Amazon Bedrock AgentCore implementation for optimizing TikTok Shop content for KrissKross fashion business.

This intelligent agent analyzes fashion products and generates:

• Viral Video Hooks: Compelling 3-second openers to stop scrolling
• Hashtag Strategies: Mix of trending, niche, and branded hashtags
• Content Angles: Creative approaches to showcase products
• Target Audience Profiles: Detailed demographic insights
• Posting Schedules: Optimal times for maximum engagement
• Engagement Tactics: Strategies to drive sales through TikTok Shop

AgentCore/
├── agent_config.py          # Agent configuration and settings
├── content_agent.py         # Main agent implementation
├── test_products.py         # Sample TikTok fashion products
├── run_agent.py            # Main execution script
├── requirements.txt        # Python dependencies
├── .env.example           # Environment variables template
└── README.md              # This file

pip install -r requirements.txt

Copy .env.example to .env and add your AWS credentials:

cp .env.example .env

Edit .env:

AWS_REGION=us-east-1
AWS_ACCESS_KEY_ID=your_actual_access_key
AWS_SECRET_ACCESS_KEY=your_actual_secret_key
BEDROCK_MODEL_ID=anthropic.claude-3-5-sonnet-20241022-v2:0

python run_agent.py

The agent comes pre-loaded with 5 TikTok fashion products:

1. Y2K Butterfly Crop Top - Nostalgic Y2K aesthetic
2. Baggy Cargo Pants - Streetwear utility style
3. Coquette Bow Mini Skirt - Romantic coquette aesthetic
4. Platform Chunky Sneakers - Retro dad shoe vibes
5. Vintage Graphic Baby Tee - 90s-inspired graphics

from content_agent import TikTokContentAgent, AgentConfig

# Initialize agent
config = AgentConfig(business_name="KrissKross")
agent = TikTokContentAgent(config)

# Analyze a product
product = {
    "name": "Oversized Denim Jacket",
    "category": "Outerwear",
    "description": "Vintage 90s style denim jacket",
    "price": 49.99,
    "features": ["Oversized fit", "Vintage wash"],
    "target_market": "Gen Z fashion enthusiasts"
}

result = agent.analyze_product(product)
print(agent.format_results(result))

The agent automatically falls back to mock responses if AWS credentials are not available, perfect for testing!

Each analysis generates:

╔══════════════════════════════════════════════════════════════╗
║  TikTok Content Strategy - [Product Name]
╚══════════════════════════════════════════════════════════════╝

📱 VIRAL VIDEO HOOKS (First 3 seconds)
─────────────────────────────────────────────────────
1. POV: You finally found THE product everyone's talking about 👀
...

🏷️  HASHTAG STRATEGY
─────────────────────────────────────────────────────
#TikTokShop #TikTokMadeMeBuyIt #KrissKross ...

🎬 CONTENT ANGLES
─────────────────────────────────────────────────────
1. Unboxing & First Impressions
...

🎯 TARGET AUDIENCE
─────────────────────────────────────────────────────
Fashion-forward Gen Z and Millennials...

⏰ OPTIMAL POSTING TIMES
─────────────────────────────────────────────────────
• Tuesday-Thursday: 7-9 AM EST
...

💡 ENGAGEMENT STRATEGY
─────────────────────────────────────────────────────
Post 2-3 times daily mixing product showcases...

1. AWS Account with Bedrock access
2. Claude 3.5 Sonnet model enabled in your region
3. IAM user with Bedrock permissions

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "bedrock:InvokeModel",
                "bedrock:InvokeModelWithResponseStream"
            ],
            "Resource": "arn:aws:bedrock:*::foundation-model/anthropic.claude-3-5-sonnet-*"
        }
    ]
}

Edit agent_config.py and update AGENT_INSTRUCTION to customize the agent's behavior and focus areas.

Edit test_products.py and add entries to TIKTOK_FASHION_PRODUCTS list.

Modify the format_results() method in content_agent.py.

Run with mock data (no AWS required):

python run_agent.py

The agent will automatically use mock responses if AWS credentials are not configured.

• Use Claude 3.5 Sonnet for best creative output
• Adjust temperature in config (0.7-0.9 for more creative hooks)
• Batch analyze products for efficiency
• Cache common hashtag strategies

This is a demonstration project for KrissKross TikTok Shop. Customize as needed for your business!

MIT License - feel free to use and modify for your own TikTok Shop business!

For AWS Bedrock setup help:

• AWS Bedrock Documentation
• Claude on Bedrock Guide

Transform your fashion products into viral TikTok content!