README.md

metadata

title: MedicalChatBot
emoji: 🔥
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 6.12.0
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Patient/Doctor Medication Management Chatbot

Domain

Medication Management

Setup Instructions

Prerequisites

• Python 3.14.4+
• Ollama
• Gradio

Installation

1. Install Ollama

    # Mac:
     brew install ollama 
    
    # Windows: Download from https://ollama.ai 
    
    # Linux:
    curl -fsSL https://ollama.com/install.sh | sh 
   

2. Download llama3.2:3b model:

   ollama pull llama3.2:3b
   

3. Install Python packages

      pip install ollama gradio
   

   Running

   python your_file.py
   

   Features

• Feature 1: Answer patient questions about medications and remembers history.

• Feature 2: Provide doctors with summaries of patient inquiries to help with medication management.

• Feature 3: Suggests prompts depending on the mode selected (different prompts for doctors and patients).

• Feature 4: Export conversation history for record-keeping or further analysis.

Technical Details

• Model: llama3.2:3b
• Framework: Ollama

Demo

[Link to video OR screenshots]

Known Limitations

Currently, both patient and doctor modes are on a shared user interface. This serves as a prototype to easily see how patients and healthcare professionals can leverage this tool to understand a patient's lived experience with their medication.

Additionally, the long-term memory of this tool is minimal. After several prompts, the chatbot will begin to respond with blanks because the context is overflowing.

Future Improvements

With more time, I would build out this interface to work as two independent applications. One for patients, and one for Healthcare professionals.

Use a more dynamic way of keeping the context of a patient's prompts, over multiple days, and without causing issues for the model. Local caching of patient's prompts in summarization form may allow a more concise version to be passed in as context. This would mean the doctor would get a more accurate idea of the patient's questions over a longer period of time.