Upload rewrite_slide.py with huggingface_hub

rewrite_slide.py

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+"""Fast rewrite as slides - no AI needed, extracts key points + images from article."""
+from main import app
+from fastapi import Request
+from fastapi.responses import JSONResponse
+import requests, re, time, random, json, os
+from bs4 import BeautifulSoup
+from urllib.parse import quote
+
+UA = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', 'Accept-Language': 'vi-VN,vi;q=0.9'}
+
+try:
+    from main import _load_wall, _save_wall
+except:
+    _data_dir = "/data" if os.path.isdir("/data") else "/app/data"
+    _wall_file = os.path.join(_data_dir, "wall_posts.json")
+    def _load_wall():
+        try:
+            if os.path.exists(_wall_file):
+                with open(_wall_file, 'r', encoding='utf-8') as f: return json.load(f)
+        except: pass
+        return []
+    def _save_wall(posts):
+        try:
+            os.makedirs(os.path.dirname(_wall_file), exist_ok=True)
+            with open(_wall_file+'.tmp', 'w', encoding='utf-8') as f: json.dump(posts[:100], f, ensure_ascii=False)
+            os.replace(_wall_file+'.tmp', _wall_file)
+        except: pass
+
+
+def _clean(s): return re.sub(r'\s+', ' ', str(s or '')).strip()
+
+
+def _scrape_article_full(url):
+    """Scrape article: extract paragraphs + ALL images."""
+    try:
+        r = requests.get(url, headers=UA, timeout=15, allow_redirects=True)
+        r.encoding = 'utf-8'
+        soup = BeautifulSoup(r.text, 'lxml')
+        for tag in soup.find_all(['script', 'style', 'nav', 'footer', 'aside', 'form']): tag.decompose()
+        
+        # Title
+        h1 = soup.find('h1')
+        ogt = soup.find('meta', property='og:title')
+        title = (h1.get_text(strip=True) if h1 else '') or (ogt.get('content', '') if ogt else '')
+        
+        # OG image
+        ogi = soup.find('meta', property='og:image')
+        og_img = ogi.get('content', '') if ogi else ''
+        if og_img and og_img.startswith('//'): og_img = 'https:' + og_img
+        
+        # Find content block
+        block = None
+        for sel in ['article', '.singular-content', '.detail-content', '.fck_detail', '.content-detail', '.knc-content', 'main', '.cms-body', '.article__body']:
+            el = soup.select_one(sel)
+            if el and len(el.find_all('p')) >= 2: block = el; break
+        if not block: block = soup.body or soup
+        
+        # Extract paragraphs and images IN ORDER
+        paragraphs = []
+        images = []
+        seen_imgs = set()
+        
+        if og_img and og_img not in seen_imgs:
+            images.append(og_img)
+            seen_imgs.add(og_img)
+        
+        for el in block.find_all(['p', 'h2', 'h3', 'figure', 'img'], recursive=True):
+            if el.name == 'p':
+                t = _clean(el.get_text(strip=True))
+                if t and len(t) > 40:
+                    paragraphs.append(t)
+            elif el.name in ('figure', 'img'):
+                im = el if el.name == 'img' else el.find('img')
+                if im:
+                    src = im.get('data-src') or im.get('src') or im.get('data-original') or ''
+                    if src and 'base64' not in src:
+                        if src.startswith('//'): src = 'https:' + src
+                        if src not in seen_imgs:
+                            images.append(src)
+                            seen_imgs.add(src)
+        
+        return {'title': _clean(title), 'paragraphs': paragraphs, 'images': images, 'og_img': og_img}
+    except Exception as e:
+        return None
+
+
+def _extract_key_points(paragraphs, max_points=5):
+    """Extract key points: take first sentence of each significant paragraph."""
+    points = []
+    for p in paragraphs:
+        if len(points) >= max_points: break
+        # Take first complete sentence (ends with . ! ?)
+        m = re.match(r'^(.+?[.!?])\s', p)
+        if m:
+            sentence = m.group(1)
+        else:
+            sentence = p[:150] + ('.' if not p.endswith('.') else '')
+        
+        # Skip if too short or duplicate
+        if len(sentence) < 30: continue
+        if any(sentence[:50] in existing for existing in points): continue
+        
+        points.append(sentence)
+    
+    return points
+
+
+@app.post("/api/rewrite_slide")
+async def api_rewrite_slide(request: Request):
+    """
+    Fast rewrite as SLIDES:
+    - Extract key points from article (1 sentence each, full and complete)
+    - Pair each point with an image from the article
+    - Return as slides array for frontend to display
+    - Save to Tường AI
+    NO AI NEEDED - instant response.
+    """
+    body = await request.json()
+    url = _clean(body.get("url", ""))
+    context = body.get("context", "")
+    
+    if not url and not context:
+        return JSONResponse({"error": "Cần URL hoặc nội dung"}, status_code=400)
+    
+    # Scrape article
+    data = None
+    if url and url.startswith("http"):
+        data = _scrape_article_full(url)
+    
+    if not data and context:
+        # Use context passed from frontend
+        paragraphs = [_clean(p) for p in context.split('\n') if len(_clean(p)) > 40]
+        data = {'title': paragraphs[0][:80] if paragraphs else 'Bài viết', 'paragraphs': paragraphs, 'images': [], 'og_img': ''}
+    
+    if not data or not data.get('paragraphs'):
+        return JSONResponse({"error": "Không đọc được bài viết"}, status_code=422)
+    
+    # Extract key points
+    points = _extract_key_points(data['paragraphs'], max_points=6)
+    if not points:
+        return JSONResponse({"error": "Không tìm được ý chính"}, status_code=422)
+    
+    # Build slides: pair each point with an image
+    images = data.get('images', [])
+    slides = []
+    for i, point in enumerate(points):
+        img = images[i] if i < len(images) else (images[-1] if images else '')
+        # Proxy dantri images
+        if img and 'cdnphoto.dantri' in img:
+            img = '/api/proxy/img?url=' + quote(img, safe='')
+        slides.append({
+            'text': point,
+            'image': img,
+            'index': i + 1
+        })
+    
+    # Create post for Tường AI
+    summary_text = '\n\n'.join([f"• {s['text']}" for s in slides])
+    # Auto voice + emotion based on topic (reuse ai_ext detector if available)
+    try:
+        from ai_ext import _detect_voice_emotion
+        _voice, _emotion = _detect_voice_emotion(data['title'], summary_text)
+    except Exception:
+        _voice, _emotion = "hoaimy", "trung_tinh"
+    post = {
+        "id": str(int(time.time() * 1000)) + str(random.randint(100, 999)),
+        "title": data['title'],
+        "text": summary_text,
+        "img": images[0] if images else '',
+        "url": url,
+        "kind": "slide_summary",
+        "slides": slides,
+        "images": images[:10],
+        "video": "",
+        "voice": _voice,
+        "emotion": _emotion,
+        "ts": int(time.time())
+    }
+    
+    # Save to wall
+    posts = _load_wall()
+    posts.insert(0, post)
+    _save_wall(posts)
+    
+    return JSONResponse({"post": post, "slides": slides})