| | --- |
| | license: mit |
| | title: Iver |
| | sdk: gradio |
| | emoji: 📚 |
| | colorFrom: blue |
| | colorTo: red |
| | short_description: Verifiseringsspesialisten Iver |
| | sdk_version: 5.23.3 |
| | --- |
| | # Iver |
| |
|
| | A Retrieval-Augmented Generation (RAG) based chatbot with excellent Norwegian language support, built using Hugging Face's Inference API. |
| |
|
| | ## Features |
| |
|
| | - **Norwegian Language Support**: Leverages state-of-the-art Norwegian language models like NorMistral, Viking, and NorskGPT |
| | - **Document Processing**: Upload and process documents in various formats (PDF, TXT, HTML) |
| | - **RAG Implementation**: Retrieves relevant context from documents to generate accurate responses |
| | - **Embeddable Interface**: Easily embed the chatbot in any website using iframe or JavaScript widget |
| | - **Lightweight Architecture**: Uses Hugging Face's Inference API instead of running models locally |
| |
|
| | ## Architecture |
| |
|
| | This chatbot uses a lightweight architecture that leverages Hugging Face's hosted models: |
| |
|
| | 1. **Document Processing**: Documents are processed locally, extracting text and splitting into chunks |
| | 2. **Embedding Generation**: Document chunks are embedded using Hugging Face's Inference API |
| | 3. **Retrieval**: When a query is received, the most relevant document chunks are retrieved |
| | 4. **Response Generation**: The LLM generates a response based on the retrieved context |
| |
|
| | ## Getting Started |
| |
|
| | ### Prerequisites |
| |
|
| | - Python 3.10+ |
| | - A Hugging Face account (for API access) |
| |
|
| | ### Installation |
| |
|
| | 1. Clone the repository: |
| | ```bash |
| | git clone https://huggingface.co/spaces/username/norwegian-rag-chatbot |
| | cd norwegian-rag-chatbot |
| | ``` |
| |
|
| | 2. Install dependencies: |
| | ```bash |
| | pip install -r requirements-ultra-light.txt |
| | ``` |
| |
|
| | 3. Set up your Hugging Face API key: |
| | ```bash |
| | export HF_API_KEY="your_api_key_here" |
| | ``` |
| |
|
| | ### Running the Chatbot |
| |
|
| | ```bash |
| | python app.py |
| | ``` |
| |
|
| | The chatbot will be available at http://localhost:7860 |
| |
|
| | ## Usage |
| |
|
| | ### Chat Interface |
| |
|
| | The main chat interface allows you to: |
| | - Ask questions in Norwegian |
| | - Receive responses based on your uploaded documents |
| | - Adjust temperature and other settings |
| |
|
| | ### Document Upload |
| |
|
| | You can upload documents to provide context for the chatbot: |
| | - Supported formats: PDF, TXT, HTML |
| | - Documents are automatically processed and indexed |
| | - The chatbot will use these documents to provide more accurate responses |
| |
|
| | ### Embedding |
| |
|
| | You can embed the chatbot in your website using: |
| | - iFrame embedding |
| | - JavaScript widget |
| | - Direct link |
| |
|
| | ## Deployment |
| |
|
| | The chatbot is designed to be deployed to Hugging Face Spaces: |
| |
|
| | 1. Create a new Space on Hugging Face |
| | 2. Upload the code to the Space |
| | 3. Set the HF_API_KEY secret in the Space settings |
| | 4. The Space will automatically build and deploy the chatbot |
| |
|
| | ## Models |
| |
|
| | The chatbot can use various Norwegian language models: |
| |
|
| | - **NorMistral-7b-scratch**: A large Norwegian language model pretrained from scratch |
| | - **Viking 7B**: A multilingual model for Nordic languages |
| | - **NorskGPT**: A Norwegian language model based on Mistral or LLAMA2 |
| |
|
| | For embeddings, it uses: |
| | - **NbAiLab/nb-sbert-base**: A Norwegian sentence embedding model |
| |
|
| | ## License |
| |
|
| | This project is licensed under the MIT License - see the LICENSE file for details. |
| |
|
| | ## Acknowledgements |
| |
|
| | - [Hugging Face](https://huggingface.co/) for hosting the models and providing the Inference API |
| | - [Gradio](https://gradio.app/) for the web interface framework |
| | - The creators of the Norwegian language models used in this project |
