Honest Journal - Personal Growth App

This repository is an app to a systematic approach to understanding life, making better decisions, and continuously improving. It represents my journey of personal growth and philosophical exploration.

Core Components

1. Journal

   • Thoughts: Capture thoughts based on questions that you create and challenge your assumptions, blind-spots and contradictions.
   • Memories: Free text entries about anecdotes, experiences and things you're thankful for and extract insights from them.
   • Learning: Capture your learnings from books, articles, videos, and podcasts and see how they connect to your life.

2. Review System

   • Challenge Beliefs: LLM-assisted questioning of your assumptions, blind-spots and contradictions.
   • Generate Insights: Generate unique perspectives on your thoughts based on your entries.
   • Summarize and Consolidate: Come back to a compacted version of your entries that you can consult and expand on.

3. Visualization and Analysis

   • Mood Tracking: Track your emotional state over time with data visualization.
   • Resource Library: Curated content on personal development and reflection techniques.
   • Integration with Other Tools: Connect with meditation apps, fitness trackers, etc.

Technical Stack

• Backend: FastAPI for API
• Frontend: Streamlit for interactive interfaces
• Infrastructure: GCP Cloud Run for containerized services
• Storage: SQLite for Reflexion Entries and Questions stored in GCP bucket
• Third Party APIs: OpenAI for LLM integration

Getting Started

1. Prerequisites

   • OpenAI API key
   • Bucket in GCP
   • GCP credentials

2. Configuration

You first need to create a .env file with the following variables:

OPENAI_API_KEY=your_openai_key
BUCKET_NAME=your_google_cloud_service_bucket
DATABASE_URL=your_sqlite_database_url

3. Local Development

   You can run the services locally using the following commands:

   # Install dependencies
   pip install -r backend/requirements.txt -r frontend/requirements.txt
   
   # Run services
   uvicorn backend/fastapi_app:app --reload --port 8000
   streamlit run frontend/main.py --server.port 8080

   You can also use docker compose to run the services

   docker compose up --build

4. Deployment

   • Automated deployment is configured via GitHub Actions
   • Workflow configuration is in .github/workflows/deploy.yml
   • Requires GCP credentials configured as repository secrets

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.