AI Content Generation Suite

A comprehensive AI content generation package with multiple providers and services, consolidated into a single installable package.

⚡ Production-ready Python package with comprehensive CLI, parallel execution, and enterprise-grade architecture

🎬 Demo Video

Click to watch the complete demo of AI Content Generation Suite in action

🎨 Available AI Models

40+ AI models across 8 categories - showing top picks below. See full models reference for complete list.

Text-to-Image (Top Picks)

| Model | Cost | Best For | |-------|------|----------| | nano_banana_pro | $0.002 | Fast & high-quality | | gpt_image_1_5 | $0.003 | GPT-powered generation |

Image-to-Video (Top Picks)

| Model | Cost | Best For | |-------|------|----------| | sora_2 | $0.40-1.20 | OpenAI quality | | kling_2_6_pro | $0.50-1.00 | Professional quality |

Text-to-Video (Top Picks)

| Model | Cost | Best For | |-------|------|----------| | sora_2 | $0.40-1.20 | OpenAI quality | | kling_2_6_pro | $0.35-1.40 | Quality + audio |

💡 Cost-Saving Tip: Use --mock flag for FREE validation: ai-content-pipeline generate-image --text "test" --mock

📚 View all 40+ models →

🏷️ Latest Release

What's New in v1.0.18

• ✅ Automated PyPI publishing via GitHub Actions
• 🔧 Consolidated setup files for cleaner package structure
• 🎯 All 40+ AI models with comprehensive parallel processing support
• 📦 Improved CI/CD workflow with skip-existing option

🚀 FLAGSHIP: AI Content Pipeline

The unified AI content generation pipeline with parallel execution support, multi-model integration, and YAML-based configuration.

Core Capabilities

• 🔄 Unified Pipeline Architecture - YAML/JSON-based configuration for complex multi-step workflows
• ⚡ Parallel Execution Engine - 2-3x performance improvement with thread-based parallel processing
• 🎯 Type-Safe Configuration - Pydantic models with comprehensive validation
• 💰 Cost Management - Real-time cost estimation and tracking across all services
• 📊 Rich Logging - Beautiful console output with progress tracking and performance metrics

AI Service Integrations

• 🖼️ FAL AI - Text-to-image, image-to-image, text-to-video, video generation, avatar creation
• 🗣️ ElevenLabs - Professional text-to-speech with 20+ voice options
• 🎥 Google Vertex AI - Veo video generation and Gemini text generation
• 🔗 OpenRouter - Alternative TTS and chat completion services

Developer Experience

• 🛠️ Professional CLI - Comprehensive command-line interface with Click
• 📦 Modular Architecture - Clean separation of concerns with extensible design
• 🧪 Comprehensive Testing - Unit and integration tests with pytest
• 📚 Type Hints - Full type coverage for excellent IDE support

📦 Installation

Quick Start

# Install from PyPI
pip install video-ai-studio

# Or install in development mode
pip install -e .

🔑 API Keys Setup

After installation, you need to configure your API keys:

1. Download the example configuration:

   # Option 1: Download from GitHub
   curl -o .env https://raw.githubusercontent.com/donghaozhang/video-agent-skill/main/.env.example
   
   # Option 2: Create manually
   touch .env

2. Add your API keys to .env:

   # Required for most functionality
   FAL_KEY=your_fal_api_key_here
   
   # Optional - add as needed
   GEMINI_API_KEY=your_gemini_api_key_here
   OPENROUTER_API_KEY=your_openrouter_api_key_here
   ELEVENLABS_API_KEY=your_elevenlabs_api_key_here

3. Get API keys from:

   • FAL AI: https://fal.ai/dashboard (required for most models)
   • Google Gemini: https://makersuite.google.com/app/apikey
   • OpenRouter: https://openrouter.ai/keys
   • ElevenLabs: https://elevenlabs.io/app/settings

📋 Dependencies

The package installs core dependencies automatically. See requirements.txt for the complete list.

🛠️ Quick Start

Console Commands

# List all available AI models
ai-content-pipeline list-models

# Generate image from text
ai-content-pipeline generate-image --text "epic space battle" --model flux_dev

# Create video (text → image → video)
ai-content-pipeline create-video --text "serene mountain lake"

# Run custom pipeline from YAML config
ai-content-pipeline run-chain --config config.yaml --input "cyberpunk city"

# Create example configurations
ai-content-pipeline create-examples

# Shortened command alias
aicp --help

Python API

from packages.core.ai_content_pipeline.pipeline.manager import AIPipelineManager

# Initialize manager
manager = AIPipelineManager()

# Quick video creation
result = manager.quick_create_video(
    text="serene mountain lake",
    image_model="flux_dev",
    video_model="auto"
)

# Run custom chain
chain = manager.create_chain_from_config("config.yaml")
result = manager.execute_chain(chain, "input text")

📚 Package Structure

Core Packages

• ai_content_pipeline - Main unified pipeline with parallel execution

Provider Packages

Google Services

• google-veo - Google Veo video generation (Vertex AI)

FAL AI Services

• fal-video - Video generation (MiniMax Hailuo-02, Kling Video 2.1)
• fal-text-to-video - Text-to-video (Hailuo Pro, Veo 3, Kling v2.6 Pro, Sora 2/Pro)
• fal-image-to-video - Image-to-video (Veo 3, Hailuo, Kling, Wan v2.6)
• fal-avatar - Avatar generation with TTS integration
• fal-text-to-image - Text-to-image (Imagen 4, Seedream v3, FLUX.1)
• fal-image-to-image - Image transformation (Luma Photon Flash)
• fal-video-to-video - Video processing (ThinksSound + Topaz)

Service Packages

• text-to-speech - ElevenLabs TTS integration (20+ voices)
• video-tools - Video processing utilities with AI analysis

🔧 Configuration

Environment Setup

Create a .env file in the project root:

# FAL AI API Configuration
FAL_KEY=your_fal_api_key

# Google Cloud Configuration (for Veo)
PROJECT_ID=your-project-id
OUTPUT_BUCKET_PATH=gs://your-bucket/veo_output/

# ElevenLabs Configuration
ELEVENLABS_API_KEY=your_elevenlabs_api_key

# Optional: Gemini for AI analysis
GEMINI_API_KEY=your_gemini_api_key

# Optional: OpenRouter for additional models
OPENROUTER_API_KEY=your_openrouter_api_key

YAML Pipeline Configuration

name: "Text to Video Pipeline"
description: "Generate video from text prompt"
steps:
  - name: "generate_image"
    type: "text_to_image"
    model: "flux_dev"
    aspect_ratio: "16:9"
    
  - name: "create_video"
    type: "image_to_video"
    model: "kling_video"
    input_from: "generate_image"
    duration: 8

Parallel Execution

Enable parallel processing for 2-3x speedup:

# Enable parallel execution
PIPELINE_PARALLEL_ENABLED=true ai-content-pipeline run-chain --config config.yaml

Example parallel pipeline configuration:

name: "Parallel Processing Example"
steps:
  - type: "parallel_group"
    steps:
      - type: "text_to_image"
        model: "flux_schnell"
        params:
          prompt: "A cat"
      - type: "text_to_image"
        model: "flux_schnell"
        params:
          prompt: "A dog"
      - type: "text_to_image"
        model: "flux_schnell"
        params:
          prompt: "A bird"

💰 Cost Management

Cost Estimation

Always estimate costs before running pipelines:

# Estimate cost for a pipeline
ai-content-pipeline estimate-cost --config config.yaml

Typical Costs

• Text-to-Image: $0.001-0.004 per image
• Image-to-Image: $0.01-0.05 per modification
• Text-to-Video: $0.08-6.00 per video (model dependent)
• Avatar Generation: $0.02-0.05 per video
• Text-to-Speech: Varies by usage (ElevenLabs pricing)
• Video Processing: $0.05-2.50 per video (model dependent)

Cost-Conscious Usage

• Use cheaper models for prototyping (flux_schnell, hailuo)
• Test with small batches before large-scale generation
• Monitor costs with built-in tracking

🧪 Testing

# Quick tests
python tests/run_all_tests.py --quick

📋 See tests/README.md for complete testing guide.

💰 Cost Management

Estimation

• FAL AI Video: ~$0.05-0.10 per video
• FAL AI Text-to-Video: ~$0.08 (MiniMax) to $2.50-6.00 (Google Veo 3)
• FAL AI Avatar: ~$0.02-0.05 per video
• FAL AI Images: ~$0.001-0.01 per image
• Text-to-Speech: Varies by usage (ElevenLabs pricing)

Best Practices

1. Always run test_setup.py first (FREE)
2. Use cost estimation in pipeline manager
3. Start wi