d3d1667a79
- Fix admin sidebar: remove duplicate Teams, add Storage nav item - Analytics: client-scoped queries, super_admin sees all (including NULL client_id) - Storage management: list/download/delete presentations with file metadata - Settings page with brand config router - AI usage tracking: new AIUsageModel, ai_usage_service, analytics endpoint - Master deck → template bridge: _register_as_template creates TemplateModel + PresentationLayoutCodeModel so parsed layouts appear in template picker - Multi-provider LLM vision in parser: Anthropic/Google/OpenAI with asyncio.to_thread - Fix PPTX upload 400: accept by .pptx extension (browser sends octet-stream) - Fix reparse FK violation: presentation_id=None for parse_master_deck jobs - Worker job_timeout increased to 1800s for LLM-heavy master deck parsing - PYTHONUNBUFFERED=1 in docker-compose worker for real-time log output - Auth: clientId in /me response, dev-login cookie improvements - Frontend: auth slice clientId, master-deck thumbnails, storage page Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
80 lines
2.4 KiB
Python
80 lines
2.4 KiB
Python
"""Fire-and-forget AI usage logging service."""
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import asyncio
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import uuid
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from typing import Optional
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from services.database import async_session_maker
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from utils.llm_context import get_llm_context
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def log(
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provider: str,
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model: str,
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call_type: str,
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input_tokens: Optional[int] = None,
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output_tokens: Optional[int] = None,
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total_tokens: Optional[int] = None,
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duration_ms: Optional[int] = None,
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user_id: Optional[uuid.UUID] = None,
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client_id: Optional[uuid.UUID] = None,
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presentation_id: Optional[uuid.UUID] = None,
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) -> None:
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"""Log AI usage asynchronously (fire-and-forget).
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If user_id/client_id/presentation_id are not provided,
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reads them from the LLMCallContext contextvar.
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"""
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ctx = get_llm_context()
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if ctx:
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user_id = user_id or ctx.user_id
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client_id = client_id or ctx.client_id
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presentation_id = presentation_id or ctx.presentation_id
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asyncio.create_task(
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_write_log(
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provider=provider,
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model=model,
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call_type=call_type,
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input_tokens=input_tokens,
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output_tokens=output_tokens,
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total_tokens=total_tokens,
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duration_ms=duration_ms,
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user_id=user_id,
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client_id=client_id,
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presentation_id=presentation_id,
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)
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)
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async def _write_log(
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provider: str,
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model: str,
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call_type: str,
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input_tokens: Optional[int],
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output_tokens: Optional[int],
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total_tokens: Optional[int],
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duration_ms: Optional[int],
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user_id: Optional[uuid.UUID],
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client_id: Optional[uuid.UUID],
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presentation_id: Optional[uuid.UUID],
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) -> None:
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try:
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from models.sql.ai_usage import AIUsageModel
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async with async_session_maker() as session:
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entry = AIUsageModel(
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provider=provider,
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model=model,
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call_type=call_type,
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input_tokens=input_tokens,
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output_tokens=output_tokens,
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total_tokens=total_tokens or ((input_tokens or 0) + (output_tokens or 0)),
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duration_ms=duration_ms,
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user_id=user_id,
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client_id=client_id,
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presentation_id=presentation_id,
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)
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session.add(entry)
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await session.commit()
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except Exception as e:
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print(f"AI usage log error: {e}")
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