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README.md Normal file
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# 003-jeremy-vertex-ai-media-master
Comprehensive Google Vertex AI multimodal mastery for Jeremy - video processing (6+ hours), audio generation, image creation with Gemini 2.0/2.5 and Imagen 4. Marketing campaign automation, content generation, and media asset production.

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---
name: vertex-campaign
description: Generate complete multimodal marketing campaigns using Vertex AI - video, audio, images, copy for all channels
model: sonnet
---
# Generate Multimodal Marketing Campaign with Vertex AI
Create a comprehensive marketing campaign with all assets generated via Google Vertex AI multimodal capabilities.
## What This Does
1. **Campaign Brief Analysis**: Understand product, target audience, goals
2. **Asset Generation**: Create all required media assets
3. **Multi-Channel Content**: Generate content for all marketing channels
4. **Implementation Guide**: Provide deployment instructions
## Campaign Assets Generated
### Visual Assets (Imagen 4)
- Hero image (1920x1080)
- Social media graphics (Instagram, Facebook, LinkedIn)
- Display ad creatives (multiple sizes)
- Product lifestyle images
- A/B test variations
### Video Assets (Gemini 2.5 Pro)
- Video scripts (30s, 60s, 2min versions)
- Storyboard descriptions
- Video editing instructions
- Thumbnail designs
### Audio Assets (Lyria)
- Background music compositions
- Voiceover scripts
- Audio ad scripts
- Podcast episode outlines
### Written Content (Gemini 2.5 Pro)
- Email marketing sequences
- Blog post (SEO optimized)
- Social media captions
- PPC ad copy
- Landing page copy
## Usage
```bash
/vertex-campaign
```
Then provide campaign details:
- Product/service name
- Target audience
- Campaign objectives
- Brand guidelines
- Budget considerations
## Example Workflow
**Input:**
```
Product: Premium noise-canceling headphones
Audience: Remote workers, 25-45, tech-savvy
Goal: Product launch, 10K units in Q1
Budget: $50K
```
**Output:**
1. 15 product images (lifestyle, studio, use-cases)
2. 30s product launch video script
3. Background music track (energetic, professional)
4. Email sequence (5 emails)
5. Social media content (30 posts across platforms)
6. Blog post "Best Headphones for Remote Work 2025"
7. PPC campaigns (Google, Facebook, LinkedIn)
## Technical Implementation
**Step 1: Initialize Vertex AI**
```python
from google.cloud import aiplatform
from vertexai.preview.generative_models import GenerativeModel
from vertexai.preview.vision_models import ImageGenerationModel
aiplatform.init(project=PROJECT_ID, location="us-central1")
```
**Step 2: Generate Visual Assets**
```python
imagen = ImageGenerationModel.from_pretrained("imagen-4")
hero_image = imagen.generate_images(
prompt=f"Professional product photography of {product}, studio lighting, clean background",
number_of_images=1,
aspect_ratio="16:9"
)
```
**Step 3: Create Video Script**
```python
gemini = GenerativeModel("gemini-2.5-pro")
video_script = gemini.generate_content([
f"Create a 30-second video script for {product} targeting {audience}. Include scene descriptions, voiceover, music cues."
])
```
**Step 4: Generate Audio**
```python
from vertexai.preview.audio_models import AudioGenerationModel
lyria = AudioGenerationModel.from_pretrained("lyria")
background_music = lyria.generate_audio(
prompt=f"Background music for {product} video ad, {mood}, 30 seconds",
duration=30
)
```
**Step 5: Create Multi-Channel Copy**
```python
content = gemini.generate_content([
f"""Generate marketing content for {product}:
- 5-email drip campaign
- 10 Instagram captions
- 5 LinkedIn posts
- SEO blog post (1500 words)
- Google Ads copy (5 variations)"""
])
```
## Cost Estimation
**Per Campaign:**
- Visual Assets: $2-3 (50 images @ $0.04 each)
- Video Scripts: $0.50 (Gemini tokens)
- Audio: $1-2 (Lyria generation)
- Written Content: $1 (Gemini tokens)
**Total: ~$5-7 per complete campaign**
## Best Practices
1. **Brand Consistency**: Provide brand guidelines in prompt
2. **Batch Generation**: Generate multiple variations simultaneously
3. **Quality Control**: Review and iterate on generated assets
4. **Version Control**: Save prompts and outputs for reproducibility
5. **A/B Testing**: Generate 3-5 variations of each asset
## Integration with Marketing Stack
**Export to:**
- Google Ads (PMax campaigns)
- Meta Business Suite (Facebook/Instagram)
- LinkedIn Campaign Manager
- Email marketing platforms (HubSpot, Mailchimp)
- CMS platforms (WordPress, Contentful)
## Performance Tracking
**Monitor:**
- Asset generation time
- Cost per asset
- Approval rates
- Campaign performance metrics
- ROI vs traditional production
---
**This command turns Jeremy into a one-person marketing agency powered by Vertex AI multimodal capabilities.**

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---
name: Vertex AI Media Master
description: |
Automatic activation for ALL Google Vertex AI multimodal operations - video processing, audio generation, image creation, and marketing campaigns.
**TRIGGER PHRASES:**
- "vertex ai", "gemini multimodal", "process video", "generate audio", "create images", "marketing campaign"
- "imagen", "video understanding", "multimodal", "content generation", "media assets"
**AUTO-INVOKES FOR:**
- Video processing and understanding (up to 6 hours)
- Audio generation and transcription
- Image generation with Imagen 4
- Marketing campaign automation
- Social media content creation
- Ad creative generation
- Multimodal content workflows
allowed-tools: Read, Write, Edit, Grep, Glob, Bash
version: 1.0.0
---
# Vertex AI Media Master - Comprehensive Multimodal AI Operations
This Agent Skill provides comprehensive mastery of Google Vertex AI multimodal capabilities for video, audio, image, and text processing with focus on marketing applications.
## Core Capabilities
### 🎥 Video Processing (Gemini 2.0/2.5)
- **Video Understanding**: Process videos up to 6 hours at low resolution or 2 hours at default resolution
- **2M Context Window**: Gemini 2.5 Pro handles massive video content
- **Audio Track Processing**: Automatic audio transcription from video
- **Multi-video Analysis**: Process multiple videos in single request
- **Video Summarization**: Extract key moments, scenes, and insights
- **Marketing Use Cases**:
- Analyze competitor video ads
- Extract highlights from long-form content
- Generate video summaries for social media
- Transcribe and caption video content
- Identify brand mentions and product placements
### 🎵 Audio Generation & Processing
- **Lyria Model (2025)**: Native audio and music generation
- **Speech-to-Text**: Transcribe audio with speaker diarization
- **Text-to-Speech**: Generate natural voiceovers
- **Music Composition**: Background music for campaigns
- **Audio Enhancement**: Noise reduction and quality improvement
- **Marketing Use Cases**:
- Generate podcast scripts and voiceovers
- Create audio ads and radio spots
- Produce background music for video campaigns
- Transcribe customer interviews
- Generate multilingual voiceovers
### 🖼️ Image Generation (Imagen 4 & Gemini 2.5 Flash Image)
- **Imagen 4**: Highest quality text-to-image generation
- **Gemini 2.5 Flash Image**: Interleaved image generation with text
- **Style Transfer**: Apply brand styles to generated images
- **Product Visualization**: Generate product mockups
- **Campaign Assets**: Create ad creatives and social media graphics
- **Marketing Use Cases**:
- Generate personalized ad images (Adios solution)
- Create social media graphics at scale
- Produce product lifestyle images
- Generate A/B test variations
- Create branded campaign visuals
### 📢 Marketing Campaign Automation
- **ViGenAiR**: Convert long-form video ads to short formats automatically
- **Adios**: Generate personalized ad images tailored to audience context
- **Campaign Asset Generation**: Photos, soundtracks, voiceovers from prompts
- **Content Pipeline**: Email copy, blog posts, social media, PMax assets
- **Catalog Enrichment**: Multi-agent workflow for product onboarding
- **Marketing Use Cases**:
- Automated campaign asset production
- Personalized content at scale
- Multi-channel content distribution
- Product catalog enhancement
- Visual merchandising automation
### 🔧 Technical Implementation
**API Integration:**
```python
from google.cloud import aiplatform
from vertexai.preview.generative_models import GenerativeModel
# Initialize Vertex AI
aiplatform.init(project="your-project", location="us-central1")
# Gemini 2.5 Pro for video
model = GenerativeModel("gemini-2.5-pro")
# Process video with audio
response = model.generate_content([
"Analyze this video and extract key marketing insights",
video_file, # Up to 6 hours
])
# Imagen 4 for image generation
from vertexai.preview.vision_models import ImageGenerationModel
imagen = ImageGenerationModel.from_pretrained("imagen-4")
images = imagen.generate_images(
prompt="Professional product photo, studio lighting, white background",
number_of_images=4
)
```
**Gemini 2.5 Flash Image (Interleaved Generation):**
```python
# Generate images within text responses
model = GenerativeModel("gemini-2.5-flash-image")
response = model.generate_content([
"Create a 5-step recipe with images for each step"
])
# Returns text + images interleaved
```
**Audio Generation (Lyria):**
```python
from vertexai.preview.audio_models import AudioGenerationModel
lyria = AudioGenerationModel.from_pretrained("lyria")
audio = lyria.generate_audio(
prompt="Upbeat background music for product launch video, 30 seconds",
duration=30
)
```
### 📊 Marketing Workflow Automation
**1. Multi-Channel Campaign Creation:**
```python
# Single prompt generates all assets
campaign = model.generate_content([
"""Create a product launch campaign for [product]:
- Hero image (1920x1080)
- 3 social media graphics (1080x1080)
- 30-second video script
- Background music description
- Email marketing copy
- Instagram caption"""
])
```
**2. Video Repurposing Pipeline:**
```python
# Long-form to short-form conversion (ViGenAiR approach)
long_video = "gs://bucket/original-ad-60s.mp4"
response = model.generate_content([
f"Extract 3 engaging 15-second clips from this video for TikTok/Reels",
long_video
])
# Auto-generates format-specific versions
```
**3. Personalized Ad Generation:**
```python
# Context-aware image generation (Adios approach)
for audience in audiences:
ad_image = imagen.generate_images(
prompt=f"Product ad for {product}, targeting {audience.demographics}, {audience.style_preference}",
aspect_ratio="16:9"
)
```
### 🎯 Best Practices for Jeremy
**1. Project Setup:**
```bash
# Set environment variables
export GOOGLE_CLOUD_PROJECT="your-project-id"
export GOOGLE_APPLICATION_CREDENTIALS="path/to/service-account.json"
# Install SDK
pip install google-cloud-aiplatform[vision,audio] google-generativeai
```
**2. Rate Limits & Quotas:**
- Gemini 2.5 Pro: 2M tokens/min (video processing)
- Imagen 4: 100 images/min
- Monitor usage in Cloud Console
**3. Cost Optimization:**
- Use Gemini 2.5 Flash for faster, cheaper operations
- Batch image generation requests
- Cache video embeddings for repeated analysis
- Use low-resolution video setting when appropriate
**4. Security & Compliance:**
- Keep API keys in Secret Manager, never in code
- Use service accounts with minimal permissions
- Enable VPC Service Controls for data residency
- Log all API calls for audit trails
### 🚀 Advanced Marketing Use Cases
**1. Campaign Performance Analysis:**
```python
# Analyze competitor campaigns
competitor_videos = ["gs://bucket/competitor1.mp4", "gs://bucket/competitor2.mp4"]
analysis = model.generate_content([
"Compare these competitor videos: themes, messaging, CTAs, production quality",
*competitor_videos
])
```
**2. Content Localization:**
```python
# Generate multilingual campaigns
for lang in ["en", "es", "fr", "de", "ja"]:
localized_content = model.generate_content([
f"Translate and culturally adapt this campaign for {lang} market:",
campaign_brief,
hero_image
])
```
**3. A/B Test Generation:**
```python
# Generate variations automatically
variations = []
for style in ["minimalist", "bold", "luxury", "playful"]:
variation = imagen.generate_images(
prompt=f"Product ad, {style} style, {brand_guidelines}",
number_of_images=1
)
variations.append(variation)
```
### 📚 Reference Documentation
**Official Documentation:**
- Vertex AI Multimodal: https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/overview
- Gemini 2.5 Pro: https://cloud.google.com/vertex-ai/generative-ai/docs/models
- Imagen 4: https://cloud.google.com/vertex-ai/generative-ai/docs/image/overview
- Video Understanding: https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/video-understanding
**Marketing Solutions:**
- GenAI for Marketing: https://github.com/GoogleCloudPlatform/genai-for-marketing
- ViGenAiR (video repurposing)
- Adios (personalized ad images)
**Pricing:**
- Gemini 2.5 Pro: $3.50/1M input tokens, $10.50/1M output tokens
- Imagen 4: $0.04/image
- Video processing: Included in Gemini token pricing
## When This Skill Activates
This skill automatically activates when you mention:
- Video processing, analysis, or understanding
- Audio generation, music composition, or voiceovers
- Image generation, ad creatives, or visual content
- Marketing campaigns, content automation, or asset production
- Gemini multimodal capabilities
- Vertex AI media operations
- Social media content, email marketing, or PMax campaigns
## Integration with Other Tools
**Google Cloud Services:**
- Cloud Storage for media asset management
- BigQuery for campaign analytics
- Cloud Functions for automation triggers
- Vertex AI Pipelines for content workflows
**Third-Party Integrations:**
- Social media APIs (LinkedIn, Twitter, Instagram)
- Marketing automation platforms (HubSpot, Marketo)
- CMS integrations (WordPress, Contentful)
- DAM systems (Bynder, Cloudinary)
## Success Metrics
**Track These KPIs:**
- Asset generation speed (baseline: 5 images/min)
- Content approval rate (target: >80%)
- Campaign personalization scale (target: 1000+ variants)
- Cost per asset (target: <$0.10/image)
- Time saved vs manual production (target: 90% reduction)
---
**This skill makes Jeremy a Vertex AI multimodal expert with instant access to video processing, audio generation, image creation, and marketing automation capabilities.**

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# Skill Assets
This directory contains static assets used by this skill.
## Purpose
Assets can include:
- Configuration files (JSON, YAML)
- Data files
- Templates
- Schemas
- Test fixtures
## Guidelines
- Keep assets small and focused
- Document asset purpose and format
- Use standard file formats
- Include schema validation where applicable
## Common Asset Types
- **config.json** - Configuration templates
- **schema.json** - JSON schemas
- **template.yaml** - YAML templates
- **test-data.json** - Test fixtures

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# Skill References
This directory contains reference materials that enhance this skill's capabilities.
## Purpose
References can include:
- Code examples
- Style guides
- Best practices documentation
- Template files
- Configuration examples
## Guidelines
- Keep references concise and actionable
- Use markdown for documentation
- Include clear examples
- Link to external resources when appropriate
## Types of References
- **examples.md** - Usage examples
- **style-guide.md** - Coding standards
- **templates/** - Reusable templates
- **patterns.md** - Design patterns

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# Skill Scripts
This directory contains optional helper scripts that support this skill's functionality.
## Purpose
Scripts here can be:
- Referenced by the skill for automation
- Used as examples for users
- Executed during skill activation
## Guidelines
- All scripts should be well-documented
- Include usage examples in comments
- Make scripts executable (`chmod +x`)
- Use `#!/bin/bash` or `#!/usr/bin/env python3` shebangs
## Adding Scripts
1. Create script file (e.g., `analyze.sh`, `process.py`)
2. Add documentation header
3. Make executable: `chmod +x script-name.sh`
4. Test thoroughly before committing