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| title: LLM Monitor | |
| emoji: 🛡️ | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| app_port: 7860 | |
| pinned: false | |
| # LLM Monitor (GenAI Shield V2) | |
| A web application powered by Llama-Prompt-Guard-2-86M for pre-inference prompt screening, and post-inference response monitoring. | |
| ## Local Development | |
| 1. Create a virtual environment and install dependencies: | |
| ```bash | |
| python -m venv venv | |
| source venv/bin/activate | |
| pip install -r requirements.txt | |
| ``` | |
| 2. Download the Prompt Guard model weights: | |
| ```bash | |
| python download_model.py | |
| ``` | |
| 3. Run the application: | |
| ```bash | |
| export GEMINI_API_KEY="your-gemini-key" | |
| python genai_app.py | |
| ``` | |
| ## Deploying to Hugging Face Spaces | |
| 1. Create a new Space on [Hugging Face](https://huggingface.co/spaces). | |
| 2. Choose **Docker** as the SDK. | |
| 3. Choose the **Blank** template. | |
| 4. Go to **Settings** > **Variables and Secrets** and add your secrets: | |
| - `GEMINI_API_KEY`: Your Google Gemini API key. | |
| 5. Push this repository to your Hugging Face Space repository. Hugging Face will automatically build and run the Docker image. | |