Disclaimer: SceneCraft is a fictional project created solely to demonstrate the potential uses of libraries like Pydantic and TinyDB in enabling AI agents to easily and accurately pass data between them. It is not a real product and should not be used for production purposes.

SceneCraft - Automated Video Project Analysis

A comprehensive tool for automating video production workflows, including script analysis, scene breakdowns, post-production planning, and audience engagement optimization, using AI.

Features

• Script Analysis:
  • Scene segmentation and prioritization
  • Key theme extraction
  • Tone and style recommendations
• Production Planning:
  • Shot list generation
  • Equipment and resource requirements
  • Scene location recommendations
• Post-Production Optimization:
  • Editing flow mapping
  • Visual effect suggestions
  • Audience testing
• Report Generation:
  • Project summaries
  • Audience engagement insights
  • Scene-level performance analysis
  • Recommendations for distribution strategies
• JSON database for efficient data storage and retrieval
• Caching system to avoid redundant processing
• Structured response format with detailed insights

Script Organization

SceneCraft supports multi-project workflows with organized script storage:

1. Place your script (PDF or TXT) in the scripts/ directory.
2. Organize it for a specific project:
   • Create project-specific directories.
   • Move the script to data/projects/<project_name>/scripts/.
   • Maintain a log at scripts/script_log.json.

You can also specify a script path directly to organize the storage.

Running Analysis

After organizing your script, run any analysis process:

Available analysis types:

• Script Analysis
• Scene Breakdown
• Production Planning
• Post-Production Optimization

Report Generation

After running the analysis processes, you can generate a comprehensive video production report:

The report generation:

• Uses large language model for enhanced content synthesis.
• Creates structured markdown reports with sections for:
  • Project Summary
  • Scene Breakdown & Analysis
  • Shot List & Production Plan
  • Post-Production Optimization
  • Audience Engagement Insights
  • Recommendations for Distribution
• Automatically formats content with proper markdown styling.
• Saves reports to data/projects/<project_name>/reports/<script_name>/sections/.

Analysis Types and Example Responses

Script Analysis

• Scene segmentation and prioritization
• Key themes and tone suggestions
• Emotional resonance tracking
• Generative AI Involvement: large language model processes themes, tones, and emotional mapping.

Example Response:

{
  "scenes": [
    {"name": "Opening Scene", "priority": "high", "theme": "introduction of main conflict"},
    {"name": "Climactic Scene", "priority": "critical", "theme": "resolution of conflict"}
  ],
  "tone_suggestions": ["suspenseful", "uplifting"],
  "emotional_resonance": ["tension", "relief"]
}

Scene Breakdown

• Scene-level analysis
• Resource and equipment recommendations
• Shot list generation
• Generative AI Involvement: AI generates detailed shot lists and resource suggestions based on scene descriptions.

Example Response:

{
  "scene": "Opening Scene",
  "shots": [
    {"type": "Wide shot", "description": "Establish setting", "equipment": ["camera crane"]},
    {"type": "Close-up", "description": "Character reaction", "equipment": ["steadycam"]}
  ]
}

Production Planning

• Equipment and resource requirements
• Scene location recommendations
• Scheduling suggestions
• Generative AI Involvement: AI optimizes resource allocation and suggests ideal locations.

Example Response:

{
  "equipment": [
    {"item": "Camera Crane", "scenes": ["Opening Scene"]},
    {"item": "Lighting Kit", "scenes": ["Opening Scene", "Climactic Scene"]}
  ],
  "locations": [
    {"scene": "Opening Scene", "recommendation": "Downtown Plaza"},
    {"scene": "Climactic Scene", "recommendation": "Studio Set"}
  ]
}

Post-Production Optimization

• Editing flow mapping
• Visual effect suggestions
• Audience testing feedback
• Generative AI Involvement: AI suggests editing workflows and synthesizes audience feedback insights.

Example Response:

{
  "editing_flow": ["Organize clips", "Apply color grading", "Add visual effects"],
  "visual_effects": [
    {"scene": "Climactic Scene", "effect": "Explosion", "software": "After Effects"}
  ],
  "audience_feedback": [
    {"segment": "Young Adults", "reaction": "Highly engaged"},
    {"segment": "Seniors", "reaction": "Neutral"}
  ]
}

Data Storage

SceneCraft uses a multi-project storage system:

1. Project Configuration (data/config.json):

   • Tracks all projects and their metadata.
   • Stores project creation dates and settings.
   • Central configuration management.

2. Project-Specific Storage:

   • Scripts (data/projects/<project>/scripts/):

     • Scripts for analysis.
     • Organized by project.
     • Tracked in scripts/script_log.json.

   • TinyDB Database (data/projects/<project>/scenecraft.json):

     • Primary storage system.
     • Efficient querying and retrieval.
     • Automatic timestamping.
     • Data versioning support.

   • JSON Files (data/projects/<project>/responses/<file_name>/<analysis_type>.json):

     • Backward compatibility.
     • Human-readable format.
     • Easy manual inspection.

3. Script Log (scripts/script_log.json):

   • Tracks script organization history.
   • Records original and project-specific locations.
   • Maintains file metadata and timestamps.