docs/PHASE2D_REALTIME_DATA_TO_IMAGE_GUIDE.md

CompI Phase 2.D: Real-Time Data Feeds to Image Generation

🌎 Overview

Phase 2.D connects your art to the pulse of the world through real-time data feeds. This phase integrates live weather data, breaking news, financial markets, and other real-time information to create artwork that captures the current moment in time and reflects the world's dynamic state.

✨ Key Features

🌐 Real-Time Data Integration

• Weather Data: Live weather conditions from OpenWeatherMap API
• News Headlines: Breaking news from RSS feeds and NewsAPI
• Financial Data: Cryptocurrency prices and exchange rates
• Social Trends: Real-time social media and trending topics (extensible)
• Custom RSS Feeds: Support for any RSS/XML data source

🧠 Intelligent Context Processing

• Data Summarization: Automatic summarization of multiple data sources
• Mood Detection: Extract emotional context from real-time data
• Theme Analysis: Identify key themes and topics
• Temporal Context: Time-aware data processing and analysis
• Artistic Inspiration: Convert data patterns into creative prompts

🔧 Technical Capabilities

• Data Caching: Intelligent caching to respect API rate limits
• Batch Processing: Multiple data source configurations
• Temporal Series: Generate art evolution over time
• Error Handling: Robust fallback mechanisms for API failures
• Comprehensive Metadata: Detailed real-time context tracking

🛠️ Installation & Setup

Prerequisites

Ensure you have the base CompI environment set up with all dependencies from requirements.txt.

Additional Dependencies

Phase 2.D uses additional packages for real-time data processing:

pip install requests feedparser

API Keys (Optional)

While Phase 2.D works with free data sources, you can enhance functionality with API keys:

OpenWeatherMap (Weather Data)

1. Sign up at OpenWeatherMap
2. Get your free API key (1000 calls/day)
3. Enter in the interface or set as environment variable

NewsAPI (News Data)

1. Sign up at NewsAPI
2. Get your free API key (100 requests/day)
3. Enter in the interface or set as environment variable

Note: Phase 2.D works without API keys using free RSS feeds and demo keys.

🎯 Quick Start

1. Launch the Interface

# Navigate to your CompI project directory
cd "C:\Users\Aksharajsinh\Documents\augment-projects\Project CompI"

# Run the Phase 2.D interface
streamlit run src/ui/compi_phase2d_streamlit_ui.py

# Or use the main CompI interface
streamlit run compi_complete_app.py
# Then select "🌎 Phase 2.D: Real-Time Data-to-Image"

2. Basic Real-Time Generation

1. Enter your creative prompt (e.g., "A cityscape reflecting today's energy")
2. Choose your art style (e.g., "cyberpunk digital art")
3. Enable data sources (Weather, News, or Financial)
4. Configure data settings (city for weather, news category, etc.)
5. Generate and watch real-time data transform into art!

3. Advanced Features

• Batch Processing: Generate multiple images with different data combinations
• Temporal Series: Create art evolution over time intervals
• Context Strength: Control how strongly real-time data influences the art
• Data Preview: See real-time context before generation

📚 Data Sources & Examples

🌤️ Weather Data Integration

Current Weather Conditions

# Example: Sunny weather in Paris
Weather Context: "Clear skies, 22°C, low humidity"
Artistic Influence: "bright and optimistic atmosphere"
Enhanced Prompt: "Parisian street scene, impressionist style, bright and optimistic atmosphere"

Weather Mood Mapping

• Clear/Sunny: Bright, optimistic, radiant
• Cloudy: Contemplative, soft, muted
• Rainy: Melancholic, reflective, dramatic
• Stormy: Intense, powerful, dynamic
• Snowy: Serene, peaceful, ethereal
• Foggy: Mysterious, ethereal, dreamlike

📰 News Data Integration

Breaking News Headlines

# Example: Technology news
Headlines: "AI breakthrough in medical research; New space mission launched"
Artistic Influence: "capturing the pulse of current events, inspired by innovation"
Enhanced Prompt: "Futuristic laboratory, sci-fi art, capturing innovation and discovery"

News Category Mapping

• Technology: Futuristic, innovative, digital
• Science: Discovery, exploration, analytical
• World: Global, diverse, interconnected
• Business: Dynamic, structured, professional
• General: Contemporary, relevant, timely

💹 Financial Data Integration

Market Conditions

# Example: Rising Bitcoin price
Financial Context: "Bitcoin: $45,000 USD, USD/EUR: 0.85"
Artistic Influence: "reflecting market dynamics and economic energy"
Enhanced Prompt: "Abstract composition, geometric art, reflecting economic energy and growth"

Market Mood Indicators

• Rising Markets: Energetic, upward, optimistic
• Falling Markets: Dramatic, intense, volatile
• Stable Markets: Balanced, steady, calm
• High Volatility: Dynamic, chaotic, electric

🎨 Creative Workflows

1. Moment Capture Workflow

Goal: Capture the current moment in artistic form

1. Enable all data sources (Weather + News + Financial)
2. Use high context strength (0.8-1.0)
3. Choose responsive styles (abstract, impressionist, contemporary)
4. Generate immediately to capture the current moment

2. Temporal Evolution Workflow

Goal: Show how the world changes over time

1. Configure temporal series (e.g., every 30 minutes)
2. Use consistent prompt and style
3. Enable news feeds for evolving content
4. Create time-lapse art series

3. Location-Based Workflow

Goal: Create art reflecting specific locations

1. Enable weather data for target city
2. Use location-specific news if available
3. Choose appropriate styles (landscape, urban, cultural)
4. Incorporate local context in prompts

4. Thematic Workflow

Goal: Focus on specific themes or topics

1. Select relevant news categories (technology, science, etc.)
2. Use thematic prompts aligned with data
3. Adjust context strength based on desired influence
4. Create thematic art series

🔧 Advanced Usage

Programmatic Access

from src.generators.compi_phase2d_realtime_to_image import CompIPhase2DRealTimeToImage

# Initialize generator
generator = CompIPhase2DRealTimeToImage()

# Generate with weather data
results = generator.generate_image(
    text_prompt="A landscape reflecting today's weather",
    style="impressionist painting",
    include_weather=True,
    weather_city="Tokyo",
    weather_api_key="your_api_key",  # Optional
    context_strength=0.8,
    num_images=2
)

# Generate with news data
results = generator.generate_image(
    text_prompt="Abstract representation of current events",
    style="modern digital art",
    include_news=True,
    news_category="technology",
    max_news=5,
    context_strength=0.7
)

# Generate with all data sources
results = generator.generate_image(
    text_prompt="The world's current state",
    style="surreal digital art",
    include_weather=True,
    weather_city="New York",
    include_news=True,
    news_category="world",
    include_financial=True,
    context_strength=0.9
)

Batch Processing

# Multiple data source configurations
data_configs = [
    {"include_weather": True, "weather_city": "London"},
    {"include_news": True, "news_category": "technology"},
    {"include_financial": True},
    {"include_weather": True, "include_news": True, "include_financial": True}
]

results = generator.batch_process_data_sources(
    text_prompt="Global perspectives",
    style="contemporary art",
    data_source_configs=data_configs,
    context_strength=0.7
)

Temporal Series Generation

# Generate art evolution over time
results = generator.generate_temporal_series(
    text_prompt="The changing world",
    style="abstract expressionism",
    data_config={
        "include_weather": True,
        "weather_city": "Paris",
        "include_news": True,
        "news_category": "general"
    },
    time_intervals=[0, 30, 60, 120],  # 0, 30min, 1hr, 2hr
    context_strength=0.8
)

📊 Understanding Real-Time Context

Phase 2.D processes real-time data across multiple dimensions:

Data Processing Pipeline

1. Data Fetching: Retrieve data from multiple APIs and feeds
2. Caching: Store data to respect rate limits and improve performance
3. Analysis: Extract mood indicators, themes, and patterns
4. Summarization: Create concise summaries of current context
5. Artistic Translation: Convert data insights into creative prompts

Context Components

• Summary: Concise description of all data sources
• Mood Indicators: Emotional context derived from data
• Key Themes: Main topics and subjects identified
• Temporal Context: Time-aware contextual information
• Artistic Inspiration: Creative interpretation for prompt enhancement

Context Strength Levels

• High (0.7-1.0): Strong data influence, detailed context integration
• Medium (0.4-0.6): Moderate data influence, balanced integration
• Low (0.1-0.3): Subtle data influence, minimal context addition

🎯 Tips for Best Results

Data Source Selection

1. Weather: Best for location-specific, atmospheric art
2. News: Ideal for contemporary, socially-relevant themes
3. Financial: Great for abstract, dynamic, economic themes
4. Combined: Use multiple sources for rich, complex context

Prompt Engineering

1. Responsive prompts: Use prompts that can adapt to data context
2. Flexible styles: Choose styles that work with various moods
3. Context awareness: Consider how data might influence your vision
4. Temporal relevance: Use time-aware language when appropriate

Context Strength Guidelines

1. High strength: When data should drive the artistic direction
2. Medium strength: For balanced data-art integration
3. Low strength: When data should provide subtle inspiration
4. Variable strength: Experiment to find optimal balance

🔍 Troubleshooting

Common Issues

"No real-time data available"

• Check internet connection
• Verify API keys if using premium features
• Try different data sources
• Check API rate limits

"API connection failed"

• Verify API keys are correct
• Check if APIs are operational
• Try using free RSS feeds instead
• Reduce request frequency

"Weak data influence"

• Increase context strength
• Use more responsive prompts
• Enable multiple data sources
• Check data quality and relevance

Performance Optimization

• Use data caching to reduce API calls
• Enable only needed data sources
• Use appropriate context strength levels
• Monitor API rate limits and usage

🚀 Next Steps

After mastering Phase 2.D, consider:

1. Multimodal Fusion: Combine real-time data with emotions (2.C) or audio (2.A)
2. Custom Data Sources: Add your own RSS feeds or APIs
3. Temporal Art Projects: Create long-term data evolution series
4. Location-Based Art: Develop city or region-specific art projects
5. News Art Automation: Set up automated news-driven art generation

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Ready to connect your art to the world's pulse? Launch the interface and start creating real-time responsive artwork! 🌎📡🎨