https://github.com/djdhairya/ai-doctor
https://github.com/djdhairya/ai-doctor
base46 deep-learning dotenv fastapi fastapi-template generative-ai groq-api jinja2-templates llama3 os pillow
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/djdhairya/ai-doctor
- Owner: djdhairya
- License: mit
- Created: 2025-02-21T09:16:18.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-02-21T09:20:32.000Z (10 months ago)
- Last Synced: 2025-06-27T04:58:06.216Z (5 months ago)
- Topics: base46, deep-learning, dotenv, fastapi, fastapi-template, generative-ai, groq-api, jinja2-templates, llama3, os, pillow
- Language: HTML
- Homepage:
- Size: 1.49 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# AI Doctor
AI Doctor is an advanced image-based medical assistant powered by Groq's AI models. It allows users to upload medical images and query AI models for insights. The system leverages Llama-3.2 models to provide responses based on image analysis and textual queries.
## Features
- Upload medical images and get AI-generated insights
- Uses Groq's Llama-3.2 models for vision-based inference
- FastAPI-based backend with a web interface
- Supports multiple AI models for better accuracy
- Error handling and logging for better debugging
## Tech Stack
- **FastAPI** for the web server
- **Python** for backend scripting
- **Jinja2** for rendering HTML templates
- **Pillow** for image processing
- **Requests** for making API calls
- **Logging** for debugging and error tracking
- **Groq API** for AI-powered analysis
## Installation
### Prerequisites
- Python 3.10+
- Virtual environment (optional but recommended)
### Setup
1. Clone the repository:
```bash
git clone https://github.com/djdhairya/AI-Doctor.git
cd Ai-Doctor
```
2. Create a `.env` file and add your Groq API key:
```ini
GROQ_API_KEY=your_api_key_here
```
## Running the Application
### Using FastAPI
Run the FastAPI server:
```bash
uvicorn app:app --host 0.0.0.0 --port 8000 --reload
```
Access the web interface at:
```
http://localhost:8000
```
### Using Command Line
To process an image using `main.py`, update the image path and query in the script, then run:
```bash
python main.py
```
## API Endpoints
### `GET /`
- Renders the web interface for image upload and querying.
### `POST /upload_and_query`
- Accepts an image and a text query.
- Returns AI-generated insights from Groq's models.
## Example Usage
### Upload and Query via Web UI
1. Open `http://localhost:8000`
2. Upload an image
3. Enter a query (e.g., "What does this X-ray indicate?")
4. Click submit to receive AI-generated insights
### Direct Image Processing via Python
Modify `main.py` to specify your image path and query:
```python
image_path = "path/to/your/image.png"
query = "What is shown in this image?"
```
Run:
```bash
python main.py
```
## Error Handling
- Ensures the image is valid before processing
- Logs errors for debugging
- Handles API failures with appropriate messages
## Future Enhancements
- Integration with more AI models
- Support for multiple image formats
- Enhanced UI for better user experience
## License
This project is licensed under the MIT License.
