AI cost observability. Track every LLM call's cost, tokens, and latency with one line of code.
Project description
costkey
AI cost observability. Track every LLM call's cost, tokens, and latency with one line of code.
Install
pip install costkey
Quick Start
import costkey
costkey.init(dsn="https://ck_your_key@app.costkey.dev/your-project")
# That's it. Every AI call is now tracked automatically.
# Works with OpenAI, Anthropic, Google Gemini, Azure OpenAI.
No wrapping. No per-client setup. No manual tagging. CostKey patches httpx and requests and auto-detects AI provider calls.
What You Get (Zero Config)
All of these work automatically after init():
- Cost tracking — per-call cost computed from built-in pricing (30+ models)
- Stack trace attribution — see which function, file, and line made each AI call
- Request tracing — group AI calls per request with
start_trace() - Feature detection — call chains are analyzed to detect logical "features" in your code
- Credential scrubbing — API keys, JWTs, and secrets are auto-redacted from captured bodies
How It Works
CostKey patches httpx.Client.send and requests.Session.send. When your code calls any AI provider:
- Detects the provider from the URL (OpenAI, Anthropic, Google, Azure)
- Extracts token usage from the response
- Captures a stack trace for automatic code attribution
- Computes cost using built-in model pricing
- Ships the event async to your CostKey dashboard
Non-AI HTTP calls pass through untouched with zero overhead.
Tracing
# Group all AI calls in a request into one trace
with costkey.start_trace(name="POST /api/search"):
intent = classify_intent(query) # AI call 1
results = search(query, intent)
summary = summarize_results(results) # AI call 2
reranked = rerank_results(results) # AI call 3
# Dashboard shows one trace with all 3 calls and total cost
Manual Context
with costkey.with_context(task="summarize", team="search"):
response = openai.chat.completions.create(...)
Privacy & Security
- Never captures API keys — request headers are never read
- Auto-scrubs credentials from captured bodies (OpenAI keys, JWTs, tokens, etc.)
before_sendhook for custom PII scrubbing:
def scrub(event):
event.request_body = None # strip prompts entirely
return event
costkey.init(dsn="...", before_send=scrub)
Supported Providers
| Provider | Auto-detected | Patches |
|---|---|---|
| OpenAI | api.openai.com |
httpx, requests |
| Anthropic | api.anthropic.com |
httpx, requests |
| Google Gemini | generativelanguage.googleapis.com |
httpx, requests |
| Azure OpenAI | *.openai.azure.com |
httpx, requests |
| Google Vertex AI | *-aiplatform.googleapis.com |
httpx, requests |
API
costkey.init(dsn, **options) — Initialize. Call once at startup.
costkey.with_context(**kwargs) — Context manager for custom tags.
costkey.start_trace(name) — Context manager for request tracing.
costkey.shutdown() — Flush and restore original HTTP clients.
costkey.register_extractor(extractor) — Add custom AI provider.
costkey.register_pricing(model, ...) — Add custom model pricing.
Also available for TypeScript
npm install costkey
import { CostKey } from 'costkey'
CostKey.init({ dsn: 'https://ck_...@app.costkey.dev/proj' })
License
MIT
Project details
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