Bridge

This is a health logging app built with FastAPI that allows users to log symptoms, view historical data, and generate summaries for healthcare professionals using the Kindo API. The project utilizes SQLite for local data storage and LlamaIndex for symptom analysis.

Requirements

Python 3.10+
Pipenv for dependency management
SQLite for local database
Uvicorn for running FastAPI
Heroku CLI (for deployment)

Step 1: Clone the Repository

git@github.com:purcell3a/bridge.git

Step 2: Set Up Environment

Use Pipenv for managing dependencies

pipenv install

Activate Virtual Environment

pipenv shell

Step 3: Create a .env File

Create a .env file in the project root directory to store your environment variables

touch .env

Step 4: Initialize the SQLite Database

Make sure your database schema is set up. Run the following command to initialize your SQLite database

python3 models.py

Step 5: Run the Application

Use uvicorn to run the FastAPI app locally:

uvicorn main:app --reload

API Endpoints

User Management

Create User: POST /create-user

    Body: { "name": "John", "email": "john@example.com" }
    Response: { "status": "User created successfully", "name": "John", "email": "john@example.com" }

Get User: GET /get-user/{user_id}

    Response: { "id": 1, "name": "John", "email": "john@example.com" }

Symptom Logging

Log Symptom: POST /log-symptom

    Body: { "symptom": "headache", "user_id": 1 }
    Response: { "status": "Symptom logged successfully" }

Doctor Summary

Generate Summary: GET /generate-summary

Response: { "summary": "Generated summary from Kindo API" }

Built With

• procfile
• python