Comprehensive AI content generation suite with multiple providers and services
Project description
📖 DeepWiki Documentation: https://deepwiki.com/donghaozhang/video-agent-claude-skill
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
73 AI models across 12 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 |
flux_dev |
$0.004 | Highest quality (12B params) |
Text-to-Video (Top Picks)
| Model | Cost | Best For |
|---|---|---|
veo3 |
$2.50-6.00 | Google's latest with audio |
sora_2 |
$0.40-1.20 | OpenAI quality |
kling_3_pro |
$0.50-1.12 | Latest Kling generation |
Image-to-Video (Top Picks)
| Model | Cost | Best For |
|---|---|---|
veo_3_1_fast |
$1.20 | Google's latest i2v |
sora_2 |
$0.40-1.20 | OpenAI quality |
kling_3_pro |
$0.50-1.12 | Latest Kling generation |
Cost-Saving Tip: Use
--mockflag for FREE validation:aicp generate-image --text "test" --mock
See full models reference for all 73 models with pricing.
Latest Release
What's New in v1.0.24
- Native structured output for LLM calls (eliminates JSON parsing fragility)
- Character portrait registry for visual consistency across scenes
- Per-chapter output organization with meaningful file names
- Documentation overhaul: slimmed README, updated all 73 models reference
- CI fix for optional
richdependency in vimax test suite
Installation
From PyPI
pip install video-ai-studio
Binary (no Python required)
Download standalone binaries from GitHub Releases:
# Linux
curl -L https://github.com/donghaozhang/video-agent-skill/releases/download/latest/aicp-linux-x86_64 -o aicp
chmod +x aicp
# macOS (Apple Silicon)
curl -L https://github.com/donghaozhang/video-agent-skill/releases/download/latest/aicp-macos-arm64 -o aicp
chmod +x aicp
# Windows
curl -L https://github.com/donghaozhang/video-agent-skill/releases/download/latest/aicp-windows-x64.exe -o aicp.exe
Development Mode
git clone https://github.com/donghaozhang/video-agent-skill.git
cd video-agent-skill
pip install -e .
API Keys Setup
After installation, configure your API keys:
-
Create a
.envfile:curl -o .env https://raw.githubusercontent.com/donghaozhang/video-agent-skill/main/.env.example
-
Add your API keys:
# 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
-
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
Quick Start
CLI Commands
# List all available AI models
aicp list-models
# Generate image from text
aicp generate-image --text "epic space battle" --model flux_dev
# Create video (text -> image -> video)
aicp create-video --text "serene mountain lake"
# Run custom pipeline from YAML config
aicp run-chain --config config.yaml --input "cyberpunk city"
# Analyze video with AI
aicp analyze-video -i video.mp4
# Generate avatar with lipsync
aicp generate-avatar --audio speech.mp3 --image portrait.jpg
# Transcribe audio
aicp transcribe --input audio.mp3
# Generate image grid
aicp generate-grid --text "mountain landscape" --layout 2x2
# Create example configurations
aicp create-examples
Unix-Style Flags
All commands support machine-readable output for scripting and CI:
# JSON output for piping to jq
aicp list-models --json | jq '.text_to_video[]'
# Quiet mode (suppress non-essential output)
aicp create-video --text "sunset" --quiet
# Read prompt from stdin
echo "cinematic drone shot" | aicp create-video --input -
# Stream progress as JSONL events
aicp run-chain --config pipeline.yaml --stream
# Combine for CI usage
aicp run-chain --config pipeline.yaml --json --quiet | jq -r '.outputs.final.path'
Python API
from 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")
Documentation
For detailed guides and references, see the full documentation:
| Topic | Link |
|---|---|
| Setup & Installation | Setup Guide |
| All 73 AI Models | Models Reference |
| CLI Commands | CLI Reference |
| YAML Pipelines | Pipeline Guide |
| Cost Management | Cost Guide |
| Architecture | Architecture Overview |
| Package Structure | Package Reference |
| Testing | Testing Guide |
| Python API | API Reference |
| Troubleshooting | FAQ & Troubleshooting |
| Contributing | Contributing Guide |
| Changelog | Version History |
| Development Guide | CLAUDE.md |
Contributing
- Follow the development patterns in CLAUDE.md
- Add tests for new features
- Update documentation as needed
- Test installation in fresh virtual environment
- Commit with descriptive messages
Project details
Release history Release notifications | RSS feed
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