app.py

import os, tempfile, io, math, time, threading
import numpy as np
import cv2
import gradio as gr
from PIL import Image, ImageDraw, ImageFont, ImageFilter, ImageEnhance

# ── TOKENS ────────────────────────────────────────────────────────
hf_token = (os.environ.get("HF_TOKEN","") or os.environ.get("HF_KEY","")).strip()
hf_client = None
if hf_token:
    try:
        from huggingface_hub import login, InferenceClient
        login(token=hf_token); hf_client = InferenceClient(token=hf_token)
        print("✅ HF ready")
    except Exception as e: print(f"⚠️ HF: {e}")

# ── HF MODELS ─────────────────────────────────────────────────────
HF_MODELS = [
    {"id": "Lightricks/LTX-2",                                 "name": "LTX-2 ⚡"},
    {"id": "Wan-AI/Wan2.2-I2V-A14B",                           "name": "Wan 2.2"},
    {"id": "stabilityai/stable-video-diffusion-img2vid-xt",    "name": "SVD-XT"},
    {"id": "KlingTeam/LivePortrait",                           "name": "Kling LivePortrait"},
    {"id": "Lightricks/LTX-Video",                             "name": "LTX-Video"},
    {"id": "__local__",                                        "name": "Ken Burns ✅"},
]

def pil_to_bytes(img):
    b=io.BytesIO(); img.save(b,format="JPEG",quality=92); return b.getvalue()

def run_timeout(fn, sec, *a, **kw):
    box=[None]; err=[None]
    def r():
        try: box[0]=fn(*a,**kw)
        except Exception as e: err[0]=str(e)
    t=threading.Thread(target=r,daemon=True); t.start(); t.join(timeout=sec)
    if t.is_alive(): print(f"  ⏱ timeout"); return None
    if err[0]: print(f"  ❌ {err[0][:80]}")
    return box[0]

def try_hf(model_id, pil, prompt):
    if not hf_client: return None
    try:
        r=hf_client.image_to_video(image=pil_to_bytes(pil),model=model_id,prompt=prompt)
        return r.read() if hasattr(r,"read") else r
    except Exception as e: print(f"  ❌ {model_id}: {e}"); return None

def get_video(pil, prompt, cb=None):
    for m in HF_MODELS:
        mid,mname=m["id"],m["name"]
        if cb: cb(f"⏳ Trying: {mname}")
        if mid=="__local__":
            return ken_burns(pil), mname
        data=run_timeout(try_hf,50,mid,pil,prompt)
        if data:
            t=tempfile.NamedTemporaryFile(suffix=".mp4",delete=False)
            t.write(data); t.flush()
            return t.name, mname
        time.sleep(1)
    return ken_burns(pil), "Ken Burns"


# ══════════════════════════════════════════════════════════════════
#  KEN BURNS  (working, image always shows)
# ══════════════════════════════════════════════════════════════════
def ease(t): t=max(0.,min(1.,t)); return t*t*(3-2*t)
def ease_cubic(t): t=max(0.,min(1.,t)); return 4*t*t*t if t<.5 else 1-math.pow(-2*t+2,3)/2
def ease_expo(t): return 1-math.pow(2,-10*t) if t<1 else 1.
def ease_bounce(t):
    if t<1/2.75: return 7.5625*t*t
    elif t<2/2.75: t-=1.5/2.75; return 7.5625*t*t+.75
    elif t<2.5/2.75: t-=2.25/2.75; return 7.5625*t*t+.9375
    else: t-=2.625/2.75; return 7.5625*t*t+.984375

def ken_burns(pil, duration_sec=6, fps=30, style="premium"):
    TW,TH=720,1280
    # Small pad — just enough for gentle movement, no aggressive zoom
    pad=60; BW,BH=TW+pad*2,TH+pad*2
    total=duration_sec*fps

    # Prepare image — fit full image, letterbox if needed
    img=pil.convert("RGB"); sw,sh=img.size
    # Fit entire image inside TH height, pad sides with blurred bg
    scale=TH/sh; nw=int(sw*scale); nh=TH
    if nw>TW: scale=TW/sw; nw=TW; nh=int(sh*scale)
    img_resized=img.resize((nw,nh),Image.LANCZOS)
    # Blurred background fill
    bg=img.resize((TW,TH),Image.LANCZOS)
    bg=bg.filter(ImageFilter.GaussianBlur(radius=20))
    bg_arr=np.array(ImageEnhance.Brightness(bg).enhance(0.5))
    canvas=Image.fromarray(bg_arr)
    # Paste sharp image centered
    px=(TW-nw)//2; py=(TH-nh)//2
    canvas.paste(img_resized,(px,py))
    canvas=canvas.filter(ImageFilter.UnsharpMask(radius=0.8,percent=110,threshold=2))
    canvas=ImageEnhance.Contrast(canvas).enhance(1.05)
    canvas=ImageEnhance.Color(canvas).enhance(1.08)
    base=np.array(canvas.resize((BW,BH),Image.LANCZOS))

    # Pre-baked vignette mask (very subtle)
    Y,X=np.ogrid[:TH,:TW]
    dist=np.sqrt(((X-TW/2)/(TW/2))**2+((Y-TH/2)/(TH/2))**2)
    vmask=np.clip(1.-0.22*np.maximum(dist-0.85,0)**2,0,1).astype(np.float32)

    # GENTLE zoom: 1.00→1.06 max — full image always visible
    SEG=[
        (0.00,0.30, 1.00,1.04,  0,          -int(pad*.40),  0,          -int(pad*.40)),
        (0.30,0.60, 1.04,1.06, -int(pad*.30), int(pad*.30), -int(pad*.40),-int(pad*.70)),
        (0.60,0.80, 1.06,1.04,  int(pad*.30), int(pad*.50), -int(pad*.70),-int(pad*.40)),
        (0.80,1.00, 1.04,1.00,  int(pad*.50), 0,            -int(pad*.40), 0),
    ]

    tmp=tempfile.NamedTemporaryFile(suffix=".mp4",delete=False)
    writer=cv2.VideoWriter(tmp.name,cv2.VideoWriter_fourcc(*"mp4v"),fps,(TW,TH))

    for i in range(total):
        tg=i/max(total-1,1)
        zoom=pan_x=pan_y=None
        for t0,t1,z0,z1,px0,px1,py0,py1 in SEG:
            if t0<=tg<=t1:
                te=ease_cubic((tg-t0)/(t1-t0))
                zoom=z0+(z1-z0)*te; pan_x=int(px0+(px1-px0)*te); pan_y=int(py0+(py1-py0)*te); break
        if zoom is None: zoom,pan_x,pan_y=1.,0,0
        # No shake — keeps image stable and well-framed

        cw,ch=int(TW/zoom),int(TH/zoom)
        ox,oy=BW//2+pan_x,BH//2+pan_y
        x1,y1=max(0,ox-cw//2),max(0,oy-ch//2)
        x2,y2=min(BW,x1+cw),min(BH,y1+ch)
        if (x2-x1)<10 or (y2-y1)<10: x1,y1,x2,y2=0,0,TW,TH

        frame=cv2.resize(base[y1:y2,x1:x2],(TW,TH),interpolation=cv2.INTER_LINEAR)

        # Very subtle color grade
        f=frame.astype(np.float32)/255.
        if style=="premium":
            f[:,:,0]=np.clip(f[:,:,0]*1.03+.01,0,1)
            f[:,:,2]=np.clip(f[:,:,2]*1.02,0,1)
        elif style=="energetic":
            gray=0.299*f[:,:,0:1]+0.587*f[:,:,1:2]+0.114*f[:,:,2:3]
            f=np.clip(gray+1.2*(f-gray),0,1); f=np.clip(f*1.04,0,1)
        elif style=="fun":
            f[:,:,0]=np.clip(f[:,:,0]*1.05,0,1)
            f[:,:,1]=np.clip(f[:,:,1]*1.03,0,1)
        frame=np.clip(f*255,0,255).astype(np.uint8)

        # Vignette
        frame=np.clip(frame.astype(np.float32)*vmask[:,:,None],0,255).astype(np.uint8)

        # Grain
        frame=np.clip(frame.astype(np.float32)+np.random.normal(0,3,frame.shape),0,255).astype(np.uint8)

        # Bars
        frame[:36,:]=0; frame[-36:,:]=0

        # Fade in (2%) / out (5%)
        if tg<0.02: alpha=ease_expo(tg/0.02)
        elif tg>0.95: alpha=ease(1-(tg-0.95)/0.05)
        else: alpha=1.
        if alpha<1.: frame=np.clip(frame.astype(np.float32)*alpha,0,255).astype(np.uint8)

        writer.write(cv2.cvtColor(frame,cv2.COLOR_RGB2BGR))
    writer.release()
    return tmp.name


# ══════════════════════════════════════════════════════════════════
#  CAPTIONS — burn into existing video via ffmpeg
# ══════════════════════════════════════════════════════════════════
def add_captions_ffmpeg(video_path, caption, duration_sec, style):
    """Burn animated captions + hashtag tag + shop-now CTA using ffmpeg drawtext."""
    import re
    def clean(t): return re.sub(r"[^A-Za-z0-9 !.,-]","",t).strip()

    words=caption.strip().split()
    mid=max(1,len(words)//2)
    line1=clean(" ".join(words[:mid]))
    line2=clean(" ".join(words[mid:])) if len(words)>1 else line1

    colors={"premium":"FFD232","energetic":"3CC8FF","fun":"FF78C8"}
    col=colors.get(style,"FFFFFF")
    out=video_path.replace(".mp4","_cap.mp4")

    font_paths=[
        "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
        "/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf",
        "/usr/share/fonts/truetype/freefont/FreeSansBold.ttf",
    ]
    font=""; font_reg=""
    for p in font_paths:
        if os.path.exists(p): font=f":fontfile='{p}'"; font_reg=font; break

    def dt(text, start, end, y, size=42, color=None, box_alpha="0.60"):
        c = color or col
        fd=0.4
        return (
            f"drawtext=text='{text}'{font}"
            f":fontsize={size}:fontcolor=#{c}"
            f":x=(w-text_w)/2:y={y}"
            f":box=1:boxcolor=black@{box_alpha}:boxborderw=14"
            f":enable='between(t,{start},{end})'"
            f":alpha='if(lt(t,{start+fd}),(t-{start})/{fd},if(gt(t,{end-fd}),({end}-t)/{fd},1))'"
        )

    end2 = min(duration_sec-0.2, 6.5)

    # 1. Main captions — inside frame, above bars
    cap1 = dt(line1,  1.0, 3.5,  "h-190")
    cap2 = dt(line2,  3.8, end2, "h-190")

    # 2. "Shop Now" CTA — appears at 4.5s, small, bottom center
    cta_colors={"premium":"FF9900","energetic":"FF4444","fun":"AA44FF"}
    cta  = dt("Shop Now >", 4.5, end2, "h-130", size=32, color=cta_colors.get(style,"FF9900"), box_alpha="0.70")

    # 3. Hashtag top-left — appears early
    tag  = dt("#NewCollection", 0.5, 3.0, "60", size=28, color="FFFFFF", box_alpha="0.40")

    vf = ",".join([cap1, cap2, cta, tag])

    ret=os.system(f'ffmpeg -y -i "{video_path}" -vf "{vf}" -c:a copy "{out}" -loglevel error')
    return out if (ret==0 and os.path.exists(out)) else video_path


# ══════════════════════════════════════════════════════════════════
#  AUDIO — BGM + optional TTS
# ══════════════════════════════════════════════════════════════════
def make_bgm(duration_sec, out_path, style="premium"):
    import wave
    sr=44100; n=int(sr*duration_sec)
    t=np.linspace(0,duration_sec,n,endpoint=False)
    bpm={"premium":88,"energetic":126,"fun":104}.get(style,88)
    beat=60./bpm

    kick=np.zeros(n,np.float32)
    for i in range(int(duration_sec/beat)+2):
        s=int(i*beat*sr)
        if s>=n: break
        l=min(int(sr*.10),n-s)
        env=np.exp(-20*np.arange(l)/sr)
        kick[s:s+l]+=env*np.sin(2*math.pi*55*np.exp(-25*np.arange(l)/sr)*np.arange(l)/sr)*0.55

    bass_f={"premium":55,"energetic":80,"fun":65}.get(style,55)
    bass=np.sin(2*math.pi*bass_f*t)*0.10*(0.5+0.5*np.sin(2*math.pi*(bpm/60/4)*t))

    mf={"premium":[261,329,392],"energetic":[330,415,494],"fun":[392,494,587]}.get(style,[261,329,392])
    mel=np.zeros(n,np.float32)
    for j,f in enumerate(mf):
        env=np.clip(0.5+0.5*np.sin(2*math.pi*1.5*t-j*2.1),0,1)
        mel+=np.sin(2*math.pi*f*t)*env*0.045

    hat=np.zeros(n,np.float32)
    hs=beat/2
    for i in range(int(duration_sec/hs)+2):
        s=int(i*hs*sr)
        if s>=n: break
        l=min(int(sr*.03),n-s)
        hat[s:s+l]+=np.random.randn(l)*np.exp(-80*np.arange(l)/sr)*0.06

    mix=np.clip((kick+bass+mel+hat)*0.18,-1,1)
    fade=int(sr*.5); mix[:fade]*=np.linspace(0,1,fade); mix[-fade:]*=np.linspace(1,0,fade)

    with wave.open(out_path,"w") as wf:
        wf.setnchannels(1); wf.setsampwidth(2); wf.setframerate(sr)
        wf.writeframes((mix*32767).astype(np.int16).tobytes())

def add_audio(video_path, caption, duration_sec, style):
    bgm=video_path.replace(".mp4","_bgm.wav")
    final=video_path.replace(".mp4","_final.mp4")
    make_bgm(duration_sec, bgm, style)

    # Try TTS voiceover
    audio=bgm
    try:
        from gtts import gTTS
        tts_mp3=video_path.replace(".mp4","_tts.mp3")
        tts_wav=video_path.replace(".mp4","_tts.wav")
        gTTS(text=caption[:200],lang="en",slow=False).save(tts_mp3)
        mixed=video_path.replace(".mp4","_mix.wav")
        os.system(f'ffmpeg -y -i "{bgm}" -i "{tts_mp3}" '
                  f'-filter_complex "[0]volume=0.20[a];[1]volume=0.95[b];[a][b]amix=inputs=2:duration=first" '
                  f'-t {duration_sec} "{mixed}" -loglevel error')
        if os.path.exists(mixed): audio=mixed
    except Exception as e: print(f"  TTS skip: {e}")

    os.system(f'ffmpeg -y -i "{video_path}" -i "{audio}" '
              f'-c:v copy -c:a aac -b:a 128k -shortest "{final}" -loglevel error')
    return final if os.path.exists(final) else video_path


# ══════════════════════════════════════════════════════════════════
#  AI BRAIN — Captions, Posting Time, Target Audience
# ══════════════════════════════════════════════════════════════════

POSTING_TIMES = {
    "Fashion":     {"slots":["7:00 AM","12:00 PM","6:00 PM","9:00 PM"],"best":"9:00 PM","days":"Tue, Thu, Fri"},
    "Food":        {"slots":["11:00 AM","1:00 PM","7:00 PM"],"best":"12:00 PM","days":"Mon, Wed, Sat"},
    "Tech":        {"slots":["8:00 AM","12:00 PM","5:00 PM"],"best":"8:00 AM","days":"Mon, Tue, Wed"},
    "Beauty":      {"slots":["8:00 AM","1:00 PM","8:00 PM"],"best":"8:00 PM","days":"Wed, Fri, Sun"},
    "Fitness":     {"slots":["6:00 AM","12:00 PM","7:00 PM"],"best":"6:00 AM","days":"Mon, Wed, Fri"},
    "Lifestyle":   {"slots":["9:00 AM","2:00 PM","7:00 PM"],"best":"7:00 PM","days":"Thu, Fri, Sat"},
    "Product/Other":{"slots":["10:00 AM","3:00 PM","8:00 PM"],"best":"8:00 PM","days":"Tue, Thu, Sat"},
}

AUDIENCES = {
    "Fashion":    "👗 18-35 yo females, fashion lovers, Instagram scrollers, trend followers",
    "Food":       "🍕 18-45 yo foodies, home cooks, restaurant goers, food bloggers",
    "Tech":       "💻 20-40 yo tech enthusiasts, early adopters, gadget buyers, professionals",
    "Beauty":     "💄 16-35 yo beauty lovers, skincare fans, makeup artists, self-care community",
    "Fitness":    "💪 18-40 yo gym goers, health-conscious buyers, athletes, wellness seekers",
    "Lifestyle":  "🌿 22-40 yo aspirational buyers, aesthetic lovers, home decor fans",
    "Product/Other":"🛍️ 18-45 yo online shoppers, deal hunters, value-conscious buyers",
}

CAPTION_TEMPLATES = {
    "English": {
        "Premium":   ["{cap} ✨ Quality that speaks for itself. 🛒 Shop Now → Link in bio",
                      "Elevate your style. {cap} 💫 DM us to order!"],
        "Energetic": ["🔥 {cap} Hit different. Grab yours NOW 👆 Limited stock!",
                      "⚡ Game changer alert! {cap} Don't sleep on this 🚀"],
        "Fun":       ["Obsessed with this!! 😍 {cap} Tag someone who needs it 👇",
                      "POV: You just found your new fav 🎉 {cap} Link in bio!"],
    },
    "Hindi": {
        "Premium":   ["{cap} ✨ क्वालिटी जो बोलती है। 🛒 अभी खरीदें → Bio में link",
                      "अपना स्टाइल बढ़ाएं। {cap} 💫 Order के लिए DM करें!"],
        "Energetic": ["🔥 {cap} एकदम अलग है! अभी grab करो 👆 Limited stock!",
                      "⚡ Game changer! {cap} मत सोचो, order करो 🚀"],
        "Fun":       ["इसके साथ तो दीवाने हो जाओगे!! 😍 {cap} किसी को tag करो 👇",
                      "POV: नया favourite मिल गया 🎉 {cap} Bio में link है!"],
    },
    "Hinglish": {
        "Premium":   ["{cap} ✨ Quality toh dekho yaar! 🛒 Shop karo → Bio mein link",
                      "Style upgrade time! {cap} 💫 DM karo order ke liye!"],
        "Energetic": ["🔥 {cap} Bilkul alag hai bhai! Abhi lo 👆 Limited stock!",
                      "⚡ Ek dum fire hai! {cap} Mat ruko, order karo 🚀"],
        "Fun":       ["Yaar yeh toh kamaal hai!! 😍 {cap} Kisi ko tag karo 👇",
                      "POV: Naya fav mil gaya 🎉 {cap} Bio mein link hai!"],
    },
}

def detect_category(caption):
    cap_low = caption.lower()
    if any(w in cap_low for w in ["shoe","sneaker","dress","outfit","wear","fashion","style","cloth","jeans","kurta"]):
        return "Fashion"
    if any(w in cap_low for w in ["food","eat","recipe","cook","restaurant","cafe","pizza","biryani"]):
        return "Food"
    if any(w in cap_low for w in ["phone","laptop","tech","gadget","device","app","software","camera"]):
        return "Tech"
    if any(w in cap_low for w in ["skin","beauty","makeup","lipstick","cream","hair","glow","face"]):
        return "Beauty"
    if any(w in cap_low for w in ["gym","fit","workout","protein","yoga","health","run","sport"]):
        return "Fitness"
    if any(w in cap_low for w in ["home","decor","interior","lifestyle","aesthetic","plant","candle"]):
        return "Lifestyle"
    return "Product/Other"

def get_smart_insights(caption, style, language):
    import random, re
    category = detect_category(caption)
    pt = POSTING_TIMES[category]
    audience = AUDIENCES[category]

    # Generate caption in selected language
    templates = CAPTION_TEMPLATES.get(language, CAPTION_TEMPLATES["English"])
    style_templates = templates.get(style, templates["Premium"])
    clean_cap = re.sub(r"[^A-Za-z0-9 !.,'-ऀ-ॿ]","",caption).strip()
    generated_cap = random.choice(style_templates).replace("{cap}", clean_cap)

    # Build insight card
    insight = f"""📊 SMART INSIGHTS
━━━━━━━━━━━━━━━━━━━━━━
🎯 Category Detected: {category}

👥 Target Audience:
{audience}

⏰ Best Time to Post:
🏆 Prime Slot: {pt['best']}
📅 Best Days: {pt['days']}
🕐 All Good Times: {', '.join(pt['slots'])}

💬 AI Caption ({language}):
{generated_cap}

#️⃣ Suggested Hashtags:
#{category.replace('/','').replace(' ','')} #Trending #NewCollection #MustHave #ShopNow #Viral #Reels #ForYou
━━━━━━━━━━━━━━━━━━━━━━"""
    return insight, generated_cap


# ══════════════════════════════════════════════════════════════════
#  MAIN
# ══════════════════════════════════════════════════════════════════
def generate(image, caption, style, language, add_aud, add_cap, progress=gr.Progress()):
    if image is None: return None,"⚠️ Upload an image!","Upload image first!"
    pil=image if isinstance(image,Image.Image) else Image.fromarray(image)
    cap=caption.strip() or "Premium Quality. Shop Now."
    prompt=f"cinematic product ad, {cap}, smooth motion, dramatic lighting"
    lines=[]
    def log(msg): lines.append(msg); progress(min(.1+len(lines)*.10,.80),desc=msg)

    # Get smart insights first (instant)
    insight, ai_caption = get_smart_insights(cap, style, language)

    progress(.05,desc="🚀 Generating video...")
    video_path, model_used = get_video(pil, prompt, cb=log)
    dur=6

    # Use AI caption for video if captions enabled
    video_caption = ai_caption if language != "English" else cap

    if add_cap:
        log("💬 Adding captions...")
        video_path=add_captions_ffmpeg(video_path, video_caption, dur, style.lower())

    if add_aud:
        log("🎵 Adding music + voice...")
        video_path=add_audio(video_path, cap, dur, style.lower())

    progress(1.0,desc="✅ Done!")
    return video_path, "\n".join(lines)+f"\n\n✅ Used: {model_used}", insight


# ── UI ────────────────────────────────────────────────────────────
css="""
#title{text-align:center;font-size:2.3rem;font-weight:900}
#sub{text-align:center;color:#888;margin-bottom:1.5rem}
.insight{font-family:monospace;font-size:.88rem;line-height:1.7}
"""
with gr.Blocks(css=css,theme=gr.themes.Soft(primary_hue="violet")) as demo:
    gr.Markdown("# 🎬 AI Reel Generator",elem_id="title")
    gr.Markdown("Image → AI video + smart captions + posting strategy",elem_id="sub")

    with gr.Row():
        # ── LEFT ──────────────────────────────────────────────────
        with gr.Column(scale=1):
            img_in  = gr.Image(label="📸 Upload Image",type="pil",height=280)
            cap_in  = gr.Textbox(label="✏️ Your Caption / Product Description",
                                  value="Step into style. Own the moment.",lines=2)
            with gr.Row():
                sty_dd  = gr.Dropdown(["Premium","Energetic","Fun"],value="Premium",label="🎨 Style")
                lang_dd = gr.Dropdown(["English","Hindi","Hinglish"],value="English",label="🌐 Language")
            with gr.Row():
                aud_cb = gr.Checkbox(label="🎵 Music + Voice",value=True)
                cap_cb = gr.Checkbox(label="💬 Captions",     value=True)
            gen_btn = gr.Button("🚀 Generate Reel + Insights",variant="primary",size="lg")
            gr.Markdown("**🔗 Chain:** LTX-2 ⚡ → Wan 2.2 → SVD-XT → Kling → LTX-Video → Ken Burns ✅")

        # ── RIGHT ─────────────────────────────────────────────────
        with gr.Column(scale=1):
            vid_out     = gr.Video(label="🎥 Reel",height=420)
            insight_out = gr.Textbox(label="📊 Smart Insights — Audience + Posting Time + AI Caption",
                                      lines=18, interactive=False, elem_classes="insight")
            log_out     = gr.Textbox(label="🔧 Log",lines=3,interactive=False)

    gen_btn.click(
        fn=generate,
        inputs=[img_in,cap_in,sty_dd,lang_dd,aud_cb,cap_cb],
        outputs=[vid_out,log_out,insight_out],
    )

if __name__=="__main__":
    demo.launch()