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# WatsonX-WebChat
WatsonX-WebChat is an interactive web application that uses IBM Watson's language models to answer questions based on the content of a provided web page URL. This application leverages Retrieval-Augmented Generation (RAG) techniques to provide accurate and contextually relevant answers.
## Features
- Extracts and processes text from a given URL.
- Embeds the text and stores it in a database.
- Answers user questions based on the embedded content using IBM Watson's language models.
- Interactive web interface built with Streamlit.
## Setup and Deployment
### Prerequisites
- Docker
- WatsonX IBM
### Installation
1. **Clone the repository:**
```sh
git clone https://github.com/your-username/WatsonX-WebChat.git
cd WatsonX-WebChat
```
2. **Create a `.env` file with your IBM Cloud credentials:**
```plaintext
API_KEY=your_ibm_cloud_api_key
PROJECT_ID=your_ibm_cloud_project_id
```
3. **Build the Docker image:**
```sh
docker build -t watsonx-webchat .
```
4. **Run the Docker container:**
```sh
docker run -p 8501:8501 --env-file .env watsonx-webchat
```
### Deploy on Hugging Face
1. **Log in to Hugging Face CLI:**
```sh
huggingface-cli login
```
2. **Create a new repository on Hugging Face.**
3. **Push the Docker image to Hugging Face:**
```sh
docker tag watsonx-webchat huggingface.co/your-username/watsonx-webchat
docker push huggingface.co/your-username/watsonx-webchat
```
4. **Configure the Hugging Face repository to use the Docker image:**
- Go to your Hugging Face repository page.
- Click on "Settings".
- Under "Custom Docker Image", set the image to `huggingface.co/your-username/watsonx-webchat`.
### Usage
1. **Access the application:**
Open your browser and go to the URL provided by Hugging Face after deploying the application.
2. **Enter the required information:**
- **API Key**: Your IBM Cloud API key.
- **Project ID**: Your IBM Cloud project ID.
- **URL**: The URL of the webpage you want to extract content from.
- **Collection Name**: A unique name for the webpage's data collection.
- **Question**: The question you want to ask based on the webpage content.
3. **Get the response:**
Click the "Answer the question" button to get a response from the application.
## Contributing
Feel free to open issues or submit pull requests if you find any bugs or have suggestions for new features.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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