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Tracing and graph extraction for agents

Project description

AgentGlass

A local, visual debugger for agentic AI workflows built on LangGraph and Google Gemini. Wrap your compiled graph in a single context manager, run it as usual, and get a live, clickable graph view in your browser with the exact input and output of every node execution — including every visit of a loop.

No hosted platform. No login. No data leaves your machine.

Install

pip install agentglass

Quickstart

from agentglass import trace
from langgraph.graph import StateGraph, END

# ... build your graph as you normally would ...
graph = StateGraph(MyState)
graph.add_node("retrieve", retrieve_fn)
graph.add_node("generate", generate_fn)
graph.set_entry_point("retrieve")
graph.add_edge("retrieve", "generate")
graph.add_edge("generate", END)
compiled = graph.compile()

with trace(compiled, port=8765):
    result = compiled.invoke({"question": "What's the weather in Tokyo?"})

A browser tab opens at http://localhost:8765 showing your graph. As the run proceeds, nodes light up. Click any node to see exactly what state went in and what update came out. Nodes inside a loop show a visit-count badge and give you per-call history in the side panel.

When the run finishes, the server keeps running so you can keep poking around. Press Ctrl-C to exit.

What's in the MVP

  • Live graph rendering via Cytoscape.js with a layered DAG layout. Conditional edges are dashed; regular edges are solid.
  • Click-to-inspect any node: input state, output state update, duration, and per-execution history for looped nodes.
  • Gemini-aware formatting of message / content arrays: role badges, function-call / function-response pairing, finish-reason warnings.
  • Safe serialization of arbitrary Python state — Pydantic, LangChain messages, dataclasses, numpy arrays, bytes — with per-field size caps.
  • Zero network egress: everything is local and in-memory.

What's not in the MVP (yet)

  • Diff view between consecutive node executions
  • Time-travel / pause-and-edit
  • Multi-run comparison
  • Persistence (SQLite) — currently in-memory only
  • Cost / latency overlays

License

MIT.

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