| | --- |
| | title: Test |
| | emoji: ⚡ |
| | colorFrom: indigo |
| | colorTo: gray |
| | sdk: gradio |
| | sdk_version: 6.5.1 |
| | app_file: app.py |
| | pinned: false |
| | --- |
| | |
| | # 🔍 Medical Document Search using sentence-transformers/embeddinggemma-300m-medical |
| |
|
| | A search tool specialized in the medical field to helps you find relevant information across your medical documents. |
| |
|
| | ## How It Works |
| |
|
| | 1. **Enter your question** in the reference sentence box (e.g., "Is Mr. Allen eligible for enrollment given his type 2 diabetes?") |
| | 2. **Add documents** to search through in the comparison sentence boxes |
| | 3. **Click "Calculate Similarity"** to see ranked results |
| | 4. **Review the scores**: |
| | - 🟢 Green (≥0.70): High similarity - very relevant |
| | - 🟠 Orange (0.50-0.69): Medium similarity - somewhat relevant |
| | - 🟣 Purple (<0.50): Lower similarity - less relevant |
| |
|
| | ## Installation |
| | ```bash |
| | pip install -r requirements.txt |
| | ``` |
| |
|
| | ## Setup |
| |
|
| | 1. Get a Hugging Face API token from [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens) |
| | 2. Create a `.env` file in the project directory: |
| | ``` |
| | HF_TOKEN=your_token_here |
| | ``` |
| | 3. Run the application: |
| | ```bash |
| | python main.py |
| | ``` |
| |
|
| | ## Notes |
| | Note that for efficiency purposes, a template of the interface code and the css code was generate with an LLM. |
| |
|
| |
|
