Show HN: AgentTrace–Observability and runtime self-healing engine for AI agents

Live Production Demo:

- 🖥️ Interactive Web Dashboard: https://agent-trace-zeta.vercel.app/

- ⚙️ FastAPI Swagger Docs: https://agenttrace-api-cdav.onrender.com/docs

An end-to-end observability SDK and dashboard for autonomous AI agent pipelines. It monitors multi-step tool calls, visualizes latency bottlenecks, and automatically repairs malformed LLM tool arguments at runtime without crashing workflows.

LLMs frequently hallucinate tool arguments during multi-step runs:

- Passing strings instead of floats (e.g. "1200 INR"instead of1200.0)

- Inventing key names (e.g. "user_identifier"instead of"user_id")

- Omitting required schema fields

Normally, these cause immediate runtime crashes. AgentTrace catches these failures and auto-repairs them at runtime.

- Decorator SDK: Python, Pydantic (Validates schema before tool run)

- Self-Healing Layer: Fast inference via Groq to repair payloads on failure

- Collector Backend: FastAPI with SQLite persistence (traces.db)

- Live Dashboard: Next.js, Tailwind CSS with Payload Diff Inspector

# In project root

python -m uvicorn main:app --reload --port 8000