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langgraph studio

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Basic Information

LangGraph Studio is a specialized integrated development environment for building, prototyping, visualizing, interacting with, and debugging agentic systems that implement the LangGraph Server API protocol. The repository provides the web-based Studio application used to inspect graph architectures, run agents locally or against the LangGraph Platform, and integrate execution traces with LangSmith for tracing, evaluation, and prompt engineering. Studio supports a full Graph mode for detailed node-level inspection and a Chat mode for simpler chat-centric testing. It is intended for developers and teams working with LangGraph graphs to iterate on prompts, manage assistants and threads, run experiments, and diagnose runtime behavior while supporting local development workflows via the langgraph CLI.

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3145
App URL
https://github.com/langchain-ai/langgraph-studio
Github Repository
https://github.com/langchain-ai/langgraph-studio/blob/main/README.md

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App Details

Features
Key features documented in the README include visual graph architecture rendering and interactive execution, the ability to run and interact with deployed or local agents, and integration with LangSmith for tracing and evaluation. Studio supports managing assistants and threads, iterating on prompts, running dataset experiments, and managing long-term memory. A Graph mode exposes detailed node traversal and intermediate state, while Chat mode provides a simplified chat-focused UI suitable for business users. The project is designed to work with graphs on the LangGraph Platform or a local LangGraph Server and relies on Docker Compose for running API, Redis and Postgres. The README also documents troubleshooting guidance for browser connectivity and graph routing issues.
Use Cases
LangGraph Studio helps developers and evaluators understand and improve agent behavior by making execution transparent and interactive. It enables visual debugging of node traversal and intermediate state, time-travel style inspection of agent state, and direct iteration on prompts and routing logic. Integration with LangSmith allows teams to trace runs, add examples to datasets, and run evaluations over datasets to measure and compare behavior. Studio supports both high-detail Graph mode for engineering workflows and a simplified Chat mode for rapid testing and business-facing validation. The README also includes practical guidance for local development such as using the langgraph CLI, accessing local services via host.docker.internal when using Docker Compose, and workarounds for browser connection issues.

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