Python Chatbot with LLaMA2 via Streamlit
Introduction
Discover the exciting possibilities of building a powerful chatbot using LLaMA2, the cutting-edge Large Language Model from Meta. This guide will take you through the steps of creating a chatbot with session chat history using the Streamlit framework for the frontend.
Key Features
* **Interactive Chatbot:** Engage with your chatbot in real-time. * **Session Chat History:** Keep track of previous conversations for seamless interactions. * **Multi-Modal Response:** Get comprehensive responses from the chatbot, including text, images, and links. * **Easy Deployment:** Deploy the chatbot easily using Streamlit.
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