mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-04-25 00:51:20 +00:00
fix(dashboard): include cache tokens in totals, track real API call count
The analytics dashboard had three accuracy issues: 1. TOTAL TOKENS excluded cache_read and cache_write tokens — only counted the non-cached input portion. With 90%+ cache hit rates typical in Hermes, this dramatically undercounted actual token usage (e.g. showing 9.1M when the real total was 169M+). 2. The 'API Calls' card displayed session count (COUNT(*) from sessions table), not actual LLM API requests. A single session makes 10-90 API calls through the tool loop, so this was ~30x lower than reality. 3. cache_write_tokens was stored in the DB but never exposed through the analytics API endpoint or frontend. Changes: - Add api_call_count column to sessions table (schema v7 migration) - Persist api_call_count=1 per LLM API call in run_agent.py - Analytics SQL queries now include cache_write_tokens and api_call_count in daily, by_model, and totals aggregations - Frontend TOTAL TOKENS card now shows input + cache_read + cache_write + output (the full prompt total + output) - API CALLS card now uses real api_call_count from DB - New Cache Hit Rate card shows cache efficiency percentage - Bar chart, tooltips, daily table, model table all use prompt totals (input + cache_read + cache_write) instead of just input - Labels changed from 'Input' to 'Prompt' to reflect the full prompt total - TypeScript interfaces and i18n strings updated (en + zh)
This commit is contained in:
kshitijk4poor
parent
da8bab77fb
commit
42aeb4ecac
10 changed files with 121 additions and 27 deletions
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@ -1977,7 +1977,8 @@ async def update_config_raw(body: RawConfigUpdate):
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@app.get("/api/analytics/usage")
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async def get_usage_analytics(days: int = 30):
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from hermes_state import SessionDB
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db = SessionDB()
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from hermes_constants import get_hermes_home
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db = SessionDB(db_path=get_hermes_home() / "state.db")
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try:
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cutoff = time.time() - (days * 86400)
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cur = db._conn.execute("""
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@ -1985,10 +1986,12 @@ 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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SUM(cache_read_tokens) as cache_read_tokens,
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SUM(cache_write_tokens) as cache_write_tokens,
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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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@ -1998,10 +2001,13 @@ async def get_usage_analytics(days: int = 30):
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SELECT model,
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SUM(input_tokens) as input_tokens,
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SUM(output_tokens) as output_tokens,
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SUM(cache_read_tokens) as cache_read_tokens,
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SUM(cache_write_tokens) as cache_write_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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GROUP BY model ORDER BY SUM(input_tokens) + SUM(cache_read_tokens) + SUM(cache_write_tokens) + SUM(output_tokens) DESC
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""", (cutoff,))
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by_model = [dict(r) for r in cur2.fetchall()]
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@ -2009,10 +2015,12 @@ async def get_usage_analytics(days: int = 30):
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SELECT SUM(input_tokens) as total_input,
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SUM(output_tokens) as total_output,
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SUM(cache_read_tokens) as total_cache_read,
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SUM(cache_write_tokens) as total_cache_write,
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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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@ -31,7 +31,7 @@ T = TypeVar("T")
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DEFAULT_DB_PATH = get_hermes_home() / "state.db"
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SCHEMA_VERSION = 6
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SCHEMA_VERSION = 7
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SCHEMA_SQL = """
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CREATE TABLE IF NOT EXISTS schema_version (
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@ -65,6 +65,7 @@ CREATE TABLE IF NOT EXISTS sessions (
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cost_source TEXT,
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pricing_version TEXT,
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title TEXT,
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api_call_count INTEGER DEFAULT 0,
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FOREIGN KEY (parent_session_id) REFERENCES sessions(id)
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);
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@ -329,6 +330,17 @@ class SessionDB:
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except sqlite3.OperationalError:
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pass # Column already exists
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cursor.execute("UPDATE schema_version SET version = 6")
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if current_version < 7:
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# v7: add api_call_count column to sessions — tracks the number
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# of individual LLM API calls made within a session (as opposed
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# to the session count itself).
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try:
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cursor.execute(
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'ALTER TABLE sessions ADD COLUMN "api_call_count" INTEGER DEFAULT 0'
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)
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except sqlite3.OperationalError:
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pass # Column already exists
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cursor.execute("UPDATE schema_version SET version = 7")
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# Unique title index — always ensure it exists (safe to run after migrations
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# since the title column is guaranteed to exist at this point)
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@ -426,6 +438,7 @@ class SessionDB:
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billing_provider: Optional[str] = None,
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billing_base_url: Optional[str] = None,
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billing_mode: Optional[str] = None,
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api_call_count: int = 0,
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absolute: bool = False,
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) -> None:
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"""Update token counters and backfill model if not already set.
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@ -455,7 +468,8 @@ class SessionDB:
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billing_provider = COALESCE(billing_provider, ?),
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billing_base_url = COALESCE(billing_base_url, ?),
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billing_mode = COALESCE(billing_mode, ?),
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model = COALESCE(model, ?)
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model = COALESCE(model, ?),
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api_call_count = ?
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WHERE id = ?"""
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else:
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sql = """UPDATE sessions SET
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@ -475,7 +489,8 @@ class SessionDB:
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billing_provider = COALESCE(billing_provider, ?),
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billing_base_url = COALESCE(billing_base_url, ?),
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billing_mode = COALESCE(billing_mode, ?),
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model = COALESCE(model, ?)
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model = COALESCE(model, ?),
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api_call_count = COALESCE(api_call_count, 0) + ?
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WHERE id = ?"""
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params = (
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input_tokens,
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@ -493,6 +508,7 @@ class SessionDB:
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billing_base_url,
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billing_mode,
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model,
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api_call_count,
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session_id,
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)
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def _do(conn):
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@ -8917,6 +8917,7 @@ class AIAgent:
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billing_mode="subscription_included"
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if cost_result.status == "included" else None,
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model=self.model,
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api_call_count=1,
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)
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except Exception:
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pass # never block the agent loop
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@ -694,6 +694,8 @@ class TestNewEndpoints:
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assert "totals" in data
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assert isinstance(data["daily"], list)
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assert "total_sessions" in data["totals"]
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assert "total_cache_write" in data["totals"]
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assert "total_api_calls" in data["totals"]
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def test_session_token_endpoint_removed(self):
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"""GET /api/auth/session-token no longer exists."""
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@ -62,6 +62,27 @@ class TestSessionLifecycle:
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assert session["input_tokens"] == 300
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assert session["output_tokens"] == 150
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def test_update_token_counts_tracks_api_call_count(self, db):
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"""api_call_count increments with each update_token_counts call."""
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db.create_session(session_id="s1", source="cli")
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db.update_token_counts("s1", input_tokens=100, output_tokens=50, api_call_count=1)
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db.update_token_counts("s1", input_tokens=100, output_tokens=50, api_call_count=1)
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db.update_token_counts("s1", input_tokens=100, output_tokens=50, api_call_count=1)
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session = db.get_session("s1")
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assert session["api_call_count"] == 3
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def test_update_token_counts_api_call_count_absolute(self, db):
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"""absolute mode sets api_call_count directly."""
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db.create_session(session_id="s1", source="cli")
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db.update_token_counts("s1", input_tokens=100, output_tokens=50, api_call_count=1)
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db.update_token_counts("s1", input_tokens=300, output_tokens=150,
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api_call_count=5, absolute=True)
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session = db.get_session("s1")
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assert session["api_call_count"] == 5
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assert session["input_tokens"] == 300
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def test_update_token_counts_backfills_model_when_null(self, db):
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db.create_session(session_id="s1", source="telegram")
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db.update_token_counts("s1", input_tokens=10, output_tokens=5, model="openai/gpt-5.4")
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@ -935,7 +956,7 @@ class TestSchemaInit:
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def test_schema_version(self, db):
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cursor = db._conn.execute("SELECT version FROM schema_version")
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version = cursor.fetchone()[0]
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assert version == 6
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assert version == 7
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def test_title_column_exists(self, db):
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"""Verify the title column was created in the sessions table."""
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@ -996,13 +1017,19 @@ class TestSchemaInit:
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# Verify migration
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cursor = migrated_db._conn.execute("SELECT version FROM schema_version")
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assert cursor.fetchone()[0] == 6
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assert cursor.fetchone()[0] == 7
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# Verify title column exists and is NULL for existing sessions
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session = migrated_db.get_session("existing")
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assert session is not None
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assert session["title"] is None
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# Verify api_call_count column was added with default 0
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cursor = migrated_db._conn.execute(
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"SELECT api_call_count FROM sessions WHERE id = 'existing'"
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)
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assert cursor.fetchone()[0] == 0
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# Verify we can set title on migrated session
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assert migrated_db.set_session_title("existing", "Migrated Title") is True
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session = migrated_db.get_session("existing")
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@ -112,11 +112,14 @@ export const en: Translations = {
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totalTokens: "Total Tokens",
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totalSessions: "Total Sessions",
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apiCalls: "API Calls",
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cacheHitRate: "Cache Hit Rate",
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dailyTokenUsage: "Daily Token Usage",
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dailyBreakdown: "Daily Breakdown",
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perModelBreakdown: "Per-Model Breakdown",
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prompt: "Prompt",
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input: "Input",
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output: "Output",
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cached: "cached",
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total: "Total",
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noUsageData: "No usage data for this period",
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startSession: "Start a session to see analytics here",
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@ -125,7 +128,6 @@ export const en: Translations = {
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tokens: "Tokens",
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perDayAvg: "/day avg",
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acrossModels: "across {count} models",
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inOut: "{input} in / {output} out",
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},
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logs: {
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@ -117,11 +117,14 @@ export interface Translations {
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totalTokens: string;
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totalSessions: string;
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apiCalls: string;
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cacheHitRate: string;
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dailyTokenUsage: string;
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dailyBreakdown: string;
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perModelBreakdown: string;
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prompt: string;
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input: string;
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output: string;
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cached: string;
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total: string;
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noUsageData: string;
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startSession: string;
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@ -130,7 +133,6 @@ export interface Translations {
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tokens: string;
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perDayAvg: string;
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acrossModels: string;
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inOut: string;
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};
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// ── Logs page ──
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@ -112,11 +112,14 @@ export const zh: Translations = {
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totalTokens: "总 Token 数",
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totalSessions: "总会话数",
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apiCalls: "API 调用",
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cacheHitRate: "缓存命中率",
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dailyTokenUsage: "每日 Token 用量",
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dailyBreakdown: "每日明细",
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perModelBreakdown: "模型用量明细",
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prompt: "提示",
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input: "输入",
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output: "输出",
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cached: "已缓存",
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total: "总计",
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noUsageData: "该时间段暂无使用数据",
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startSession: "开始会话后将在此显示分析数据",
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@ -125,7 +128,6 @@ export const zh: Translations = {
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tokens: "Token",
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perDayAvg: "/天 平均",
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acrossModels: "共 {count} 个模型",
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inOut: "输入 {input} / 输出 {output}",
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},
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logs: {
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@ -269,18 +269,23 @@ export interface AnalyticsDailyEntry {
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input_tokens: number;
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output_tokens: number;
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cache_read_tokens: number;
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cache_write_tokens: number;
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reasoning_tokens: number;
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estimated_cost: number;
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actual_cost: number;
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sessions: number;
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api_calls: number;
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}
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export interface AnalyticsModelEntry {
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model: string;
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input_tokens: number;
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output_tokens: number;
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cache_read_tokens: number;
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cache_write_tokens: number;
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estimated_cost: number;
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sessions: number;
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api_calls: number;
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}
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export interface AnalyticsResponse {
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@ -290,10 +295,12 @@ export interface AnalyticsResponse {
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total_input: number;
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total_output: number;
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total_cache_read: number;
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total_cache_write: number;
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total_reasoning: number;
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total_estimated_cost: number;
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total_actual_cost: number;
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total_sessions: number;
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total_api_calls: number;
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};
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}
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@ -4,6 +4,7 @@ import {
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Cpu,
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Hash,
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TrendingUp,
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Zap,
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} from "lucide-react";
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import { api } from "@/lib/api";
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import type { AnalyticsResponse, AnalyticsDailyEntry, AnalyticsModelEntry } from "@/lib/api";
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@ -19,6 +20,11 @@ const PERIODS = [
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const CHART_HEIGHT_PX = 160;
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/** Compute total prompt tokens (input + cache_read + cache_write). */
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function getPromptTokens(d: { input_tokens: number; cache_read_tokens?: number; cache_write_tokens?: number }): number {
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return d.input_tokens + (d.cache_read_tokens ?? 0) + (d.cache_write_tokens ?? 0);
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}
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function formatTokens(n: number): string {
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if (n >= 1_000_000) return `${(n / 1_000_000).toFixed(1)}M`;
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if (n >= 1_000) return `${(n / 1_000).toFixed(1)}K`;
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@ -63,7 +69,7 @@ function TokenBarChart({ daily }: { daily: AnalyticsDailyEntry[] }) {
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const { t } = useI18n();
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if (daily.length === 0) return null;
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const maxTokens = Math.max(...daily.map((d) => d.input_tokens + d.output_tokens), 1);
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const maxTokens = Math.max(...daily.map((d) => getPromptTokens(d) + d.output_tokens), 1);
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return (
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<Card>
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@ -75,7 +81,7 @@ function TokenBarChart({ daily }: { daily: AnalyticsDailyEntry[] }) {
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<div className="flex items-center gap-4 text-xs text-muted-foreground">
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<div className="flex items-center gap-1.5">
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<div className="h-2.5 w-2.5 bg-[#ffe6cb]" />
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{t.analytics.input}
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{t.analytics.prompt}
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</div>
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<div className="flex items-center gap-1.5">
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<div className="h-2.5 w-2.5 bg-emerald-500" />
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@ -86,8 +92,9 @@ function TokenBarChart({ daily }: { daily: AnalyticsDailyEntry[] }) {
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<CardContent>
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<div className="flex items-end gap-[2px]" style={{ height: CHART_HEIGHT_PX }}>
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{daily.map((d) => {
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const total = d.input_tokens + d.output_tokens;
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const inputH = Math.round((d.input_tokens / maxTokens) * CHART_HEIGHT_PX);
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const promptTokens = getPromptTokens(d);
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const total = promptTokens + d.output_tokens;
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const inputH = Math.round((promptTokens / maxTokens) * CHART_HEIGHT_PX);
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const outputH = Math.round((d.output_tokens / maxTokens) * CHART_HEIGHT_PX);
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return (
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<div
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@ -99,7 +106,7 @@ function TokenBarChart({ daily }: { daily: AnalyticsDailyEntry[] }) {
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<div className="absolute bottom-full left-1/2 -translate-x-1/2 mb-2 hidden group-hover:block z-10 pointer-events-none">
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<div className="bg-card border border-border px-2.5 py-1.5 text-[10px] text-foreground shadow-lg whitespace-nowrap">
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<div className="font-medium">{formatDate(d.day)}</div>
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<div>{t.analytics.input}: {formatTokens(d.input_tokens)}</div>
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<div>{t.analytics.prompt}: {formatTokens(promptTokens)}</div>
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<div>{t.analytics.output}: {formatTokens(d.output_tokens)}</div>
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<div>{t.analytics.total}: {formatTokens(total)}</div>
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</div>
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@ -152,18 +159,19 @@ function DailyTable({ daily }: { daily: AnalyticsDailyEntry[] }) {
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<tr className="border-b border-border text-muted-foreground text-xs">
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<th className="text-left py-2 pr-4 font-medium">{t.analytics.date}</th>
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<th className="text-right py-2 px-4 font-medium">{t.sessions.title}</th>
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<th className="text-right py-2 px-4 font-medium">{t.analytics.input}</th>
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||||
<th className="text-right py-2 px-4 font-medium">{t.analytics.prompt}</th>
|
||||
<th className="text-right py-2 pl-4 font-medium">{t.analytics.output}</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{sorted.map((d) => {
|
||||
const promptTokens = getPromptTokens(d);
|
||||
return (
|
||||
<tr key={d.day} className="border-b border-border/50 hover:bg-secondary/20 transition-colors">
|
||||
<td className="py-2 pr-4 font-medium">{formatDate(d.day)}</td>
|
||||
<td className="text-right py-2 px-4 text-muted-foreground">{d.sessions}</td>
|
||||
<td className="text-right py-2 px-4">
|
||||
<span className="text-[#ffe6cb]">{formatTokens(d.input_tokens)}</span>
|
||||
<span className="text-[#ffe6cb]">{formatTokens(promptTokens)}</span>
|
||||
</td>
|
||||
<td className="text-right py-2 pl-4">
|
||||
<span className="text-emerald-400">{formatTokens(d.output_tokens)}</span>
|
||||
|
|
@ -184,7 +192,7 @@ function ModelTable({ models }: { models: AnalyticsModelEntry[] }) {
|
|||
if (models.length === 0) return null;
|
||||
|
||||
const sorted = [...models].sort(
|
||||
(a, b) => b.input_tokens + b.output_tokens - (a.input_tokens + a.output_tokens),
|
||||
(a, b) => (getPromptTokens(b) + b.output_tokens) - (getPromptTokens(a) + a.output_tokens),
|
||||
);
|
||||
|
||||
return (
|
||||
|
|
@ -213,7 +221,7 @@ function ModelTable({ models }: { models: AnalyticsModelEntry[] }) {
|
|||
</td>
|
||||
<td className="text-right py-2 px-4 text-muted-foreground">{m.sessions}</td>
|
||||
<td className="text-right py-2 pl-4">
|
||||
<span className="text-[#ffe6cb]">{formatTokens(m.input_tokens)}</span>
|
||||
<span className="text-[#ffe6cb]">{formatTokens(getPromptTokens(m))}</span>
|
||||
{" / "}
|
||||
<span className="text-emerald-400">{formatTokens(m.output_tokens)}</span>
|
||||
</td>
|
||||
|
|
@ -283,12 +291,17 @@ export default function AnalyticsPage() {
|
|||
{data && (
|
||||
<>
|
||||
{/* Summary cards */}
|
||||
<div className="grid gap-4 sm:grid-cols-2 lg:grid-cols-3">
|
||||
<div className="grid gap-4 sm:grid-cols-2 lg:grid-cols-4">
|
||||
<SummaryCard
|
||||
icon={Hash}
|
||||
label={t.analytics.totalTokens}
|
||||
value={formatTokens(data.totals.total_input + data.totals.total_output)}
|
||||
sub={t.analytics.inOut.replace("{input}", formatTokens(data.totals.total_input)).replace("{output}", formatTokens(data.totals.total_output))}
|
||||
value={formatTokens(
|
||||
(data.totals.total_input ?? 0) +
|
||||
(data.totals.total_cache_read ?? 0) +
|
||||
(data.totals.total_cache_write ?? 0) +
|
||||
(data.totals.total_output ?? 0)
|
||||
)}
|
||||
sub={`${formatTokens((data.totals.total_input ?? 0) + (data.totals.total_cache_read ?? 0) + (data.totals.total_cache_write ?? 0))} ${t.analytics.prompt} / ${formatTokens(data.totals.total_output ?? 0)} ${t.analytics.output.toLowerCase()}`}
|
||||
/>
|
||||
<SummaryCard
|
||||
icon={BarChart3}
|
||||
|
|
@ -297,11 +310,25 @@ export default function AnalyticsPage() {
|
|||
sub={`~${(data.totals.total_sessions / days).toFixed(1)}${t.analytics.perDayAvg}`}
|
||||
/>
|
||||
<SummaryCard
|
||||
icon={TrendingUp}
|
||||
icon={Zap}
|
||||
label={t.analytics.apiCalls}
|
||||
value={String(data.daily.reduce((sum, d) => sum + d.sessions, 0))}
|
||||
value={String(data.totals.total_api_calls ?? data.daily.reduce((sum, d) => sum + d.sessions, 0))}
|
||||
sub={t.analytics.acrossModels.replace("{count}", String(data.by_model.length))}
|
||||
/>
|
||||
{(() => {
|
||||
const promptSent = (data.totals.total_input ?? 0) + (data.totals.total_cache_read ?? 0);
|
||||
const rate = promptSent > 0
|
||||
? `${((data.totals.total_cache_read ?? 0) / promptSent * 100).toFixed(0)}%`
|
||||
: "—";
|
||||
return (
|
||||
<SummaryCard
|
||||
icon={TrendingUp}
|
||||
label={t.analytics.cacheHitRate}
|
||||
value={rate}
|
||||
sub={`${formatTokens(data.totals.total_cache_read ?? 0)} ${t.analytics.cached}`}
|
||||
/>
|
||||
);
|
||||
})()}
|
||||
</div>
|
||||
|
||||
{/* Bar chart */}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue