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| title: Jack Patel AI Assistant | |
| emoji: 🦙 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 5.34.1 | |
| app_file: main.py | |
| license: mit | |
| # 🤖 Jack Patel AI Assistant | |
| A personalized AI assistant powered by a fine-tuned TinyLlama model, trained to answer questions about Jack Patel using custom data stored in `Data.json`. | |
| ## 🌟 Features | |
| - **Personalized Responses**: Trained on 150+ question-answer pairs about Jack Patel (from `Data.json`) | |
| - **Smart Fallback**: If a match isn't found in the training data, the model generates a response using TinyLlama | |
| - **Modern UI**: FastAPI-powered UI using a clean and responsive HTML form | |
| - **API Access**: RESTful API endpoints for programmatic access | |
| - **Container-Ready**: Deployable instantly on Hugging Face Spaces via Docker or source files | |
| ## 🚀 How to Use | |
| ### 🖥️ Web Interface | |
| Visit the Space and type any question — get a smart response about Jack Patel. | |
| ### 🔌 API Usage | |
| Make a GET request to: | |
| ``` | |
| /api/generate?instruction=your_question | |
| ``` | |
| ### ✅ Health Check | |
| Use: | |
| ``` | |
| /health | |
| ``` | |
| to confirm the app is running correctly. | |
| ## 📝 Example Questions | |
| - "What is your name?" | |
| - "What is your father's name?" | |
| - "Which school did you attend?" | |
| - "What are your technical skills?" | |
| - "Tell me about your hobbies" | |
| ## 🛠️ Technical Details | |
| - **Base Model**: `TinyLlama/TinyLlama-1.1B-Chat-v1.0` | |
| - **Fine-Tuning**: LoRA with your `Data.json` file containing personal Q&A pairs | |
| - **Framework**: FastAPI (backend), Jinja2 (templates) | |
| - **Interface**: HTML/CSS in `templates/index.html` | |
| - **Model Inference**: PyTorch + Transformers | |
| ## 📁 File Structure | |
| ``` | |
| ├── main.py # FastAPI application logic | |
| ├── requirements.txt # Dependencies | |
| ├── Dockerfile # Build config for Hugging Face Space | |
| ├── Data.json # Personalized Q&A training data | |
| ├── templates/ | |
| │ └── index.html # Web-based UI | |
| ├── lora_model/ # LoRA fine-tuned TinyLlama model | |
| └── static/ # Optional static files (CSS, JS) | |
| ``` | |
| ## 📊 Model Behavior | |
| - **Uses Data.json**: Loads Q&A pairs at runtime for exact matching | |
| - **Model-Generated Responses**: For non-exact matches, the TinyLlama model generates contextual answers | |
| - **Fallback Intelligence**: Matches similar or rephrased queries using embedding similarity | |
| ## 🔧 Setup Instructions | |
| ### 🧪 Local Development | |
| ```bash | |
| pip install -r requirements.txt | |
| python main.py | |
| ``` | |
| ### ☁️ Hugging Face Spaces | |
| 1. Upload all project files including: | |
| * `main.py` | |
| * `Data.json` | |
| * `lora_model/` folder | |
| * `requirements.txt` | |
| * `templates/index.html` | |
| 2. Hugging Face will automatically detect and run your app. | |
| ## 🔒 Privacy & Security | |
| * No data is stored or logged | |
| * Responses are generated locally in-memory | |
| * No external API calls | |
| * Entirely contained in the Hugging Face Space runtime | |
| ## 🤝 Contributing | |
| Want to improve this AI assistant? You can: | |
| * Add new question-answer pairs to `Data.json` | |
| * Enhance the UI | |
| * Optimize performance and latency | |
| * Add advanced features (like semantic search) | |
| ## 📄 License | |
| This project is licensed under the MIT License. | |
| **Built with ❤️ using FastAPI, PyTorch, and Hugging Face Transformers** |