curo1305
0d34867a69
- New `features/doc-service` FastAPI microservice: PDF upload, async text extraction (pdfplumber), AI classification via Anthropic/Ollama/ LM Studio, per-user categories, file download - Alembic migration isolated with `alembic_version_doc_service` table - Main backend: httpx proxy routers for /api/documents/* and /api/documents/categories/*, admin settings API at /api/settings/* - Runtime config in /config/doc_service_config.json (shared Docker volume); api_key masking on reads; atomic write with os.replace() - Frontend: DocumentsPage, DocumentAdminSettingsPage, updated AppsPage launcher hub, simplified Nav (removed Settings link), new routes - docker-compose: doc-service service, doc_data + app_config volumes, removed internal:true from backend-net for outbound AI API calls - Fix pre-commit hook: probe Docker socket path so git subprocess picks up Docker Desktop on macOS - Fix security_check.py: use sys.executable for bandit so venv python is used instead of system python Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
"""
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Reads doc_service_config.json from the shared config volume.
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Caches the result for 30 seconds to avoid hitting the filesystem on every request.
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Uses asyncio.to_thread so the synchronous file read doesn't block the event loop.
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"""
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import asyncio
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import json
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import time
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from pathlib import Path
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from app.core.config import settings
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_DEFAULT_CONFIG: dict = {
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"ai": {
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"provider": "anthropic",
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"anthropic": {"api_key": "", "model": "claude-haiku-4-5-20251001"},
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"ollama": {"base_url": "http://localhost:11434/v1", "model": "llama3.2", "api_key": "ollama"},
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"lmstudio": {"base_url": "http://localhost:1234/v1", "model": "local-model", "api_key": ""},
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},
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"documents": {"max_pdf_bytes": 20 * 1024 * 1024},
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}
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_cache: dict | None = None
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_cache_at: float = 0.0
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_CACHE_TTL = 30.0
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def _read_config_sync() -> dict:
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path = Path(settings.CONFIG_PATH)
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if not path.exists():
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return _DEFAULT_CONFIG.copy()
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with open(path) as f:
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return json.load(f)
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async def load_doc_config() -> dict:
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global _cache, _cache_at
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now = time.monotonic()
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if _cache is not None and (now - _cache_at) < _CACHE_TTL:
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return _cache
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data = await asyncio.to_thread(_read_config_sync)
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_cache = data
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_cache_at = now
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return data
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