING
+
+
+def format_sse_event(event_type: SSEEventType, data: dict[str, Any]) -> ServerSentEvent:
+    """Format data as SSE event."""
+    return ServerSentEvent(
+        event=event_type.value,
+        data=json.dumps(data, ensure_ascii=False),
+    )
+
+
+def create_message_event(delta: str) -> ServerSentEvent:
+    """[AC-AISVC-07] Create a message event with incremental content."""
+    event_data = SSEMessageEvent(delta=delta)
+    return format_sse_event(SSEEventType.MESSAGE, event_data.model_dump())
+
+
+def create_final_event(
+    reply: str,
+    confidence: float,
+    should_transfer: bool,
+    transfer_reason: str | None = None,
+    metadata: dict[str, Any] | None = None,
+) -> ServerSentEvent:
+    """[AC-AISVC-08] Create a final event with complete response."""
+    event_data = SSEFinalEvent(
+        reply=reply,
+        confidence=confidence,
+        should_transfer=should_transfer,
+        transfer_reason=transfer_reason,
+        metadata=metadata,
+    )
+    return format_sse_event(SSEEventType.FINAL, event_data.model_dump(exclude_none=True))
+
+
+def create_error_event(
+    code: str,
+    message: str,
+    details: list[dict[str, Any]] | None = None,
+) -> ServerSentEvent:
+    """[AC-AISVC-09] Create an error event."""
+    event_data = SSEErrorEvent(
+        code=code,
+        message=message,
+        details=details,
+    )
+    return format_sse_event(SSEEventType.ERROR, event_data.model_dump(exclude_none=True))
+
+
+async def ping_generator(interval_seconds: int) -> AsyncGenerator[str, None]:
+    """
+    [AC-AISVC-06] Generate ping comments for SSE keep-alive.
+    Sends ': ping' as comment lines (not events) to keep connection alive.
+    """
+    while True:
+        await asyncio.sleep(interval_seconds)
+        yield ": ping\n\n"
+
+
+class SSEResponseBuilder:
+    """
+    Builder for SSE response with proper event sequencing and ping keep-alive.
+    """
+
+    def __init__(self):
+        self._state_machine = SSEStateMachine()
+        self._settings = get_settings()
+
+    async def build_response(
+        self,
+        content_generator: AsyncGenerator[ServerSentEvent, None],
+    ) -> EventSourceResponse:
+        """
+        Build SSE response with ping keep-alive mechanism.
+        [AC-AISVC-06] Implements ping keep-alive to prevent connection timeout.
+        """
+
+        async def event_generator() -> AsyncGenerator[ServerSentEvent, None]:
+            await self._state_machine.transition_to_streaming()
+            try:
+                async for event in content_generator:
+                    if self._state_machine.can_send_message():
+                        yield event
+                    else:
+                        break
+            except Exception as e:
+                logger.error(f"[AC-AISVC-09] Error during SSE streaming: {e}")
+                if await self._state_machine.transition_to_error():
+                    yield create_error_event(
+                        code="STREAMING_ERROR",
+                        message=str(e),
+                    )
+            finally:
+                await self._state_machine.close()
+
+        return EventSourceResponse(
+            event_generator(),
+            ping=self._settings.sse_ping_interval_seconds,
+        )

ai-service/app/core/tenant.py

@@ -0,0 +1,31 @@
+"""
+Tenant context management.
+[AC-AISVC-10, AC-AISVC-12] Multi-tenant isolation via X-Tenant-Id header.
+"""
+
+from contextvars import ContextVar
+from dataclasses import dataclass
+
+tenant_context: ContextVar["TenantContext | None"] = ContextVar("tenant_context", default=None)
+
+
+@dataclass
+class TenantContext:
+    tenant_id: str
+
+
+def set_tenant_context(tenant_id: str) -> None:
+    tenant_context.set(TenantContext(tenant_id=tenant_id))
+
+
+def get_tenant_context() -> TenantContext | None:
+    return tenant_context.get()
+
+
+def get_tenant_id() -> str | None:
+    ctx = get_tenant_context()
+    return ctx.tenant_id if ctx else None
+
+
+def clear_tenant_context() -> None:
+    tenant_context.set(None)

ai-service/app/main.py

@@ -0,0 +1,123 @@
+"""
+Main FastAPI application for AI Service.
+[AC-AISVC-01] Entry point with middleware and exception handlers.
+"""
+
+import logging
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI, Request, status
+from fastapi.exceptions import HTTPException, RequestValidationError
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+
+from app.api import chat_router, health_router
+from app.core.config import get_settings
+from app.core.database import close_db, init_db
+from app.core.exceptions import (
+    AIServiceException,
+    ErrorCode,
+    ErrorResponse,
+    ai_service_exception_handler,
+    generic_exception_handler,
+    http_exception_handler,
+)
+from app.core.middleware import TenantContextMiddleware
+from app.core.qdrant_client import close_qdrant_client
+
+settings = get_settings()
+
+logging.basicConfig(
+    level=getattr(logging, settings.log_level.upper()),
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
+)
+
+logger = logging.getLogger(__name__)
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """
+    [AC-AISVC-01, AC-AISVC-11] Application lifespan manager.
+    Handles startup and shutdown of database and external connections.
+    """
+    logger.info(f"[AC-AISVC-01] Starting {settings.app_name} v{settings.app_version}")
+
+    try:
+        await init_db()
+        logger.info("[AC-AISVC-11] Database initialized successfully")
+    except Exception as e:
+        logger.warning(f"[AC-AISVC-11] Database initialization skipped: {e}")
+
+    yield
+
+    await close_db()
+    await close_qdrant_client()
+    logger.info(f"Shutting down {settings.app_name}")
+
+
+app = FastAPI(
+    title=settings.app_name,
+    version=settings.app_version,
+    description="""
+    Python AI Service for intelligent chat with RAG support.
+    
+    ## Features
+    - Multi-tenant isolation via X-Tenant-Id header
+    - SSE streaming support via Accept: text/event-stream
+    - RAG-powered responses with confidence scoring
+    
+    ## Response Modes
+    - **JSON**: Default response mode (Accept: application/json or no Accept header)
+    - **SSE Streaming**: Set Accept: text/event-stream for streaming responses
+    """,
+    docs_url="/docs",
+    redoc_url="/redoc",
+    lifespan=lifespan,
+)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+app.add_middleware(TenantContextMiddleware)
+
+app.add_exception_handler(AIServiceException, ai_service_exception_handler)
+app.add_exception_handler(HTTPException, http_exception_handler)
+app.add_exception_handler(Exception, generic_exception_handler)
+
+
+@app.exception_handler(RequestValidationError)
+async def validation_exception_handler(request: Request, exc: RequestValidationError):
+    """
+    [AC-AISVC-03] Handle request validation errors with structured response.
+    """
+    logger.warning(f"[AC-AISVC-03] Request validation error: {exc.errors()}")
+    error_response = ErrorResponse(
+        code=ErrorCode.INVALID_REQUEST.value,
+        message="Request validation failed",
+        details=[{"loc": list(err["loc"]), "msg": err["msg"], "type": err["type"]} for err in exc.errors()],
+    )
+    return JSONResponse(
+        status_code=status.HTTP_400_BAD_REQUEST,
+        content=error_response.model_dump(exclude_none=True),
+    )
+
+
+app.include_router(health_router)
+app.include_router(chat_router)
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(
+        "app.main:app",
+        host=settings.host,
+        port=settings.port,
+        reload=settings.debug,
+    )

ai-service/app/models/__init__.py

@@ -0,0 +1,88 @@
+"""
+Data models for AI Service.
+[AC-AISVC-02] Request/Response models aligned with OpenAPI contract.
+[AC-AISVC-13] Entity models for database persistence.
+"""
+
+from enum import Enum
+from typing import Any
+
+from pydantic import BaseModel, Field
+
+
+class ChannelType(str, Enum):
+    WECHAT = "wechat"
+    DOUYIN = "douyin"
+    JD = "jd"
+
+
+class Role(str, Enum):
+    USER = "user"
+    ASSISTANT = "assistant"
+
+
+class ChatMessage(BaseModel):
+    role: Role = Field(..., description="Message role: user or assistant")
+    content: str = Field(..., description="Message content")
+
+
+class ChatRequest(BaseModel):
+    session_id: str = Field(..., alias="sessionId", description="Session ID for conversation tracking")
+    current_message: str = Field(..., alias="currentMessage", description="Current user message")
+    channel_type: ChannelType = Field(..., alias="channelType", description="Channel type: wechat, douyin, jd")
+    history: list[ChatMessage] | None = Field(default=None, description="Optional conversation history")
+    metadata: dict[str, Any] | None = Field(default=None, description="Optional metadata")
+
+    model_config = {"populate_by_name": True}
+
+
+class ChatResponse(BaseModel):
+    reply: str = Field(..., description="AI generated reply content")
+    confidence: float = Field(..., ge=0.0, le=1.0, description="Confidence score between 0.0 and 1.0")
+    should_transfer: bool = Field(..., alias="shouldTransfer", description="Whether to suggest transfer to human agent")
+    transfer_reason: str | None = Field(default=None, alias="transferReason", description="Reason for transfer suggestion")
+    metadata: dict[str, Any] | None = Field(default=None, description="Response metadata")
+
+    model_config = {"populate_by_name": True}
+
+
+class ErrorCode(str, Enum):
+    INVALID_REQUEST = "INVALID_REQUEST"
+    MISSING_TENANT_ID = "MISSING_TENANT_ID"
+    INTERNAL_ERROR = "INTERNAL_ERROR"
+    SERVICE_UNAVAILABLE = "SERVICE_UNAVAILABLE"
+    TIMEOUT = "TIMEOUT"
+    LLM_ERROR = "LLM_ERROR"
+    RETRIEVAL_ERROR = "RETRIEVAL_ERROR"
+
+
+class ErrorResponse(BaseModel):
+    code: str = Field(..., description="Error code")
+    message: str = Field(..., description="Error message")
+    details: list[dict[str, Any]] | None = Field(default=None, description="Detailed error information")
+
+
+class SSEEventType(str, Enum):
+    MESSAGE = "message"
+    FINAL = "final"
+    ERROR = "error"
+
+
+class SSEMessageEvent(BaseModel):
+    delta: str = Field(..., description="Incremental text content")
+
+
+class SSEFinalEvent(BaseModel):
+    reply: str = Field(..., description="Complete AI reply")
+    confidence: float = Field(..., ge=0.0, le=1.0, description="Confidence score")
+    should_transfer: bool = Field(..., alias="shouldTransfer", description="Transfer suggestion")
+    transfer_reason: str | None = Field(default=None, alias="transferReason", description="Transfer reason")
+    metadata: dict[str, Any] | None = Field(default=None, description="Response metadata")
+
+    model_config = {"populate_by_name": True}
+
+
+class SSEErrorEvent(BaseModel):
+    code: str = Field(..., description="Error code")
+    message: str = Field(..., description="Error message")
+    details: list[dict[str, Any]] | None = Field(default=None, description="Error details")

ai-service/app/models/entities.py

@@ -0,0 +1,74 @@
+"""
+Memory layer entities for AI Service.
+[AC-AISVC-13] SQLModel entities for chat sessions and messages with tenant isolation.
+"""
+
+import uuid
+from datetime import datetime
+from typing import Any
+
+from sqlalchemy import Column, JSON
+from sqlmodel import Field, Index, SQLModel
+
+
+class ChatSession(SQLModel, table=True):
+    """
+    [AC-AISVC-13] Chat session entity with tenant isolation.
+    Primary key: (tenant_id, session_id) composite unique constraint.
+    """
+
+    __tablename__ = "chat_sessions"
+    __table_args__ = (
+        Index("ix_chat_sessions_tenant_session", "tenant_id", "session_id", unique=True),
+        Index("ix_chat_sessions_tenant_id", "tenant_id"),
+    )
+
+    id: uuid.UUID = Field(default_factory=uuid.uuid4, primary_key=True)
+    tenant_id: str = Field(..., description="Tenant ID for multi-tenant isolation", index=True)
+    session_id: str = Field(..., description="Session ID for conversation tracking")
+    channel_type: str | None = Field(default=None, description="Channel type: wechat, douyin, jd")
+    metadata_: dict[str, Any] | None = Field(
+        default=None,
+        sa_column=Column("metadata", JSON, nullable=True),
+        description="Session metadata"
+    )
+    created_at: datetime = Field(default_factory=datetime.utcnow, description="Session creation time")
+    updated_at: datetime = Field(default_factory=datetime.utcnow, description="Last update time")
+
+
+class ChatMessage(SQLModel, table=True):
+    """
+    [AC-AISVC-13] Chat message entity with tenant isolation.
+    Messages are scoped by (tenant_id, session_id) for multi-tenant security.
+    """
+
+    __tablename__ = "chat_messages"
+    __table_args__ = (
+        Index("ix_chat_messages_tenant_session", "tenant_id", "session_id"),
+        Index("ix_chat_messages_tenant_session_created", "tenant_id", "session_id", "created_at"),
+    )
+
+    id: uuid.UUID = Field(default_factory=uuid.uuid4, primary_key=True)
+    tenant_id: str = Field(..., description="Tenant ID for multi-tenant isolation", index=True)
+    session_id: str = Field(..., description="Session ID for conversation tracking", index=True)
+    role: str = Field(..., description="Message role: user or assistant")
+    content: str = Field(..., description="Message content")
+    created_at: datetime = Field(default_factory=datetime.utcnow, description="Message creation time")
+
+
+class ChatSessionCreate(SQLModel):
+    """Schema for creating a new chat session."""
+
+    tenant_id: str
+    session_id: str
+    channel_type: str | None = None
+    metadata_: dict[str, Any] | None = None
+
+
+class ChatMessageCreate(SQLModel):
+    """Schema for creating a new chat message."""
+
+    tenant_id: str
+    session_id: str
+    role: str
+    content: str

ai-service/app/services/__init__.py

@@ -0,0 +1,9 @@
+"""
+Services module for AI Service.
+[AC-AISVC-13, AC-AISVC-16] Core services for memory and retrieval.
+"""
+
+from app.services.memory import MemoryService
+from app.services.orchestrator import OrchestratorService, get_orchestrator_service
+
+__all__ = ["MemoryService", "OrchestratorService", "get_orchestrator_service"]

ai-service/app/services/llm/__init__.py

@@ -0,0 +1,15 @@
+"""
+LLM Adapter module for AI Service.
+[AC-AISVC-02, AC-AISVC-06] Provides unified interface for LLM providers.
+"""
+
+from app.services.llm.base import LLMClient, LLMConfig, LLMResponse, LLMStreamChunk
+from app.services.llm.openai_client import OpenAIClient
+
+__all__ = [
+    "LLMClient",
+    "LLMConfig",
+    "LLMResponse",
+    "LLMStreamChunk",
+    "OpenAIClient",
+]

ai-service/app/services/llm/base.py

@@ -0,0 +1,115 @@
+"""
+Base LLM client interface.
+[AC-AISVC-02, AC-AISVC-06] Abstract interface for LLM providers.
+
+Design reference: design.md Section 8.1 - LLMClient interface
+- generate(prompt, params) -> text
+- stream_generate(prompt, params) -> iterator[delta]
+"""
+
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from typing import Any, AsyncGenerator
+
+
+@dataclass
+class LLMConfig:
+    """
+    Configuration for LLM client.
+    [AC-AISVC-02] Supports configurable model parameters.
+    """
+    model: str = "gpt-4o-mini"
+    max_tokens: int = 2048
+    temperature: float = 0.7
+    top_p: float = 1.0
+    timeout_seconds: int = 30
+    max_retries: int = 3
+    extra_params: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class LLMResponse:
+    """
+    Response from LLM generation.
+    [AC-AISVC-02] Contains generated content and metadata.
+    """
+    content: str
+    model: str
+    usage: dict[str, int] = field(default_factory=dict)
+    finish_reason: str = "stop"
+    metadata: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class LLMStreamChunk:
+    """
+    Streaming chunk from LLM.
+    [AC-AISVC-06, AC-AISVC-07] Incremental output for SSE streaming.
+    """
+    delta: str
+    model: str
+    finish_reason: str | None = None
+    metadata: dict[str, Any] = field(default_factory=dict)
+
+
+class LLMClient(ABC):
+    """
+    Abstract base class for LLM clients.
+    [AC-AISVC-02, AC-AISVC-06] Provides unified interface for different LLM providers.
+
+    Design reference: design.md Section 8.2 - Plugin points
+    - OpenAICompatibleClient / LocalModelClient can be swapped
+    """
+
+    @abstractmethod
+    async def generate(
+        self,
+        messages: list[dict[str, str]],
+        config: LLMConfig | None = None,
+        **kwargs: Any,
+    ) -> LLMResponse:
+        """
+        Generate a non-streaming response.
+        [AC-AISVC-02] Returns complete response for ChatResponse.
+
+        Args:
+            messages: List of chat messages with 'role' and 'content'.
+            config: Optional LLM configuration overrides.
+            **kwargs: Additional provider-specific parameters.
+
+        Returns:
+            LLMResponse with generated content and metadata.
+
+        Raises:
+            LLMException: If generation fails.
+        """
+        pass
+
+    @abstractmethod
+    async def stream_generate(
+        self,
+        messages: list[dict[str, str]],
+        config: LLMConfig | None = None,
+        **kwargs: Any,
+    ) -> AsyncGenerator[LLMStreamChunk, None]:
+        """
+        Generate a streaming response.
+        [AC-AISVC-06, AC-AISVC-07] Yields incremental chunks for SSE.
+
+        Args:
+            messages: List of chat messages with 'role' and 'content'.
+            config: Optional LLM configuration overrides.
+            **kwargs: Additional provider-specific parameters.
+
+        Yields:
+            LLMStreamChunk with incremental content.
+
+        Raises:
+            LLMException: If generation fails.
+        """
+        pass
+
+    @abstractmethod
+    async def close(self) -> None:
+        """Close the client and release resources."""
+        pass

ai-service/app/services/llm/openai_client.py

@@ -0,0 +1,319 @@
+"""
+OpenAI-compatible LLM client implementation.
+[AC-AISVC-02, AC-AISVC-06] Concrete implementation using httpx for OpenAI API.
+
+Design reference: design.md Section 8.1 - LLMClient interface
+- Uses langchain-openai or official SDK pattern
+- Supports generate and stream_generate
+"""
+
+import json
+import logging
+from typing import Any, AsyncGenerator
+
+import httpx
+from tenacity import (
+    retry,
+    retry_if_exception_type,
+    stop_after_attempt,
+    wait_exponential,
+)
+
+from app.core.config import get_settings
+from app.core.exceptions import AIServiceException, ErrorCode, ServiceUnavailableException, TimeoutException
+from app.services.llm.base import LLMClient, LLMConfig, LLMResponse, LLMStreamChunk
+
+logger = logging.getLogger(__name__)
+
+
+class LLMException(AIServiceException):
+    """Exception raised when LLM operations fail."""
+
+    def __init__(self, message: str, details: list[dict] | None = None):
+        super().__init__(
+            code=ErrorCode.LLM_ERROR,
+            message=message,
+            status_code=503,
+            details=details,
+        )
+
+
+class OpenAIClient(LLMClient):
+    """
+    OpenAI-compatible LLM client.
+    [AC-AISVC-02, AC-AISVC-06] Implements LLMClient interface for OpenAI API.
+
+    Supports:
+    - OpenAI API (official)
+    - OpenAI-compatible endpoints (Azure, local models, etc.)
+    """
+
+    def __init__(
+        self,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        model: str | None = None,
+        default_config: LLMConfig | None = None,
+    ):
+        settings = get_settings()
+        self._api_key = api_key or settings.llm_api_key
+        self._base_url = (base_url or settings.llm_base_url).rstrip("/")
+        self._model = model or settings.llm_model
+        self._default_config = default_config or LLMConfig(
+            model=self._model,
+            max_tokens=settings.llm_max_tokens,
+            temperature=settings.llm_temperature,
+            timeout_seconds=settings.llm_timeout_seconds,
+            max_retries=settings.llm_max_retries,
+        )
+        self._client: httpx.AsyncClient | None = None
+
+    def _get_client(self, timeout_seconds: int) -> httpx.AsyncClient:
+        """Get or create HTTP client."""
+        if self._client is None:
+            self._client = httpx.AsyncClient(
+                timeout=httpx.Timeout(timeout_seconds),
+                headers={
+                    "Authorization": f"Bearer {self._api_key}",
+                    "Content-Type": "application/json",
+                },
+            )
+        return self._client
+
+    def _build_request_body(
+        self,
+        messages: list[dict[str, str]],
+        config: LLMConfig,
+        stream: bool = False,
+        **kwargs: Any,
+    ) -> dict[str, Any]:
+        """Build request body for OpenAI API."""
+        body: dict[str, Any] = {
+            "model": config.model,
+            "messages": messages,
+            "max_tokens": config.max_tokens,
+            "temperature": config.temperature,
+            "top_p": config.top_p,
+            "stream": stream,
+        }
+        body.update(config.extra_params)
+        body.update(kwargs)
+        return body
+
+    @retry(
+        retry=retry_if_exception_type(httpx.TimeoutException),
+        stop=stop_after_attempt(3),
+        wait=wait_exponential(multiplier=1, min=1, max=10),
+    )
+    async def generate(
+        self,
+        messages: list[dict[str, str]],
+        config: LLMConfig | None = None,
+        **kwargs: Any,
+    ) -> LLMResponse:
+        """
+        Generate a non-streaming response.
+        [AC-AISVC-02] Returns complete response for ChatResponse.
+
+        Args:
+            messages: List of chat messages with 'role' and 'content'.
+            config: Optional LLM configuration overrides.
+            **kwargs: Additional provider-specific parameters.
+
+        Returns:
+            LLMResponse with generated content and metadata.
+
+        Raises:
+            LLMException: If generation fails.
+            TimeoutException: If request times out.
+        """
+        effective_config = config or self._default_config
+        client = self._get_client(effective_config.timeout_seconds)
+
+        body = self._build_request_body(messages, effective_config, stream=False, **kwargs)
+
+        logger.info(f"[AC-AISVC-02] Generating response with model={effective_config.model}")
+
+        try:
+            response = await client.post(
+                f"{self._base_url}/chat/completions",
+                json=body,
+            )
+            response.raise_for_status()
+            data = response.json()
+
+        except httpx.TimeoutException as e:
+            logger.error(f"[AC-AISVC-02] LLM request timeout: {e}")
+            raise TimeoutException(message=f"LLM request timed out: {e}")
+
+        except httpx.HTTPStatusError as e:
+            logger.error(f"[AC-AISVC-02] LLM API error: {e}")
+            error_detail = self._parse_error_response(e.response)
+            raise LLMException(
+                message=f"LLM API error: {error_detail}",
+                details=[{"status_code": e.response.status_code, "response": error_detail}],
+            )
+
+        except json.JSONDecodeError as e:
+            logger.error(f"[AC-AISVC-02] Failed to parse LLM response: {e}")
+            raise LLMException(message=f"Failed to parse LLM response: {e}")
+
+        try:
+            choice = data["choices"][0]
+            content = choice["message"]["content"]
+            usage = data.get("usage", {})
+            finish_reason = choice.get("finish_reason", "stop")
+
+            logger.info(
+                f"[AC-AISVC-02] Generated response: "
+                f"tokens={usage.get('total_tokens', 'N/A')}, "
+                f"finish_reason={finish_reason}"
+            )
+
+            return LLMResponse(
+                content=content,
+                model=data.get("model", effective_config.model),
+                usage=usage,
+                finish_reason=finish_reason,
+                metadata={"raw_response": data},
+            )
+
+        except (KeyError, IndexError) as e:
+            logger.error(f"[AC-AISVC-02] Unexpected LLM response format: {e}")
+            raise LLMException(
+                message=f"Unexpected LLM response format: {e}",
+                details=[{"response": str(data)}],
+            )
+
+    async def stream_generate(
+        self,
+        messages: list[dict[str, str]],
+        config: LLMConfig | None = None,
+        **kwargs: Any,
+    ) -> AsyncGenerator[LLMStreamChunk, None]:
+        """
+        Generate a streaming response.
+        [AC-AISVC-06, AC-AISVC-07] Yields incremental chunks for SSE.
+
+        Args:
+            messages: List of chat messages with 'role' and 'content'.
+            config: Optional LLM configuration overrides.
+            **kwargs: Additional provider-specific parameters.
+
+        Yields:
+            LLMStreamChunk with incremental content.
+
+        Raises:
+            LLMException: If generation fails.
+            TimeoutException: If request times out.
+        """
+        effective_config = config or self._default_config
+        client = self._get_client(effective_config.timeout_seconds)
+
+        body = self._build_request_body(messages, effective_config, stream=True, **kwargs)
+
+        logger.info(f"[AC-AISVC-06] Starting streaming generation with model={effective_config.model}")
+
+        try:
+            async with client.stream(
+                "POST",
+                f"{self._base_url}/chat/completions",
+                json=body,
+            ) as response:
+                response.raise_for_status()
+
+                async for line in response.aiter_lines():
+                    if not line or line == "data: [DONE]":
+                        continue
+
+                    if line.startswith("data: "):
+                        json_str = line[6:]
+                        try:
+                            chunk_data = json.loads(json_str)
+                            chunk = self._parse_stream_chunk(chunk_data, effective_config.model)
+                            if chunk:
+                                yield chunk
+                        except json.JSONDecodeError as e:
+                            logger.warning(f"[AC-AISVC-06] Failed to parse stream chunk: {e}")
+                            continue
+
+        except httpx.TimeoutException as e:
+            logger.error(f"[AC-AISVC-06] LLM streaming request timeout: {e}")
+            raise TimeoutException(message=f"LLM streaming request timed out: {e}")
+
+        except httpx.HTTPStatusError as e:
+            logger.error(f"[AC-AISVC-06] LLM streaming API error: {e}")
+            error_detail = self._parse_error_response(e.response)
+            raise LLMException(
+                message=f"LLM streaming API error: {error_detail}",
+                details=[{"status_code": e.response.status_code, "response": error_detail}],
+            )
+
+        logger.info(f"[AC-AISVC-06] Streaming generation completed")
+
+    def _parse_stream_chunk(
+        self,
+        data: dict[str, Any],
+        model: str,
+    ) -> LLMStreamChunk | None:
+        """Parse a streaming chunk from OpenAI API."""
+        try:
+            choices = data.get("choices", [])
+            if not choices:
+                return None
+
+            delta = choices[0].get("delta", {})
+            content = delta.get("content", "")
+            finish_reason = choices[0].get("finish_reason")
+
+            if not content and not finish_reason:
+                return None
+
+            return LLMStreamChunk(
+                delta=content,
+                model=data.get("model", model),
+                finish_reason=finish_reason,
+                metadata={"raw_chunk": data},
+            )
+
+        except (KeyError, IndexError) as e:
+            logger.warning(f"[AC-AISVC-06] Failed to parse stream chunk: {e}")
+            return None
+
+    def _parse_error_response(self, response: httpx.Response) -> str:
+        """Parse error response from API."""
+        try:
+            data = response.json()
+            if "error" in data:
+                error = data["error"]
+                if isinstance(error, dict):
+                    return error.get("message", str(error))
+                return str(error)
+            return response.text
+        except Exception:
+            return response.text
+
+    async def close(self) -> None:
+        """Close the HTTP client."""
+        if self._client:
+            await self._client.aclose()
+            self._client = None
+
+
+_llm_client: OpenAIClient | None = None
+
+
+def get_llm_client() -> OpenAIClient:
+    """Get or create LLM client instance."""
+    global _llm_client
+    if _llm_client is None:
+        _llm_client = OpenAIClient()
+    return _llm_client
+
+
+async def close_llm_client() -> None:
+    """Close the global LLM client."""
+    global _llm_client
+    if _llm_client:
+        await _llm_client.close()
+        _llm_client = None

ai-service/app/services/memory.py

@@ -0,0 +1,170 @@
+"""
+Memory service for AI Service.
+[AC-AISVC-13] Session-based memory management with tenant isolation.
+"""
+
+import logging
+from typing import Sequence
+
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlmodel import col
+
+from app.models.entities import ChatMessage, ChatMessageCreate, ChatSession, ChatSessionCreate
+
+logger = logging.getLogger(__name__)
+
+
+class MemoryService:
+    """
+    [AC-AISVC-13] Memory service for session-based conversation history.
+    All operations are scoped by (tenant_id, session_id) for multi-tenant isolation.
+    """
+
+    def __init__(self, session: AsyncSession):
+        self._session = session
+
+    async def get_or_create_session(
+        self,
+        tenant_id: str,
+        session_id: str,
+        channel_type: str | None = None,
+        metadata: dict | None = None,
+    ) -> ChatSession:
+        """
+        [AC-AISVC-13] Get existing session or create a new one.
+        Ensures tenant isolation by querying with tenant_id.
+        """
+        stmt = select(ChatSession).where(
+            ChatSession.tenant_id == tenant_id,
+            ChatSession.session_id == session_id,
+        )
+        result = await self._session.execute(stmt)
+        existing_session = result.scalar_one_or_none()
+
+        if existing_session:
+            logger.info(
+                f"[AC-AISVC-13] Found existing session: tenant={tenant_id}, session={session_id}"
+            )
+            return existing_session
+
+        new_session = ChatSession(
+            tenant_id=tenant_id,
+            session_id=session_id,
+            channel_type=channel_type,
+            metadata_=metadata,
+        )
+        self._session.add(new_session)
+        await self._session.flush()
+
+        logger.info(
+            f"[AC-AISVC-13] Created new session: tenant={tenant_id}, session={session_id}"
+        )
+        return new_session
+
+    async def load_history(
+        self,
+        tenant_id: str,
+        session_id: str,
+        limit: int | None = None,
+    ) -> Sequence[ChatMessage]:
+        """
+        [AC-AISVC-13] Load conversation history for a session.
+        All queries are filtered by tenant_id to ensure isolation.
+        """
+        stmt = (
+            select(ChatMessage)
+            .where(
+                ChatMessage.tenant_id == tenant_id,
+                ChatMessage.session_id == session_id,
+            )
+            .order_by(col(ChatMessage.created_at).asc())
+        )
+
+        if limit:
+            stmt = stmt.limit(limit)
+
+        result = await self._session.execute(stmt)
+        messages = result.scalars().all()
+
+        logger.info(
+            f"[AC-AISVC-13] Loaded {len(messages)} messages for tenant={tenant_id}, session={session_id}"
+        )
+        return messages
+
+    async def append_message(
+        self,
+        tenant_id: str,
+        session_id: str,
+        role: str,
+        content: str,
+    ) -> ChatMessage:
+        """
+        [AC-AISVC-13] Append a message to the session history.
+        Message is scoped by tenant_id for isolation.
+        """
+        message = ChatMessage(
+            tenant_id=tenant_id,
+            session_id=session_id,
+            role=role,
+            content=content,
+        )
+        self._session.add(message)
+        await self._session.flush()
+
+        logger.info(
+            f"[AC-AISVC-13] Appended message: tenant={tenant_id}, session={session_id}, role={role}"
+        )
+        return message
+
+    async def append_messages(
+        self,
+        tenant_id: str,
+        session_id: str,
+        messages: list[dict[str, str]],
+    ) -> list[ChatMessage]:
+        """
+        [AC-AISVC-13] Append multiple messages to the session history.
+        Used for batch insertion of conversation turns.
+        """
+        chat_messages = []
+        for msg in messages:
+            message = ChatMessage(
+                tenant_id=tenant_id,
+                session_id=session_id,
+                role=msg["role"],
+                content=msg["content"],
+            )
+            self._session.add(message)
+            chat_messages.append(message)
+
+        await self._session.flush()
+
+        logger.info(
+            f"[AC-AISVC-13] Appended {len(chat_messages)} messages for tenant={tenant_id}, session={session_id}"
+        )
+        return chat_messages
+
+    async def clear_history(self, tenant_id: str, session_id: str) -> int:
+        """
+        [AC-AISVC-13] Clear all messages for a session.
+        Only affects messages within the tenant's scope.
+        """
+        stmt = select(ChatMessage).where(
+            ChatMessage.tenant_id == tenant_id,
+            ChatMessage.session_id == session_id,
+        )
+        result = await self._session.execute(stmt)
+        messages = result.scalars().all()
+
+        count = 0
+        for message in messages:
+            await self._session.delete(message)
+            count += 1
+
+        await self._session.flush()
+
+        logger.info(
+            f"[AC-AISVC-13] Cleared {count} messages for tenant={tenant_id}, session={session_id}"
+        )
+        return count

ai-service/app/services/orchestrator.py

@@ -0,0 +1,97 @@
+"""
+Orchestrator service for AI Service.
+[AC-AISVC-01, AC-AISVC-02] Core orchestration logic for chat generation.
+"""
+
+import logging
+from typing import AsyncGenerator
+
+from sse_starlette.sse import ServerSentEvent
+
+from app.models import ChatRequest, ChatResponse
+from app.core.sse import create_final_event, create_message_event, SSEStateMachine
+
+logger = logging.getLogger(__name__)
+
+
+class OrchestratorService:
+    """
+    [AC-AISVC-01, AC-AISVC-02] Orchestrator for chat generation.
+    Coordinates memory, retrieval, and LLM components.
+    """
+
+    async def generate(self, tenant_id: str, request: ChatRequest) -> ChatResponse:
+        """
+        Generate a non-streaming response.
+        [AC-AISVC-02] Returns ChatResponse with reply, confidence, shouldTransfer.
+        """
+        logger.info(
+            f"[AC-AISVC-01] Generating response for tenant={tenant_id}, "
+            f"session={request.session_id}"
+        )
+
+        reply = f"Received your message: {request.current_message}"
+        return ChatResponse(
+            reply=reply,
+            confidence=0.85,
+            should_transfer=False,
+        )
+
+    async def generate_stream(
+        self, tenant_id: str, request: ChatRequest
+    ) -> AsyncGenerator[ServerSentEvent, None]:
+        """
+        Generate a streaming response.
+        [AC-AISVC-06, AC-AISVC-07, AC-AISVC-08] Yields SSE events in proper sequence.
+        """
+        logger.info(
+            f"[AC-AISVC-06] Starting streaming generation for tenant={tenant_id}, "
+            f"session={request.session_id}"
+        )
+
+        state_machine = SSEStateMachine()
+        await state_machine.transition_to_streaming()
+
+        try:
+            reply_parts = ["Received", " your", " message:", f" {request.current_message}"]
+            full_reply = ""
+
+            for part in reply_parts:
+                if state_machine.can_send_message():
+                    full_reply += part
+                    yield create_message_event(delta=part)
+                await self._simulate_llm_delay()
+
+            if await state_machine.transition_to_final():
+                yield create_final_event(
+                    reply=full_reply,
+                    confidence=0.85,
+                    should_transfer=False,
+                )
+
+        except Exception as e:
+            logger.error(f"[AC-AISVC-09] Error during streaming: {e}")
+            if await state_machine.transition_to_error():
+                from app.core.sse import create_error_event
+                yield create_error_event(
+                    code="GENERATION_ERROR",
+                    message=str(e),
+                )
+        finally:
+            await state_machine.close()
+
+    async def _simulate_llm_delay(self) -> None:
+        """Simulate LLM processing delay for demo purposes."""
+        import asyncio
+        await asyncio.sleep(0.1)
+
+
+_orchestrator_service: OrchestratorService | None = None
+
+
+def get_orchestrator_service() -> OrchestratorService:
+    """Get or create orchestrator service instance."""
+    global _orchestrator_service
+    if _orchestrator_service is None:
+        _orchestrator_service = OrchestratorService()
+    return _orchestrator_service

ai-service/app/services/retrieval/__init__.py

@@ -0,0 +1,21 @@
+"""
+Retrieval module for AI Service.
+[AC-AISVC-16] Provides retriever implementations with plugin architecture.
+"""
+
+from app.services.retrieval.base import (
+    BaseRetriever,
+    RetrievalContext,
+    RetrievalHit,
+    RetrievalResult,
+)
+from app.services.retrieval.vector_retriever import VectorRetriever, get_vector_retriever
+
+__all__ = [
+    "BaseRetriever",
+    "RetrievalContext",
+    "RetrievalHit",
+    "RetrievalResult",
+    "VectorRetriever",
+    "get_vector_retriever",
+]

ai-service/app/services/retrieval/base.py

@@ -0,0 +1,96 @@
+"""
+Retrieval layer for AI Service.
+[AC-AISVC-16] Abstract base class for retrievers with plugin point support.
+"""
+
+import logging
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class RetrievalContext:
+    """
+    [AC-AISVC-16] Context for retrieval operations.
+    Contains all necessary information for retrieval plugins.
+    """
+
+    tenant_id: str
+    query: str
+    session_id: str | None = None
+    channel_type: str | None = None
+    metadata: dict[str, Any] | None = None
+
+
+@dataclass
+class RetrievalHit:
+    """
+    [AC-AISVC-16] Single retrieval result hit.
+    Unified structure for all retriever types.
+    """
+
+    text: str
+    score: float
+    source: str
+    metadata: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class RetrievalResult:
+    """
+    [AC-AISVC-16] Result from retrieval operation.
+    Contains hits and optional diagnostics.
+    """
+
+    hits: list[RetrievalHit] = field(default_factory=list)
+    diagnostics: dict[str, Any] | None = None
+
+    @property
+    def is_empty(self) -> bool:
+        """Check if no hits were found."""
+        return len(self.hits) == 0
+
+    @property
+    def max_score(self) -> float:
+        """Get the maximum score among hits."""
+        if not self.hits:
+            return 0.0
+        return max(hit.score for hit in self.hits)
+
+    @property
+    def hit_count(self) -> int:
+        """Get the number of hits."""
+        return len(self.hits)
+
+
+class BaseRetriever(ABC):
+    """
+    [AC-AISVC-16] Abstract base class for retrievers.
+    Provides plugin point for different retrieval strategies (Vector, Graph, Hybrid).
+    """
+
+    @abstractmethod
+    async def retrieve(self, ctx: RetrievalContext) -> RetrievalResult:
+        """
+        [AC-AISVC-16] Retrieve relevant documents for the given context.
+
+        Args:
+            ctx: Retrieval context containing tenant_id, query, and optional metadata.
+
+        Returns:
+            RetrievalResult with hits and optional diagnostics.
+        """
+        pass
+
+    @abstractmethod
+    async def health_check(self) -> bool:
+        """
+        Check if the retriever is healthy and ready to serve requests.
+
+        Returns:
+            True if healthy, False otherwise.
+        """
+        pass

ai-service/app/services/retrieval/vector_retriever.py

@@ -0,0 +1,169 @@
+"""
+Vector retriever for AI Service.
+[AC-AISVC-16, AC-AISVC-17] Qdrant-based vector retrieval with score threshold filtering.
+"""
+
+import logging
+from typing import Any
+
+from app.core.config import get_settings
+from app.core.qdrant_client import QdrantClient, get_qdrant_client
+from app.services.retrieval.base import (
+    BaseRetriever,
+    RetrievalContext,
+    RetrievalHit,
+    RetrievalResult,
+)
+
+logger = logging.getLogger(__name__)
+
+settings = get_settings()
+
+
+class VectorRetriever(BaseRetriever):
+    """
+    [AC-AISVC-16, AC-AISVC-17] Vector-based retriever using Qdrant.
+    Supports score threshold filtering and tenant isolation.
+    """
+
+    def __init__(
+        self,
+        qdrant_client: QdrantClient | None = None,
+        top_k: int | None = None,
+        score_threshold: float | None = None,
+        min_hits: int | None = None,
+    ):
+        self._qdrant_client = qdrant_client
+        self._top_k = top_k or settings.rag_top_k
+        self._score_threshold = score_threshold or settings.rag_score_threshold
+        self._min_hits = min_hits or settings.rag_min_hits
+
+    async def _get_client(self) -> QdrantClient:
+        """Get Qdrant client instance."""
+        if self._qdrant_client is None:
+            self._qdrant_client = await get_qdrant_client()
+        return self._qdrant_client
+
+    async def retrieve(self, ctx: RetrievalContext) -> RetrievalResult:
+        """
+        [AC-AISVC-16, AC-AISVC-17] Retrieve documents from vector store.
+
+        Steps:
+        1. Generate embedding for query (placeholder - requires embedding provider)
+        2. Search in tenant's collection
+        3. Filter by score threshold
+        4. Return structured result
+
+        Args:
+            ctx: Retrieval context with tenant_id and query.
+
+        Returns:
+            RetrievalResult with filtered hits.
+        """
+        logger.info(
+            f"[AC-AISVC-16] Starting vector retrieval for tenant={ctx.tenant_id}, query={ctx.query[:50]}..."
+        )
+
+        try:
+            client = await self._get_client()
+
+            query_vector = await self._get_embedding(ctx.query)
+
+            hits = await client.search(
+                tenant_id=ctx.tenant_id,
+                query_vector=query_vector,
+                limit=self._top_k,
+                score_threshold=self._score_threshold,
+            )
+
+            retrieval_hits = [
+                RetrievalHit(
+                    text=hit.get("payload", {}).get("text", ""),
+                    score=hit.get("score", 0.0),
+                    source=hit.get("payload", {}).get("source", "vector"),
+                    metadata=hit.get("payload", {}),
+                )
+                for hit in hits
+                if hit.get("score", 0.0) >= self._score_threshold
+            ]
+
+            is_insufficient = len(retrieval_hits) < self._min_hits
+
+            diagnostics = {
+                "query_length": len(ctx.query),
+                "top_k": self._top_k,
+                "score_threshold": self._score_threshold,
+                "min_hits": self._min_hits,
+                "total_candidates": len(hits),
+                "filtered_hits": len(retrieval_hits),
+                "is_insufficient": is_insufficient,
+                "max_score": max((h.score for h in retrieval_hits), default=0.0),
+            }
+
+            logger.info(
+                f"[AC-AISVC-17] Retrieval complete: {len(retrieval_hits)} hits, "
+                f"insufficient={is_insufficient}, max_score={diagnostics['max_score']:.3f}"
+            )
+
+            return RetrievalResult(
+                hits=retrieval_hits,
+                diagnostics=diagnostics,
+            )
+
+        except Exception as e:
+            logger.error(f"[AC-AISVC-16] Retrieval error: {e}")
+            return RetrievalResult(
+                hits=[],
+                diagnostics={"error": str(e), "is_insufficient": True},
+            )
+
+    async def _get_embedding(self, text: str) -> list[float]:
+        """
+        Generate embedding for text.
+        [AC-AISVC-16] Placeholder for embedding generation.
+
+        TODO: Integrate with actual embedding provider (OpenAI, local model, etc.)
+        """
+        import hashlib
+
+        hash_obj = hashlib.sha256(text.encode())
+        hash_bytes = hash_obj.digest()
+
+        embedding = []
+        for i in range(0, min(len(hash_bytes) * 8, settings.qdrant_vector_size)):
+            byte_idx = i // 8
+            bit_idx = i % 8
+            if byte_idx < len(hash_bytes):
+                val = (hash_bytes[byte_idx] >> bit_idx) & 1
+                embedding.append(float(val))
+            else:
+                embedding.append(0.0)
+
+        while len(embedding) < settings.qdrant_vector_size:
+            embedding.append(0.0)
+
+        return embedding[: settings.qdrant_vector_size]
+
+    async def health_check(self) -> bool:
+        """
+        [AC-AISVC-16] Check if Qdrant connection is healthy.
+        """
+        try:
+            client = await self._get_client()
+            qdrant = await client.get_client()
+            await qdrant.get_collections()
+            return True
+        except Exception as e:
+            logger.error(f"[AC-AISVC-16] Health check failed: {e}")
+            return False
+
+
+_vector_retriever: VectorRetriever | None = None
+
+
+async def get_vector_retriever() -> VectorRetriever:
+    """Get or create VectorRetriever instance."""
+    global _vector_retriever
+    if _vector_retriever is None:
+        _vector_retriever = VectorRetriever()
+    return _vector_retriever

ai-service/pyproject.toml

@@ -0,0 +1,53 @@
+[project]
+name = "ai-service"
+version = "0.1.0"
+description = "Python AI Service for intelligent chat with RAG support"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "fastapi>=0.109.0",
+    "uvicorn[standard]>=0.27.0",
+    "pydantic>=2.5.0",
+    "pydantic-settings>=2.1.0",
+    "sse-starlette>=2.0.0",
+    "httpx>=0.26.0",
+    "tenacity>=8.2.0",
+    "sqlmodel>=0.0.14",
+    "asyncpg>=0.29.0",
+    "qdrant-client>=1.7.0",
+    "tiktoken>=0.5.0",
+]
+
+[project.optional-dependencies]
+dev = [
+    "pytest>=7.4.0",
+    "pytest-asyncio>=0.23.0",
+    "pytest-cov>=4.1.0",
+    "httpx>=0.26.0",
+    "ruff>=0.1.0",
+    "mypy>=1.8.0",
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["app"]
+
+[tool.ruff]
+line-length = 120
+target-version = "py310"
+
+[tool.ruff.lint]
+select = ["E", "F", "I", "N", "W", "UP"]
+
+[tool.mypy]
+python_version = "3.10"
+strict = true
+warn_return_any = true
+warn_unused_configs = true
+
+[tool.pytest.ini_options]
+asyncio_mode = "auto"
+testpaths = ["tests"]

ai-service/tests/__init__.py

@@ -0,0 +1,3 @@
+"""
+Tests package for AI Service.
+"""

ai-service/tests/conftest.py

@@ -0,0 +1,10 @@
+"""
+Pytest configuration for AI Service tests.
+"""
+
+import pytest
+
+
+@pytest.fixture
+def anyio_backend():
+    return "asyncio"

ai-service/tests/test_accept_switching.py

@@ -0,0 +1,285 @@
+"""
+Tests for response mode switching based on Accept header.
+[AC-AISVC-06] Tests for automatic switching between JSON and SSE streaming modes.
+"""
+
+import pytest
+from fastapi.testclient import TestClient
+from httpx import AsyncClient
+
+from app.main import app
+
+
+class TestAcceptHeaderSwitching:
+    """
+    [AC-AISVC-06] Test cases for Accept header based response mode switching.
+    """
+
+    @pytest.fixture
+    def client(self):
+        return TestClient(app)
+
+    @pytest.fixture
+    def valid_request_body(self):
+        return {
+            "sessionId": "test_session_001",
+            "currentMessage": "Hello, how are you?",
+            "channelType": "wechat",
+        }
+
+    @pytest.fixture
+    def valid_headers(self):
+        return {"X-Tenant-Id": "tenant_001"}
+
+    def test_json_response_with_default_accept(
+        self, client: TestClient, valid_request_body: dict, valid_headers: dict
+    ):
+        """
+        [AC-AISVC-06] Test that default Accept header returns JSON response.
+        """
+        response = client.post(
+            "/ai/chat",
+            json=valid_request_body,
+            headers=valid_headers,
+        )
+
+        assert response.status_code == 200
+        assert response.headers["content-type"] == "application/json"
+
+        data = response.json()
+        assert "reply" in data
+        assert "confidence" in data
+        assert "shouldTransfer" in data
+
+    def test_json_response_with_application_json_accept(
+        self, client: TestClient, valid_request_body: dict, valid_headers: dict
+    ):
+        """
+        [AC-AISVC-06] Test that Accept: application/json returns JSON response.
+        """
+        headers = {**valid_headers, "Accept": "application/json"}
+
+        response = client.post(
+            "/ai/chat",
+            json=valid_request_body,
+            headers=headers,
+        )
+
+        assert response.status_code == 200
+        assert response.headers["content-type"] == "application/json"
+
+        data = response.json()
+        assert "reply" in data
+        assert "confidence" in data
+        assert "shouldTransfer" in data
+
+    def test_sse_response_with_text_event_stream_accept(
+        self, client: TestClient, valid_request_body: dict, valid_headers: dict
+    ):
+        """
+        [AC-AISVC-06] Test that Accept: text/event-stream returns SSE response.
+        """
+        headers = {**valid_headers, "Accept": "text/event-stream"}
+
+        response = client.post(
+            "/ai/chat",
+            json=valid_request_body,
+            headers=headers,
+        )
+
+        assert response.status_code == 200
+        assert "text/event-stream" in response.headers["content-type"]
+
+        content = response.text
+        assert "event: message" in content
+        assert "event: final" in content
+
+    def test_sse_response_event_sequence(
+        self, client: TestClient, valid_request_body: dict, valid_headers: dict
+    ):
+        """
+        [AC-AISVC-07, AC-AISVC-08] Test that SSE events follow proper sequence.
+        message* -> final -> close
+        """
+        headers = {**valid_headers, "Accept": "text/event-stream"}
+
+        response = client.post(
+            "/ai/chat",
+            json=valid_request_body,
+            headers=headers,
+        )
+
+        content = response.text
+
+        assert "event:message" in content or "event: message" in content, f"Expected message event in: {content[:500]}"
+        assert "event:final" in content or "event: final" in content, f"Expected final event in: {content[:500]}"
+
+        message_idx = content.find("event:message")
+        if message_idx == -1:
+            message_idx = content.find("event: message")
+        final_idx = content.find("event:final")
+        if final_idx == -1:
+            final_idx = content.find("event: final")
+
+        assert final_idx > message_idx, "final event should come after message events"
+
+    def test_missing_tenant_id_returns_400(
+        self, client: TestClient, valid_request_body: dict
+    ):
+        """
+        [AC-AISVC-12] Test that missing X-Tenant-Id returns 400 error.
+        """
+        response = client.post(
+            "/ai/chat",
+            json=valid_request_body,
+        )
+
+        assert response.status_code == 400
+
+        data = response.json()
+        assert data["code"] == "MISSING_TENANT_ID"
+        assert "message" in data
+
+    def test_invalid_channel_type_returns_400(
+        self, client: TestClient, valid_headers: dict
+    ):
+        """
+        [AC-AISVC-03] Test that invalid channel type returns 400 error.
+        """
+        invalid_body = {
+            "sessionId": "test_session_001",
+            "currentMessage": "Hello",
+            "channelType": "invalid_channel",
+        }
+
+        response = client.post(
+            "/ai/chat",
+            json=invalid_body,
+            headers=valid_headers,
+        )
+
+        assert response.status_code == 400
+
+    def test_missing_required_fields_returns_400(
+        self, client: TestClient, valid_headers: dict
+    ):
+        """
+        [AC-AISVC-03] Test that missing required fields return 400 error.
+        """
+        incomplete_body = {
+            "sessionId": "test_session_001",
+        }
+
+        response = client.post(
+            "/ai/chat",
+            json=incomplete_body,
+            headers=valid_headers,
+        )
+
+        assert response.status_code == 400
+
+
+class TestHealthEndpoint:
+    """
+    [AC-AISVC-20] Test cases for health check endpoint.
+    """
+
+    @pytest.fixture
+    def client(self):
+        return TestClient(app)
+
+    def test_health_check_returns_200(self, client: TestClient):
+        """
+        [AC-AISVC-20] Test that health check returns 200 with status.
+        """
+        response = client.get("/ai/health")
+
+        assert response.status_code == 200
+        data = response.json()
+        assert data["status"] == "healthy"
+
+
+class TestSSEStateMachine:
+    """
+    [AC-AISVC-08, AC-AISVC-09] Test cases for SSE state machine.
+    """
+
+    @pytest.mark.asyncio
+    async def test_state_transitions(self):
+        from app.core.sse import SSEState, SSEStateMachine
+
+        state_machine = SSEStateMachine()
+
+        assert state_machine.state == SSEState.INIT
+
+        success = await state_machine.transition_to_streaming()
+        assert success is True
+        assert state_machine.state == SSEState.STREAMING
+
+        assert state_machine.can_send_message() is True
+
+        success = await state_machine.transition_to_final()
+        assert success is True
+        assert state_machine.state == SSEState.FINAL_SENT
+
+        assert state_machine.can_send_message() is False
+
+        await state_machine.close()
+        assert state_machine.state == SSEState.CLOSED
+
+    @pytest.mark.asyncio
+    async def test_error_transition_from_streaming(self):
+        from app.core.sse import SSEState, SSEStateMachine
+
+        state_machine = SSEStateMachine()
+        await state_machine.transition_to_streaming()
+
+        success = await state_machine.transition_to_error()
+        assert success is True
+        assert state_machine.state == SSEState.ERROR_SENT
+
+    @pytest.mark.asyncio
+    async def test_cannot_transition_to_final_from_init(self):
+        from app.core.sse import SSEStateMachine
+
+        state_machine = SSEStateMachine()
+
+        success = await state_machine.transition_to_final()
+        assert success is False
+
+
+class TestMiddleware:
+    """
+    [AC-AISVC-10, AC-AISVC-12] Test cases for middleware.
+    """
+
+    @pytest.fixture
+    def client(self):
+        return TestClient(app)
+
+    def test_tenant_context_extraction(
+        self, client: TestClient
+    ):
+        """
+        [AC-AISVC-10] Test that X-Tenant-Id is properly extracted and used.
+        """
+        headers = {"X-Tenant-Id": "tenant_test_123"}
+        body = {
+            "sessionId": "session_001",
+            "currentMessage": "Test message",
+            "channelType": "wechat",
+        }
+
+        response = client.post("/ai/chat", json=body, headers=headers)
+
+        assert response.status_code == 200
+
+    def test_health_endpoint_bypasses_tenant_check(
+        self, client: TestClient
+    ):
+        """
+        Test that health endpoint doesn't require X-Tenant-Id.
+        """
+        response = client.get("/ai/health")
+
+        assert response.status_code == 200

ai-service/tests/test_llm_adapter.py

@@ -0,0 +1,319 @@
+"""
+Unit tests for LLM Adapter.
+[AC-AISVC-02, AC-AISVC-06] Tests for LLM client interface.
+
+Tests cover:
+- Non-streaming generation
+- Streaming generation
+- Error handling
+- Retry logic
+"""
+
+import json
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import httpx
+import pytest
+
+from app.services.llm.base import LLMConfig, LLMResponse, LLMStreamChunk
+from app.services.llm.openai_client import (
+    LLMException,
+    OpenAIClient,
+    TimeoutException,
+)
+
+
+@pytest.fixture
+def mock_settings():
+    """Mock settings for testing."""
+    settings = MagicMock()
+    settings.llm_api_key = "test-api-key"
+    settings.llm_base_url = "https://api.openai.com/v1"
+    settings.llm_model = "gpt-4o-mini"
+    settings.llm_max_tokens = 2048
+    settings.llm_temperature = 0.7
+    settings.llm_timeout_seconds = 30
+    settings.llm_max_retries = 3
+    return settings
+
+
+@pytest.fixture
+def llm_client(mock_settings):
+    """Create LLM client with mocked settings."""
+    with patch("app.services.llm.openai_client.get_settings", return_value=mock_settings):
+        client = OpenAIClient()
+        yield client
+
+
+@pytest.fixture
+def mock_messages():
+    """Sample chat messages for testing."""
+    return [
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Hello, how are you?"},
+    ]
+
+
+@pytest.fixture
+def mock_generate_response():
+    """Sample non-streaming response from OpenAI API."""
+    return {
+        "id": "chatcmpl-123",
+        "object": "chat.completion",
+        "created": 1677652288,
+        "model": "gpt-4o-mini",
+        "choices": [
+            {
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": "Hello! I'm doing well, thank you for asking!",
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 20,
+            "completion_tokens": 15,
+            "total_tokens": 35,
+        },
+    }
+
+
+@pytest.fixture
+def mock_stream_chunks():
+    """Sample streaming chunks from OpenAI API."""
+    return [
+        "data: {\"id\":\"chatcmpl-123\",\"choices\":[{\"delta\":{\"content\":\"Hello\"},\"finish_reason\":null}]}\n",
+        "data: {\"id\":\"chatcmpl-123\",\"choices\":[{\"delta\":{\"content\":\"!\"},\"finish_reason\":null}]}\n",
+        "data: {\"id\":\"chatcmpl-123\",\"choices\":[{\"delta\":{\"content\":\" How\"},\"finish_reason\":null}]}\n",
+        "data: {\"id\":\"chatcmpl-123\",\"choices\":[{\"delta\":{\"content\":\" can I help?\"},\"finish_reason\":\"stop\"}]}\n",
+        "data: [DONE]\n",
+    ]
+
+
+class TestOpenAIClientGenerate:
+    """Tests for non-streaming generation. [AC-AISVC-02]"""
+
+    @pytest.mark.asyncio
+    async def test_generate_success(self, llm_client, mock_messages, mock_generate_response):
+        """[AC-AISVC-02] Test successful non-streaming generation."""
+        mock_response = MagicMock()
+        mock_response.json.return_value = mock_generate_response
+        mock_response.raise_for_status = MagicMock()
+
+        with patch.object(
+            llm_client, "_get_client"
+        ) as mock_get_client:
+            mock_client = AsyncMock()
+            mock_client.post = AsyncMock(return_value=mock_response)
+            mock_get_client.return_value = mock_client
+
+            result = await llm_client.generate(mock_messages)
+
+            assert isinstance(result, LLMResponse)
+            assert result.content == "Hello! I'm doing well, thank you for asking!"
+            assert result.model == "gpt-4o-mini"
+            assert result.finish_reason == "stop"
+            assert result.usage["total_tokens"] == 35
+
+    @pytest.mark.asyncio
+    async def test_generate_with_custom_config(self, llm_client, mock_messages, mock_generate_response):
+        """[AC-AISVC-02] Test generation with custom configuration."""
+        custom_config = LLMConfig(
+            model="gpt-4",
+            max_tokens=1024,
+            temperature=0.5,
+        )
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {**mock_generate_response, "model": "gpt-4"}
+        mock_response.raise_for_status = MagicMock()
+
+        with patch.object(llm_client, "_get_client") as mock_get_client:
+            mock_client = AsyncMock()
+            mock_client.post = AsyncMock(return_value=mock_response)
+            mock_get_client.return_value = mock_client
+
+            result = await llm_client.generate(mock_messages, config=custom_config)
+
+            assert result.model == "gpt-4"
+
+    @pytest.mark.asyncio
+    async def test_generate_timeout_error(self, llm_client, mock_messages):
+        """[AC-AISVC-02] Test timeout error handling."""
+        with patch.object(llm_client, "_get_client") as mock_get_client:
+            mock_client = AsyncMock()
+            mock_client.post = AsyncMock(side_effect=httpx.TimeoutException("Timeout"))
+            mock_get_client.return_value = mock_client
+
+            with pytest.raises(TimeoutException):
+                await llm_client.generate(mock_messages)
+
+    @pytest.mark.asyncio
+    async def test_generate_api_error(self, llm_client, mock_messages):
+        """[AC-AISVC-02] Test API error handling."""
+        mock_response = MagicMock()
+        mock_response.status_code = 401
+        mock_response.text = '{"error": {"message": "Invalid API key"}}'
+        mock_response.json.return_value = {"error": {"message": "Invalid API key"}}
+
+        http_error = httpx.HTTPStatusError(
+            "Unauthorized",
+            request=MagicMock(),
+            response=mock_response,
+        )
+
+        with patch.object(llm_client, "_get_client") as mock_get_client:
+            mock_client = AsyncMock()
+            mock_client.post = AsyncMock(side_effect=http_error)
+            mock_get_client.return_value = mock_client
+
+            with pytest.raises(LLMException) as exc_info:
+                await llm_client.generate(mock_messages)
+
+            assert "Invalid API key" in str(exc_info.value.message)
+
+    @pytest.mark.asyncio
+    async def test_generate_malformed_response(self, llm_client, mock_messages):
+        """[AC-AISVC-02] Test handling of malformed response."""
+        mock_response = MagicMock()
+        mock_response.json.return_value = {"invalid": "response"}
+        mock_response.raise_for_status = MagicMock()
+
+        with patch.object(llm_client, "_get_client") as mock_get_client:
+            mock_client = AsyncMock()
+            mock_client.post = AsyncMock(return_value=mock_response)
+            mock_get_client.return_value = mock_client
+
+            with pytest.raises(LLMException):
+                await llm_client.generate(mock_messages)
+
+
+class MockAsyncStreamContext:
+    """Mock async context manager for streaming."""
+
+    def __init__(self, response):
+        self._response = response
+
+    async def __aenter__(self):
+        return self._response
+
+    async def __aexit__(self, *args):
+        pass
+
+
+class TestOpenAIClientStreamGenerate:
+    """Tests for streaming generation. [AC-AISVC-06, AC-AISVC-07]"""
+
+    @pytest.mark.asyncio
+    async def test_stream_generate_success(self, llm_client, mock_messages, mock_stream_chunks):
+        """[AC-AISVC-06, AC-AISVC-07] Test successful streaming generation."""
+        async def mock_aiter_lines():
+            for chunk in mock_stream_chunks:
+                yield chunk
+
+        mock_response = MagicMock()
+        mock_response.raise_for_status = MagicMock()
+        mock_response.aiter_lines = mock_aiter_lines
+
+        mock_client = AsyncMock()
+        mock_client.stream = MagicMock(return_value=MockAsyncStreamContext(mock_response))
+
+        with patch.object(llm_client, "_get_client", return_value=mock_client):
+            chunks = []
+            async for chunk in llm_client.stream_generate(mock_messages):
+                chunks.append(chunk)
+
+            assert len(chunks) == 4
+            assert chunks[0].delta == "Hello"
+            assert chunks[-1].finish_reason == "stop"
+
+    @pytest.mark.asyncio
+    async def test_stream_generate_timeout_error(self, llm_client, mock_messages):
+        """[AC-AISVC-06] Test streaming timeout error handling."""
+        mock_client = AsyncMock()
+
+        class TimeoutContext:
+            async def __aenter__(self):
+                raise httpx.TimeoutException("Timeout")
+            async def __aexit__(self, *args):
+                pass
+
+        mock_client.stream = MagicMock(return_value=TimeoutContext())
+
+        with patch.object(llm_client, "_get_client", return_value=mock_client):
+            with pytest.raises(TimeoutException):
+                async for _ in llm_client.stream_generate(mock_messages):
+                    pass
+
+    @pytest.mark.asyncio
+    async def test_stream_generate_api_error(self, llm_client, mock_messages):
+        """[AC-AISVC-06] Test streaming API error handling."""
+        mock_response = MagicMock()
+        mock_response.status_code = 500
+        mock_response.text = "Internal Server Error"
+        mock_response.json.return_value = {"error": {"message": "Internal Server Error"}}
+
+        http_error = httpx.HTTPStatusError(
+            "Internal Server Error",
+            request=MagicMock(),
+            response=mock_response,
+        )
+
+        mock_client = AsyncMock()
+
+        class ErrorContext:
+            async def __aenter__(self):
+                raise http_error
+            async def __aexit__(self, *args):
+                pass
+
+        mock_client.stream = MagicMock(return_value=ErrorContext())
+
+        with patch.object(llm_client, "_get_client", return_value=mock_client):
+            with pytest.raises(LLMException):
+                async for _ in llm_client.stream_generate(mock_messages):
+                    pass
+
+
+class TestOpenAIClientConfig:
+    """Tests for LLM configuration."""
+
+    def test_default_config(self, mock_settings):
+        """Test default configuration from settings."""
+        with patch("app.services.llm.openai_client.get_settings", return_value=mock_settings):
+            client = OpenAIClient()
+
+            assert client._model == "gpt-4o-mini"
+            assert client._default_config.max_tokens == 2048
+            assert client._default_config.temperature == 0.7
+
+    def test_custom_config_override(self, mock_settings):
+        """Test custom configuration override."""
+        with patch("app.services.llm.openai_client.get_settings", return_value=mock_settings):
+            client = OpenAIClient(
+                api_key="custom-key",
+                base_url="https://custom.api.com/v1",
+                model="gpt-4",
+            )
+
+            assert client._api_key == "custom-key"
+            assert client._base_url == "https://custom.api.com/v1"
+            assert client._model == "gpt-4"
+
+
+class TestOpenAIClientClose:
+    """Tests for client cleanup."""
+
+    @pytest.mark.asyncio
+    async def test_close_client(self, llm_client):
+        """Test client close releases resources."""
+        mock_client = AsyncMock()
+        mock_client.aclose = AsyncMock()
+        llm_client._client = mock_client
+
+        await llm_client.close()
+
+        mock_client.aclose.assert_called_once()
+        assert llm_client._client is None

ai-service/tests/test_memory.py

@@ -0,0 +1,210 @@
+"""
+Unit tests for Memory service.
+[AC-AISVC-10, AC-AISVC-11, AC-AISVC-13] Tests for multi-tenant session and message management.
+"""
+
+import pytest
+from unittest.mock import AsyncMock, MagicMock, patch
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.models.entities import ChatMessage, ChatSession
+from app.services.memory import MemoryService
+
+
+@pytest.fixture
+def mock_session():
+    """Create a mock AsyncSession."""
+    session = AsyncMock(spec=AsyncSession)
+    session.add = MagicMock()
+    session.flush = AsyncMock()
+    session.delete = AsyncMock()
+    return session
+
+
+@pytest.fixture
+def memory_service(mock_session):
+    """Create MemoryService with mocked session."""
+    return MemoryService(mock_session)
+
+
+class TestMemoryServiceTenantIsolation:
+    """
+    [AC-AISVC-10, AC-AISVC-11] Tests for multi-tenant isolation in memory service.
+    """
+
+    @pytest.mark.asyncio
+    async def test_get_or_create_session_tenant_isolation(self, memory_service, mock_session):
+        """
+        [AC-AISVC-11] Different tenants with same session_id should have separate sessions.
+        """
+        mock_result = MagicMock()
+        mock_result.scalar_one_or_none.return_value = None
+        mock_session.execute = AsyncMock(return_value=mock_result)
+
+        session1 = await memory_service.get_or_create_session(
+            tenant_id="tenant_a",
+            session_id="session_123",
+        )
+        session2 = await memory_service.get_or_create_session(
+            tenant_id="tenant_b",
+            session_id="session_123",
+        )
+
+        assert session1.tenant_id == "tenant_a"
+        assert session2.tenant_id == "tenant_b"
+        assert session1.session_id == "session_123"
+        assert session2.session_id == "session_123"
+
+    @pytest.mark.asyncio
+    async def test_load_history_tenant_isolation(self, memory_service, mock_session):
+        """
+        [AC-AISVC-11] Loading history should only return messages for the specific tenant.
+        """
+        mock_result = MagicMock()
+        mock_scalars = MagicMock()
+        mock_scalars.all.return_value = [
+            ChatMessage(tenant_id="tenant_a", session_id="session_123", role="user", content="Hello"),
+        ]
+        mock_result.scalars.return_value = mock_scalars
+        mock_session.execute = AsyncMock(return_value=mock_result)
+
+        messages = await memory_service.load_history(
+            tenant_id="tenant_a",
+            session_id="session_123",
+        )
+
+        assert len(messages) == 1
+        assert messages[0].tenant_id == "tenant_a"
+
+    @pytest.mark.asyncio
+    async def test_append_message_tenant_scoped(self, memory_service, mock_session):
+        """
+        [AC-AISVC-10, AC-AISVC-13] Appended messages should be scoped to tenant.
+        """
+        message = await memory_service.append_message(
+            tenant_id="tenant_a",
+            session_id="session_123",
+            role="user",
+            content="Test message",
+        )
+
+        assert message.tenant_id == "tenant_a"
+        assert message.session_id == "session_123"
+        assert message.role == "user"
+        assert message.content == "Test message"
+
+
+class TestMemoryServiceSessionManagement:
+    """
+    [AC-AISVC-13] Tests for session-based memory management.
+    """
+
+    @pytest.mark.asyncio
+    async def test_get_existing_session(self, memory_service, mock_session):
+        """
+        [AC-AISVC-13] Should return existing session if it exists.
+        """
+        existing_session = ChatSession(
+            tenant_id="tenant_a",
+            session_id="session_123",
+        )
+        mock_result = MagicMock()
+        mock_result.scalar_one_or_none.return_value = existing_session
+        mock_session.execute = AsyncMock(return_value=mock_result)
+
+        session = await memory_service.get_or_create_session(
+            tenant_id="tenant_a",
+            session_id="session_123",
+        )
+
+        assert session.tenant_id == "tenant_a"
+        assert session.session_id == "session_123"
+
+    @pytest.mark.asyncio
+    async def test_create_new_session(self, memory_service, mock_session):
+        """
+        [AC-AISVC-13] Should create new session if it doesn't exist.
+        """
+        mock_result = MagicMock()
+        mock_result.scalar_one_or_none.return_value = None
+        mock_session.execute = AsyncMock(return_value=mock_result)
+
+        session = await memory_service.get_or_create_session(
+            tenant_id="tenant_a",
+            session_id="session_new",
+            channel_type="wechat",
+            metadata={"user_id": "user_123"},
+        )
+
+        assert session.tenant_id == "tenant_a"
+        assert session.session_id == "session_new"
+        assert session.channel_type == "wechat"
+
+    @pytest.mark.asyncio
+    async def test_append_multiple_messages(self, memory_service, mock_session):
+        """
+        [AC-AISVC-13] Should append multiple messages in batch.
+        """
+        messages_data = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there!"},
+        ]
+
+        messages = await memory_service.append_messages(
+            tenant_id="tenant_a",
+            session_id="session_123",
+            messages=messages_data,
+        )
+
+        assert len(messages) == 2
+        assert messages[0].role == "user"
+        assert messages[1].role == "assistant"
+
+    @pytest.mark.asyncio
+    async def test_load_history_with_limit(self, memory_service, mock_session):
+        """
+        [AC-AISVC-13] Should limit the number of messages returned.
+        """
+        mock_result = MagicMock()
+        mock_scalars = MagicMock()
+        mock_scalars.all.return_value = [
+            ChatMessage(tenant_id="tenant_a", session_id="session_123", role="user", content=f"Msg {i}")
+            for i in range(5)
+        ]
+        mock_result.scalars.return_value = mock_scalars
+        mock_session.execute = AsyncMock(return_value=mock_result)
+
+        messages = await memory_service.load_history(
+            tenant_id="tenant_a",
+            session_id="session_123",
+            limit=3,
+        )
+
+        assert len(messages) == 5
+
+
+class TestMemoryServiceClearHistory:
+    """
+    [AC-AISVC-13] Tests for clearing session history.
+    """
+
+    @pytest.mark.asyncio
+    async def test_clear_history_tenant_scoped(self, memory_service, mock_session):
+        """
+        [AC-AISVC-11] Clearing history should only affect the specified tenant's messages.
+        """
+        mock_result = MagicMock()
+        mock_scalars = MagicMock()
+        mock_scalars.all.return_value = [
+            ChatMessage(tenant_id="tenant_a", session_id="session_123", role="user", content="Msg 1"),
+            ChatMessage(tenant_id="tenant_a", session_id="session_123", role="assistant", content="Msg 2"),
+        ]
+        mock_result.scalars.return_value = mock_scalars
+        mock_session.execute = AsyncMock(return_value=mock_result)
+
+        count = await memory_service.clear_history(
+            tenant_id="tenant_a",
+            session_id="session_123",
+        )
+
+        assert count == 2