docling-studio/document-parser/main.py
Pier-Jean Malandrino 8ae9dcdc04 refactor(audit): remediate 0.5.0 audit findings — clean architecture, security, DRY, SOLID, perf
Closes the 12 MAJ raised by the release/0.5.0 audit pipeline (cf.
docs/audit/reports/release-0.5.0/summary.md → summary-reaudit.md).

Volet 1 — Reasoning architecture (audits 01/02/06/07 strengthening)
  * Domain ports: LLMProvider, ReasoningRunner, ReasoningParseError
  * Domain DTOs: LLMProviderType, ReasoningResult, ReasoningIteration
  * infra/llm/ollama_provider.py — OllamaProvider with health_check
  * infra/docling_agent_reasoning.py — runner adapter, encapsulates the
    private _rag_loop call (tracked at docling-project/docling-agent#26),
    commits OLLAMA_HOST once at boot (eliminates the per-request env race),
    translates upstream IndexError into ReasoningParseError
  * api/reasoning.py — zero coupling to docling-agent / mellea / docling-core,
    consumes app.state.reasoning_runner via the port
  * main.py — DI wires OllamaProvider + DoclingAgentReasoningRunner at boot
    when REASONING_ENABLED=true and deps are importable
  * Rename RAG_* env vars → REASONING_*, endpoint /rag → /reasoning,
    type RAGResult → ReasoningResult, frontend feature flag wiring,
    i18n strings, tests, docs (BREAKING — pre-1.0 surface, no external
    consumers in production)
  * 17 new tests: adapter unit tests with sys.modules stubs, OllamaProvider
    httpx tests, R3 concurrent-host isolation, R6 multi-iteration trace
    serialization, R13 Protocol conformance via isinstance
  * E2E Karate scenario: nav-reasoning hidden when REASONING_ENABLED=false
  * README — Live Reasoning section (env vars, archi, link to issue #26)

Bloc B — Security (audit 08, dev-only context)
  * docker-compose.yml — DEV DEFAULTS header, OpenSearch DISABLE_SECURITY_PLUGIN
    flagged as dev-only with link to OpenSearch security docs
  * main.py — boot warning if NEO4J_URI is set with the default 'changeme'
    password, so prod operators can't silently inherit it

Bloc C — DRY frontend (audit 05)
  * shared/storage/keys.ts — STORAGE_KEYS centralised (theme, locale)
  * features/settings/store.ts — dead apiUrl ref + orphan i18n keys removed
  * api/schemas.py — DOCUMENT_STATUS_UPLOADED constant

Bloc D — Quality (audits 02/06/07/09/10/12)
  * domain/ports.py — DocumentConverter.supports_page_batching property
    (LSP fix, replaces isinstance(ServeConverter) check)
  * domain/ports.py — VectorStore.ping() (encapsulation, replaces
    _vector_store._client.info() reach-around)
  * api/analyses.py + api/ingestion.py — path params {job_id} → {analysis_id}
    aligned with the user-facing terminology (URLs unchanged)
  * api/documents.py — Path.read_bytes() + generate_preview() wrapped in
    asyncio.to_thread, unblocks the FastAPI event loop on /preview
  * infra/docling_tree.py — PEP 604 union for isinstance (Ruff UP038)
  * src/__tests__/integration/ — cross-feature integration test relocated
    out of features/history/ so feature folders stay self-contained
  * Tightened terminal `assert X is not None` checks (isinstance(.., datetime),
    exact value comparisons)

Validation
  * 446 backend pytest, 202 frontend vitest — all green
  * ruff + ruff format + ESLint + Prettier + vue-tsc clean
  * Re-audit verdict: 0 CRIT / 0 MAJ, score ~94/100, GO

Closes #200
2026-04-29 09:23:09 +02:00

307 lines
11 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,
timeout=settings.conversion_timeout,
)
else:
from infra.local_converter import LocalConverter
logger.info("Using local Docling converter")
return LocalConverter()
def _build_chunker():
"""Build the chunker adapter.
Uses LocalChunker in all modes — in remote mode it chunks the
DoclingDocument JSON returned by Docling Serve, so docling-core
(lightweight) is the only local dependency needed.
"""
from infra.local_chunker import LocalChunker
return LocalChunker()
def _build_repos() -> tuple[SqliteDocumentRepository, SqliteAnalysisRepository]:
return SqliteDocumentRepository(), SqliteAnalysisRepository()
def _build_analysis_service(
document_repo: SqliteDocumentRepository,
analysis_repo: SqliteAnalysisRepository,
neo4j_driver=None,
) -> 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,
neo4j_driver=neo4j_driver,
)
async def _init_neo4j():
"""Initialize the Neo4j driver and bootstrap schema — skip if not configured."""
if not settings.neo4j_uri:
logger.info("Neo4j disabled (NEO4J_URI not set)")
return None
if settings.neo4j_password == "changeme":
# The dev compose stack ships with "changeme" so `docker compose up`
# works immediately. Anyone running the backend against a non-dev
# Neo4j with this password almost certainly forgot to override it.
logger.warning(
"Neo4j is configured with the dev default password 'changeme'. "
"Override NEO4J_PASSWORD before deploying outside localhost."
)
from infra.neo4j import bootstrap_schema, get_driver
try:
neo = await get_driver(
settings.neo4j_uri,
settings.neo4j_user,
settings.neo4j_password,
)
await bootstrap_schema(neo)
logger.info("Neo4j ready (uri=%s)", settings.neo4j_uri)
return neo
except Exception:
logger.exception("Neo4j init failed — continuing without graph storage")
return None
def _build_ingestion_service(neo4j_driver=None) -> 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,
default_limit=settings.opensearch_default_limit,
)
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, neo4j_driver=neo4j_driver)
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()
# Exposed on app.state so routers that need direct repo access (e.g. the
# reasoning-graph endpoint, which reads `document_json` from SQLite to
# build the graph without touching Neo4j) can reach them without going
# through a service.
app.state.analysis_repo = analysis_repo
app.state.document_repo = document_repo
app.state.neo4j = await _init_neo4j()
app.state.analysis_service = _build_analysis_service(
document_repo, analysis_repo, neo4j_driver=app.state.neo4j
)
app.state.document_service = _build_document_service(document_repo, analysis_repo)
ingestion_service = _build_ingestion_service(neo4j_driver=app.state.neo4j)
app.state.ingestion_service = ingestion_service
if ingestion_service is not None:
app.include_router(ingestion_router)
logger.info("Ingestion router mounted")
logger.info("Docling Studio backend ready (engine=%s)", settings.conversion_engine)
try:
yield
finally:
if app.state.neo4j is not None:
from infra.neo4j import close_driver
await close_driver()
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)
# Graph view — mounted regardless; individual requests 503 if Neo4j is absent.
from api.graph import router as graph_router # noqa: E402
app.include_router(graph_router)
# Live reasoning (docling-agent runner). Router is mounted unconditionally so
# the route is introspectable in OpenAPI; the handler itself 503s when
# `REASONING_ENABLED` is off or the deps aren't installed.
from api.reasoning import router as reasoning_router # noqa: E402
from infra.docling_agent_reasoning import DoclingAgentReasoningRunner # noqa: E402
from infra.docling_agent_reasoning import deps_present as _reasoning_deps_present # noqa: E402
from infra.llm.ollama_provider import OllamaProvider # noqa: E402
app.include_router(reasoning_router)
def _build_reasoning_runner() -> DoclingAgentReasoningRunner | None:
"""Wire the reasoning runner if `REASONING_ENABLED=true` and deps are
importable. Today only `LLM_PROVIDER_TYPE=ollama` is supported (cf.
`LLMProvider` docstring); other values fall through to a logged warning
+ None so the rest of the app boots cleanly.
"""
if not settings.reasoning_enabled:
return None
if not _reasoning_deps_present():
logger.warning(
"REASONING_ENABLED=true but docling-agent / mellea not importable — "
"reasoning runner disabled"
)
return None
if settings.llm_provider_type != "ollama":
logger.warning(
"Unsupported LLM_PROVIDER_TYPE=%s — reasoning runner disabled (only "
"'ollama' is realizable today, see "
"https://github.com/docling-project/docling-agent/issues/26)",
settings.llm_provider_type,
)
return None
provider = OllamaProvider(
host=settings.ollama_host,
default_model_id=settings.reasoning_model_id,
)
return DoclingAgentReasoningRunner(provider=provider)
app.state.reasoning_runner = _build_reasoning_runner()
@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"
runner = getattr(app.state, "reasoning_runner", None)
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,
max_paste_image_size_mb=(
settings.max_paste_image_size_mb if settings.max_paste_image_size_mb > 0 else None
),
paste_allowed_image_types=settings.paste_allowed_image_types,
ingestion_available=getattr(app.state, "ingestion_service", None) is not None,
# True when the runner is wired and reports itself available. The
# actual Ollama reachability is checked lazily at call-time to avoid
# blocking health checks on the LLM host.
reasoning_available=runner is not None and runner.is_available,
)