Show HN: AgentLens – Chrome DevTools for AI Agents (open-source, self-hosted)
<p>Agents are opaque. AgentLens is Chrome‑DevTools for AI agents — self‑hosted, open‑source. It traces tool calls and visualizes decision trees so you can see why an agent picked a tool. Repo: <a href="https://github.com/tranhoangtu-it/agentlens" rel="noopener noreferrer">https://github.com/tranhoangtu-it/agentlens</a></p> <p>It plugs into LangChain/FastAPI stacks, uses OpenTelemetry spans, and ships a React frontend (Python backend, TypeScript UI). You get per-tool inputs/outputs, timestamps, and branching paths — the raw traces you actually need to debug agents.</p> <p>Practical playbook: emit spans from your agent, sample 100% in dev, 1–5% in prod. Persist traces off your user data store (filter PII). Watch for repeated tool calls, backoff loops, and input drift. AgentLens gives visibil
Agents are opaque. AgentLens is Chrome‑DevTools for AI agents — self‑hosted, open‑source. It traces tool calls and visualizes decision trees so you can see why an agent picked a tool. Repo: https://github.com/tranhoangtu-it/agentlens
It plugs into LangChain/FastAPI stacks, uses OpenTelemetry spans, and ships a React frontend (Python backend, TypeScript UI). You get per-tool inputs/outputs, timestamps, and branching paths — the raw traces you actually need to debug agents.
Practical playbook: emit spans from your agent, sample 100% in dev, 1–5% in prod. Persist traces off your user data store (filter PII). Watch for repeated tool calls, backoff loops, and input drift. AgentLens gives visibility; you still own reliability and ops.
Takeaway: observability is the first thing you add once an agent makes real decisions. AgentLens is a usable, self‑hosted starting point — not enterprise polish. Try it locally, wire traces, then ask: which tool calls do we actually trust?
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