https://github.com/rizwan2000rm/health-copilot
Your health co-pilot, feed your health data to the agent to get personalised lifestyle improvements for a better tomorrow
https://github.com/rizwan2000rm/health-copilot
agents ai healthcare hevy hevy-api llms mcp
Last synced: 2 months ago
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Your health co-pilot, feed your health data to the agent to get personalised lifestyle improvements for a better tomorrow
- Host: GitHub
- URL: https://github.com/rizwan2000rm/health-copilot
- Owner: rizwan2000rm
- Created: 2025-09-01T17:14:02.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-10-14T11:58:16.000Z (9 months ago)
- Last Synced: 2026-04-30T12:33:46.262Z (2 months ago)
- Topics: agents, ai, healthcare, hevy, hevy-api, llms, mcp
- Language: Python
- Homepage: https://drive.google.com/file/d/1BXxQBdg-OFj2EhvZ8n32th7-qB-_yt6f/view
- Size: 2.23 MB
- Stars: 4
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Agents: AGENTS.md
Awesome Lists containing this project
README
# Health Coach
Being fit and healthy is easy, and most of the time we make it too complicated that has to be, that is why I built this health coach. Health Coach helps you plan minimalistic workout routines (using Hevy as a workout tracking tool) it can also help you with sleep and steps planning.
My idea of fitness following the minimalism principle is as follows:
1. Simple Workout Routines - 45 mins strength training + 15 mins cardio
2. Sleep Optimization - 7-9 hours of sleep everyday with proper routine
3. Steps Tracking - Gradually building a habit of walking upto 10,000-12,000 steps per day
4. Nutrition (Coming Soon) - No calorie counting but focusing on better food choices. Grilled chicken over fried chicken, zero sugar drinks over sugary drinks etc
[Health Coach Demo](https://drive.google.com/file/d/1BXxQBdg-OFj2EhvZ8n32th7-qB-_yt6f/view)
## Features
- 📅 Weekly workout planning
- 🤖 AI-powered recommendations and coaching for workouts, sleep and steps
- 📚 Knowledge base with fitness minimalistic training research papers and guides
- 🏋️♂️ Hevy Workout Tracking and Management
## Project Overview
This project consists of following components:
1. **AI Fitness Coach Agent** (`agent/`) - The main application providing AI-powered fitness coaching
2. **Hevy MCP Server** (`hevy-mcp/`) - MCP server for integrating with Hevy workout tracking API
3. **Health Coach App** (`ui/`) - React Native application for interacting with the AI Fitness Coach Agent and Hevy MCP Server
4. **Chroma DB** (`chromadb/`) - Chroma DB for storing and querying embeddings of research content
## Prerequisites
- Python 3.13+ (for hevy-mcp) / Python 3.8+ (for agent)
- OpenAI Key or [Ollama](https://ollama.ai/) installed and running
- Hevy API key (for workout tracking features)
- [uv](https://github.com/astral-sh/uv) package manager (for hevy-mcp)
## Setup Instructions
### 1. Clone and Navigate to Project
```bash
git clone
cd health-copilot
```
### 2. Configure Environment Variables
Create a `.env` file in the `agent/` directory:
#### For Hevy API Integration
```bash
echo "HEVY_API_KEY=your_hevy_api_key_here" > agent/.env
```
#### For OpenAI Integration
```bash
echo "OPENAI_API_KEY=your_openai_api_key_here" > agent/.env
```
### 3. Set Up Hevy MCP Server
```bash
cd hevy-mcp
# Install dependencies using uv
uv sync
```
### 4. Set Up AI Fitness Coach Agent
The agent uses a virtual environment (`.venv` is already present):
```bash
cd agent
# Activate the virtual environment
source .venv/bin/activate
# Install dependencies
pip install -r requirements.txt
```
## Running the Application
### Run AI Fitness Coach
```bash
# Navigate to agent directory
cd agent
# Activate virtual environment
source .venv/bin/activate
# Run the main application
uvicorn main:app --host 0.0.0.0 --port 8000
```
## Usage
#### Standalone Hevy MCP Integration
```json
{
"mcpServers": {
"hevy": {
"command": "/path/to/uv",
"args": [
"--directory",
"/path/to/health-copilot/hevy-mcp/",
"run",
"app.py"
],
"env": {
"HEVY_API_KEY": "your_hevy_api_key_here"
}
}
}
}
```
#### Using React Native Client:
```bash
# Navigate to agent directory
cd ui
# Install dependencies
npm install
# Start the application
EXPO_PUBLIC_AGENT_URL=http://192.168.xxx.xx:8000 npm run start
```