Chatbot Implementations with Langchain + Streamlit

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

🖥️ 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.