curo1305
88c1ea297e
All feature containers now POST messages to ai-service (port 8010) instead of calling AI providers directly. ai-service routes to LM Studio, Ollama, or Anthropic based on /config/ai_service_config.json. doc-service AI providers removed; replaced by httpx ai_client.py. Backend settings restructured to /api/settings/ai. Frontend gets dedicated AIAdminSettingsPage and AI Service card in AppsPage. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
56 lines
1.3 KiB
Python
56 lines
1.3 KiB
Python
"""
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Reads doc_service_config.json from the shared config volume.
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30-second TTL cache + env var overrides.
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Env var overrides (all optional):
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DOC_MAX_PDF_MB — max upload size in megabytes (e.g. "50")
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"""
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import asyncio
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import json
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import os
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import time
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from copy import deepcopy
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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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"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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base = deepcopy(_DEFAULT_CONFIG)
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else:
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with open(path) as f:
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base = json.load(f)
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return _apply_env_overrides(base)
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def _apply_env_overrides(config: dict) -> dict:
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cfg = deepcopy(config)
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docs = cfg.setdefault("documents", {})
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if v := os.environ.get("DOC_MAX_PDF_MB"):
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try:
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docs["max_pdf_bytes"] = int(v) * 1024 * 1024
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except ValueError:
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pass
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return cfg
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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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