Passive LLM endpoint identity and stability instrumentation
Project description
llmwho
Passive LLM endpoint identity and stability instrumentation for Python.
pip install llmwho
import llmwho
handle = llmwho.init()
Direct Anthropic Messages API calls need no LLMWho-specific wrapper:
import llmwho
from anthropic import Anthropic
llmwho.init()
client = Anthropic()
client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=64,
messages=[{"role": "user", "content": "Hello"}],
)
One call instruments installed HTTPX (sync and async) and requests clients for
recognized LLM routes. It writes content-free observations to
~/.llmwho/events.ndjson; it never sends active traffic. Calls are idempotent,
streaming responses are not consumed, and handle.shutdown() safely restores
only LLMWho-owned patches.
Run an explicit OpenAI-compatible compatibility canary:
report = llmwho.probe(
base_url="https://api.openai.com/v1",
api_key="…",
model="gpt-4o-mini",
)
Inspect local history:
llmwho summary
llmwho dashboard
Identity results are probabilistic evidence, not cryptographic attestation. Version 0.2 uses response model metadata; its smoke suite measures capability and does not uniquely identify arbitrary model weights. Raw prompts, responses, headers, query strings, and credentials are never stored.
Full documentation, research review, and source: github.com/tcztzy/llmwho.
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