AgentTrace

Visual debugger for AI agent loops. Step-by-step. Locally. Zero config.

Quick Start

npx @ravaniroshan/agentrace

Opens the trace viewer at http://localhost:7823

Full Setup

Install the Python tracer in your agent project:

pip install agentrace

Add decorators to your agent:

from agentrace import trace, trace_llm, trace_tool

@trace(name="my_agent")
def run_agent(task: str):
    ...

@trace_llm
def call_llm(messages):
    return ollama.chat(model="qwen2.5:7b", messages=messages)

@trace_tool
def web_search(query: str) -> str:
    ...

View traces from any terminal:

npx @ravaniroshan/agentrace

Commands

npx @ravaniroshan/agentrace              # start UI viewer (default)
npx @ravaniroshan/agentrace ui           # start UI viewer
npx @ravaniroshan/agentrace traces       # list all traces in terminal
npx @ravaniroshan/agentrace clear        # delete all traces
npx @ravaniroshan/agentrace --version    # show version
npx @ravaniroshan/agentrace --help       # show help

Global Install

npm install -g @ravaniroshan/agentrace
agentrace ui

How It Works

The Python library saves trace files to ~/.agentrace/traces/ The npm CLI reads those same files and serves the web viewer. No configuration needed between the two.

Requirements

• Node.js 18+
• Python agent instrumented with pip install agentrace

License

MIT