Update app.py

app.py

@@ -1,354 +1,201 @@
-# app.py
+import modal
 import os
-import oss2
-import sys
-import uuid
-import shutil
 import time
-import gradio as gr
-import requests
-
-from pathlib import Path
-from datetime import datetime, timedelta
-
-import dashscope
-# from dashscope.utils.oss_utils import check_and_upload_local
-
-DASHSCOPE_API_KEY = os.getenv("DASHSCOPE_API_KEY")
-dashscope.api_key = DASHSCOPE_API_KEY
-
-
-
-def get_upload_policy(api_key, model_name):
-    """获取文件上传凭证"""
-    url = "https://dashscope.aliyuncs.com/api/v1/uploads"
-    headers = {
-        "Authorization": f"Bearer {api_key}",
-        "Content-Type": "application/json"
-    }
-    params = {
-        "action": "getPolicy",
-        "model": model_name
-    }
-    
-    response = requests.get(url, headers=headers, params=params)
-    if response.status_code != 200:
-        raise Exception(f"Failed to get upload policy: {response.text}")
-    
-    return response.json()['data']
-
-def upload_file_to_oss(policy_data, file_path):
-    """将文件上传到临时存储OSS"""
-    file_name = Path(file_path).name
-    key = f"{policy_data['upload_dir']}/{file_name}"
-    
-    with open(file_path, 'rb') as file:
-        files = {
-            'OSSAccessKeyId': (None, policy_data['oss_access_key_id']),
-            'Signature': (None, policy_data['signature']),
-            'policy': (None, policy_data['policy']),
-            'x-oss-object-acl': (None, policy_data['x_oss_object_acl']),
-            'x-oss-forbid-overwrite': (None, policy_data['x_oss_forbid_overwrite']),
-            'key': (None, key),
-            'success_action_status': (None, '200'),
-            'file': (file_name, file)
-        }
-        
-        response = requests.post(policy_data['upload_host'], files=files)
-        if response.status_code != 200:
-            raise Exception(f"Failed to upload file: {response.text}")
+import asyncio
+import subprocess
+from flask import Flask
+from threading import Thread
+from telegram import Update
+from telegram.ext import ApplicationBuilder, CommandHandler, MessageHandler, filters, ContextTypes
+
+# ─────────────────────────────────────────────────────────────
+# 0. RENDER İÇİN SAHTE WEB SUNUCUSU (7/24 HİLESİ)
+# ─────────────────────────────────────────────────────────────
+web_app = Flask(__name__)
+
+@web_app.route('/')
+def home():
+    return "MrBeast Fabrikası 7/24 Aktif! 🚀"
+
+def run_flask():
+    # Render PORT çevre değişkenini kullanır
+    port = int(os.environ.get("PORT", 8080))
+    web_app.run(host="0.0.0.0", port=port)
+
+# ─────────────────────────────────────────────────────────────
+# 1. MODAL KURULUMU
+# ─────────────────────────────────────────────────────────────
+def download_models():
+    import whisper, clip, torch
+    print("🤖 [MODAL] Modeller indiriliyor (Whisper & CLIP)...")
+    whisper.load_model("medium")
+    clip.load("ViT-L/14", device="cpu")
+
+image = (
+    modal.Image.debian_slim(python_version="3.10")
+    .apt_install("ffmpeg", "git", "libdav1d-dev", "libavcodec-extra", "libass-dev", "curl", "fontconfig")
+    .run_commands(
+        "mkdir -p /usr/share/fonts/truetype/montserrat",
+        "curl -L https://github.com/google/fonts/raw/main/ofl/montserrat/static/Montserrat-ExtraBold.ttf -o /usr/share/fonts/truetype/montserrat/Montserrat-ExtraBold.ttf",
+        "fc-cache -fv"
+    )
+    .pip_install("torch", "torchvision", "openai-whisper", "moviepy==1.0.3", "scenedetect[opencv]", "deep-translator", "python-telegram-bot", "flask")
+    .pip_install("git+https://github.com/openai/CLIP.git")
+    .run_function(download_models)
+)
+
+app = modal.App("telegram-beast-v45")
+
+# ─────────────────────────────────────────────────────────────
+# 2. ANA MOTOR (A10G GPU)
+# ─────────────────────────────────────────────────────────────
+def masterpiece_engine(video_path, audio_path):
+    import torch, clip, whisper, subprocess, time
+    from PIL import Image
+    from moviepy.editor import VideoFileClip, AudioFileClip, concatenate_videoclips
+    import moviepy.video.fx.all as vfx
+    from scenedetect import VideoManager, SceneManager
+    from scenedetect.detectors import ContentDetector
+    from deep_translator import GoogleTranslator
+
+    print("🎬 [ENGINE] Kurgu motoru ateşlendi...")
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    whisper_model = whisper.load_model("medium", device=device)
     
-    return f"oss://{key}"
-
-def upload_file_and_get_url(api_key, model_name, file_path):
-    """上传文件并获取URL"""
-    # 1. 获取上传凭证，上传凭证接口有限流，超出限流将导致请求失败
-    policy_data = get_upload_policy(api_key, model_name) 
-    # 2. 上传文件到OSS
-    oss_url = upload_file_to_oss(policy_data, file_path)
+    trans = whisper_model.transcribe(audio_path, language=None, word_timestamps=True)
+    full_v = VideoFileClip(video_path).without_audio()
+    audio_clip = AudioFileClip(audio_path)
+    audio_dur = audio_clip.duration
     
-    return oss_url
-
-
-class WanAnimateApp:
-    def __init__(self, url, get_url):
-        self.url = url
-        self.get_url = get_url
-
-    def predict(
-        self, 
-        ref_img,
-        video,
-        model_id,
-        model,
-    ):
-        # Upload files to OSS if needed and get URLs
-        image_url = upload_file_and_get_url(DASHSCOPE_API_KEY, model_id, ref_img)
-        video_url = upload_file_and_get_url(DASHSCOPE_API_KEY, model_id, video)
-
-        # Prepare the request payload
-        payload = {
-            "model": model_id,
-            "input": {
-                "image_url": image_url,
-                "video_url": video_url
-            },
-            "parameters": {
-                "check_image": True,
-                "mode": model,
-            }
-        }
-        
-        # Set up headers
-        headers = {
-            "X-DashScope-Async": "enable",
-            "X-DashScope-OssResourceResolve": "enable",
-            "Authorization": f"Bearer {DASHSCOPE_API_KEY}",
-            "Content-Type": "application/json"
-        }
-        
-        # Make the initial API request
-        url = self.url
-        response = requests.post(url, json=payload, headers=headers, timeout=60)
-        
-        # Check if request was successful
-        if response.status_code != 200:
-            raise Exception(f"Initial request failed with status code {response.status_code}: {response.text}")
-        
-        # Get the task ID from response
-        result = response.json()
-        task_id = result.get("output", {}).get("task_id")
-        if not task_id:
-            raise Exception("Failed to get task ID from response")
+    vm = VideoManager([video_path]); sm = SceneManager()
+    sm.add_detector(ContentDetector(threshold=27.0))
+    vm.start(); sm.detect_scenes(frame_source=vm)
+    s_list = sm.get_scene_list() or [(0, full_v.duration)]
+
+    clip_m, pre = clip.load("ViT-L/14", device=device)
+    pool = []
+    for start, end in s_list:
+        try:
+            s, e = start.get_seconds(), end.get_seconds()
+            if (e-s) < 0.2: continue
+            feat = clip_m.encode_image(pre(Image.fromarray(full_v.get_frame(s + (e-s)/2))).unsqueeze(0).to(device))
+            pool.append({'clip': full_v.subclip(s, e), 'feat': feat / feat.norm(dim=-1, keepdim=True), 'used': False})
+        except: continue
+
+    translator = GoogleTranslator(source='auto', target='en')
+    final_clips = []
+    scenes_per_seg = max(2, round(len(pool) / len(trans['segments'])))
+
+    for idx, seg in enumerate(trans['segments']):
+        t_en = translator.translate(seg['text'])
+        t_feat = clip_m.encode_text(clip.tokenize([t_en], truncate=True).to(device))
+        t_feat /= t_feat.norm(dim=-1, keepdim=True)
+        available = [p for p in pool if not p['used']] or pool
+        scores = sorted([( (t_feat @ sc['feat'].T).item(), i ) for i, sc in enumerate(available)], key=lambda x: x[0], reverse=True)
         
-        # Poll for results
-        get_url = f"{self.get_url}/{task_id}"
-        headers = {
-            "Authorization": f"Bearer {DASHSCOPE_API_KEY}",
-            "Content-Type": "application/json"
-        }
+        seg_dur = seg['end'] - seg['start']
+        k = scenes_per_seg if seg_dur > 1.2 else 1
+        top_matches = [available[i[1]] for i in scores[:k]]
+        temp_clips = [match['clip'] for match in top_matches]
+        for match in top_matches: match['used'] = True
         
-        while True:
-            response = requests.get(get_url, headers=headers, timeout=60)
-            if response.status_code != 200:
-                raise Exception(f"Failed to get task status: {response.status_code}: {response.text}")
-            
-            result = response.json()
-            print(result)
-            task_status = result.get("output", {}).get("task_status")
-            
-            if task_status == "SUCCEEDED":
-                # Task completed successfully, return video URL
-                video_url = result["output"]["results"]["video_url"]
-                return video_url, "SUCCEEDED"
-            elif task_status == "PENDING" or task_status == "RUNNING":
-                # Task is still running, wait and retry
-                time.sleep(10)  # Wait 10 seconds before polling again
-            else:
-                # Task failed or unknown, raise an exception with error message
-                error_msg = result.get("output", {}).get("message", "Unknown error")
-                code_msg = result.get("output", {}).get("code", "Unknown code")
-                print(f"\n\nTask failed: {error_msg} Code: {code_msg} TaskId: {task_id}\n\n")
-                return None, f"Task failed: {error_msg} Code: {code_msg} TaskId: {task_id}"
-                # raise Exception(f"Task failed: {error_msg} TaskId: {task_id}")
-
-def start_app():
-    import argparse
-    parser = argparse.ArgumentParser(description="Wan2.2-Animate 视频生成工具")
-    args = parser.parse_args()
+        if temp_clips:
+            combined = concatenate_videoclips(temp_clips, method="chain")
+            final_clips.append(combined.fx(vfx.speedx, combined.duration/seg_dur).set_duration(seg_dur))
+
+    curr_dur = sum([c.duration for c in final_clips])
+    if curr_dur < audio_dur and len(final_clips) > 0:
+        gap = audio_dur - curr_dur
+        first_c = final_clips[0]
+        loop_p = first_c.subclip(0, min(gap, first_c.duration))
+        final_clips.append(loop_p.set_duration(gap))
+
+    final_video = concatenate_videoclips(final_clips, method="chain").set_audio(audio_clip).set_duration(audio_dur)
+    temp_raw = f"/tmp/raw_{time.time()}.mp4"
+    final_video.write_videofile(temp_raw, codec="libx264", audio_codec="aac", fps=30, preset='ultrafast', threads=8)
+
+    ass_path = f"/tmp/subs_{time.time()}.ass"
+    header = "[Script Info]\nScriptType: v4.00+\nPlayResX: 1080\nPlayResY: 1920\n\n[V4+ Styles]\nFormat: Name, Fontname, Fontsize, PrimaryColour, SecondaryColour, OutlineColour, BackColour, Bold, Italic, Underline, StrikeOut, ScaleX, ScaleY, Spacing, Angle, BorderStyle, Outline, Shadow, Alignment, MarginL, MarginR, MarginV, Encoding\nStyle: Default,Montserrat,85,&H00FFFFFF,&H0000FFFF,&H00000000,&H00000000,-1,0,0,0,100,100,0,0,1,8,0,2,180,180,400,1\n"
+    lines = [header, "\n[Events]\nFormat: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text\n"]
+    for seg in trans['segments']:
+        for w in seg.get('words', []):
+            def f_t(s): return f"{int(s//3600)}:{int((s%3600)//60):02d}:{int(s%60):02d}.{int(round((s%1)*100)):02d}"
+            lines.append(f"Dialogue: 0,{f_t(w['start'])},{f_t(w['end'])},Default,,0,0,0,," + r"{\c&H0000FFFF&}{\fscx0\fscy0\t(0,100,\fscx125\fscy125)\t(100,200,\fscx100\fscy100)}" + f"{w['word'].strip().upper()}\n")
     
-    url = "https://dashscope.aliyuncs.com/api/v1/services/aigc/image2video/video-synthesis/"
-    # url = "https://poc-dashscope.aliyuncs.com/api/v1/services/aigc/image2video/video-synthesis"
-
-    get_url = f"https://dashscope.aliyuncs.com/api/v1/tasks/"
-    # get_url = f"https://poc-dashscope.aliyuncs.com/api/v1/tasks"
-    app = WanAnimateApp(url=url, get_url=get_url)
-
-    with gr.Blocks(title="Wan2.2-Animate 视频生成") as demo:
-        gr.HTML("""
-
-            
-            <div style="padding: 2rem; text-align: center; max-width: 1200px; margin: 0 auto; font-family: Arial, sans-serif;">
-
-                <h1 style="font-size: 2.5rem; font-weight: bold; margin-bottom: 0.5rem; color: #333;">
-                    Wan2.2-Animate: Unified Character Animation and Replacement with Holistic Replication
-                </h1>
-                
-                <h3 style="font-size: 2.5rem; font-weight: bold; margin-bottom: 0.5rem; color: #333;">
-                    Wan2.2-Animate: 统一的角色动画和视频人物替换模型
-                </h3>
-
-                <div style="font-size: 1.25rem; margin-bottom: 1.5rem; color: #555;">
-                    Tongyi Lab, Alibaba
-                </div>
-
-                <div style="display: flex; flex-wrap: wrap; justify-content: center; gap: 1rem; margin-bottom: 1rem;">
-                    <!-- 第一行按钮 -->
-                    <a href="https://arxiv.org/abs/2509.14055" target="_blank"
-                    style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; /* 浅灰色背景 */ color: #333; /* 深色文字 */ text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;">
-                        <span style="margin-right: 0.5rem;">📄</span> <!-- 使用文档图标 -->
-                        <span>Paper</span>
-                    </a>
-
-                    <a href="https://github.com/Wan-Video/Wan2.2" target="_blank"
-                    style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;">
-                        <span style="margin-right: 0.5rem;">💻</span> <!-- 使用电脑图标 -->
-                        <span>GitHub</span>
-                    </a>
-
-                    <a href="https://huggingface.co/Wan-AI/Wan2.2-Animate-14B" target="_blank"
-                    style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;">
-                        <span style="margin-right: 0.5rem;">🤗</span>
-                        <span>HF Model</span>
-                    </a>
-
-                    <a href="https://www.modelscope.cn/models/Wan-AI/Wan2.2-Animate-14B" target="_blank"
-                    style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;">
-                        <span style="margin-right: 0.5rem;">🤖</span>
-                        <span>MS Model</span>
-                    </a>
-                </div>
-
-                <div style="display: flex; flex-wrap: wrap; justify-content: center; gap: 1rem;">
-                    <!-- 第二行按钮 -->
-                    <a href="https://huggingface.co/spaces/Wan-AI/Wan2.2-Animate" target="_blank"
-                    style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;">
-                        <span style="margin-right: 0.5rem;">🤗</span>
-                        <span>HF Space</span>
-                    </a>
-
-                    <a href="https://www.modelscope.cn/studios/Wan-AI/Wan2.2-Animate" target="_blank"
-                    style="display: inline-flex; align-items: center; padding: 0.5rem 1rem; background-color: #f0f0f0; color: #333; text-decoration: none; border-radius: 9999px; font-weight: 500; transition: background-color 0.3s;">
-                        <span style="margin-right: 0.5rem;">🤖</span>
-                        <span>MS Studio</span>
-                    </a>
-                </div>
-
-            </div>
-            
-            """)
-        
-        gr.HTML("""
-                <details>
-                    <summary>‼️Usage (使用说明)</summary>
-                    
-                    Wan-Animate supports two mode:
-                    <ul>
-                        <li>Move Mode: animate the  character in input image with movements from the input video</li>
-                        <li>Mix Mode: replace the character in input video with the character in input image</li>
-                    </ul>
-                    
-                    Wan-Animate 支持两种模式:
-                    <ul>
-                        <li>Move模式: 用输入视频中提取的动作，驱动输入图片中的角色</li>
-                        <li>Mix模式: 用输入图片中的角色，替换输入视频中的角色</li>
-                    </ul>
-
-                    Currently, the following restrictions apply to inputs:
-
-                    <ul> <li>Video file size: Less than 200MB</li> 
-                    <li>Video resolution: The shorter side must be greater than 200, and the longer side must be less than 2048</li> 
-                    <li>Video duration: 2s to 30s</li> 
-                    <li>Video aspect ratio: 1:3 to 3:1</li> 
-                    <li>Video formats: mp4, avi, mov</li> 
-                    <li>Image file size: Less than 5MB</li> 
-                    <li>Image resolution: The shorter side must be greater than 200, and the longer side must be less than 4096</li> 
-                    <li>Image formats: jpg, png, jpeg, webp, bmp</li> </ul>
-
-                    
-                    当前，对于输入有以下的限制 
-
-                    <ul>
-                        <li>视频文件大小: 小于 200MB</li>
-                        <li>视频分辨率： 最小边大于 200, 最大边小于2048</li>
-                        <li>视频时长: 2s ~ 30s </li> 
-                        <li>视频比例：1:3 ~ 3:1 </li>
-                        <li>视频格式: mp4, avi, mov </li> 
-                        <li>图片文件大小: 小于5MB </li>
-                        <li>图片分辨率：最小边大于200，最大边小于4096 </li>
-                        <li>图片格式: jpg, png, jpeg, webp, bmp </li> 
-                    </ul>     
-                    
-                    <p> Currently, the inference quality has two variants. You can use our open-source code for more flexible configuration. </p>
-                    
-                    <p>当前，推理质量有两个变种。 您可以使用我们的开源代码，来进行更灵活的设置。</p>
-                    
-                    <ul>
-                        <li> wan-pro: 25fps, 720p </li> 
-                        <li> wan-std: 15fps, 720p  </li>
-                    </ul>     
-                              
-
-                </details>                
-                """)
-
-        with gr.Row():
-            with gr.Column():    
-                ref_img = gr.Image(
-                    label="Reference Image(参考图像)",
-                    type="filepath",
-                    sources=["upload"],
-                )
-                
-                video = gr.Video(
-                    label="Template Video(模版视频)",
-                    sources=["upload"],
-                )
-                
-                with gr.Row():
-                    model_id = gr.Dropdown(
-                        label="Mode(模式)",
-                        choices=["wan2.2-animate-move", "wan2.2-animate-mix"],
-                        value="wan2.2-animate-move",
-                        info=""
-                    )
-
-                    model = gr.Dropdown(
-                        label="推理质量(Inference Quality)",
-                        choices=["wan-pro", "wan-std"],
-                        value="wan-pro",
-                    )
-
-                run_button = gr.Button("Generate Video(生成视频)")
-
-            with gr.Column():
-                output_video = gr.Video(label="Output Video(输出视频)")
-                output_status = gr.Textbox(label="Status(状态)")
-        
-        run_button.click(
-            fn=app.predict,
-            inputs=[
-                ref_img,
-                video,
-                model_id,
-                model,
-            ],
-            outputs=[output_video, output_status],
-        )
-
-        example_data = [
-            ['./examples/mov/1/1.jpeg', './examples/mov/1/1.mp4', 'wan2.2-animate-move', 'wan-pro'],
-            ['./examples/mov/2/2.jpeg', './examples/mov/2/2.mp4', 'wan2.2-animate-move', 'wan-pro'],
-            ['./examples/mix/1/1.jpeg', './examples/mix/1/1.mp4', 'wan2.2-animate-mix', 'wan-pro'],
-            ['./examples/mix/2/2.jpeg', './examples/mix/2/2.mp4', 'wan2.2-animate-mix', 'wan-pro']
-        ]
-
-        if example_data:
-            gr.Examples(
-                examples=example_data,
-                inputs=[ref_img, video, model_id, model],
-                outputs=[output_video, output_status],
-                fn=app.predict,
-                cache_examples="lazy",
-            )
+    with open(ass_path, "w", encoding="utf-8") as f: f.write("".join(lines))
+    final_out = f"/tmp/final_{time.time()}.mp4"
+    subprocess.run(["ffmpeg", "-y", "-i", temp_raw, "-vf", f"subtitles={ass_path}", "-c:a", "copy", final_out], check=True)
+    return final_out
+
+# ─────────────────────────────────────────────────────────────
+# 3. MODAL FONKSİYONU
+# ─────────────────────────────────────────────────────────────
+@app.function(image=image, gpu="A10G", timeout=3600, keep_warm=1)
+async def process_via_telegram(vid_bytes, aud_bytes):
+    import os, subprocess
+    with open("/tmp/vid.mp4", "wb") as f: f.write(vid_bytes)
+    with open("/tmp/aud.mp3", "wb") as f: f.write(aud_bytes)
     
-    demo.queue(default_concurrency_limit=100)
+    if os.path.getsize("/tmp/vid.mp4") > 15 * 1024 * 1024:
+        subprocess.run(["ffmpeg", "-y", "-i", "/tmp/vid.mp4", "-c:v", "libx264", "-crf", "28", "-preset", "veryfast", "-c:a", "copy", "/tmp/comp.mp4"], check=True)
+        os.replace("/tmp/comp.mp4", "/tmp/vid.mp4")
+
+    res_path = masterpiece_engine("/tmp/vid.mp4", "/tmp/aud.mp3")
+    with open(res_path, "rb") as f: return f.read()
+
+# ─────────────────────────────────────────────────────────────
+# 4. TELEGRAM BOTU
+# ─────────────────────────────────────────────────────────────
+TOKEN = "7700336574:AAHD-4d-4LCYgEMm4f4ccDEAnAqsuJ-wEWU"
+user_data = {}
+
+async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    await update.message.reply_text("Nağarsan kələ? Mənə bi dənə SƏS faylı (.mp3) at🚀")
+
+async def handle_docs(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    chat_id = update.effective_chat.id
+    doc = update.message.document or update.message.audio or update.message.video
+    if not doc: return
     
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860
-    )
-
-
+    f_name = doc.file_name.lower() if hasattr(doc, 'file_name') and doc.file_name else ""
+    is_audio = f_name.endswith(('.mp3', '.m4a', '.wav')) or update.message.audio
+    is_video = f_name.endswith(('.mp4', '.mov', '.avi')) or update.message.video
+
+    if chat_id not in user_data:
+        if is_audio:
+            file = await context.bot.get_file(doc.file_id)
+            user_data[chat_id] = {'aud': await file.download_as_bytearray()}
+            await update.message.reply_text("✅ İndi VİDEO (.mp4) göndər.")
+        else:
+            await update.message.reply_text("Əvvəlcə SƏS göndər.")
+    else:
+        if is_video:
+            await update.message.reply_text("🚀 Hazırlanır, gözlə kələ...")
+            try:
+                file = await context.bot.get_file(doc.file_id)
+                vid_bytes = await file.download_as_bytearray()
+                res_bytes = await process_via_telegram.remote.aio(bytes(vid_bytes), bytes(user_data[chat_id]['aud']))
+                
+                out = f"final_{chat_id}.mp4"
+                with open(out, "wb") as f: f.write(res_bytes)
+                await update.message.reply_document(document=open(out, "rb"))
+                os.remove(out)
+                del user_data[chat_id]
+            except Exception as e:
+                await update.message.reply_text(f"Hata: {str(e)}")
+        else:
+            await update.message.reply_text("Video göndər.")
+
+# ─────────────────────────────────────────────────────────────
+# 5. MAIN (RENDER UYUMLU)
+# ─────────────────────────────────────────────────────────────
 if __name__ == "__main__":
-    start_app()
+    # Arka planda Flask'ı başlat (Render 7/24 uyanık kalsın diye)
+    Thread(target=run_flask).start()
+    
+    print("🚀 Bot başlatılıyor...")
+    with app.run():
+        application = ApplicationBuilder().token(TOKEN).build()
+        application.add_handler(CommandHandler("start", start))
+        application.add_handler(MessageHandler(filters.ALL, handle_docs))
+        application.run_polling(drop_pending_updates=True)