Skip to main content

Visualize live LangGraph execution and see how your agent thinks as it runs.

Project description

LangGraphics

LangGraphics is a live visualization tool for LangGraph agents. It's especially useful when working with large networks: graphs with many nodes, branching conditions, and cycles are hard to reason about from the logs alone.

Demo

Why it helps

Seeing the execution path visually makes it immediately obvious which branches were taken, where loops occurred, and where the agent got stuck or failed. It also helps when onboarding to an unfamiliar graph - a single run tells you more about the workflow than reading the graph definition ever could.

How to use

One line is all it takes - wrap the compiled graph of your agent workflow with LangGraphics' watch function before invoking it, and the visualization opens in your browser automatically, tracking the agent in real time.

from langgraph.graph import StateGraph, MessagesState
from langgraphics import watch

workflow = StateGraph(MessagesState)
workflow.add_node(...)
workflow.add_edge(...)

graph = watch(workflow.compile())

await graph.ainvoke({"messages": [...]})

Works with any LangGraph agent, no matter how simple or complex the graph is. Add it during a debugging session, or keep it in while you're actively building - it has no effect on how the agent behaves or what it returns.

Features

Feature LangGraphics LangFuse LangSmith
Fully local ✅ 🟥 🟥
Standalone ✅ 🟥 🟥
Easy to learn ✅ 🟥 🟥
One-line setup ✅ 🟥 🟥
Data stays local ✅ 🟥 🟥
No API key required ✅ 🟥 🟥
Live execution graph ✅ 🟥 🟥
No refactoring required ✅ 🟥 🟥
Self-hosted ✅ ✅ 🟥
No vendor lock-in ✅ ✅ 🟥
Unlimited free usage ✅ ✅ 🟥
Graph visualization ✅ ✅ ✅
Cost & latency tracking ✅ ✅ ✅
Prompt evaluation 🟥 ✅ ✅

Contribute

Any contribution is welcome. Feel free to open an issue or a discussion if you have any questions not covered here. If you have any ideas or suggestions, please open a pull request.

License

Copyright (C) 2026 Artyom Vancyan. MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

langgraphics-0.1.0b3.tar.gz (329.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

langgraphics-0.1.0b3-py3-none-any.whl (334.1 kB view details)

Uploaded Python 3

File details

Details for the file langgraphics-0.1.0b3.tar.gz.

File metadata

  • Download URL: langgraphics-0.1.0b3.tar.gz
  • Upload date:
  • Size: 329.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for langgraphics-0.1.0b3.tar.gz
Algorithm Hash digest
SHA256 0337ee7028c977faf1f632d5b1576c33ddd100737554088a2870bc33bcd6cd82
MD5 c794baf393967ef32c0b2bf416f9e696
BLAKE2b-256 2070ea350aa185e2dbe4e1e239aa57a608ce571c4cfa5d7df54b70b1bfb4ffbe

See more details on using hashes here.

File details

Details for the file langgraphics-0.1.0b3-py3-none-any.whl.

File metadata

  • Download URL: langgraphics-0.1.0b3-py3-none-any.whl
  • Upload date:
  • Size: 334.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for langgraphics-0.1.0b3-py3-none-any.whl
Algorithm Hash digest
SHA256 acd870fffb4453180729e5539fa38299c9782c07223c0c83034f47a476a75f08
MD5 9aa9c4fc732f909da64a0c90b4a3ce3e
BLAKE2b-256 6fac995fb58920ccaf657c56e635459233fdd5259f5ed6d0728c2f187057d590

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page