3e9ccafad2
- Model renames: gpt-5.2 → gpt-5.4-2026-03-05, gemini-3-pro-preview → gemini-3.1-pro-preview; retire gpt-4.1 via alias fallback - New: llm_usage_context.py (ContextVar-based attribution), model_pricing.py (tiered pricing + 60s cache), usage_event.py (append-only telemetry), quota.py (user/FG quota enforcement with 80% warning) - Wire _record_usage into all 3 LLM methods; set_llm_context at every service entry point - Fix admin_required decorator (was sync, never awaited User.find_by_id); add active_required and with_user_context decorators - Inject user_id into ContextVar from JWT on every authenticated request - Add DB indexes for usage_events, model_pricing, users collections - Seed script for model pricing (gpt-5.4 single-tier, gemini-3.1 two-tier 200k threshold) - Fix parse_json_response NameError (logger undefined at module level) - 70 passing tests: conftest.py with sys.modules stubs, test_usage_infrastructure.py (52 tests), rewrite stale test_llm_service.py (18 tests) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
101 lines
3 KiB
Python
101 lines
3 KiB
Python
#!/usr/bin/env python3
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"""Seed model pricing for Semblance.
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Run from the backend/ directory:
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source venv/bin/activate
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python scripts/seed_model_pricing.py
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Idempotent — upserts on {model, effective_from}. Safe to re-run.
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"""
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import sys
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import os
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from dotenv import load_dotenv
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load_dotenv()
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import pymongo
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from datetime import datetime, timezone
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MONGO_URI = os.environ.get("MONGO_URI")
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MONGO_USER = os.environ.get("MONGO_USER")
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MONGO_PASS = os.environ.get("MONGO_PASS")
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MONGO_HOST = os.environ.get("MONGO_HOST", "localhost")
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MONGO_PORT = os.environ.get("MONGO_PORT", "27017")
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if not MONGO_URI:
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if MONGO_USER and MONGO_PASS:
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MONGO_URI = f"mongodb://{MONGO_USER}:{MONGO_PASS}@{MONGO_HOST}:{MONGO_PORT}/semblance_db?authSource=admin"
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else:
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MONGO_URI = f"mongodb://{MONGO_HOST}:{MONGO_PORT}"
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# Pricing effective from project start — covers all historical backfill
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EFFECTIVE_FROM = datetime(2024, 1, 1, tzinfo=timezone.utc)
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PRICING_ROWS = [
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{
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"model": "gpt-5.4-2026-03-05",
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"provider": "openai",
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"currency": "USD",
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"tiers": [
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{
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"threshold_input_tokens": 0,
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"input_per_mtok": 2.50,
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"cached_input_per_mtok": 0.25,
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"output_per_mtok": 15.00,
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"image_per_mtok": None,
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}
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],
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"effective_from": EFFECTIVE_FROM,
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"effective_until": None,
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"notes": "gpt-5.4-2026-03-05 pricing as of 2026-04",
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},
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{
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"model": "gemini-3.1-pro-preview",
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"provider": "gemini",
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"currency": "USD",
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"tiers": [
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{
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"threshold_input_tokens": 0,
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"input_per_mtok": 2.00,
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"cached_input_per_mtok": None,
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"output_per_mtok": 12.00,
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"image_per_mtok": None,
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},
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{
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"threshold_input_tokens": 200_000,
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"input_per_mtok": 4.00,
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"cached_input_per_mtok": None,
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"output_per_mtok": 18.00,
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"image_per_mtok": None,
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},
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],
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"effective_from": EFFECTIVE_FROM,
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"effective_until": None,
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"notes": "gemini-3.1-pro-preview pricing: $2/$12 (<200k ctx), $4/$18 (>=200k ctx)",
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},
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]
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def main():
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client = pymongo.MongoClient(MONGO_URI, serverSelectionTimeoutMS=5000)
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db = client.semblance_db
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db.model_pricing.create_index(
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[("model", pymongo.ASCENDING), ("effective_from", pymongo.DESCENDING)],
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background=True,
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)
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for row in PRICING_ROWS:
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key = {"model": row["model"], "effective_from": row["effective_from"]}
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result = db.model_pricing.update_one(key, {"$set": row}, upsert=True)
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action = "inserted" if result.upserted_id else "updated"
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print(f" {action}: {row['model']} (effective from {row['effective_from'].date()})")
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print(f"\nDone. {len(PRICING_ROWS)} pricing rows seeded.")
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client.close()
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if __name__ == "__main__":
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main()
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