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Chatbot Implementations with Langchain + Streamlit

Open in GitHub Codespaces

Langchain is a powerful framework designed to streamline the development of applications using Language Models (LLMs).
It provides a comprehensive integration of various components, simplifying the process of assembling them to create robust applications.

💬 Sample chatbot use cases

Here are a few examples of chatbot implementations using Langchain and Streamlit:

  • Basic Chatbot
    Engage in interactive conversations with the LLM.

  • Context aware chatbot
    A chatbot that remembers previous conversations and provides responses accordingly.

  • Chatbot with Internet Access
    An internet-enabled chatbot capable of answering user queries about recent events.

  • Chat with your documents
    Empower the chatbot with the ability to access custom documents, enabling it to provide answers to user queries based on the referenced information.

  • Chat with SQL database
    Enable the chatbot to interact with a SQL database through simple, conversational commands.

  • Chat with Websites
    Enable the chatbot to interact with website contents.

Streamlit App

Created a multi-page streamlit app containing all sample chatbot use cases.
You can access this app through this link: langchain-chatbot.streamlit.app

Streamlit App

🖥️ Running locally

# Run main streamlit app
$ streamlit run Home.py

📦 Running with Docker

# To generate image
$ docker build -t langchain-chatbot .

# To run the docker container
$ docker run -p 8501:8501 langchain-chatbot

💁 Contributing

Planning to add more chatbot examples over time. PRs are welcome.