nishantsbi/streamlit-agent

Reference implementations of several LangChain agents as Streamlit apps

🦜️🔗 LangChain 🤝 Streamlit agent examples

This repository contains reference implementations of various LangChain agents as Streamlit apps including:

• basic_streaming.py: Simple streaming app with langchain.chat_models.ChatOpenAI (View the app)
• mrkl_demo.py: An agent that replicates the MRKL demo (View the app)
• minimal_agent.py: A minimal agent with search (requires setting OPENAI_API_KEY env to run)
• search_and_chat.py: A search-enabled chatbot that remembers chat history (View the app)
• chat_with_documents.py: Chatbot capable of answering queries by referring custom documents (View the app)
• chat_with_sql_db.py: Chatbot which can communicate with your database (View the app)
• chat_pandas_df.py: Chatbot to ask questions about a pandas DF (View the app)

Apps feature LangChain 🤝 Streamlit integrations such as the Callback integration.

Setup

This project uses Poetry for dependency management.

# Create Python environment
$ poetry install

# Install git pre-commit hooks
$ poetry shell
$ pre-commit install

Running

# Run mrkl_demo.py or another app the same way
$ streamlit run streamlit_agent/mrkl_demo.py

Running with Docker

This project includes Dockerfile to run the app in Docker container. In order to optimise the Docker Image is optimised for size and building time with cache techniques.

To generate Image with DOCKER_BUILDKIT, follow below command

DOCKER_BUILDKIT=1 docker build --target=runtime . -t langchain-streamlit-agent:latest

1. Run the docker container directly

docker run -d --name langchain-streamlit-agent -p 8051:8051 langchain-streamlit-agent:latest

2. Run the docker container using docker-compose (Recommended)

Edit the Command in docker-compose with target streamlit app

docker-compose up

Contributing

We plan to add more agent and chain examples over time and improve the existing ones - PRs welcome! 🚀