import asyncio import logging import os from contextlib import asynccontextmanager from pathlib import Path from dotenv import find_dotenv, load_dotenv from pydantic_ai import Agent from pydantic_ai.ui import SSE_CONTENT_TYPE from pydantic_ai.ui.ag_ui import AGUIAdapter from starlette.applications import Starlette from starlette.middleware import Middleware from starlette.middleware.cors import CORSMiddleware from starlette.requests import Request from starlette.responses import JSONResponse, Response, StreamingResponse from starlette.routing import Route from haiku.rag.client import HaikuRAG from haiku.rag.config import load_yaml_config from haiku.rag.config.models import AppConfig from haiku.rag.skills.rag import create_skill, get_agent_preamble from haiku.rag.utils import get_model from haiku.skills import ( SkillDeps, SkillToolset, run_agui_stream, ) from haiku.skills.prompts import build_system_prompt load_dotenv(find_dotenv(usecwd=True)) # Configure logfire (only sends data if LOGFIRE_TOKEN is present) try: import logfire logfire.configure(send_to_logfire="if-token-present", console=False) logfire.instrument_pydantic_ai() except Exception: pass logging.basicConfig( level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s" ) logger = logging.getLogger(__name__) # Load config config_path = Path("/app/haiku.rag.yaml") if config_path.exists(): yaml_data = load_yaml_config(config_path) Config = AppConfig.model_validate(yaml_data) else: Config = AppConfig() # Get DB path from environment db_path_str = os.getenv("DB_PATH", "haiku_rag.lancedb") db_path = Path(db_path_str) logger.info(f"Database path: {db_path}") logger.info(f"QA Provider: {Config.qa.model.provider}, Model: {Config.qa.model.name}") # Only HaikuRAG client is a singleton (expensive to create) _client: HaikuRAG | None = None _client_lock = asyncio.Lock() async def get_client() -> HaikuRAG: """Get or create the cached client. Guarded by a lock because the first request after startup can race with itself: two concurrent callers would both pass the None check, each build and enter a HaikuRAG, and the loser would leak its LanceDB connection. """ global _client if _client is None: async with _client_lock: if _client is None: client = HaikuRAG(db_path=db_path, config=Config, create=True) await client.__aenter__() _client = client return _client # Create skill, toolset, and agent skill = create_skill(db_path=db_path, config=Config) toolset = SkillToolset(skills=[skill]) agent = Agent( get_model(Config.qa.model, Config), instructions=build_system_prompt( toolset.skill_catalog, preamble=get_agent_preamble(Config) ), toolsets=[toolset], deps_type=SkillDeps, ) async def stream_chat(request: Request) -> Response: """Chat streaming endpoint with AG-UI protocol.""" body = await request.body() accept = request.headers.get("accept", SSE_CONTENT_TYPE) run_input = AGUIAdapter.build_run_input(body) adapter = AGUIAdapter(agent=agent, run_input=run_input, accept=accept) async def event_stream(): async with run_agui_stream( adapter, toolset=toolset, deps=SkillDeps() ) as stream: async for chunk in adapter.encode_stream(stream): yield chunk return StreamingResponse( event_stream(), media_type=accept, headers={ "Cache-Control": "no-cache", "Connection": "keep-alive", "X-Accel-Buffering": "no", }, ) async def health_check(_: Request) -> JSONResponse: """Health check endpoint.""" return JSONResponse( { "status": "healthy", "qa_provider": Config.qa.model.provider, "qa_model": Config.qa.model.name, "db_path": str(db_path), "db_exists": db_path.exists(), } ) async def list_documents(_: Request) -> JSONResponse: """List all documents in the database.""" if not db_path.exists(): return JSONResponse({"documents": [], "error": "Database not found"}) client = await get_client() docs = await client.document_repository.list_all() return JSONResponse( { "documents": [ {"id": doc.id, "title": doc.title, "uri": doc.uri} for doc in docs ] } ) async def db_info(_: Request) -> JSONResponse: """Get database info and statistics.""" if not db_path.exists(): return JSONResponse( { "exists": False, "path": str(db_path), "documents": 0, "chunks": 0, } ) from haiku.rag.store.engine import get_database_stats client = await get_client() stats = await get_database_stats(client.store.db) return JSONResponse( { "exists": True, "path": str(db_path), "documents": stats["documents"].get("num_rows", 0), "chunks": stats["chunks"].get("num_rows", 0), "documents_bytes": stats["documents"].get("total_bytes", 0), "chunks_bytes": stats["chunks"].get("total_bytes", 0), "has_vector_index": stats["chunks"].get("has_vector_index", False), } ) async def visualize_chunk(request: Request) -> JSONResponse: """Return visual grounding images for a chunk as base64.""" import base64 from io import BytesIO chunk_id = request.path_params["chunk_id"] if not db_path.exists(): return JSONResponse({"error": "Database not found"}, status_code=404) client = await get_client() chunk = await client.chunk_repository.get_by_id(chunk_id) if not chunk: return JSONResponse({"error": "Chunk not found"}, status_code=404) images = await client.visualize_chunk(chunk) if not images: return JSONResponse({"images": [], "message": "No visual grounding available"}) base64_images = [] for img in images: buffer = BytesIO() img.save(buffer, format="PNG") buffer.seek(0) base64_images.append(base64.b64encode(buffer.read()).decode("utf-8")) return JSONResponse( { "images": base64_images, "chunk_id": chunk_id, "document_uri": chunk.document_uri, } ) @asynccontextmanager async def lifespan(app: Starlette): """Shut down the cached HaikuRAG client cleanly on app exit. Awaits any in-flight background vacuum tasks and closes the LanceDB connection. Without this, vacuum tasks are cancelled abruptly and the connection is never closed on process shutdown. """ yield global _client if _client is not None: await _client.__aexit__(None, None, None) _client = None # Create Starlette app app = Starlette( routes=[ Route("/v1/chat/stream", stream_chat, methods=["POST"]), Route("/api/documents", list_documents, methods=["GET"]), Route("/api/info", db_info, methods=["GET"]), Route("/api/visualize/{chunk_id}", visualize_chunk, methods=["GET"]), Route("/health", health_check, methods=["GET"]), ], middleware=[ Middleware( CORSMiddleware, # type: ignore[invalid-argument-type] allow_origins=["http://localhost:3000", "http://frontend:3000"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) ], lifespan=lifespan, ) if __name__ == "__main__": import uvicorn uvicorn.run( "main:app", host="0.0.0.0", port=8000, reload=True, )