langchain-ai/agent-chat-ui

🦜💬 Web app for interacting with any LangGraph agent (PY & TS) via a chat interface.

View on GitHub ↗Jump to charts ↓

Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 1 hour ago
Added to GitGenius on September 21st, 2026
Created on February 18th, 2025
Open Issues & Pull Requests: 90 (+0)
GitHub issues: Enabled
Number of forks: 695
Total Stargazers: 3,203 (+0)
Total Subscribers: 19 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2.0 days
Mean response time: 15.5 days
90th percentile: 64.0 days
Tracked items: 73

How this project is maintained

100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Three people close 74% of everything that gets resolved.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 57
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 337 days
Stale 30+ days: 56
Stale 90+ days: 54

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • good first issue (1)

Most active issues this week

Sign in to see which issues are moving.
Sign in

Detailed Description

Agent Chat UI is a web application that provides a chat interface for interacting with LangGraph agents written in Python or TypeScript.

The tool solves the problem of accessing and testing LangGraph agents through a user-friendly chat interface rather than requiring direct code interaction. It works by connecting to any LangGraph agent backend and exposing its capabilities through a web-based chat UI, allowing developers and end users to converse with agents naturally without needing to understand the underlying agent implementation.

Developers should choose this tool if they have built LangGraph agents and want to quickly expose them to users through a chat interface without building a custom frontend. It suits projects where the primary interaction model is conversational and where the agent logic is already implemented in LangGraph. The tool supports both Python and TypeScript agent implementations, making it flexible across different development environments.

The project shows active development with regular commits addressing bug fixes and feature improvements. The codebase demonstrates ongoing refinement of the chat interface and agent integration patterns. Maintenance activity indicates responsiveness to issues and a commitment to keeping the tool functional with current versions of its dependencies.