curo1305
1cdc532fff
- pytest suite for doc-service: 20+ tests covering category CRUD, document upload/get/delete/patch, ownership isolation, category assignment, AI processing (mock), and live PDF tests (auto-skipped when tests/pdfs/ is empty) - Minimal in-memory PDF builder in conftest so tests run without any fixture files; real PDFs can be dropped into tests/pdfs/ to activate live extraction tests - AI prompt updated to return suggested_categories (2–5 short names) - Frontend: SuggestionChip component in DocumentRow shows AI-suggested categories after processing; "Assign" links to an existing category, "Create & Assign" creates it first, ✕ dismisses locally - Default AI provider changed to LM Studio at http://host.docker.internal:1234/v1 (host.docker.internal resolves to the macOS host from inside Docker Desktop) - tests/pdfs/ directory tracked via .gitkeep; *.pdf excluded by .gitignore Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
48 lines
1.5 KiB
Python
48 lines
1.5 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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# Default: LM Studio running on the host machine at port 1234.
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# Inside Docker, host.docker.internal resolves to the host; for local
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# dev outside Docker use http://localhost:1234/v1 instead.
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"provider": "lmstudio",
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"anthropic": {"api_key": "", "model": "claude-haiku-4-5-20251001"},
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"ollama": {"base_url": "http://host.docker.internal:11434/v1", "model": "llama3.2", "api_key": "ollama"},
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"lmstudio": {"base_url": "http://host.docker.internal:1234/v1", "model": "local-model", "api_key": "lm-studio"},
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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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