225 lines
8.5 KiB
Python
225 lines
8.5 KiB
Python
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#!/usr/bin/env python3
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"""
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quiXzoom Academy — Bildgenerator
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Använder OpenAI DALL-E 3 för att generera pedagogiska bilder
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"""
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import os
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import requests
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import json
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from datetime import datetime
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from pathlib import Path
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# OpenAI API-nyckel (från AAMOS)
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OPENAI_API_KEY = "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"
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# S3-konfiguration
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S3_BUCKET = "quixzoom-landing-prod"
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# Bilder att generera
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IMAGES = {
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"m1l1": {
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"title": "Välkommen till quiXzoom",
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"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."
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},
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"m2l1": {
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"title": "AI-granskning av bilder",
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"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. Blue and green accents."
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},
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"m2l2": {
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"title": "Ljus och exponering",
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"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."
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},
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"m2l3": {
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"title": "Fokus och skärpa",
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"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."
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},
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"m2l4": {
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"title": "Framing och komposition",
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"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."
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},
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"m3l1": {
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"title": "GPS-accuracy",
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"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."
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},
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"m4l1": {
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"title": "Personlig säkerhet",
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"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."
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},
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"m5l1": {
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"title": "Batch-fotografering",
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"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."
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},
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"m6l1": {
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"title": "Utbetalningsflöde",
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"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."
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}
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}
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def generate_image(image_id: str, prompt: str) -> str:
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"""Generera bild med DALL-E 3"""
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url = "https://api.openai.com/v1/images/generations"
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headers = {
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"Authorization": f"Bearer {OPENAI_API_KEY}",
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"Content-Type": "application/json"
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}
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payload = {
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"model": "dall-e-3",
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"prompt": prompt,
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"size": "1792x1024",
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"quality": "standard",
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"n": 1
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}
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try:
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response = requests.post(url, headers=headers, json=payload, timeout=60)
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if response.status_code == 200:
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data = response.json()
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image_url = data['data'][0]['url']
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return image_url
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else:
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print(f" ❌ OpenAI fel: {response.status_code}")
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print(f" {response.text[:200]}")
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return None
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except Exception as e:
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print(f" ❌ Fel: {e}")
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return None
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def download_image(url: str, filename: str) -> bool:
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"""Ladda ner bild från URL"""
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try:
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response = requests.get(url, timeout=30)
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if response.status_code == 200:
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with open(filename, 'wb') as f:
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f.write(response.content)
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return True
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else:
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print(f" ❌ Kunde inte ladda ner bild: {response.status_code}")
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return False
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except Exception as e:
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print(f" ❌ Fel vid nedladdning: {e}")
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return False
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def upload_to_s3(local_path: str, s3_key: str) -> str:
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"""Ladda upp bild till S3"""
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import subprocess
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cmd = [
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"aws", "s3", "cp", local_path,
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f"s3://{S3_BUCKET}/{s3_key}",
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"--acl", "public-read",
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"--content-type", "image/png"
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]
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result = subprocess.run(cmd, capture_output=True, text=True)
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if result.returncode == 0:
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url = f"https://{S3_BUCKET}.s3.eu-north-1.amazonaws.com/{s3_key}"
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print(f" ✅ Uppladdad: {url}")
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return url
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else:
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print(f" ❌ S3-fel: {result.stderr}")
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return None
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def generate_all_images():
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"""Generera alla bilder för Academy"""
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print("🎨 quiXzoom Academy — Bildgenerator (DALL-E 3)")
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print("=" * 60)
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# Skapa output-mapp
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output_dir = Path("academy-images")
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output_dir.mkdir(exist_ok=True)
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results = []
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for image_id, image_data in IMAGES.items():
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print(f"\n📚 {image_data['title']}")
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print(f" ID: {image_id}")
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# Generera bild
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image_url = generate_image(image_id, image_data['prompt'])
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if image_url:
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print(f" ✅ Bild genererad")
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print(f" 📥 Laddar ner...")
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# Ladda ner bild
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local_path = output_dir / f"{image_id}.png"
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if download_image(image_url, str(local_path)):
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print(f" ✅ Sparad: {local_path}")
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# Ladda upp till S3
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s3_key = f"academy/images/{image_id}.png"
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s3_url = upload_to_s3(str(local_path), s3_key)
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if s3_url:
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results.append({
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"id": image_id,
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"title": image_data['title'],
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"url": s3_url,
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"status": "completed"
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})
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else:
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print(f" ❌ Kunde inte ladda ner")
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else:
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print(f" ❌ Kunde inte generera bild")
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# Spara sammanfattning
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summary = {
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"generated_at": datetime.utcnow().isoformat(),
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"total_images": len(IMAGES),
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"successful": len(results),
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"failed": len(IMAGES) - len(results),
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"images": results
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}
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with open(output_dir / "summary.json", "w") as f:
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json.dump(summary, f, indent=2)
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print(f"\n{'=' * 60}")
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print(f"✅ {len(results)}/{len(IMAGES)} bilder genererade och uppladdade")
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print(f"📄 Sammanfattning: academy-images/summary.json")
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return summary
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if __name__ == "__main__":
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import sys
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if len(sys.argv) > 1 and sys.argv[1] == "--generate":
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generate_all_images()
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else:
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print("Användning:")
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print(" python generate-academy-images.py --generate")
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print("")
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print("Detta kommer att:")
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print(" 1. Generera 9 pedagogiska bilder med DALL-E 3")
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print(" 2. Ladda ner bilderna lokalt")
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print(" 3. Ladda upp till S3 (quixzoom-landing-prod)")
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print("")
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print("Kostnad: ~$0.20 per bild (totalt ~$1.80)")
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print("")
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# Testa API-nyckel
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print("Testar API-nyckel...")
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test = requests.get(
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"https://api.openai.com/v1/models",
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headers={"Authorization": f"Bearer {OPENAI_API_KEY}"}
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)
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if test.status_code == 200:
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print("✅ API-nyckel fungerar!")
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print(f" Tillgängliga modeller: {len(test.json().get('data', []))}")
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else:
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print(f"❌ API-nyckel fungerar inte: {test.status_code}")
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