feat: Add sample content generation script

- Standalone script to demonstrate full content generation workflow
- Uses ContentOrchestrator to generate text, images, and compliance checks
- Supports custom briefs and products via JSON files
- Includes sample brief and product data for testing

Author: hunterjam

content-gen/scripts/sample_content_generation.py

@@ -0,0 +1,361 @@
+#!/usr/bin/env python3
+"""
+Sample Content Generation Script
+
+This script demonstrates how to use the ContentOrchestrator to generate
+complete marketing content packages including text and images.
+
+Prerequisites:
+1. Set up environment variables (or use a .env file):
+   - AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpoint
+   - AZURE_OPENAI_GPT_MODEL: GPT model deployment name
+   - AZURE_OPENAI_GPT_IMAGE_ENDPOINT: (Optional) Endpoint for images
+   - AZURE_OPENAI_IMAGE_MODEL: Image model name (e.g., gpt-image-1)
+   - AZURE_COSMOS_ENDPOINT: Your CosmosDB endpoint
+   - AZURE_COSMOS_DATABASE_NAME: content-generation
+   - AZURE_COSMOS_CONVERSATIONS_CONTAINER: conversations
+   
+2. Ensure you have RBAC access:
+   - "Cognitive Services OpenAI User" role on the Azure OpenAI resource
+   - "Cosmos DB Built-in Data Contributor" on CosmosDB (if using products)
+
+Usage:
+    python sample_content_generation.py
+    python sample_content_generation.py --no-images
+    python sample_content_generation.py --output results.json
+"""
+
+import asyncio
+import argparse
+import json
+import os
+import sys
+from datetime import datetime
+from pathlib import Path
+
+# Add the backend directory to the path
+backend_path = Path(__file__).parent.parent / "src" / "backend"
+sys.path.insert(0, str(backend_path))
+
+# Now import the orchestrator and models
+from orchestrator import ContentOrchestrator
+from models import CreativeBrief
+
+
+def create_sample_brief() -> CreativeBrief:
+    """Create a sample creative brief for testing."""
+    return CreativeBrief(
+        overview="Spring home refresh campaign promoting interior paint colors",
+        objectives="Drive awareness and consideration for spring paint collection, increase website traffic by 20%",
+        target_audience="Homeowners aged 30-55, interested in DIY home improvement and interior design",
+        key_message="Transform your home this spring with our fresh, on-trend paint colors that bring warmth and style to any room",
+        tone_and_style="Inspiring, approachable, and aspirational. Use warm, inviting language that speaks to the joy of home improvement",
+        deliverable="Social media carousel post (3-5 images) with captions for Instagram and Facebook",
+        timelines="Launch by March 15th for spring campaign",
+        visual_guidelines="Bright, airy rooms with natural lighting. Show before/after transformations. Feature paint swatches in context. Modern, clean aesthetic",
+        cta="Shop the Spring Collection - Visit our website for color inspiration",
+        raw_input="Sample brief for testing content generation"
+    )
+
+
+def create_sample_products() -> list:
+    """Create sample product data for testing."""
+    return [
+        {
+            "id": "sample-1",
+            "product_name": "Morning Mist",
+            "description": "A soft, ethereal blue-gray that evokes early morning calm. Perfect for bedrooms and living spaces.",
+            "tags": "blue, gray, soft, calming, bedroom, living room",
+            "price": 45.99,
+            "image_url": "https://example.com/morning-mist.jpg"
+        },
+        {
+            "id": "sample-2", 
+            "product_name": "Sunlit Meadow",
+            "description": "A warm, golden yellow that brings sunshine indoors. Ideal for kitchens and breakfast nooks.",
+            "tags": "yellow, warm, sunny, kitchen, cheerful",
+            "price": 42.99,
+            "image_url": "https://example.com/sunlit-meadow.jpg"
+        },
+        {
+            "id": "sample-3",
+            "product_name": "Forest Haven",
+            "description": "A rich, deep green inspired by lush forest canopies. Creates a sophisticated, grounding atmosphere.",
+            "tags": "green, deep, sophisticated, nature, accent wall",
+            "price": 48.99,
+            "image_url": "https://example.com/forest-haven.jpg"
+        }
+    ]
+
+
+async def generate_content_sample(
+    brief: CreativeBrief = None,
+    products: list = None,
+    generate_images: bool = True,
+    output_path: str = None
+) -> dict:
+    """
+    Generate a complete content package using the orchestrator.
+    
+    Args:
+        brief: Creative brief (uses sample if not provided)
+        products: Products to feature (uses samples if not provided)
+        generate_images: Whether to generate images
+        output_path: Path to save results JSON (optional)
+    
+    Returns:
+        Dictionary with generation results
+    """
+    # Use defaults if not provided
+    brief = brief or create_sample_brief()
+    products = products or create_sample_products()
+    
+    print(f"\n{'='*70}")
+    print("CONTENT GENERATION SAMPLE")
+    print(f"{'='*70}")
+    print(f"\nCreative Brief Overview: {brief.overview}")
+    print(f"Target Audience: {brief.target_audience}")
+    print(f"Deliverable: {brief.deliverable}")
+    print(f"Products: {len(products)} items")
+    print(f"Generate Images: {generate_images}")
+    
+    print(f"\n{'='*70}")
+    print("Initializing Content Orchestrator...")
+    print(f"{'='*70}\n")
+    
+    # Create and initialize the orchestrator
+    orchestrator = ContentOrchestrator()
+    orchestrator.initialize()
+    
+    print("Orchestrator initialized successfully!")
+    print("\nGenerating content...\n")
+    
+    # Generate the content
+    start_time = datetime.now()
+    
+    results = await orchestrator.generate_content(
+        brief=brief,
+        products=products,
+        generate_images=generate_images
+    )
+    
+    elapsed = (datetime.now() - start_time).total_seconds()
+    
+    # Display results
+    print(f"\n{'='*70}")
+    print("GENERATION RESULTS")
+    print(f"{'='*70}")
+    print(f"\nTime elapsed: {elapsed:.1f} seconds")
+    
+    # Text content
+    if results.get("text_content"):
+        print(f"\n{'─'*40}")
+        print("TEXT CONTENT:")
+        print(f"{'─'*40}")
+        text_content = results["text_content"]
+        # Show first 1000 chars
+        if len(text_content) > 1000:
+            print(text_content[:1000] + "\n\n[...truncated...]")
+        else:
+            print(text_content)
+    
+    # Image prompt
+    if results.get("image_prompt"):
+        print(f"\n{'─'*40}")
+        print("IMAGE PROMPT:")
+        print(f"{'─'*40}")
+        print(results["image_prompt"][:500] + "..." if len(results.get("image_prompt", "")) > 500 else results["image_prompt"])
+    
+    # Generated image
+    if results.get("generated_image"):
+        print(f"\n{'─'*40}")
+        print("GENERATED IMAGE:")
+        print(f"{'─'*40}")
+        img = results["generated_image"]
+        if img.get("success"):
+            print(f"✅ Image generated successfully")
+            print(f"   Model: {img.get('model', 'unknown')}")
+            if img.get("image_base64"):
+                print(f"   Data size: {len(img['image_base64']) / 1024:.1f} KB (base64)")
+        else:
+            print(f"❌ Image generation failed: {img.get('error', 'unknown error')}")
+    
+    # Compliance
+    if results.get("compliance"):
+        print(f"\n{'─'*40}")
+        print("COMPLIANCE CHECK:")
+        print(f"{'─'*40}")
+        print(results["compliance"])
+    
+    if results.get("violations"):
+        print(f"\n⚠️ Violations found: {len(results['violations'])}")
+        for v in results["violations"]:
+            print(f"   - {v}")
+    
+    if results.get("requires_modification"):
+        print("\n⚠️ Content requires modification before publishing")
+    
+    # Save results if output path provided
+    if output_path:
+        # Prepare results for JSON serialization
+        output_data = {
+            "timestamp": datetime.now().isoformat(),
+            "elapsed_seconds": elapsed,
+            "brief": brief.model_dump(),
+            "products": products,
+            "generate_images": generate_images,
+            "results": {
+                "text_content": results.get("text_content"),
+                "image_prompt": results.get("image_prompt"),
+                "compliance": results.get("compliance"),
+                "violations": results.get("violations"),
+                "requires_modification": results.get("requires_modification"),
+            }
+        }
+        
+        # Handle generated image separately (base64 can be large)
+        if results.get("generated_image"):
+            img = results["generated_image"]
+            output_data["results"]["generated_image"] = {
+                "success": img.get("success"),
+                "model": img.get("model"),
+                "error": img.get("error"),
+                "revised_prompt": img.get("revised_prompt"),
+                # Store base64 in separate file to keep JSON readable
+                "has_image_data": bool(img.get("image_base64"))
+            }
+            
+            # Save image to separate file if successful
+            if img.get("success") and img.get("image_base64"):
+                import base64
+                image_path = output_path.replace(".json", "_image.png")
+                image_data = base64.b64decode(img["image_base64"])
+                with open(image_path, "wb") as f:
+                    f.write(image_data)
+                output_data["results"]["generated_image"]["image_file"] = image_path
+                print(f"\n📁 Image saved to: {image_path}")
+        
+        with open(output_path, "w") as f:
+            json.dump(output_data, f, indent=2)
+        print(f"📁 Results saved to: {output_path}")
+    
+    return results
+
+
+async def main():
+    """Main entry point for the sample script."""
+    parser = argparse.ArgumentParser(
+        description="Generate marketing content using the Content Orchestrator"
+    )
+    parser.add_argument(
+        "--no-images",
+        action="store_true",
+        help="Skip image generation"
+    )
+    parser.add_argument(
+        "--output", "-o",
+        type=str,
+        default=None,
+        help="Output file path for results JSON"
+    )
+    parser.add_argument(
+        "--brief-file",
+        type=str,
+        default=None,
+        help="Path to JSON file containing creative brief"
+    )
+    parser.add_argument(
+        "--products-file",
+        type=str,
+        default=None,
+        help="Path to JSON file containing products list"
+    )
+    
+    args = parser.parse_args()
+    
+    # Load brief from file if provided
+    brief = None
+    if args.brief_file:
+        with open(args.brief_file, "r") as f:
+            brief_data = json.load(f)
+            brief = CreativeBrief(**brief_data)
+    
+    # Load products from file if provided
+    products = None
+    if args.products_file:
+        with open(args.products_file, "r") as f:
+            products = json.load(f)
+    
+    # Generate content
+    try:
+        result = await generate_content_sample(
+            brief=brief,
+            products=products,
+            generate_images=not args.no_images,
+            output_path=args.output
+        )
+        
+        print(f"\n{'='*70}")
+        print("✅ Content generation completed!")
+        print(f"{'='*70}\n")
+        
+        sys.exit(0)
+        
+    except Exception as e:
+        print(f"\n❌ Error during content generation: {e}")
+        import traceback
+        traceback.print_exc()
+        sys.exit(1)
+
+
+# Example: Custom brief and products
+async def custom_example():
+    """Example with custom brief and products."""
+    
+    # Custom brief for a summer promotion
+    brief = CreativeBrief(
+        overview="Summer outdoor living promotion for patio furniture",
+        objectives="Increase summer patio sales by 30%, drive foot traffic to showrooms",
+        target_audience="Suburban homeowners, 35-60, with outdoor entertaining spaces",
+        key_message="Create your perfect outdoor oasis with our premium patio collection",
+        tone_and_style="Relaxed, aspirational, lifestyle-focused. Evoke summer gatherings and outdoor relaxation",
+        deliverable="Email banner and 2 social media posts",
+        timelines="Launch Memorial Day weekend",
+        visual_guidelines="Outdoor settings at golden hour, families enjoying patios, lush greenery, modern outdoor furniture",
+        cta="Explore the Summer Collection - 20% off this weekend only"
+    )
+    
+    # Custom products
+    products = [
+        {
+            "id": "patio-1",
+            "product_name": "Sunset Lounger",
+            "description": "Premium outdoor chaise lounge with weather-resistant cushions in coastal blue",
+            "tags": "patio, lounge, outdoor, blue, relaxation",
+            "price": 599.99
+        },
+        {
+            "id": "patio-2",
+            "product_name": "Garden Dining Set",
+            "description": "6-piece aluminum dining set with tempered glass table, perfect for outdoor entertaining",
+            "tags": "patio, dining, aluminum, entertaining, family",
+            "price": 1299.99
+        }
+    ]
+    
+    results = await generate_content_sample(
+        brief=brief,
+        products=products,
+        generate_images=True,
+        output_path="custom_content_results.json"
+    )
+    
+    return results
+
+
+if __name__ == "__main__":
+    # Run the main function
+    asyncio.run(main())
+    
+    # Uncomment below to run custom example instead:
+    # asyncio.run(custom_example())