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https://github.com/muhammadadilnaeem/medical-chatbot-assistant-using-llama2-and-huggingface-embeddings-and-pinecone-vector-db
Welcome to the Medical Chatbot Assistant project! This repository contains a powerful and efficient medical chatbot built using the LLaMA 2 model, Hugging Face embeddings, and Pinecone vector database. The chatbot is designed to assist users with medical inquiries, providing reliable and accurate responses.
https://github.com/muhammadadilnaeem/medical-chatbot-assistant-using-llama2-and-huggingface-embeddings-and-pinecone-vector-db
huggingface huggingface-models langchain llama2 pineconedb python
Last synced: about 13 hours ago
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Welcome to the Medical Chatbot Assistant project! This repository contains a powerful and efficient medical chatbot built using the LLaMA 2 model, Hugging Face embeddings, and Pinecone vector database. The chatbot is designed to assist users with medical inquiries, providing reliable and accurate responses.
- Host: GitHub
- URL: https://github.com/muhammadadilnaeem/medical-chatbot-assistant-using-llama2-and-huggingface-embeddings-and-pinecone-vector-db
- Owner: muhammadadilnaeem
- License: mit
- Created: 2024-08-08T16:19:54.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2024-09-06T05:10:36.000Z (22 days ago)
- Last Synced: 2024-09-23T18:31:57.994Z (4 days ago)
- Topics: huggingface, huggingface-models, langchain, llama2, pineconedb, python
- Language: Jupyter Notebook
- Homepage:
- Size: 10.4 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
---
# **🩺 Medical Chatbot Assistant using LLaMA 2, Hugging Face, and Pinecone**
Welcome to the **Medical Chatbot Assistant** project! This repository contains a powerful and efficient medical chatbot built using the LLaMA 2 model, Hugging Face embeddings, and Pinecone vector database. The chatbot is designed to assist users with medical inquiries, providing reliable and accurate responses.
https://github.com/user-attachments/assets/5f284cde-532f-4c96-9258-1b2760d254ee
https://github.com/user-attachments/assets/751fa823-1140-45a4-82b5-5181e8fabb69
## **🚀 Features**
- **LLaMA 2 Model Integration**: Powered by Meta's LLaMA 2 model, offering state-of-the-art conversational AI.
- **Hugging Face Embeddings**: Utilizes Hugging Face's embeddings for precise and context-aware responses.
- **Pinecone Vector Database**: Efficiently stores and retrieves embeddings, ensuring quick and relevant answers.
- **Scalable**: Easily scale the system to handle a growing number of users and queries.
- **Customizable**: Adapt the chatbot for various medical specializations or integrate it with other healthcare systems.
## **🛠️ Installation**
1. **Clone the repository:**
```bash
git clone https://github.com/muhammadadilnaeem/Medical-Chatbot-Assistant-Using-Llama2-and-HuggingFace-Embeddings-and-Pinecone-Vector-db.git
cd Medical-Chatbot-Assistant-Using-Llama2-and-HuggingFace-Embeddings-and-Pinecone-Vector-db
```
2. **Install dependencies:**
```bash
pip install -r requirements.txt
```
3. **Set up environment variables:**
Create a `.env` file in the root directory and add your API keys and configuration settings:
```env
HUGGINGFACE_API_KEY=your_huggingface_api_key
PINECONE_API_KEY=your_pinecone_api_key
```
4. **Run the application:**
```bash
python app.py
```
## **📚 Usage**
- **Ask Medical Questions**: The chatbot is trained to understand and respond to a wide range of medical queries. Simply type your question, and the bot will provide an accurate response.
- **Customize the Knowledge Base**: You can add or modify the medical data the chatbot uses by updating the embeddings stored in Pinecone.
## **🧠 How It Works**
1. **User Query**: The user inputs a medical question.
2. **Embeddings**: The question is converted into embeddings using Hugging Face models.
3. **Pinecone Retrieval**: The embeddings are matched against a database of medical knowledge stored in Pinecone.
4. **Response Generation**: The LLaMA 2 model generates a response based on the retrieved information.
## **🤖 Future Enhancements**
- **Multi-language Support**: Extend the chatbot to support multiple languages.
- **Voice Interface**: Integrate with speech-to-text and text-to-speech for a more interactive experience.
- **Integration with EHR Systems**: Connect the chatbot to Electronic Health Records (EHR) for personalized advice.
## **📄 License**
This project is licensed under the MIT License. See the [LICENSE](https://github.com/muhammadadilnaeem/Medical-Chatbot-Assistant-Using-Llama2-and-HuggingFace-Embeddings-and-Pinecone-Vector-db/blob/main/LICENSE) file for more details.
## **📧 Contact**
For any questions or inquiries, please reach out to me at [[email protected]]([email protected]).