LLM apps are getting more complex. A simple prompt call turns into a pipeline: embed the query, retrieve documents, call a model, parse the answer, maybe call tools, then run a second model pass. When something breaks, terminal logs are not enough. That is where tracing tools help. LangSmith does this well — but it requires a cloud account, works best inside LangChain, and sends your trace data to a hosted service. For a lot of projects, that is more than I need. I wanted something closer to this: pip install opensmith Enter fullscreen mode Exit fullscreen mode No Docker. No account. No config. No data leaving my machine. So I built opensmith . What is opensmith? opensmith is a local-first LLM pipeline tracer for Python . It stores traces in SQLite at ~/.opensmith/traces.db and serves a local dashboard at localhost:7823 . The dashboard shows traces, nested steps, inputs, outputs, errors, latency, token usage, cost estimates, and live updates via WebSocket.…