docling-studio/document-parser/main.py
2026-04-10 21:12:11 +02:00

191 lines
6.4 KiB
Python

"""Docling Studio — unified FastAPI backend.
Single service providing document management (upload, CRUD), analysis
orchestration (async Docling processing), and PDF preview — all backed
by SQLite.
Conversion engine is selected via CONVERSION_ENGINE env var:
- "local" → Docling runs in-process as a Python library (default)
- "remote" → delegates to a Docling Serve instance via HTTP
"""
from __future__ import annotations
import logging
from collections.abc import AsyncIterator
from contextlib import asynccontextmanager
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from api.analyses import router as analyses_router
from api.documents import router as documents_router
from api.ingestion import router as ingestion_router
from api.schemas import HealthResponse
from infra.rate_limiter import RateLimiterMiddleware
from infra.settings import settings
from persistence.analysis_repo import SqliteAnalysisRepository
from persistence.database import get_connection, init_db
from persistence.document_repo import SqliteDocumentRepository
from services.analysis_service import AnalysisConfig, AnalysisService
from services.document_service import DocumentConfig, DocumentService
from services.ingestion_service import IngestionConfig, IngestionService
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(name)s%(message)s",
)
logger = logging.getLogger(__name__)
def _build_converter():
"""Build the converter adapter based on configuration."""
if settings.conversion_engine == "remote":
from infra.serve_converter import ServeConverter
logger.info("Using remote Docling Serve at %s", settings.docling_serve_url)
return ServeConverter(
base_url=settings.docling_serve_url,
api_key=settings.docling_serve_api_key,
)
else:
from infra.local_converter import LocalConverter
logger.info("Using local Docling converter")
return LocalConverter()
def _build_chunker():
"""Build the chunker adapter — only available in local mode."""
if settings.conversion_engine == "local":
from infra.local_chunker import LocalChunker
return LocalChunker()
return None
def _build_repos() -> tuple[SqliteDocumentRepository, SqliteAnalysisRepository]:
return SqliteDocumentRepository(), SqliteAnalysisRepository()
def _build_analysis_service(
document_repo: SqliteDocumentRepository,
analysis_repo: SqliteAnalysisRepository,
) -> AnalysisService:
converter = _build_converter()
chunker = _build_chunker()
config = AnalysisConfig(
default_table_mode=settings.default_table_mode,
batch_page_size=settings.batch_page_size,
)
return AnalysisService(
converter=converter,
analysis_repo=analysis_repo,
document_repo=document_repo,
chunker=chunker,
conversion_timeout=settings.conversion_timeout,
max_concurrent=settings.max_concurrent_analyses,
config=config,
)
def _build_ingestion_service() -> IngestionService | None:
"""Build the ingestion service — only if embedding + opensearch are configured."""
if not settings.embedding_url or not settings.opensearch_url:
logger.info("Ingestion disabled (EMBEDDING_URL or OPENSEARCH_URL not set)")
return None
from infra.embedding_client import EmbeddingClient
from infra.opensearch_store import OpenSearchStore
embedding = EmbeddingClient(settings.embedding_url)
vector_store = OpenSearchStore(settings.opensearch_url)
config = IngestionConfig(
embedding_dimension=settings.embedding_dimension,
)
logger.info(
"Ingestion enabled (embedding=%s, opensearch=%s)",
settings.embedding_url,
settings.opensearch_url,
)
return IngestionService(embedding, vector_store, config)
def _build_document_service(
document_repo: SqliteDocumentRepository,
analysis_repo: SqliteAnalysisRepository,
) -> DocumentService:
config = DocumentConfig(
upload_dir=settings.upload_dir,
max_file_size_mb=settings.max_file_size_mb,
max_page_count=settings.max_page_count,
)
return DocumentService(
document_repo=document_repo,
analysis_repo=analysis_repo,
config=config,
)
# ---------------------------------------------------------------------------
# FastAPI app
# ---------------------------------------------------------------------------
@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncIterator[None]:
await init_db()
document_repo, analysis_repo = _build_repos()
app.state.analysis_service = _build_analysis_service(document_repo, analysis_repo)
app.state.document_service = _build_document_service(document_repo, analysis_repo)
app.state.ingestion_service = _build_ingestion_service()
logger.info("Docling Studio backend ready (engine=%s)", settings.conversion_engine)
yield
app = FastAPI(
title="Docling Studio",
description="Document analysis studio powered by Docling",
lifespan=lifespan,
)
app.add_middleware(
CORSMiddleware,
allow_origins=settings.cors_origins,
allow_credentials=True,
allow_methods=["GET", "POST", "PATCH", "DELETE", "OPTIONS"],
allow_headers=["Content-Type", "Authorization"],
)
if settings.rate_limit_rpm > 0:
app.add_middleware(
RateLimiterMiddleware,
requests_per_window=settings.rate_limit_rpm,
window_seconds=60,
)
app.include_router(documents_router)
app.include_router(analyses_router)
app.include_router(ingestion_router)
@app.get("/api/health", response_model=HealthResponse)
async def health() -> HealthResponse:
"""Health check endpoint — verifies database connectivity."""
db_status = "ok"
try:
async with get_connection() as db:
await db.execute("SELECT 1")
except Exception:
db_status = "error"
logger.warning("Health check: database unreachable", exc_info=True)
status = "ok" if db_status == "ok" else "degraded"
return HealthResponse(
status=status,
version=settings.app_version,
engine=settings.conversion_engine,
deployment_mode=settings.deployment_mode,
database=db_status,
max_page_count=settings.max_page_count if settings.max_page_count > 0 else None,
max_file_size_mb=settings.max_file_size_mb if settings.max_file_size_mb > 0 else None,
)