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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. | |
| """) |