This project automates the process of responding to patient meal picture queries for Curelink, which provides care for patients with conditions like PCOS, pregnancy, and preconception. The goal is to replace human effort in this process with AI-generated responses, ensuring they align with each patient's diet chart and health profile.
- Python: Data handling and interaction with the AI model.
- Anthropic Claude API: Used the
claude-3-5-sonnet-20240620
model to generate responses.
queries.json
: Sample patient queries, including their profile context, chat history, and ideal responses.app.py
: The Python script that processes the queries and generates AI-based responses.output.json
: The generated responses based on the queries.README.md
: This document providing an overview of the project.
- Input Parsing: The script loads and parses the patient queries from
queries.json
. - AI Response Generation: For each query, the script uses the
claude-3-5-sonnet-20240620
model to generate a response that matches the patient's diet chart and specific health conditions. - Output: The generated responses are saved in
output.json
in the required format.
- Ensure you have Python installed.
- Install the required packages:
pip install anthropic
- Run the script:
python app.py
- The responses will be saved in the
output.json
file.