c2e91262c6
Unbounded asyncio.create_task calls could exhaust CPU and memory on modest hardware. Add a configurable semaphore (MAX_CONCURRENT_ANALYSES, default 3) so excess jobs queue instead of running all at once.
109 lines
3.1 KiB
Python
109 lines
3.1 KiB
Python
"""Docling Studio — unified FastAPI backend.
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Single service providing document management (upload, CRUD), analysis
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orchestration (async Docling processing), and PDF preview — all backed
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by SQLite.
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Conversion engine is selected via CONVERSION_ENGINE env var:
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- "local" → Docling runs in-process as a Python library (default)
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- "remote" → delegates to a Docling Serve instance via HTTP
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"""
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from __future__ import annotations
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import logging
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from collections.abc import AsyncIterator
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from contextlib import asynccontextmanager
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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from api.analyses import router as analyses_router
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from api.documents import router as documents_router
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from infra.settings import settings
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from persistence.database import init_db
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from services.analysis_service import AnalysisService
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s [%(levelname)s] %(name)s — %(message)s",
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)
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logger = logging.getLogger(__name__)
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def _build_converter():
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"""Build the converter adapter based on configuration."""
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if settings.conversion_engine == "remote":
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from infra.serve_converter import ServeConverter
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logger.info("Using remote Docling Serve at %s", settings.docling_serve_url)
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return ServeConverter(
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base_url=settings.docling_serve_url,
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api_key=settings.docling_serve_api_key,
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)
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else:
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from infra.local_converter import LocalConverter
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logger.info("Using local Docling converter")
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return LocalConverter()
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def _build_chunker():
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"""Build the chunker adapter — only available in local mode."""
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if settings.conversion_engine == "local":
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from infra.local_chunker import LocalChunker
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return LocalChunker()
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return None
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def _build_analysis_service() -> AnalysisService:
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converter = _build_converter()
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chunker = _build_chunker()
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return AnalysisService(
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converter=converter,
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chunker=chunker,
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conversion_timeout=settings.conversion_timeout,
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max_concurrent=settings.max_concurrent_analyses,
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)
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# ---------------------------------------------------------------------------
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# FastAPI app
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# ---------------------------------------------------------------------------
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@asynccontextmanager
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async def lifespan(app: FastAPI) -> AsyncIterator[None]:
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await init_db()
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app.state.analysis_service = _build_analysis_service()
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logger.info("Docling Studio backend ready (engine=%s)", settings.conversion_engine)
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yield
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app = FastAPI(
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title="Docling Studio",
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description="Document analysis studio powered by Docling",
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lifespan=lifespan,
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)
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app.add_middleware(
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CORSMiddleware,
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allow_origins=settings.cors_origins,
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allow_credentials=True,
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allow_methods=["GET", "POST", "DELETE", "OPTIONS"],
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allow_headers=["Content-Type", "Authorization"],
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)
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app.include_router(documents_router)
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app.include_router(analyses_router)
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@app.get("/api/health")
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def health() -> dict[str, str]:
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"""Health check endpoint."""
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return {
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"status": "ok",
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"version": settings.app_version,
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"engine": settings.conversion_engine,
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}
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