"""Custom agent with AG-UI streaming. A Starlette app that serves an AG-UI streaming endpoint using the haiku.rag RAG skill with haiku.skills SkillToolset. Requirements: - An Ollama instance running locally (default embedder) - An Anthropic API key (for the QA model) or adjust the model below Usage: DB_PATH=/path/to/db.lancedb uv run uvicorn examples.custom_agent_agui:app --reload --port 8000 """ import os import sys from pathlib import Path from pydantic_ai import Agent from pydantic_ai.ag_ui import AGUIAdapter from pydantic_ai.ui import SSE_CONTENT_TYPE from starlette.applications import Starlette from starlette.requests import Request from starlette.responses import JSONResponse, Response, StreamingResponse from starlette.routing import Route from haiku.rag.skills.rag import create_skill from haiku.skills.agent import SkillToolset db_path = os.environ.get("DB_PATH") if not db_path: print( "Set DB_PATH environment variable to your haiku.rag database", file=sys.stderr ) sys.exit(1) skill = create_skill(db_path=Path(db_path)) toolset = SkillToolset(skills=[skill]) agent = Agent( "anthropic:claude-haiku-4-5-20251001", instructions=toolset.system_prompt, toolsets=[toolset], ) async def stream_chat(request: Request) -> Response: 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) event_stream = adapter.run_stream() sse_event_stream = adapter.encode_stream(event_stream) return StreamingResponse( sse_event_stream, media_type=accept, headers={ "Cache-Control": "no-cache", "Connection": "keep-alive", "X-Accel-Buffering": "no", }, ) async def health_check(_: Request) -> JSONResponse: return JSONResponse({"status": "healthy"}) app = Starlette( routes=[ Route("/v1/chat/stream", stream_chat, methods=["POST"]), Route("/health", health_check, methods=["GET"]), ], )