rag-chatbot-with-cohere's Introduction

RAG Chatbot with cohere

This is a simple chatbot application that leverages the Cohere API for text embedding, document retrieval, and conversation generation.

Setup

Install the required dependencies:
```
pip install -r requirements.txt
```

Make sure to create a virtual environment if needed.

Set up .env-File (adding COHERE API KEY)

COHERE_API_KEY=your_cohere_api_key

Run the application
```
python app.py
```

Files

'app.py'

This file contains the main application logic. It initializes a chatbot using the Cohere API and allows users to interact with the chatbot through the command line.

'cohere_chatbot.py'

This file defines two classes: Documents and Chatbot. The Documents class loads, embeds, and indexes documents for efficient retrieval. The Chatbot class generates responses based on user input and retrieves relevant documents using the Documents class.

Usage

Run the app.py file to start the chatbot application.
Enter your messages in the command line, and the chatbot will respond based on the documents it has indexed.
Type "quit" to end the conversation.

Dependencies

Cohere API: Used for text embedding, document retrieval, and conversation generation.
python-dotenv: Used for loading environment variables from a .env file.
hnswlib: Used for efficient k-NN search.

Additional Resources

Cohere's Guide to Build a RAG-Powered Chatbot with Chat, Embed, and Rerank

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