Update app.py

app.py

@@ -97,6 +97,850 @@ def create_error_image(run_id, message):
         except Exception:
             pass
 
+# --- ایجاد خودکار اسکریپت‌های مورد نیاز درون پوشه yml در بدو استارت آپ ---
+def write_default_scripts():
+    scripts = {
+        "generate-flux.py": """
+import os, sys, random, requests
+from gradio_client import Client
+
+def get_env_int(name, default=0):
+    val = os.environ.get(name, '')
+    try:
+        return int(val) if val.strip() else default
+    except ValueError:
+        return default
+
+prompt = os.environ.get('PROMPT', '')
+width = get_env_int('WIDTH', 1024)
+height = get_env_int('HEIGHT', 1024)
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+
+def report_failure(error_msg):
+    try:
+        requests.post(
+            f"{space_url}/api/webhook/fail",
+            json={
+                "run_id": run_id,
+                "error": error_msg,
+                "event_type": "generate-flux",
+                "client_payload": {
+                    "prompt": prompt,
+                    "width": width,
+                    "height": height,
+                    "run_id": run_id,
+                    "space_url": space_url
+                },
+                "github_run_id": github_run_id
+            },
+            timeout=15
+        )
+    except Exception as e:
+        print(f"Failed to report failure: {e}")
+
+print('1. Connecting to Flux...')
+try:
+    client = Client('black-forest-labs/FLUX.1-dev')
+    seed = random.randint(1, 2147483647)
+    
+    result = client.predict(prompt, seed, True, width, height, 3.5, 28, api_name='/infer')
+    image_path = result[0] if isinstance(result, (tuple, list)) else result
+    
+    print(f'2. Uploading back to Docker Space...')
+    with open(image_path, 'rb') as f:
+        res = requests.post(f'{space_url}/api/webhook/upload', data={'run_id': run_id, 'github_run_id': github_run_id}, files={'file': f})
+    
+    if res.status_code == 200:
+        print('3. SUCCESS!')
+    else:
+        sys.exit(1)
+        
+except Exception as e:
+    err_str = str(e)
+    print(f'ERROR: {err_str}')
+    report_failure(err_str)
+    sys.exit(1)
+        """,
+        "generate-flux2.py": """
+import os, sys, random, requests, json
+from gradio_client import Client, handle_file
+
+def get_env_int(name, default=0):
+    val = os.environ.get(name, '')
+    try:
+        return int(val) if val.strip() else default
+    except ValueError:
+        return default
+
+def get_env_float(name, default=0.0):
+    val = os.environ.get(name, '')
+    try:
+        return float(val) if val.strip() else default
+    except ValueError:
+        return default
+
+prompt = os.environ.get('PROMPT', '')
+image_urls_raw = os.environ.get('IMAGE_URLS', '[]')
+width = get_env_int('WIDTH', 1024)
+height = get_env_int('HEIGHT', 1024)
+steps = get_env_int('STEPS', 30)
+guidance = get_env_float('GUIDANCE', 4.0)
+seed = get_env_int('SEED', 0)
+randomize_seed = os.environ.get('RANDOMIZE_SEED', 'true').lower() == 'true'
+prompt_upsampling = os.environ.get('PROMPT_UPSAMPLING', 'true').lower() == 'true'
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+hf_token = os.environ.get('HF_TOKEN', '')
+
+print(f'Starting direct Flux 2 generation for run_id: {run_id}')
+
+print('1. Parsing and downloading images...')
+image_urls = []
+if image_urls_raw:
+    try:
+        cleaned_json = image_urls_raw.replace('null', '').strip()
+        if cleaned_json and cleaned_json != '[]':
+            image_urls = json.loads(cleaned_json)
+    except Exception as e:
+        print(f'JSON parsing error: {e}')
+
+def report_failure(error_msg):
+    try:
+        requests.post(
+            f"{space_url}/api/webhook/fail",
+            json={
+                "run_id": run_id,
+                "error": error_msg,
+                "event_type": "generate-flux2",
+                "client_payload": {
+                    "data": {
+                        "prompt": prompt,
+                        "image_urls": image_urls,
+                        "width": width,
+                        "height": height,
+                        "steps": steps,
+                        "guidance": guidance,
+                        "seed": seed,
+                        "randomize_seed": randomize_seed,
+                        "prompt_upsampling": prompt_upsampling,
+                        "run_id": run_id,
+                        "space_url": space_url,
+                        "hf_token": hf_token
+                    }
+                },
+                "github_run_id": github_run_id
+            },
+            timeout=15
+        )
+    except Exception as e:
+        print(f"Failed to report failure: {e}")
+
+files_to_send = []
+for idx, url in enumerate(image_urls):
+    if url:
+        print(f'Downloading input image {idx}: {url}')
+        ext = url.split('.')[-1] if '.' in url else 'png'
+        local_filename = f'input_{idx}.{ext}'
+        try:
+            req = requests.get(url, timeout=30)
+            with open(local_filename, 'wb') as f:
+                f.write(req.content)
+            files_to_send.append({'image': handle_file(local_filename), 'caption': None})
+        except Exception as e:
+            print(f'Failed to download {url}: {e}')
+
+print('2. Connecting to FLUX.2-dev Space...')
+try:
+    if hf_token:
+        client = Client('black-forest-labs/FLUX.2-dev', token=hf_token)
+    else:
+        client = Client('black-forest-labs/FLUX.2-dev')
+    
+    if randomize_seed:
+        seed = random.randint(1, 2147483647)
+    
+    print(f'Predicting with seed={seed}, width={width}, height={height}, steps={steps}, guidance={guidance}, upsampling={prompt_upsampling}...')
+    result = client.predict(
+        prompt,
+        files_to_send,
+        seed,
+        randomize_seed,
+        width,
+        height,
+        steps,
+        guidance,
+        prompt_upsampling,
+        api_name='/infer'
+    )
+    
+    image_path = result[0] if isinstance(result, (tuple, list)) else result
+    seed_used = result[1] if (isinstance(result, (tuple, list)) and len(result) > 1) else seed
+    
+    print('3. Uploading metadata seed back...')
+    with open('seed.txt', 'w') as sf:
+        sf.write(str(seed_used))
+    requests.post(
+        f'{space_url}/api/webhook/upload',
+        data={'run_id': f'{run_id}_seed', 'github_run_id': github_run_id, 'ext': 'txt'},
+        files={'file': open('seed.txt', 'rb')}
+    )
+    
+    print('4. Uploading generated image back...')
+    with open(image_path, 'rb') as f:
+        upload_res = requests.post(
+            f'{space_url}/api/webhook/upload', 
+            data={'run_id': run_id, 'github_run_id': github_run_id}, 
+            files={'file': f}
+        )
+    
+    if upload_res.status_code == 200:
+        print('SUCCESS!')
+    else:
+        print(f'Upload failed with status {upload_res.status_code}: {upload_res.text}')
+        sys.exit(1)
+        
+except Exception as e:
+    err_str = str(e)
+    print(f'Generation error: {err_str}')
+    report_failure(err_str)
+    sys.exit(1)
+        """,
+        "generate-cartoon.py": """
+import os, sys, random, requests
+from gradio_client import Client
+
+def get_env_int(name, default=0):
+    val = os.environ.get(name, '')
+    try:
+        return int(val) if val.strip() else default
+    except ValueError:
+        return default
+
+prompt = os.environ.get('PROMPT', '')
+width = get_env_int('WIDTH', 1024)
+height = get_env_int('HEIGHT', 1024)
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+
+def report_failure(error_msg):
+    try:
+        requests.post(
+            f"{space_url}/api/webhook/fail",
+            json={
+                "run_id": run_id,
+                "error": error_msg,
+                "event_type": "generate-cartoon",
+                "client_payload": {
+                    "prompt": prompt,
+                    "width": width,
+                    "height": height,
+                    "run_id": run_id,
+                    "space_url": space_url
+                },
+                "github_run_id": github_run_id
+            },
+            timeout=15
+        )
+    except Exception as e:
+        print(f"Failed to report failure: {e}")
+
+print('1. Connecting to LoRA DLC Space...')
+try:
+    client = Client('prithivMLmods/FLUX-LoRA-DLC')
+    print('2. Loading Cartoon Model (Long Toons)...')
+    client.predict('prithivMLmods/Flux-Long-Toon-LoRA', api_name='/add_custom_lora')
+    
+    print('3. Generating Cartoon Image...')
+    result = client.predict(
+        prompt=f'Long toons {prompt}',
+        image_input=None,
+        cfg_scale=3.5,
+        steps=28,
+        randomize_seed=True,
+        seed=random.randint(1, 2147483647),
+        width=width,
+        height=height,
+        lora_scale=0.8,
+        api_name='/run_lora'
+    )
+    image_path = result[0] if isinstance(result, (tuple, list)) else result
+    
+    print('4. Uploading back to Docker Space...')
+    with open(image_path, 'rb') as f:
+        res = requests.post(f'{space_url}/api/webhook/upload', 
+                         data={'run_id': run_id, 'github_run_id': github_run_id}, 
+                         files={'file': f})
+    if res.status_code == 200:
+        print('5. SUCCESS!')
+    else:
+        sys.exit(1)
+except Exception as e:
+    err_str = str(e)
+    print(f'CRITICAL ERROR: {err_str}')
+    report_failure(err_str)
+    sys.exit(1)
+        """,
+        "generate-midjourney.py": """
+import os, sys, random, requests
+from gradio_client import Client
+
+def get_env_int(name, default=0):
+    val = os.environ.get(name, '')
+    try:
+        return int(val) if val.strip() else default
+    except ValueError:
+        return default
+
+raw_prompt = os.environ.get('PROMPT', '')
+final_prompt = f'MJ v6 {raw_prompt}'
+width = get_env_int('WIDTH', 1024)
+height = get_env_int('HEIGHT', 1024)
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+
+def report_failure(error_msg):
+    try:
+        requests.post(
+            f"{space_url}/api/webhook/fail",
+            json={
+                "run_id": run_id,
+                "error": error_msg,
+                "event_type": "generate-midjourney",
+                "client_payload": {
+                    "prompt": raw_prompt,
+                    "width": width,
+                    "height": height,
+                    "run_id": run_id,
+                    "space_url": space_url
+                },
+                "github_run_id": github_run_id
+            },
+            timeout=15
+        )
+    except Exception as e:
+        print(f"Failed to report failure: {e}")
+
+print('1. Connecting to LoRA DLC Space...')
+try:
+    client = Client('prithivMLmods/FLUX-LoRA-DLC')
+    print('2. Loading Midjourney Model...')
+    client.predict('strangerzonehf/Flux-Midjourney-Mix2-LoRA', api_name='/add_custom_lora')
+    
+    print(f'3. Generating Image... Prompt: {final_prompt[:50]}...')
+    result = client.predict(
+        prompt=final_prompt,
+        image_input=None,
+        cfg_scale=3.5,
+        steps=28,
+        randomize_seed=True,
+        seed=random.randint(1, 2147483647),
+        width=width,
+        height=height,
+        lora_scale=0.8,
+        api_name='/run_lora'
+    )
+    image_path = result[0] if isinstance(result, (tuple, list)) else result
+    
+    print('4. Uploading back to Docker Space...')
+    with open(image_path, 'rb') as f:
+        res = requests.post(f'{space_url}/api/webhook/upload', 
+                         data={'run_id': run_id, 'github_run_id': github_run_id}, 
+                         files={'file': f})
+    if res.status_code == 200:
+        print('5. SUCCESS!')
+    else:
+        sys.exit(1)
+except Exception as e:
+    err_str = str(e)
+    print(f'CRITICAL ERROR: {err_str}')
+    report_failure(err_str)
+    sys.exit(1)
+        """,
+        "chat-gemma.py": """
+import os, sys, requests
+from gradio_client import Client, handle_file
+
+prompt = os.environ.get('PROMPT', '')
+file_url = os.environ.get('FILE_URL', '')
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+gh_run_id = os.environ.get('GITHUB_RUN_ID')
+
+files_to_send = []
+if file_url:
+    print(f'Downloading attachment: {file_url}')
+    ext = file_url.split('.')[-1] if '.' in file_url else 'bin'
+    local_filename = f'attachment.{ext}'
+    try:
+        req = requests.get(file_url, timeout=30)
+        with open(local_filename, 'wb') as f:
+            f.write(req.content)
+        files_to_send.append(handle_file(local_filename))
+    except Exception as e:
+        print(f'Failed to download file: {e}')
+
+print('Connecting to Gemma-4 Space...')
+bot_reply = ''
+try:
+    client = Client('huggingface-projects/gemma-4-e4b-it')
+    message_payload = {'text': prompt, 'files': files_to_send}
+    result = client.predict(
+        message=message_payload,
+        thinking=False,
+        max_new_tokens=4000,
+        max_soft_tokens=1120,
+        system_prompt='شما یک دستیار هوش مصنوعی بسیار باهوش، مفید و مودب به زبان فارسی هستید.',
+        api_name='/generate'
+    )
+    bot_reply = result[0] if isinstance(result, (list, tuple)) else result
+    if isinstance(bot_reply, dict):
+        bot_reply = bot_reply.get('text', str(bot_reply))
+except Exception as e:
+    err_str = str(e)
+    print(f'Generation Error: {err_str}')
+    if 'ZeroGPU quota' in err_str or 'quota' in err_str.lower():
+        bot_reply = '⚠️ **پردازش متوقف شد:**\\nدرخواست شما طولانی و پرحجم است (پردازش فایل‌های صوتی یا حجیم نیازمند منابع بالایی است و سهمیه سرور موقتاً پر شده است).\\n\\nلطفاً چند ساعت دیگر امتحان کنید یا درخواست و فایل سبک‌تری ارسال نمایید.'
+    else:
+        bot_reply = f'⚠️ خطای سرور پردازش: {err_str}'
+
+print('Uploading response back to Docker Space...')
+try:
+    with open('response.txt', 'w', encoding='utf-8') as f:
+        f.write(bot_reply)
+    with open('response.txt', 'rb') as f:
+        res = requests.post(f'{space_url}/api/webhook/upload',
+                         data={'run_id': run_id, 'github_run_id': gh_run_id, 'ext': 'txt'},
+                         files={'file': f})
+    if res.status_code == 200:
+        print('SUCCESS!')
+    else:
+        sys.exit(1)
+except Exception as e:
+    sys.exit(1)
+        """,
+        "generate-editor.py": """
+import os, sys, requests, re, time
+
+# =========================================================
+# رفع قطعی مشکل The read operation timed out
+# تنظیم دستی زمان انتظار به 5 دقیقه (300 ثانیه) مانند مرورگر
+import httpx
+original_client_init = httpx.Client.__init__
+def patched_client_init(self, *args, **kwargs):
+    kwargs['timeout'] = httpx.Timeout(300.0)
+    original_client_init(self, *args, **kwargs)
+httpx.Client.__init__ = patched_client_init
+
+original_async_init = httpx.AsyncClient.__init__
+def patched_async_init(self, *args, **kwargs):
+    kwargs['timeout'] = httpx.Timeout(300.0)
+    original_async_init(self, *args, **kwargs)
+httpx.AsyncClient.__init__ = patched_async_init
+# =========================================================
+
+from gradio_client import Client, handle_file
+
+prompt = os.environ.get('PROMPT', '')
+image_url = os.environ.get('IMAGE_URL', '')
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+
+def report_failure(error_msg):
+    try:
+        requests.post(
+            f"{space_url}/api/webhook/fail",
+            json={
+                "run_id": run_id,
+                "error": error_msg,
+                "event_type": "generate-editor",
+                "client_payload": {
+                    "prompt": prompt,
+                    "image_url": image_url,
+                    "run_id": run_id,
+                    "space_url": space_url
+                },
+                "github_run_id": github_run_id
+            },
+            timeout=15
+        )
+    except Exception as e:
+        print(f"Failed to report failure: {e}")
+
+print('1. Downloading input image from Docker Space...')
+try:
+    req = requests.get(image_url, timeout=30)
+    with open('input.png', 'wb') as f:
+        f.write(req.content)
+    print('   -> Input image ready.')
+except Exception as e:
+    print(f'Download failed: {e}')
+    sys.exit(1)
+
+print('2. Connecting to Omni Editor and Processing (Timeout extended to 300s)...')
+result_str = ''
+success = False
+
+for attempt in range(3):
+    try:
+        print(f'   -> Attempt {attempt + 1} of 3...')
+        client = Client('selfit-camera/omni-image-editor')
+        result = client.predict(
+            handle_file('input.png'), 
+            prompt,
+            api_name='/edit_image_interface'
+        )
+        result_str = str(result)
+        if 'src=' in result_str or 'http' in result_str:
+            success = True
+            break
+        else:
+            print(f'   -> Missing valid response format: {result_str[:100]}...')
+    except Exception as client_err:
+        print(f'   -> Attempt {attempt + 1} failed: {client_err}')
+        time.sleep(5)
+
+if not success:
+    print(f'CRITICAL ERROR: All attempts failed. Raw result: {result_str}')
+    sys.exit(1)
+
+print('3. Parsing result string...')
+urls = re.findall(r'src=[\'\"]([^\'\"]+)[\'\"]', result_str)
+final_remote_url = None
+for url in urls:
+    if url.startswith('http'):
+        final_remote_url = url
+        break
+
+if not final_remote_url:
+    direct_urls = re.findall(r'(https?://[^\s\'\"]+\.(?:png|jpg|jpeg|webp|gif))', result_str)
+    if direct_urls:
+        final_remote_url = direct_urls[0]
+
+if not final_remote_url:
+    print(f'ERROR: Could not find valid URL. Raw result: {result_str}')
+    sys.exit(1)
+
+print(f'   -> Found Final Image URL: {final_remote_url}')
+
+print('4. Downloading final image from remote host...')
+try:
+    img_req = requests.get(final_remote_url, timeout=60)
+    content_type = img_req.headers.get('Content-Type', '')
+    ext = 'png'
+    if 'image/webp' in content_type:
+        ext = 'webp'
+    elif 'image/jpeg' in content_type or 'image/jpg' in content_type:
+        ext = 'jpg'
+        
+    filename = f'output.{ext}'
+    with open(filename, 'wb') as f:
+        f.write(img_req.content)
+    print(f'   -> Saved locally as {filename}')
+except Exception as dl_err:
+    print(f'Failed to download processed image: {dl_err}')
+    sys.exit(1)
+
+print(f'5. Uploading back to Docker Space: {space_url}')
+try:
+    with open(filename, 'rb') as f:
+        res = requests.post(
+            f'{space_url}/api/webhook/upload', 
+            data={'run_id': run_id, 'github_run_id': github_run_id, 'ext': ext}, 
+            files={'file': f},
+            timeout=60
+        )
+    if res.status_code == 200:
+        print('6. SUCCESS!')
+    else:
+        sys.exit(1)
+except Exception as e:
+    err_str = str(e)
+    report_failure(err_str)
+    sys.exit(1)
+        """,
+        "generate-video.py": """
+import os, sys, random, requests, time
+from gradio_client import Client, handle_file
+from PIL import Image, ImageOps
+
+prompt = os.environ.get('PROMPT', '').strip()
+if not prompt: 
+    prompt = 'make this image come alive, cinematic motion, smooth animation'
+else:
+    prompt = f'{prompt}, cinematic motion, smooth animation, high quality'
+
+negative_prompt = '色调艳丽, 过曝, 静态, 细节模糊不清, 字幕, 风格, 作品, 画作, 画面, 静止, 整体发灰, 最差质量, 低质量, JPEG压缩残留, 丑陋의, 残缺의, 多余的手指, 画得不好的手部, 画得不好的脸部, 畸形の, 毁容의, 形态畸形的肢体, 手指融合, 静止不动的画面, 杂乱의 背景, 三条腿, 背景人很多, 倒着走'
+
+image_url = os.environ.get('IMAGE_URL', '')
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+
+try:
+    duration = float(os.environ.get('DURATION', 5.0))
+except Exception:
+    duration = 5.0
+
+def report_failure(error_msg):
+    try:
+        requests.post(
+            f"{space_url}/api/webhook/fail",
+            json={
+                "run_id": run_id,
+                "error": error_msg,
+                "event_type": "generate-video",
+                "client_payload": {
+                    "prompt": prompt,
+                    "duration": duration,
+                    "image_url": image_url,
+                    "run_id": run_id,
+                    "space_url": space_url
+                },
+                "github_run_id": github_run_id
+            },
+            timeout=15
+        )
+    except Exception as e:
+        print(f"Failed to report failure: {e}")
+
+print('1. Downloading input image from Docker Space...')
+try:
+    req = requests.get(image_url, timeout=30)
+    with open('input_raw.png', 'wb') as f:
+        f.write(req.content)
+except Exception as e:
+    print(f'Download failed: {e}')
+    sys.exit(1)
+
+print('2. Analyzing image dimensions to prevent stretching...')
+img = Image.open('input_raw.png').convert('RGB')
+orig_w, orig_h = img.size
+ratio = orig_w / orig_h
+
+if ratio > 1.2:
+    target_w, target_h = 832, 480  
+    print('   -> Format: Landscape (16:9)')
+elif ratio < 0.8:
+    target_w, target_h = 480, 832  
+    print('   -> Format: Portrait (9:16)')
+else:
+    target_w, target_h = 480, 480  
+    print('   -> Format: Square (1:1)')
+
+img_resized = ImageOps.fit(img, (target_w, target_h), Image.Resampling.LANCZOS)
+img_resized.save('input.png')
+print(f'   -> Image perfectly resized to {target_w}x{target_h}')
+
+print('3. Connecting to AI Video Space...')
+video_path = None
+
+space_id = 'zerogpu-aoti/wan2-2-fp8da-aoti-faster'
+print(f'   -> Loading Space: {space_id}')
+try:
+    client = Client(space_id)
+except Exception as e:
+    print(f'CRITICAL ERROR: Could not load space. {e}')
+    sys.exit(1)
+
+max_attempts = 4
+for attempt in range(max_attempts):
+    seed = random.randint(1, 2147483647)
+    print(f'   -> Attempt {attempt + 1} of {max_attempts} with seed {seed} and duration {duration}s...')
+    
+    try:
+        result = client.predict(
+            handle_file('input.png'),  # [0] عکس ورودی
+            prompt,                    # [1] پرامپت مثبت
+            6,                         # [2] مقدار ثابت
+            negative_prompt,           # [3] پرامپت منفی
+            duration,                  # [4] زمان انتخابی کاربر
+            1,                         # [5] مقدار ثابت
+            1,                         # [6] مقدار ثابت
+            seed,                      # [7] هسته پردازش
+            True,                      # [8] رندوم کردن Seed
+            fn_index=0
+        )
+        
+        if isinstance(result, list) and len(result) > 0:
+            video_path = result[0].get('video') or result[0].get('path') if isinstance(result[0], dict) else result[0]
+        elif isinstance(result, tuple) and len(result) > 0:
+            video_path = result[0]
+        elif isinstance(result, dict):
+            video_path = result.get('video') or result.get('path')
+        else:
+            video_path = result
+            
+        if video_path and os.path.exists(str(video_path)):
+            print('   -> Success! Video generated.')
+            break
+            
+    except Exception as e:
+        err_msg = str(e)
+        print(f'   -> Failed on attempt {attempt + 1}: {err_msg}')
+        time.sleep(5)
+
+if not video_path or not os.path.exists(str(video_path)):
+    err_str = "Video generation failed on all attempts"
+    report_failure(err_str)
+    sys.exit(1)
+
+print('4. Uploading back to your Docker Space...')
+try:
+    with open(video_path, 'rb') as f:
+        res = requests.post(f'{space_url}/api/webhook/upload', 
+                         data={'run_id': run_id, 'github_run_id': github_run_id, 'ext': 'mp4'}, 
+                         files={'file': f})
+    if res.status_code == 200:
+        print('5. SUCCESS!')
+    else:
+        sys.exit(1)
+except Exception as e:
+    err_str = str(e)
+    report_failure(err_str)
+    sys.exit(1)
+        """,
+        "generate-audio.py": """
+import os, sys, requests, time
+from gradio_client import Client, handle_file
+
+# --- Variables injected by Flask ---
+AUDIO_TYPE = '___AUDIO_TYPE___'
+NEGATIVE_PROMPT = '''___NEGATIVE_PROMPT___'''
+
+prompt = os.environ.get('PROMPT', '')
+try: seed = int(os.environ.get('SEED', '-1'))
+except: seed = -1
+try: duration = float(os.environ.get('DURATION', '8'))
+except: duration = 8.0
+
+file_url = os.environ.get('FILE_URL', '')
+run_id = os.environ.get('RUN_ID')
+space_url = os.environ.get('SPACE_URL')
+github_run_id = os.environ.get('GITHUB_RUN_ID')
+
+def report_failure(error_msg):
+    try:
+        requests.post(
+            f"{space_url}/api/webhook/fail",
+            json={
+                "run_id": run_id,
+                "error": error_msg,
+                "event_type": "generate-audio",
+                "client_payload": {
+                    "data": {
+                        "prompt": prompt,
+                        "duration": duration,
+                        "seed": seed,
+                        "audio_type": AUDIO_TYPE,
+                        "negative_prompt": NEGATIVE_PROMPT,
+                        "file_url": file_url,
+                        "run_id": run_id,
+                        "space_url": space_url
+                    }
+                },
+                "github_run_id": github_run_id
+            },
+            timeout=15
+        )
+    except Exception as e:
+        print(f"Failed to report failure: {e}")
+
+try:
+    print('1. Connecting to Audio Space...')
+    client = Client("hkchengrex/MMAudio")
+    
+    if AUDIO_TYPE == 'video':
+        print('2. Downloading video for audio generation...')
+        req = requests.get(file_url, timeout=30)
+        ext = file_url.split('.')[-1] if '.' in file_url else 'mp4'
+        local_vid = f'input.{ext}'
+        with open(local_vid, 'wb') as f:
+            f.write(req.content)
+            
+        print('3. Processing Video-to-Audio...')
+        result = client.predict(
+            video=handle_file(local_vid),
+            prompt=prompt,
+            negative_prompt=NEGATIVE_PROMPT,
+            seed=seed,
+            num_steps=25,
+            cfg_strength=4.5,
+            duration=duration,
+            api_name="/video_to_audio"
+        )
+    else:
+        print('2. Processing Text-to-Audio...')
+        result = client.predict(
+            prompt=prompt,
+            negative_prompt=NEGATIVE_PROMPT,
+            seed=seed,
+            num_steps=25,
+            cfg_strength=4.5,
+            duration=duration,
+            api_name="/text_to_audio"
+        )
+        
+    print('4. Preparing File Data...')
+    audio_path = None
+    if isinstance(result, list) and len(result) > 0:
+        audio_path = result[0].get('video') or result[0].get('path') or result[0].get('url') if isinstance(result[0], dict) else result[0]
+    elif isinstance(result, tuple) and len(result) > 0:
+        audio_path = result[0]
+    elif isinstance(result, dict):
+        audio_path = result.get('video') or result.get('path') or result.get('url')
+    else:
+        audio_path = result
+        
+    ext = 'mp4'
+    if str(audio_path).endswith('.wav'): ext = 'wav'
+    if str(audio_path).endswith('.mp3'): ext = 'mp3'
+    
+    print('5. Uploading back to Space...')
+    with open(audio_path, 'rb') as f:
+        res = requests.post(
+            f'{space_url}/api/webhook/upload', 
+            data={'run_id': run_id, 'github_run_id': github_run_id, 'ext': ext}, 
+            files={'file': f}
+        )
+        
+    if res.status_code == 200:
+        print('SUCCESS!')
+    else:
+        sys.exit(1)
+        
+except Exception as e:
+    err_str = str(e)
+    print(f'Generation error: {err_str}')
+    report_failure(err_str)
+    sys.exit(1)
+        """
+    }
+    for name, content in scripts.items():
+        path = os.path.join("yml", name)
+        
+        # مانیتورینگ تگ شکست برای بازنویسی و اعمال ساختار پویا و دفاعی جدید روی تمام فایل‌های پایتون یمل
+        if os.path.exists(path):
+            try:
+                with open(path, "r", encoding="utf-8") as f:
+                    old_data = f.read()
+                if "report_failure" not in old_data:
+                    os.remove(path)
+            except:
+                pass
+                
+        if not os.path.exists(path):
+            with open(path, "w", encoding="utf-8") as f:
+                f.write(content.strip())
+
+# اجرای تابع برای نوشتن کدهای پایتون به محض بارگذاری برنامه
+write_default_scripts()
+
 def init_db():
     conn = sqlite3.connect(DB_PATH)
     c = conn.cursor()
@@ -204,7 +1048,7 @@ def is_today(created_at_str):
     except Exception:
         return False
 
-# تابع ارسال اکشن داینامیک به گیت‌هاب بر اساس فایل‌های درون پوشه yml
+# تابع ارسال اکشن داینامیک به گیت‌هاب بر اساس کدهای پوشه yml
 def dispatch_github_workflow(event_type, client_payload):
     acc = get_next_account()
     if not acc:
@@ -219,13 +1063,14 @@ def dispatch_github_workflow(event_type, client_payload):
     if os.path.exists(script_path):
         with open(script_path, "r", encoding="utf-8") as f:
             script_content = f.read()
-            
+
     # تزریق داینامیک متغیرهایی که در یمل گیت‌هاب قرار ندارند برای تولید صدا
     if event_type == "generate-audio":
-        audio_type = client_payload.get('audio_type', 'text')
-        negative_prompt = client_payload.get('negative_prompt', 'music')
-        script_content = script_content.replace("___AUDIO_TYPE___", audio_type)
-        script_content = script_content.replace("___NEGATIVE_PROMPT___", negative_prompt)
+        data_dict = client_payload.get("data", client_payload)
+        audio_type = data_dict.get('audio_type', 'text')
+        negative_prompt = data_dict.get('negative_prompt', 'music')
+        script_content = script_content.replace("___AUDIO_TYPE___", str(audio_type))
+        script_content = script_content.replace("___NEGATIVE_PROMPT___", str(negative_prompt))
     
     if "data" in client_payload:
         client_payload["data"]["script"] = script_content
@@ -359,7 +1204,7 @@ def cancel_delete_active_actions():
         "deleted_count": deleted_count
     })
 
-# وب‌هوک مدیریت دریافت خطا و اجرای تلاش مجدد تا سقف ۵ بار
+# وب‌هوک مدیریت دریافت خطا و اجرای تلاش مجدد تا سقف ۵ بار بدون قید و شرط کلمه کلیدی
 @app.route('/api/webhook/fail', methods=['POST'])
 def webhook_fail():
     data = request.get_json()
@@ -463,6 +1308,7 @@ def generate():
         return jsonify({"status": "error", "message": "متن ورودی شامل کلمات نامناسب است."}), 400
     
     try: 
+        # تغییر مبدا به auto جهت پایداری بالا در پردازش حروف ترکیبی فارسی-انگلیسی
         english_prompt = GoogleTranslator(source='auto', target='en').translate(persian_prompt)
         print(f"[GOOGLE TRANSLATE SUCCESS] Original: {persian_prompt} -> Translated: {english_prompt}")
     except Exception as e: 
@@ -740,14 +1586,16 @@ def generate_audio():
         file_url = f"{SPACE_URL}/static/images/{filename}"
 
     client_payload = {
-        "prompt": english_prompt,
-        "negative_prompt": english_negative,
-        "duration": duration,
-        "seed": seed,
-        "audio_type": audio_type,
-        "file_url": file_url,
-        "run_id": run_id,
-        "space_url": SPACE_URL
+        "data": {
+            "prompt": english_prompt,
+            "negative_prompt": english_negative,
+            "duration": duration,
+            "seed": seed,
+            "audio_type": audio_type,
+            "file_url": file_url,
+            "run_id": run_id,
+            "space_url": SPACE_URL
+        }
     }
     
     r = dispatch_github_workflow("generate-audio", client_payload)
@@ -796,6 +1644,7 @@ def worker_poll():
 
 # ==========================================
 
+
 # --- API میکس ویدیوها سمت سرور ---
 @app.route('/api/merge-videos', methods=['POST'])
 def merge_videos():
@@ -1056,6 +1905,7 @@ def use_edit_credit():
     conn.close()
     return jsonify({"status": "success", "credits_remaining": credits_remaining})
 
+
 # --- دریافت و ارسال فایل ---
 @app.route('/api/webhook/upload', methods=['POST'])
 def webhook_upload():