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feat(dashboard): track real API call count per session
Adds schema v7 'api_call_count' column. run_agent.py increments it by 1 per LLM API call, web_server analytics SQL aggregates it, frontend uses the real counter instead of summing sessions. The 'API Calls' card on the analytics dashboard previously displayed COUNT(*) from the sessions table — the number of conversations, not LLM requests. Each session makes 10-90 API calls through the tool loop, so the reported number was ~30x lower than real. Salvaged from PR #10140 (@kshitijk4poor). The cache-token accuracy portions of the original PR were deferred — per-provider analytics is the better path there, since cache_write_tokens and actual_cost_usd are only reliably available from a subset of providers (Anthropic native, Codex Responses, OpenRouter with usage.include). Tests: - schema_version v7 assertion - migration v2 -> v7 adds api_call_count column with default 0 - update_token_counts increments api_call_count by provided delta - absolute=True sets api_call_count directly - /api/analytics/usage exposes total_api_calls in totals
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7 changed files with 61 additions and 10 deletions
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@ -2189,7 +2189,8 @@ async def get_usage_analytics(days: int = 30):
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SUM(reasoning_tokens) as reasoning_tokens,
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COALESCE(SUM(estimated_cost_usd), 0) as estimated_cost,
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COALESCE(SUM(actual_cost_usd), 0) as actual_cost,
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COUNT(*) as sessions
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COUNT(*) as sessions,
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SUM(COALESCE(api_call_count, 0)) as api_calls
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FROM sessions WHERE started_at > ?
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GROUP BY day ORDER BY day
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""", (cutoff,))
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@ -2200,7 +2201,8 @@ async def get_usage_analytics(days: int = 30):
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SUM(input_tokens) as input_tokens,
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SUM(output_tokens) as output_tokens,
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COALESCE(SUM(estimated_cost_usd), 0) as estimated_cost,
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COUNT(*) as sessions
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COUNT(*) as sessions,
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SUM(COALESCE(api_call_count, 0)) as api_calls
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FROM sessions WHERE started_at > ? AND model IS NOT NULL
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GROUP BY model ORDER BY SUM(input_tokens) + SUM(output_tokens) DESC
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""", (cutoff,))
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@ -2213,7 +2215,8 @@ async def get_usage_analytics(days: int = 30):
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SUM(reasoning_tokens) as total_reasoning,
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COALESCE(SUM(estimated_cost_usd), 0) as total_estimated_cost,
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COALESCE(SUM(actual_cost_usd), 0) as total_actual_cost,
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COUNT(*) as total_sessions
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COUNT(*) as total_sessions,
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SUM(COALESCE(api_call_count, 0)) as total_api_calls
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FROM sessions WHERE started_at > ?
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""", (cutoff,))
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totals = dict(cur3.fetchone())
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