c762564d40
- Fix 71 invalid-syntax files (class-body newline-broken assignments) - Add from/None chain to 307 B904 raise-without-from sites - Add B008 ignore to ruff.toml (already in pyproject.toml) - Noqa F401 on __init__.py re-exports (137 sites) - Noqa E402 on deferred imports (63 sites) - Bulk-add stdlib/FastAPI/project imports for F821 (127 sites) - Replace ×→x, –→-, …→... in docstrings (4093 chars) - Manual refactor of 5 SIM103/SIM116 patterns Tests: 791 passed (66 deselected due to pre-existing Redis issues in test_rag.py) Co-authored-by: opencode <opencode@rugmunch.io>
111 lines
4.1 KiB
Python
111 lines
4.1 KiB
Python
"""#10 - Cost-Per-Model Tracking. Tracks $/1K tokens per model/provider.
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Auto-routes to cheapest model that meets quality threshold."""
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from datetime import UTC, datetime
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from fastapi import APIRouter, Query
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router = APIRouter(prefix="/api/v1/costs", tags=["cost-tracking"])
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# Cost per 1M tokens (USD) - updated June 2026
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MODEL_COSTS = {
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"deepseek-v4-flash": {"input": 0.14, "output": 0.28, "provider": "deepseek"},
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"deepseek-v4-pro": {"input": 0.55, "output": 2.19, "provider": "deepseek"},
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# Gemini pricing (paid tier, per 1M tokens)
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"gemini-2.5-flash": {"input": 0.15, "output": 0.60, "provider": "gemini"},
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"gemini-2.5-pro": {"input": 1.25, "output": 10.00, "provider": "gemini"},
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"gemini-3.5-flash": {"input": 1.50, "output": 9.00, "provider": "gemini"},
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"mistral-small-latest": {"input": 0.0, "output": 0.0, "provider": "mistral", "note": "Free tier - 1B tokens/mo"},
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"mistral-medium-latest": {"input": 0.0, "output": 0.0, "provider": "mistral", "note": "Free tier - use sparingly"},
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"mistral-embed": {
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"input": 0.0,
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"output": 0.0,
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"provider": "mistral",
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"note": "Free tier - state of art embeddings",
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},
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"mistral-large": {"input": 2.00, "output": 6.00, "provider": "mistral"},
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"mistral-small": {"input": 0.20, "output": 0.60, "provider": "mistral"},
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"qwen2.5-coder:7b": {"input": 0.0, "output": 0.0, "provider": "ollama"},
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"gpt-oss-120b": {
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"input": 0.0,
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"output": 0.0,
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"provider": "cerebras",
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"note": "Free tier - 14.4K req/day, 9ms latency",
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},
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"mistral:7b": {"input": 0.0, "output": 0.0, "provider": "ollama"},
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"bge-m3": {"input": 0.0, "output": 0.0, "provider": "ollama"},
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}
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_usage_log: list[dict] = []
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def log_usage(model: str, input_tokens: int, output_tokens: int, latency_ms: float):
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"""Log model usage for cost tracking."""
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costs = MODEL_COSTS.get(model, {"input": 0, "output": 0, "provider": "unknown"})
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input_cost = (input_tokens / 1_000_000) * costs["input"]
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output_cost = (output_tokens / 1_000_000) * costs["output"]
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total_cost = input_cost + output_cost
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_usage_log.append(
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{
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"timestamp": datetime.now(UTC).isoformat(),
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"model": model,
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"provider": costs["provider"],
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"input_tokens": input_tokens,
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"output_tokens": output_tokens,
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"cost_usd": round(total_cost, 6),
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"latency_ms": latency_ms,
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}
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)
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def get_cheapest_model(models: list[str]) -> str:
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"""Pick the cheapest model from a list that meets quality."""
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best = None
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best_cost = float("inf")
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for m in models:
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c = MODEL_COSTS.get(m, {})
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cost = c.get("output", 1.0)
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if cost < best_cost:
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best_cost = cost
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best = m
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return best or models[0]
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@router.get("/rates")
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async def get_rates() -> dict:
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"""Get current model pricing."""
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return {"models": MODEL_COSTS, "updated": "2026-06-15"}
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@router.get("/usage")
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async def get_usage(limit: int = Query(50, le=200)) -> dict:
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"""Get recent usage log."""
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recent = _usage_log[-limit:]
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total_cost = sum(e["cost_usd"] for e in recent)
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total_tokens = sum(e["input_tokens"] + e["output_tokens"] for e in recent)
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return {
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"total_cost_usd": round(total_cost, 4),
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"total_tokens": total_tokens,
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"entries": len(recent),
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"log": recent,
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}
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@router.get("/cheapest")
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async def cheapest_for_task(quality: str = Query("medium", description="minimum quality tier")) -> dict:
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"""Get cheapest model for a given quality tier."""
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if quality == "high":
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candidates = ["deepseek-v4-pro", "gemini-2.5-pro", "mistral-large"]
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elif quality == "medium":
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candidates = ["deepseek-v4-flash", "gemini-2.5-flash", "mistral-small", "qwen2.5-coder:7b"]
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else:
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candidates = ["qwen2.5-coder:7b", "mistral:7b", "deepseek-v4-flash"]
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cheapest = get_cheapest_model(candidates)
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return {
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"quality_tier": quality,
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"candidates": candidates,
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"cheapest": cheapest,
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"cost_per_1M_output": MODEL_COSTS.get(cheapest, {}).get("output", "?"),
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}
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