d92a099ade
- _get_runtime_config(): reads active provider endpoint, api_key, main/mini model from app_settings (60s cache), falls back to env vars - get_azure_client() now async, accepts cfg dict - All generate_* methods call _get_runtime_config() per invocation so DB changes take effect without restart - app_settings: _seed_from_env() backfills empty endpoint/api_key from env vars on first load so the admin UI shows current values immediately Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
104 lines
3.5 KiB
Python
104 lines
3.5 KiB
Python
"""
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App-wide configuration stored in MongoDB.
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Single document with _id='config'. Cached in-memory for 60 seconds.
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"""
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import time
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import logging
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from typing import Any
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from app.db import get_db
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logger = logging.getLogger(__name__)
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_cache: dict[str, Any] = {}
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_cache_ts: float = 0
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_CACHE_TTL = 60 # seconds
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DEFAULTS = {
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"_id": "config",
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"persona_cost": 2,
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"run_cost": 40,
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"trial_grant": 50,
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"credit_packs": [
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{"id": "starter", "name": "Starter", "price_usd": 49, "credits": 50},
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{"id": "pro", "name": "Pro", "price_usd": 199, "credits": 220, "popular": True},
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{"id": "scale", "name": "Scale", "price_usd": 499, "credits": 600},
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],
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"active_provider": "azure_openai",
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"active_main_model": "gpt-5.4",
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"active_mini_model": "gpt-5.4-mini",
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"ai_providers": [
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{
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"id": "azure_openai",
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"name": "Azure OpenAI",
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"enabled": True,
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"endpoint": "", # populated from env var on first load
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"api_key": "", # populated from env var on first load
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"models": [
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{"id": "gpt-5.4", "display_name": "GPT-5.4", "role": "main", "enabled": True},
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{"id": "gpt-5.4-mini", "display_name": "GPT-5.4 Mini", "role": "mini", "enabled": True},
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],
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},
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],
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}
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def _seed_from_env(doc: dict) -> dict:
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"""Backfill endpoint/api_key from env vars when DB fields are still empty."""
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import os
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changed = False
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for p in doc.get("ai_providers", []):
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if not p.get("endpoint"):
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p["endpoint"] = os.environ.get("AZURE_AI_ENDPOINT", "")
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changed = True
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if not p.get("api_key"):
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p["api_key"] = os.environ.get("AZURE_AI_API_KEY", "")
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changed = True
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if not doc.get("active_main_model"):
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doc["active_main_model"] = os.environ.get("AZURE_AI_MODEL_MAIN", "gpt-5.4")
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changed = True
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if not doc.get("active_mini_model"):
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doc["active_mini_model"] = os.environ.get("AZURE_AI_MODEL_MINI", "gpt-5.4-mini")
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changed = True
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return doc if changed else doc
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async def get_settings() -> dict:
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global _cache, _cache_ts
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if _cache and (time.monotonic() - _cache_ts) < _CACHE_TTL:
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return _cache
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db = await get_db()
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doc = await db.app_settings.find_one({"_id": "config"})
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if not doc:
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await db.app_settings.insert_one(DEFAULTS.copy())
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doc = DEFAULTS.copy()
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else:
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# Fill in any keys added to DEFAULTS since the document was first created
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missing = {k: v for k, v in DEFAULTS.items() if k not in doc}
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if missing:
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await db.app_settings.update_one({"_id": "config"}, {"$set": missing})
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doc.update(missing)
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# Backfill endpoint/api_key from env if still empty (first run after feature added)
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before = {p['id']: (p.get('endpoint'), p.get('api_key')) for p in doc.get('ai_providers', [])}
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_seed_from_env(doc)
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after = {p['id']: (p.get('endpoint'), p.get('api_key')) for p in doc.get('ai_providers', [])}
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if before != after:
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await db.app_settings.update_one({"_id": "config"}, {"$set": {"ai_providers": doc["ai_providers"]}})
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_cache = doc
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_cache_ts = time.monotonic()
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return doc
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async def update_settings(fields: dict) -> dict:
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global _cache, _cache_ts
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db = await get_db()
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await db.app_settings.update_one(
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{"_id": "config"},
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{"$set": fields},
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upsert=True,
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)
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_cache = {} # invalidate cache
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return await get_settings()
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