sentinelproxy (Python)

Mirror your LangChain or LiteLLM agent turns to SentinelProxy — the self-healing layer for AI agents. The judge catches hallucinations, prompt injections, PII leaks and competitor mentions, then hands you a hardened system prompt.

Install

pip install sentinelproxy            # core + LiteLLM
pip install "sentinelproxy[langchain]"   # + LangChain callback handler

Get a per-project API key from your dashboard → project → Connect tab.

LangChain

from sentinelproxy import SentinelProxyCallbackHandler

handler = SentinelProxyCallbackHandler(
    api_key="sk_sentinel_…",
    system_prompt="You are a support agent for Acme.",
)
llm.invoke(messages, config={"callbacks": [handler]})

LiteLLM

import litellm
from sentinelproxy import sentinel_litellm_callback

litellm.success_callback = [sentinel_litellm_callback("sk_sentinel_…")]

Low-level client

from sentinelproxy import SentinelClient

SentinelClient("sk_sentinel_…").log(
    system_prompt="You are a support agent for Acme.",
    user_input="Where's my order?",
    llm_response="Let me check…",
    latency_ms=820,
)

Logging is best-effort and off your critical path — failures are swallowed so observability never breaks the agent (pass raise_on_error=True to SentinelClient to surface them). PII is scrubbed at the SentinelProxy edge before anything is stored.

Build & publish

python -m build
python -m twine upload dist/*

License

MIT