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# Amazon E-commerce Visual Assistant | |
A multimodal AI assistant that helps users search and explore Amazon products through natural language and image-based interactions. | |
## Features | |
- Text and image-based product search | |
- Product comparisons and recommendations | |
- Visual product recognition | |
- Detailed product information retrieval | |
- Price analysis and comparison | |
## Technologies Used | |
- FashionCLIP for visual understanding | |
- Mistral-7B Language Model for text generation | |
- FAISS for efficient similarity search | |
- Streamlit for the user interface | |
## Setup and Installation | |
1. Clone the repository: | |
```bash | |
git clone https://github.com/wisdom196473/amazon-multimodal-product-assistant.git | |
cd amazon-multimodal-product-assistant | |
``` | |
2. Install dependencies: | |
```bash | |
pip install -r requirements.txt | |
``` | |
3. Run the application: | |
```bash | |
streamlit run amazon_app.py | |
``` | |
## Project Structure | |
- `amazon_app.py`: Main Streamlit application | |
- `model.py`: Core AI model implementations | |
- `requirements.txt`: Project dependencies | |
## Future Directions | |
- [ ] Fine-Tune FashionClip embedding model based on the specific domain data | |
- [ ] Fine-Tune large language model to improve its generalization capabilities | |
- [ ] Develop feedback loops for continuous improvement |