boc/generate-academy-images-aamos.py

#!/usr/bin/env python3
"""
quiXzoom Academy — Bildgenerator via AAMOS
Använder AAMOS video-pipeline DALL-E integration
"""

import requests
import json
import os
from pathlib import Path

# AAMOS API-konfiguration
AAMOS_BASE = "http://localhost:3100"
SVEN_KEY = "sven-aamos-integration-2026-wavult"

# Bilder att generera
IMAGES = {
    "m1l1": {
        "title": "Välkommen till quiXzoom",
        "prompt": "A friendly illustration of a person with a smartphone photographing a bridge at sunset. Modern, clean style with blue (#0066FF) and green (#00C853) colors. Pedagogical feel, not photorealistic. 16:9 format. The person looks happy and professional. Warm lighting."
    },
    "m2l1": {
        "title": "AI-granskning av bilder",
        "prompt": "A technical illustration showing AI analysis of a photograph. Split image: left side shows original photo of a bridge, right side shows AI analysis overlay with color-coded indicators marking sharpness, lighting, and composition. Futuristic but pedagogical style."
    },
    "m2l2": {
        "title": "Ljus och exponering",
        "prompt": "Three photos in a row showing the same bridge from the same angle: 1. Left: Underexposed (too dark, details lost), 2. Middle: Perfectly exposed (golden hour, warm light, all details visible), 3. Right: Overexposed (too bright, washed out). Photorealistic style. Educational comparison."
    },
    "m2l3": {
        "title": "Fokus och skärpa",
        "prompt": "Two photos showing a road sign: left image is blurry and out of focus, right image is razor sharp with a magnifying glass effect showing crisp details. Photorealistic with graphic overlay elements. Educational comparison style."
    },
    "m2l4": {
        "title": "Framing och komposition",
        "prompt": "A bridge photographed with correct composition. Overlay showing rule of thirds grid lines, arrow pointing to main subject, green markings indicating good composition. Educational diagram style with photo-realistic base. Clean and modern."
    },
    "m3l1": {
        "title": "GPS-accuracy",
        "prompt": "A technical illustration of a city map from above with a smartphone in the center. 4 GPS satellites above sending signals to the phone. Color-coded accuracy circles around the phone: green (accurate, small circle), yellow (medium), red (low accuracy, large circle). Modern, clean style."
    },
    "m4l1": {
        "title": "Personlig säkerhet",
        "prompt": "A person wearing a reflective safety vest and holding a smartphone, photographing a bridge from a safe distance. Traffic cone, safety distance marked with dashed lines, passing car in background. Modern, friendly illustration style. Blue and orange accents."
    },
    "m5l1": {
        "title": "Batch-fotografering",
        "prompt": "A stylized map illustration with multiple photo points (A, B, C, D, E) connected by an optimized green route. A person with smartphone efficiently following the route. Modern map style with blue and green colors. Clean and pedagogical."
    },
    "m6l1": {
        "title": "Utbetalningsflöde",
        "prompt": "A horizontal flow diagram showing: 1. Approved photo (green checkmark) → 2. AI review (robot icon) → 3. Approval (stamp) → 4. Payment (money/bank icon) → 5. Money in account (happy person). Modern, clean illustration with icons and arrows. Green and blue colors."
    }
}

def generate_via_aamos(image_id: str, prompt: str) -> str:
    """Generera bild via AAMOS video-pipeline"""
    
    url = f"{AAMOS_BASE}/api/aamos/video-pipeline/thumbnail/generate"
    
    headers = {
        "Content-Type": "application/json",
        "x-sven-key": SVEN_KEY
    }
    
    payload = {
        "videoId": f"academy-{image_id}",
        "imagePrompt": prompt,
        "size": "1792x1024"
    }
    
    try:
        response = requests.post(url, headers=headers, json=payload, timeout=60)
        
        if response.status_code == 200:
            data = response.json()
            if data.get('imageUrl'):
                return data['imageUrl']
            else:
                print(f"   ⚠️  Ingen bild-URL i svaret: {data.get('error', 'Okänt fel')}")
                return None
        else:
            print(f"   ⚠️  AAMOS fel: {response.status_code}")
            print(f"      {response.text[:200]}")
            return None
    
    except Exception as e:
        print(f"   ⚠️  Fel: {e}")
        return None

def download_image(url: str, filename: str) -> bool:
    """Ladda ner bild från URL"""
    
    try:
        response = requests.get(url, timeout=30)
        
        if response.status_code == 200:
            with open(filename, 'wb') as f:
                f.write(response.content)
            return True
        else:
            print(f"   ❌ Kunde inte ladda ner: {response.status_code}")
            return False
    
    except Exception as e:
        print(f"   ❌ Fel: {e}")
        return False

def upload_to_s3(local_path: str, s3_key: str) -> str:
    """Ladda upp till S3"""
    
    import subprocess
    
    cmd = [
        "aws", "s3", "cp", local_path,
        f"s3://quixzoom-landing-prod/{s3_key}",
        "--acl", "public-read",
        "--content-type", "image/png"
    ]
    
    result = subprocess.run(cmd, capture_output=True, text=True)
    
    if result.returncode == 0:
        url = f"https://quixzoom-landing-prod.s3.eu-north-1.amazonaws.com/{s3_key}"
        print(f"   ✅ Uppladdad: {url}")
        return url
    else:
        print(f"   ❌ S3-fel: {result.stderr}")
        return None

def generate_all_images():
    """Generera alla bilder"""
    
    print("🎨 quiXzoom Academy — Bildgenerator via AAMOS")
    print("=" * 60)
    
    output_dir = Path("academy-images-final")
    output_dir.mkdir(exist_ok=True)
    
    results = []
    
    for image_id, image_data in IMAGES.items():
        print(f"\n📚 {image_data['title']}")
        
        # Generera via AAMOS
        image_url = generate_via_aamos(image_id, image_data['prompt'])
        
        if image_url:
            print(f"   ✅ Bild genererad")
            print(f"   📥 Laddar ner...")
            
            local_path = output_dir / f"{image_id}.png"
            
            if download_image(image_url, str(local_path)):
                print(f"   ✅ Sparad")
                
                # Ladda upp till S3
                s3_key = f"academy/images/{image_id}.png"
                s3_url = upload_to_s3(str(local_path), s3_key)
                
                if s3_url:
                    results.append({
                        "id": image_id,
                        "title": image_data['title'],
                        "url": s3_url
                    })
        else:
            print(f"   ❌ Kunde inte generera")
    
    print(f"\n{'=' * 60}")
    print(f"✅ {len(results)}/{len(IMAGES)} bilder genererade")
    
    return results

if __name__ == "__main__":
    import sys
    
    if len(sys.argv) > 1 and sys.argv[1] == "--generate":
        generate_all_images()
    else:
        print("Användning:")
        print("  python generate-academy-images-aamos.py --generate")
        print("")
        print("Detta kommer att:")
        print("  1. Ansluta till AAMOS video-pipeline API")
        print("  2. Generera 9 pedagogiska bilder med DALL-E")
        print("  3. Ladda upp till S3")
        print("")
        print("Testar anslutning...")
        
        try:
            r = requests.get(f"{AAMOS_BASE}/health", timeout=5)
            if r.status_code == 200:
                print("✅ AAMOS är tillgänglig!")
            else:
                print(f"⚠️  AAMOS svarade: {r.status_code}")
        except:
            print("❌ Kunde inte ansluta till AAMOS")