Hermes - BrainSteel VPS
50960bab21
- Brief: Market Intelligence (Binance data + LLM analysis) - Decio: Strategy decision (BUY/HOLD/SELL) - PaperT: Order executor (Binance API) - Anime-style Flask dashboard - Traefik-ready Docker deployment
78 lines
2.7 KiB
Python
78 lines
2.7 KiB
Python
"""
|
|
BrainSteel Fin — Token Tracker
|
|
Logs LLM token usage per agent per call.
|
|
"""
|
|
import sqlite3, os
|
|
from datetime import datetime, timedelta
|
|
|
|
COSTS = {
|
|
"google/gemma-4-31b-it:free": 0.0,
|
|
"google/gemma-4-26b-a4b-it:free": 0.0,
|
|
"deepseek/deepseek-v4-flash:free": 0.0,
|
|
"anthropic/claude-sonnet-4": 3.0,
|
|
"default": 0.0,
|
|
}
|
|
|
|
def log_tokens(agent: str, model: str, usage: dict):
|
|
prompt_t = usage.get("prompt_tokens", 0)
|
|
completion_t = usage.get("completion_tokens", 0)
|
|
total_t = usage.get("total_tokens", prompt_t + completion_t)
|
|
cost = COSTS.get(model, COSTS["default"]) * total_t / 1_000_000
|
|
db_path = os.path.join(os.path.dirname(__file__), "..", "data", "executions.db")
|
|
conn = sqlite3.connect(db_path)
|
|
c = conn.cursor()
|
|
c.execute(
|
|
"INSERT INTO token_usage (timestamp, agent, model, prompt_tokens, completion_tokens, total_tokens, cost_usd) VALUES (?,?,?,?,?,?,?)",
|
|
(datetime.now().isoformat(), agent, model, prompt_t, completion_t, total_t, cost)
|
|
)
|
|
conn.commit()
|
|
conn.close()
|
|
|
|
def get_token_stats(days: int = 7) -> dict:
|
|
db_path = os.path.join(os.path.dirname(__file__), "..", "data", "executions.db")
|
|
conn = sqlite3.connect(db_path)
|
|
c = conn.cursor()
|
|
cutoff = (datetime.now() - timedelta(days=days)).isoformat()
|
|
|
|
c.execute("""
|
|
SELECT DATE(timestamp) as day, agent,
|
|
SUM(prompt_tokens) as p, SUM(completion_tokens) as c, SUM(total_tokens) as t
|
|
FROM token_usage
|
|
WHERE timestamp >= ?
|
|
GROUP BY day, agent
|
|
ORDER BY day, agent
|
|
""", (cutoff,))
|
|
rows = c.fetchall()
|
|
|
|
c.execute("""
|
|
SELECT DATE(timestamp) as day,
|
|
SUM(prompt_tokens), SUM(completion_tokens), SUM(total_tokens), SUM(cost_usd)
|
|
FROM token_usage
|
|
WHERE timestamp >= ?
|
|
GROUP BY day ORDER BY day
|
|
""", (cutoff,))
|
|
daily = c.fetchall()
|
|
|
|
c.execute("SELECT SUM(total_tokens), SUM(cost_usd), COUNT(*) FROM token_usage")
|
|
total = c.fetchone()
|
|
conn.close()
|
|
|
|
agents = ["Brief", "Decio", "PaperT", "Audit"]
|
|
days_set = sorted(set(r[0] for r in rows))
|
|
chart_data = []
|
|
for day in days_set:
|
|
entry = {"date": day}
|
|
for ag in agents:
|
|
row = next((r for r in rows if r[0] == day and r[1] == ag), None)
|
|
entry[ag] = row[4] if row else 0
|
|
chart_data.append(entry)
|
|
|
|
return {
|
|
"total_all_time": total[0] or 0,
|
|
"total_cost_usd": total[1] or 0.0,
|
|
"total_calls": total[2] or 0,
|
|
"daily_totals": [{"date": r[0], "prompt": r[1], "completion": r[2], "total": r[3], "cost": r[4]}
|
|
for r in daily],
|
|
"chart_data": chart_data,
|
|
"agents": agents,
|
|
} |