import os, re, json, time, random, html as html_lib, subprocess, uuid
from urllib.parse import quote_plus, quote, urlparse
from typing import Optional
import requests
from bs4 import BeautifulSoup
from fastapi import Request
from fastapi.responses import HTMLResponse, JSONResponse, FileResponse

from main import app

try:
    from huggingface_hub import AsyncInferenceClient
except Exception:
    AsyncInferenceClient = None
try:
    from gtts import gTTS
except Exception:
    gTTS = None
try:
    from PIL import Image, ImageDraw, ImageFont
except Exception:
    Image = ImageDraw = ImageFont = None


def _hf_token():
    for k in ("HF_TOKEN", "HUGGINGFACEHUB_API_TOKEN", "HUGGING_FACE_HUB_TOKEN", "HF_API_TOKEN"):
        v = os.getenv(k, "").strip()
        if v:
            return v
    return ""

HF_TOKEN = _hf_token()
QWEN_VL_MODEL = os.getenv("QWEN_VL_MODEL", "Qwen/Qwen2.5-VL-7B-Instruct")
DATA_DIR = "/data" if os.path.isdir("/data") else "/app/data"
WALL_FILE = os.path.join(DATA_DIR, "ai_wall_posts.json")
SHORTS_DIR = os.path.join(DATA_DIR, "ai_shorts")
HEADERS = {"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36","Accept-Language":"vi-VN,vi;q=0.9,en;q=0.8"}
LAST_QWEN_ERROR = ""


def _load_ai_wall():
    try:
        if os.path.exists(WALL_FILE):
            with open(WALL_FILE, "r", encoding="utf-8") as f:
                return json.load(f)
    except Exception:
        pass
    return []


def _save_ai_wall(posts):
    try:
        os.makedirs(os.path.dirname(WALL_FILE), exist_ok=True)
        tmp = WALL_FILE + ".tmp"
        with open(tmp, "w", encoding="utf-8") as f:
            json.dump(posts[:100], f, ensure_ascii=False)
        os.replace(tmp, WALL_FILE)
    except Exception:
        pass


def _clean_text(s: str) -> str:
    s = html_lib.unescape(s or "")
    return re.sub(r"\s+", " ", s).strip()


def _domain(u):
    try:
        return urlparse(u).netloc.replace("www.", "")
    except Exception:
        return ""


def _reader_url(target_url: str) -> str:
    safe = quote(target_url, safe=":/?#[]@!$&'()*+,;=%")
    return "https://r.jina.ai/http://" + safe


def jina_reader_markdown(url: str) -> str:
    jr = _reader_url(url)
    r = requests.get(jr, headers={"Accept":"text/markdown,text/plain,*/*", "X-Return-Format":"markdown", "User-Agent":"Mozilla/5.0"}, timeout=35)
    r.raise_for_status()
    return r.text or ""


def _parse_jina_markdown(md: str, url: str):
    lines = [x.rstrip() for x in (md or "").splitlines()]
    title = ""; image = ""; content_lines = []; in_content = False
    for ln in lines:
        if ln.startswith("Title:") and not title:
            title = _clean_text(ln.replace("Title:", "", 1)); continue
        if ln.startswith("URL Source:"):
            continue
        if ln.startswith("Markdown Content:"):
            in_content = True; continue
        mimg = re.search(r'!\[[^\]]*\]\((https?://[^)]+)\)', ln)
        if mimg and not image:
            image = mimg.group(1)
        if in_content or (title and not ln.startswith("Title:")):
            if ln.strip(): content_lines.append(ln)
    text = "\n".join(content_lines)
    text = re.sub(r'!\[[^\]]*\]\([^)]+\)', '', text)
    text = re.sub(r'\[[^\]]+\]\((https?://[^)]+)\)', lambda m: m.group(0).split('](')[0].strip('['), text)
    paras = []
    for part in re.split(r'\n{2,}|\n(?=#{1,3}\s)', text):
        t = _clean_text(re.sub(r'^#{1,6}\s*', '', part))
        if len(t) >= 40: paras.append(t)
        if len(paras) >= 35: break
    if not title and paras: title = paras[0][:90]
    return {"url": url, "title": title or url, "summary": paras[0] if paras else "", "text": "\n".join(paras), "image": image, "images": [image] if image else [], "via":"jina"}


def _best_content_block(soup):
    best, best_score = None, 0
    for el in soup.find_all(["article", "main", "section", "div"]):
        ps = el.find_all("p")
        txt = " ".join(p.get_text(" ", strip=True) for p in ps)
        score = len(ps) * 100 + len(txt)
        cls = " ".join(el.get("class", []))
        if any(k in cls.lower() for k in ["content", "article", "detail", "body", "post", "entry"]): score += 800
        if score > best_score: best, best_score = el, score
    return best


def scrape_any_url_direct(url: str):
    r = requests.get(url, headers=HEADERS, timeout=18)
    if r.status_code in {401,403,406,409,429,451,503}: raise RuntimeError(f"blocked status {r.status_code}")
    r.encoding = "utf-8"; soup = BeautifulSoup(r.text, "lxml")
    for tag in soup.find_all(["script","style","nav","footer","aside","form","noscript"]): tag.decompose()
    title = soup.find("h1").get_text(" ", strip=True) if soup.find("h1") else ""
    if not title:
        ogt = soup.find("meta", property="og:title") or soup.find("meta", attrs={"name":"title"})
        title = ogt.get("content", "") if ogt else (soup.title.get_text(strip=True) if soup.title else "")
    desc_tag = soup.find("meta", property="og:description") or soup.find("meta", attrs={"name":"description"})
    summary = desc_tag.get("content", "") if desc_tag else ""
    img_tag = soup.find("meta", property="og:image") or soup.find("meta", attrs={"name":"twitter:image"})
    image = img_tag.get("content", "") if img_tag else ""
    if image and image.startswith("//"): image = "https:" + image
    block = _best_content_block(soup) or soup
    paras, images, seen_p, seen_i = [], [], set(), set()
    for p in block.find_all("p"):
        t = _clean_text(p.get_text(" ", strip=True))
        if len(t) >= 40 and t not in seen_p:
            seen_p.add(t); paras.append(t)
        if len(paras) >= 35: break
    for im in block.find_all("img"):
        src = im.get("data-src") or im.get("data-original") or im.get("src") or ""
        if src.startswith("//"): src = "https:" + src
        if src and "base64" not in src and src not in seen_i:
            seen_i.add(src); images.append(src)
        if len(images) >= 8: break
    if not image and images: image = images[0]
    data = {"url":url,"title":_clean_text(title),"summary":_clean_text(summary),"text":"\n".join(paras),"image":image,"images":images,"via":"direct"}
    if len(data["text"]) < 160: raise RuntimeError("direct scrape too short")
    return data


def scrape_any_url(url: str):
    try:
        return scrape_any_url_direct(url)
    except Exception as direct_error:
        md = jina_reader_markdown(url)
        data = _parse_jina_markdown(md, url)
        if len(data.get("text", "")) < 120:
            raise RuntimeError(f"Jina Reader also returned too little content; direct={direct_error}")
        return data


def pollinations_image_url(topic: str, width=1024, height=576):
    prompt = f"editorial illustration, topic: {topic}, modern clean cinematic news image, high quality, no text, no watermark"
    return f"https://image.pollinations.ai/prompt/{quote_plus(prompt)}?width={width}&height={height}&seed={random.randint(1,999999)}&nologo=true&private=true"


def jina_search(query: str, limit=6):
    for accept in ("application/json", "text/plain"):
        try:
            url = "https://s.jina.ai/" + quote(query, safe="")
            r = requests.get(url, headers={"Accept":accept, "User-Agent":"Mozilla/5.0"}, timeout=30)
            if accept == "application/json" and r.status_code == 200 and r.text.strip().startswith("{"):
                payload = r.json(); data = payload.get("data", [])
                if isinstance(data, dict): data=[data]
                out=[]
                for item in data[:limit]:
                    out.append({"title":_clean_text(item.get("title","")),"url":item.get("url",""),"description":_clean_text(item.get("description","")),"content":_clean_text(item.get("content",""))[:1200]})
                if out: return out
            elif r.status_code == 200 and r.text.strip():
                chunks = re.split(r'\n(?=\[\d+\]|Title:)', r.text)
                out=[]
                for c in chunks[:limit]:
                    title = re.search(r'Title:\s*(.+)', c)
                    urlm = re.search(r'URL Source:\s*(https?://\S+)', c)
                    desc = re.search(r'Description:\s*(.+)', c)
                    out.append({"title":_clean_text(title.group(1) if title else c[:80]),"url":urlm.group(1) if urlm else "","description":_clean_text(desc.group(1) if desc else ""),"content":_clean_text(c)[:1200]})
                if out: return out
        except Exception:
            pass
    return []


def duck_context(topic: str, limit=6):
    try:
        url = "https://duckduckgo.com/html/?q=" + quote_plus(topic + " tin tức phân tích bối cảnh")
        r = requests.get(url, headers=HEADERS, timeout=12); soup = BeautifulSoup(r.text, "lxml")
        results=[]
        for res in soup.select(".result")[:limit]:
            a = res.select_one(".result__a") or res.find("a", href=True)
            href = a.get("href", "") if a else ""; title = _clean_text(a.get_text(" ", strip=True) if a else "")
            sn = res.select_one(".result__snippet"); snippet = _clean_text(sn.get_text(" ", strip=True) if sn else "")
            if title or snippet: results.append({"title":title,"url":href,"description":snippet,"content":snippet})
        return results
    except Exception: return []


def web_context(topic: str, limit=6):
    queries = [topic + " tin tức phân tích bối cảnh", topic]
    results=[]
    for q in queries:
        results = jina_search(q, limit=limit)
        if results: break
    if not results: results = duck_context(topic, limit=limit)
    enriched=[]
    for item in results[:limit]:
        content = item.get("content") or item.get("description") or ""
        if len(content) < 250 and item.get("url", "").startswith("http"):
            try:
                page = scrape_any_url(item["url"])
                content = (page.get("summary") or "") + " " + page.get("text", "")[:900]
            except Exception: pass
        enriched.append({**item, "excerpt": _clean_text(content)[:1200]})
    context = "\n".join([f"- {x.get('title') or _domain(x.get('url',''))} ({_domain(x.get('url',''))}): {x.get('excerpt') or x.get('description','')}" for x in enriched if x.get("excerpt") or x.get("title")])
    return context, enriched


async def qwen_generate(prompt: str, image_url: Optional[str] = None, max_tokens: int = 1200):
    global LAST_QWEN_ERROR, HF_TOKEN
    HF_TOKEN = _hf_token()
    if not HF_TOKEN:
        LAST_QWEN_ERROR = "Không tìm thấy token trong env: HF_TOKEN / HUGGINGFACEHUB_API_TOKEN / HUGGING_FACE_HUB_TOKEN. Hãy Restart Space sau khi thêm secret."
        return None
    if not AsyncInferenceClient:
        LAST_QWEN_ERROR = "Thiếu thư viện huggingface_hub hoặc import lỗi."
        return None
    errors=[]; models=[]
    for m in [QWEN_VL_MODEL, "Qwen/Qwen2.5-VL-7B-Instruct", "Qwen/Qwen2.5-VL-3B-Instruct"]:
        if m and m not in models: models.append(m)
    for model in models:
        try:
            client = AsyncInferenceClient(provider="auto", api_key=HF_TOKEN, timeout=90)
            content=[]
            if image_url: content.append({"type":"image_url", "image_url":{"url": image_url}})
            content.append({"type":"text", "text": prompt})
            messages=[{"role":"system","content":"Bạn là biên tập viên AI tiếng Việt. Nhiệm vụ chính là tóm tắt súc tích nội dung nguồn, không viết lại toàn bài, không lặp ý, không bịa chi tiết."},{"role":"user","content":content}]
            resp=await client.chat_completion(model=model, messages=messages, max_tokens=max_tokens, temperature=0.45, top_p=0.85)
            txt=(resp.choices[0].message.content or "").strip()
            if txt:
                LAST_QWEN_ERROR=""; return txt
        except Exception as e:
            errors.append(f"{model}: {type(e).__name__}: {str(e)[:220]}")
    LAST_QWEN_ERROR = " | ".join(errors) or "Qwen không trả nội dung."
    print("[qwen errors]", LAST_QWEN_ERROR)
    return None


def make_post(title, text, image, source_url, kind, sources=None):
    return {"id":str(int(time.time()*1000))+str(random.randint(100,999)),"title":title,"text":text,"img":image,"url":source_url,"kind":kind,"sources":sources or [],"video":"","ts":int(time.time())}


@app.get("/api/ai_wall")
def api_ai_wall(): return JSONResponse({"posts":_load_ai_wall()[:80]})


@app.get("/api/ai/status")
def api_ai_status():
    return JSONResponse({"has_token":bool(_hf_token()),"client_imported":AsyncInferenceClient is not None,"model":QWEN_VL_MODEL,"last_error":LAST_QWEN_ERROR,"tts_ready":gTTS is not None})


@app.post("/api/ai/topic")
async def api_ai_topic(request:Request):
    body=await request.json(); topic=_clean_text(body.get("topic",""))
    if not topic: return JSONResponse({"error":"missing topic"},status_code=400)
    ctx,sources=web_context(topic)
    if not ctx: return JSONResponse({"error":"Không lấy được dữ liệu internet cho chủ đề này. Hãy thử chủ đề cụ thể hơn."},status_code=422)
    image=pollinations_image_url(topic)
    prompt=f"""Tóm tắt chủ đề để đăng Tường AI.

Chủ đề: {topic}

Yêu cầu:
- Chỉ tóm tắt các ý chính dựa trên nguồn internet bên dưới.
- Không viết lại thành bài dài, không lan man, không lặp lại.
- 1 tiêu đề ngắn.
- 3-5 gạch đầu dòng, mỗi dòng tối đa 1 câu.
- 1 câu kết luận ngắn.
- Cuối cùng ghi nguồn tham khảo bằng tên website.

Nguồn/bối cảnh internet:
{ctx}"""
    text=await qwen_generate(prompt,image_url=image,max_tokens=900)
    if not text: return JSONResponse({"error":"Qwen2.5-VL chưa sẵn sàng: "+LAST_QWEN_ERROR},status_code=503)
    post=make_post(topic,text,image,"","topic",sources=sources[:5]); posts=_load_ai_wall(); posts.insert(0,post); _save_ai_wall(posts)
    return JSONResponse({"post":post})


@app.post("/api/ai/url")
async def api_ai_url(request:Request):
    body=await request.json(); url=_clean_text(body.get("url",""))
    if not url.startswith("http"): return JSONResponse({"error":"missing url"},status_code=400)
    try: data=scrape_any_url(url)
    except Exception as e: return JSONResponse({"error":"Không scrape được URL: "+str(e)[:180]},status_code=422)
    raw=(data.get("summary","")+"\n"+data.get("text","")).strip()
    if len(raw)<120: return JSONResponse({"error":"URL không có đủ nội dung để Qwen tóm tắt"},status_code=422)
    prompt=f"""Tóm tắt bài viết nguồn dưới đây để đăng lên Tường AI VNEWS.

Yêu cầu bắt buộc:
- Chỉ viết TÓM TẮT theo nội dung chính, không viết lại toàn bộ bài.
- Ngắn gọn, xúc tích, cụ thể.
- Tránh lặp lại ý và câu chữ trong bài gốc.
- Không thêm chi tiết ngoài nguồn.
- Độ dài tối đa 6 gạch đầu dòng hoặc 2 đoạn ngắn.
- Nếu có nhân vật/sự kiện/thời điểm quan trọng, giữ lại.

Tiêu đề gốc: {data.get('title','')}
Nguồn scrape: {data.get('via','')}
Nội dung gốc:
{raw[:16000]}"""
    text=await qwen_generate(prompt,image_url=data.get("image") or None,max_tokens=900)
    if not text: return JSONResponse({"error":"Qwen2.5-VL chưa sẵn sàng: "+LAST_QWEN_ERROR},status_code=503)
    post=make_post(data.get("title") or "Bài viết",text,data.get("image") or "",url,"url",sources=[{"title":data.get("title"),"url":url,"excerpt":raw[:500],"via":data.get("via")}])
    posts=_load_ai_wall(); posts.insert(0,post); _save_ai_wall(posts)
    return JSONResponse({"post":post})


@app.post("/api/rewrite_share")
async def api_rewrite_share(request:Request):
    body=await request.json(); url=_clean_text(body.get("url",""))
    if not url.startswith("http"): return JSONResponse({"error":"missing url"},status_code=400)
    try: data=scrape_any_url(url)
    except Exception as e: return JSONResponse({"error":"Không đọc được bài viết: "+str(e)[:180]},status_code=422)
    raw=(data.get("summary","")+"\n"+data.get("text","")).strip()
    prompt=f"""Tóm tắt bài viết sau bằng tiếng Việt.

Yêu cầu:
- Chỉ nêu nội dung chính, không viết lại toàn bài.
- Ngắn gọn, cụ thể, dễ hiểu.
- Tối đa 5 gạch đầu dòng hoặc 2 đoạn ngắn.
- Không lặp ý, không thêm chi tiết ngoài nguồn.

Tiêu đề: {data.get('title','')}
Nội dung:
{raw[:16000]}"""
    text=await qwen_generate(prompt,image_url=data.get("image") or None,max_tokens=900)
    if not text: return JSONResponse({"error":"Qwen2.5-VL chưa sẵn sàng: "+LAST_QWEN_ERROR},status_code=503)
    post=make_post(data.get("title") or "Bài viết",text,data.get("image") or "",url,"rewrite")
    posts=_load_ai_wall(); posts.insert(0,post); _save_ai_wall(posts)
    return JSONResponse({"post":post})


def _safe_name(s): return re.sub(r"[^a-zA-Z0-9_-]+", "_", s)[:80]


def _wrap_text(text, width=32, max_lines=10):
    words=_clean_text(text).split(); lines=[]; cur=""
    for w in words:
        if len(cur)+len(w)+1<=width: cur=(cur+" "+w).strip()
        else:
            if cur: lines.append(cur)
            cur=w
        if len(lines)>=max_lines: break
    if cur and len(lines)<max_lines: lines.append(cur)
    return "\n".join(lines)


def _make_short_frame(post, img_path, out_path):
    if Image is None: raise RuntimeError("Pillow chưa sẵn sàng")
    W,H=1080,1920
    bg=Image.new("RGB",(W,H),(14,14,14))
    try:
        im=Image.open(img_path).convert("RGB")
        # cover top area 1080x860
        target=(1080,860)
        im_ratio=im.width/im.height; target_ratio=target[0]/target[1]
        if im_ratio>target_ratio:
            new_h=target[1]; new_w=int(new_h*im_ratio)
        else:
            new_w=target[0]; new_h=int(new_w/im_ratio)
        im=im.resize((new_w,new_h))
        left=(new_w-target[0])//2; top=(new_h-target[1])//2
        im=im.crop((left,top,left+target[0],top+target[1]))
        bg.paste(im,(0,0))
    except Exception:
        pass
    draw=ImageDraw.Draw(bg)
    try:
        font_title=ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",52)
        font_body=ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",40)
        font_label=ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",32)
    except Exception:
        font_title=font_body=font_label=None
    draw.rectangle((0,780,W,H),fill=(14,14,14))
    draw.text((54,830),"VNEWS · Tường AI",fill=(92,184,122),font=font_label)
    title=_wrap_text(post.get("title",""),24,3)
    draw.multiline_text((54,900),title,fill=(255,255,255),font=font_title,spacing=10)
    body=_wrap_text(post.get("text",""),34,10)
    draw.multiline_text((54,1120),body,fill=(220,220,220),font=font_body,spacing=12)
    bg.save(out_path,quality=92)


def _download_image(url, fallback_topic, out_path):
    if url:
        try:
            r=requests.get(url,headers=HEADERS,timeout=15)
            if r.status_code==200 and len(r.content)>1000:
                with open(out_path,"wb") as f:f.write(r.content)
                return out_path
        except Exception: pass
    # fallback generated image
    gen=pollinations_image_url(fallback_topic)
    try:
        r=requests.get(gen,headers=HEADERS,timeout=25)
        if r.status_code==200 and len(r.content)>1000:
            with open(out_path,"wb") as f:f.write(r.content)
            return out_path
    except Exception: pass
    if Image:
        Image.new("RGB",(1080,860),(30,55,42)).save(out_path)
        return out_path
    raise RuntimeError("Không tạo được ảnh")


def _short_script(post):
    txt=_clean_text(post.get("text",""))
    # TTS should read concise summary, not entire huge post.
    if len(txt)>900: txt=txt[:900].rsplit(" ",1)[0]+"."
    return f"{post.get('title','')}. {txt}"


@app.post("/api/ai/short/{post_id}")
def api_ai_short(post_id:str):
    posts=_load_ai_wall(); post=next((p for p in posts if str(p.get("id"))==str(post_id)),None)
    if not post: return JSONResponse({"error":"post not found"},status_code=404)
    os.makedirs(SHORTS_DIR,exist_ok=True)
    out_mp4=os.path.join(SHORTS_DIR,_safe_name(post_id)+".mp4")
    if os.path.exists(out_mp4):
        post["video"]="/api/ai/short-file/"+post_id
        _save_ai_wall(posts)
        return JSONResponse({"video":post["video"]})
    if gTTS is None: return JSONResponse({"error":"gTTS chưa sẵn sàng"},status_code=503)
    work=os.path.join(SHORTS_DIR,_safe_name(post_id))
    os.makedirs(work,exist_ok=True)
    img=os.path.join(work,"image.jpg"); frame=os.path.join(work,"frame.jpg"); audio=os.path.join(work,"voice.mp3")
    try:
        _download_image(post.get("img"), post.get("title","AI news"), img)
        _make_short_frame(post,img,frame)
        script=_short_script(post)
        gTTS(script,lang="vi").save(audio)
        cmd=["ffmpeg","-y","-loop","1","-i",frame,"-i",audio,"-shortest","-c:v","libx264","-tune","stillimage","-pix_fmt","yuv420p","-c:a","aac","-b:a","128k","-vf","scale=1080:1920",out_mp4]
        subprocess.run(cmd,check=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE,timeout=180)
        post["video"]="/api/ai/short-file/"+post_id
        _save_ai_wall(posts)
        return JSONResponse({"video":post["video"]})
    except Exception as e:
        return JSONResponse({"error":"Không tạo được shorts: "+str(e)[:180]},status_code=500)


@app.get("/api/ai/short-file/{post_id}")
def api_ai_short_file(post_id:str):
    path=os.path.join(SHORTS_DIR,_safe_name(post_id)+".mp4")
    if not os.path.exists(path): return JSONResponse({"error":"not found"},status_code=404)
    return FileResponse(path,media_type="video/mp4",filename=f"vnews-ai-{post_id}.mp4")


# Override index route to show Tường AI slide + shorts generation.
app.router.routes=[r for r in app.router.routes if not (getattr(r,'path',None)=='/' and 'GET' in getattr(r,'methods',set()))]
AI_INJECT=r'''
<style>.ai-wall-extra{margin:6px 4px;background:#1a1a1a;border:1px solid #2a2a2a;border-radius:8px;overflow:hidden}.ai-wall-card{flex:0 0 250px;background:#141414;border:1px solid #2b2b2b;border-radius:10px;padding:8px}.ai-wall-img{width:100%;aspect-ratio:16/9;background:#222;border-radius:8px;overflow:hidden;margin-bottom:6px}.ai-wall-img img{width:100%;height:100%;object-fit:cover}.ai-wall-title{font-size:12px;color:#5cb87a;font-weight:800;line-height:1.3;margin-bottom:4px}.ai-wall-text{font-size:11px;color:#bbb;line-height:1.45;white-space:pre-wrap;display:-webkit-box;-webkit-line-clamp:5;-webkit-box-orient:vertical;overflow:hidden}.ai-wall-actions{display:flex;gap:6px;margin-top:8px}.ai-wall-actions button{flex:1;border:1px solid #333;background:#222;color:#ddd;border-radius:14px;padding:6px 8px;font-size:10px}.ai-wall-actions button.primary{background:#2d8659;border-color:#2d8659;color:#fff}</style><script>(function(){function esc(s){return String(s||'').replace(/[&<>"']/g,m=>({'&':'&amp;','<':'&lt;','>':'&gt;','"':'&quot;',"'":'&#39;'}[m]));}let aiWall=[];async function refreshAiWall(){try{const r=await fetch('/api/ai_wall');const j=await r.json();aiWall=j.posts||[];renderAiWall();}catch(e){}}function renderAiWall(){const home=document.getElementById('view-home');if(!home)return;let old=document.getElementById('ai-wall-block');if(old)old.remove();if(!aiWall.length)return;let wrap=document.createElement('div');wrap.id='ai-wall-block';wrap.className='ai-wall-extra';let h='<div class="slider-header"><span class="slider-label">🧱 Tường AI</span></div><div class="slider-track">';aiWall.slice(0,30).forEach((p,i)=>{h+=`<div class="ai-wall-card"><div class="ai-wall-img">${p.img?`<img src="${p.img}">`:''}</div><div class="ai-wall-title">${esc(p.title)}</div><div class="ai-wall-text">${esc(p.text)}</div><div class="ai-wall-actions"><button onclick="aiReadWall(${i})">Xem</button><button class="primary" onclick="aiMakeShort(${i})">Shorts</button></div></div>`});h+='</div>';wrap.innerHTML=h;home.prepend(wrap)}window.aiReadWall=function(i){const p=aiWall[i];if(!p)return;showView('view-article');let sources='';if(p.sources&&p.sources.length){sources='<div class="article-summary"><b>Nguồn tham khảo:</b><br>'+p.sources.slice(0,5).map(s=>`• ${esc(s.title||s.url||'Nguồn')} ${s.url?`(${esc(new URL(s.url).hostname.replace('www.',''))})`:''}`).join('<br>')+'</div>'}let h=`<button class="back-btn" onclick="switchCat('home')">← Quay lại</button><div class="article-view"><span class="badge badge-ai">AI</span><h1 class="article-title">${esc(p.title)}</h1>${p.img?`<img class="article-img" src="${p.img}">`:''}${sources}<p class="article-p" style="white-space:pre-wrap">${esc(p.text)}</p>${p.video?`<video class="article-img" src="${p.video}" controls playsinline></video>`:''}<div class="article-actions">${p.url?`<button onclick="window.open('${p.url}','_blank')">🔗 Nguồn</button>`:''}<button onclick="aiMakeShort(${i})">🎬 Tạo video shorts</button></div></div>`;document.getElementById('view-article').innerHTML=h;window.scrollTo(0,0)};window.aiMakeShort=async function(i){const p=aiWall[i];if(!p)return;try{alert('Đang tạo shorts AI, vui lòng chờ...');const r=await fetch('/api/ai/short/'+p.id,{method:'POST'});const j=await r.json();if(!r.ok||j.error)throw new Error(j.error||'Lỗi');p.video=j.video;aiReadWall(i);refreshAiWall();}catch(e){alert(e.message)}};const oldLoad=window.loadHome;if(typeof oldLoad==='function'){window.loadHome=async function(){await oldLoad.apply(this,arguments);setTimeout(refreshAiWall,50);};}setTimeout(refreshAiWall,1200);})();</script>'''
@app.get('/')
async def index_ai():
    with open('/app/static/index.html','r',encoding='utf-8') as f: html=f.read()
    return HTMLResponse(html.replace('</body>',AI_INJECT+'\n</body>'))