"""Screenshot & Vision Analysis — takes screenshots and classifies with local LLM."""
import base64, json, subprocess, tempfile, os, urllib.request, time

OLLAMA_URL = "http://10.30.20.186:11434"
VISION_MODEL = "minicpm-v4.5:8b"  # Best local vision model available

def take_screenshot(url, width=1280, height=900):
    """Take a screenshot of a URL using Playwright."""
    try:
        from playwright.sync_api import sync_playwright
        with sync_playwright() as p:
            browser = p.chromium.launch(headless=True)
            page = browser.new_page(viewport={'width': width, 'height': height})
            page.goto(url, wait_until='networkidle', timeout=15000)
            time.sleep(1)  # Let page settle
            screenshot = page.screenshot(full_page=False)
            browser.close()
            return screenshot
    except ImportError:
        # Fallback: use macos screencapture via Safari (less reliable)
        return None
    except Exception as e:
        print(f"Screenshot error for {url}: {e}")
        return None

def screenshot_to_base64(screenshot_bytes):
    """Convert screenshot bytes to base64 for Ollama."""
    return base64.b64encode(screenshot_bytes).decode('utf-8')

def analyze_screenshot(url, screenshot_bytes, processor_name):
    """Analyze a screenshot using local vision model to describe the site."""
    if not screenshot_bytes:
        return generate_placeholder_description(url, processor_name)
    
    img_b64 = screenshot_to_base64(screenshot_bytes)
    
    prompt = f"""Look at this screenshot of a website. The site likely uses {processor_name} as a payment processor.
Describe this site in 2-3 sentences covering:
1. What type of site is this? (e-commerce, gambling, SaaS, adult, CBD, firearms, subscription, crypto, etc.)
2. What does it sell or offer?
3. What's the overall vibe/quality level?

Respond with just the description, no prefixes."""
    
    try:
        req = urllib.request.Request(
            f"{OLLAMA_URL}/api/generate",
            data=json.dumps({
                "model": VISION_MODEL,
                "prompt": prompt,
                "images": [img_b64],
                "stream": False,
                "options": {"temperature": 0.3, "num_predict": 150}
            }).encode(),
            headers={"Content-Type": "application/json"}
        )
        resp = urllib.request.urlopen(req, timeout=30)
        data = json.loads(resp.read())
        return data.get('response', '').strip()
    except Exception as e:
        print(f"Vision analysis error: {e}")
        return generate_placeholder_description(url, processor_name)

def generate_placeholder_description(url, processor_name):
    """Generate a description when vision isn't available."""
    domain = urllib.parse.urlparse(url).netloc.replace('www.', '')
    return f"Website at {domain}. Uses {processor_name} for payment processing. Visit the site to learn more about their products and services."

def batch_analyze(sites, processor_name, max_screenshots=5):
    """Analyze multiple sites with screenshots."""
    results = []
    for i, site in enumerate(sites[:max_screenshots]):
        url = site.get('url', '')
        if not url:
            continue
        
        print(f"  Screenshot {i+1}/{min(len(sites), max_screenshots)}: {site.get('domain','?')}")
        screenshot = take_screenshot(url)
        description = analyze_screenshot(url, screenshot, processor_name)
        
        results.append({
            **site,
            'description': description,
            'screenshot_available': screenshot is not None,
            'screenshot_base64': screenshot_to_base64(screenshot) if screenshot else None
        })
    return results