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https://github.com/seekai-786/medi_bot_customgpt
I have created a new AI Chatbot with Hugging Face to allow users to interact with different chatbot and soon I will implement fine tuning on these models to works more efficiently on one specific domain
https://github.com/seekai-786/medi_bot_customgpt
Last synced: 22 days ago
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I have created a new AI Chatbot with Hugging Face to allow users to interact with different chatbot and soon I will implement fine tuning on these models to works more efficiently on one specific domain
- Host: GitHub
- URL: https://github.com/seekai-786/medi_bot_customgpt
- Owner: SeekAI-786
- License: apache-2.0
- Created: 2024-12-02T06:43:59.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-12-12T18:37:43.000Z (24 days ago)
- Last Synced: 2024-12-12T18:37:52.367Z (24 days ago)
- Language: Jupyter Notebook
- Size: 23.4 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
---
# AI Chat Interface with Hugging Face Fine-Tuned Models on Medical Datasets
This project provides an interactive web application built with **Streamlit**, allowing users to chat with AI models hosted on **Hugging Face**. The interface offers a **demo version** of the AI chat functionality, showcasing how these models can be fine tuned to generate responses to medical and mental health-related queries.
---
## 🚀 Features
- **Model Selection**: Choose from a range of **pre-trained AI models** hosted on Hugging Face fine tune those models for medical and mental health-related tasks.
- **Dynamic Response Generation**: Send prompts to selected models and receive AI-generated responses.
- **Conversation History**: Maintain a log of all conversations within a session.
- **Download Capability**: Download individual prompts and responses as `.txt` files.
- **Responsive UI**: A clean and intuitive interface for seamless interaction.
- **Error Handling**: Handles API request errors gracefully, providing user-friendly error messages.
---
## 🛠️ Tech Stack
- **Frontend**: Streamlit
- **APIs**: Hugging Face Inference API
- **Languages**: Python
- **Dependencies**:
- `streamlit`
- `huggingface_hub`
- `requests`
---
## 📦 Installation
### 1. Clone the Repository
```bash
git clone https://github.com/yourusername/ai-chat-interface.git
cd ai-chat-interface
```
### 2. Set Up a Virtual Environment
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
### 3. Install Dependencies
```bash
pip install -r requirements.txt
```
### 4. Set Up API Keys
- Create a `.env` file in the root directory and add your Hugging Face API key:
```
HF_API_KEY=
```
---
## ▶️ Usage
### 1. Run the Application
```bash
streamlit run app.py
```
### 2. Interact with the App
- **Select a Model**: Use the sidebar to choose your desired AI model.
- **Enter a Query**: Type your prompt into the input box and click "Generate Response."
- **View Responses**: Generated responses are displayed alongside the prompts.
- **Download Logs**: Save individual prompts and responses using the download buttons.
---
## 🎨 App Design
### Light Theme
- White background with light gray accents for text areas and containers.
- Clear contrast between components for a professional look.
---
## 📖 Hugging Face Models
Here are the **models** hosted on Hugging Face that are used in the demo:
1. **Llama-3.2-1B-Lora-Fine-Tune-FineTome**
Model URL: [Llama-3.2-1B-Lora-Fine-Tune-FineTome](https://huggingface.co/Muhammad7865253/llama-3.2-1B-Lora-Fine_Tune-FineTome)
- This model excels in handling **medical-related queries** and provides specialized responses for healthcare topics.
2. **Gemma-Mental-Health-Fine-Tune**
Model URL: [Gemma-Mental-Health-Fine-Tune](https://huggingface.co/Muhammad7865253/gemma-mental-health-fine-tune)
- This model is ideal for **mental health-related conversations**, offering insights, therapy suggestions, and emotional support.
3. **Qwen-1.5B-Medical-QA**
Model URL: [Qwen-1.5B-Medical-QA](https://huggingface.co/Muhammad7865253/qwen-1.5B-medical-QA)
- This model is designed for **medical question-answering** tasks, with high accuracy for healthcare-related inquiries.
---
## 🌐 Streamlit Interface
The web app for interacting with the models is available at:
[Streamlit App URL](https://medibotcustomgpt-eepnvsgmhzcrmzbiuwdgp4.streamlit.app/)
*Note*: Due to limited resources on Streamlit, the **fine-tuned models** could not be hosted directly on the platform. The app demonstrates how the models work via Hugging Face’s API, providing a similar experience.
---
## 🔧 Future Enhancements
- Add support for additional AI models.
- Implement More Fine Tuning for Better Accuracy.
- Provide advanced settings for customizing API parameters.
---
## 🤝 Contributing
Contributions are welcome! Feel free to submit a pull request or raise issues for improvements.
---
## 📜 License
This project is licensed under the MIT License. See the `LICENSE` file for details.
---
## 👤 Author
**Your Name**
- [GitHub](https://github.com/SeekAI-786)
- [LinkedIn]([Mohammad-Aun-Ali](https://www.linkedin.com/in/mohammad-aun-ali-705852293/)
---