YouTube Chatbot with Langchain, RAG, Cohere Embedding, Chroma DB, LLama3, and Ollama

Overview

This project leverages Langchain, RAG, Cohere Embedding, Chroma DB, LLama3, and Ollama to create a YouTube Chatbot. The chatbot can summarize YouTube videos and answer questions based on the video's transcript.

Features

• Video Summarization: Generate concise summaries of YouTube videos.
• Question Answering: Answer questions related to the content of YouTube videos using their transcripts.
• Advanced Embeddings: Utilize Cohere Embedding for efficient and accurate text representation.
• Robust Vector Database: Store and retrieve data using Chroma DB.
• Powerful Language Models: Employ LLama3 and Ollama for natural language understanding and generation.

Installation

1. Clone the repository:

   git clone https://github.com/SOURABHMISHRA5221/YoutubeVideoChatBotLLM.git
   cd YoutubeVideoChatBotLLM

Usage

1. Run the main script:

   pip install -r requirements.txt
   python ChatBot.py

2. Interact with the chatbot through the provided interface.

Configuration

• Make sure to add .env file. Ensure that the .env file contains the correct values for:
• MODEL_URL (the URL for your LLama3 or Ollama model)
• COHERE_API_KEY (your API key for Cohere embeddings)

Acknowledgements

• Langchain
• Cohere
• Chroma DB
• LLama3
• Ollama

To Host llama3 or any model locally checkout :

• Hosting LLM Locally