https://github.com/engichang1467/rag-chatbot-cohere
Retrieval Augmented Generation Chatbot with Cohere and HuggingFace 🤗
https://github.com/engichang1467/rag-chatbot-cohere
chatbot cohere huggingface llm rag
Last synced: 4 months ago
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Retrieval Augmented Generation Chatbot with Cohere and HuggingFace 🤗
- Host: GitHub
- URL: https://github.com/engichang1467/rag-chatbot-cohere
- Owner: engichang1467
- License: mit
- Created: 2024-03-23T05:17:44.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-03-23T05:32:50.000Z (over 2 years ago)
- Last Synced: 2025-02-21T18:14:21.865Z (over 1 year ago)
- Topics: chatbot, cohere, huggingface, llm, rag
- Language: Python
- Homepage: https://huggingface.co/spaces/mca183/rag-cohere
- Size: 4.88 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# RAG chatbot with Cohere API and Hugging Face 🤗
Retrieval Augmented Generation Chatbot with Cohere API and HuggingFace 🤗
## Overview
Introducing the Retrieval Augmented Generation Chatbot, a groundbreaking fusion of Cohere API and Hugging Face's technology, revolutionizing conversational AI by seamlessly blending factual accuracy with fluent dialogue. Leveraging Cohere API's robust knowledge retrieval and Hugging Face's generative capabilities, this innovative chatbot delivers contextually relevant and human-like conversations across domains like customer service and education, setting a new standard in interactive technology.
## Getting Started
### Environment Setup
To get started, create a virtual environment and activate it:
```bash
virtualenv venv
source venv/bin/activate
```
Create a local environment file (`.env`) and add your huggingface API key:
```bash
COHERE_API=your_cohere_api_key
```
### Install Dependencies
Next, install the required dependencies using pip:
```bash
pip install -r requirements.txt
```
### Run the Application
Now, you can run the application:
```bash
gradio app.py
```
This will start the application, allowing you to chat with the RAG model.
## Usage
Once the application is up and running, you can interact with the chatbot through a web interface.
## Additional Resources
- Check out the chatbot on [](https://huggingface.co/spaces/mca183/rag-cohere)
- Explore more about the Dynamic-TinyBERT model [here](https://huggingface.co/Intel/dynamic_tinybert)