#!/usr/bin/env python3
"""
Auto-post to website from image
Usage: python3 auto-post-website.py <image_path> <company_id> <brief_description>
"""

import sys
import base64
import requests
import json

# Configuration
API_URL = "https://your-website.com/api/posts"
API_TOKEN = "your-bearer-token-here"

def encode_image(image_path):
    """Convert image to base64"""
    with open(image_path, "rb") as f:
        return base64.b64encode(f.read()).decode("utf-8")

def generate_content(image_path, description, company_name):
    """Generate bilingual content using AI"""
    
    # Read image as base64 for context (optional - depends on your AI setup)
    image_base64 = encode_image(image_path)
    
    prompt = f"""Generate a bilingual website post about this image.

Context: {description}
Company: {company_name}

Generate in this JSON format:
{{
  "titleId": "Judul menarik dalam Bahasa Indonesia",
  "titleEn": "Compelling English title",
  "contentId": "Konten detail dalam Bahasa Indonesia (2-3 paragraf)",
  "contentEn": "Detailed content in English (2-3 paragraphs)",
  "captionId": "Caption singkat Indonesia",
  "captionEn": "Short English caption",
  "tags": ["tag1", "tag2", "tag3"]
}}

Guidelines:
- Professional tone suitable for company website
- Highlight key features or achievements
- Include relevant technical details if applicable
- SEO-friendly titles"""

    # Call your AI model (OpenClaw, OpenAI, etc.)
    # This is a placeholder - replace with actual AI call
    response = call_ai_model(prompt, image_base64)
    return json.loads(response)

def post_to_website(data, image_base64):
    """Post content to website API"""
    
    payload = {
        **data,
        "media": [image_base64]
    }
    
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {API_TOKEN}"
    }
    
    response = requests.post(API_URL, json=payload, headers=headers)
    return response.json()

def main():
    if len(sys.argv) < 4:
        print("Usage: python3 auto-post-website.py <image_path> <company_id> <description>")
        sys.exit(1)
    
    image_path = sys.argv[1]
    company_id = int(sys.argv[2])
    description = sys.argv[3]
    
    # Company mapping
    companies = {
        1: "Company A",
        2: "Company B", 
        3: "Company C",
        4: "Company D"
    }
    company_name = companies.get(company_id, "Unknown")
    
    print(f"📝 Processing image for {company_name}...")
    
    # Generate content
    content = generate_content(image_path, description, company_name)
    content["companyId"] = company_id
    
    print("✅ Content generated:")
    print(f"   ID Title: {content['titleId']}")
    print(f"   EN Title: {content['titleEn']}")
    
    # Encode image
    image_base64 = encode_image(image_path)
    
    # Post to website
    print("🚀 Posting to website...")
    result = post_to_website(content, image_base64)
    
    if result.get("success"):
        print(f"✅ Posted successfully!")
        print(f"   Post ID: {result.get('id')}")
        print(f"   URL: {result.get('url')}")
    else:
        print(f"❌ Failed: {result.get('error')}")
        sys.exit(1)

if __name__ == "__main__":
    main()

media = []
for img_path in image_paths:
    media.append(encode_image(img_path))
    
payload["media"] = media

def generate_tags(content):
    prompt = f"Generate 3-5 SEO tags for: {content['titleEn']}"
    tags = call_ai_model(prompt)
    return tags.split(", ")

from datetime import datetime, timedelta

payload["publishAt"] = (datetime.now() + timedelta(hours=1)).isoformat()

from PIL import Image

def resize_image(image_path, max_size=(1920, 1080)):
    img = Image.open(image_path)
    img.thumbnail(max_size)
    img.save(image_path, quality=85)

response = requests.post(API_URL, json=payload, headers=headers, timeout=30)