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import streamlit as st | |
st.set_page_config( | |
page_title="Langchain Chatbot", | |
page_icon='π¬', | |
layout='wide' | |
) | |
st.header("Chatbot Implementations with Langchain") | |
st.write(""" | |
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. | |
Leveraging the power of Langchain, the creation of chatbots becomes effortless. Here are a few examples of chatbot implementations catering to different use cases: | |
- **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. | |
We will improve this implementation to include these examples as we progress in the course. | |
""") |