MedIQ

Medical-Chatbot

Instructions to Run the Application:

STEP 1 - Create the CONDA environment

Creating Environment:

conda create -n mchatbot python=3.11 -y

Activating Environment:

conda activate mchatbot

STEP 2 - install the requirements

Installing all frameworks and libraries listed in requirements.txt:

pip install -r requirements.txt

Create a .env file in the root directory and add your Pinecone credentials as follows:

API Keys are not meant to be shared with others. As such, it is essential for it to not appear in code that will be publicly viewable on version control softwares. .env is already put inside the .gitignore file, so it is not tracked by Git.

PINECONE_API_KEY = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxx"

Download the Llama 2 LLM from the link below:

## Download the following model:

llama-2-7b-chat.ggmlv3.q4_0.bin


## From the following link:
https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/tree/main

The following command ensures vector embeddings are created and stored in Pincone (the Vector DB) for future retrieval.

# run the following command
python store_index.py

The following command will run the application, and you will be able to interact with MedIQ in the chatting UI.

# Finally run the following command
python app.py

Now,

open up localhost:

Tech Stack Used:

• Python
• LangChain
• Flask
• Meta Llama2 LLM
• Pinecone Vector DB
• Hugging Face