Roomy
Roomy is a local-first observability toolkit for LangChain agents. It records what entered the model (messages, tools, retrievers), token usage, latency, and structured traces in SQLite, with a CLI and an optional web UI for inspection.
Install
pip install roomy-observability
- PyPI package:
roomy-observability - Python import:
import roomy - CLI:
roomy(e.g.roomy serve,roomy sessions list,roomy dashboardto open the web UI in a browser)
Requires Python 3.11+.
Quick start
from roomy import end_session, instrument_langchain
bindings = instrument_langchain(app_name="my-agent", db_path="./traces.db")
result = chain.invoke(
{"topic": "Hello"},
config={"callbacks": bindings.callbacks},
)
end_session(bindings.manager)
Use wrap_agent(chain, bindings.manager) if you prefer binding callbacks on a Runnable.
Optional extras
| Extra | Purpose |
|---|---|
api |
FastAPI + Uvicorn (roomy serve for the inspector API) |
openai |
tiktoken for better token estimates |
examples |
LangGraph + OpenAI + dotenv + httpx (for repo examples under examples/) |
dev |
Tests, ruff, mypy, build, twine |
pip install "roomy-observability[api,openai]"
pip install "roomy-observability[api,openai,examples]" # LangGraph example deps
Documentation & source
Full monorepo (sample agents, web app, architecture docs): github.com/Sarang-Pramode/Roomy
Author: Sarang Pramode · License: MIT
1 maintainer
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