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import torch
import yt_dlp
import os
import subprocess
import json
from transformers import AutoTokenizer, AutoModelForCausalLM
import moviepy.editor as mp
import langdetect
import uuid
import time
import random
import tempfile
import shutil
import traceback
import sys
# --- CONFIGURACIÓN INICIAL CON DEBUGGING ---
print("🔧 DEBUGGING MODE ACTIVATED")
print("🐍 Python version:", sys.version)
print("📦 Starting intensive debugging version...")
# Verificar dependencias críticas
dependencies_status = {}
try:
import curl_cffi
dependencies_status['curl_cffi'] = f"✅ Available (v{curl_cffi.__version__})"
CURL_CFFI_AVAILABLE = True
except ImportError as e:
dependencies_status['curl_cffi'] = f"❌ Not available: {str(e)}"
CURL_CFFI_AVAILABLE = False
try:
import yt_dlp
dependencies_status['yt_dlp'] = f"✅ Available (v{yt_dlp.__version__})"
except Exception as e:
dependencies_status['yt_dlp'] = f"❌ Error: {str(e)}"
# Verificar impersonation targets
try:
with yt_dlp.YoutubeDL() as ydl:
# Test para ver qué targets están disponibles
print("🧪 Testing impersonation targets...")
test_result = subprocess.run(['yt-dlp', '--list-impersonate-targets'],
capture_output=True, text=True, timeout=10)
if test_result.returncode == 0:
targets = test_result.stdout
dependencies_status['impersonation'] = f"✅ Available targets:\n{targets[:200]}..."
else:
dependencies_status['impersonation'] = f"❌ Command failed: {test_result.stderr}"
except Exception as e:
dependencies_status['impersonation'] = f"❌ Test failed: {str(e)}"
print("\n📊 DEPENDENCY STATUS:")
for dep, status in dependencies_status.items():
print(f" {dep}: {status}")
# Carga del modelo
model_path = "Qwen/Qwen2.5-7B-Instruct"
print(f"\n🤖 Loading model {model_path}...")
try:
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.float16, trust_remote_code=True)
model = model.eval()
print("✅ Model loaded successfully")
dependencies_status['model'] = "✅ Loaded"
except Exception as e:
print(f"❌ Model loading failed: {e}")
dependencies_status['model'] = f"❌ Failed: {str(e)}"
model = None
tokenizer = None
# --- FUNCIONES DE DEBUGGING ---
def debug_log(message, level="INFO"):
"""Log con timestamp"""
timestamp = time.strftime("%H:%M:%S")
print(f"[{timestamp}] {level}: {message}")
def test_yt_dlp_basic():
"""Test básico de yt-dlp"""
debug_log("Testing basic yt-dlp functionality...")
try:
# Test con video público conocido
test_url = "https://www.youtube.com/watch?v=dQw4w9WgXcQ" # Rick Roll - siempre funciona
ydl_opts = {'quiet': True, 'no_warnings': True}
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
info = ydl.extract_info(test_url, download=False)
if info:
debug_log("✅ Basic yt-dlp test PASSED")
return True
else:
debug_log("❌ Basic yt-dlp test FAILED - no info returned")
return False
except Exception as e:
debug_log(f"❌ Basic yt-dlp test FAILED: {str(e)}", "ERROR")
return False
def test_vimeo_access():
"""Test específico de acceso a Vimeo"""
debug_log("Testing Vimeo access...")
try:
# Video público de test de Vimeo
test_url = "https://vimeo.com/34741214"
ydl_opts = {
'quiet': True,
'no_warnings': True,
'socket_timeout': 15
}
# Test 1: Sin impersonation
debug_log("Test 1: Basic Vimeo access (no impersonation)")
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
info = ydl.extract_info(test_url, download=False)
if info:
debug_log("✅ Basic Vimeo access: SUCCESS")
return "basic_success"
except Exception as e:
debug_log(f"❌ Basic Vimeo access failed: {str(e)}", "ERROR")
# Test 2: Con impersonation si está disponible
if CURL_CFFI_AVAILABLE:
try:
debug_log("Test 2: Vimeo with chrome120 impersonation")
ydl_opts['impersonate'] = 'chrome120'
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
info = ydl.extract_info(test_url, download=False)
if info:
debug_log("✅ Vimeo with impersonation: SUCCESS")
return "impersonation_success"
except Exception as e2:
debug_log(f"❌ Vimeo with impersonation failed: {str(e2)}", "ERROR")
return f"failed: {str(e)}"
# Ejecutar tests al inicio
basic_test_result = test_yt_dlp_basic()
vimeo_test_result = test_vimeo_access()
dependencies_status['basic_test'] = "✅ Passed" if basic_test_result else "❌ Failed"
dependencies_status['vimeo_test'] = vimeo_test_result
# --- FUNCIONES AUXILIARES ---
def generate_unique_filename(extension):
return f"{uuid.uuid4()}{extension}"
def cleanup_files(*files):
for file in files:
if file and os.path.exists(file):
try:
os.remove(file)
debug_log(f"Cleaned up: {file}")
except OSError as e:
debug_log(f"Cleanup error: {file} - {e}", "ERROR")
def clean_url(url):
"""Limpiar URL como en código exitoso"""
cleaned = url.split('?')[0] if '?' in url else url
debug_log(f"URL cleaned: {url} → {cleaned}")
return cleaned
# --- FUNCIÓN PRINCIPAL CON DEBUGGING INTENSIVO ---
def download_video_debug(url):
"""
Función con debugging intensivo para identificar exactamente dónde falla
"""
debug_log(f"🎯 STARTING DEBUG DOWNLOAD", "INFO")
debug_log(f"Original URL: {url}")
# Limpiar URL
clean_url_value = clean_url(url)
debug_log(f"Cleaned URL: {clean_url_value}")
# Crear directorio temporal
with tempfile.TemporaryDirectory() as temp_dir:
debug_log(f"Temp directory: {temp_dir}")
temp_filename = generate_unique_filename("")
debug_log(f"Temp filename base: {temp_filename}")
# Lista de métodos a probar
methods = [
{
'name': 'Chrome120 Impersonation',
'opts': {
'format': 'bestaudio/best',
'outtmpl': os.path.join(temp_dir, f'{temp_filename}_method1.%(ext)s'),
'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'wav', 'preferredquality': '64'}],
'quiet': True, 'no_warnings': True, 'retries': 1, 'socket_timeout': 30,
'impersonate': 'chrome120',
'postprocessor_args': ['-ar', '16000', '-ac', '1']
}
},
{
'name': 'Chrome Generic',
'opts': {
'format': 'bestaudio/best',
'outtmpl': os.path.join(temp_dir, f'{temp_filename}_method2.%(ext)s'),
'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'wav'}],
'quiet': True, 'no_warnings': True, 'retries': 1, 'socket_timeout': 30,
'impersonate': 'chrome'
}
},
{
'name': 'No Impersonation',
'opts': {
'format': 'bestaudio/best',
'outtmpl': os.path.join(temp_dir, f'{temp_filename}_method3.%(ext)s'),
'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'wav'}],
'quiet': True, 'no_warnings': True, 'retries': 1, 'socket_timeout': 45
}
},
{
'name': 'Basic Fallback',
'opts': {
'format': 'best',
'outtmpl': os.path.join(temp_dir, f'{temp_filename}_method4.%(ext)s'),
'quiet': False, 'no_warnings': False, 'retries': 1, 'socket_timeout': 60
}
}
]
# Probar cada método
for i, method in enumerate(methods):
method_name = method['name']
ydl_opts = method['opts']
debug_log(f"\n🔄 METHOD {i+1}: {method_name}")
debug_log(f"Options: {json.dumps(ydl_opts, indent=2)}")
try:
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
# Paso 1: Extraer información
debug_log("Step 1: Extracting video info...")
try:
info_dict = ydl.extract_info(clean_url_value, download=False)
if not info_dict:
raise Exception("No info_dict returned")
video_title = info_dict.get('title', 'Unknown')
duration = info_dict.get('duration')
uploader = info_dict.get('uploader', 'Unknown')
debug_log(f"✅ Info extracted successfully:")
debug_log(f" Title: {video_title}")
debug_log(f" Duration: {duration} seconds")
debug_log(f" Uploader: {uploader}")
# Verificar duración
if duration and duration > 1800: # 30 minutos
raise Exception(f"Video too long: {duration}s > 1800s")
except Exception as extract_error:
debug_log(f"❌ Info extraction failed: {str(extract_error)}", "ERROR")
debug_log(f"Full traceback: {traceback.format_exc()}", "ERROR")
continue
# Paso 2: Descargar
debug_log("Step 2: Downloading audio...")
try:
ydl.download([clean_url_value])
debug_log("✅ Download command completed")
except Exception as download_error:
debug_log(f"❌ Download failed: {str(download_error)}", "ERROR")
debug_log(f"Full traceback: {traceback.format_exc()}", "ERROR")
continue
# Paso 3: Verificar archivos descargados
debug_log("Step 3: Checking downloaded files...")
files_found = []
for filename in os.listdir(temp_dir):
file_path = os.path.join(temp_dir, filename)
file_size = os.path.getsize(file_path)
files_found.append((filename, file_size))
debug_log(f" Found: {filename} ({file_size} bytes)")
# Buscar archivo de audio válido
for filename, file_size in files_found:
if filename.endswith(('.wav', '.mp3', '.m4a', '.webm')) and file_size >= 1024:
source_path = os.path.join(temp_dir, filename)
final_path = generate_unique_filename(".wav")
shutil.copy2(source_path, final_path)
debug_log(f"✅ SUCCESS with {method_name}!")
debug_log(f" Final file: {final_path} ({file_size} bytes)")
return final_path, f"Success with {method_name}"
debug_log(f"❌ No valid audio file found from {method_name}", "ERROR")
except Exception as method_error:
debug_log(f"❌ Method {method_name} failed completely: {str(method_error)}", "ERROR")
debug_log(f"Full traceback: {traceback.format_exc()}", "ERROR")
continue
# Si llegamos aquí, todos los métodos fallaron
debug_log("❌ ALL METHODS FAILED", "ERROR")
raise Exception("All download methods failed. Check debug logs for details.")
def transcribe_audio_debug(file_path):
"""Transcripción con debugging"""
debug_log(f"🎤 Starting transcription: {file_path}")
try:
if not os.path.exists(file_path):
raise FileNotFoundError(f"Audio file not found: {file_path}")
file_size = os.path.getsize(file_path)
debug_log(f"Audio file size: {file_size} bytes")
if file_size < 1000:
raise Exception("Audio file too small")
# Usar whisper directamente para debugging
output_file = generate_unique_filename(".json")
command = [
"insanely-fast-whisper",
"--file-name", file_path,
"--device-id", "cpu",
"--model-name", "openai/whisper-large-v3",
"--task", "transcribe",
"--timestamp", "chunk",
"--transcript-path", output_file,
"--batch-size", "1",
]
debug_log(f"Whisper command: {' '.join(command)}")
result = subprocess.run(
command,
check=True,
capture_output=True,
text=True,
timeout=300
)
debug_log(f"Whisper stdout: {result.stdout}")
if result.stderr:
debug_log(f"Whisper stderr: {result.stderr}")
# Leer resultado
with open(output_file, "r", encoding='utf-8') as f:
transcription_data = json.load(f)
result_text = transcription_data.get("text", "").strip()
cleanup_files(output_file)
debug_log(f"Transcription completed: {len(result_text)} characters")
return result_text
except Exception as e:
debug_log(f"Transcription error: {str(e)}", "ERROR")
debug_log(f"Full traceback: {traceback.format_exc()}", "ERROR")
raise
def generate_summary_debug(transcription):
"""Resumen con debugging"""
if not transcription or len(transcription.strip()) < 20:
return "⚠️ Transcription too short"
if not model:
return "⚠️ Model not available"
try:
detected_language = langdetect.detect(transcription)
debug_log(f"Detected language: {detected_language}")
except:
detected_language = "en"
text = transcription[:8000]
prompt = f"Summarize this in {detected_language} (150-250 words): {text}"
try:
response, _ = model.chat(tokenizer, prompt, history=[])
return response
except Exception as e:
debug_log(f"Summary error: {str(e)}", "ERROR")
return f"Summary error: {str(e)}"
# --- FUNCIONES DE INTERFAZ CON DEBUGGING ---
def process_video_debug(url):
"""Función principal con debugging completo"""
if not url or not url.strip():
return "❌ No URL provided", "❌ No URL"
url = url.strip()
debug_log(f"\n{'='*60}")
debug_log(f"🎯 PROCESSING VIDEO WITH FULL DEBUGGING")
debug_log(f"URL: {url}")
debug_log(f"Dependencies: {json.dumps(dependencies_status, indent=2)}")
debug_log(f"{'='*60}")
audio_file = None
try:
# Download con debugging
audio_file, download_method = download_video_debug(url)
debug_log(f"Download successful with: {download_method}")
# Transcription con debugging
transcription = transcribe_audio_debug(audio_file)
success_msg = f"✅ Success with {download_method} ({len(transcription)} chars)"
debug_log(f"FINAL SUCCESS: {success_msg}")
return transcription, success_msg
except Exception as e:
error_msg = str(e)
debug_log(f"FINAL ERROR: {error_msg}", "ERROR")
debug_log(f"Full traceback: {traceback.format_exc()}", "ERROR")
# Error detallado
detailed_error = f"""❌ DETAILED ERROR REPORT:
Primary Error: {error_msg}
System Status:
{json.dumps(dependencies_status, indent=2)}
Debug Info:
- curl-cffi: {dependencies_status.get('curl_cffi', 'Unknown')}
- Basic test: {dependencies_status.get('basic_test', 'Unknown')}
- Vimeo test: {dependencies_status.get('vimeo_test', 'Unknown')}
Check console logs for full debugging information."""
return detailed_error, f"❌ Error: {error_msg[:50]}..."
finally:
if audio_file and os.path.exists(audio_file):
cleanup_files(audio_file)
# --- INTERFAZ GRADIO CON DEBUGGING ---
with gr.Blocks(theme=gr.themes.Soft(), title="🔧 Debug Mode") as demo:
gr.Markdown("# 🔧 DEBUG MODE - Intensive Diagnostics")
# Status de dependencias
status_md = "## 📊 System Status\n"
for dep, status in dependencies_status.items():
status_md += f"- **{dep}**: {status}\n"
gr.Markdown(status_md)
with gr.Row():
url_input = gr.Textbox(
label="Video URL for Debug",
placeholder="https://vimeo.com/34741214 (test video)",
info="Try with this test URL first"
)
url_button = gr.Button("🔧 Debug Process", variant="primary")
with gr.Row():
transcription_output = gr.Textbox(
label="📝 Transcription / Debug Output",
lines=20,
interactive=True
)
summary_output = gr.Textbox(
label="📊 Summary",
lines=10
)
status_output = gr.Textbox(
label="🔍 Debug Status",
interactive=False,
lines=3
)
summary_button = gr.Button("📝 Generate Summary", variant="secondary")
gr.Markdown("""
## 🔍 Debug Instructions
1. **Try the test URL first**: `https://vimeo.com/34741214`
2. **Check console logs** in your browser (F12 → Console)
3. **Report any errors** with the full debug output
This version will tell us **exactly** where and why it's failing.
""")
# Event handlers
url_button.click(
fn=process_video_debug,
inputs=[url_input],
outputs=[transcription_output, status_output]
)
summary_button.click(
fn=generate_summary_debug,
inputs=[transcription_output],
outputs=[summary_output]
)
debug_log("🎨 Gradio interface ready in DEBUG MODE")
demo.launch(server_name="0.0.0.0", server_port=7860, show_error=True) |