tare-sdk 0.1.0

LLM cost attribution proxy SDK — drop-in OpenAI client with feature tagging

Tare SDK

Drop-in replacement for openai.OpenAI that routes every call through the Tare proxy and attributes cost to the product feature that made it.

5-line integration

import tare

llm = tare.client(api_key="sk-...", feature="chat")
resp = llm.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Summarise this in one sentence."}],
)
print(resp.choices[0].message.content)

That's it — every call is now tracked in the Tare dashboard, broken down by the feature label you pass.

Installation

# From the monorepo root (local dev)
pip install -e ./sdk

# Future PyPI release
pip install tare

Configuration

Env var	Default	Description
TARE_PROXY_URL	http://localhost:8000	Running Tare proxy base URL

The /v1 path suffix is appended automatically, so you never need to add it.

# Override at call time — useful in staging / prod
llm = tare.client(
    api_key="sk-...",
    feature="summarizer",
    proxy_url="https://tare.internal",
)

How it works

tare.client() returns a standard openai.OpenAI instance configured with:

• base_url → <proxy_url>/v1
• default_headers → {"X-Tare-Feature": "<feature>"}

The proxy forwards the request to OpenAI unchanged, records token usage, cost, and latency against the feature label, then returns the original response. Zero behaviour change for the caller.

Running the test suite

# Requires the proxy running on localhost:8000
cd sdk
pip install -e ".[dev]"
pytest

Reminder: Add a LICENSE file before publishing to PyPI.