langchain-streamlit-template
Template for deploying a LangGraph agent on Streamlit
GraphCanon updated 1w · GitHub synced 1w
Decision brief
Decision-critical facts for langchain-streamlit-template
Good fit when
- You need a specific template that is designed for LangGraph agents and Streamlit.
- If your AI project involves using LangGraph to deploy chatbots or similar applications and you want quick observability with LangSmith.
Avoid when
- If you prefer frameworks other than Streamlit for creating web apps, this tool will not be suitable.
- This tool is not recommended if you are working on projects that do not require integration with or monitoring through LangGraph agents.
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (580d since push)
- As of 1w
- Provenance
- Not a fork · Personal account
- As of 1w
- Security (OSV)
- No criticals
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install langchain-streamlit-templateSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides a template repository to deploy a LangGraph AI agent using Streamlit, a Python library for creating web apps. It includes features like setting up environment variables and integrating with LangSmith for observability.
Capability facts
- Languages
- python
Source: github.language · Aug 15, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 15, 2026)
# LangChain-Streamlit TemplateSource link
Source: README excerpt (regex_v1, Aug 15, 2026)
This repo serves as a template for how to deploy a [LangGraph](https://langchain-ai.github.io/langgraph/) agent on Streamlit.Source link
Source: README excerpt (regex_v1, Aug 15, 2026)
After installing dependencies with e.g. `$ pip install -r requirements.txt`, you can run this project locally with the following commaSource link
Tags
README
LangChain-Streamlit Template
This repo serves as a template for how to deploy a LangGraph agent on Streamlit.
This repo contains an main.py file which has a template for a chatbot implementation.
Adding your chain
To add your chain, you need to change the load_chain function in main.py.
Depending on the type of your chain, you may also need to change the inputs/outputs that occur later on.
Run locally
After installing dependencies with e.g. $ pip install -r requirements.txt, you can run this project locally with the following command:
$ streamlit run main.py
Deploy on Streamlit
This is easily deployable on the Streamlit platform.
Note that when setting up your Streamlit app you should make sure to add OPENAI_API_KEY as a secret environment variable.
Setting up LangSmith
To quickly spot issues and improve the performance of your LangGraph projects, sign up for LangSmith. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started here.
For agents
This page has a .md twin and JSON over the API.