e910e00edf
- New UsageLog model tracking every LLM API call (provider, model, tokens, estimated cost, user, module, check name) - Instrument LLMConfig.call_vision_api() to auto-log each call - New /usage tab in nav bar with dashboard showing: - Summary cards (total calls, tokens, estimated cost) - Breakdowns by provider, model, tool, and user - Recent API calls table - Time filters (All Time, 30 Days, 7 Days, Today) - Cost estimates based on per-model token pricing - Pass logged-in user through executor context for tracking Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
133 lines
4.9 KiB
Python
133 lines
4.9 KiB
Python
"""Usage Dashboard Routes."""
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import logging
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from datetime import datetime, timedelta
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from flask import Blueprint, render_template, request, jsonify
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from sqlalchemy import func, desc
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from core.models.usage_log import UsageLog
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from core.models.database import db
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logger = logging.getLogger(__name__)
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usage_bp = Blueprint('usage', __name__, url_prefix='/usage',
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template_folder='templates')
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@usage_bp.route('/')
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@usage_bp.route('/index')
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def index():
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"""Render usage dashboard."""
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return render_template('usage/dashboard.html', active_tab='usage')
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@usage_bp.route('/api/stats')
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def api_stats():
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"""Get usage statistics as JSON, with optional time filter."""
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try:
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days = request.args.get('days', type=int)
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query = UsageLog.query
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if days:
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cutoff = datetime.utcnow() - timedelta(days=days)
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query = query.filter(UsageLog.timestamp >= cutoff)
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# Total stats
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total_calls = query.count()
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total_tokens = db.session.query(func.sum(UsageLog.tokens_used)).filter(
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*_time_filter(days)
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).scalar() or 0
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total_cost = db.session.query(func.sum(UsageLog.estimated_cost_usd)).filter(
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*_time_filter(days)
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).scalar() or 0
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# By provider
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by_provider = db.session.query(
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UsageLog.provider,
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func.count(UsageLog.id).label('calls'),
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func.sum(UsageLog.tokens_used).label('tokens'),
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func.sum(UsageLog.estimated_cost_usd).label('cost')
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).filter(*_time_filter(days)).group_by(UsageLog.provider).all()
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# By model
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by_model = db.session.query(
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UsageLog.provider,
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UsageLog.model,
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func.count(UsageLog.id).label('calls'),
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func.sum(UsageLog.tokens_used).label('tokens'),
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func.sum(UsageLog.estimated_cost_usd).label('cost')
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).filter(*_time_filter(days)).group_by(UsageLog.provider, UsageLog.model).all()
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# By module (tool)
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by_module = db.session.query(
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UsageLog.module,
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func.count(UsageLog.id).label('calls'),
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func.sum(UsageLog.tokens_used).label('tokens'),
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func.sum(UsageLog.estimated_cost_usd).label('cost')
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).filter(*_time_filter(days)).group_by(UsageLog.module).all()
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# By user
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by_user = db.session.query(
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UsageLog.user,
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func.count(UsageLog.id).label('calls'),
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func.sum(UsageLog.tokens_used).label('tokens'),
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func.sum(UsageLog.estimated_cost_usd).label('cost')
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).filter(*_time_filter(days)).group_by(UsageLog.user).all()
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# Daily usage (last 30 days max)
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daily_cutoff = datetime.utcnow() - timedelta(days=min(days or 30, 30))
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daily = db.session.query(
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func.date(UsageLog.timestamp).label('date'),
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func.count(UsageLog.id).label('calls'),
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func.sum(UsageLog.tokens_used).label('tokens'),
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func.sum(UsageLog.estimated_cost_usd).label('cost')
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).filter(UsageLog.timestamp >= daily_cutoff).group_by(
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func.date(UsageLog.timestamp)
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).order_by(func.date(UsageLog.timestamp)).all()
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# Recent calls
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recent = query.order_by(desc(UsageLog.timestamp)).limit(20).all()
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return jsonify({
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'summary': {
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'total_calls': total_calls,
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'total_tokens': int(total_tokens),
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'total_cost': round(float(total_cost), 4)
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},
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'by_provider': [
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{'provider': r.provider, 'calls': r.calls,
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'tokens': int(r.tokens or 0), 'cost': round(float(r.cost or 0), 4)}
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for r in by_provider
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],
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'by_model': [
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{'provider': r.provider, 'model': r.model, 'calls': r.calls,
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'tokens': int(r.tokens or 0), 'cost': round(float(r.cost or 0), 4)}
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for r in by_model
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],
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'by_module': [
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{'module': r.module or 'unknown', 'calls': r.calls,
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'tokens': int(r.tokens or 0), 'cost': round(float(r.cost or 0), 4)}
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for r in by_module
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],
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'by_user': [
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{'user': r.user or 'anonymous', 'calls': r.calls,
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'tokens': int(r.tokens or 0), 'cost': round(float(r.cost or 0), 4)}
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for r in by_user
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],
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'daily': [
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{'date': str(r.date), 'calls': r.calls,
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'tokens': int(r.tokens or 0), 'cost': round(float(r.cost or 0), 4)}
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for r in daily
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],
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'recent': [r.to_dict() for r in recent]
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})
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except Exception as e:
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logger.error(f"Usage stats error: {e}", exc_info=True)
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return jsonify({'error': str(e)}), 500
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def _time_filter(days):
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"""Build time filter conditions."""
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if days:
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cutoff = datetime.utcnow() - timedelta(days=days)
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return [UsageLog.timestamp >= cutoff]
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return []
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