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finn
b96e0e0008 slimming before fastapi refactor 2026-01-02 22:10:13 -07:00
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.env.example
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# Daily Journal Prompt Generator - Environment Variables
# Copy this file to .env and fill in your values
# API Keys (required - at least one)
DEEPSEEK_API_KEY=your_deepseek_api_key_here
OPENAI_API_KEY=your_openai_api_key_here
# API Configuration
API_BASE_URL=https://api.deepseek.com
MODEL=deepseek-chat
# Application Settings
DEBUG=false
ENVIRONMENT=development
NODE_ENV=development
# Server Settings
HOST=0.0.0.0
PORT=8000
# CORS Settings (comma-separated list)
BACKEND_CORS_ORIGINS=http://localhost:3000,http://localhost:80
# Prompt Settings
MIN_PROMPT_LENGTH=500
MAX_PROMPT_LENGTH=1000
NUM_PROMPTS_PER_SESSION=6
CACHED_POOL_VOLUME=20
HISTORY_BUFFER_SIZE=60
FEEDBACK_HISTORY_SIZE=30
# File Paths
DATA_DIR=data
PROMPT_TEMPLATE_PATH=data/ds_prompt.txt
FEEDBACK_TEMPLATE_PATH=data/ds_feedback.txt
SETTINGS_CONFIG_PATH=data/settings.cfg
# Data File Names
PROMPTS_HISTORIC_FILE=prompts_historic.json
PROMPTS_POOL_FILE=prompts_pool.json
FEEDBACK_WORDS_FILE=feedback_words.json
FEEDBACK_HISTORIC_FILE=feedback_historic.json

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.gitignore vendored
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.env
venv
__pycache__
#historic_prompts.json
#pool_prompts.json
#feedback_words.json
journal_prompt_*

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AGENTS.md
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API_DOCUMENTATION.md
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# Daily Journal Prompt Generator - API Documentation
## Overview
The Daily Journal Prompt Generator API provides endpoints for generating, managing, and interacting with AI-powered journal writing prompts. The API is built with FastAPI and provides automatic OpenAPI documentation.
## Base URL
- Development: `http://localhost:8000`
- Production: `https://your-domain.com`
## API Version
All endpoints are prefixed with `/api/v1`
## Authentication
Currently, the API does not require authentication as it's designed for single-user use. Future versions may add authentication for multi-user support.
## Error Handling
All endpoints return appropriate HTTP status codes:
- `200`: Success
- `400`: Bad Request (validation errors)
- `404`: Resource Not Found
- `422`: Unprocessable Entity (request validation failed)
- `500`: Internal Server Error
Error responses follow this format:
```json
{
"error": {
"type": "ErrorType",
"message": "Human-readable error message",
"details": {}, // Optional additional details
"status_code": 400
}
}
```
## Endpoints
### Prompt Operations
#### 1. Draw Prompts from Pool
**GET** `/api/v1/prompts/draw`
Draw prompts from the existing pool without making API calls.
**Query Parameters:**
- `count` (optional, integer): Number of prompts to draw (default: 6)
**Response:**
```json
{
"prompts": [
"Write about a time when...",
"Imagine you could..."
],
"count": 2,
"remaining_in_pool": 18
}
```
#### 2. Fill Prompt Pool
**POST** `/api/v1/prompts/fill-pool`
Fill the prompt pool to target volume using AI.
**Response:**
```json
{
"added": 5,
"total_in_pool": 20,
"target_volume": 20
}
```
#### 3. Get Pool Statistics
**GET** `/api/v1/prompts/stats`
Get statistics about the prompt pool.
**Response:**
```json
{
"total_prompts": 15,
"prompts_per_session": 6,
"target_pool_size": 20,
"available_sessions": 2,
"needs_refill": true
}
```
#### 4. Get History Statistics
**GET** `/api/v1/prompts/history/stats`
Get statistics about prompt history.
**Response:**
```json
{
"total_prompts": 8,
"history_capacity": 60,
"available_slots": 52,
"is_full": false
}
```
#### 5. Get Prompt History
**GET** `/api/v1/prompts/history`
Get prompt history with optional limit.
**Query Parameters:**
- `limit` (optional, integer): Maximum number of history items to return
**Response:**
```json
[
{
"key": "prompt00",
"text": "Most recent prompt text...",
"position": 0
},
{
"key": "prompt01",
"text": "Previous prompt text...",
"position": 1
}
]
```
#### 6. Select Prompt (Add to History)
**POST** `/api/v1/prompts/select/{prompt_index}`
Select a prompt from drawn prompts to add to history.
**Path Parameters:**
- `prompt_index` (integer): Index of the prompt to select (0-based)
**Note:** This endpoint requires session management and is not fully implemented in the initial version.
### Feedback Operations
#### 7. Generate Theme Feedback Words
**GET** `/api/v1/feedback/generate`
Generate 6 theme feedback words using AI based on historic prompts.
**Response:**
```json
{
"theme_words": ["creativity", "reflection", "growth", "memory", "imagination", "emotion"],
"count": 6
}
```
#### 8. Rate Feedback Words
**POST** `/api/v1/feedback/rate`
Rate feedback words and update feedback system.
**Request Body:**
```json
{
"ratings": {
"creativity": 5,
"reflection": 6,
"growth": 4,
"memory": 3,
"imagination": 5,
"emotion": 4
}
}
```
**Response:**
```json
{
"feedback_words": [
{
"key": "feedback00",
"word": "creativity",
"weight": 5
},
// ... 5 more items
],
"added_to_history": true
}
```
#### 9. Get Current Feedback Words
**GET** `/api/v1/feedback/current`
Get current feedback words with weights.
**Response:**
```json
[
{
"key": "feedback00",
"word": "creativity",
"weight": 5
}
]
```
#### 10. Get Feedback History
**GET** `/api/v1/feedback/history`
Get feedback word history.
**Response:**
```json
[
{
"key": "feedback00",
"word": "creativity"
}
]
```
## Data Models
### PromptResponse
```json
{
"key": "string", // e.g., "prompt00"
"text": "string", // Prompt text content
"position": "integer" // Position in history (0 = most recent)
}
```
### PoolStatsResponse
```json
{
"total_prompts": "integer",
"prompts_per_session": "integer",
"target_pool_size": "integer",
"available_sessions": "integer",
"needs_refill": "boolean"
}
```
### HistoryStatsResponse
```json
{
"total_prompts": "integer",
"history_capacity": "integer",
"available_slots": "integer",
"is_full": "boolean"
}
```
### FeedbackWord
```json
{
"key": "string", // e.g., "feedback00"
"word": "string", // Feedback word
"weight": "integer" // Weight from 0-6
}
```
## Configuration
### Environment Variables
| Variable | Description | Default |
|----------|-------------|---------|
| `DEEPSEEK_API_KEY` | DeepSeek API key | (required) |
| `OPENAI_API_KEY` | OpenAI API key | (optional) |
| `API_BASE_URL` | API base URL | `https://api.deepseek.com` |
| `MODEL` | AI model to use | `deepseek-chat` |
| `DEBUG` | Debug mode | `false` |
| `ENVIRONMENT` | Environment | `development` |
| `HOST` | Server host | `0.0.0.0` |
| `PORT` | Server port | `8000` |
| `MIN_PROMPT_LENGTH` | Minimum prompt length | `500` |
| `MAX_PROMPT_LENGTH` | Maximum prompt length | `1000` |
| `NUM_PROMPTS_PER_SESSION` | Prompts per session | `6` |
| `CACHED_POOL_VOLUME` | Target pool size | `20` |
| `HISTORY_BUFFER_SIZE` | History capacity | `60` |
| `FEEDBACK_HISTORY_SIZE` | Feedback history capacity | `30` |
### File Structure
```
data/
├── prompts_historic.json # Historic prompts (cyclic buffer)
├── prompts_pool.json # Prompt pool
├── feedback_words.json # Current feedback words with weights
├── feedback_historic.json # Historic feedback words
├── ds_prompt.txt # Prompt generation template
├── ds_feedback.txt # Feedback analysis template
└── settings.cfg # Application settings
```
## Running the API
### Development
```bash
cd backend
uvicorn main:app --reload
```
### Production
```bash
cd backend
uvicorn main:app --host 0.0.0.0 --port 8000
```
### Docker
```bash
docker-compose up --build
```
## Interactive Documentation
FastAPI provides automatic interactive documentation:
- Swagger UI: `http://localhost:8000/docs`
- ReDoc: `http://localhost:8000/redoc`
## Rate Limiting
Currently, the API does not implement rate limiting. Consider implementing rate limiting in production if needed.
## CORS
CORS is configured to allow requests from:
- `http://localhost:3000` (frontend dev server)
- `http://localhost:80` (frontend production)
Additional origins can be configured via the `BACKEND_CORS_ORIGINS` environment variable.
## Health Check
**GET** `/health`
Returns:
```json
{
"status": "healthy",
"service": "daily-journal-prompt-api"
}
```
## Root Endpoint
**GET** `/`
Returns API information:
```json
{
"name": "Daily Journal Prompt Generator API",
"version": "1.0.0",
"description": "API for generating and managing journal writing prompts",
"docs": "/docs",
"health": "/health"
}
```
## Future Enhancements
1. **Authentication**: Add JWT or session-based authentication
2. **Rate Limiting**: Implement request rate limiting
3. **WebSocket Support**: Real-time prompt generation updates
4. **Export Functionality**: Export prompts to PDF/Markdown
5. **Prompt Customization**: User-defined prompt templates
6. **Multi-language Support**: Generate prompts in different languages
7. **Analytics**: Track prompt usage and user engagement
8. **Social Features**: Share prompts, community prompts

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README.md
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# Daily Journal Prompt Generator - Web Application
# Daily Journal Prompt Generator
A modern web application for generating AI-powered journal writing prompts, refactored from a CLI tool to a full web stack with FastAPI backend and Astro frontend.
A Python tool that uses OpenAI-compatible AI endpoints to generate creative writing prompts for daily journaling. The tool maintains awareness of previous prompts to minimize repetition while providing diverse, thought-provoking topics for journal writing.
## ✨ Features
- **AI-Powered Prompt Generation**: Uses DeepSeek/OpenAI API to generate creative writing prompts
- **Smart History System**: 60-prompt cyclic buffer to avoid repetition and steer themes
- **Prompt Pool Management**: Caches prompts for offline use with automatic refilling
- **Theme Feedback System**: AI analyzes your preferences to improve future prompts
- **Modern Web Interface**: Responsive design with intuitive UI
- **RESTful API**: Fully documented API for programmatic access
- **Docker Support**: Easy deployment with Docker and Docker Compose
- **AI-Powered Prompt Generation**: Uses OpenAI-compatible APIs to generate creative writing prompts
- **Smart Repetition Avoidance**: Maintains history of the last 60 prompts to minimize thematic overlap
- **Multiple Options**: Generates 6 different prompt options for each session
- **Diverse Topics**: Covers a wide range of themes including memories, creativity, self-reflection, and imagination
- **Simple Configuration**: Easy setup with environment variables for API keys
- **JSON-Based History**: Stores prompt history in a structured JSON format for easy management
## 🏗️ Architecture
## 📋 Prerequisites
### Backend (FastAPI)
- **Framework**: FastAPI with async/await support
- **API Documentation**: Automatic OpenAPI/Swagger documentation
- **Data Persistence**: JSON file storage with async file operations
- **Services**: Modular architecture with clear separation of concerns
- **Validation**: Pydantic models for request/response validation
- **Error Handling**: Comprehensive error handling with custom exceptions
- Python 3.7+
- An API key from an OpenAI-compatible service (DeepSeek, OpenAI, etc.)
- Basic knowledge of Python and command line usage
### Frontend (Astro + React)
- **Framework**: Astro with React components for interactivity
- **Styling**: Custom CSS with modern design system
- **Responsive Design**: Mobile-first responsive layout
- **API Integration**: Proxy configuration for seamless backend communication
- **Component Architecture**: Reusable React components
## 🚀 Installation & Setup
### Infrastructure
- **Docker**: Multi-container setup with development and production configurations
- **Docker Compose**: Orchestration for local development
- **Nginx**: Reverse proxy for frontend serving
- **Health Checks**: Container health monitoring
1. **Clone the repository**:
```bash
git clone <repository-url>
cd daily-journal-prompt
```
2. **Set up a Python virtual environment (recommended)**:
```bash
# Create a virtual environment
python -m venv venv
# Activate the virtual environment
# On Linux/macOS:
source venv/bin/activate
# On Windows:
# venv\Scripts\activate
```
3. **Set up environment variables**:
```bash
cp example.env .env
```
Edit the `.env` file and add your API key:
```env
# DeepSeek
DEEPSEEK_API_KEY="sk-your-actual-api-key-here"
# Or for OpenAI
# OPENAI_API_KEY="sk-your-openai-api-key"
```
4. **Install required Python packages**:
```bash
pip install -r requirements.txt
```
## 📁 Project Structure
```
daily-journal-prompt/
├── backend/ # FastAPI backend
│ ├── app/
│ │ ├── api/v1/ # API endpoints
│ │ ├── core/ # Configuration, logging, exceptions
│ │ ├── models/ # Pydantic models
│ │ └── services/ # Business logic services
│ ├── main.py # FastAPI application entry point
│ └── requirements.txt # Python dependencies
├── frontend/ # Astro frontend
│ ├── src/
│ │ ├── components/ # React components
│ │ ├── layouts/ # Layout components
│ │ ├── pages/ # Astro pages
│ │ └── styles/ # CSS styles
│ ├── astro.config.mjs # Astro configuration
│ └── package.json # Node.js dependencies
├── data/ # Data storage (mounted volume)
│ ├── prompts_historic.json # Historic prompts
│ ├── prompts_pool.json # Prompt pool
│ ├── feedback_words.json # Feedback words with weights
│ ├── feedback_historic.json # Historic feedback
│ ├── ds_prompt.txt # Prompt template
│ ├── ds_feedback.txt # Feedback template
│ └── settings.cfg # Application settings
├── docker-compose.yml # Docker Compose configuration
├── backend/Dockerfile # Backend Dockerfile
├── frontend/Dockerfile # Frontend Dockerfile
├── .env.example # Environment variables template
├── API_DOCUMENTATION.md # API documentation
├── AGENTS.md # Project planning and architecture
└── README.md # This file
├── README.md # This documentation
├── generate_prompts.py # Main Python script with rich interface
├── run.sh # Convenience bash script
├── test_project.py # Test suite for the project
├── requirements.txt # Python dependencies
├── ds_prompt.txt # AI prompt template for generating journal prompts
├── historic_prompts.json # History of previous 60 prompts (JSON format)
├── pool_prompts.json # Pool of available prompts for selection (JSON format)
├── example.env # Example environment configuration
├── .env # Your actual environment configuration (gitignored)
├── settings.cfg # Configuration file for prompt settings and pool size
└── .gitignore # Git ignore rules
```
## 🚀 Quick Start
### File Descriptions
### Prerequisites
- Python 3.11+
- Node.js 18+
- Docker and Docker Compose (optional)
- API key from DeepSeek or OpenAI
- **generate_prompts.py**: Main Python script with interactive mode, rich formatting, and full features
- **run.sh**: Convenience bash script for easy execution
- **test_project.py**: Test suite to verify project setup
- **requirements.txt**: Python dependencies (openai, python-dotenv, rich)
- **ds_prompt.txt**: The core prompt template that instructs the AI to generate new journal prompts
- **historic_prompts.json**: JSON array containing the last 60 generated prompts (cyclic buffer)
- **pool_prompts.json**: JSON array containing the pool of available prompts for selection
- **example.env**: Template for your environment configuration
- **.env**: Your actual environment variables (not tracked in git for security)
- **settings.cfg**: Configuration file for prompt settings (length, count) and pool size
### Option 1: Docker (Recommended)
## 🎯 Quick Start
1. **Clone and setup**
### Using the Bash Script (Recommended)
```bash
git clone <repository-url>
cd daily-journal-prompt
cp .env.example .env
# Make the script executable
chmod +x run.sh
# Generate prompts (default)
./run.sh
# Interactive mode with rich interface
./run.sh --interactive
# Show statistics
./run.sh --stats
# Show help
./run.sh --help
```
2. **Edit .env file**
### Using Python Directly
```bash
# Add your API key
DEEPSEEK_API_KEY=your_api_key_here
# or
OPENAI_API_KEY=your_api_key_here
```
# First, activate your virtual environment (if using one)
# On Linux/macOS:
# source venv/bin/activate
# On Windows:
# venv\Scripts\activate
3. **Start with Docker Compose**
```bash
docker-compose up --build
```
4. **Access the application**
- Frontend: http://localhost:3000
- Backend API: http://localhost:8000
- API Documentation: http://localhost:8000/docs
### Option 2: Manual Setup
#### Backend Setup
```bash
cd backend
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Set environment variables
export DEEPSEEK_API_KEY=your_api_key_here
# or
export OPENAI_API_KEY=your_api_key_here
# Generate prompts (default)
python generate_prompts.py
# Interactive mode
python generate_prompts.py --interactive
# Show statistics
python generate_prompts.py --stats
# Run the backend
uvicorn main:app --reload
```
#### Frontend Setup
### Testing Your Setup
```bash
cd frontend
npm install
npm run dev
# Run the test suite
python test_project.py
```
## 📚 API Usage
## 🔧 Usage
The API provides comprehensive endpoints for prompt management:
### New Pool-Based System
The system now uses a two-step process:
1. **Fill the Prompt Pool**: Generate prompts using AI and add them to the pool
2. **Draw from Pool**: Select prompts from the pool for journaling sessions
### Command Line Options
### Basic Operations
```bash
# Draw prompts from pool
curl http://localhost:8000/api/v1/prompts/draw
# Default: Draw prompts from pool (no API call)
python generate_prompts.py
# Fill prompt pool
curl -X POST http://localhost:8000/api/v1/prompts/fill-pool
# Interactive mode with menu
python generate_prompts.py --interactive
# Get statistics
curl http://localhost:8000/api/v1/prompts/stats
# Fill the prompt pool using AI (makes API call)
python generate_prompts.py --fill-pool
# Show pool statistics
python generate_prompts.py --pool-stats
# Show history statistics
python generate_prompts.py --stats
# Help
python generate_prompts.py --help
```
### Interactive Documentation
Access the automatic API documentation at:
- Swagger UI: http://localhost:8000/docs
- ReDoc: http://localhost:8000/redoc
### Interactive Mode Options
## 🔧 Configuration
1. **Draw prompts from pool (no API call)**: Displays and consumes prompts from the pool file
2. **Fill prompt pool using API**: Generates new prompts using AI and adds them to pool
3. **View pool statistics**: Shows pool size, target size, and available sessions
4. **View history statistics**: Shows historic prompt count and capacity
5. **Exit**: Quit the program
### Prompt Generation Process
1. User chooses to fill the prompt pool.
2. The system reads the template from `ds_prompt.txt`
3. It loads the previous 60 prompts from the fixed length cyclic buffer `historic_prompts.json`
4. The AI generates some number of new prompts, attempting to minimize repetition
5. The new prompts are used to fill the prompt pool to the `settings.cfg` configured value.
### Prompt Selection Process
1. A `settings.cfg` configurable number of prompts are drawn from the prompt pool and displayed to the user.
2. User selects one prompt for his/her journal writing session, which is added to the `historic_prompts.json` cyclic buffer.
3. All prompts which were displayed are removed from the prompt pool permanently.
## 📝 Prompt Examples
The tool generates prompts like these (from `historic_prompts.json`):
- **Memory-based**: "Describe a memory you have that is tied to a specific smell..."
- **Creative Writing**: "Invent a mythological creature for a modern urban setting..."
- **Self-Reflection**: "Write a dialogue between two aspects of yourself..."
- **Observational**: "Describe your current emotional state as a weather system..."
Each prompt is designed to inspire 1-2 pages of journal writing and ranges from 500-1000 characters.
## ⚙️ Configuration
### Environment Variables
Create a `.env` file based on `.env.example`:
Create a `.env` file with your API configuration:
```env
# Required: At least one API key
DEEPSEEK_API_KEY=your_deepseek_api_key
OPENAI_API_KEY=your_openai_api_key
# For DeepSeek
DEEPSEEK_API_KEY="sk-your-deepseek-api-key"
# Optional: Customize behavior
API_BASE_URL=https://api.deepseek.com
MODEL=deepseek-chat
DEBUG=false
CACHED_POOL_VOLUME=20
NUM_PROMPTS_PER_SESSION=6
# For OpenAI
# OPENAI_API_KEY="sk-your-openai-api-key"
# Optional: Custom API base URL
# API_BASE_URL="https://api.deepseek.com"
```
### Application Settings
Edit `data/settings.cfg` to customize:
- Prompt length constraints
- Number of prompts per session
- Pool volume targets
### Prompt Template Customization
## 🐛 Troubleshooting
You can modify `ds_prompt.txt` to change the prompt generation parameters:
### Docker Permission Issues
If you encounter permission errors when running Docker containers:
- Number of prompts generated (default: 6)
- Prompt length requirements (default: 500-1000 characters)
- Specific themes or constraints
- Output format specifications
1. **Check directory permissions**:
```bash
ls -la data/
```
The `data/` directory should be readable/writable by your user (UID 1000 typically).
## 🔄 Maintaining Prompt History
2. **Fix permissions** (if needed):
```bash
chmod 700 data/
chown -R $(id -u):$(id -g) data/
```
The `historic_prompts.json` file maintains a rolling history of the last 60 prompts. This helps:
3. **Verify Docker user matches host user**:
The Dockerfile creates a user with UID 1000. If your host user has a different UID:
```bash
# Check your UID
id -u
# Update Dockerfile to match your UID
# Change: RUN useradd -m -u 1000 appuser
# To: RUN useradd -m -u YOUR_UID appuser
```
### npm Build Errors
If you see `npm ci` errors:
- The Dockerfile uses `npm install` instead of `npm ci` for development
- For production, generate a `package-lock.json` file first:
```bash
cd frontend
npm install
```
### API Connection Issues
If the backend can't connect to AI APIs:
1. Verify your API key is set in `.env`
2. Check network connectivity
3. Ensure the API service is available
## 🧪 Testing
Run the backend tests:
```bash
python test_backend.py
```
## 🐳 Docker Development
### Development Mode
```bash
# Hot reload for both backend and frontend
docker-compose up --build
# View logs
docker-compose logs -f
# Stop services
docker-compose down
```
### Useful Commands
```bash
# Rebuild specific service
docker-compose build backend
# Run single service
docker-compose up backend
# Execute commands in container
docker-compose exec backend python -m pytest
```
## 🔄 Migration from CLI
The web application maintains full compatibility with the original CLI data format:
1. **Data Files**: Existing JSON files are automatically used
2. **Templates**: Same prompt and feedback templates
3. **Settings**: Compatible settings.cfg format
4. **Functionality**: All CLI features available via API
## 📊 Features Comparison
| Feature | CLI Version | Web Version |
|---------|------------|-------------|
| Prompt Generation | ✅ | ✅ |
| Prompt Pool | ✅ | ✅ |
| History Management | ✅ | ✅ |
| Theme Feedback | ✅ | ✅ |
| Web Interface | ❌ | ✅ |
| REST API | ❌ | ✅ |
| Docker Support | ❌ | ✅ |
| Multi-user Ready | ❌ | ✅ (future) |
| Mobile Responsive | ❌ | ✅ |
## 🛠️ Development
### Backend Development
```bash
cd backend
# Install development dependencies
pip install -r requirements.txt
# Run with hot reload
uvicorn main:app --reload --host 0.0.0.0 --port 8000
# Run tests
python test_backend.py
```
### Frontend Development
```bash
cd frontend
# Install dependencies
npm install
# Run development server
npm run dev
# Build for production
npm run build
```
### Code Structure
- **Backend**: Follows FastAPI best practices with dependency injection
- **Frontend**: Uses Astro islands architecture with React components
- **Services**: Async/await pattern for I/O operations
- **Error Handling**: Comprehensive error handling at all levels
1. **Avoid repetition**: The AI references previous prompts to generate new, diverse topics
2. **Track usage**: See what types of prompts have been generated
3. **Quality control**: Monitor the variety and quality of generated prompts
## 🤝 Contributing
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request
Contributions are welcome! Here are some ways you can contribute:
### Development Guidelines
- Follow PEP 8 for Python code
- Use TypeScript for React components when possible
- Write meaningful commit messages
- Update documentation for new features
- Add tests for new functionality
1. **Add new prompt templates** for different writing styles
2. **Improve the AI prompt engineering** for better results
3. **Add support for more AI providers**
4. **Create a CLI interface** for easier usage
5. **Add tests** to ensure reliability
## 📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
[Add appropriate license information here]
## 🙏 Acknowledgments
- Built with [FastAPI](https://fastapi.tiangolo.com/)
- Frontend with [Astro](https://astro.build/)
- AI integration with [OpenAI](https://openai.com/) and [DeepSeek](https://www.deepseek.com/)
- Icons from [Font Awesome](https://fontawesome.com/)
- Inspired by the need for consistent journaling practice
- Built with OpenAI-compatible AI services
- Community contributions welcome
## 📞 Support
## 🆘 Support
- **Issues**: Use GitHub Issues for bug reports and feature requests
- **Documentation**: Check `API_DOCUMENTATION.md` for API details
- **Examples**: See the test files for usage examples
## 🚀 Deployment
### Cloud Platforms
- **Render**: One-click deployment with Docker
- **Railway**: Easy deployment with environment management
- **Fly.io**: Global deployment with edge computing
- **AWS/GCP/Azure**: Traditional cloud deployment
### Deployment Steps
1. Set environment variables
2. Build Docker images
3. Configure database (if migrating from JSON)
4. Set up reverse proxy (nginx/caddy)
5. Configure SSL certificates
6. Set up monitoring and logging
---
**Happy Journaling! 📓✨**
For issues, questions, or suggestions:
1. Check the existing issues on GitHub
2. Create a new issue with detailed information
3. Provide examples of problematic prompts or errors

30
backend/Dockerfile
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@@ -1,30 +0,0 @@
FROM python:3.11-slim
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y \
gcc \
&& rm -rf /var/lib/apt/lists/*
# Copy requirements first for better caching
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy application code
COPY . .
# Create non-root user
RUN useradd -m -u 1000 appuser && chown -R appuser:appuser /app
USER appuser
# Expose port
EXPOSE 8000
# Health check
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')" || exit 1
# Run the application
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

15
backend/app/api/v1/api.py
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"""
API router for version 1 endpoints.
"""
from fastapi import APIRouter
from app.api.v1.endpoints import prompts, feedback
# Create main API router
api_router = APIRouter()
# Include endpoint routers
api_router.include_router(prompts.router, prefix="/prompts", tags=["prompts"])
api_router.include_router(feedback.router, prefix="/feedback", tags=["feedback"])

193
backend/app/api/v1/endpoints/feedback.py
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"""
Feedback-related API endpoints.
"""
from typing import List, Dict, Any
from fastapi import APIRouter, HTTPException, Depends, status
from pydantic import BaseModel
from app.services.prompt_service import PromptService
from app.models.prompt import FeedbackWord, RateFeedbackWordsRequest, RateFeedbackWordsResponse
# Create router
router = APIRouter()
# Response models
class GenerateFeedbackWordsResponse(BaseModel):
"""Response model for generating feedback words."""
theme_words: List[str]
count: int = 6
class FeedbackQueuedWordsResponse(BaseModel):
"""Response model for queued feedback words."""
queued_words: List[FeedbackWord]
count: int
class FeedbackActiveWordsResponse(BaseModel):
"""Response model for active feedback words."""
active_words: List[FeedbackWord]
count: int
class FeedbackHistoricResponse(BaseModel):
"""Response model for full feedback history."""
feedback_history: List[Dict[str, Any]]
count: int
# Service dependency
async def get_prompt_service() -> PromptService:
"""Dependency to get PromptService instance."""
return PromptService()
@router.get("/queued", response_model=FeedbackQueuedWordsResponse)
async def get_queued_feedback_words(
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Get queued feedback words (positions 0-5) for user weighting.
Returns:
List of queued feedback words with weights
"""
try:
# Get queued feedback words from PromptService
queued_feedback_items = await prompt_service.get_feedback_queued_words()
# Convert to FeedbackWord models
queued_words = []
for i, item in enumerate(queued_feedback_items):
key = list(item.keys())[0]
word = item[key]
weight = item.get("weight", 3) # Default weight is 3
queued_words.append(FeedbackWord(key=key, word=word, weight=weight))
return FeedbackQueuedWordsResponse(
queued_words=queued_words,
count=len(queued_words)
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error getting queued feedback words: {str(e)}"
)
@router.get("/active", response_model=FeedbackActiveWordsResponse)
async def get_active_feedback_words(
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Get active feedback words (positions 6-11) for prompt generation.
Returns:
List of active feedback words with weights
"""
try:
# Get active feedback words from PromptService
active_feedback_items = await prompt_service.get_feedback_active_words()
# Convert to FeedbackWord models
active_words = []
for i, item in enumerate(active_feedback_items):
key = list(item.keys())[0]
word = item[key]
weight = item.get("weight", 3) # Default weight is 3
active_words.append(FeedbackWord(key=key, word=word, weight=weight))
return FeedbackActiveWordsResponse(
active_words=active_words,
count=len(active_words)
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error getting active feedback words: {str(e)}"
)
@router.get("/generate", response_model=GenerateFeedbackWordsResponse)
async def generate_feedback_words(
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Generate 6 theme feedback words using AI.
Returns:
List of 6 theme words for feedback
"""
try:
theme_words = await prompt_service.generate_theme_feedback_words()
if len(theme_words) != 6:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Expected 6 theme words, got {len(theme_words)}"
)
return GenerateFeedbackWordsResponse(
theme_words=theme_words,
count=len(theme_words)
)
except ValueError as e:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=str(e)
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error generating feedback words: {str(e)}"
)
@router.post("/rate", response_model=RateFeedbackWordsResponse)
async def rate_feedback_words(
request: RateFeedbackWordsRequest,
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Rate feedback words and update feedback system.
Args:
request: Dictionary of word to rating (0-6)
Returns:
Updated feedback words
"""
try:
feedback_words = await prompt_service.update_feedback_words(request.ratings)
return RateFeedbackWordsResponse(
feedback_words=feedback_words,
added_to_history=True
)
except ValueError as e:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=str(e)
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error rating feedback words: {str(e)}"
)
@router.get("/history", response_model=FeedbackHistoricResponse)
async def get_feedback_history(
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Get full feedback word history.
Returns:
Full feedback history with weights
"""
try:
feedback_historic = await prompt_service.get_feedback_historic()
return FeedbackHistoricResponse(
feedback_history=feedback_historic,
count=len(feedback_historic)
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error getting feedback history: {str(e)}"
)

196
backend/app/api/v1/endpoints/prompts.py
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"""
Prompt-related API endpoints.
"""
from typing import List, Optional
from fastapi import APIRouter, HTTPException, Depends, status
from pydantic import BaseModel
from app.services.prompt_service import PromptService
from app.models.prompt import PromptResponse, PoolStatsResponse, HistoryStatsResponse
# Create router
router = APIRouter()
# Response models
class DrawPromptsResponse(BaseModel):
"""Response model for drawing prompts."""
prompts: List[str]
count: int
remaining_in_pool: int
class FillPoolResponse(BaseModel):
"""Response model for filling prompt pool."""
added: int
total_in_pool: int
target_volume: int
class SelectPromptRequest(BaseModel):
"""Request model for selecting a prompt."""
prompt_text: str
class SelectPromptResponse(BaseModel):
"""Response model for selecting a prompt."""
selected_prompt: str
position_in_history: str # e.g., "prompt00"
history_size: int
# Service dependency
async def get_prompt_service() -> PromptService:
"""Dependency to get PromptService instance."""
return PromptService()
@router.get("/draw", response_model=DrawPromptsResponse)
async def draw_prompts(
count: Optional[int] = None,
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Draw prompts from the pool.
Args:
count: Number of prompts to draw (defaults to settings.NUM_PROMPTS_PER_SESSION)
prompt_service: PromptService instance
Returns:
List of prompts drawn from pool
"""
try:
prompts = await prompt_service.draw_prompts_from_pool(count)
pool_size = prompt_service.get_pool_size()
return DrawPromptsResponse(
prompts=prompts,
count=len(prompts),
remaining_in_pool=pool_size
)
except ValueError as e:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=str(e)
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error drawing prompts: {str(e)}"
)
@router.post("/fill-pool", response_model=FillPoolResponse)
async def fill_prompt_pool(
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Fill the prompt pool to target volume using AI.
Returns:
Information about added prompts
"""
try:
added_count = await prompt_service.fill_pool_to_target()
pool_size = prompt_service.get_pool_size()
target_volume = prompt_service.get_target_volume()
return FillPoolResponse(
added=added_count,
total_in_pool=pool_size,
target_volume=target_volume
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error filling prompt pool: {str(e)}"
)
@router.get("/stats", response_model=PoolStatsResponse)
async def get_pool_stats(
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Get statistics about the prompt pool.
Returns:
Pool statistics
"""
try:
return await prompt_service.get_pool_stats()
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error getting pool stats: {str(e)}"
)
@router.get("/history/stats", response_model=HistoryStatsResponse)
async def get_history_stats(
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Get statistics about prompt history.
Returns:
History statistics
"""
try:
return await prompt_service.get_history_stats()
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error getting history stats: {str(e)}"
)
@router.get("/history", response_model=List[PromptResponse])
async def get_prompt_history(
limit: Optional[int] = None,
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Get prompt history.
Args:
limit: Maximum number of history items to return
Returns:
List of historical prompts
"""
try:
return await prompt_service.get_prompt_history(limit)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error getting prompt history: {str(e)}"
)
@router.post("/select", response_model=SelectPromptResponse)
async def select_prompt(
request: SelectPromptRequest,
prompt_service: PromptService = Depends(get_prompt_service)
):
"""
Select a prompt to add to history.
Adds the provided prompt text to the historic prompts cyclic buffer.
The prompt will be added at position 0 (most recent), shifting existing prompts down.
Args:
request: SelectPromptRequest containing the prompt text
Returns:
Confirmation of prompt selection with position in history
"""
try:
# Add the prompt to history
position_key = await prompt_service.add_prompt_to_history(request.prompt_text)
# Get updated history stats
history_stats = await prompt_service.get_history_stats()
return SelectPromptResponse(
selected_prompt=request.prompt_text,
position_in_history=position_key,
history_size=history_stats.total_prompts
)
except Exception as e:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=f"Error selecting prompt: {str(e)}"
)

76
backend/app/core/config.py
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@@ -1,76 +0,0 @@
"""
Configuration settings for the application.
Uses Pydantic settings management with environment variable support.
"""
import os
from typing import List, Optional
from pydantic_settings import BaseSettings
from pydantic import AnyHttpUrl, validator
class Settings(BaseSettings):
"""Application settings."""
# API Settings
API_V1_STR: str = "/api/v1"
PROJECT_NAME: str = "Daily Journal Prompt Generator API"
VERSION: str = "1.0.0"
DEBUG: bool = False
ENVIRONMENT: str = "development"
# Server Settings
HOST: str = "0.0.0.0"
PORT: int = 8000
# CORS Settings
BACKEND_CORS_ORIGINS: List[AnyHttpUrl] = [
"http://localhost:3000", # Frontend dev server
"http://localhost:80", # Frontend production
]
# API Keys
DEEPSEEK_API_KEY: Optional[str] = None
OPENAI_API_KEY: Optional[str] = None
API_BASE_URL: str = "https://api.deepseek.com"
MODEL: str = "deepseek-chat"
# Application Settings
MIN_PROMPT_LENGTH: int = 500
MAX_PROMPT_LENGTH: int = 1000
NUM_PROMPTS_PER_SESSION: int = 3
CACHED_POOL_VOLUME: int = 20
HISTORY_BUFFER_SIZE: int = 60
FEEDBACK_HISTORY_SIZE: int = 30
# File Paths (relative to project root)
DATA_DIR: str = "data"
PROMPT_TEMPLATE_PATH: str = "data/ds_prompt.txt"
FEEDBACK_TEMPLATE_PATH: str = "data/ds_feedback.txt"
SETTINGS_CONFIG_PATH: str = "data/settings.cfg"
# Data File Names (relative to DATA_DIR)
PROMPTS_HISTORIC_FILE: str = "prompts_historic.json"
PROMPTS_POOL_FILE: str = "prompts_pool.json"
FEEDBACK_HISTORIC_FILE: str = "feedback_historic.json"
# Note: feedback_words.json is deprecated and merged into feedback_historic.json
@validator("BACKEND_CORS_ORIGINS", pre=True)
def assemble_cors_origins(cls, v: str | List[str]) -> List[str] | str:
"""Parse CORS origins from string or list."""
if isinstance(v, str) and not v.startswith("["):
return [i.strip() for i in v.split(",")]
elif isinstance(v, (list, str)):
return v
raise ValueError(v)
class Config:
"""Pydantic configuration."""
env_file = ".env"
case_sensitive = True
extra = "ignore"
# Create global settings instance
settings = Settings()

130
backend/app/core/exception_handlers.py
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"""
Exception handlers for the application.
"""
import logging
from typing import Any, Dict
from fastapi import FastAPI, Request, status
from fastapi.responses import JSONResponse
from fastapi.exceptions import RequestValidationError
from pydantic import ValidationError as PydanticValidationError
from app.core.exceptions import DailyJournalPromptException
from app.core.logging import setup_logging
logger = setup_logging()
def setup_exception_handlers(app: FastAPI) -> None:
"""Set up exception handlers for the FastAPI application."""
@app.exception_handler(DailyJournalPromptException)
async def daily_journal_prompt_exception_handler(
request: Request,
exc: DailyJournalPromptException,
) -> JSONResponse:
"""Handle DailyJournalPromptException."""
logger.error(f"DailyJournalPromptException: {exc.detail}")
return JSONResponse(
status_code=exc.status_code,
content={
"error": {
"type": exc.__class__.__name__,
"message": str(exc.detail),
"status_code": exc.status_code,
}
},
)
@app.exception_handler(RequestValidationError)
async def request_validation_exception_handler(
request: Request,
exc: RequestValidationError,
) -> JSONResponse:
"""Handle request validation errors."""
logger.warning(f"RequestValidationError: {exc.errors()}")
return JSONResponse(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
content={
"error": {
"type": "ValidationError",
"message": "Invalid request data",
"details": exc.errors(),
"status_code": status.HTTP_422_UNPROCESSABLE_ENTITY,
}
},
)
@app.exception_handler(PydanticValidationError)
async def pydantic_validation_exception_handler(
request: Request,
exc: PydanticValidationError,
) -> JSONResponse:
"""Handle Pydantic validation errors."""
logger.warning(f"PydanticValidationError: {exc.errors()}")
return JSONResponse(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
content={
"error": {
"type": "ValidationError",
"message": "Invalid data format",
"details": exc.errors(),
"status_code": status.HTTP_422_UNPROCESSABLE_ENTITY,
}
},
)
@app.exception_handler(Exception)
async def generic_exception_handler(
request: Request,
exc: Exception,
) -> JSONResponse:
"""Handle all other exceptions."""
logger.exception(f"Unhandled exception: {exc}")
return JSONResponse(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
content={
"error": {
"type": "InternalServerError",
"message": "An unexpected error occurred",
"status_code": status.HTTP_500_INTERNAL_SERVER_ERROR,
}
},
)
@app.exception_handler(404)
async def not_found_exception_handler(
request: Request,
exc: Exception,
) -> JSONResponse:
"""Handle 404 Not Found errors."""
logger.warning(f"404 Not Found: {request.url}")
return JSONResponse(
status_code=status.HTTP_404_NOT_FOUND,
content={
"error": {
"type": "NotFoundError",
"message": f"Resource not found: {request.url}",
"status_code": status.HTTP_404_NOT_FOUND,
}
},
)
@app.exception_handler(405)
async def method_not_allowed_exception_handler(
request: Request,
exc: Exception,
) -> JSONResponse:
"""Handle 405 Method Not Allowed errors."""
logger.warning(f"405 Method Not Allowed: {request.method} {request.url}")
return JSONResponse(
status_code=status.HTTP_405_METHOD_NOT_ALLOWED,
content={
"error": {
"type": "MethodNotAllowedError",
"message": f"Method {request.method} not allowed for {request.url}",
"status_code": status.HTTP_405_METHOD_NOT_ALLOWED,
}
},
)

172
backend/app/core/exceptions.py
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@@ -1,172 +0,0 @@
"""
Custom exceptions for the application.
"""
from typing import Any, Dict, Optional
from fastapi import HTTPException, status
class DailyJournalPromptException(HTTPException):
"""Base exception for Daily Journal Prompt application."""
def __init__(
self,
status_code: int = status.HTTP_500_INTERNAL_SERVER_ERROR,
detail: Any = None,
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(status_code=status_code, detail=detail, headers=headers)
class ValidationError(DailyJournalPromptException):
"""Exception for validation errors."""
def __init__(
self,
detail: Any = "Validation error",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_400_BAD_REQUEST,
detail=detail,
headers=headers,
)
class NotFoundError(DailyJournalPromptException):
"""Exception for resource not found errors."""
def __init__(
self,
detail: Any = "Resource not found",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_404_NOT_FOUND,
detail=detail,
headers=headers,
)
class UnauthorizedError(DailyJournalPromptException):
"""Exception for unauthorized access errors."""
def __init__(
self,
detail: Any = "Unauthorized access",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_401_UNAUTHORIZED,
detail=detail,
headers=headers,
)
class ForbiddenError(DailyJournalPromptException):
"""Exception for forbidden access errors."""
def __init__(
self,
detail: Any = "Forbidden access",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_403_FORBIDDEN,
detail=detail,
headers=headers,
)
class AIServiceError(DailyJournalPromptException):
"""Exception for AI service errors."""
def __init__(
self,
detail: Any = "AI service error",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
detail=detail,
headers=headers,
)
class DataServiceError(DailyJournalPromptException):
"""Exception for data service errors."""
def __init__(
self,
detail: Any = "Data service error",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=detail,
headers=headers,
)
class ConfigurationError(DailyJournalPromptException):
"""Exception for configuration errors."""
def __init__(
self,
detail: Any = "Configuration error",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=detail,
headers=headers,
)
class PromptPoolEmptyError(DailyJournalPromptException):
"""Exception for empty prompt pool."""
def __init__(
self,
detail: Any = "Prompt pool is empty",
headers: Optional[Dict[str, str]] = None,
) -> None:
super().__init__(
status_code=status.HTTP_400_BAD_REQUEST,
detail=detail,
headers=headers,
)
class InsufficientPoolSizeError(DailyJournalPromptException):
"""Exception for insufficient pool size."""
def __init__(
self,
current_size: int,
requested: int,
headers: Optional[Dict[str, str]] = None,
) -> None:
detail = f"Pool only has {current_size} prompts, requested {requested}"
super().__init__(
status_code=status.HTTP_400_BAD_REQUEST,
detail=detail,
headers=headers,
)
class TemplateNotFoundError(DailyJournalPromptException):
"""Exception for missing template files."""
def __init__(
self,
template_name: str,
headers: Optional[Dict[str, str]] = None,
) -> None:
detail = f"Template not found: {template_name}"
super().__init__(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=detail,
headers=headers,
)

54
backend/app/core/logging.py
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@@ -1,54 +0,0 @@
"""
Logging configuration for the application.
"""
import logging
import sys
from typing import Optional
from app.core.config import settings
def setup_logging(
logger_name: str = "daily_journal_prompt",
log_level: Optional[str] = None,
) -> logging.Logger:
"""
Set up logging configuration.
Args:
logger_name: Name of the logger
log_level: Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
Returns:
Configured logger instance
"""
if log_level is None:
log_level = "DEBUG" if settings.DEBUG else "INFO"
# Create logger
logger = logging.getLogger(logger_name)
logger.setLevel(getattr(logging, log_level.upper()))
# Remove existing handlers to avoid duplicates
logger.handlers.clear()
# Create console handler
console_handler = logging.StreamHandler(sys.stdout)
console_handler.setLevel(getattr(logging, log_level.upper()))
# Create formatter
formatter = logging.Formatter(
"%(asctime)s - %(name)s - %(levelname)s - %(message)s",
datefmt="%Y-%m-%d %H:%M:%S"
)
console_handler.setFormatter(formatter)
# Add handler to logger
logger.addHandler(console_handler)
# Prevent propagation to root logger
logger.propagate = False
return logger

88
backend/app/models/prompt.py
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@@ -1,88 +0,0 @@
"""
Pydantic models for prompt-related data.
"""
from typing import List, Optional, Dict, Any
from pydantic import BaseModel, Field
class PromptResponse(BaseModel):
"""Response model for a single prompt."""
key: str = Field(..., description="Prompt key (e.g., 'prompt00')")
text: str = Field(..., description="Prompt text content")
position: int = Field(..., description="Position in history (0 = most recent)")
class Config:
"""Pydantic configuration."""
from_attributes = True
class PoolStatsResponse(BaseModel):
"""Response model for pool statistics."""
total_prompts: int = Field(..., description="Total prompts in pool")
prompts_per_session: int = Field(..., description="Prompts drawn per session")
target_pool_size: int = Field(..., description="Target pool volume")
available_sessions: int = Field(..., description="Available sessions in pool")
needs_refill: bool = Field(..., description="Whether pool needs refilling")
class HistoryStatsResponse(BaseModel):
"""Response model for history statistics."""
total_prompts: int = Field(..., description="Total prompts in history")
history_capacity: int = Field(..., description="Maximum history capacity")
available_slots: int = Field(..., description="Available slots in history")
is_full: bool = Field(..., description="Whether history is full")
class FeedbackWord(BaseModel):
"""Model for a feedback word with weight."""
key: str = Field(..., description="Feedback key (e.g., 'feedback00')")
word: str = Field(..., description="Feedback word")
weight: int = Field(..., ge=0, le=6, description="Weight from 0-6")
class FeedbackHistoryItem(BaseModel):
"""Model for a feedback history item (word only, no weight)."""
key: str = Field(..., description="Feedback key (e.g., 'feedback00')")
word: str = Field(..., description="Feedback word")
class GeneratePromptsRequest(BaseModel):
"""Request model for generating prompts."""
count: Optional[int] = Field(
None,
ge=1,
le=20,
description="Number of prompts to generate (defaults to settings)"
)
use_history: bool = Field(
True,
description="Whether to use historic prompts as context"
)
use_feedback: bool = Field(
True,
description="Whether to use feedback words as context"
)
class GeneratePromptsResponse(BaseModel):
"""Response model for generated prompts."""
prompts: List[str] = Field(..., description="Generated prompts")
count: int = Field(..., description="Number of prompts generated")
used_history: bool = Field(..., description="Whether history was used")
used_feedback: bool = Field(..., description="Whether feedback was used")
class RateFeedbackWordsRequest(BaseModel):
"""Request model for rating feedback words."""
ratings: Dict[str, int] = Field(
...,
description="Dictionary of word to rating (0-6)"
)
class RateFeedbackWordsResponse(BaseModel):
"""Response model for rated feedback words."""
feedback_words: List[FeedbackWord] = Field(..., description="Rated feedback words")
added_to_history: bool = Field(..., description="Whether added to history")

352
backend/app/services/ai_service.py
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@@ -1,352 +0,0 @@
"""
AI service for handling OpenAI/DeepSeek API calls.
"""
import json
from typing import List, Dict, Any, Optional
from openai import OpenAI, AsyncOpenAI
from app.core.config import settings
from app.core.logging import setup_logging
logger = setup_logging()
class AIService:
"""Service for handling AI API calls."""
def __init__(self):
"""Initialize AI service."""
api_key = settings.DEEPSEEK_API_KEY or settings.OPENAI_API_KEY
if not api_key:
raise ValueError("No API key found. Set DEEPSEEK_API_KEY or OPENAI_API_KEY in environment.")
self.client = AsyncOpenAI(
api_key=api_key,
base_url=settings.API_BASE_URL
)
self.model = settings.MODEL
def _clean_ai_response(self, response_content: str) -> str:
"""
Clean up AI response content to handle common formatting issues.
Handles:
1. Leading/trailing backticks (```json ... ```)
2. Leading "json" string on its own line
3. Extra whitespace and newlines
"""
content = response_content.strip()
# Remove leading/trailing backticks (```json ... ```)
if content.startswith('```'):
lines = content.split('\n')
if len(lines) > 1:
first_line = lines[0].strip()
if 'json' in first_line.lower() or first_line == '```':
content = '\n'.join(lines[1:])
# Remove trailing backticks if present
if content.endswith('```'):
content = content[:-3].rstrip()
# Remove leading "json" string on its own line (case-insensitive)
lines = content.split('\n')
if len(lines) > 0:
first_line = lines[0].strip().lower()
if first_line == 'json':
content = '\n'.join(lines[1:])
# Also handle the case where "json" might be at the beginning of the first line
content = content.strip()
if content.lower().startswith('json\n'):
content = content[4:].strip()
return content.strip()
async def generate_prompts(
self,
prompt_template: str,
historic_prompts: List[Dict[str, str]],
feedback_words: Optional[List[Dict[str, Any]]] = None,
count: Optional[int] = None,
min_length: Optional[int] = None,
max_length: Optional[int] = None
) -> List[str]:
"""
Generate journal prompts using AI.
Args:
prompt_template: Base prompt template
historic_prompts: List of historic prompts for context
feedback_words: List of feedback words with weights
count: Number of prompts to generate
min_length: Minimum prompt length
max_length: Maximum prompt length
Returns:
List of generated prompts
"""
if count is None:
count = settings.NUM_PROMPTS_PER_SESSION
if min_length is None:
min_length = settings.MIN_PROMPT_LENGTH
if max_length is None:
max_length = settings.MAX_PROMPT_LENGTH
# Prepare the full prompt
full_prompt = self._prepare_prompt(
prompt_template,
historic_prompts,
feedback_words,
count,
min_length,
max_length
)
logger.info(f"Generating {count} prompts with AI")
try:
# Call the AI API
response = await self.client.chat.completions.create(
model=self.model,
messages=[
{
"role": "system",
"content": "You are a creative writing assistant that generates journal prompts. Always respond with valid JSON."
},
{
"role": "user",
"content": full_prompt
}
],
temperature=0.7,
max_tokens=2000
)
response_content = response.choices[0].message.content
logger.debug(f"AI response received: {len(response_content)} characters")
# Parse the response
prompts = self._parse_prompt_response(response_content, count)
logger.info(f"Successfully parsed {len(prompts)} prompts from AI response")
return prompts
except Exception as e:
logger.error(f"Error calling AI API: {e}")
logger.debug(f"Full prompt sent to API: {full_prompt[:500]}...")
raise
def _prepare_prompt(
self,
template: str,
historic_prompts: List[Dict[str, str]],
feedback_words: Optional[List[Dict[str, Any]]],
count: int,
min_length: int,
max_length: int
) -> str:
"""Prepare the full prompt with all context."""
# Add the instruction for the specific number of prompts
prompt_instruction = f"Please generate {count} writing prompts, each between {min_length} and {max_length} characters."
# Start with template and instruction
full_prompt = f"{template}\n\n{prompt_instruction}"
# Add historic prompts if available
if historic_prompts:
historic_context = json.dumps(historic_prompts, indent=2)
full_prompt = f"{full_prompt}\n\nPrevious prompts:\n{historic_context}"
# Add feedback words if available
if feedback_words:
feedback_context = json.dumps(feedback_words, indent=2)
full_prompt = f"{full_prompt}\n\nFeedback words:\n{feedback_context}"
return full_prompt
def _parse_prompt_response(self, response_content: str, expected_count: int) -> List[str]:
"""Parse AI response to extract prompts."""
cleaned_content = self._clean_ai_response(response_content)
try:
data = json.loads(cleaned_content)
if isinstance(data, list):
if len(data) >= expected_count:
return data[:expected_count]
else:
logger.warning(f"AI returned {len(data)} prompts, expected {expected_count}")
return data
elif isinstance(data, dict):
logger.warning("AI returned dictionary format, expected list format")
prompts = []
for i in range(expected_count):
key = f"newprompt{i}"
if key in data:
prompts.append(data[key])
return prompts
else:
logger.warning(f"AI returned unexpected data type: {type(data)}")
return []
except json.JSONDecodeError:
logger.warning("AI response is not valid JSON, attempting to extract prompts...")
return self._extract_prompts_from_text(response_content, expected_count)
def _extract_prompts_from_text(self, text: str, expected_count: int) -> List[str]:
"""Extract prompts from plain text response."""
lines = text.strip().split('\n')
prompts = []
for line in lines[:expected_count]:
line = line.strip()
if line and len(line) > 50: # Reasonable minimum length for a prompt
prompts.append(line)
return prompts
async def generate_theme_feedback_words(
self,
feedback_template: str,
historic_prompts: List[Dict[str, str]],
queued_feedback_words: Optional[List[Dict[str, Any]]] = None,
historic_feedback_words: Optional[List[Dict[str, Any]]] = None
) -> List[str]:
"""
Generate theme feedback words using AI.
Args:
feedback_template: Feedback analysis template
historic_prompts: List of historic prompts for context
queued_feedback_words: Queued feedback words with weights (positions 0-5)
historic_feedback_words: Historic feedback words with weights (all positions)
Returns:
List of 6 theme words
"""
# Prepare the full prompt
full_prompt = self._prepare_feedback_prompt(
feedback_template,
historic_prompts,
queued_feedback_words,
historic_feedback_words
)
logger.info("Generating theme feedback words with AI")
try:
# Call the AI API
response = await self.client.chat.completions.create(
model=self.model,
messages=[
{
"role": "system",
"content": "You are a creative writing assistant that analyzes writing prompts. Always respond with valid JSON."
},
{
"role": "user",
"content": full_prompt
}
],
temperature=0.7,
max_tokens=1000
)
response_content = response.choices[0].message.content
logger.debug(f"AI feedback response received: {len(response_content)} characters")
# Parse the response
theme_words = self._parse_feedback_response(response_content)
logger.info(f"Successfully parsed {len(theme_words)} theme words from AI response")
if len(theme_words) != 6:
logger.warning(f"Expected 6 theme words, got {len(theme_words)}")
return theme_words
except Exception as e:
logger.error(f"Error calling AI API for feedback: {e}")
logger.debug(f"Full feedback prompt sent to API: {full_prompt[:500]}...")
raise
def _prepare_feedback_prompt(
self,
template: str,
historic_prompts: List[Dict[str, str]],
queued_feedback_words: Optional[List[Dict[str, Any]]],
historic_feedback_words: Optional[List[Dict[str, Any]]]
) -> str:
"""Prepare the full feedback prompt."""
if not historic_prompts:
raise ValueError("No historic prompts available for feedback analysis")
full_prompt = f"{template}\n\nPrevious prompts:\n{json.dumps(historic_prompts, indent=2)}"
# Add queued feedback words if available (these have user-adjusted weights)
if queued_feedback_words:
# Extract just the words and weights for clarity
queued_words_with_weights = []
for item in queued_feedback_words:
key = list(item.keys())[0]
word = item[key]
weight = item.get("weight", 3)
queued_words_with_weights.append({"word": word, "weight": weight})
feedback_context = json.dumps(queued_words_with_weights, indent=2)
full_prompt = f"{full_prompt}\n\nQueued feedback themes (with user-adjusted weights):\n{feedback_context}"
# Add historic feedback words if available (these may have weights too)
if historic_feedback_words:
# Extract just the words for historic context
historic_words = []
for item in historic_feedback_words:
key = list(item.keys())[0]
word = item[key]
historic_words.append(word)
feedback_historic_context = json.dumps(historic_words, indent=2)
full_prompt = f"{full_prompt}\n\nHistoric feedback themes (just words):\n{feedback_historic_context}"
return full_prompt
def _parse_feedback_response(self, response_content: str) -> List[str]:
"""Parse AI response to extract theme words."""
cleaned_content = self._clean_ai_response(response_content)
try:
data = json.loads(cleaned_content)
if isinstance(data, list):
theme_words = []
for word in data:
if isinstance(word, str):
theme_words.append(word.lower().strip())
else:
theme_words.append(str(word).lower().strip())
return theme_words
else:
logger.warning(f"AI returned unexpected data type for feedback: {type(data)}")
return []
except json.JSONDecodeError:
logger.warning("AI feedback response is not valid JSON, attempting to extract theme words...")
return self._extract_theme_words_from_text(response_content)
def _extract_theme_words_from_text(self, text: str) -> List[str]:
"""Extract theme words from plain text response."""
lines = text.strip().split('\n')
theme_words = []
for line in lines:
line = line.strip()
if line and len(line) < 50: # Theme words should be short
words = [w.lower().strip('.,;:!?()[]{}\"\'') for w in line.split()]
theme_words.extend(words)
if len(theme_words) >= 6:
break
return theme_words[:6]

191
backend/app/services/data_service.py
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@@ -1,191 +0,0 @@
"""
Data service for handling JSON file operations.
"""
import json
import os
import aiofiles
from typing import Any, List, Dict, Optional
from pathlib import Path
from app.core.config import settings
from app.core.logging import setup_logging
logger = setup_logging()
class DataService:
"""Service for handling data persistence in JSON files."""
def __init__(self):
"""Initialize data service."""
self.data_dir = Path(settings.DATA_DIR)
self.data_dir.mkdir(exist_ok=True)
def _get_file_path(self, filename: str) -> Path:
"""Get full path for a data file."""
return self.data_dir / filename
async def load_json(self, filename: str, default: Any = None) -> Any:
"""
Load JSON data from file.
Args:
filename: Name of the JSON file
default: Default value if file doesn't exist or is invalid
Returns:
Loaded data or default value
"""
file_path = self._get_file_path(filename)
if not file_path.exists():
logger.warning(f"File {filename} not found, returning default")
return default if default is not None else []
try:
async with aiofiles.open(file_path, 'r', encoding='utf-8') as f:
content = await f.read()
return json.loads(content)
except json.JSONDecodeError as e:
logger.error(f"Error decoding JSON from {filename}: {e}")
return default if default is not None else []
except Exception as e:
logger.error(f"Error loading {filename}: {e}")
return default if default is not None else []
async def save_json(self, filename: str, data: Any) -> bool:
"""
Save data to JSON file.
Args:
filename: Name of the JSON file
data: Data to save
Returns:
True if successful, False otherwise
"""
file_path = self._get_file_path(filename)
try:
# Create backup of existing file if it exists
if file_path.exists():
backup_path = file_path.with_suffix('.json.bak')
async with aiofiles.open(file_path, 'r', encoding='utf-8') as src:
async with aiofiles.open(backup_path, 'w', encoding='utf-8') as dst:
await dst.write(await src.read())
# Save new data
async with aiofiles.open(file_path, 'w', encoding='utf-8') as f:
await f.write(json.dumps(data, indent=2, ensure_ascii=False))
logger.info(f"Saved data to {filename}")
return True
except Exception as e:
logger.error(f"Error saving {filename}: {e}")
return False
async def load_prompts_historic(self) -> List[Dict[str, str]]:
"""Load historic prompts from JSON file."""
return await self.load_json(
settings.PROMPTS_HISTORIC_FILE,
default=[]
)
async def save_prompts_historic(self, prompts: List[Dict[str, str]]) -> bool:
"""Save historic prompts to JSON file."""
return await self.save_json(settings.PROMPTS_HISTORIC_FILE, prompts)
async def load_prompts_pool(self) -> List[str]:
"""Load prompt pool from JSON file."""
return await self.load_json(
settings.PROMPTS_POOL_FILE,
default=[]
)
async def save_prompts_pool(self, prompts: List[str]) -> bool:
"""Save prompt pool to JSON file."""
return await self.save_json(settings.PROMPTS_POOL_FILE, prompts)
async def load_feedback_historic(self) -> List[Dict[str, Any]]:
"""Load historic feedback words from JSON file."""
return await self.load_json(
settings.FEEDBACK_HISTORIC_FILE,
default=[]
)
async def save_feedback_historic(self, feedback_words: List[Dict[str, Any]]) -> bool:
"""Save historic feedback words to JSON file."""
return await self.save_json(settings.FEEDBACK_HISTORIC_FILE, feedback_words)
async def get_feedback_queued_words(self) -> List[Dict[str, Any]]:
"""Get queued feedback words (positions 0-5) for user weighting."""
feedback_historic = await self.load_feedback_historic()
return feedback_historic[:6] if len(feedback_historic) >= 6 else feedback_historic
async def get_feedback_active_words(self) -> List[Dict[str, Any]]:
"""Get active feedback words (positions 6-11) for prompt generation."""
feedback_historic = await self.load_feedback_historic()
if len(feedback_historic) >= 12:
return feedback_historic[6:12]
elif len(feedback_historic) > 6:
return feedback_historic[6:]
else:
return []
async def load_prompt_template(self) -> str:
"""Load prompt template from file."""
template_path = Path(settings.PROMPT_TEMPLATE_PATH)
if not template_path.exists():
logger.error(f"Prompt template not found at {template_path}")
return ""
try:
async with aiofiles.open(template_path, 'r', encoding='utf-8') as f:
return await f.read()
except Exception as e:
logger.error(f"Error loading prompt template: {e}")
return ""
async def load_feedback_template(self) -> str:
"""Load feedback template from file."""
template_path = Path(settings.FEEDBACK_TEMPLATE_PATH)
if not template_path.exists():
logger.error(f"Feedback template not found at {template_path}")
return ""
try:
async with aiofiles.open(template_path, 'r', encoding='utf-8') as f:
return await f.read()
except Exception as e:
logger.error(f"Error loading feedback template: {e}")
return ""
async def load_settings_config(self) -> Dict[str, Any]:
"""Load settings from config file."""
config_path = Path(settings.SETTINGS_CONFIG_PATH)
if not config_path.exists():
logger.warning(f"Settings config not found at {config_path}")
return {}
try:
import configparser
config = configparser.ConfigParser()
config.read(config_path)
settings_dict = {}
if 'prompts' in config:
prompts_section = config['prompts']
settings_dict['min_length'] = int(prompts_section.get('min_length', settings.MIN_PROMPT_LENGTH))
settings_dict['max_length'] = int(prompts_section.get('max_length', settings.MAX_PROMPT_LENGTH))
settings_dict['num_prompts'] = int(prompts_section.get('num_prompts', settings.NUM_PROMPTS_PER_SESSION))
if 'prefetch' in config:
prefetch_section = config['prefetch']
settings_dict['cached_pool_volume'] = int(prefetch_section.get('cached_pool_volume', settings.CACHED_POOL_VOLUME))
return settings_dict
except Exception as e:
logger.error(f"Error loading settings config: {e}")
return {}

470
backend/app/services/prompt_service.py
View File

@@ -1,470 +0,0 @@
"""
Main prompt service that orchestrates prompt generation and management.
"""
from typing import List, Dict, Any, Optional
from datetime import datetime
from app.core.config import settings
from app.core.logging import setup_logging
from app.services.data_service import DataService
from app.services.ai_service import AIService
from app.models.prompt import (
PromptResponse,
PoolStatsResponse,
HistoryStatsResponse,
FeedbackWord,
FeedbackHistoryItem
)
logger = setup_logging()
class PromptService:
"""Main service for prompt generation and management."""
def __init__(self):
"""Initialize prompt service with dependencies."""
self.data_service = DataService()
self.ai_service = AIService()
# Load settings from config file
self.settings_config = {}
# Cache for loaded data
self._prompts_historic_cache = None
self._prompts_pool_cache = None
self._feedback_words_cache = None
self._feedback_historic_cache = None
self._prompt_template_cache = None
self._feedback_template_cache = None
async def _load_settings_config(self):
"""Load settings from config file if not already loaded."""
if not self.settings_config:
self.settings_config = await self.data_service.load_settings_config()
async def _get_setting(self, key: str, default: Any) -> Any:
"""Get setting value, preferring config file over environment."""
await self._load_settings_config()
return self.settings_config.get(key, default)
# Data loading methods with caching
async def get_prompts_historic(self) -> List[Dict[str, str]]:
"""Get historic prompts with caching."""
if self._prompts_historic_cache is None:
self._prompts_historic_cache = await self.data_service.load_prompts_historic()
return self._prompts_historic_cache
async def get_prompts_pool(self) -> List[str]:
"""Get prompt pool with caching."""
if self._prompts_pool_cache is None:
self._prompts_pool_cache = await self.data_service.load_prompts_pool()
return self._prompts_pool_cache
async def get_feedback_historic(self) -> List[Dict[str, Any]]:
"""Get historic feedback words with caching."""
if self._feedback_historic_cache is None:
self._feedback_historic_cache = await self.data_service.load_feedback_historic()
return self._feedback_historic_cache
async def get_feedback_queued_words(self) -> List[Dict[str, Any]]:
"""Get queued feedback words (positions 0-5) for user weighting."""
feedback_historic = await self.get_feedback_historic()
return feedback_historic[:6] if len(feedback_historic) >= 6 else feedback_historic
async def get_feedback_active_words(self) -> List[Dict[str, Any]]:
"""Get active feedback words (positions 6-11) for prompt generation."""
feedback_historic = await self.get_feedback_historic()
if len(feedback_historic) >= 12:
return feedback_historic[6:12]
elif len(feedback_historic) > 6:
return feedback_historic[6:]
else:
return []
async def get_prompt_template(self) -> str:
"""Get prompt template with caching."""
if self._prompt_template_cache is None:
self._prompt_template_cache = await self.data_service.load_prompt_template()
return self._prompt_template_cache
async def get_feedback_template(self) -> str:
"""Get feedback template with caching."""
if self._feedback_template_cache is None:
self._feedback_template_cache = await self.data_service.load_feedback_template()
return self._feedback_template_cache
# Core prompt operations
async def draw_prompts_from_pool(self, count: Optional[int] = None) -> List[str]:
"""
Draw prompts from the pool.
Args:
count: Number of prompts to draw
Returns:
List of drawn prompts
"""
if count is None:
count = await self._get_setting('num_prompts', settings.NUM_PROMPTS_PER_SESSION)
pool = await self.get_prompts_pool()
if len(pool) < count:
raise ValueError(
f"Pool only has {len(pool)} prompts, requested {count}. "
f"Use fill-pool endpoint to add more prompts."
)
# Draw prompts from the beginning of the pool
drawn_prompts = pool[:count]
remaining_pool = pool[count:]
# Update cache and save
self._prompts_pool_cache = remaining_pool
await self.data_service.save_prompts_pool(remaining_pool)
logger.info(f"Drew {len(drawn_prompts)} prompts from pool, {len(remaining_pool)} remaining")
return drawn_prompts
async def fill_pool_to_target(self) -> int:
"""
Fill the prompt pool to target volume.
Returns:
Number of prompts added
"""
target_volume = await self._get_setting('cached_pool_volume', settings.CACHED_POOL_VOLUME)
current_pool = await self.get_prompts_pool()
current_size = len(current_pool)
if current_size >= target_volume:
logger.info(f"Pool already at target volume: {current_size}/{target_volume}")
return 0
prompts_needed = target_volume - current_size
logger.info(f"Generating {prompts_needed} prompts to fill pool")
# Generate prompts
new_prompts = await self.generate_prompts(
count=prompts_needed,
use_history=True,
use_feedback=True
)
if not new_prompts:
logger.error("Failed to generate prompts for pool")
return 0
# Add to pool
updated_pool = current_pool + new_prompts
self._prompts_pool_cache = updated_pool
await self.data_service.save_prompts_pool(updated_pool)
added_count = len(new_prompts)
logger.info(f"Added {added_count} prompts to pool, new size: {len(updated_pool)}")
return added_count
async def generate_prompts(
self,
count: Optional[int] = None,
use_history: bool = True,
use_feedback: bool = True
) -> List[str]:
"""
Generate new prompts using AI.
Args:
count: Number of prompts to generate
use_history: Whether to use historic prompts as context
use_feedback: Whether to use feedback words as context
Returns:
List of generated prompts
"""
if count is None:
count = await self._get_setting('num_prompts', settings.NUM_PROMPTS_PER_SESSION)
min_length = await self._get_setting('min_length', settings.MIN_PROMPT_LENGTH)
max_length = await self._get_setting('max_length', settings.MAX_PROMPT_LENGTH)
# Load templates and data
prompt_template = await self.get_prompt_template()
if not prompt_template:
raise ValueError("Prompt template not found")
historic_prompts = await self.get_prompts_historic() if use_history else []
feedback_words = await self.get_feedback_active_words() if use_feedback else None
# Generate prompts using AI
new_prompts = await self.ai_service.generate_prompts(
prompt_template=prompt_template,
historic_prompts=historic_prompts,
feedback_words=feedback_words,
count=count,
min_length=min_length,
max_length=max_length
)
return new_prompts
async def add_prompt_to_history(self, prompt_text: str) -> str:
"""
Add a prompt to the historic prompts cyclic buffer.
Args:
prompt_text: Prompt text to add
Returns:
Position key of the added prompt (e.g., "prompt00")
"""
historic_prompts = await self.get_prompts_historic()
# Create the new prompt object
new_prompt = {"prompt00": prompt_text}
# Shift all existing prompts down by one position
updated_prompts = [new_prompt]
# Add all existing prompts, shifting their numbers down by one
for i, prompt_dict in enumerate(historic_prompts):
if i >= settings.HISTORY_BUFFER_SIZE - 1: # Keep only HISTORY_BUFFER_SIZE prompts
break
# Get the prompt text
prompt_key = list(prompt_dict.keys())[0]
prompt_text = prompt_dict[prompt_key]
# Create prompt with new number (shifted down by one)
new_prompt_key = f"prompt{i+1:02d}"
updated_prompts.append({new_prompt_key: prompt_text})
# Update cache and save
self._prompts_historic_cache = updated_prompts
await self.data_service.save_prompts_historic(updated_prompts)
logger.info(f"Added prompt to history as prompt00, history size: {len(updated_prompts)}")
return "prompt00"
# Statistics methods
async def get_pool_stats(self) -> PoolStatsResponse:
"""Get statistics about the prompt pool."""
pool = await self.get_prompts_pool()
total_prompts = len(pool)
prompts_per_session = await self._get_setting('num_prompts', settings.NUM_PROMPTS_PER_SESSION)
target_pool_size = await self._get_setting('cached_pool_volume', settings.CACHED_POOL_VOLUME)
available_sessions = total_prompts // prompts_per_session if prompts_per_session > 0 else 0
needs_refill = total_prompts < target_pool_size
return PoolStatsResponse(
total_prompts=total_prompts,
prompts_per_session=prompts_per_session,
target_pool_size=target_pool_size,
available_sessions=available_sessions,
needs_refill=needs_refill
)
async def get_history_stats(self) -> HistoryStatsResponse:
"""Get statistics about prompt history."""
historic_prompts = await self.get_prompts_historic()
total_prompts = len(historic_prompts)
history_capacity = settings.HISTORY_BUFFER_SIZE
available_slots = max(0, history_capacity - total_prompts)
is_full = total_prompts >= history_capacity
return HistoryStatsResponse(
total_prompts=total_prompts,
history_capacity=history_capacity,
available_slots=available_slots,
is_full=is_full
)
async def get_prompt_history(self, limit: Optional[int] = None) -> List[PromptResponse]:
"""
Get prompt history.
Args:
limit: Maximum number of history items to return
Returns:
List of historical prompts
"""
historic_prompts = await self.get_prompts_historic()
if limit is not None:
historic_prompts = historic_prompts[:limit]
prompts = []
for i, prompt_dict in enumerate(historic_prompts):
prompt_key = list(prompt_dict.keys())[0]
prompt_text = prompt_dict[prompt_key]
prompts.append(PromptResponse(
key=prompt_key,
text=prompt_text,
position=i
))
return prompts
# Feedback operations
async def generate_theme_feedback_words(self) -> List[str]:
"""Generate 6 theme feedback words using AI."""
feedback_template = await self.get_feedback_template()
if not feedback_template:
raise ValueError("Feedback template not found")
historic_prompts = await self.get_prompts_historic()
if not historic_prompts:
raise ValueError("No historic prompts available for feedback analysis")
queued_feedback_words = await self.get_feedback_queued_words()
historic_feedback_words = await self.get_feedback_historic()
theme_words = await self.ai_service.generate_theme_feedback_words(
feedback_template=feedback_template,
historic_prompts=historic_prompts,
queued_feedback_words=queued_feedback_words,
historic_feedback_words=historic_feedback_words
)
return theme_words
async def update_feedback_words(self, ratings: Dict[str, int]) -> List[FeedbackWord]:
"""
Update feedback words with new ratings.
Args:
ratings: Dictionary of word to rating (0-6)
Returns:
Updated feedback words
"""
if len(ratings) != 6:
raise ValueError(f"Expected 6 ratings, got {len(ratings)}")
# Get current feedback historic
feedback_historic = await self.get_feedback_historic()
# Update weights for queued words (positions 0-5)
for i, (word, rating) in enumerate(ratings.items()):
if not 0 <= rating <= 6:
raise ValueError(f"Rating for '{word}' must be between 0 and 6, got {rating}")
if i < len(feedback_historic):
# Get the existing item and its key
existing_item = feedback_historic[i]
# Find the feedback key (not "weight")
existing_keys = [k for k in existing_item.keys() if k != "weight"]
if existing_keys:
existing_key = existing_keys[0]
else:
# Fallback to generating a key
existing_key = f"feedback{i:02d}"
# Update the item with existing key, same word, new weight
feedback_historic[i] = {
existing_key: word,
"weight": rating
}
else:
# If we don't have enough items, add a new one
feedback_key = f"feedback{i:02d}"
feedback_historic.append({
feedback_key: word,
"weight": rating
})
# Update cache and save
self._feedback_historic_cache = feedback_historic
await self.data_service.save_feedback_historic(feedback_historic)
# Generate new feedback words and insert at position 0
await self._generate_and_insert_new_feedback_words(feedback_historic)
# Get updated queued words for response
updated_queued_words = feedback_historic[:6] if len(feedback_historic) >= 6 else feedback_historic
# Convert to FeedbackWord models
feedback_words = []
for i, item in enumerate(updated_queued_words):
key = list(item.keys())[0]
word = item[key]
weight = item.get("weight", 3) # Default weight is 3
feedback_words.append(FeedbackWord(key=key, word=word, weight=weight))
logger.info(f"Updated feedback words with {len(feedback_words)} items")
return feedback_words
async def _generate_and_insert_new_feedback_words(self, feedback_historic: List[Dict[str, Any]]) -> None:
"""Generate new feedback words and insert at position 0."""
try:
# Generate 6 new feedback words
new_words = await self.generate_theme_feedback_words()
if len(new_words) != 6:
logger.warning(f"Expected 6 new feedback words, got {len(new_words)}. Not inserting.")
return
# Create new feedback items with default weight of 3
new_feedback_items = []
for i, word in enumerate(new_words):
# Generate unique key based on position in buffer
# New items will be at positions 0-5, so use those indices
feedback_key = f"feedback{i:02d}"
new_feedback_items.append({
feedback_key: word,
"weight": 3 # Default weight
})
# Insert new words at position 0
# Keep only FEEDBACK_HISTORY_SIZE items total
updated_feedback_historic = new_feedback_items + feedback_historic
if len(updated_feedback_historic) > settings.FEEDBACK_HISTORY_SIZE:
updated_feedback_historic = updated_feedback_historic[:settings.FEEDBACK_HISTORY_SIZE]
# Re-key all items to ensure unique keys
for i, item in enumerate(updated_feedback_historic):
# Get the word and weight from the current item
# Each item has structure: {"feedbackXX": "word", "weight": N}
old_key = list(item.keys())[0]
if old_key == "weight":
# Handle edge case where weight might be first key
continue
word = item[old_key]
weight = item.get("weight", 3)
# Create new key based on position
new_key = f"feedback{i:02d}"
# Replace the item with new structure
updated_feedback_historic[i] = {
new_key: word,
"weight": weight
}
# Update cache and save
self._feedback_historic_cache = updated_feedback_historic
await self.data_service.save_feedback_historic(updated_feedback_historic)
logger.info(f"Inserted 6 new feedback words at position 0, history size: {len(updated_feedback_historic)}")
except Exception as e:
logger.error(f"Error generating and inserting new feedback words: {e}")
raise
# Utility methods for API endpoints
def get_pool_size(self) -> int:
"""Get current pool size (synchronous for API endpoints)."""
if self._prompts_pool_cache is None:
raise RuntimeError("Pool cache not initialized")
return len(self._prompts_pool_cache)
def get_target_volume(self) -> int:
"""Get target pool volume (synchronous for API endpoints)."""
return settings.CACHED_POOL_VOLUME

90
backend/main.py
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@@ -1,90 +0,0 @@
"""
Daily Journal Prompt Generator - FastAPI Backend
Main application entry point
"""
import os
from pathlib import Path
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from contextlib import asynccontextmanager
from app.api.v1.api import api_router
from app.core.config import settings
from app.core.logging import setup_logging
from app.core.exception_handlers import setup_exception_handlers
# Setup logging
logger = setup_logging()
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Lifespan context manager for startup and shutdown events."""
# Startup
logger.info("Starting Daily Journal Prompt Generator API")
logger.info(f"Environment: {settings.ENVIRONMENT}")
logger.info(f"Debug mode: {settings.DEBUG}")
# Create data directory if it doesn't exist
data_dir = Path(settings.DATA_DIR)
data_dir.mkdir(exist_ok=True)
logger.info(f"Data directory: {data_dir.absolute()}")
yield
# Shutdown
logger.info("Shutting down Daily Journal Prompt Generator API")
# Create FastAPI app
app = FastAPI(
title="Daily Journal Prompt Generator API",
description="API for generating and managing journal writing prompts",
version="1.0.0",
docs_url="/docs",
redoc_url="/redoc",
lifespan=lifespan
)
# Setup exception handlers
setup_exception_handlers(app)
# Configure CORS
if settings.BACKEND_CORS_ORIGINS:
app.add_middleware(
CORSMiddleware,
allow_origins=[str(origin) for origin in settings.BACKEND_CORS_ORIGINS],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# Include API router
app.include_router(api_router, prefix="/api/v1")
@app.get("/")
async def root():
"""Root endpoint with API information."""
return {
"name": "Daily Journal Prompt Generator API",
"version": "1.0.0",
"description": "API for generating and managing journal writing prompts",
"docs": "/docs",
"redoc": "/redoc",
"health": "/health"
}
@app.get("/health")
async def health_check():
"""Health check endpoint."""
return {"status": "healthy", "service": "daily-journal-prompt-api"}
if __name__ == "__main__":
import uvicorn
uvicorn.run(
"main:app",
host=settings.HOST,
port=settings.PORT,
reload=settings.DEBUG,
log_level="info"
)

8
backend/requirements.txt
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@@ -1,8 +0,0 @@
fastapi>=0.104.0
uvicorn[standard]>=0.24.0
pydantic>=2.0.0
pydantic-settings>=2.0.0
python-dotenv>=1.0.0
openai>=1.0.0
aiofiles>=23.0.0

18
data/ds_feedback.txt
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@@ -1,18 +0,0 @@
Request for generation of writing prompts for journaling
Payload:
The previous 60 prompts have been provided as a JSON array for reference.
The previous 30 feedback themes are also provided. You should avoid re-using these words.
Guidelines:
The six total returned words should be unique.
Using the attached JSON of writing prompts, you should try to pick out 4 unique and intentionally vague single-word themes that apply to some portion of the list. They can range from common to uncommon words.
Then add 2 more single word divergent themes that are less related to the historic prompts and are somewhat different from the other 4 for a total of 6 words.
These 2 divergent themes give the user the option to steer away from existing themes, so be bold and unique.
A very high temperature AI response is warranted here to generate a large vocabulary.
Expected Output:
Output as a JSON list with just the six words, in lowercase.
Despite the provided history being a keyed list or dictionary, the expected return JSON will be a simple list with no keys.
Respond ONLY with valid JSON. No explanations, no markdown, no backticks.

122
data/feedback_historic.json
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@@ -1,122 +0,0 @@
[
{
"feedback00": "labyrinthine",
"weight": 3
},
{
"feedback01": "verdant",
"weight": 3
},
{
"feedback02": "cacophony",
"weight": 3
},
{
"feedback03": "solitude",
"weight": 3
},
{
"feedback04": "kaleidoscope",
"weight": 3
},
{
"feedback05": "zenith",
"weight": 3
},
{
"feedback06": "mellifluous",
"weight": 3
},
{
"feedback07": "detritus",
"weight": 4
},
{
"feedback08": "liminal",
"weight": 1
},
{
"feedback09": "palimpsest",
"weight": 1
},
{
"feedback10": "phantasmagoria",
"weight": 3
},
{
"feedback11": "ephemeral",
"weight": 3
},
{
"feedback12": "gambol",
"weight": 3
},
{
"feedback13": "fathom",
"weight": 6
},
{
"feedback14": "cipher",
"weight": 1
},
{
"feedback15": "lucid",
"weight": 3
},
{
"feedback16": "sublime",
"weight": 3
},
{
"feedback17": "quiver",
"weight": 6
},
{
"feedback18": "murmur",
"weight": 3
},
{
"feedback19": "glaze",
"weight": 3
},
{
"feedback20": "warp",
"weight": 3
},
{
"feedback21": "silt",
"weight": 6
},
{
"feedback22": "quasar",
"weight": 6
},
{
"feedback23": "glyph",
"weight": 3
},
{
"feedback24": "gossamer",
"weight": 4
},
{
"feedback25": "algorithm",
"weight": 4
},
{
"feedback26": "plenum",
"weight": 4
},
{
"feedback27": "drift",
"weight": 4
},
{
"feedback28": "cryptid",
"weight": 4
},
{
"feedback29": "volta",
"weight": 4
}
]

122
data/feedback_historic.json.bak
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@@ -1,122 +0,0 @@
[
{
"feedback00": "mellifluous",
"weight": 3
},
{
"feedback01": "detritus",
"weight": 4
},
{
"feedback02": "liminal",
"weight": 1
},
{
"feedback03": "palimpsest",
"weight": 1
},
{
"feedback04": "phantasmagoria",
"weight": 3
},
{
"feedback05": "ephemeral",
"weight": 3
},
{
"feedback06": "gambol",
"weight": 3
},
{
"feedback07": "fathom",
"weight": 6
},
{
"feedback08": "cipher",
"weight": 1
},
{
"feedback09": "lucid",
"weight": 3
},
{
"feedback10": "sublime",
"weight": 3
},
{
"feedback11": "quiver",
"weight": 6
},
{
"feedback12": "murmur",
"weight": 3
},
{
"feedback13": "glaze",
"weight": 3
},
{
"feedback14": "warp",
"weight": 3
},
{
"feedback15": "silt",
"weight": 6
},
{
"feedback16": "quasar",
"weight": 6
},
{
"feedback17": "glyph",
"weight": 3
},
{
"feedback18": "gossamer",
"weight": 4
},
{
"feedback19": "algorithm",
"weight": 4
},
{
"feedback20": "plenum",
"weight": 4
},
{
"feedback21": "drift",
"weight": 4
},
{
"feedback22": "cryptid",
"weight": 4
},
{
"feedback23": "volta",
"weight": 4
},
{
"feedback24": "lacuna",
"weight": 3
},
{
"feedback25": "mycelium",
"weight": 1
},
{
"feedback26": "talisman",
"weight": 3
},
{
"feedback27": "effulgence",
"weight": 3
},
{
"feedback28": "chrysalis",
"weight": 6
},
{
"feedback29": "sonder",
"weight": 1
}
]

182
data/prompts_historic.json
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@@ -1,182 +0,0 @@
[
{
"prompt00": "Describe a routine journey you make regularly—a commute, a walk to a local shop, a drive you know by heart. For one trip, perform it in reverse order if possible, or simply pay hyper-attentive, first-time attention to every detail. What do you notice that habit has rendered invisible? Does the familiar path become strange, beautiful, or tedious in a new way? Write about the act of defamiliarizing your own life."
},
{
"prompt01": "Recall a moment when reality seemed to glitch—a déjà vu so strong it was disorienting, a brief failure of recognition for a familiar face, or a dream detail that inexplicably appeared in waking life. Describe the sensation of the world's software briefly stuttering. Did it feel ominous, amusing, or profoundly strange? Explore what such moments reveal about the constructed nature of our perception and the seams in our conscious experience."
},
{
"prompt02": "Describe a container in your home that is almost always empty—a vase, a decorative bowl, a certain drawer. Why is it empty? Is it waiting for the perfect thing, or is its emptiness part of its function or beauty? Contemplate the purpose and presence of void spaces. What would happen if you deliberately filled it with something, or committed to keeping it perpetually empty?"
},
{
"prompt03": "Describe a wall in your city or neighborhood that is covered in layers of peeling posters and graffiti. Read it as a chaotic, collaborative public diary. What events were advertised, what messages were proclaimed, what art was left behind? Imagine the hands that placed each layer. Write about the history and humanity documented in this slow, uncurated accumulation."
},
{
"prompt04": "Describe a skill you learned through sheer, repetitive failure. Chart the arc from initial clumsy attempts, through frustration, to eventual unconscious competence. What did the process teach you about your own capacity for patience and persistence beyond the skill itself? Write about the hidden curriculum of learning by doing things wrong, over and over."
},
{
"prompt05": "You inherit a collection of someone else's bookmarks: train tickets, dried flowers, scraps of paper with cryptic notes. Deduce a portrait of the reader from these interstitial artifacts. What journeys were they on, both literal and literary? What passages were they marking to return to? Write a character study based on the quiet traces left in the pages of another life."
},
{
"prompt06": "Stand in the umbra—the full shadow—of a large object at midday. Describe the quality of light and temperature within this sharp-edged darkness. How does it feel to be so definitively separated from the sun's glare? Now, consider a metaphorical umbra in your life: a situation or emotion that casts a deep, distinct shadow. What grows, or what becomes clearer, in this cooler, shaded space?"
},
{
"prompt07": "Observe a tiled floor, a honeycomb, or a patchwork quilt. Study the tessellation—the repeating pattern of individual units creating a cohesive whole. Now, apply this concept to a week of your life. What are the fundamental, repeating units (tasks, interactions, thoughts) that combine to form the larger pattern? Is the overall design harmonious, chaotic, or in need of a new tile? Write about the beauty and constraint of life's inherent patterning."
},
{
"prompt08": "Consider the concept of a 'personal zenith'—the peak moment of a day, a project, or a phase of life, often recognized only in hindsight. Describe a recent zenith you experienced. What were the conditions that led to it? How did you know you had reached the apex? Was there a feeling of culmination, or was it a quiet cresting? Explore the gentle descent or plateau that followed, and how one navigates the landscape after the highest point has been passed."
},
{
"prompt09": "Imagine you are tasked with designing a new public holiday that celebrates a quiet, overlooked aspect of human experience—like the feeling of a first cool breeze after a heatwave, or the shared silence of strangers waiting in line. What would you call it? What rituals or observances would define it? How would people prepare for it, and what would they be encouraged to reflect upon? Write about the values and subtleties this holiday would enshrine, and why such a celebration feels necessary in the rhythm of the year."
},
{
"prompt10": "Consider the concept of a 'hinterland'—the remote, uncharted territory beyond the familiar borders of your daily awareness. Identify a mental or emotional hinterland within yourself: a set of feelings, memories, or potentials you rarely visit. Describe its imagined landscape. What keeps it distant? Write about a deliberate expedition into this interior wilderness. What do you discover, and how does the journey change your map of yourself?"
},
{
"prompt11": "Recall a moment when you were the recipient of a stranger's gaze—a brief, wordless look exchanged on the street, in a waiting room, or across a crowded space. Reconstruct the micro-expressions you perceived. What story did you instinctively write for them in that instant? Now, reverse the perspective. Imagine you were the stranger, and the look you gave was being interpreted. What unspoken narrative might they have constructed about you? Explore the silent, rapid-fire fiction we create in the gaps between people."
},
{
"prompt12": "You discover an old, handmade 'effigy'—a doll, a figurine, a crude sculpture—whose purpose is unclear. Describe its materials and construction. Who might have made it, and for what ritual or private reason? Does it feel protective, commemorative, or malevolent? Hold it. Write a speculative history of its creation and journey to you, exploring the human impulse to craft physical representations of our fears, hopes, or memories, and the quiet power these objects retain."
},
{
"prompt13": "Conduct a thought experiment: your mind is a 'plenum' of memories. There is no true forgetting, only layers of accumulation. Choose a recent, minor event and trace its connections downward through the strata, linking it to older, deeper memories it subtly echoes. Describe the archaeology of this mental space. What is it like to inhabit a consciousness where nothing is ever truly empty or lost?"
},
{
"prompt14": "Map your personal cosmology. Identify the 'quasars' (energetic cores), the 'gossamer' nebulae (dreamy, forming ideas), the stable planets (routines), and the dark matter (unseen influences). How do these celestial bodies interact? Is there a governing 'algorithm' or natural law to their motions? Write a guide to your inner universe, describing its scale, its mysteries, and its current celestial weather."
},
{
"prompt15": "Describe a structure in your life that functions as a 'plenum' for others—perhaps your attention for a friend, your home for your family, your schedule for your work. You are the space that is filled by their needs, conversations, or expectations. How do you maintain the integrity of your own walls? Do you ever feel on the verge of overpressure? Explore the physics of being a container and the quiet adjustments required to remain both full and whole."
},
{
"prompt16": "Consider the 'algorithm' of your morning routine. Deconstruct it into its fundamental steps, decisions, and conditional loops (if tired, then coffee; if sunny, then walk). Now, introduce a deliberate bug or a random variable. Break one step. Observe how the entire program of your day adapts, crashes, or discovers a new, unexpected function. Write about the poetry and the vulnerability hidden within your personal, daily code."
},
{
"prompt17": "Describe a piece of music that feels like a physical landscape to you. Don't just name the emotions; map the topography. Where are the soaring cliffs, the deep valleys, the calm meadows, the treacherous passes? When do you walk, when do you climb, when are you carried by a current? Write about journeying through this sonic territory. What part of yourself do you encounter in each region? Does the landscape change when you listen with closed eyes versus open? Explore the synesthesia of listening with your whole body."
},
{
"prompt18": "You are an archivist of vanishing sounds. For one day, consciously catalog the ephemeral auditory moments that usually go unnoticed: the specific creak of a floorboard, the sigh of a refrigerator cycling off, the rustle of a particular fabric. Describe these sounds with the precision of someone preserving them for posterity. Why do you choose these particular ones? What memory or feeling is tied to each? Write about the poignant act of listening to the present as if it were already becoming the past, and the history held in transient vibrations."
},
{
"prompt19": "Imagine your mind as a 'lattice'—a delicate, interconnected framework of beliefs, memories, and associations. Describe the nodes and the struts that connect them. Which connections are strong and frequently traveled? Which are fragile or overgrown? Now, consider a new idea or experience that doesn't fit neatly onto this existing lattice. Does it build a new node, strain an old connection, or require you to gently reshape the entire structure? Write about the mental architecture of integration and the quiet labor of building scaffolds for new understanding."
},
{
"prompt20": "Consider the concept of 'patina'—the beautiful, acquired sheen on an object from long use and exposure. Find an object in your possession that has developed its own patina through years of handling. Describe its surface in detail: the worn spots, the subtle discolorations, the softened edges. What stories of use and care are etched into its material? Now, reflect on the metaphorical patinas you have developed. What experiences have polished some parts of your character, while leaving others gently weathered? Write about the beauty of a life lived, not in pristine condition, but with the honorable marks of time and interaction."
},
{
"prompt21": "Recall a piece of clothing you once loved but no longer wear. Describe its texture, its fit, the memories woven into its fibers. Why did you stop wearing it? Did it wear out, fall out of style, or cease to fit the person you became? Write a eulogy for this garment, honoring its service and the version of yourself it once clothed. What have you shed along with it?"
},
{
"prompt22": "Recall a dream that presented itself as a cipher—a series of vivid but inexplicable images. Describe the dream's symbols without attempting to decode them. Sit with their inherent strangeness. What if the value of the dream lies not in its translatable meaning, but in its resistance to interpretation? Write about the experience of holding a mysterious internal artifact and choosing not to solve it."
},
{
"prompt23": "You encounter a natural system in a state of gentle decay—a rotting log, fallen leaves, a piece of fruit fermenting. Observe it closely. Describe the actors in this process: insects, fungi, bacteria. Reframe this not as an end, but as a vibrant, teeming transformation. How does witnessing this quiet, relentless alchemy change your perception of endings? Write about decay as a form of busy, purposeful life."
},
{
"prompt24": "Describe a public space you frequent at a specific time of day—a park bench, a café corner, a bus stop. For one week, observe the choreography of its other inhabitants. Note the regulars, their patterns, their unspoken agreements about space and proximity. Write about your role in this daily ballet. Are you a participant, an observer, or both? What story does this silent, collective movement tell?"
},
{
"prompt25": "Recall a moment when you felt a subtle tremor—not in the earth, but in your convictions, a relationship, or your understanding of a situation. Describe the initial, almost imperceptible vibration. Did it build into a quake, or subside into a new, stable silence? How did you steady yourself? Write about detecting and responding to these foundational shifts that precede more visible change."
},
{
"prompt26": "You find a single, interestingly shaped stone. Hold it in your hand. Consider its journey over millennia: the forces that shaped it, the places it has been, how it came to rest where you found it. Now, consider your own lifespan in comparison. Write a dialogue between you and the stone, exploring scales of time, permanence, and the brief, bright flicker of conscious life."
},
{
"prompt27": "Contemplate the concept of 'drift'—the slow, almost imperceptible movement away from an original position or intention. Identify an area of your life where you have experienced drift: in a relationship, a career path, a personal goal. Describe the subtle currents that caused it. Was it a passive surrender or a series of conscious micro-choices? Do you wish to correct your course, or are you curious to see where this new current leads?"
},
{
"prompt28": "You are tasked with composing a letter that will be sealed in a time capsule to be opened in 100 years. It cannot be about major world events, but about the mundane, beautiful details of an ordinary day in your life now. What do you describe? What do you assume will be incomprehensible to the future reader? What do you hope will be timeless?"
},
{
"prompt29": "Find a crack in a wall or pavement. Observe it closely. How did it form? What tiny ecosystems exist within it? Trace its path with your finger (in reality or in your mind). Use this flaw as a starting point to write about the beauty and necessity of imperfection, not as a deviation from wholeness, but as an integral part of a structure's story and character."
},
{
"prompt30": "Recall a time you witnessed an act of quiet, uncelebrated kindness between strangers. Describe the scene in detail. What was the gesture? How did the recipient react? How did it make you feel as an observer? Explore the ripple effect of such moments. Did it alter your behavior or outlook, even subtly, in the days that followed?"
},
{
"prompt31": "Create a cartography of a single, perfect day from your past. Do not map it chronologically. Instead, chart it by emotional landmarks and sensory waypoints. Where is the bay of contentment? The crossroads of a key decision? The forest of laughter? Draw this map in words, connecting the sites with paths of memory. What does this non-linear geography reveal about the day's true shape and impact?"
},
{
"prompt32": "Consider the alchemy of your daily routine. Take a mundane, repetitive task—making coffee, commuting, sorting mail—and describe it as a sacred, transformative ritual. What base materials (beans, traffic, paper) are you transmuting? What is the philosopher's stone in this process—your attention, your intention, or something else? Write about finding the hidden gold in the lead of habit."
},
{
"prompt33": "Choose a common material—wood, glass, concrete, fabric—and follow its presence through your day. Note every instance you encounter it. Describe its different forms, functions, and textures. By day's end, write about this material not as a passive substance, but as a silent, ubiquitous character in the story of your daily life. How does its constancy shape your experience?"
},
{
"prompt34": "Meditate on the feeling of 'enough.' Identify one area of your life (possessions, information, work, social interaction) where you recently felt a clear sense of sufficiency. Describe the precise moment that feeling arrived. What were its qualities? Contrast it with the more common feeling of scarcity or desire for more. How can you recognize the threshold of 'enough' when you encounter it again?"
},
{
"prompt35": "Think of a skill or talent you admire in someone else but feel you lack. Instead of framing it as a deficiency, imagine it as a different sensory apparatus. If their skill is a form of sight, what color do they see that you cannot? If it's a form of hearing, what frequency do they detect? Write about the world as experienced through this hypothetical sense you don't possess. What beautiful things might you be missing?"
},
{
"prompt36": "Contemplate the concept of 'waste'—not just trash, but wasted time, wasted potential, wasted emotion. Find a physical example of waste in your environment (a discarded object, spoiled food). Describe it without judgment. Then, trace its lineage back to its origin as something useful or desired. Can you find any hidden value or beauty in its current state? Explore the tension between utility and decay."
},
{
"prompt37": "Describe a place you know only through stories—a parent's childhood home, a friend's distant travels, a historical event's location. Build a sensory portrait of this place from second-hand descriptions. Now, imagine finally visiting it. Does the reality match the imagined geography? Write about the collision between inherited memory and firsthand experience, and which feels more real."
},
{
"prompt38": "You are given a blank, high-quality piece of paper and a single, perfect pen. The instruction is to create a map, but not of a physical place. Map the emotional landscape of a recent week. What are its mountain ranges of joy, its valleys of fatigue, its rivers of thought? Where are the uncharted territories? Label the landmarks with the small events that shaped them. Write about the act of cartography as a form of understanding."
},
{
"prompt39": "Contemplate the concept of 'waste' in your life—discarded time, unused potential, physical objects headed for landfill. Select one instance and personify it. Give this 'waste' a voice. What story does it tell about the system that produced it? Does it lament its fate, accept it, or propose an alternative existence? Write a dialogue with this personified fragment, exploring the guilt, inevitability, or hidden value we assign to what we cast aside."
},
{
"prompt40": "You are given a single, unmarked seed. Plant it in a pot of soil and place it where you will see it daily. For the next week, keep a log of your observations and the thoughts it provokes. Do you find yourself impatient for a sign of growth, or content with the mystery? How does this small, silent act of fostering potential mirror other, less tangible forms of nurturing in your life? Write about the discipline and faith in hidden processes."
},
{
"prompt41": "Describe a moment of profound stillness you experienced in a normally chaotic environment—a busy train station, a loud household, a crowded market. How did the noise and motion recede into the background, leaving you in a bubble of quiet observation? What details became hyper-visible in this state? Explore the feeling of being an island of calm within a sea of activity, and what this temporary detachment revealed about your connection to the world around you."
},
{
"prompt42": "Recall a piece of practical knowledge you possess that feels almost like a secret—a shortcut, a repair trick, a way of predicting the weather. How did you acquire it? Was it taught, stumbled upon, or earned through failure? Describe the feeling of holding this minor, useful wisdom. When do you choose to share it, and with whom? Explore the value of these small, uncelebrated competencies that help navigate daily life."
},
{
"prompt43": "Choose a tool you use for creation—a pen, a brush, a kitchen knife, a software cursor. Personify it not as a servant, but as a collaborator with its own temperament. Describe its ideal conditions, its quirks, its moments of resistance or fluid grace. Write about a specific project from its perspective. What does it 'feel' as you work? How does the partnership between your intention and its material properties shape the final outcome?"
},
{
"prompt44": "Describe a moment of profound silence you experienced—not just an absence of sound, but a resonant quiet that felt thick and full. Where were you? What thoughts or feelings arose in that space? Did the silence feel like a void or a presence? Explore how this deep quiet contrasted with the usual noise of your life, and what it revealed about your need for stillness or your fear of it."
},
{
"prompt45": "Recall a dream that took place in a liminal setting: an airport terminal, a ferry, a long corridor. What was the feeling of transit in the dream? Were you trying to reach a gate, find a door, or catch a vehicle? Explore what this dream-space might represent in your waking life. What are you in the process of leaving behind, and what are you attempting to board or enter? Write about the symbolism of dream travel."
},
{
"prompt46": "Meditate on the void left by a finished project, a concluded journey, or a resolved conflict. The effort and focus are gone, leaving an empty space where they once lived. Do you feel relief, disorientation, or a quiet emptiness? How do you inhabit this new quiet? Do you rush to fill it, or allow yourself to rest in the void, understanding it as a necessary pause between acts? Describe the landscape of completion."
},
{
"prompt47": "Think of a piece of art, music, or literature that created a profound echo in your soul—something that resonated so deeply it seemed to vibrate within you long after the initial experience. Deconstruct the echo. What specific frequencies (themes, melodies, images) matched your own internal tuning? Has the echo changed over time, growing fainter or merging with other sounds? Write about the anatomy of a lasting resonance."
},
{
"prompt48": "Choose a book you have read multiple times over the years. Each reading has left a layer of understanding, colored by who you were at the time. Open it now and find a heavily annotated page or a familiar passage. Read it as a palimpsest of your former selves. What do the different layers of your marginalia—the underlines, the question marks, the exclamations—reveal about your evolving relationship with the text and with your own mind?"
},
{
"prompt49": "Listen for an echo in your daily life—not a sonic one, but a recurrence. It could be a phrase someone uses that reminds you of another person, a pattern in your mistakes, or a feeling that returns in different circumstances. Trace this echo back to its source. Is it a memory, a habit, or a unresolved piece of your past? Write about the journey of following this reverberation to its origin and understanding why it persists."
},
{
"prompt50": "Imagine you could perceive the subtle, invisible networks that connect all things—the mycelial threads of relationship, influence, and shared history. Choose a single, ordinary object in your room. Trace its hypothetical connections: to the people who made it, the materials that compose it, the places it has been. Write about the moment your perception shifts, and you see not an isolated item, but a luminous node in a vast, humming web of interdependence."
},
{
"prompt51": "You inherit a box of someone else's photographs. The people and places are largely unknown to you. Select one image and build a speculative history for it. Who are the subjects? What was the occasion? What happened just before and just after the shutter clicked? Write the story this silent image suggests, exploring the act of constructing narrative from anonymous fragments."
},
{
"prompt52": "Recall a time you were lost, not in a wilderness, but in a familiar place made strange—perhaps by fog, darkness, or a disorienting emotional state. Describe the moment your internal map failed. How did you navigate without reliable landmarks? What did you discover about your surroundings and yourself in that state of productive disorientation?"
},
{
"prompt53": "Describe a piece of furniture in your home that has been with you through multiple life stages. Chronicle the conversations it has silently witnessed, the weight of different people who have sat upon it, the objects it has held. How has its function or meaning evolved alongside your own story? What would it say if it could speak of the quiet history embedded in its grain and upholstery?"
},
{
"prompt54": "Find a tree with visible scars—from pruning, lightning, disease, or carved initials. Describe these marks as entries in the tree's personal diary. What do they record about survival, interaction, and the passage of time? Imagine the tree's perspective on healing, which does not erase the wound but grows around it, incorporating the damage into its expanding self. What scars of your own have become part of your structure?"
},
{
"prompt55": "Recall a promise you made to yourself long ago—a vow about the person you would become, the life you would lead, or a principle you would never break. Have you kept it? If so, describe the quiet fidelity required. If not, explore the moment and the reasons for the divergence. Does the broken promise feel like a betrayal or an evolution? Is the ghost of that old vow a compassionate or an accusing presence?"
},
{
"prompt56": "Describe a recurring dream you have not had in years, but whose emotional residue still lingers. What was its landscape, its characters, its unspoken rules? Why do you think it has ceased its nocturnal visits? Explore the possibility that it was a messenger whose work is done, or a story your mind no longer needs to tell. What quiet tremor in your waking life might have signaled its departure?"
},
{
"prompt57": "Imagine you could send a message to yourself ten years in the past. You are limited to five words. What would those five words be? Why? Now, imagine receiving a five-word message from your future self, ten years from now. What might it say? Write about the agonizing economy and profound potential of such constrained communication."
},
{
"prompt58": "Observe a shadow throughout the day. It could be the shadow of a tree, a building, or a simple object on your desk. Chronicle its slow, silent journey. How does its shape, length, and sharpness change? Use this as a meditation on time's passage. What is the relationship between the solid object and its fleeting, dependent silhouette?"
},
{
"prompt59": "Contemplate the concept of a 'horizon'—both literal and metaphorical. Describe a time you physically journeyed toward a horizon. What was the experience of it perpetually receding? Now, identify a current personal or professional horizon. How do you navigate toward something that by definition moves as you do? Write about the tension between the journey and the ever-distant line."
}
]

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[
{
"prompt00": "Recall a moment when reality seemed to glitch—a déjà vu so strong it was disorienting, a brief failure of recognition for a familiar face, or a dream detail that inexplicably appeared in waking life. Describe the sensation of the world's software briefly stuttering. Did it feel ominous, amusing, or profoundly strange? Explore what such moments reveal about the constructed nature of our perception and the seams in our conscious experience."
},
{
"prompt01": "Describe a container in your home that is almost always empty—a vase, a decorative bowl, a certain drawer. Why is it empty? Is it waiting for the perfect thing, or is its emptiness part of its function or beauty? Contemplate the purpose and presence of void spaces. What would happen if you deliberately filled it with something, or committed to keeping it perpetually empty?"
},
{
"prompt02": "Describe a wall in your city or neighborhood that is covered in layers of peeling posters and graffiti. Read it as a chaotic, collaborative public diary. What events were advertised, what messages were proclaimed, what art was left behind? Imagine the hands that placed each layer. Write about the history and humanity documented in this slow, uncurated accumulation."
},
{
"prompt03": "Describe a skill you learned through sheer, repetitive failure. Chart the arc from initial clumsy attempts, through frustration, to eventual unconscious competence. What did the process teach you about your own capacity for patience and persistence beyond the skill itself? Write about the hidden curriculum of learning by doing things wrong, over and over."
},
{
"prompt04": "You inherit a collection of someone else's bookmarks: train tickets, dried flowers, scraps of paper with cryptic notes. Deduce a portrait of the reader from these interstitial artifacts. What journeys were they on, both literal and literary? What passages were they marking to return to? Write a character study based on the quiet traces left in the pages of another life."
},
{
"prompt05": "Stand in the umbra—the full shadow—of a large object at midday. Describe the quality of light and temperature within this sharp-edged darkness. How does it feel to be so definitively separated from the sun's glare? Now, consider a metaphorical umbra in your life: a situation or emotion that casts a deep, distinct shadow. What grows, or what becomes clearer, in this cooler, shaded space?"
},
{
"prompt06": "Observe a tiled floor, a honeycomb, or a patchwork quilt. Study the tessellation—the repeating pattern of individual units creating a cohesive whole. Now, apply this concept to a week of your life. What are the fundamental, repeating units (tasks, interactions, thoughts) that combine to form the larger pattern? Is the overall design harmonious, chaotic, or in need of a new tile? Write about the beauty and constraint of life's inherent patterning."
},
{
"prompt07": "Consider the concept of a 'personal zenith'—the peak moment of a day, a project, or a phase of life, often recognized only in hindsight. Describe a recent zenith you experienced. What were the conditions that led to it? How did you know you had reached the apex? Was there a feeling of culmination, or was it a quiet cresting? Explore the gentle descent or plateau that followed, and how one navigates the landscape after the highest point has been passed."
},
{
"prompt08": "Imagine you are tasked with designing a new public holiday that celebrates a quiet, overlooked aspect of human experience—like the feeling of a first cool breeze after a heatwave, or the shared silence of strangers waiting in line. What would you call it? What rituals or observances would define it? How would people prepare for it, and what would they be encouraged to reflect upon? Write about the values and subtleties this holiday would enshrine, and why such a celebration feels necessary in the rhythm of the year."
},
{
"prompt09": "Consider the concept of a 'hinterland'—the remote, uncharted territory beyond the familiar borders of your daily awareness. Identify a mental or emotional hinterland within yourself: a set of feelings, memories, or potentials you rarely visit. Describe its imagined landscape. What keeps it distant? Write about a deliberate expedition into this interior wilderness. What do you discover, and how does the journey change your map of yourself?"
},
{
"prompt10": "Recall a moment when you were the recipient of a stranger's gaze—a brief, wordless look exchanged on the street, in a waiting room, or across a crowded space. Reconstruct the micro-expressions you perceived. What story did you instinctively write for them in that instant? Now, reverse the perspective. Imagine you were the stranger, and the look you gave was being interpreted. What unspoken narrative might they have constructed about you? Explore the silent, rapid-fire fiction we create in the gaps between people."
},
{
"prompt11": "You discover an old, handmade 'effigy'—a doll, a figurine, a crude sculpture—whose purpose is unclear. Describe its materials and construction. Who might have made it, and for what ritual or private reason? Does it feel protective, commemorative, or malevolent? Hold it. Write a speculative history of its creation and journey to you, exploring the human impulse to craft physical representations of our fears, hopes, or memories, and the quiet power these objects retain."
},
{
"prompt12": "Conduct a thought experiment: your mind is a 'plenum' of memories. There is no true forgetting, only layers of accumulation. Choose a recent, minor event and trace its connections downward through the strata, linking it to older, deeper memories it subtly echoes. Describe the archaeology of this mental space. What is it like to inhabit a consciousness where nothing is ever truly empty or lost?"
},
{
"prompt13": "Map your personal cosmology. Identify the 'quasars' (energetic cores), the 'gossamer' nebulae (dreamy, forming ideas), the stable planets (routines), and the dark matter (unseen influences). How do these celestial bodies interact? Is there a governing 'algorithm' or natural law to their motions? Write a guide to your inner universe, describing its scale, its mysteries, and its current celestial weather."
},
{
"prompt14": "Describe a structure in your life that functions as a 'plenum' for others—perhaps your attention for a friend, your home for your family, your schedule for your work. You are the space that is filled by their needs, conversations, or expectations. How do you maintain the integrity of your own walls? Do you ever feel on the verge of overpressure? Explore the physics of being a container and the quiet adjustments required to remain both full and whole."
},
{
"prompt15": "Consider the 'algorithm' of your morning routine. Deconstruct it into its fundamental steps, decisions, and conditional loops (if tired, then coffee; if sunny, then walk). Now, introduce a deliberate bug or a random variable. Break one step. Observe how the entire program of your day adapts, crashes, or discovers a new, unexpected function. Write about the poetry and the vulnerability hidden within your personal, daily code."
},
{
"prompt16": "Describe a piece of music that feels like a physical landscape to you. Don't just name the emotions; map the topography. Where are the soaring cliffs, the deep valleys, the calm meadows, the treacherous passes? When do you walk, when do you climb, when are you carried by a current? Write about journeying through this sonic territory. What part of yourself do you encounter in each region? Does the landscape change when you listen with closed eyes versus open? Explore the synesthesia of listening with your whole body."
},
{
"prompt17": "You are an archivist of vanishing sounds. For one day, consciously catalog the ephemeral auditory moments that usually go unnoticed: the specific creak of a floorboard, the sigh of a refrigerator cycling off, the rustle of a particular fabric. Describe these sounds with the precision of someone preserving them for posterity. Why do you choose these particular ones? What memory or feeling is tied to each? Write about the poignant act of listening to the present as if it were already becoming the past, and the history held in transient vibrations."
},
{
"prompt18": "Imagine your mind as a 'lattice'—a delicate, interconnected framework of beliefs, memories, and associations. Describe the nodes and the struts that connect them. Which connections are strong and frequently traveled? Which are fragile or overgrown? Now, consider a new idea or experience that doesn't fit neatly onto this existing lattice. Does it build a new node, strain an old connection, or require you to gently reshape the entire structure? Write about the mental architecture of integration and the quiet labor of building scaffolds for new understanding."
},
{
"prompt19": "Consider the concept of 'patina'—the beautiful, acquired sheen on an object from long use and exposure. Find an object in your possession that has developed its own patina through years of handling. Describe its surface in detail: the worn spots, the subtle discolorations, the softened edges. What stories of use and care are etched into its material? Now, reflect on the metaphorical patinas you have developed. What experiences have polished some parts of your character, while leaving others gently weathered? Write about the beauty of a life lived, not in pristine condition, but with the honorable marks of time and interaction."
},
{
"prompt20": "Recall a piece of clothing you once loved but no longer wear. Describe its texture, its fit, the memories woven into its fibers. Why did you stop wearing it? Did it wear out, fall out of style, or cease to fit the person you became? Write a eulogy for this garment, honoring its service and the version of yourself it once clothed. What have you shed along with it?"
},
{
"prompt21": "Recall a dream that presented itself as a cipher—a series of vivid but inexplicable images. Describe the dream's symbols without attempting to decode them. Sit with their inherent strangeness. What if the value of the dream lies not in its translatable meaning, but in its resistance to interpretation? Write about the experience of holding a mysterious internal artifact and choosing not to solve it."
},
{
"prompt22": "You encounter a natural system in a state of gentle decay—a rotting log, fallen leaves, a piece of fruit fermenting. Observe it closely. Describe the actors in this process: insects, fungi, bacteria. Reframe this not as an end, but as a vibrant, teeming transformation. How does witnessing this quiet, relentless alchemy change your perception of endings? Write about decay as a form of busy, purposeful life."
},
{
"prompt23": "Describe a public space you frequent at a specific time of day—a park bench, a café corner, a bus stop. For one week, observe the choreography of its other inhabitants. Note the regulars, their patterns, their unspoken agreements about space and proximity. Write about your role in this daily ballet. Are you a participant, an observer, or both? What story does this silent, collective movement tell?"
},
{
"prompt24": "Recall a moment when you felt a subtle tremor—not in the earth, but in your convictions, a relationship, or your understanding of a situation. Describe the initial, almost imperceptible vibration. Did it build into a quake, or subside into a new, stable silence? How did you steady yourself? Write about detecting and responding to these foundational shifts that precede more visible change."
},
{
"prompt25": "You find a single, interestingly shaped stone. Hold it in your hand. Consider its journey over millennia: the forces that shaped it, the places it has been, how it came to rest where you found it. Now, consider your own lifespan in comparison. Write a dialogue between you and the stone, exploring scales of time, permanence, and the brief, bright flicker of conscious life."
},
{
"prompt26": "Contemplate the concept of 'drift'—the slow, almost imperceptible movement away from an original position or intention. Identify an area of your life where you have experienced drift: in a relationship, a career path, a personal goal. Describe the subtle currents that caused it. Was it a passive surrender or a series of conscious micro-choices? Do you wish to correct your course, or are you curious to see where this new current leads?"
},
{
"prompt27": "You are tasked with composing a letter that will be sealed in a time capsule to be opened in 100 years. It cannot be about major world events, but about the mundane, beautiful details of an ordinary day in your life now. What do you describe? What do you assume will be incomprehensible to the future reader? What do you hope will be timeless?"
},
{
"prompt28": "Find a crack in a wall or pavement. Observe it closely. How did it form? What tiny ecosystems exist within it? Trace its path with your finger (in reality or in your mind). Use this flaw as a starting point to write about the beauty and necessity of imperfection, not as a deviation from wholeness, but as an integral part of a structure's story and character."
},
{
"prompt29": "Recall a time you witnessed an act of quiet, uncelebrated kindness between strangers. Describe the scene in detail. What was the gesture? How did the recipient react? How did it make you feel as an observer? Explore the ripple effect of such moments. Did it alter your behavior or outlook, even subtly, in the days that followed?"
},
{
"prompt30": "Create a cartography of a single, perfect day from your past. Do not map it chronologically. Instead, chart it by emotional landmarks and sensory waypoints. Where is the bay of contentment? The crossroads of a key decision? The forest of laughter? Draw this map in words, connecting the sites with paths of memory. What does this non-linear geography reveal about the day's true shape and impact?"
},
{
"prompt31": "Consider the alchemy of your daily routine. Take a mundane, repetitive task—making coffee, commuting, sorting mail—and describe it as a sacred, transformative ritual. What base materials (beans, traffic, paper) are you transmuting? What is the philosopher's stone in this process—your attention, your intention, or something else? Write about finding the hidden gold in the lead of habit."
},
{
"prompt32": "Choose a common material—wood, glass, concrete, fabric—and follow its presence through your day. Note every instance you encounter it. Describe its different forms, functions, and textures. By day's end, write about this material not as a passive substance, but as a silent, ubiquitous character in the story of your daily life. How does its constancy shape your experience?"
},
{
"prompt33": "Meditate on the feeling of 'enough.' Identify one area of your life (possessions, information, work, social interaction) where you recently felt a clear sense of sufficiency. Describe the precise moment that feeling arrived. What were its qualities? Contrast it with the more common feeling of scarcity or desire for more. How can you recognize the threshold of 'enough' when you encounter it again?"
},
{
"prompt34": "Think of a skill or talent you admire in someone else but feel you lack. Instead of framing it as a deficiency, imagine it as a different sensory apparatus. If their skill is a form of sight, what color do they see that you cannot? If it's a form of hearing, what frequency do they detect? Write about the world as experienced through this hypothetical sense you don't possess. What beautiful things might you be missing?"
},
{
"prompt35": "Contemplate the concept of 'waste'—not just trash, but wasted time, wasted potential, wasted emotion. Find a physical example of waste in your environment (a discarded object, spoiled food). Describe it without judgment. Then, trace its lineage back to its origin as something useful or desired. Can you find any hidden value or beauty in its current state? Explore the tension between utility and decay."
},
{
"prompt36": "Describe a place you know only through stories—a parent's childhood home, a friend's distant travels, a historical event's location. Build a sensory portrait of this place from second-hand descriptions. Now, imagine finally visiting it. Does the reality match the imagined geography? Write about the collision between inherited memory and firsthand experience, and which feels more real."
},
{
"prompt37": "You are given a blank, high-quality piece of paper and a single, perfect pen. The instruction is to create a map, but not of a physical place. Map the emotional landscape of a recent week. What are its mountain ranges of joy, its valleys of fatigue, its rivers of thought? Where are the uncharted territories? Label the landmarks with the small events that shaped them. Write about the act of cartography as a form of understanding."
},
{
"prompt38": "Contemplate the concept of 'waste' in your life—discarded time, unused potential, physical objects headed for landfill. Select one instance and personify it. Give this 'waste' a voice. What story does it tell about the system that produced it? Does it lament its fate, accept it, or propose an alternative existence? Write a dialogue with this personified fragment, exploring the guilt, inevitability, or hidden value we assign to what we cast aside."
},
{
"prompt39": "You are given a single, unmarked seed. Plant it in a pot of soil and place it where you will see it daily. For the next week, keep a log of your observations and the thoughts it provokes. Do you find yourself impatient for a sign of growth, or content with the mystery? How does this small, silent act of fostering potential mirror other, less tangible forms of nurturing in your life? Write about the discipline and faith in hidden processes."
},
{
"prompt40": "Describe a moment of profound stillness you experienced in a normally chaotic environment—a busy train station, a loud household, a crowded market. How did the noise and motion recede into the background, leaving you in a bubble of quiet observation? What details became hyper-visible in this state? Explore the feeling of being an island of calm within a sea of activity, and what this temporary detachment revealed about your connection to the world around you."
},
{
"prompt41": "Recall a piece of practical knowledge you possess that feels almost like a secret—a shortcut, a repair trick, a way of predicting the weather. How did you acquire it? Was it taught, stumbled upon, or earned through failure? Describe the feeling of holding this minor, useful wisdom. When do you choose to share it, and with whom? Explore the value of these small, uncelebrated competencies that help navigate daily life."
},
{
"prompt42": "Choose a tool you use for creation—a pen, a brush, a kitchen knife, a software cursor. Personify it not as a servant, but as a collaborator with its own temperament. Describe its ideal conditions, its quirks, its moments of resistance or fluid grace. Write about a specific project from its perspective. What does it 'feel' as you work? How does the partnership between your intention and its material properties shape the final outcome?"
},
{
"prompt43": "Describe a moment of profound silence you experienced—not just an absence of sound, but a resonant quiet that felt thick and full. Where were you? What thoughts or feelings arose in that space? Did the silence feel like a void or a presence? Explore how this deep quiet contrasted with the usual noise of your life, and what it revealed about your need for stillness or your fear of it."
},
{
"prompt44": "Recall a dream that took place in a liminal setting: an airport terminal, a ferry, a long corridor. What was the feeling of transit in the dream? Were you trying to reach a gate, find a door, or catch a vehicle? Explore what this dream-space might represent in your waking life. What are you in the process of leaving behind, and what are you attempting to board or enter? Write about the symbolism of dream travel."
},
{
"prompt45": "Meditate on the void left by a finished project, a concluded journey, or a resolved conflict. The effort and focus are gone, leaving an empty space where they once lived. Do you feel relief, disorientation, or a quiet emptiness? How do you inhabit this new quiet? Do you rush to fill it, or allow yourself to rest in the void, understanding it as a necessary pause between acts? Describe the landscape of completion."
},
{
"prompt46": "Think of a piece of art, music, or literature that created a profound echo in your soul—something that resonated so deeply it seemed to vibrate within you long after the initial experience. Deconstruct the echo. What specific frequencies (themes, melodies, images) matched your own internal tuning? Has the echo changed over time, growing fainter or merging with other sounds? Write about the anatomy of a lasting resonance."
},
{
"prompt47": "Choose a book you have read multiple times over the years. Each reading has left a layer of understanding, colored by who you were at the time. Open it now and find a heavily annotated page or a familiar passage. Read it as a palimpsest of your former selves. What do the different layers of your marginalia—the underlines, the question marks, the exclamations—reveal about your evolving relationship with the text and with your own mind?"
},
{
"prompt48": "Listen for an echo in your daily life—not a sonic one, but a recurrence. It could be a phrase someone uses that reminds you of another person, a pattern in your mistakes, or a feeling that returns in different circumstances. Trace this echo back to its source. Is it a memory, a habit, or a unresolved piece of your past? Write about the journey of following this reverberation to its origin and understanding why it persists."
},
{
"prompt49": "Imagine you could perceive the subtle, invisible networks that connect all things—the mycelial threads of relationship, influence, and shared history. Choose a single, ordinary object in your room. Trace its hypothetical connections: to the people who made it, the materials that compose it, the places it has been. Write about the moment your perception shifts, and you see not an isolated item, but a luminous node in a vast, humming web of interdependence."
},
{
"prompt50": "You inherit a box of someone else's photographs. The people and places are largely unknown to you. Select one image and build a speculative history for it. Who are the subjects? What was the occasion? What happened just before and just after the shutter clicked? Write the story this silent image suggests, exploring the act of constructing narrative from anonymous fragments."
},
{
"prompt51": "Recall a time you were lost, not in a wilderness, but in a familiar place made strange—perhaps by fog, darkness, or a disorienting emotional state. Describe the moment your internal map failed. How did you navigate without reliable landmarks? What did you discover about your surroundings and yourself in that state of productive disorientation?"
},
{
"prompt52": "Describe a piece of furniture in your home that has been with you through multiple life stages. Chronicle the conversations it has silently witnessed, the weight of different people who have sat upon it, the objects it has held. How has its function or meaning evolved alongside your own story? What would it say if it could speak of the quiet history embedded in its grain and upholstery?"
},
{
"prompt53": "Find a tree with visible scars—from pruning, lightning, disease, or carved initials. Describe these marks as entries in the tree's personal diary. What do they record about survival, interaction, and the passage of time? Imagine the tree's perspective on healing, which does not erase the wound but grows around it, incorporating the damage into its expanding self. What scars of your own have become part of your structure?"
},
{
"prompt54": "Recall a promise you made to yourself long ago—a vow about the person you would become, the life you would lead, or a principle you would never break. Have you kept it? If so, describe the quiet fidelity required. If not, explore the moment and the reasons for the divergence. Does the broken promise feel like a betrayal or an evolution? Is the ghost of that old vow a compassionate or an accusing presence?"
},
{
"prompt55": "Describe a recurring dream you have not had in years, but whose emotional residue still lingers. What was its landscape, its characters, its unspoken rules? Why do you think it has ceased its nocturnal visits? Explore the possibility that it was a messenger whose work is done, or a story your mind no longer needs to tell. What quiet tremor in your waking life might have signaled its departure?"
},
{
"prompt56": "Imagine you could send a message to yourself ten years in the past. You are limited to five words. What would those five words be? Why? Now, imagine receiving a five-word message from your future self, ten years from now. What might it say? Write about the agonizing economy and profound potential of such constrained communication."
},
{
"prompt57": "Observe a shadow throughout the day. It could be the shadow of a tree, a building, or a simple object on your desk. Chronicle its slow, silent journey. How does its shape, length, and sharpness change? Use this as a meditation on time's passage. What is the relationship between the solid object and its fleeting, dependent silhouette?"
},
{
"prompt58": "Contemplate the concept of a 'horizon'—both literal and metaphorical. Describe a time you physically journeyed toward a horizon. What was the experience of it perpetually receding? Now, identify a current personal or professional horizon. How do you navigate toward something that by definition moves as you do? Write about the tension between the journey and the ever-distant line."
},
{
"prompt59": "Describe a food or dish that is deeply connected to a specific memory of a person or place. Go beyond taste. Describe the sounds of its preparation, the smells that filled the air, the textures. Now, attempt to recreate it or seek it out. Does the experience live up to the memory, or does it highlight the irreproducible context of the original moment? Write about the pursuit of sensory time travel."
}
]

22
data/prompts_pool.json
View File

@@ -1,22 +0,0 @@
[
"You are asked to contribute an entry to an 'Encyclopedia of Small Joys.' Your task is to define and describe one specific, minor pleasure in exhaustive, almost scientific detail. What do you choose? (e.g., 'The sound of rain on a skylight,' 'The weight of a sleeping cat on your lap,' 'The first sip of cold water when thirsty'). Detail its parameters, its effects, and the conditions under which it is most potent. Write a loving taxonomy of a tiny delight.",
"Recall a piece of advice you were given that you profoundly disagreed with at the time, but which later revealed a kernel of truth. What was the context? Why did you reject it? What experience or perspective shift allowed you to later understand its value? Write about the slow, often grudging, integration of wisdom that arrives before its time.",
"Describe a handmade gift you once received. Focus not on its monetary value or aesthetic perfection, but on the evidence of the giver's labor—the slightly uneven stitch, the handwritten note, the chosen colors. What does the object communicate about the relationship and the thought behind it? Has your appreciation for it changed over time? Explore the unique language of crafted, imperfect generosity.",
"Imagine you could perceive the emotional weather of the rooms you enter—not as metaphors, but as tangible atmospheres: a tense meeting room might feel thick and staticky, a friend's kitchen might be warm and golden. Describe walking through your day with this synesthetic sense. How would it change your interactions? Would you seek out certain climates and avoid others? Write about navigating the invisible emotional ecosystems we all create and inhabit.",
"Contemplate the concept of 'inventory.' Conduct a non-material inventory of your current state. What are your primary stores of energy, patience, curiosity, and courage? Which are depleted, which are ample? What unseen resources are you drawing upon? Don't judge, simply observe and record. Write about the internal economy that governs your days, and the quiet transactions that fill and drain your reserves.",
"Find a reflection—in a window, a puddle, a darkened screen—that is slightly distorted. Observe your own face or the world through this warped mirror. How does the distortion change your perception? Does it feel revealing, grotesque, or playful? Use this as a starting point to write about the ways our self-perception is always a kind of reflection, subject to the curvature of mood, memory, and context.",
"Recall a time you had to translate something—a concept for a child, a feeling into words, an experience for someone from a different culture. Describe the struggle and creativity of finding equivalences. What was lost in translation? What was unexpectedly clarified or discovered in the attempt? Write about the spaces between languages and understandings, and the bridges we build across them.",
"Describe a smell that instantly transports you to a specific, powerful memory. Don't just name the smell; dissect its components. Where does it take you? Is the memory vivid or fragmented? Does the scent bring comfort, sadness, or a complex mixture? Explore the direct, unmediated pathway that scent has to our past, bypassing conscious thought to drop us into a fully realized moment.",
"Consider the concept of 'drift' in your friendships. Think of a friend from a different chapter of your life with whom you are no longer close. Map the gentle currents of circumstance, geography, or changing interests that created the gradual separation. Do you feel the space between you as a loss, a natural evolution, or both? Write a letter to this friend (not to send) that acknowledges the drift without blame, honoring the shared history while releasing the present connection.",
"You are tasked with writing the instruction manual for a common, everyday object, but from the perspective of the object itself. Choose something simple: a door, a spoon, a light switch. What are its core functions? What are its operating principles? What warnings would it give about misuse? Write the manual with empathy for the object's experience, exploring the hidden life and purpose of the inanimate things we take for granted.",
"Describe witnessing an act of unobserved integrity—someone returning a lost wallet, correcting a mistake that benefited them, choosing honesty when a lie would have been easier. You were the only witness. Why did this act stand out to you? Did it inspire you, shame you, or simply reassure you? Explore the quiet, uncelebrated moral choices that form the ethical bedrock of daily life, and why seeing them matters.",
"Consider the concept of 'gossamer'—something extremely light, delicate, and insubstantial. Identify a gossamer thread in your life: a fragile hope, a half-formed idea, a delicate connection with someone. Describe its texture and how it holds tension. What gentle forces could strengthen it into something more durable, and what rough touch would cause it to snap? Explore the courage and care required to nurture what is barely there.",
"You encounter a 'cryptid' of your own making—a persistent, shadowy feeling or belief that others dismiss or cannot see, yet feels undeniably real to you. Describe its characteristics and habitat within your mind. When does it emerge? What does it feed on? Instead of trying to prove or disprove its existence, write about learning to coexist with this internal mystery, mapping its territory and understanding its role in your personal ecology.",
"Recall a moment of 'volta'—a subtle but definitive turn in a conversation, a relationship, or your understanding of a situation. It wasn't a dramatic reversal, but a quiet pivot point after which things were irrevocably different. Describe the atmosphere just before and just after this turn. What small word, glance, or realization acted as the hinge? Explore the anatomy of quiet change and how we navigate the new direction of a path we thought was straight.",
"Describe a riverbank after the water has receded, leaving behind a layer of fine, damp silt. Observe the patterns it has formed—the ripples, the tiny channels, the imprints of leaves and twigs. This sediment holds the history of the river's recent flow. What has it deposited here? What is now buried, and what is newly revealed on the surface? Write about the slow, patient work of accumulation and what it means to read the stories written in this soft, transitional ground.",
"You discover a series of strange, carved markings—glyphs—on an old piece of furniture or a forgotten wall. They are not a language you recognize. Document their shapes and arrangement. Who might have made them, and for what purpose? Were they a code, a tally, a protective symbol, or simply idle carving? Contemplate the human urge to leave a mark, even an indecipherable one. Write about the silent conversation you attempt to have with this anonymous, enduring message.",
"Recall a conversation overheard in fragments—a murmur from another room, a phone call on a park bench, the distant voices of neighbors. You only catch phrases, tones, and pauses. From these pieces, construct the possible whole. What relationship do the speakers have? What is the context of their discussion? Now, acknowledge the inevitable warp your imagination has applied. Write about the narratives we spin from the incomplete threads of other people's lives, and how this act of listening and inventing reflects our own preoccupations.",
"Recall a moment of pure, unselfconscious play from your childhood—a game of make-believe, a physical gambol in a field or park. Describe the sensation of your body in motion, the rules of the invented world, the feeling of time dissolving. Now, consider the last time you felt a similar, fleeting sense of abandon as an adult. What activity prompted it? Write about the distance between these two experiences and the possibility of inviting more unstructured, joyful movement into your present life.",
"You are given a single, perfect seashell. Hold it to your ear. The old cliché speaks of the ocean's roar, but listen deeper. What else might you fathom in that hollow resonance? The sigh of the creature that once lived there? The whisper of ancient currents? The memory of a distant shore? Now, turn the metaphor inward. What deep, resonant chamber exists within you, and what is the sound it holds when you listen with total, patient attention? Write about the act of listening for the profound in the small and contained.",
"Describe a moment when an emotion—joy, grief, awe, fear—caused a physical quiver in your body. It might have been a shiver down your spine, a tremor in your hands, a catch in your breath. Locate the precise point of origin for this somatic echo. Did the feeling move through you like a wave, or settle in one place? Explore the conversation between your inner state and your physical vessel. How does the body register what the mind cannot yet fully articulate?"
]

19
data/prompts_pool.json.bak
View File

@@ -1,19 +0,0 @@
[
"You are asked to contribute an entry to an 'Encyclopedia of Small Joys.' Your task is to define and describe one specific, minor pleasure in exhaustive, almost scientific detail. What do you choose? (e.g., 'The sound of rain on a skylight,' 'The weight of a sleeping cat on your lap,' 'The first sip of cold water when thirsty'). Detail its parameters, its effects, and the conditions under which it is most potent. Write a loving taxonomy of a tiny delight.",
"Recall a piece of advice you were given that you profoundly disagreed with at the time, but which later revealed a kernel of truth. What was the context? Why did you reject it? What experience or perspective shift allowed you to later understand its value? Write about the slow, often grudging, integration of wisdom that arrives before its time.",
"Describe a handmade gift you once received. Focus not on its monetary value or aesthetic perfection, but on the evidence of the giver's labor—the slightly uneven stitch, the handwritten note, the chosen colors. What does the object communicate about the relationship and the thought behind it? Has your appreciation for it changed over time? Explore the unique language of crafted, imperfect generosity.",
"Imagine you could perceive the emotional weather of the rooms you enter—not as metaphors, but as tangible atmospheres: a tense meeting room might feel thick and staticky, a friend's kitchen might be warm and golden. Describe walking through your day with this synesthetic sense. How would it change your interactions? Would you seek out certain climates and avoid others? Write about navigating the invisible emotional ecosystems we all create and inhabit.",
"Contemplate the concept of 'inventory.' Conduct a non-material inventory of your current state. What are your primary stores of energy, patience, curiosity, and courage? Which are depleted, which are ample? What unseen resources are you drawing upon? Don't judge, simply observe and record. Write about the internal economy that governs your days, and the quiet transactions that fill and drain your reserves.",
"Find a reflection—in a window, a puddle, a darkened screen—that is slightly distorted. Observe your own face or the world through this warped mirror. How does the distortion change your perception? Does it feel revealing, grotesque, or playful? Use this as a starting point to write about the ways our self-perception is always a kind of reflection, subject to the curvature of mood, memory, and context.",
"Recall a time you had to translate something—a concept for a child, a feeling into words, an experience for someone from a different culture. Describe the struggle and creativity of finding equivalences. What was lost in translation? What was unexpectedly clarified or discovered in the attempt? Write about the spaces between languages and understandings, and the bridges we build across them.",
"Describe a smell that instantly transports you to a specific, powerful memory. Don't just name the smell; dissect its components. Where does it take you? Is the memory vivid or fragmented? Does the scent bring comfort, sadness, or a complex mixture? Explore the direct, unmediated pathway that scent has to our past, bypassing conscious thought to drop us into a fully realized moment.",
"Consider the concept of 'drift' in your friendships. Think of a friend from a different chapter of your life with whom you are no longer close. Map the gentle currents of circumstance, geography, or changing interests that created the gradual separation. Do you feel the space between you as a loss, a natural evolution, or both? Write a letter to this friend (not to send) that acknowledges the drift without blame, honoring the shared history while releasing the present connection.",
"You are tasked with writing the instruction manual for a common, everyday object, but from the perspective of the object itself. Choose something simple: a door, a spoon, a light switch. What are its core functions? What are its operating principles? What warnings would it give about misuse? Write the manual with empathy for the object's experience, exploring the hidden life and purpose of the inanimate things we take for granted.",
"Describe witnessing an act of unobserved integrity—someone returning a lost wallet, correcting a mistake that benefited them, choosing honesty when a lie would have been easier. You were the only witness. Why did this act stand out to you? Did it inspire you, shame you, or simply reassure you? Explore the quiet, uncelebrated moral choices that form the ethical bedrock of daily life, and why seeing them matters.",
"Consider the concept of 'gossamer'—something extremely light, delicate, and insubstantial. Identify a gossamer thread in your life: a fragile hope, a half-formed idea, a delicate connection with someone. Describe its texture and how it holds tension. What gentle forces could strengthen it into something more durable, and what rough touch would cause it to snap? Explore the courage and care required to nurture what is barely there.",
"You encounter a 'cryptid' of your own making—a persistent, shadowy feeling or belief that others dismiss or cannot see, yet feels undeniably real to you. Describe its characteristics and habitat within your mind. When does it emerge? What does it feed on? Instead of trying to prove or disprove its existence, write about learning to coexist with this internal mystery, mapping its territory and understanding its role in your personal ecology.",
"Recall a moment of 'volta'—a subtle but definitive turn in a conversation, a relationship, or your understanding of a situation. It wasn't a dramatic reversal, but a quiet pivot point after which things were irrevocably different. Describe the atmosphere just before and just after this turn. What small word, glance, or realization acted as the hinge? Explore the anatomy of quiet change and how we navigate the new direction of a path we thought was straight.",
"Describe a riverbank after the water has receded, leaving behind a layer of fine, damp silt. Observe the patterns it has formed—the ripples, the tiny channels, the imprints of leaves and twigs. This sediment holds the history of the river's recent flow. What has it deposited here? What is now buried, and what is newly revealed on the surface? Write about the slow, patient work of accumulation and what it means to read the stories written in this soft, transitional ground.",
"You discover a series of strange, carved markings—glyphs—on an old piece of furniture or a forgotten wall. They are not a language you recognize. Document their shapes and arrangement. Who might have made them, and for what purpose? Were they a code, a tally, a protective symbol, or simply idle carving? Contemplate the human urge to leave a mark, even an indecipherable one. Write about the silent conversation you attempt to have with this anonymous, enduring message.",
"Recall a conversation overheard in fragments—a murmur from another room, a phone call on a park bench, the distant voices of neighbors. You only catch phrases, tones, and pauses. From these pieces, construct the possible whole. What relationship do the speakers have? What is the context of their discussion? Now, acknowledge the inevitable warp your imagination has applied. Write about the narratives we spin from the incomplete threads of other people's lives, and how this act of listening and inventing reflects our own preoccupations."
]

94
docker-compose.yml
View File

@@ -1,94 +0,0 @@
version: '3.8'
services:
backend:
build: ./backend
container_name: daily-journal-prompt-backend
ports:
- "8000:8000"
volumes:
- ./backend:/app
- ./data:/app/data
environment:
- DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY:-}
- OPENAI_API_KEY=${OPENAI_API_KEY:-}
- API_BASE_URL=${API_BASE_URL:-https://api.deepseek.com}
- MODEL=${MODEL:-deepseek-chat}
- DEBUG=${DEBUG:-false}
- ENVIRONMENT=${ENVIRONMENT:-development}
env_file:
- .env
develop:
watch:
- action: sync
path: ./backend
target: /app
ignore:
- __pycache__/
- .pytest_cache/
- .coverage
- action: rebuild
path: ./backend/requirements.txt
healthcheck:
test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
interval: 30s
timeout: 10s
retries: 3
start_period: 40s
restart: unless-stopped
networks:
- journal-network
frontend:
build: ./frontend
container_name: daily-journal-prompt-frontend
ports:
- "3000:80" # Production frontend on nginx
volumes:
- ./frontend:/app
- /app/node_modules
environment:
- NODE_ENV=${NODE_ENV:-production}
depends_on:
backend:
condition: service_healthy
restart: unless-stopped
networks:
- journal-network
# Development frontend (hot reload)
frontend-dev:
build:
context: ./frontend
target: builder
container_name: daily-journal-prompt-frontend-dev
ports:
- "3001:3000" # Development server on different port
volumes:
- ./frontend:/app
- /app/node_modules
environment:
- NODE_ENV=development
command: npm run dev
develop:
watch:
- action: sync
path: ./frontend/src
target: /app/src
- action: rebuild
path: ./frontend/package.json
depends_on:
backend:
condition: service_healthy
restart: unless-stopped
networks:
- journal-network
networks:
journal-network:
driver: bridge
volumes:
data:
driver: local

9
data/ds_prompt.txt → ds_prompt.txt
View File

@@ -2,7 +2,6 @@ Request for generation of writing prompts for journaling
Payload:
The previous 60 prompts have been provided as a JSON array for reference.
Some vague feedback themes have been provided, each having a weight value from 1 to 6.
Guidelines:
Please generate some number of individual writing prompts in English following these guidelines.
@@ -14,14 +13,6 @@ The provided history brackets two mechanisms.
The history will allow for reducing repetition, however some thematic overlap is acceptable. Try harder to avoid overlap with lower indices in the array.
As the user discards prompts, the themes will be very slowly steered, so it's okay to take some inspiration from the history.
Feedback Themes:
A JSON of single-word feedback themes is provided with each having a weight value from 1 to 6.
Consider these weighted themes only rarely when creating a new writing prompt. Most prompts should be created with full creative freedom.
Only gently influence writing prompts with these. It is better to have all generated prompts ignore a theme than have many reference a theme too overtly.
If a theme word is submitted with a weight of 1, there should be a fair chance that no generated prompts consider it.
If a theme word is submitted with a weight of 6, there should be a high chance at least one generated prompt considers it.
THESE ARE NOT SIMPLY WORDS TO INSERT INTO PROMPTS. They are themes that should only be felt in the background.
Expected Output:
Output as a JSON list with the requested number of elements.
Despite the provided history being a keyed list or dictionary, the expected return JSON will be a simple list with no keys.

92
feedback_historic.json
View File

@@ -1,92 +0,0 @@
[
{
"feedback00": "labyrinth"
},
{
"feedback01": "residue"
},
{
"feedback02": "tremor"
},
{
"feedback03": "effigy"
},
{
"feedback04": "quasar"
},
{
"feedback05": "gossamer"
},
{
"feedback06": "resonance"
},
{
"feedback07": "erosion"
},
{
"feedback08": "surrender"
},
{
"feedback09": "excess"
},
{
"feedback10": "chaos"
},
{
"feedback11": "fabric"
},
{
"feedback12": "palimpsest"
},
{
"feedback13": "lacuna"
},
{
"feedback14": "efflorescence"
},
{
"feedback15": "tessellation"
},
{
"feedback16": "sublimation"
},
{
"feedback17": "vertigo"
},
{
"feedback18": "artifact"
},
{
"feedback19": "mycelium"
},
{
"feedback20": "threshold"
},
{
"feedback21": "cartography"
},
{
"feedback22": "spectacle"
},
{
"feedback23": "friction"
},
{
"feedback24": "mutation"
},
{
"feedback25": "echo"
},
{
"feedback26": "repair"
},
{
"feedback27": "velocity"
},
{
"feedback28": "syntax"
},
{
"feedback29": "divergence"
}
]

26
feedback_words.json
View File

@@ -1,26 +0,0 @@
[
{
"feedback00": "labyrinth",
"weight": 3
},
{
"feedback01": "residue",
"weight": 3
},
{
"feedback02": "tremor",
"weight": 3
},
{
"feedback03": "effigy",
"weight": 3
},
{
"feedback04": "quasar",
"weight": 3
},
{
"feedback05": "gossamer",
"weight": 3
}
]

5
frontend/.astro/settings.json
View File

@@ -1,5 +0,0 @@
{
"_variables": {
"lastUpdateCheck": 1767467593775
}
}

1
frontend/.astro/types.d.ts vendored
View File

@@ -1 +0,0 @@
/// <reference types="astro/client" />

35
frontend/Dockerfile
View File

@@ -1,35 +0,0 @@
FROM node:18-alpine AS builder
WORKDIR /app
# Copy package files
COPY package*.json ./
# Install dependencies
# Use npm install for development (npm ci requires package-lock.json)
RUN npm install
# Copy source code
COPY . .
# Build the application
RUN npm run build
# Production stage
FROM nginx:alpine
# Copy built files from builder stage
COPY --from=builder /app/dist /usr/share/nginx/html
# Copy nginx configuration
COPY nginx.conf /etc/nginx/conf.d/default.conf
# Expose port
EXPOSE 80
# Health check
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD wget --no-verbose --tries=1 --spider http://localhost:80/ || exit 1
CMD ["nginx", "-g", "daemon off;"]

22
frontend/astro.config.mjs
View File

@@ -1,22 +0,0 @@
import { defineConfig } from 'astro/config';
import react from '@astrojs/react';
// https://astro.build/config
export default defineConfig({
integrations: [react()],
server: {
port: 3000,
host: true
},
vite: {
server: {
proxy: {
'/api': {
target: 'http://localhost:8000',
changeOrigin: true,
}
}
}
}
});

49
frontend/nginx.conf
View File

@@ -1,49 +0,0 @@
server {
listen 80;
server_name localhost;
root /usr/share/nginx/html;
index index.html;
# Gzip compression
gzip on;
gzip_vary on;
gzip_min_length 1024;
gzip_types text/plain text/css text/xml text/javascript application/javascript application/xml+rss application/json;
# Security headers
add_header X-Frame-Options "SAMEORIGIN" always;
add_header X-Content-Type-Options "nosniff" always;
add_header X-XSS-Protection "1; mode=block" always;
# Cache static assets
location ~* \.(jpg|jpeg|png|gif|ico|css|js|svg|woff|woff2|ttf|eot)$ {
expires 1y;
add_header Cache-Control "public, immutable";
}
# Handle SPA routing
location / {
try_files $uri $uri/ /index.html;
}
# API proxy for development (in production, this would be handled separately)
location /api/ {
proxy_pass http://backend:8000/api/;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection 'upgrade';
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_cache_bypass $http_upgrade;
}
# Error pages
error_page 404 /index.html;
error_page 500 502 503 504 /50x.html;
location = /50x.html {
root /usr/share/nginx/html;
}
}

21
frontend/package.json
View File

@@ -1,21 +0,0 @@
{
"name": "daily-journal-prompt-frontend",
"type": "module",
"version": "1.0.0",
"description": "Frontend for Daily Journal Prompt Generator",
"scripts": {
"dev": "astro dev",
"build": "astro build",
"preview": "astro preview",
"astro": "astro"
},
"dependencies": {
"astro": "^4.0.0"
},
"devDependencies": {
"@astrojs/react": "^3.0.0",
"react": "^18.0.0",
"react-dom": "^18.0.0"
}
}

220
frontend/src/components/FeedbackWeighting.jsx
View File

@@ -1,220 +0,0 @@
import React, { useState, useEffect } from 'react';
const FeedbackWeighting = ({ onComplete, onCancel }) => {
const [feedbackWords, setFeedbackWords] = useState([]);
const [loading, setLoading] = useState(true);
const [error, setError] = useState(null);
const [submitting, setSubmitting] = useState(false);
const [weights, setWeights] = useState({});
useEffect(() => {
fetchQueuedFeedbackWords();
}, []);
const fetchQueuedFeedbackWords = async () => {
setLoading(true);
setError(null);
try {
const response = await fetch('/api/v1/feedback/queued');
if (response.ok) {
const data = await response.json();
const words = data.queued_words || [];
setFeedbackWords(words);
// Initialize weights state
const initialWeights = {};
words.forEach(word => {
initialWeights[word.word] = word.weight;
});
setWeights(initialWeights);
} else {
throw new Error(`Failed to fetch feedback words: ${response.status}`);
}
} catch (err) {
console.error('Error fetching feedback words:', err);
setError('Failed to load feedback words. Please try again.');
// Fallback to mock data for development
const mockWords = [
{ key: 'feedback00', word: 'labyrinth', weight: 3 },
{ key: 'feedback01', word: 'residue', weight: 3 },
{ key: 'feedback02', word: 'tremor', weight: 3 },
{ key: 'feedback03', word: 'effigy', weight: 3 },
{ key: 'feedback04', word: 'quasar', weight: 3 },
{ key: 'feedback05', word: 'gossamer', weight: 3 }
];
setFeedbackWords(mockWords);
const initialWeights = {};
mockWords.forEach(word => {
initialWeights[word.word] = word.weight;
});
setWeights(initialWeights);
} finally {
setLoading(false);
}
};
const handleWeightChange = (word, newWeight) => {
setWeights(prev => ({
...prev,
[word]: newWeight
}));
};
const handleSubmit = async () => {
setSubmitting(true);
setError(null);
try {
const response = await fetch('/api/v1/feedback/rate', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({ ratings: weights })
});
if (response.ok) {
const data = await response.json();
console.log('Feedback words rated successfully:', data);
// Call onComplete callback if provided
if (onComplete) {
onComplete(data);
}
} else {
const errorData = await response.json();
throw new Error(errorData.detail || `Failed to rate feedback words: ${response.status}`);
}
} catch (err) {
console.error('Error rating feedback words:', err);
setError(`Failed to submit ratings: ${err.message}`);
} finally {
setSubmitting(false);
}
};
if (loading) {
return (
<div className="bg-white rounded-lg shadow-md p-6 mb-6">
<div className="flex items-center justify-center py-8">
<div className="animate-spin rounded-full h-12 w-12 border-b-2 border-blue-500"></div>
<span className="ml-3 text-gray-600">Loading feedback words...</span>
</div>
</div>
);
}
return (
<div className="bg-white rounded-lg shadow-md p-6 mb-6">
<div className="flex justify-between items-center mb-6">
<h2 className="text-xl font-bold text-gray-800">
Rate Feedback Words
</h2>
<button
onClick={onCancel}
className="text-gray-500 hover:text-gray-700"
title="Cancel"
>
<i className="fas fa-times text-xl"></i>
</button>
</div>
{error && (
<div className="bg-red-50 border-l-4 border-red-400 p-4 mb-6">
<div className="flex">
<div className="flex-shrink-0">
<i className="fas fa-exclamation-circle text-red-400"></i>
</div>
<div className="ml-3">
<p className="text-sm text-red-700">{error}</p>
</div>
</div>
</div>
)}
<div className="space-y-4">
{feedbackWords.map((item, index) => (
<div key={item.key} className="border border-gray-200 rounded-lg p-4">
<div className="mb-3">
<h3 className="text-lg font-semibold text-gray-800 mb-2">
{item.word}
</h3>
<div className="relative">
<input
type="range"
min="0"
max="6"
value={weights[item.word] || 3}
onChange={(e) => handleWeightChange(item.word, parseInt(e.target.value))}
className="w-full h-8 bg-gray-200 rounded-lg appearance-none cursor-pointer slider-thumb-hidden"
style={{
background: `linear-gradient(to right, #ef4444 0%, #f97316 16.67%, #eab308 33.33%, #22c55e 50%, #3b82f6 66.67%, #8b5cf6 83.33%, #a855f7 100%)`
}}
/>
</div>
</div>
</div>
))}
</div>
<div className="mt-8 pt-6 border-t border-gray-200">
<div className="flex justify-end space-x-3">
<button
onClick={onCancel}
className="px-4 py-2 border border-gray-300 rounded-md text-gray-700 hover:bg-gray-50 focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-gray-500"
disabled={submitting}
>
Cancel
</button>
<button
onClick={handleSubmit}
disabled={submitting}
className="px-4 py-2 bg-blue-500 text-white rounded-md hover:bg-blue-600 focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-blue-500 disabled:opacity-50 disabled:cursor-not-allowed"
>
{submitting ? (
<>
<i className="fas fa-spinner fa-spin mr-2"></i>
Submitting...
</>
) : (
<>
<i className="fas fa-check mr-2"></i>
Submit
</>
)}
</button>
</div>
</div>
<style jsx>{`
.slider-thumb-hidden::-webkit-slider-thumb {
-webkit-appearance: none;
appearance: none;
width: 24px;
height: 24px;
background: #3b82f6;
border-radius: 50%;
cursor: pointer;
border: 2px solid white;
box-shadow: 0 2px 4px rgba(0,0,0,0.2);
}
.slider-thumb-hidden::-moz-range-thumb {
width: 24px;
height: 24px;
background: #3b82f6;
border-radius: 50%;
cursor: pointer;
border: 2px solid white;
box-shadow: 0 2px 4px rgba(0,0,0,0.2);
}
`}</style>
</div>
);
};
export default FeedbackWeighting;

336
frontend/src/components/PromptDisplay.jsx
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@@ -1,336 +0,0 @@
import React, { useState, useEffect } from 'react';
import FeedbackWeighting from './FeedbackWeighting';
const PromptDisplay = () => {
const [prompts, setPrompts] = useState([]); // Changed to array to handle multiple prompts
const [loading, setLoading] = useState(true);
const [error, setError] = useState(null);
const [selectedIndex, setSelectedIndex] = useState(null);
const [viewMode, setViewMode] = useState('history'); // 'history' or 'drawn'
const [poolStats, setPoolStats] = useState({
total: 0,
target: 20,
sessions: 0,
needsRefill: true
});
const [showFeedbackWeighting, setShowFeedbackWeighting] = useState(false);
const [fillPoolLoading, setFillPoolLoading] = useState(false);
const [drawButtonDisabled, setDrawButtonDisabled] = useState(false);
useEffect(() => {
fetchMostRecentPrompt();
fetchPoolStats();
}, []);
const fetchMostRecentPrompt = async () => {
setLoading(true);
setError(null);
setDrawButtonDisabled(false); // Re-enable draw button when returning to history view
try {
// Try to fetch from actual API first
const response = await fetch('/api/v1/prompts/history');
if (response.ok) {
const data = await response.json();
// API returns array directly, not object with 'prompts' key
if (Array.isArray(data) && data.length > 0) {
// Get the most recent prompt (first in array, position 0)
// Show only one prompt from history
setPrompts([{ text: data[0].text, position: data[0].position }]);
setViewMode('history');
} else {
// No history yet, show placeholder
setPrompts([{ text: "No recent prompts in history. Draw some prompts to get started!", position: 0 }]);
}
} else {
// API not available, use mock data
setPrompts([{ text: "Write about a time when you felt completely at peace with yourself and the world around you. What were the circumstances that led to this feeling, and how did it change your perspective on life?", position: 0 }]);
}
} catch (err) {
console.error('Error fetching prompt:', err);
// Fallback to mock data
setPrompts([{ text: "Imagine you could have a conversation with your future self 10 years from now. What questions would you ask, and what advice do you think your future self would give you?", position: 0 }]);
} finally {
setLoading(false);
}
};
const handleDrawPrompts = async () => {
setDrawButtonDisabled(true); // Disable the button when clicked
setLoading(true);
setError(null);
setSelectedIndex(null);
try {
// Draw 3 prompts from pool (Task 4)
const response = await fetch('/api/v1/prompts/draw?count=3');
if (response.ok) {
const data = await response.json();
// Draw API returns object with 'prompts' array
if (data.prompts && data.prompts.length > 0) {
// Show all drawn prompts
const drawnPrompts = data.prompts.map((text, index) => ({
text,
position: index
}));
setPrompts(drawnPrompts);
setViewMode('drawn');
} else {
setError('No prompts available in pool. Please fill the pool first.');
}
} else {
setError('Failed to draw prompts. Please try again.');
}
} catch (err) {
setError('Failed to draw prompts. Please try again.');
} finally {
setLoading(false);
}
};
const handleAddToHistory = async (index) => {
if (index < 0 || index >= prompts.length) {
setError('Invalid prompt index');
return;
}
try {
const promptText = prompts[index].text;
// Send the prompt to the API to add to history
const response = await fetch('/api/v1/prompts/select', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({ prompt_text: promptText }),
});
if (response.ok) {
const data = await response.json();
// Mark as selected and show success
setSelectedIndex(index);
// Refresh the page to show the updated history and pool stats
// The default view shows the most recent prompt from history (position 0)
fetchMostRecentPrompt();
fetchPoolStats();
setDrawButtonDisabled(false); // Re-enable draw button after selection
} else {
const errorData = await response.json();
setError(`Failed to add prompt to history: ${errorData.detail || 'Unknown error'}`);
}
} catch (err) {
setError('Failed to add prompt to history');
}
};
const fetchPoolStats = async () => {
try {
const response = await fetch('/api/v1/prompts/stats');
if (response.ok) {
const data = await response.json();
setPoolStats({
total: data.total_prompts || 0,
target: data.target_pool_size || 20,
sessions: data.available_sessions || 0,
needsRefill: data.needs_refill || true
});
}
} catch (err) {
console.error('Error fetching pool stats:', err);
}
};
const handleFillPool = async () => {
// Start pool refill immediately (uses active words 6-11)
setFillPoolLoading(true);
setError(null);
try {
const response = await fetch('/api/v1/prompts/fill-pool', { method: 'POST' });
if (response.ok) {
const data = await response.json();
console.log('Pool refill started:', data);
// Pool refill started successfully, now show feedback weighting UI
setShowFeedbackWeighting(true);
} else {
const errorData = await response.json();
throw new Error(errorData.detail || `Failed to start pool refill: ${response.status}`);
}
} catch (err) {
console.error('Error starting pool refill:', err);
setError(`Failed to start pool refill: ${err.message}`);
} finally {
setFillPoolLoading(false);
}
};
const handleFeedbackComplete = async (feedbackData) => {
// After feedback is submitted, refresh the UI
setShowFeedbackWeighting(false);
// Refresh the prompt and pool stats
fetchMostRecentPrompt();
fetchPoolStats();
};
const handleFeedbackCancel = () => {
setShowFeedbackWeighting(false);
};
if (showFeedbackWeighting) {
return (
<FeedbackWeighting
onComplete={handleFeedbackComplete}
onCancel={handleFeedbackCancel}
/>
);
}
if (fillPoolLoading) {
return (
<div className="bg-white rounded-lg shadow-md p-6 mb-6">
<div className="flex items-center justify-center py-8">
<div className="animate-spin rounded-full h-12 w-12 border-b-2 border-blue-500"></div>
<span className="ml-3 text-gray-600">Filling prompt pool...</span>
</div>
</div>
);
}
if (error) {
return (
<div className="alert alert-error">
<i className="fas fa-exclamation-circle mr-2"></i>
{error}
</div>
);
}
return (
<div>
{prompts.length > 0 ? (
<>
<div className="mb-6">
<div className="grid grid-cols-1 gap-4">
{prompts.map((promptObj, index) => (
<div
key={index}
className={`prompt-card ${viewMode === 'drawn' ? 'cursor-pointer' : ''} ${selectedIndex === index ? 'selected' : ''}`}
onClick={viewMode === 'drawn' ? () => setSelectedIndex(index) : undefined}
>
<div className="flex items-start gap-3">
<div className={`flex-shrink-0 w-8 h-8 rounded-full flex items-center justify-center ${selectedIndex === index ? 'bg-green-100 text-green-600' : 'bg-blue-100 text-blue-600'}`}>
{selectedIndex === index ? (
<i className="fas fa-check"></i>
) : (
<span>{index + 1}</span>
)}
</div>
<div className="flex-grow">
<p className="prompt-text">{promptObj.text}</p>
<div className="prompt-meta">
<span>
<i className="fas fa-ruler-combined mr-1"></i>
{promptObj.text.length} characters
</span>
<span>
{viewMode === 'drawn' ? (
selectedIndex === index ? (
<span className="text-green-600">
<i className="fas fa-check-circle mr-1"></i>
Selected
</span>
) : (
<span className="text-gray-500">
Click to select
</span>
)
) : (
<span className="text-gray-600">
<i className="fas fa-history mr-1"></i>
Most recent from history
</span>
)}
</span>
</div>
</div>
</div>
</div>
))}
</div>
</div>
<div className="flex flex-col gap-4">
<div className="flex gap-2">
{viewMode === 'drawn' && (
<button
className="btn btn-success w-1/2"
onClick={() => handleAddToHistory(selectedIndex !== null ? selectedIndex : 0)}
disabled={selectedIndex === null}
>
<i className="fas fa-history"></i>
{selectedIndex !== null ? 'Use Selected Prompt' : 'Select a Prompt First'}
</button>
)}
<button
className={`btn btn-primary ${viewMode === 'drawn' ? 'w-1/2' : 'w-full'}`}
onClick={handleDrawPrompts}
disabled={drawButtonDisabled}
>
<i className="fas fa-dice"></i>
{viewMode === 'history' ? 'Draw 3 New Prompts' : 'Draw 3 More Prompts'}
</button>
</div>
<div className="">
<button className="btn btn-secondary w-full relative overflow-hidden" onClick={handleFillPool}>
<div className="absolute top-0 left-0 h-full bg-green-500 opacity-20 transition-all duration-300"
style={{ width: `${Math.min((poolStats.total / poolStats.target) * 100, 100)}%` }}>
</div>
<div className="relative z-10 flex items-center justify-center gap-2">
<i className="fas fa-sync"></i>
<span>Fill Prompt Pool ({poolStats.total}/{poolStats.target})</span>
</div>
</button>
<div className="text-xs text-gray-600 mt-1 text-center">
{Math.round((poolStats.total / poolStats.target) * 100)}% full
</div>
</div>
</div>
<div className="mt-6 text-sm text-gray-600">
<p>
<i className="fas fa-info-circle mr-1"></i>
<strong>
{viewMode === 'history' ? 'Most Recent Prompt from History' : `${prompts.length} Drawn Prompts`}:
</strong>
{viewMode === 'history'
? ' This is the latest prompt from your history. Using it helps the AI learn your preferences.'
: ' Select a prompt to use for journaling. The AI will learn from your selection.'}
</p>
<p className="mt-2">
<i className="fas fa-lightbulb mr-1"></i>
<strong>Tip:</strong> The prompt pool needs regular refilling. Check the stats panel
to see how full it is.
</p>
</div>
</>
) : (
<div className="text-center p-8">
<i className="fas fa-inbox fa-3x mb-4" style={{ color: 'var(--gray-color)' }}></i>
<h3>No Prompts Available</h3>
<p className="mb-4">There are no prompts in history or pool. Get started by filling the pool.</p>
<button className="btn btn-primary" onClick={handleFillPool}>
<i className="fas fa-plus"></i> Fill Prompt Pool
</button>
</div>
)}
</div>
);
};
export default PromptDisplay;

189
frontend/src/components/StatsDashboard.jsx
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@@ -1,189 +0,0 @@
import React, { useState, useEffect } from 'react';
const StatsDashboard = () => {
const [stats, setStats] = useState({
pool: {
total: 0,
target: 20,
sessions: 0,
needsRefill: true
},
history: {
total: 0,
capacity: 60,
available: 60,
isFull: false
}
});
const [loading, setLoading] = useState(true);
useEffect(() => {
fetchStats();
}, []);
const fetchStats = async () => {
try {
// Fetch pool stats
const poolResponse = await fetch('/api/v1/prompts/stats');
const poolData = poolResponse.ok ? await poolResponse.json() : {
total_prompts: 0,
target_pool_size: 20,
available_sessions: 0,
needs_refill: true
};
// Fetch history stats
const historyResponse = await fetch('/api/v1/prompts/history/stats');
const historyData = historyResponse.ok ? await historyResponse.json() : {
total_prompts: 0,
history_capacity: 60,
available_slots: 60,
is_full: false
};
setStats({
pool: {
total: poolData.total_prompts || 0,
target: poolData.target_pool_size || 20,
sessions: poolData.available_sessions || 0,
needsRefill: poolData.needs_refill || true
},
history: {
total: historyData.total_prompts || 0,
capacity: historyData.history_capacity || 60,
available: historyData.available_slots || 60,
isFull: historyData.is_full || false
}
});
} catch (error) {
console.error('Error fetching stats:', error);
// Use default values on error
} finally {
setLoading(false);
}
};
const handleFillPool = async () => {
try {
const response = await fetch('/api/v1/prompts/fill-pool', { method: 'POST' });
if (response.ok) {
// Refresh stats - no alert needed, UI will show updated stats
fetchStats();
} else {
alert('Failed to fill prompt pool');
}
} catch (error) {
alert('Failed to fill prompt pool');
}
};
if (loading) {
return (
<div className="text-center p-4">
<div className="spinner mx-auto"></div>
<p className="mt-2 text-sm">Loading stats...</p>
</div>
);
}
return (
<div>
<div className="flex justify-between items-center mb-4">
<h3 className="text-lg font-semibold">Quick Stats</h3>
<button
className="btn btn-secondary btn-sm"
onClick={fetchStats}
disabled={loading}
>
<i className="fas fa-sync"></i>
Refresh
</button>
</div>
<div className="grid grid-cols-2 gap-4 mb-6">
<div className="stats-card">
<div className="p-3">
<i className="fas fa-database fa-2x mb-2" style={{ color: 'var(--primary-color)' }}></i>
<div className="stats-value">{stats.pool.total}</div>
<div className="stats-label">Prompts in Pool</div>
<div className="mt-2 text-sm">
Target: {stats.pool.target}
</div>
</div>
</div>
<div className="stats-card">
<div className="p-3">
<i className="fas fa-history fa-2x mb-2" style={{ color: 'var(--secondary-color)' }}></i>
<div className="stats-value">{stats.history.total}</div>
<div className="stats-label">History Items</div>
<div className="mt-2 text-sm">
Capacity: {stats.history.capacity}
</div>
</div>
</div>
</div>
<div className="space-y-4">
<div>
<div className="flex justify-between items-center mb-1">
<span className="text-sm font-medium">Prompt Pool</span>
<span className="text-sm">{stats.pool.total}/{stats.pool.target}</span>
</div>
<div className="w-full bg-gray-200 rounded-full h-2">
<div
className="bg-blue-600 h-2 rounded-full transition-all duration-300"
style={{ width: `${Math.min((stats.pool.total / stats.pool.target) * 100, 100)}%` }}
></div>
</div>
</div>
<div>
<div className="flex justify-between items-center mb-1">
<span className="text-sm font-medium">Prompt History</span>
<span className="text-sm">{stats.history.total}/{stats.history.capacity}</span>
</div>
<div className="w-full bg-gray-200 rounded-full h-2">
<div
className="bg-purple-600 h-2 rounded-full transition-all duration-300"
style={{ width: `${Math.min((stats.history.total / stats.history.capacity) * 100, 100)}%` }}
></div>
</div>
</div>
</div>
<div className="mt-6">
<ul className="space-y-2 text-sm">
<li className="flex items-start">
<i className="fas fa-calendar-day text-blue-600 mt-1 mr-2"></i>
<span>
<strong>{stats.pool.sessions} sessions</strong> available in pool
</span>
</li>
<li className="flex items-start">
<i className="fas fa-bolt text-yellow-600 mt-1 mr-2"></i>
<span>
<span className="text-gray-600">Pool is {Math.round((stats.pool.total / stats.pool.target) * 100)}% full</span>
</span>
</li>
<li className="flex items-start">
<i className="fas fa-brain text-purple-600 mt-1 mr-2"></i>
<span>
AI has learned from <strong>{stats.history.total} prompts</strong> in history
</span>
</li>
<li className="flex items-start">
<i className="fas fa-chart-line text-green-600 mt-1 mr-2"></i>
<span>
History is <strong>{Math.round((stats.history.total / stats.history.capacity) * 100)}% full</strong>
</span>
</li>
</ul>
</div>
</div>
);
};
export default StatsDashboard;

1
frontend/src/env.d.ts vendored
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@@ -1 +0,0 @@
/// <reference path="../.astro/types.d.ts" />

137
frontend/src/layouts/Layout.astro
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@@ -1,137 +0,0 @@
---
import '../styles/global.css';
---
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Daily Journal Prompt Generator</title>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css" />
</head>
<body>
<header>
<nav>
<div class="logo">
<i class="fas fa-book-open"></i>
<h1>daily-journal-prompt</h1>
</div>
<div class="nav-links">
<a href="/"><i class="fas fa-home"></i> Home</a>
<a href="/api/v1/prompts/history"><i class="fas fa-history"></i> History</a>
<a href="/api/v1/prompts/stats"><i class="fas fa-chart-bar"></i> Stats</a>
</div>
</nav>
</header>
<main>
<slot />
</main>
<footer>
<p>daily-journal-prompt &copy; 2026</p>
</footer>
</body>
</html>
<style>
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, sans-serif;
line-height: 1.6;
color: #333;
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
min-height: 100vh;
}
header {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
padding: 1rem 2rem;
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
}
nav {
display: flex;
justify-content: space-between;
align-items: center;
max-width: 1200px;
margin: 0 auto;
}
.logo {
display: flex;
align-items: center;
gap: 1rem;
}
.logo i {
font-size: 2rem;
}
.logo h1 {
font-size: 1.5rem;
font-weight: 600;
}
.nav-links {
display: flex;
gap: 2rem;
}
.nav-links a {
color: white;
text-decoration: none;
display: flex;
align-items: center;
gap: 0.5rem;
padding: 0.5rem 1rem;
border-radius: 4px;
transition: background-color 0.3s;
}
.nav-links a:hover {
background-color: rgba(255, 255, 255, 0.1);
}
main {
max-width: 1200px;
margin: 2rem auto;
padding: 0 2rem;
}
footer {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
text-align: center;
padding: 2rem;
margin-top: 3rem;
}
footer p {
margin: 0.5rem 0;
}
@media (max-width: 768px) {
nav {
flex-direction: column;
gap: 1rem;
}
.nav-links {
width: 100%;
justify-content: center;
}
main {
padding: 0 1rem;
}
}
</style>

76
frontend/src/pages/index.astro
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@@ -1,76 +0,0 @@
---
import Layout from '../layouts/Layout.astro';
import PromptDisplay from '../components/PromptDisplay.jsx';
import StatsDashboard from '../components/StatsDashboard.jsx';
---
<Layout>
<div class="container">
<div class="grid grid-cols-1 lg:grid-cols-3 gap-4">
<div class="lg:col-span-2">
<div class="card">
<div class="card-header">
<h2><i class="fas fa-scroll"></i> Today's Writing Prompt</h2>
</div>
<PromptDisplay client:load />
</div>
</div>
<div>
<div class="card">
<div class="card-header">
<h2><i class="fas fa-chart-bar"></i> Quick Stats</h2>
</div>
<StatsDashboard client:load />
</div>
<div class="card mt-4">
<div class="card-header">
<h2><i class="fas fa-lightbulb"></i> Quick Actions</h2>
</div>
<div class="flex flex-col gap-2">
<button class="btn btn-warning" onclick="window.location.href='/api/v1/prompts/history'">
<i class="fas fa-history"></i> View History (API)
</button>
</div>
</div>
</div>
</div>
<div class="card mt-4">
<div class="card-header">
<h2><i class="fas fa-info-circle"></i> How It Works</h2>
</div>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4">
<div class="text-center">
<div class="p-4">
<i class="fas fa-robot fa-3x mb-3" style="color: var(--primary-color);"></i>
<h3>AI-Powered</h3>
<p>Prompts are generated using AI models trained on creative writing</p>
</div>
</div>
<div class="text-center">
<div class="p-4">
<i class="fas fa-brain fa-3x mb-3" style="color: var(--secondary-color);"></i>
<h3>Smart History</h3>
<p>The AI learns from your previous prompts to avoid repetition and improve relevance</p>
</div>
</div>
<div class="text-center">
<div class="p-4">
<i class="fas fa-battery-full fa-3x mb-3" style="color: var(--success-color);"></i>
<h3>Prompt Pool</h3>
<p>Prompt pool caching system is a proof of concept with the ultimate goal being offline use on mobile devices. Airplane mode is a path to distraction-free writing.</p>
</div>
</div>
</div>
</div>
</div>
</Layout>

361
frontend/src/styles/global.css
View File

@@ -1,361 +0,0 @@
/* Global styles for Daily Journal Prompt Generator */
:root {
--primary-color: #667eea;
--secondary-color: #764ba2;
--accent-color: #f56565;
--success-color: #48bb78;
--warning-color: #ed8936;
--info-color: #4299e1;
--light-color: #f7fafc;
--dark-color: #2d3748;
--gray-color: #a0aec0;
--border-radius: 8px;
--box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
--transition: all 0.3s ease;
}
/* Reset and base styles */
* {
margin: 0;
padding: 0;
box-sizing: border-box;
}
body {
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, sans-serif;
line-height: 1.6;
color: var(--dark-color);
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
min-height: 100vh;
}
/* Typography */
h1, h2, h3, h4, h5, h6 {
font-weight: 600;
line-height: 1.2;
margin-bottom: 1rem;
color: var(--dark-color);
}
h1 {
font-size: 2.5rem;
}
h2 {
font-size: 2rem;
}
h3 {
font-size: 1.5rem;
}
p {
margin-bottom: 1rem;
}
a {
color: var(--primary-color);
text-decoration: none;
transition: var(--transition);
}
a:hover {
color: var(--secondary-color);
}
/* Buttons */
.btn {
display: inline-flex;
align-items: center;
justify-content: center;
gap: 0.5rem;
padding: 0.75rem 1.5rem;
border: none;
border-radius: var(--border-radius);
font-size: 1rem;
font-weight: 600;
cursor: pointer;
transition: var(--transition);
text-decoration: none;
}
.btn-primary {
background: linear-gradient(135deg, var(--primary-color) 0%, var(--secondary-color) 100%);
color: white;
}
.btn-primary:hover {
box-shadow: 0 6px 12px rgba(0, 0, 0, 0.15);
opacity: 0.95;
}
.btn-secondary {
background-color: white;
color: var(--primary-color);
border: 2px solid var(--primary-color);
}
.btn-secondary:hover {
background-color: var(--primary-color);
color: white;
}
.btn-success {
background-color: var(--success-color);
color: white;
}
.btn-warning {
background-color: var(--warning-color);
color: white;
}
.btn-danger {
background-color: var(--accent-color);
color: white;
}
.btn:disabled {
opacity: 0.6;
cursor: not-allowed;
transform: none !important;
}
/* Cards */
.card {
background: white;
border-radius: var(--border-radius);
box-shadow: var(--box-shadow);
padding: 1.5rem;
margin-bottom: 1.5rem;
transition: var(--transition);
}
.card:hover {
box-shadow: 0 8px 16px rgba(0, 0, 0, 0.1);
}
.card-header {
display: flex;
justify-content: space-between;
align-items: center;
margin-bottom: 1rem;
padding-bottom: 0.5rem;
border-bottom: 2px solid var(--light-color);
}
/* Forms */
.form-group {
margin-bottom: 1.5rem;
}
.form-label {
display: block;
margin-bottom: 0.5rem;
font-weight: 600;
color: var(--dark-color);
}
.form-control {
width: 100%;
padding: 0.75rem;
border: 2px solid var(--gray-color);
border-radius: var(--border-radius);
font-size: 1rem;
transition: var(--transition);
}
.form-control:focus {
outline: none;
border-color: var(--primary-color);
box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1);
}
.form-control.error {
border-color: var(--accent-color);
}
.form-error {
color: var(--accent-color);
font-size: 0.875rem;
margin-top: 0.25rem;
}
/* Alerts */
.alert {
padding: 1rem;
border-radius: var(--border-radius);
margin-bottom: 1rem;
border-left: 4px solid;
}
.alert-success {
background-color: rgba(72, 187, 120, 0.1);
border-left-color: var(--success-color);
color: #22543d;
}
.alert-warning {
background-color: rgba(237, 137, 54, 0.1);
border-left-color: var(--warning-color);
color: #744210;
}
.alert-error {
background-color: rgba(245, 101, 101, 0.1);
border-left-color: var(--accent-color);
color: #742a2a;
}
.alert-info {
background-color: rgba(66, 153, 225, 0.1);
border-left-color: var(--info-color);
color: #2a4365;
}
/* Loading spinner */
.spinner {
display: inline-block;
width: 2rem;
height: 2rem;
border: 3px solid rgba(0, 0, 0, 0.1);
border-radius: 50%;
border-top-color: var(--primary-color);
animation: spin 1s ease-in-out infinite;
}
@keyframes spin {
to {
transform: rotate(360deg);
}
}
/* Utility classes */
.container {
max-width: 1200px;
margin: 0 auto;
padding: 0 1rem;
}
.text-center {
text-align: center;
}
.mt-1 { margin-top: 0.5rem; }
.mt-2 { margin-top: 1rem; }
.mt-3 { margin-top: 1.5rem; }
.mt-4 { margin-top: 2rem; }
.mb-1 { margin-bottom: 0.5rem; }
.mb-2 { margin-bottom: 1rem; }
.mb-3 { margin-bottom: 1.5rem; }
.mb-4 { margin-bottom: 2rem; }
.p-1 { padding: 0.5rem; }
.p-2 { padding: 1rem; }
.p-3 { padding: 1.5rem; }
.p-4 { padding: 2rem; }
.flex {
display: flex;
}
.flex-col {
flex-direction: column;
}
.items-center {
align-items: center;
}
.justify-between {
justify-content: space-between;
}
.justify-center {
justify-content: center;
}
.gap-1 { gap: 0.5rem; }
.gap-2 { gap: 1rem; }
.gap-3 { gap: 1.5rem; }
.gap-4 { gap: 2rem; }
.grid {
display: grid;
gap: 1.5rem;
}
.grid-cols-1 { grid-template-columns: 1fr; }
.grid-cols-2 { grid-template-columns: repeat(2, 1fr); }
.grid-cols-3 { grid-template-columns: repeat(3, 1fr); }
.grid-cols-4 { grid-template-columns: repeat(4, 1fr); }
@media (max-width: 768px) {
.grid-cols-2,
.grid-cols-3,
.grid-cols-4 {
grid-template-columns: 1fr;
}
h1 {
font-size: 2rem;
}
h2 {
font-size: 1.5rem;
}
.btn {
padding: 0.5rem 1rem;
}
}
/* Prompt card specific styles */
.prompt-card {
background: linear-gradient(135deg, #ffffff 0%, #f8f9fa 100%);
border-left: 4px solid var(--primary-color);
}
.prompt-card.selected {
border-left-color: var(--success-color);
background: linear-gradient(135deg, #f0fff4 0%, #e6fffa 100%);
}
.prompt-text {
font-size: 1.1rem;
line-height: 1.8;
color: var(--dark-color);
}
.prompt-meta {
display: flex;
justify-content: space-between;
align-items: center;
margin-top: 1rem;
padding-top: 1rem;
border-top: 1px solid var(--light-color);
font-size: 0.875rem;
color: var(--gray-color);
}
/* Stats cards */
.stats-card {
text-align: center;
}
.stats-value {
font-size: 2.5rem;
font-weight: 700;
color: var(--primary-color);
margin: 0.5rem 0;
}
.stats-label {
font-size: 0.875rem;
color: var(--gray-color);
text-transform: uppercase;
letter-spacing: 0.05em;
}

341
generate_prompts.py
View File

@@ -30,8 +30,6 @@ class JournalPromptGenerator:
self.client = None
self.historic_prompts = []
self.pool_prompts = []
self.feedback_words = []
self.feedback_historic = []
self.prompt_template = ""
self.settings = {}
@@ -43,8 +41,6 @@ class JournalPromptGenerator:
self._load_prompt_template()
self._load_historic_prompts()
self._load_pool_prompts()
self._load_feedback_words()
self._load_feedback_historic()
def _load_config(self):
"""Load configuration from environment file."""
@@ -124,13 +120,13 @@ class JournalPromptGenerator:
def _load_historic_prompts(self):
"""Load historic prompts from JSON file."""
try:
with open("prompts_historic.json", "r") as f:
with open("historic_prompts.json", "r") as f:
self.historic_prompts = json.load(f)
except FileNotFoundError:
self.console.print("[yellow]Warning: prompts_historic.json not found, starting with empty history[/yellow]")
self.console.print("[yellow]Warning: historic_prompts.json not found, starting with empty history[/yellow]")
self.historic_prompts = []
except json.JSONDecodeError:
self.console.print("[yellow]Warning: prompts_historic.json is corrupted, starting with empty history[/yellow]")
self.console.print("[yellow]Warning: historic_prompts.json is corrupted, starting with empty history[/yellow]")
self.historic_prompts = []
def _save_historic_prompts(self):
@@ -139,62 +135,24 @@ class JournalPromptGenerator:
if len(self.historic_prompts) > 60:
self.historic_prompts = self.historic_prompts[:60]
with open("prompts_historic.json", "w") as f:
with open("historic_prompts.json", "w") as f:
json.dump(self.historic_prompts, f, indent=2)
def _load_pool_prompts(self):
"""Load pool prompts from JSON file."""
try:
with open("prompts_pool.json", "r") as f:
with open("pool_prompts.json", "r") as f:
self.pool_prompts = json.load(f)
except FileNotFoundError:
self.console.print("[yellow]Warning: prompts_pool.json not found, starting with empty pool[/yellow]")
self.console.print("[yellow]Warning: pool_prompts.json not found, starting with empty pool[/yellow]")
self.pool_prompts = []
except json.JSONDecodeError:
self.console.print("[yellow]Warning: prompts_pool.json is corrupted, starting with empty pool[/yellow]")
self.console.print("[yellow]Warning: pool_prompts.json is corrupted, starting with empty pool[/yellow]")
self.pool_prompts = []
def _load_feedback_words(self):
"""Load feedback words from JSON file."""
try:
with open("feedback_words.json", "r") as f:
self.feedback_words = json.load(f)
except FileNotFoundError:
self.console.print("[yellow]Warning: feedback_words.json not found, starting with empty feedback words[/yellow]")
self.feedback_words = []
except json.JSONDecodeError:
self.console.print("[yellow]Warning: feedback_words.json is corrupted, starting with empty feedback words[/yellow]")
self.feedback_words = []
def _load_feedback_historic(self):
"""Load historic feedback words from JSON file."""
try:
with open("feedback_historic.json", "r") as f:
self.feedback_historic = json.load(f)
except FileNotFoundError:
self.console.print("[yellow]Warning: feedback_historic.json not found, starting with empty feedback history[/yellow]")
self.feedback_historic = []
except json.JSONDecodeError:
self.console.print("[yellow]Warning: feedback_historic.json is corrupted, starting with empty feedback history[/yellow]")
self.feedback_historic = []
def _save_feedback_words(self):
"""Save feedback words to JSON file."""
with open("feedback_words.json", "w") as f:
json.dump(self.feedback_words, f, indent=2)
def _save_feedback_historic(self):
"""Save historic feedback words to JSON file (keeping only first 30)."""
# Keep only the first 30 feedback words (newest are at the beginning)
if len(self.feedback_historic) > 30:
self.feedback_historic = self.feedback_historic[:30]
with open("feedback_historic.json", "w") as f:
json.dump(self.feedback_historic, f, indent=2)
def _save_pool_prompts(self):
"""Save pool prompts to JSON file."""
with open("prompts_pool.json", "w") as f:
with open("pool_prompts.json", "w") as f:
json.dump(self.pool_prompts, f, indent=2)
def add_prompts_to_pool(self, prompts: List[str]):
@@ -228,6 +186,22 @@ class JournalPromptGenerator:
return drawn_prompts
def show_pool_stats(self):
"""Show statistics about the prompt pool."""
total_prompts = len(self.pool_prompts)
table = Table(title="Prompt Pool Statistics")
table.add_column("Metric", style="cyan")
table.add_column("Value", style="green")
table.add_row("Prompts in pool", str(total_prompts))
table.add_row("Prompts per session", str(self.settings['num_prompts']))
table.add_row("Target pool size", str(self.settings['cached_pool_volume']))
table.add_row("Available sessions", str(total_prompts // self.settings['num_prompts']))
self.console.print(table)
def add_prompt_to_history(self, prompt_text: str):
"""
Add a single prompt to the historic prompts cyclic buffer.
@@ -260,53 +234,6 @@ class JournalPromptGenerator:
self.historic_prompts = updated_prompts
self._save_historic_prompts()
def add_feedback_words_to_history(self):
"""
Add current feedback words to the historic feedback words cyclic buffer.
The 6 new feedback words become feedback00-feedback05, all others shift down,
and feedback29 is discarded (keeping only 30 items total).
"""
# Extract just the words from the current feedback words
# Current feedback_words structure: [{"feedback00": "word", "weight": 3}, ...]
new_feedback_words = []
for i, feedback_item in enumerate(self.feedback_words):
# Get the word from the feedback item (key is feedback00, feedback01, etc.)
feedback_key = f"feedback{i:02d}"
if feedback_key in feedback_item:
word = feedback_item[feedback_key]
# Create new feedback word object with just the word (no weight)
new_feedback_words.append({
feedback_key: word
})
# If we don't have 6 feedback words, we can't add them to history
if len(new_feedback_words) != 6:
self.console.print(f"[yellow]Warning: Expected 6 feedback words, got {len(new_feedback_words)}. Not adding to history.[/yellow]")
return
# Shift all existing feedback words down by 6 positions
# We'll create a new list starting with the 6 new feedback words
updated_feedback_historic = new_feedback_words
# Add all existing feedback words, shifting their numbers down by 6
for i, feedback_dict in enumerate(self.feedback_historic):
if i >= 24: # We only keep 30 feedback words total (00-29), and we've already added 6
break
# Get the feedback word
feedback_key = list(feedback_dict.keys())[0]
word = feedback_dict[feedback_key]
# Create feedback word with new number (shifted down by 6)
new_feedback_key = f"feedback{i+6:02d}"
updated_feedback_historic.append({
new_feedback_key: word
})
self.feedback_historic = updated_feedback_historic
self._save_feedback_historic()
self.console.print("[green]Added 6 feedback words to history[/green]")
def _parse_ai_response(self, response_content: str) -> List[str]:
"""
@@ -502,11 +429,6 @@ class JournalPromptGenerator:
else:
full_prompt = f"{template}\n\n{prompt_instruction}"
# Add feedback words if available
if self.feedback_words:
feedback_context = json.dumps(self.feedback_words, indent=2)
full_prompt = f"{full_prompt}\n\nFeedback words:\n{feedback_context}"
return full_prompt
def _parse_ai_response_with_count(self, response_content: str, expected_count: int) -> List[str]:
@@ -588,162 +510,6 @@ class JournalPromptGenerator:
self.console.print("[red]Failed to generate prompts[/red]")
return 0
def generate_theme_feedback_words(self) -> List[str]:
"""Generate 6 theme feedback words using AI based on historic prompts."""
self.console.print("\n[cyan]Generating theme feedback words based on historic prompts...[/cyan]")
# Load the feedback prompt template
try:
with open("ds_feedback.txt", "r") as f:
feedback_template = f.read()
except FileNotFoundError:
self.console.print("[red]Error: ds_feedback.txt not found[/red]")
return []
# Prepare the full prompt with historic context and feedback words
if self.historic_prompts:
historic_context = json.dumps(self.historic_prompts, indent=2)
full_prompt = f"{feedback_template}\n\nPrevious prompts:\n{historic_context}"
# Add current feedback words if available (with weights)
if self.feedback_words:
feedback_context = json.dumps(self.feedback_words, indent=2)
full_prompt = f"{full_prompt}\n\nCurrent feedback themes (with weights):\n{feedback_context}"
# Add historic feedback words if available (just words, no weights)
if self.feedback_historic:
feedback_historic_context = json.dumps(self.feedback_historic, indent=2)
full_prompt = f"{full_prompt}\n\nHistoric feedback themes (just words):\n{feedback_historic_context}"
else:
self.console.print("[yellow]Warning: No historic prompts available for feedback analysis[/yellow]")
return []
# Show progress
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
transient=True,
) as progress:
task = progress.add_task("Calling AI API for theme analysis...", total=None)
try:
# Call the AI API
response = self.client.chat.completions.create(
model=self.model,
messages=[
{"role": "system", "content": "You are a creative writing assistant that analyzes writing prompts. Always respond with valid JSON."},
{"role": "user", "content": full_prompt}
],
temperature=0.7,
max_tokens=1000
)
response_content = response.choices[0].message.content
except Exception as e:
self.console.print(f"[red]Error calling AI API: {e}[/red]")
self.console.print(f"[yellow]Full prompt sent to API (first 500 chars):[/yellow]")
self.console.print(f"[yellow]{full_prompt[:500]}...[/yellow]")
return []
# Parse the response to get 6 theme words
theme_words = self._parse_theme_words_response(response_content)
if not theme_words or len(theme_words) != 6:
self.console.print(f"[red]Error: Expected 6 theme words, got {len(theme_words) if theme_words else 0}[/red]")
return []
return theme_words
def _parse_theme_words_response(self, response_content: str) -> List[str]:
"""
Parse the AI response to extract 6 theme words.
Expected format: JSON list of 6 lowercase words.
"""
# First, try to clean up the response content
cleaned_content = self._clean_ai_response(response_content)
try:
# Try to parse as JSON
data = json.loads(cleaned_content)
# Check if data is a list
if isinstance(data, list):
# Ensure all items are strings and lowercase them
theme_words = []
for word in data:
if isinstance(word, str):
theme_words.append(word.lower().strip())
else:
theme_words.append(str(word).lower().strip())
return theme_words
else:
self.console.print(f"[yellow]Warning: AI returned unexpected data type: {type(data)}[/yellow]")
return []
except json.JSONDecodeError:
# If not valid JSON, try to extract words from text
self.console.print("[yellow]Warning: AI response is not valid JSON, attempting to extract theme words...[/yellow]")
# Look for patterns in the text
lines = response_content.strip().split('\n')
theme_words = []
for line in lines:
line = line.strip()
if line and len(line) < 50: # Theme words should be short
# Try to extract words (lowercase, no punctuation)
words = [w.lower().strip('.,;:!?()[]{}"\'') for w in line.split()]
theme_words.extend(words)
if len(theme_words) >= 6:
break
return theme_words[:6]
def collect_feedback_ratings(self, theme_words: List[str]) -> List[Dict[str, Any]]:
"""Collect user ratings (0-6) for each theme word and return structured feedback."""
self.console.print("\n[bold]Please rate each theme word from 0 to 6:[/bold]")
self.console.print("[dim]0 = Not relevant, 6 = Very relevant[/dim]\n")
feedback_items = []
for i, word in enumerate(theme_words):
while True:
try:
rating = Prompt.ask(
f"[bold]Word {i+1}: {word}[/bold]",
choices=[str(x) for x in range(0, 7)], # 0-6 inclusive
default="3"
)
rating_int = int(rating)
if 0 <= rating_int <= 6:
# Create feedback item with key (feedback00, feedback01, etc.)
feedback_key = f"feedback{i:02d}"
feedback_items.append({
feedback_key: word,
"weight": rating_int
})
break
else:
self.console.print("[yellow]Please enter a number between 0 and 6[/yellow]")
except ValueError:
self.console.print("[yellow]Please enter a valid number[/yellow]")
return feedback_items
def update_feedback_words(self, new_feedback_items: List[Dict[str, Any]]):
"""Update feedback words with new ratings."""
# Replace existing feedback words with new ones
self.feedback_words = new_feedback_items
self._save_feedback_words()
self.console.print(f"[green]Updated feedback words with {len(new_feedback_items)} items[/green]")
# Also add the new feedback words to the historic buffer
self.add_feedback_words_to_history()
def display_prompts(self, prompts: List[str]):
"""Display generated prompts in a nice format."""
self.console.print("\n" + "="*60)
@@ -761,33 +527,19 @@ class JournalPromptGenerator:
self.console.print(panel)
self.console.print() # Empty line between prompts
def show_combined_stats(self):
"""Show combined statistics about both prompt pool and history."""
# Pool statistics
total_pool_prompts = len(self.pool_prompts)
pool_table = Table(title="Prompt Pool Statistics")
pool_table.add_column("Metric", style="cyan")
pool_table.add_column("Value", style="green")
def show_history_stats(self):
"""Show statistics about prompt history."""
total_prompts = len(self.historic_prompts)
pool_table.add_row("Prompts in pool", str(total_pool_prompts))
pool_table.add_row("Prompts per session", str(self.settings['num_prompts']))
pool_table.add_row("Target pool size", str(self.settings['cached_pool_volume']))
pool_table.add_row("Available sessions", str(total_pool_prompts // self.settings['num_prompts']))
table = Table(title="Prompt History Statistics")
table.add_column("Metric", style="cyan")
table.add_column("Value", style="green")
# History statistics
total_history_prompts = len(self.historic_prompts)
history_table = Table(title="Prompt History Statistics")
history_table.add_column("Metric", style="cyan")
history_table.add_column("Value", style="green")
table.add_row("Total prompts in history", str(total_prompts))
table.add_row("History capacity", "60 prompts")
table.add_row("Available slots", str(max(0, 60 - total_prompts)))
history_table.add_row("Total prompts in history", str(total_history_prompts))
history_table.add_row("History capacity", "60 prompts")
history_table.add_row("Available slots", str(max(0, 60 - total_history_prompts)))
# Display both tables
self.console.print(pool_table)
self.console.print() # Empty line between tables
self.console.print(history_table)
self.console.print(table)
def interactive_mode(self):
"""Run in interactive mode with user prompts."""
@@ -813,8 +565,8 @@ class JournalPromptGenerator:
self.console.print("\n[bold]Options:[/bold]")
self.console.print("1. Draw prompts from pool (no API call)")
self.console.print("2. Fill prompt pool using API")
self.console.print("3. View combined statistics")
self.console.print("4. Generate and rate theme feedback words")
self.console.print("3. View pool statistics")
self.console.print("4. View history statistics")
self.console.print("5. Exit")
choice = Prompt.ask("\nEnter your choice", choices=["1", "2", "3", "4", "5"], default="1")
@@ -848,16 +600,10 @@ class JournalPromptGenerator:
self.console.print("[yellow]No prompts were added to pool[/yellow]")
elif choice == "3":
self.show_combined_stats()
self.show_pool_stats()
elif choice == "4":
# Generate and rate theme feedback words
theme_words = self.generate_theme_feedback_words()
if theme_words:
feedback_items = self.collect_feedback_ratings(theme_words)
self.update_feedback_words(feedback_items)
else:
self.console.print("[yellow]No theme words were generated[/yellow]")
self.show_history_stats()
elif choice == "5":
self.console.print("[green]Goodbye! Happy journaling! 📓[/green]")
@@ -880,7 +626,12 @@ def main():
parser.add_argument(
"--stats", "-s",
action="store_true",
help="Show combined statistics (pool and history)"
help="Show history statistics"
)
parser.add_argument(
"--pool-stats", "-p",
action="store_true",
help="Show pool statistics"
)
parser.add_argument(
"--fill-pool", "-f",
@@ -894,7 +645,9 @@ def main():
generator = JournalPromptGenerator(config_path=args.config)
if args.stats:
generator.show_combined_stats()
generator.show_history_stats()
elif args.pool_stats:
generator.show_pool_stats()
elif args.fill_pool:
# Fill prompt pool to target volume using API
total_added = generator.fill_pool_to_target()

182
historic_prompts.json Normal file
View File

@@ -0,0 +1,182 @@
[
{
"prompt00": "Choose a street you walk down often. Today, walk it with the mission of noticing five things you've never seen before. They can be tiny: a crack in the pavement shaped like a continent, a particular stain on a wall, a hidden doorbell. Document each discovery in detail. Then, reflect on the phenomenon of selective attention. What had you been filtering out, and why? How does this exercise change your sense of the familiar path?"
},
{
"prompt01": "Imagine you could host a dinner party for three fictional characters from different books, films, or myths. Who would you invite and why? Don't just list them. Set the scene: the table setting, the menu, the lighting. Write the conversation that unfolds. What would they argue about? What surprising common ground might they find? How would their presence challenge or affirm your own worldview? Let the dialogue reveal their core natures."
},
{
"prompt02": "Describe a taste you loved as a child but have since grown indifferent to or now dislike. Recreate the sensory memory of that taste with precision. What was its context? Who was with you? Now, analyze the shift. Did your palate change, or did the associations sour? Is there a way to reclaim the innocent pleasure of that taste, or is its loss a necessary marker of growing up? Explore the nostalgia and slight grief in outgrowing a flavor."
},
{
"prompt03": "Contemplate the concept of 'waste' in your daily life. Choose one item destined for the trash or recycling. Trace its journey backwards from your hand to its origins as raw material. Then, project its journey forward after it leaves your custody. What systems does it touch? What hands might process it? Write a biography of this discarded object, granting it dignity and narrative. How does this perspective alter your sense of responsibility and connection?"
},
{
"prompt04": "Invent a small, personal ritual you could perform to mark the transition from one part of your day to another (e.g., work to home, waking to activity). Describe each step with deliberate, sensory care. What object is involved? What words, if any, are said? How does your posture change? The goal isn't superstition, but mindfulness. Write about performing this ritual for a week. What subtle shifts in your awareness might it create? How does deliberately carving out a threshold affect your experience of time?"
},
{
"prompt05": "Consider a piece of music that feels like a physical space to you\u2014a song you can walk into. Describe the architecture of this auditory landscape. What is the floor made of? How high is the ceiling? What color is the light? Where are the shadows? What happens to your body and breath as you move through its sections\u2014the verses, the chorus, the bridge? Is it a place of refuge, confrontation, or memory? Explore how sound can build an environment you inhabit, not just hear."
},
{
"prompt06": "Describe your ideal sanctuary\u2014not a grand fantasy, but a realistically attainable space you could create. Detail its location, size, lighting, furnishings, and most importantly, its rules (e.g., 'no devices,' 'only music without words,' 'must contain something living'). What specific activities would you do there? What state of mind does this space architecturally encourage? How would visiting it regularly change the rhythm of your weeks?"
},
{
"prompt07": "Describe a skill or piece of knowledge you possess that you learned in an unconventional, self-taught, or accidental way. Detail the messy, non-linear process of that learning. Who or what were your unlikely teachers? Celebrate the inefficiency and personal quirks of your method. How does this 'uncurated' knowledge differ in feel and application from something you were formally taught?"
},
{
"prompt08": "Think of a skill or piece of knowledge you possess that feels almost instinctual, something you can do without conscious thought (like riding a bike, typing, or a native language's grammar). Deconstruct this automatic competence. Describe the first clumsy attempts to learn it, the plateau of frustration, the moment it 'clicked' into muscle memory. Explore the duality of this knowledge: how it is both a part of you and a separate tool. What does this ingrained ability allow you to forget, and what freedom does that forgetfulness grant?"
},
{
"prompt09": "Choose a natural element you feel a kinship with\u2014fire, stone, water, wind, or earth. Personify it deeply: give it desires, memories, a voice. Write a monologue from its perspective about its ancient, slow existence and its observations of human brevity and frenzy. Then, write about a moment in your life when you felt most aligned with this element's essence. How does connecting with this primal force alter your sense of time and scale?"
},
{
"prompt10": "Imagine you could preserve one hour from your recent memory in a vial, to be re-experienced fully at a future date. Which hour would you choose? Describe it not just as events, but as a full sensory immersion: the light, the sounds, the emotional texture, the quality of the air. Why is this particular slice of time worth encapsulating? What fears or hopes do you have about opening that vial years from now? Write about the desire to hold onto a fleeting feeling, and the wisdom or melancholy that might come from revisiting it."
},
{
"prompt11": "Contemplate the concept of 'enough.' In our culture of more, what does sufficiency feel like in your body and mind? Describe a recent moment when you felt truly, deeply 'enough'\u2014not in lack, not in excess. It could be related to time, accomplishment, possessions, or love. What were the conditions? How did it settle in your posture or breath? Then, contrast this with a sphere of your life where the feeling of 'not enough' persistently hums. Explore the tension between these two states. What would it take to cultivate more of the former?"
},
{
"prompt12": "Recall a piece of bad advice you once received and followed. Who gave it and why did you trust them? Walk through the consequences, large or small. Now, reframe that experience not as a mistake, but as a necessary detour. What did you learn about yourself, about advice, or about the gap between theory and practice that you couldn't have learned any other way? Write the thank-you note you would send to that advisor today, acknowledging the unexpected gift of their misguidance."
},
{
"prompt13": "You are tasked with composing a guided audio meditation for a stranger experiencing intense anxiety. Write the script. Use your voice to lead them through a physical space\u2014a forest path, a quiet beach, a cozy room. Describe not just visuals, but textures, sounds, temperatures, and the rhythm of breathing. What reassurance would you offer without being trite? What simple, grounding observations would you point out? Craft a verbal sanctuary meant to hold someone's fragile attention."
},
{
"prompt14": "Recall a piece of clothing you once owned and loved, but have since lost, given away, or worn out. Recreate it stitch by stitch in words\u2014its fabric, its fit, its smell, the way it moved with you. Narrate its life with you: the occasions it witnessed, the stains it earned, the comfort it provided. What did wearing it allow you to feel or project? Write an ode to this second skin, and explore what its absence represents."
},
{
"prompt15": "Test prompt"
},
{
"prompt16": "Observe the sky right now, in this exact moment. Describe its color, cloud formations, light quality, and movement with meticulous attention. Then, let this observation launch you into a reflection on scale and perspective. Consider the atmospheric phenomena occurring beyond your sight\u2014jet streams, weather systems, celestial motions. How does contemplating the vast, impersonal sky make you feel about your current concerns, joys, or plans? Write about the tension between the immediacy of your personal world and the silent, ongoing spectacle above."
},
{
"prompt17": "Choose a machine or appliance in your home that has a distinct sound\u2014a refrigerator hum, a heater's click, a fan's whir. Close your eyes and listen to it for a full minute. Describe its rhythm, pitch, and constancy. Now, personify this sound. What is its personality? Is it a loyal guardian, a complaining old friend, a distant observer? Write a monologue from its perspective about the life it monitors within these walls. What has it learned about you from its unchanging post?"
},
{
"prompt18": "Recall a public space you frequented often in the past but have not visited in years (a library, a park, a diner, a store). Reconstruct it from memory in vivid detail. Then, imagine returning to it today. Describe the inevitable changes\u2014the renovations, the new faces, the faded paint. But also, hunt for the one thing that remains exactly, miraculously the same. How does the coexistence of change and permanence in this space make you feel about the passage of your own time?"
},
{
"prompt19": "\"newprompt3\": \"Recall a teacher, mentor, or elder who said something to you in passing that you have never forgotten. It might have been a compliment, a criticism, or an offhand observation. Reconstruct the scene. Why did their words carry such weight? How have you turned them over in your mind since? Explore the power of brief, seemingly casual utterances to shape a person's self-concept.\","
},
{
"prompt20": "\"newprompt0\": \"Write a detailed portrait of a tree you know well\u2014not just its appearance, but its history in that spot, the way its branches move in different winds, the creatures that inhabit it, the shadows it casts at various hours. Imagine its perspective across seasons and years. What has it witnessed? What would it say about change, resilience, or stillness if it could speak? Let the tree become a mirror for your own sense of place and time.\","
},
{
"prompt21": "Describe a memory you have that is tied to a specific smell. Don't just tell the story of the event; focus on describing the scent itself in as much detail as possible\u2014its texture, its weight in the air, its nuances. How does conjuring that smell now make you feel in your body? Let the description of the aroma lead you back into the memory's landscape."
},
{
"prompt22": "Write a letter to your 15-year-old self. Be kind, be blunt, be humorous, or be stern. What do you know now that you desperately needed to hear then? What mystery about your future life could you tantalizingly hint at without giving it all away? Don't just give advice; try to capture the voice and tone you wish an older, wiser person had used with you."
},
{
"prompt23": "You find a forgotten door in a place you know well\u2014your home, your workplace, your daily park. It wasn't there yesterday. You open it. Describe what is on the other side using only sensory details: sight, sound, temperature, smell. Do not explain its purpose or origin. Simply document the experience of crossing that threshold."
},
{
"prompt24": "Make a list of ten tiny, perfect moments from the past month that no one else probably noticed or would remember. The way light fell on a spoon, a stranger's half-smile, the sound of rain stopping. Elaborate on at least three of them, expanding them into full vignettes. Why did these micro-moments stick with you?"
},
{
"prompt25": "Invent a mythological creature for a modern urban setting. What does it look like? What is its behavior and habitat (e.g., subway tunnels, server farms, air vents)? What folklore do people whisper about it? What does it symbolize\u2014anxiety, forgotten connections, hope? Describe a recent 'sighting' of this creature in vivid detail."
},
{
"prompt26": "Choose an object in your immediate line of sight that is not electronic. Write its biography. Where was it made? Who owned it before you? What conversations has it overheard? What secrets does it hold? What small damages or wear marks does it have, and what story does each tell? Give this ordinary item an epic history."
},
{
"prompt27": "Describe your current emotional state as a weather system. Is it a still, high-pressure fog? A sudden, sharp hailstorm? A lingering, humid drizzle? Map its boundaries, its intensity, its forecast. What terrain does it move over\u2014the mountains of your responsibilities, the plains of your routine? How does it affect your internal climate?"
},
{
"prompt28": "Recall a time you were deeply embarrassed. Write about it from the perspective of a sympathetic observer who was there\u2014or invent one. How might they have perceived the event? What context or kindness might they have seen that you, in your self-focused shame, completely missed? Reframe the memory through their eyes."
},
{
"prompt29": "What skill or craft have you always wanted to learn but haven't? Immerse yourself in a detailed fantasy of mastering it. Describe the feel of the tools in your hands, the initial frustrations, the first small success, the growing muscle memory. What does the final, perfected product of your labor look or feel like? Live in that imagined\u6210\u5c31\u611f."
},
{
"prompt30": "Write a dialogue between two aspects of yourself (e.g., Your Ambitious Self and Your Tired Self; Your Cynical Self and Your Hopeful Self). Give them distinct voices. What are they arguing about, negotiating, or planning? Don't just state positions; let them bicker, persuade, or sit in silence together. See where the conversation goes."
},
{
"prompt31": "Describe your childhood home from the perspective of a small animal (a mouse, a squirrel, a bird) that lived there concurrently with you. What did this creature notice about your family's rhythms, the layout, the dangers, and the treasures (crumbs, cozy materials)? How did it perceive you, the giant human child?"
},
{
"prompt32": "List five paths your life could have taken if you'd made one different choice. Briefly outline each alternate reality. Then, choose one and dive deep: write a journal entry from that version of you today. What are their worries, joys, and regrets? How is their voice similar to or different from your own?"
},
{
"prompt33": "Think of a person you see regularly but do not know (a barista, a neighbor, a commuter). Invent a rich, secret inner life for them. What profound private mission are they on? What hidden talent do they possess? What great sorrow or hope are they carrying today as they serve your coffee or stand on the platform? Write from their perspective."
},
{
"prompt34": "What is a belief you held strongly five or ten years ago that you have since questioned or abandoned? Trace the evolution of that change. Was it a sudden shattering or a slow erosion? What person, experience, or piece of information was the catalyst? Describe the feeling of the ground shifting under that particular piece of your worldview."
},
{
"prompt35": "Describe a common, mundane process (making tea, tying your shoes, doing laundry) in extreme, almost absurdly epic detail, as if you were writing a sacred manual or a scientific treatise for an alien civilization. Break down every micro-action, every sensation, every potential variable. Find the profound in the procedural."
},
{
"prompt36": "You are given a suitcase and told you must leave your home in one hour, not knowing if or when you'll return. You can only take what fits in the case. Describe, in real-time, the frantic and deliberate process of choosing. What practical items make the cut? What irreplaceable tokens? What do you leave behind, and what does that feel like?"
},
{
"prompt37": "Write about water in three different forms: as a memory involving a body of water (ocean, river, bath), as a description of drinking a glass of water right now, and as a metaphor for an emotion. Move seamlessly between these three aspects. Let the fluidity of the theme connect them."
},
{
"prompt38": "What does silence sound like in your current environment? Don't just say 'quiet.' Describe the layers of sound that actually constitute the silence\u2014the hums, ticks, distant rumbles, the sound of your own body. Now, project what this same space sounded like 100 years ago, and what it might sound like 100 years from now."
},
{
"prompt39": "Create a recipe for a dish that represents your current life phase. List ingredients (e.g., \"two cups of transition,\" \"a pinch of anxiety,\" \"a steady base of routine\"). Write the instructions, including the method, cooking time, and necessary equipment. Describe the final product's taste, texture, and who it should be shared with."
},
{
"prompt40": "Recall a dream from the past week, however fragmentary. Don't interpret it. Instead, expand it. Continue the narrative from where it left off. Describe the dream logic, the landscape, the characters. Let it become a story. Where does your dreaming mind take you when given free rein on the page?"
},
{
"prompt41": "Make a list of everything that is blue in your immediate environment. Describe each shade specifically (slate, cobalt, robin's egg, faded denim). Then, choose one blue object and write about its journey to being here, in this blue state, in front of you. How did it get its color? What has it reflected?"
},
{
"prompt42": "Write a eulogy for something you've lost that isn't a person\u2014a habit, a version of a city, a relationship dynamic, a part of your identity. Acknowledge its virtues and its flaws. Say goodbye properly, with humor, regret, and gratitude. What did it give you? What space has its departure created?"
},
{
"prompt43": "Describe your hands. Not just their appearance, but their capabilities, their scars, their memories. What have they held, built, comforted, or torn down? What do their specific aches and strengths tell you about the life you've lived so far? If your hands could speak, what would they say they want to do next?"
},
{
"prompt44": "Imagine you can overhear the conversation of the people at the table next to you in a caf\u00e9, but they are speaking in a language you don't understand. Based on their tone, gestures, pauses, and expressions, invent the dialogue. What crucial, funny, or tragic misunderstanding are they having? What are they *really* talking about?"
},
{
"prompt45": "What is a piece of art (a song, painting, film, book) that fundamentally moved you? Describe the first time you encountered it. Don't just analyze why it's good; describe the physical and emotional reaction it provoked. Has its meaning changed for you over time? How does it live inside you now?"
},
{
"prompt46": "You have one day completely alone, with no obligations and no possibility of communication. The power and internet are out. How do you spend the hours from waking to sleeping? Detail the rituals, the wanderings, the thoughts, the meals. Do you enjoy the solitude or chafe against it? What arises in the quiet?"
},
{
"prompt47": "Personify a negative emotion you've been feeling lately (e.g., anxiety, envy, restlessness). Give it a name, a form, a voice. Write a character profile of it. What does it want? What does it fear? What flawed logic does it operate under? Then, write a short scene of you having a cup of tea with it, listening to its perspective."
},
{
"prompt48": "Describe a city you've never been to, based solely on the stories, images, and snippets you've absorbed about it. Build it from imagination and second-hand clues. Then, contrast that with a description of your own street, seen with the hyper-attentive eyes of a first-time visitor. Make the familiar alien, and the alien familiar."
},
{
"prompt49": "Think of a crossroads in your past. Now, imagine you see a ghost of your former self standing there, frozen in that moment of decision. What would you want to say to that ghost? Would you offer comfort, a warning, or just silent companionship? Write the encounter. Does the ghost speak back?"
},
{
"prompt50": "What is a tradition in your family or community\u2014big or small\u2014that you find meaningful? Describe its sensory details, its rhythms, its players. Now, trace its origin. How did it start? Has it mutated over time? What does its continued practice say about what your family values, fears, or hopes for?"
},
{
"prompt51": "Choose a year from your past. Catalog the soundtrack of that year: songs on the radio, albums you loved, jingles, background music. For each, describe a specific memory or feeling it evokes. How does the music of that time period color your memory of the entire era? What does it sound like to you now?"
},
{
"prompt52": "Write instructions for a stranger on how to be you for a day. Include the essential routines, the internal dialogues to expect, the things to avoid, the small comforts to lean on, and the passwords to your various anxieties. Be brutally honest and surprisingly practical. What would they find hardest to mimic?"
},
{
"prompt53": "Describe a moment of unexpected kindness, either given or received. Don't frame it as a grand gesture. Focus on a small, almost invisible act. What were the circumstances? Why was it so potent? How did it ripple out, changing the temperature of your day or your perception of someone?"
},
{
"prompt54": "You discover you have a superpower, but it is frustratingly mundane and specific (e.g., the ability to always know exactly what time it is without a clock, to perfectly fold fitted sheets, to find lost buttons). Explore the practical uses, the minor heroics, the unexpected downsides, and the peculiar loneliness of this unique gift."
},
{
"prompt55": "Go to a window. Describe the view in extreme detail, as if painting it with words, for five minutes. Then, close your eyes and describe the view from a window that was significant to you in the past (your childhood bedroom, a previous office, a grandparent's house). Juxtapose the two landscapes on the page."
},
{
"prompt56": "What is a question you are tired of being asked? Write a rant about why it's so irritating, reductive, or painful. Then, flip it: write the question you wish people would ask you instead. Answer that new question fully and generously."
},
{
"prompt57": "Describe a hobby or interest you have from the perspective of someone who finds it utterly baffling and boring. Then, defend it with the passionate zeal of a true devotee. Try to convey its magic and depth to this imagined skeptic. What is the core beauty you see that they miss?"
},
{
"prompt58": "List ten things you would do if you were not afraid. They can be grand (quit my job) or small (sing karaoke). Choose one and vividly imagine doing it. Walk through every step, from decision to action to aftermath. How does the air feel different on the other side of that fear?"
},
{
"prompt59": "Write about a time you got exactly what you wanted\u2014and it was not what you expected. Describe the desire, the anticipation, the moment of attainment, and the subtle (or not-so-subtle) disappointment or confusion that followed. What did that experience teach you about wanting?"
}
]

3
pool_prompts.json Normal file
View File

@@ -0,0 +1,3 @@
[
"What is something you've been putting off and why?"
]

16
run.sh
View File

@@ -36,6 +36,7 @@ fi
# Parse command line arguments
INTERACTIVE=false
STATS=false
POOL_STATS=false
FILL_POOL=false
HELP=false
@@ -49,6 +50,10 @@ while [[ $# -gt 0 ]]; do
STATS=true
shift
;;
--pool-stats)
POOL_STATS=true
shift
;;
--fill-pool)
FILL_POOL=true
shift
@@ -70,21 +75,26 @@ if [ "$HELP" = true ]; then
echo ""
echo "Options:"
echo " -i, --interactive Run in interactive mode (with rich interface)"
echo " --stats Show combined statistics (pool and history)"
echo " --stats Show prompt history statistics"
echo " --pool-stats Show prompt pool statistics"
echo " --fill-pool Fill prompt pool using AI (makes API call)"
echo " -h, --help Show this help message"
echo ""
echo "Examples:"
echo " ./run.sh # Draw prompts from pool (default)"
echo " ./run.sh -i # Interactive mode"
echo " ./run.sh --stats # Show combined statistics"
echo " ./run.sh --stats # Show history statistics"
echo " ./run.sh --pool-stats # Show pool statistics"
echo " ./run.sh --fill-pool # Fill prompt pool using AI"
exit 0
fi
if [ "$STATS" = true ]; then
echo "📊 Showing combined statistics..."
echo "📊 Showing history statistics..."
python3 generate_prompts.py --stats
elif [ "$POOL_STATS" = true ]; then
echo "📊 Showing pool statistics..."
python3 generate_prompts.py --pool-stats
elif [ "$FILL_POOL" = true ]; then
echo "🔄 Filling prompt pool using AI..."
python3 generate_prompts.py --fill-pool

253
run_webapp.sh
View File

@@ -1,253 +0,0 @@
#!/bin/bash
# Daily Journal Prompt Generator - Web Application Runner
# This script helps you run the web application with various options
set -e
# Colors for output
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m' # No Color
print_header() {
echo -e "${BLUE}"
echo "=========================================="
echo "Daily Journal Prompt Generator - Web App"
echo "=========================================="
echo -e "${NC}"
}
print_success() {
echo -e "${GREEN}✓ $1${NC}"
}
print_warning() {
echo -e "${YELLOW}⚠ $1${NC}"
}
print_error() {
echo -e "${RED}✗ $1${NC}"
}
check_dependencies() {
print_header
echo "Checking dependencies..."
# Check Docker
if command -v docker &> /dev/null; then
print_success "Docker is installed"
else
print_warning "Docker is not installed. Docker is recommended for easiest setup."
fi
# Check Docker Compose
if command -v docker-compose &> /dev/null || docker compose version &> /dev/null; then
print_success "Docker Compose is available"
else
print_warning "Docker Compose is not available"
fi
# Check Python
if command -v python3 &> /dev/null; then
PYTHON_VERSION=$(python3 --version | cut -d' ' -f2)
print_success "Python $PYTHON_VERSION is installed"
else
print_error "Python 3 is not installed"
exit 1
fi
# Check Node.js
if command -v node &> /dev/null; then
NODE_VERSION=$(node --version)
print_success "Node.js $NODE_VERSION is installed"
else
print_warning "Node.js is not installed (needed for frontend development)"
fi
echo ""
}
setup_environment() {
echo "Setting up environment..."
if [ ! -f ".env" ]; then
if [ -f ".env.example" ]; then
cp .env.example .env
print_success "Created .env file from template"
print_warning "Please edit .env file and add your API keys"
else
print_error ".env.example not found"
exit 1
fi
else
print_success ".env file already exists"
fi
# Check data directory
if [ ! -d "data" ]; then
mkdir -p data
print_success "Created data directory"
fi
echo ""
}
run_docker() {
print_header
echo "Starting with Docker Compose..."
echo ""
if command -v docker-compose &> /dev/null; then
docker-compose up --build
elif docker compose version &> /dev/null; then
docker compose up --build
else
print_error "Docker Compose is not available"
exit 1
fi
}
run_backend() {
print_header
echo "Starting Backend API..."
echo ""
cd backend
# Check virtual environment
if [ ! -d "venv" ]; then
print_warning "Creating Python virtual environment..."
python3 -m venv venv
fi
# Activate virtual environment
if [ -f "venv/bin/activate" ]; then
source venv/bin/activate
elif [ -f "venv/Scripts/activate" ]; then
source venv/Scripts/activate
fi
# Install dependencies
if [ ! -f "venv/bin/uvicorn" ]; then
print_warning "Installing Python dependencies..."
pip install -r requirements.txt
fi
# Run backend
print_success "Starting FastAPI backend on http://localhost:8000"
echo "API Documentation: http://localhost:8000/docs"
echo ""
uvicorn main:app --reload --host 0.0.0.0 --port 8000
cd ..
}
run_frontend() {
print_header
echo "Starting Frontend..."
echo ""
cd frontend
# Check node_modules
if [ ! -d "node_modules" ]; then
print_warning "Installing Node.js dependencies..."
npm install
fi
# Run frontend
print_success "Starting Astro frontend on http://localhost:3000"
echo ""
npm run dev
cd ..
}
run_tests() {
print_header
echo "Running Backend Tests..."
echo ""
if [ -f "test_backend.py" ]; then
python test_backend.py
else
print_error "test_backend.py not found"
fi
}
show_help() {
print_header
echo "Usage: $0 [OPTION]"
echo ""
echo "Options:"
echo " docker Run with Docker Compose (recommended)"
echo " backend Run only the backend API"
echo " frontend Run only the frontend"
echo " all Run both backend and frontend separately"
echo " test Run backend tests"
echo " setup Check dependencies and setup environment"
echo " help Show this help message"
echo ""
echo "Examples:"
echo " $0 docker # Run full stack with Docker"
echo " $0 all # Run backend and frontend separately"
echo " $0 setup # Setup environment and check dependencies"
echo ""
}
case "${1:-help}" in
docker)
check_dependencies
setup_environment
run_docker
;;
backend)
check_dependencies
setup_environment
run_backend
;;
frontend)
check_dependencies
setup_environment
run_frontend
;;
all)
check_dependencies
setup_environment
print_header
echo "Starting both backend and frontend..."
echo "Backend: http://localhost:8000"
echo "Frontend: http://localhost:3000"
echo ""
echo "Open two terminal windows and run:"
echo "1. $0 backend"
echo "2. $0 frontend"
echo ""
;;
test)
check_dependencies
run_tests
;;
setup)
check_dependencies
setup_environment
print_success "Setup complete!"
echo ""
echo "Next steps:"
echo "1. Edit .env file and add your API keys"
echo "2. Run with: $0 docker (recommended)"
echo "3. Or run with: $0 all"
;;
help|--help|-h)
show_help
;;
*)
print_error "Unknown option: $1"
show_help
exit 1
;;
esac

0
data/settings.cfg → settings.cfg
View File

257
test_backend.py
View File

@@ -1,257 +0,0 @@
#!/usr/bin/env python3
"""
Test script to verify the backend API structure.
"""
import sys
import os
# Add backend to path
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'backend'))
def test_imports():
"""Test that all required modules can be imported."""
print("Testing imports...")
try:
from app.core.config import settings
print("✓ Config module imported successfully")
from app.core.logging import setup_logging
print("✓ Logging module imported successfully")
from app.services.data_service import DataService
print("✓ DataService imported successfully")
from app.services.ai_service import AIService
print("✓ AIService imported successfully")
from app.services.prompt_service import PromptService
print("✓ PromptService imported successfully")
from app.models.prompt import PromptResponse, PoolStatsResponse
print("✓ Models imported successfully")
from app.api.v1.api import api_router
print("✓ API router imported successfully")
return True
except ImportError as e:
print(f"✗ Import error: {e}")
return False
except Exception as e:
print(f"✗ Error: {e}")
return False
def test_config():
"""Test configuration loading."""
print("\nTesting configuration...")
try:
from app.core.config import settings
print(f"✓ Project name: {settings.PROJECT_NAME}")
print(f"✓ Version: {settings.VERSION}")
print(f"✓ Debug mode: {settings.DEBUG}")
print(f"✓ Environment: {settings.ENVIRONMENT}")
print(f"✓ Host: {settings.HOST}")
print(f"✓ Port: {settings.PORT}")
print(f"✓ Min prompt length: {settings.MIN_PROMPT_LENGTH}")
print(f"✓ Max prompt length: {settings.MAX_PROMPT_LENGTH}")
print(f"✓ Prompts per session: {settings.NUM_PROMPTS_PER_SESSION}")
print(f"✓ Cached pool volume: {settings.CACHED_POOL_VOLUME}")
return True
except Exception as e:
print(f"✗ Configuration error: {e}")
return False
def test_data_service():
"""Test DataService initialization."""
print("\nTesting DataService...")
try:
from app.services.data_service import DataService
data_service = DataService()
print("✓ DataService initialized successfully")
# Check data directory
import os
data_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), "data")
if os.path.exists(data_dir):
print(f"✓ Data directory exists: {data_dir}")
# Check for required files
required_files = [
'prompts_historic.json',
'prompts_pool.json',
'feedback_words.json',
'feedback_historic.json',
'ds_prompt.txt',
'ds_feedback.txt',
'settings.cfg'
]
for file in required_files:
file_path = os.path.join(data_dir, file)
if os.path.exists(file_path):
print(f"✓ {file} exists")
else:
print(f"⚠ {file} not found (this may be OK for new installations)")
else:
print(f"⚠ Data directory not found: {data_dir}")
return True
except Exception as e:
print(f"✗ DataService error: {e}")
return False
def test_models():
"""Test Pydantic models."""
print("\nTesting Pydantic models...")
try:
from app.models.prompt import (
PromptResponse,
PoolStatsResponse,
HistoryStatsResponse,
FeedbackWord
)
# Test PromptResponse
prompt = PromptResponse(
key="prompt00",
text="Test prompt text",
position=0
)
print("✓ PromptResponse model works")
# Test PoolStatsResponse
pool_stats = PoolStatsResponse(
total_prompts=10,
prompts_per_session=6,
target_pool_size=20,
available_sessions=1,
needs_refill=True
)
print("✓ PoolStatsResponse model works")
# Test HistoryStatsResponse
history_stats = HistoryStatsResponse(
total_prompts=5,
history_capacity=60,
available_slots=55,
is_full=False
)
print("✓ HistoryStatsResponse model works")
# Test FeedbackWord
feedback_word = FeedbackWord(
key="feedback00",
word="creativity",
weight=5
)
print("✓ FeedbackWord model works")
return True
except Exception as e:
print(f"✗ Models error: {e}")
return False
def test_api_structure():
"""Test API endpoint structure."""
print("\nTesting API structure...")
try:
from fastapi import FastAPI
from app.api.v1.api import api_router
app = FastAPI()
app.include_router(api_router, prefix="/api/v1")
# Check routes
routes = []
for route in app.routes:
if hasattr(route, 'path'):
routes.append(route.path)
expected_routes = [
'/api/v1/prompts/draw',
'/api/v1/prompts/fill-pool',
'/api/v1/prompts/stats',
'/api/v1/prompts/history/stats',
'/api/v1/prompts/history',
'/api/v1/prompts/select/{prompt_index}',
'/api/v1/feedback/generate',
'/api/v1/feedback/rate',
'/api/v1/feedback/current',
'/api/v1/feedback/history'
]
print("✓ API router integrated successfully")
print(f"✓ Found {len(routes)} routes")
# Check for key routes
for expected_route in expected_routes:
if any(expected_route in route for route in routes):
print(f"✓ Route found: {expected_route}")
else:
print(f"⚠ Route not found: {expected_route}")
return True
except Exception as e:
print(f"✗ API structure error: {e}")
return False
def main():
"""Run all tests."""
print("=" * 60)
print("Daily Journal Prompt Generator - Backend API Test")
print("=" * 60)
tests = [
("Imports", test_imports),
("Configuration", test_config),
("Data Service", test_data_service),
("Models", test_models),
("API Structure", test_api_structure),
]
results = []
for test_name, test_func in tests:
print(f"\n{test_name}:")
print("-" * 40)
success = test_func()
results.append((test_name, success))
print("\n" + "=" * 60)
print("Test Summary:")
print("=" * 60)
all_passed = True
for test_name, success in results:
status = "✓ PASS" if success else "✗ FAIL"
print(f"{test_name:20} {status}")
if not success:
all_passed = False
print("\n" + "=" * 60)
if all_passed:
print("All tests passed! 🎉")
print("Backend API structure is ready.")
else:
print("Some tests failed. Please check the errors above.")
return all_passed
if __name__ == "__main__":
success = main()
sys.exit(0 if success else 1)

12
test_docker_build.sh
View File

@@ -1,12 +0,0 @@
#!/bin/bash
# Test Docker build for the backend
echo "Testing backend Docker build..."
docker build -t daily-journal-prompt-backend-test ./backend
# Test Docker build for the frontend
echo -e "\nTesting frontend Docker build..."
docker build -t daily-journal-prompt-frontend-test ./frontend
echo -e "\nDocker build tests completed."

4
tests/test_end_to_end.py → test_end_to_end.py
View File

@@ -7,8 +7,8 @@ import json
import sys
import os
# Add the parent directory to the Python path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
# Add the current directory to the Python path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from generate_prompts import JournalPromptGenerator

178
test_feedback_integration.py
View File

@@ -1,178 +0,0 @@
#!/usr/bin/env python3
"""
Integration test for complete feedback workflow.
Tests the end-to-end flow from user clicking "Fill Prompt Pool" to pool being filled.
"""
import asyncio
import sys
import os
# Add backend to path
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'backend'))
from app.services.prompt_service import PromptService
from app.services.data_service import DataService
async def test_complete_feedback_workflow():
"""Test the complete feedback workflow."""
print("Testing complete feedback workflow...")
print("=" * 60)
prompt_service = PromptService()
data_service = DataService()
try:
# Step 1: Get initial state
print("\n1. Getting initial state...")
# Get queued feedback words (should be positions 0-5)
queued_words = await prompt_service.get_feedback_queued_words()
print(f" Found {len(queued_words)} queued feedback words")
# Get active feedback words (should be positions 6-11)
active_words = await prompt_service.get_feedback_active_words()
print(f" Found {len(active_words)} active feedback words")
# Get pool stats
pool_stats = await prompt_service.get_pool_stats()
print(f" Pool: {pool_stats.total_prompts}/{pool_stats.target_pool_size} prompts")
# Get history stats
history_stats = await prompt_service.get_history_stats()
print(f" History: {history_stats.total_prompts}/{history_stats.history_capacity} prompts")
# Step 2: Verify data structure
print("\n2. Verifying data structure...")
feedback_historic = await prompt_service.get_feedback_historic()
if len(feedback_historic) == 30:
print(" ✓ Feedback history has 30 items (full capacity)")
else:
print(f" ⚠ Feedback history has {len(feedback_historic)} items (expected 30)")
if len(queued_words) == 6:
print(" ✓ Found 6 queued words (positions 0-5)")
else:
print(f" ⚠ Found {len(queued_words)} queued words (expected 6)")
if len(active_words) == 6:
print(" ✓ Found 6 active words (positions 6-11)")
else:
print(f" ⚠ Found {len(active_words)} active words (expected 6)")
# Step 3: Test feedback word update (simulate user weighting)
print("\n3. Testing feedback word update (simulating user weighting)...")
# Create test ratings (increase weight by 1 for each word, max 6)
ratings = {}
for i, item in enumerate(queued_words):
key = list(item.keys())[0]
word = item[key]
current_weight = item.get("weight", 3)
new_weight = min(current_weight + 1, 6)
ratings[word] = new_weight
print(f" Created test ratings for {len(ratings)} words")
for word, weight in ratings.items():
print(f" - '{word}': weight {weight}")
# Note: We're not actually calling update_feedback_words() here
# because it would generate new feedback words and modify the data
print(" ⚠ Skipping actual update to avoid modifying data")
# Step 4: Test prompt generation with active words
print("\n4. Testing prompt generation with active words...")
# Get active words for prompt generation
active_words_for_prompts = await prompt_service.get_feedback_active_words()
if active_words_for_prompts:
print(f" ✓ Active words available for prompt generation: {len(active_words_for_prompts)}")
for i, item in enumerate(active_words_for_prompts):
key = list(item.keys())[0]
word = item[key]
weight = item.get("weight", 3)
print(f" - {key}: '{word}' (weight: {weight})")
else:
print(" ⚠ No active words available for prompt generation")
# Step 5: Test pool fill workflow
print("\n5. Testing pool fill workflow...")
# Check if pool needs refill
if pool_stats.needs_refill:
print(f" ✓ Pool needs refill: {pool_stats.total_prompts}/{pool_stats.target_pool_size}")
print(" Workflow would be:")
print(" 1. User clicks 'Fill Prompt Pool'")
print(" 2. Frontend shows feedback weighting UI")
print(" 3. User adjusts weights and submits")
print(" 4. Backend generates new feedback words")
print(" 5. Backend fills pool using active words")
print(" 6. Frontend shows updated pool stats")
else:
print(f" ⚠ Pool doesn't need refill: {pool_stats.total_prompts}/{pool_stats.target_pool_size}")
# Step 6: Verify API endpoints are accessible
print("\n6. Verifying API endpoints...")
endpoints = [
("/api/v1/feedback/queued", "GET", "Queued feedback words"),
("/api/v1/feedback/active", "GET", "Active feedback words"),
("/api/v1/feedback/history", "GET", "Feedback history"),
("/api/v1/prompts/stats", "GET", "Pool statistics"),
("/api/v1/prompts/history", "GET", "Prompt history"),
]
print(" ✓ All API endpoints defined in feedback.py and prompts.py")
print(" ✓ Backend services properly integrated")
print("\n" + "=" * 60)
print("✅ Integration test completed successfully!")
print("=" * 60)
print("\nSummary:")
print(f"- Queued feedback words: {len(queued_words)}/6")
print(f"- Active feedback words: {len(active_words)}/6")
print(f"- Feedback history: {len(feedback_historic)}/30 items")
print(f"- Prompt pool: {pool_stats.total_prompts}/{pool_stats.target_pool_size}")
print(f"- Prompt history: {history_stats.total_prompts}/{history_stats.history_capacity}")
print("\nThe feedback mechanism is fully implemented and ready for use!")
print("Users can now:")
print("1. Click 'Fill Prompt Pool' to see feedback weighting UI")
print("2. Adjust weights for 6 queued feedback words")
print("3. Submit ratings to influence future prompt generation")
print("4. Have the pool filled using active feedback words")
return True
except Exception as e:
print(f"\n❌ Error during integration test: {e}")
import traceback
traceback.print_exc()
return False
async def main():
"""Main test function."""
print("=" * 60)
print("Feedback Mechanism Integration Test")
print("=" * 60)
print("Testing complete end-to-end workflow...")
success = await test_complete_feedback_workflow()
if success:
print("\n✅ All integration tests passed!")
print("The feedback mechanism is ready for deployment.")
else:
print("\n❌ Integration tests failed")
print("Please check the implementation.")
print("=" * 60)
if __name__ == "__main__":
asyncio.run(main())

230
test_parsing.py Normal file
View File

@@ -0,0 +1,230 @@
#!/usr/bin/env python3
"""
Consolidated test file for parsing AI responses and format handling.
Combines tests from:
- test_final_fix.py (AttributeError fix for list responses)
- test_new_format.py (new list format with locally generated keys)
- test_valid_response.py (valid JSON response handling)
"""
import json
import sys
import os
# Add the current directory to the Python path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from generate_prompts import JournalPromptGenerator
def test_attribute_error_fix():
"""Test the fix for AttributeError when API returns list instead of dict."""
print("\n=== Test: AttributeError fix for list responses ===")
# Create a mock generator
generator = JournalPromptGenerator()
# Test with empty list []
list_response = json.dumps([]) # Empty list
print("\n1. Testing with empty list []:")
try:
result = generator._parse_ai_response(list_response)
print(f" Result: Successfully parsed {len(result)} prompts (no AttributeError)")
except AttributeError as e:
print(f" ERROR: AttributeError occurred: {e}")
return False
except Exception as e:
print(f" Other error: {type(e).__name__}: {e}")
return False
# Test with list containing dictionaries
list_with_dicts = json.dumps([
{"some_key": "some value"},
{"another_key": "another value"}
])
print("\n2. Testing with list of dictionaries:")
try:
result = generator._parse_ai_response(list_with_dicts)
print(f" Result: Successfully parsed {len(result)} prompts (no AttributeError)")
except AttributeError as e:
print(f" ERROR: AttributeError occurred: {e}")
return False
except Exception as e:
print(f" Other error: {type(e).__name__}: {e}")
return False
print("\n✅ AttributeError fix tests passed!")
return True
def test_new_list_format():
"""Test the new format where AI returns a list and keys are generated locally."""
print("\n=== Test: New list format with locally generated keys ===")
# Create a mock generator
generator = JournalPromptGenerator()
# Create a mock AI response in the new list format
mock_ai_response = [
"Write about a childhood memory that still makes you smile.",
"Describe your perfect day from start to finish.",
"What is something you've been putting off and why?",
"Imagine you could have a conversation with any historical figure.",
"Write a letter to your future self one year from now.",
"Describe a place that feels like home to you."
]
# Convert to JSON string
json_response = json.dumps(mock_ai_response)
print("\n1. Testing _parse_ai_response with list format:")
result = generator._parse_ai_response(json_response)
print(f" Result type: {type(result)}")
print(f" Number of prompts: {len(result)}")
print(f" First prompt: {result[0][:50]}...")
# Verify it's a list of strings
assert isinstance(result, list), "Result should be a list"
assert all(isinstance(prompt, str) for prompt in result), "All items should be strings"
print("\n2. Testing add_prompts_to_pool with list of strings:")
# Get initial pool size
initial_pool_size = len(generator.pool_prompts)
print(f" Initial pool size: {initial_pool_size}")
# Add prompts to pool
generator.add_prompts_to_pool(result)
# Check new pool size
new_pool_size = len(generator.pool_prompts)
print(f" New pool size: {new_pool_size}")
print(f" Added {new_pool_size - initial_pool_size} prompts")
print("\n✅ New list format tests passed!")
return True
def test_valid_json_responses():
"""Test with valid JSON responses in various formats."""
print("\n=== Test: Valid JSON response handling ===")
# Create a mock generator
generator = JournalPromptGenerator()
# Create a valid response with 4 prompts as a list (new format)
valid_response = [
"Write about a time when you felt truly at peace.",
"Describe your ideal morning routine in detail.",
"What are three things you're grateful for today?",
"Reflect on a recent challenge and what you learned from it."
]
# Convert to JSON string
json_response = json.dumps(valid_response)
print("\n1. Testing with valid JSON response (list format):")
result = generator._parse_ai_response(json_response)
print(f" Number of prompts extracted: {len(result)}")
print(f" Type of result: {type(result)}")
for i, prompt_text in enumerate(result):
print(f" Prompt {i+1}: {prompt_text[:50]}...")
# Test with backticks
print("\n2. Testing with valid JSON response with backticks:")
backticks_response = f"```json\n{json_response}\n```"
result = generator._parse_ai_response(backticks_response)
print(f" Number of prompts extracted: {len(result)}")
# Test with "json" prefix
print("\n3. Testing with valid JSON response with 'json' prefix:")
json_prefix_response = f"json\n{json_response}"
result = generator._parse_ai_response(json_prefix_response)
print(f" Number of prompts extracted: {len(result)}")
# Test fallback for old dictionary format
print("\n4. Testing fallback for old dictionary format:")
old_format_response = {
"newprompt0": "Write about a time when you felt truly at peace.",
"newprompt1": "Describe your ideal morning routine in detail.",
"newprompt2": "What are three things you're grateful for today?",
"newprompt3": "Reflect on a recent challenge and what you learned from it."
}
json_old_response = json.dumps(old_format_response)
result = generator._parse_ai_response(json_old_response)
print(f" Number of prompts extracted: {len(result)}")
print("\n✅ Valid JSON response tests passed!")
return True
def test_clean_ai_response():
"""Test the _clean_ai_response method."""
print("\n=== Test: _clean_ai_response method ===")
generator = JournalPromptGenerator()
# Test cases
test_cases = [
("```json\n[1, 2, 3]\n```", "[1, 2, 3]"),
("```\n[1, 2, 3]\n```", "[1, 2, 3]"),
("json\n[1, 2, 3]", "[1, 2, 3]"),
("JSON\n[1, 2, 3]", "[1, 2, 3]"),
(" [1, 2, 3] ", "[1, 2, 3]"),
("```json\n{\"a\": 1}\n```", "{\"a\": 1}"),
]
all_passed = True
for i, (input_text, expected) in enumerate(test_cases):
cleaned = generator._clean_ai_response(input_text)
if cleaned == expected:
print(f" Test {i+1} passed: '{input_text[:20]}...' -> '{cleaned}'")
else:
print(f" Test {i+1} FAILED: '{input_text[:20]}...' -> '{cleaned}' (expected: '{expected}')")
all_passed = False
if all_passed:
print("\n✅ _clean_ai_response tests passed!")
return True
else:
print("\n❌ _clean_ai_response tests failed!")
return False
def main():
"""Run all parsing tests."""
print("=" * 60)
print("Running Consolidated Parsing Tests")
print("=" * 60)
all_passed = True
# Run all tests
if not test_attribute_error_fix():
all_passed = False
if not test_new_list_format():
all_passed = False
if not test_valid_json_responses():
all_passed = False
if not test_clean_ai_response():
all_passed = False
print("\n" + "=" * 60)
if all_passed:
print("✅ ALL PARSING TESTS PASSED!")
else:
print("❌ SOME TESTS FAILED!")
print("=" * 60)
return all_passed
if __name__ == "__main__":
success = main()
sys.exit(0 if success else 1)

0
tests/test_project.py → test_project.py
View File

98
test_prompt_logic.py Normal file
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@@ -0,0 +1,98 @@
#!/usr/bin/env python3
"""
Test script to verify the prompt numbering logic.
"""
import json
import configparser
def get_num_prompts():
"""Get the number of prompts from settings.cfg or default."""
config = configparser.ConfigParser()
num_prompts = 6 # Default value
try:
config.read('settings.cfg')
if 'prompts' in config and 'num_prompts' in config['prompts']:
num_prompts = int(config['prompts']['num_prompts'])
except (FileNotFoundError, ValueError):
pass
return num_prompts
def test_renumbering():
"""Test the renumbering logic."""
# Get number of prompts from config
num_prompts = get_num_prompts()
# Create a sample historic prompts list
historic_prompts = []
for i in range(60):
historic_prompts.append({
f"prompt{i:02d}": f"Old prompt {i}"
})
print(f"Original prompts: {len(historic_prompts)}")
print(f"First prompt key: {list(historic_prompts[0].keys())[0]}")
print(f"Last prompt key: {list(historic_prompts[-1].keys())[0]}")
print(f"Number of prompts from config: {num_prompts}")
# Simulate adding new prompts (as the current code would create them)
new_prompts = []
for i in range(num_prompts):
new_prompts.append({
f"prompt{len(historic_prompts) + i:02d}": f"New prompt {i}"
})
print(f"\nNew prompts to add: {len(new_prompts)}")
for i, prompt in enumerate(new_prompts):
print(f" New prompt {i}: {list(prompt.keys())[0]}")
# Prepend new prompts (reverse to maintain order)
for prompt in reversed(new_prompts):
historic_prompts.insert(0, prompt)
print(f"\nAfter prepending: {len(historic_prompts)} prompts")
print(f"First 3 prompts keys:")
for i in range(3):
print(f" {i}: {list(historic_prompts[i].keys())[0]}")
# Renumber all prompts
renumbered_prompts = []
for i, prompt_dict in enumerate(historic_prompts):
prompt_key = list(prompt_dict.keys())[0]
prompt_text = prompt_dict[prompt_key]
new_prompt_key = f"prompt{i:02d}"
renumbered_prompts.append({
new_prompt_key: prompt_text
})
print(f"\nAfter renumbering: {len(renumbered_prompts)} prompts")
print(f"First 10 prompts keys:")
for i in range(10):
print(f" prompt{i:02d}: {list(renumbered_prompts[i].keys())[0]} = {renumbered_prompts[i][f'prompt{i:02d}'][:30]}...")
# Keep only first 60
if len(renumbered_prompts) > 60:
renumbered_prompts = renumbered_prompts[:60]
print(f"\nAfter keeping only first 60: {len(renumbered_prompts)} prompts")
print(f"First prompt: {list(renumbered_prompts[0].keys())[0]} = {renumbered_prompts[0]['prompt00'][:30]}...")
print(f"Last prompt: {list(renumbered_prompts[-1].keys())[0]} = {renumbered_prompts[-1]['prompt59'][:30]}...")
# Verify the range
for i in range(60):
expected_key = f"prompt{i:02d}"
actual_key = list(renumbered_prompts[i].keys())[0]
if expected_key != actual_key:
print(f"ERROR: Expected {expected_key}, got {actual_key}")
return False
print("\n✅ All tests passed! Prompt numbering is correct.")
return True
if __name__ == "__main__":
test_renumbering()

55
tests/test_feedback_integration.py
View File

@@ -1,55 +0,0 @@
#!/usr/bin/env python3
"""
Test script to verify feedback_words integration
"""
import sys
import os
# Add the parent directory to the Python path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from generate_prompts import JournalPromptGenerator
def test_feedback_words_loading():
"""Test that feedback_words are loaded correctly."""
print("Testing feedback_words integration...")
try:
# Initialize the generator
generator = JournalPromptGenerator()
# Check if feedback_words were loaded
print(f"Number of feedback words loaded: {len(generator.feedback_words)}")
if generator.feedback_words:
print("Feedback words loaded successfully:")
for i, feedback in enumerate(generator.feedback_words):
print(f" {i+1}. {feedback}")
else:
print("No feedback words loaded (this might be expected if file is empty)")
# Test _prepare_prompt_with_count method
print("\nTesting _prepare_prompt_with_count method...")
prompt_with_count = generator._prepare_prompt_with_count(3)
print(f"Prompt with count length: {len(prompt_with_count)} characters")
# Check if feedback words are included in the prompt with count
if generator.feedback_words and "Feedback words:" in prompt_with_count:
print("✓ Feedback words are included in the prompt with count")
else:
print("✗ Feedback words are NOT included in the prompt with count")
print("\n✅ All tests passed!")
return True
except Exception as e:
print(f"\n❌ Error during testing: {e}")
import traceback
traceback.print_exc()
return False
if __name__ == "__main__":
success = test_feedback_words_loading()
sys.exit(0 if success else 1)

67
tests/test_valid_response.py
View File

@@ -1,67 +0,0 @@
#!/usr/bin/env python3
"""
Test the error handling with a valid response.
"""
import sys
import os
import json
# Add the parent directory to the Python path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from generate_prompts import JournalPromptGenerator
def test_valid_response():
"""Test with a valid JSON response."""
# Create a mock generator
generator = JournalPromptGenerator(config_path=".env")
# Create a valid response with 4 prompts as a list (new format)
valid_response = [
"Write about a time when you felt truly at peace.",
"Describe your ideal morning routine in detail.",
"What are three things you're grateful for today?",
"Reflect on a recent challenge and what you learned from it."
]
# Convert to JSON string
json_response = json.dumps(valid_response)
print("\n=== Test: Valid JSON response (list format) ===")
result = generator._parse_ai_response(json_response)
print(f"Number of prompts extracted: {len(result)}")
print(f"Type of result: {type(result)}")
for i, prompt_text in enumerate(result):
print(f"Prompt {i+1}: {prompt_text[:50]}...")
# Test with backticks
print("\n=== Test: Valid JSON response with backticks ===")
backticks_response = f"```json\n{json_response}\n```"
result = generator._parse_ai_response(backticks_response)
print(f"Number of prompts extracted: {len(result)}")
# Test with "json" prefix
print("\n=== Test: Valid JSON response with 'json' prefix ===")
json_prefix_response = f"json\n{json_response}"
result = generator._parse_ai_response(json_prefix_response)
print(f"Number of prompts extracted: {len(result)}")
# Test fallback for old dictionary format
print("\n=== Test: Fallback for old dictionary format ===")
old_format_response = {
"newprompt0": "Write about a time when you felt truly at peace.",
"newprompt1": "Describe your ideal morning routine in detail.",
"newprompt2": "What are three things you're grateful for today?",
"newprompt3": "Reflect on a recent challenge and what you learned from it."
}
json_old_response = json.dumps(old_format_response)
result = generator._parse_ai_response(json_old_response)
print(f"Number of prompts extracted: {len(result)}")
if __name__ == "__main__":
test_valid_response()