genpark-agentic-voice-video-ad-skill
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Agentic Voice & Video Ad creator skill designed to generate interactive voice dialogue scripts and cinematic video prompts.
genpark-agentic-voice-video-ad-skill
GenPark AI Agent Skill -- # Agentic Voice & Video Ad Creator Skill
This repository contains the Agentic Voice & Video Ad Creator Skill — an agent skill configuration interface (skill.json), developer SDK client (voice_video_ad.py), and validation script for generating interactive audio/voice loops (Alexa+ style) and cinematic visual scene description prompts.
🚀 Capabilities
- Interactive Voice Assistant Flow: Generates voice dialogue loops prompting user engagement, mapping possible answers (yes, info, decline) to shopping cart transactions and assistant audio cues.
- Cinematic Video Prompt Synthesizer: Creates descriptive, highly detailed styling instructions (lighting, angles, textures) optimized for AI video models (Runway Gen-3, Grok Imagine, Sora).
- Atmospheric Cohesion: Automatically aligns visual prompts and voice scripts with a defined campaign mood (e.g. futuristic, comfort, luxury).
🛠️ Setup & Installation
Install dependencies:
pip install -r requirements.txtConfiguration:
Set your API environment variables if executing requests against the live production server (otherwise, client executes in mock mode):- PowerShell:
$env:AD_CREATOR_API_KEY="your_api_key" - bash:
export AD_CREATOR_API_KEY="your_api_key"
- PowerShell:
💻 SDK Usage Reference
from voice_video_ad import VoiceVideoAdClient
# Initialize Client (mock mode by default)
client = VoiceVideoAdClient()
# Generate Alexa+ style voice script
voice = client.generate_interactive_script(
product_name="Zenith Speaker",
pitch="Great sound.",
mood="futuristic"
)
print(voice["voice_script"])
print(voice["user_replies_mapped"])
# Generate cinematic video scene prompts
prompts = client.generate_video_prompts(
product_name="Zenith Speaker",
mood="futuristic"
)
print(prompts[0]["visual_prompt"])
📜 License
This project is licensed under the MIT License.
📊 Agentic Architecture Flowchart
graph LR
User([User / AI Agent]) -->|JSON Request| Skill[GenPark AI Skill]
Skill -->|Execution Logic| CoreEngine[Core Analytics & Processing]
CoreEngine -->|Structured Output| User
🔌 MCP (Model Context Protocol) Integration
Run natively as an MCP server for Cursor, Claude Desktop & LLM frameworks:
python mcp_server.py
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