---
title: AI Life Coach
emoji: 🧘
colorFrom: purple
colorTo: blue
sdk: streamlit
sdk_version: "1.24.0"
app_file: app.py
pinned: false
---

# AI Life Coach 🧘

Your personal AI-powered life coaching assistant.

## Features

- Personalized life coaching conversations
- Redis-based conversation memory
- Multiple LLM provider support (Ollama, Hugging Face, OpenAI)
- Dynamic model selection
- Remote Ollama integration via ngrok

## How to Use

1. Select a user from the sidebar
2. Configure your Ollama connection (if using remote Ollama)
3. Choose your preferred model
4. Start chatting with your AI Life Coach!

## Requirements

All requirements are specified in `requirements.txt`. The app automatically handles:
- Streamlit UI
- FastAPI backend (for future expansion)
- Redis connection for persistent memory
- Multiple LLM integrations

## Environment Variables

Configure these in your Hugging Face Space secrets or local `.env` file:

- `OLLAMA_HOST`: Your Ollama server URL (default: ngrok URL)
- `LOCAL_MODEL_NAME`: Default model name (default: mistral)
- `HF_TOKEN`: Hugging Face API token (for Hugging Face models)
- `HF_API_ENDPOINT_URL`: Hugging Face inference API endpoint
- `USE_FALLBACK`: Whether to use fallback providers (true/false)
- `REDIS_HOST`: Redis server hostname (default: localhost)
- `REDIS_PORT`: Redis server port (default: 6379)
- `REDIS_USERNAME`: Redis username (optional)
- `REDIS_PASSWORD`: Redis password (optional)

## Architecture

This application consists of:
- Streamlit frontend (`app.py`)
- Core LLM abstraction (`core/llm.py`)
- Memory management (`core/memory.py`)
- Configuration management (`utils/config.py`)
- API endpoints (in `api/` directory for future expansion)

Built with Python, Streamlit, FastAPI, and Redis.