https://github.com/abhroroy365/medical-chatbot
A Retrieval-Augmented Generation (RAG) based Medical Chatbot. With the base model as Llama2 from Meta, the Retrieval system uses a medical document as corpus to generate context-rich output.
https://github.com/abhroroy365/medical-chatbot
genai-chatbot generative-ai huggingface langchain llama2 natural-language-processing prompt-engineering retrieval-augmented-generation
Last synced: about 1 month ago
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A Retrieval-Augmented Generation (RAG) based Medical Chatbot. With the base model as Llama2 from Meta, the Retrieval system uses a medical document as corpus to generate context-rich output.
- Host: GitHub
- URL: https://github.com/abhroroy365/medical-chatbot
- Owner: abhroroy365
- License: apache-2.0
- Created: 2024-04-20T05:14:51.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2024-07-02T18:53:00.000Z (over 1 year ago)
- Last Synced: 2024-10-10T05:30:17.585Z (about 1 year ago)
- Topics: genai-chatbot, generative-ai, huggingface, langchain, llama2, natural-language-processing, prompt-engineering, retrieval-augmented-generation
- Language: Jupyter Notebook
- Homepage:
- Size: 9.66 MB
- Stars: 2
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Project Title
A Retrieval-Augmented Generation (RAG) based Medical Chatbot. With the base model as Llama2 from Meta, the Retrieval system uses a medical document as corpus to generate context-rich output.
## Model and dataset
* Model: llama-2, Download from [hugging face](https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main)
* Embeddings from [hugging face](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2)
* Dataset: Gale Encyclopedia of Medicine Vol. 2 (N-S).pdf [Link](https://www.academia.edu/32752835/The_GALE_ENCYCLOPEDIA_of_MEDICINE_SECOND_EDITION)
## Run Locally
Clone the project
```bash
git clone https://github.com/abhroroy365/Medical-Chatbot
```
Go to the project directory
```bash
cd Medical-Chatbot
```
Create virtual environment
```bash
python -m venv env
```
Install dependencies
```bash
pip install -r requirements.txt
```
Start the server
```bash
python app.py
```
## Links
[](https://www.linkedin.com/in/abhra-ray-chaudhuri-aba3081b5/)
[](https://www.linkedin.com/in/abhra-ray-chaudhuri-aba3081b5/)
## Screenshot
