add new ui and options for demo

app.py

@@ -1,6 +1,4 @@
-
-#os.system("git clone https://github.com/R3gm/SoniTranslate")
-# pip install -r requirements.txt
+#%cd SoniTranslate
 import numpy as np
 import gradio as gr
 import whisperx
@@ -17,45 +15,41 @@ import os
 from soni_translate.audio_segments import create_translated_audio
 from soni_translate.text_to_speech import make_voice_gradio
 from soni_translate.translate_segments import translate_text
-#from soni_translate import test
 
 title = "<center><strong><font size='7'>📽️ SoniTranslate 🈷️</font></strong></center>"
 
 news = """ ## 📖 News
-        🔥 2023/07/01: Support  (Thanks for [text](https://github.com)).
-        """  
+        🔥 2023/07/26: new UI and mix options add.
+        """
+
+description = """ 
+### 🎥 **Translate videos easily with SoniTranslate!** 📽️
+
+Upload a video or provide a video link. Limitation: 10 seconds for CPU, but no restrictions with a GPU.
+
+For faster results and no duration limits, try the Colab notebook with a GPU:
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/R3gm/SoniTranslate/blob/main/SoniTranslate_Colab.ipynb)
+
+📽️ **This a demo of SoniTranslate; GitHub repository: [SoniTranslate](https://github.com/R3gm/SoniTranslate)!**
+
+See the tab labeled 'Help' for instructions on how to use it. Let's start having fun with video translation! 🚀🎉
+"""
 
-description = """ ## Translate the audio of a video content from one language to another while preserving synchronization.
 
 
-                This is a demo on Github project 📽️ [SoniTranslate](https://github.com/R3gm/SoniTranslate).
-                
-                📼 You can upload a video or provide a video link. The generation is **limited to 10 seconds** to prevent errors with the queue in cpu. If you use a GPU, you won't have any of these limitations.
-                
-                🚀 For **translate a video of any duration** and faster results, you can use the Colab notebook with GPU.   
+tutorial = """ 
+## 🔰 **Instructions for use:**
 
-                [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/R3gm/SoniTranslate/blob/main/SoniTranslate_Colab.ipynb)
-                 
-              """
+1. 📤 **Upload a video** on the first tab or 🌐 **use a video link** on the second tab.
 
-tutorial = """ # 🔰 Instructions for use.
-                
-                1. Upload a video on the first tab or use a video link on the second tab.
-                
-                2. Choose the language in which you want to translate the video.
-                
-                3. Specify the number of people speaking in the video and assign each one a text-to-speech voice suitable for the translation language.
-                
-                4. Press the 'Translate' button to obtain the results.
-                
-              """
+2. 🌍 Choose the language in which you want to **translate the video**.
 
+3. 🗣️ Specify the **number of people speaking** in the video and **assign each one a text-to-speech voice** suitable for the translation language.
+
+4. 🚀 Press the '**Translate**' button to obtain the results.
+"""
 
-if not os.path.exists('audio'):
-    os.makedirs('audio')
 
-if not os.path.exists('audio2/audio'):
-    os.makedirs('audio2/audio')
 
 # Check GPU
 if torch.cuda.is_available():
@@ -70,74 +64,151 @@ else:
     whisper_model_default = 'base'
 print('Working in: ', device)
 
+list_tts = ['af-ZA-AdriNeural-Female', 'af-ZA-WillemNeural-Male', 'am-ET-AmehaNeural-Male', 'am-ET-MekdesNeural-Female', 'ar-AE-FatimaNeural-Female', 'ar-AE-HamdanNeural-Male', 'ar-BH-AliNeural-Male', 'ar-BH-LailaNeural-Female', 'ar-DZ-AminaNeural-Female', 'ar-DZ-IsmaelNeural-Male', 'ar-EG-SalmaNeural-Female', 'ar-EG-ShakirNeural-Male', 'ar-IQ-BasselNeural-Male', 'ar-IQ-RanaNeural-Female', 'ar-JO-SanaNeural-Female', 'ar-JO-TaimNeural-Male', 'ar-KW-FahedNeural-Male', 'ar-KW-NouraNeural-Female', 'ar-LB-LaylaNeural-Female', 'ar-LB-RamiNeural-Male', 'ar-LY-ImanNeural-Female', 'ar-LY-OmarNeural-Male', 'ar-MA-JamalNeural-Male', 'ar-MA-MounaNeural-Female', 'ar-OM-AbdullahNeural-Male', 'ar-OM-AyshaNeural-Female', 'ar-QA-AmalNeural-Female', 'ar-QA-MoazNeural-Male', 'ar-SA-HamedNeural-Male', 'ar-SA-ZariyahNeural-Female', 'ar-SY-AmanyNeural-Female', 'ar-SY-LaithNeural-Male', 'ar-TN-HediNeural-Male', 'ar-TN-ReemNeural-Female', 'ar-YE-MaryamNeural-Female', 'ar-YE-SalehNeural-Male', 'az-AZ-BabekNeural-Male', 'az-AZ-BanuNeural-Female', 'bg-BG-BorislavNeural-Male', 'bg-BG-KalinaNeural-Female', 'bn-BD-NabanitaNeural-Female', 'bn-BD-PradeepNeural-Male', 'bn-IN-BashkarNeural-Male', 'bn-IN-TanishaaNeural-Female', 'bs-BA-GoranNeural-Male', 'bs-BA-VesnaNeural-Female', 'ca-ES-EnricNeural-Male', 'ca-ES-JoanaNeural-Female', 'cs-CZ-AntoninNeural-Male', 'cs-CZ-VlastaNeural-Female', 'cy-GB-AledNeural-Male', 'cy-GB-NiaNeural-Female', 'da-DK-ChristelNeural-Female', 'da-DK-JeppeNeural-Male', 'de-AT-IngridNeural-Female', 'de-AT-JonasNeural-Male', 'de-CH-JanNeural-Male', 'de-CH-LeniNeural-Female', 'de-DE-AmalaNeural-Female', 'de-DE-ConradNeural-Male', 'de-DE-KatjaNeural-Female', 'de-DE-KillianNeural-Male', 'el-GR-AthinaNeural-Female', 'el-GR-NestorasNeural-Male', 'en-AU-NatashaNeural-Female', 'en-AU-WilliamNeural-Male', 'en-CA-ClaraNeural-Female', 'en-CA-LiamNeural-Male', 'en-GB-LibbyNeural-Female', 'en-GB-MaisieNeural-Female', 'en-GB-RyanNeural-Male', 'en-GB-SoniaNeural-Female', 'en-GB-ThomasNeural-Male', 'en-HK-SamNeural-Male', 'en-HK-YanNeural-Female', 'en-IE-ConnorNeural-Male', 'en-IE-EmilyNeural-Female', 'en-IN-NeerjaExpressiveNeural-Female', 'en-IN-NeerjaNeural-Female', 'en-IN-PrabhatNeural-Male', 'en-KE-AsiliaNeural-Female', 'en-KE-ChilembaNeural-Male', 'en-NG-AbeoNeural-Male', 'en-NG-EzinneNeural-Female', 'en-NZ-MitchellNeural-Male', 'en-NZ-MollyNeural-Female', 'en-PH-JamesNeural-Male', 'en-PH-RosaNeural-Female', 'en-SG-LunaNeural-Female', 'en-SG-WayneNeural-Male', 'en-TZ-ElimuNeural-Male', 'en-TZ-ImaniNeural-Female', 'en-US-AnaNeural-Female', 'en-US-AriaNeural-Female', 'en-US-ChristopherNeural-Male', 'en-US-EricNeural-Male', 'en-US-GuyNeural-Male', 'en-US-JennyNeural-Female', 'en-US-MichelleNeural-Female', 'en-US-RogerNeural-Male', 'en-US-SteffanNeural-Male', 'en-ZA-LeahNeural-Female', 'en-ZA-LukeNeural-Male', 'es-AR-ElenaNeural-Female', 'es-AR-TomasNeural-Male', 'es-BO-MarceloNeural-Male', 'es-BO-SofiaNeural-Female', 'es-CL-CatalinaNeural-Female', 'es-CL-LorenzoNeural-Male', 'es-CO-GonzaloNeural-Male', 'es-CO-SalomeNeural-Female', 'es-CR-JuanNeural-Male', 'es-CR-MariaNeural-Female', 'es-CU-BelkysNeural-Female', 'es-CU-ManuelNeural-Male', 'es-DO-EmilioNeural-Male', 'es-DO-RamonaNeural-Female', 'es-EC-AndreaNeural-Female', 'es-EC-LuisNeural-Male', 'es-ES-AlvaroNeural-Male', 'es-ES-ElviraNeural-Female', 'es-GQ-JavierNeural-Male', 'es-GQ-TeresaNeural-Female', 'es-GT-AndresNeural-Male', 'es-GT-MartaNeural-Female', 'es-HN-CarlosNeural-Male', 'es-HN-KarlaNeural-Female', 'es-MX-DaliaNeural-Female', 'es-MX-JorgeNeural-Male', 'es-NI-FedericoNeural-Male', 'es-NI-YolandaNeural-Female', 'es-PA-MargaritaNeural-Female', 'es-PA-RobertoNeural-Male', 'es-PE-AlexNeural-Male', 'es-PE-CamilaNeural-Female', 'es-PR-KarinaNeural-Female', 'es-PR-VictorNeural-Male', 'es-PY-MarioNeural-Male', 'es-PY-TaniaNeural-Female', 'es-SV-LorenaNeural-Female', 'es-SV-RodrigoNeural-Male', 'es-US-AlonsoNeural-Male', 'es-US-PalomaNeural-Female', 'es-UY-MateoNeural-Male', 'es-UY-ValentinaNeural-Female', 'es-VE-PaolaNeural-Female', 'es-VE-SebastianNeural-Male', 'et-EE-AnuNeural-Female', 'et-EE-KertNeural-Male', 'fa-IR-DilaraNeural-Female', 'fa-IR-FaridNeural-Male', 'fi-FI-HarriNeural-Male', 'fi-FI-NooraNeural-Female', 'fil-PH-AngeloNeural-Male', 'fil-PH-BlessicaNeural-Female', 'fr-BE-CharlineNeural-Female', 'fr-BE-GerardNeural-Male', 'fr-CA-AntoineNeural-Male', 'fr-CA-JeanNeural-Male', 'fr-CA-SylvieNeural-Female', 'fr-CH-ArianeNeural-Female', 'fr-CH-FabriceNeural-Male', 'fr-FR-DeniseNeural-Female', 'fr-FR-EloiseNeural-Female', 'fr-FR-HenriNeural-Male', 'ga-IE-ColmNeural-Male', 'ga-IE-OrlaNeural-Female', 'gl-ES-RoiNeural-Male', 'gl-ES-SabelaNeural-Female', 'gu-IN-DhwaniNeural-Female', 'gu-IN-NiranjanNeural-Male', 'he-IL-AvriNeural-Male', 'he-IL-HilaNeural-Female', 'hi-IN-MadhurNeural-Male', 'hi-IN-SwaraNeural-Female', 'hr-HR-GabrijelaNeural-Female', 'hr-HR-SreckoNeural-Male', 'hu-HU-NoemiNeural-Female', 'hu-HU-TamasNeural-Male', 'id-ID-ArdiNeural-Male', 'id-ID-GadisNeural-Female', 'is-IS-GudrunNeural-Female', 'is-IS-GunnarNeural-Male', 'it-IT-DiegoNeural-Male', 'it-IT-ElsaNeural-Female', 'it-IT-IsabellaNeural-Female', 'ja-JP-KeitaNeural-Male', 'ja-JP-NanamiNeural-Female', 'jv-ID-DimasNeural-Male', 'jv-ID-SitiNeural-Female', 'ka-GE-EkaNeural-Female', 'ka-GE-GiorgiNeural-Male', 'kk-KZ-AigulNeural-Female', 'kk-KZ-DauletNeural-Male', 'km-KH-PisethNeural-Male', 'km-KH-SreymomNeural-Female', 'kn-IN-GaganNeural-Male', 'kn-IN-SapnaNeural-Female', 'ko-KR-InJoonNeural-Male', 'ko-KR-SunHiNeural-Female', 'lo-LA-ChanthavongNeural-Male', 'lo-LA-KeomanyNeural-Female', 'lt-LT-LeonasNeural-Male', 'lt-LT-OnaNeural-Female', 'lv-LV-EveritaNeural-Female', 'lv-LV-NilsNeural-Male', 'mk-MK-AleksandarNeural-Male', 'mk-MK-MarijaNeural-Female', 'ml-IN-MidhunNeural-Male', 'ml-IN-SobhanaNeural-Female', 'mn-MN-BataaNeural-Male', 'mn-MN-YesuiNeural-Female', 'mr-IN-AarohiNeural-Female', 'mr-IN-ManoharNeural-Male', 'ms-MY-OsmanNeural-Male', 'ms-MY-YasminNeural-Female', 'mt-MT-GraceNeural-Female', 'mt-MT-JosephNeural-Male', 'my-MM-NilarNeural-Female', 'my-MM-ThihaNeural-Male', 'nb-NO-FinnNeural-Male', 'nb-NO-PernilleNeural-Female', 'ne-NP-HemkalaNeural-Female', 'ne-NP-SagarNeural-Male', 'nl-BE-ArnaudNeural-Male', 'nl-BE-DenaNeural-Female', 'nl-NL-ColetteNeural-Female', 'nl-NL-FennaNeural-Female', 'nl-NL-MaartenNeural-Male', 'pl-PL-MarekNeural-Male', 'pl-PL-ZofiaNeural-Female', 'ps-AF-GulNawazNeural-Male', 'ps-AF-LatifaNeural-Female', 'pt-BR-AntonioNeural-Male', 'pt-BR-FranciscaNeural-Female', 'pt-PT-DuarteNeural-Male', 'pt-PT-RaquelNeural-Female', 'ro-RO-AlinaNeural-Female', 'ro-RO-EmilNeural-Male', 'ru-RU-DmitryNeural-Male', 'ru-RU-SvetlanaNeural-Female', 'si-LK-SameeraNeural-Male', 'si-LK-ThiliniNeural-Female', 'sk-SK-LukasNeural-Male', 'sk-SK-ViktoriaNeural-Female', 'sl-SI-PetraNeural-Female', 'sl-SI-RokNeural-Male', 'so-SO-MuuseNeural-Male', 'so-SO-UbaxNeural-Female', 'sq-AL-AnilaNeural-Female', 'sq-AL-IlirNeural-Male', 'sr-RS-NicholasNeural-Male', 'sr-RS-SophieNeural-Female', 'su-ID-JajangNeural-Male', 'su-ID-TutiNeural-Female', 'sv-SE-MattiasNeural-Male', 'sv-SE-SofieNeural-Female', 'sw-KE-RafikiNeural-Male', 'sw-KE-ZuriNeural-Female', 'sw-TZ-DaudiNeural-Male', 'sw-TZ-RehemaNeural-Female', 'ta-IN-PallaviNeural-Female', 'ta-IN-ValluvarNeural-Male', 'ta-LK-KumarNeural-Male', 'ta-LK-SaranyaNeural-Female', 'ta-MY-KaniNeural-Female', 'ta-MY-SuryaNeural-Male', 'ta-SG-AnbuNeural-Male', 'ta-SG-VenbaNeural-Female', 'te-IN-MohanNeural-Male', 'te-IN-ShrutiNeural-Female', 'th-TH-NiwatNeural-Male', 'th-TH-PremwadeeNeural-Female', 'tr-TR-AhmetNeural-Male', 'tr-TR-EmelNeural-Female', 'uk-UA-OstapNeural-Male', 'uk-UA-PolinaNeural-Female', 'ur-IN-GulNeural-Female', 'ur-IN-SalmanNeural-Male', 'ur-PK-AsadNeural-Male', 'ur-PK-UzmaNeural-Female', 'uz-UZ-MadinaNeural-Female', 'uz-UZ-SardorNeural-Male', 'vi-VN-HoaiMyNeural-Female', 'vi-VN-NamMinhNeural-Male', 'zh-CN-XiaoxiaoNeural-Female', 'zh-CN-XiaoyiNeural-Female', 'zh-CN-YunjianNeural-Male', 'zh-CN-YunxiNeural-Male', 'zh-CN-YunxiaNeural-Male', 'zh-CN-YunyangNeural-Male', 'zh-CN-liaoning-XiaobeiNeural-Female', 'zh-CN-shaanxi-XiaoniNeural-Female']
 
-# Download an audio
-#url = "https://www.youtube.com/watch?v=Rdi-SNhe2v4"
-
-### INIT
-list_tts = ['af-ZA-AdriNeural-Female', 'af-ZA-WillemNeural-Male', 'am-ET-AmehaNeural-Male', 'am-ET-MekdesNeural-Female', 'ar-AE-FatimaNeural-Female', 'ar-AE-HamdanNeural-Male', 'ar-BH-AliNeural-Male', 'ar-BH-LailaNeural-Female', 'ar-DZ-AminaNeural-Female', 'ar-DZ-IsmaelNeural-Male', 'ar-EG-SalmaNeural-Female', 'ar-EG-ShakirNeural-Male', 'ar-IQ-BasselNeural-Male', 'ar-IQ-RanaNeural-Female', 'ar-JO-SanaNeural-Female', 'ar-JO-TaimNeural-Male', 'ar-KW-FahedNeural-Male', 'ar-KW-NouraNeural-Female', 'ar-LB-LaylaNeural-Female', 'ar-LB-RamiNeural-Male', 'ar-LY-ImanNeural-Female', 'ar-LY-OmarNeural-Male', 'ar-MA-JamalNeural-Male', 'ar-MA-MounaNeural-Female', 'ar-OM-AbdullahNeural-Male', 'ar-OM-AyshaNeural-Female', 'ar-QA-AmalNeural-Female', 'ar-QA-MoazNeural-Male', 'ar-SA-HamedNeural-Male', 'ar-SA-ZariyahNeural-Female', 'ar-SY-AmanyNeural-Female', 'ar-SY-LaithNeural-Male', 'ar-TN-HediNeural-Male', 'ar-TN-ReemNeural-Female', 'ar-YE-MaryamNeural-Female', 'ar-YE-SalehNeural-Male', 'az-AZ-BabekNeural-Male', 'az-AZ-BanuNeural-Female', 'bg-BG-BorislavNeural-Male', 'bg-BG-KalinaNeural-Female', 'bn-BD-NabanitaNeural-Female', 'bn-BD-PradeepNeural-Male', 'bn-IN-BashkarNeural-Male', 'bn-IN-TanishaaNeural-Female', 'bs-BA-GoranNeural-Male', 'bs-BA-VesnaNeural-Female', 'ca-ES-EnricNeural-Male', 'ca-ES-JoanaNeural-Female', 'cs-CZ-AntoninNeural-Male', 'cs-CZ-VlastaNeural-Female', 'cy-GB-AledNeural-Male', 'cy-GB-NiaNeural-Female', 'da-DK-ChristelNeural-Female', 'da-DK-JeppeNeural-Male', 'de-AT-IngridNeural-Female', 'de-AT-JonasNeural-Male', 'de-CH-JanNeural-Male', 'de-CH-LeniNeural-Female', 'de-DE-AmalaNeural-Female', 'de-DE-ConradNeural-Male', 'de-DE-KatjaNeural-Female', 'de-DE-KillianNeural-Male', 'el-GR-AthinaNeural-Female', 'el-GR-NestorasNeural-Male', 'en-AU-NatashaNeural-Female', 'en-AU-WilliamNeural-Male', 'en-CA-ClaraNeural-Female', 'en-CA-LiamNeural-Male', 'en-GB-LibbyNeural-Female', 'en-GB-MaisieNeural-Female', 'en-GB-RyanNeural-Male', 'en-GB-SoniaNeural-Female', 'en-GB-ThomasNeural-Male', 'en-HK-SamNeural-Male', 'en-HK-YanNeural-Female', 'en-IE-ConnorNeural-Male', 'en-IE-EmilyNeural-Female', 'en-IN-NeerjaExpressiveNeural-Female', 'en-IN-NeerjaNeural-Female', 'en-IN-PrabhatNeural-Male', 'en-KE-AsiliaNeural-Female', 'en-KE-ChilembaNeural-Male', 'en-NG-AbeoNeural-Male', 'en-NG-EzinneNeural-Female', 'en-NZ-MitchellNeural-Male', 'en-NZ-MollyNeural-Female', 'en-PH-JamesNeural-Male', 'en-PH-RosaNeural-Female', 'en-SG-LunaNeural-Female', 'en-SG-WayneNeural-Male', 'en-TZ-ElimuNeural-Male', 'en-TZ-ImaniNeural-Female', 'en-US-AnaNeural-Female', 'en-US-AriaNeural-Female', 'en-US-ChristopherNeural-Male', 'en-US-EricNeural-Male', 'en-US-GuyNeural-Male', 'en-US-JennyNeural-Female', 'en-US-MichelleNeural-Female', 'en-US-RogerNeural-Male', 'en-US-SteffanNeural-Male', 'en-ZA-LeahNeural-Female', 'en-ZA-LukeNeural-Male', 'es-AR-ElenaNeural-Female', 'es-AR-TomasNeural-Male', 'es-BO-MarceloNeural-Male', 'es-BO-SofiaNeural-Female', 'es-CL-CatalinaNeural-Female', 'es-CL-LorenzoNeural-Male', 'es-CO-GonzaloNeural-Male', 'es-CO-SalomeNeural-Female', 'es-CR-JuanNeural-Male', 'es-CR-MariaNeural-Female', 'es-CU-BelkysNeural-Female', 'es-CU-ManuelNeural-Male', 'es-DO-EmilioNeural-Male', 'es-DO-RamonaNeural-Female', 'es-EC-AndreaNeural-Female', 'es-EC-LuisNeural-Male', 'es-ES-AlvaroNeural-Male', 'es-ES-ElviraNeural-Female', 'es-GQ-JavierNeural-Male', 'es-GQ-TeresaNeural-Female', 'es-GT-AndresNeural-Male', 'es-GT-MartaNeural-Female', 'es-HN-CarlosNeural-Male', 'es-HN-KarlaNeural-Female', 'es-MX-DaliaNeural-Female', 'es-MX-JorgeNeural-Male', 'es-NI-FedericoNeural-Male', 'es-NI-YolandaNeural-Female', 'es-PA-MargaritaNeural-Female', 'es-PA-RobertoNeural-Male', 'es-PE-AlexNeural-Male', 'es-PE-CamilaNeural-Female', 'es-PR-KarinaNeural-Female', 'es-PR-VictorNeural-Male', 'es-PY-MarioNeural-Male', 'es-PY-TaniaNeural-Female', 'es-SV-LorenaNeural-Female', 'es-SV-RodrigoNeural-Male', 'es-US-AlonsoNeural-Male', 'es-US-PalomaNeural-Female', 'es-UY-MateoNeural-Male', 'es-UY-ValentinaNeural-Female', 'es-VE-PaolaNeural-Female', 'es-VE-SebastianNeural-Male', 'et-EE-AnuNeural-Female', 'et-EE-KertNeural-Male', 'fa-IR-DilaraNeural-Female', 'fa-IR-FaridNeural-Male', 'fi-FI-HarriNeural-Male', 'fi-FI-NooraNeural-Female', 'fil-PH-AngeloNeural-Male', 'fil-PH-BlessicaNeural-Female', 'fr-BE-CharlineNeural-Female', 'fr-BE-GerardNeural-Male', 'fr-CA-AntoineNeural-Male', 'fr-CA-JeanNeural-Male', 'fr-CA-SylvieNeural-Female', 'fr-CH-ArianeNeural-Female', 'fr-CH-FabriceNeural-Male', 'fr-FR-DeniseNeural-Female', 'fr-FR-EloiseNeural-Female', 'fr-FR-HenriNeural-Male', 'ga-IE-ColmNeural-Male', 'ga-IE-OrlaNeural-Female', 'gl-ES-RoiNeural-Male', 'gl-ES-SabelaNeural-Female', 'gu-IN-DhwaniNeural-Female', 'gu-IN-NiranjanNeural-Male', 'he-IL-AvriNeural-Male', 'he-IL-HilaNeural-Female', 'hi-IN-MadhurNeural-Male', 'hi-IN-SwaraNeural-Female', 'hr-HR-GabrijelaNeural-Female', 'hr-HR-SreckoNeural-Male', 'hu-HU-NoemiNeural-Female', 'hu-HU-TamasNeural-Male', 'id-ID-ArdiNeural-Male', 'id-ID-GadisNeural-Female', 'is-IS-GudrunNeural-Female', 'is-IS-GunnarNeural-Male', 'it-IT-DiegoNeural-Male', 'it-IT-ElsaNeural-Female', 'it-IT-IsabellaNeural-Female', 'ja-JP-KeitaNeural-Male', 'ja-JP-NanamiNeural-Female', 'jv-ID-DimasNeural-Male', 'jv-ID-SitiNeural-Female', 'ka-GE-EkaNeural-Female', 'ka-GE-GiorgiNeural-Male', 'kk-KZ-AigulNeural-Female', 'kk-KZ-DauletNeural-Male', 'km-KH-PisethNeural-Male', 'km-KH-SreymomNeural-Female', 'kn-IN-GaganNeural-Male', 'kn-IN-SapnaNeural-Female', 'ko-KR-InJoonNeural-Male', 'ko-KR-SunHiNeural-Female', 'lo-LA-ChanthavongNeural-Male', 'lo-LA-KeomanyNeural-Female', 'lt-LT-LeonasNeural-Male', 'lt-LT-OnaNeural-Female', 'lv-LV-EveritaNeural-Female', 'lv-LV-NilsNeural-Male', 'mk-MK-AleksandarNeural-Male', 'mk-MK-MarijaNeural-Female', 'ml-IN-MidhunNeural-Male', 'ml-IN-SobhanaNeural-Female', 'mn-MN-BataaNeural-Male', 'mn-MN-YesuiNeural-Female', 'mr-IN-AarohiNeural-Female', 'mr-IN-ManoharNeural-Male', 'ms-MY-OsmanNeural-Male', 'ms-MY-YasminNeural-Female', 'mt-MT-GraceNeural-Female', 'mt-MT-JosephNeural-Male', 'my-MM-NilarNeural-Female', 'my-MM-ThihaNeural-Male', 'nb-NO-FinnNeural-Male', 'nb-NO-PernilleNeural-Female', 'ne-NP-HemkalaNeural-Female', 'ne-NP-SagarNeural-Male', 'nl-BE-ArnaudNeural-Male', 'nl-BE-DenaNeural-Female', 'nl-NL-ColetteNeural-Female', 'nl-NL-FennaNeural-Female', 'nl-NL-MaartenNeural-Male', 'pl-PL-MarekNeural-Male', 'pl-PL-ZofiaNeural-Female', 'ps-AF-GulNawazNeural-Male', 'ps-AF-LatifaNeural-Female', 'pt-BR-AntonioNeural-Male', 'pt-BR-FranciscaNeural-Female', 'pt-PT-DuarteNeural-Male', 'pt-PT-RaquelNeural-Female', 'ro-RO-AlinaNeural-Female', 'ro-RO-EmilNeural-Male', 'ru-RU-DmitryNeural-Male', 'ru-RU-SvetlanaNeural-Female', 'si-LK-SameeraNeural-Male', 'si-LK-ThiliniNeural-Female', 'sk-SK-LukasNeural-Male', 'sk-SK-ViktoriaNeural-Female', 'sl-SI-PetraNeural-Female', 'sl-SI-RokNeural-Male', 'so-SO-MuuseNeural-Male', 'so-SO-UbaxNeural-Female', 'sq-AL-AnilaNeural-Female', 'sq-AL-IlirNeural-Male', 'sr-RS-NicholasNeural-Male', 'sr-RS-SophieNeural-Female', 'su-ID-JajangNeural-Male', 'su-ID-TutiNeural-Female', 'sv-SE-MattiasNeural-Male', 'sv-SE-SofieNeural-Female', 'sw-KE-RafikiNeural-Male', 'sw-KE-ZuriNeural-Female', 'sw-TZ-DaudiNeural-Male', 'sw-TZ-RehemaNeural-Female', 'ta-IN-PallaviNeural-Female', 'ta-IN-ValluvarNeural-Male', 'ta-LK-KumarNeural-Male', 'ta-LK-SaranyaNeural-Female', 'ta-MY-KaniNeural-Female', 'ta-MY-SuryaNeural-Male', 'ta-SG-AnbuNeural-Male', 'ta-SG-VenbaNeural-Female', 'te-IN-MohanNeural-Male', 'te-IN-ShrutiNeural-Female', 'th-TH-NiwatNeural-Male', 'th-TH-PremwadeeNeural-Female', 'tr-TR-AhmetNeural-Male', 'tr-TR-EmelNeural-Female', 'uk-UA-OstapNeural-Male', 'uk-UA-PolinaNeural-Female', 'ur-IN-GulNeural-Female', 'ur-IN-SalmanNeural-Male', 'ur-PK-AsadNeural-Male', 'ur-PK-UzmaNeural-Female', 'uz-UZ-MadinaNeural-Female', 'uz-UZ-SardorNeural-Male', 'vi-VN-HoaiMyNeural-Female', 'vi-VN-NamMinhNeural-Male', 'zh-CN-XiaoxiaoNeural-Female', 'zh-CN-XiaoyiNeural-Female', 'zh-CN-YunjianNeural-Male', 'zh-CN-YunxiNeural-Male', 'zh-CN-YunxiaNeural-Male', 'zh-CN-YunyangNeural-Male', 'zh-CN-liaoning-XiaobeiNeural-Female', 'zh-CN-shaanxi-XiaoniNeural-Female'] 
-
-
-def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type, 
+'''
+def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
                          TRANSLATE_AUDIO_TO, min_speakers, max_speakers,
                          tts_voice00, tts_voice01,tts_voice02,tts_voice03,tts_voice04,tts_voice05):
 
     YOUR_HF_TOKEN = os.getenv("My_hf_token")
 
-                             
+    create_translated_audio(result_diarize, audio_files, Output_name_file)
+
+    os.system("rm audio_dub_stereo.wav")
+    os.system("ffmpeg -i audio_dub_solo.wav -ac 1 audio_dub_stereo.wav")
+
+    os.system(f"rm {mix_audio}")
+    os.system(f'ffmpeg -y -i audio.wav -i audio_dub_stereo.wav -filter_complex "[0:0]volume=0.15[a];[1:0]volume=1.90[b];[a][b]amix=inputs=2:duration=longest" -c:a libmp3lame {mix_audio}')
+
+    os.system(f"rm {video_output}")
+    os.system(f"ffmpeg -i {OutputFile} -i {mix_audio} -c:v copy -c:a copy -map 0:v -map 1:a -shortest {video_output}")
+
+    return video_output
+'''
+
+def translate_from_video(
+    video,
+    YOUR_HF_TOKEN,
+    preview=False,
+    WHISPER_MODEL_SIZE="large-v1",
+    batch_size=16,
+    compute_type="float16",
+    SOURCE_LANGUAGE= "Automatic detection",
+    TRANSLATE_AUDIO_TO="English (en)",
+    min_speakers=1,
+    max_speakers=2,
+    tts_voice00="en-AU-WilliamNeural-Male",
+    tts_voice01="en-CA-ClaraNeural-Female",
+    tts_voice02="en-GB-ThomasNeural-Male",
+    tts_voice03="en-GB-SoniaNeural-Female",
+    tts_voice04="en-NZ-MitchellNeural-Male",
+    tts_voice05="en-GB-MaisieNeural-Female",
+    video_output="video_dub.mp4",
+    AUDIO_MIX_METHOD='Adjusting volumes and mixing audio',
+    ):
+
+    if YOUR_HF_TOKEN == "" or YOUR_HF_TOKEN == None:
+      YOUR_HF_TOKEN = os.getenv("YOUR_HF_TOKEN")
+      if YOUR_HF_TOKEN == None:
+        print('No valid token')
+        return 
+
+    if "SET_LIMIT" == os.getenv("DEMO"):
+      preview=True
+      print("DEMO; set preview=True; The generation is **limited to 10 seconds** to prevent errors with the CPU. If you use a GPU, you won't have any of these limitations.")
+      AUDIO_MIX_METHOD='Adjusting volumes and mixing audio'
+      print("DEMO; set Adjusting volumes and mixing audio")
+
+    LANGUAGES = {
+        'Automatic detection': 'Automatic detection',
+        'English (en)': 'en',
+        'French (fr)': 'fr',
+        'German (de)': 'de',
+        'Spanish (es)': 'es',
+        'Italian (it)': 'it',
+        'Japanese (ja)': 'ja',
+        'Chinese (zh)': 'zh',
+        'Dutch (nl)': 'nl',
+        'Ukrainian (uk)': 'uk',
+        'Portuguese (pt)': 'pt'
+    }
+
+    TRANSLATE_AUDIO_TO = LANGUAGES[TRANSLATE_AUDIO_TO]
+    SOURCE_LANGUAGE = LANGUAGES[SOURCE_LANGUAGE]
+
+
+    if not os.path.exists('audio'):
+        os.makedirs('audio')
+
+    if not os.path.exists('audio2/audio'):
+        os.makedirs('audio2/audio')
+
+    # Check GPU
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    compute_type = "float32" if device == "cpu" else compute_type
+
     OutputFile = 'Video.mp4'
     audio_wav = "audio.wav"
-    Output_name_file = "audio_dub_solo.wav"
+    Output_name_file = "audio_dub_solo.ogg"
     mix_audio = "audio_mix.mp3"
-    video_output = "diar_output.mp4"
-                             
-    os.system(f"rm {Output_name_file}")
+
     os.system("rm Video.mp4")
-    #os.system("rm diar_output.mp4")
+    os.system("rm audio.webm")
     os.system("rm audio.wav")
-                            
 
     if os.path.exists(video):
-        print(f"### Start Video ###")  
-        if device == 'cpu':
-            # max 1 minute in cpu
-            print('10 s. Limited for CPU ')
+        if preview:
+            print('Creating a preview video of 10 seconds, to disable this option, go to advanced settings and turn off preview.')
             os.system(f'ffmpeg -y -i "{video}" -ss 00:00:20 -t 00:00:10 -c:v libx264 -c:a aac -strict experimental Video.mp4')
         else:
             os.system(f'ffmpeg -y -i "{video}" -c:v libx264 -c:a aac -strict experimental Video.mp4')
-        
+
         os.system("ffmpeg -y -i Video.mp4 -vn -acodec pcm_s16le -ar 44100 -ac 2 audio.wav")
     else:
-        print(f"### Start {video} ###")  
-        if device == 'cpu':
-            # max 1 minute in cpu
-            print('10 s. Limited for CPU ')
+        if preview:
+            print('Creating a preview from the link, 10 seconds to disable this option, go to advanced settings and turn off preview.')
             #https://github.com/yt-dlp/yt-dlp/issues/2220
             mp4_ = f'yt-dlp -f "mp4" --downloader ffmpeg --downloader-args "ffmpeg_i: -ss 00:00:20 -t 00:00:10" --force-overwrites --max-downloads 1 --no-warnings --no-abort-on-error --ignore-no-formats-error --restrict-filenames -o {OutputFile} {video}'
-            wav_ = "ffmpeg -y -i Video.mp4 -vn -acodec pcm_s16le -ar 44100 -ac 1 audio.wav"
+            wav_ = "ffmpeg -y -i Video.mp4 -vn -acodec pcm_s16le -ar 44100 -ac 2 audio.wav"
+            os.system(mp4_)
+            os.system(wav_)
         else:
             mp4_ = f'yt-dlp -f "mp4" --force-overwrites --max-downloads 1 --no-warnings --no-abort-on-error --ignore-no-formats-error --restrict-filenames -o {OutputFile} {video}'
             wav_ = f'python -m yt_dlp --output {audio_wav} --force-overwrites --max-downloads 1 --no-warnings --no-abort-on-error --ignore-no-formats-error --extract-audio --audio-format wav {video}'
-            
-        os.system(mp4_)
-        os.system(wav_)
+
+            os.system(wav_)
+
+            for i in range (120):
+                time.sleep(1)
+                print('process audio...')
+                if os.path.exists(audio_wav) and not os.path.exists('audio.webm'):
+                    time.sleep(1)
+                    os.system(mp4_)
+                    break
+                if i == 119:
+                  print('Error donwloading the audio')
+                  return
 
     print("Set file complete.")
-        
+
+    SOURCE_LANGUAGE = None if SOURCE_LANGUAGE == 'Automatic detection' else SOURCE_LANGUAGE
+
     # 1. Transcribe with original whisper (batched)
     model = whisperx.load_model(
         WHISPER_MODEL_SIZE,
         device,
-        compute_type=compute_type
+        compute_type=compute_type,
+        language= SOURCE_LANGUAGE,
         )
     audio = whisperx.load_audio(audio_wav)
     result = model.transcribe(audio, batch_size=batch_size)
     gc.collect(); torch.cuda.empty_cache(); del model
     print("Transcript complete")
-                             
+
     # 2. Align whisper output
     model_a, metadata = whisperx.load_align_model(
-        language_code=result["language"], 
+        language_code=result["language"],
         device=device
         )
     result = whisperx.align(
@@ -150,7 +221,11 @@ def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
         )
     gc.collect(); torch.cuda.empty_cache(); del model_a
     print("Align complete")
-                             
+
+    if result['segments'] == []:
+      print('No active speech found in audio')
+      return
+
     # 3. Assign speaker labels
     diarize_model = whisperx.DiarizationPipeline(use_auth_token=YOUR_HF_TOKEN, device=device)
     diarize_segments = diarize_model(
@@ -160,10 +235,10 @@ def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
     result_diarize = whisperx.assign_word_speakers(diarize_segments, result)
     gc.collect(); torch.cuda.empty_cache(); del diarize_model
     print("Diarize complete")
-                             
+
     result_diarize['segments'] = translate_text(result_diarize['segments'], TRANSLATE_AUDIO_TO)
     print("Translation complete")
-    
+
     audio_files = []
 
     # Mapping speakers to voice variables
@@ -176,7 +251,7 @@ def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
         'SPEAKER_05': tts_voice05
     }
 
-    for segment in result_diarize['segments']:
+    for segment in tqdm(result_diarize['segments']):
 
         text = segment['text']
         start = segment['start']
@@ -193,7 +268,7 @@ def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
         filename = f"audio/{start}.ogg"
 
         if speaker in speaker_to_voice and speaker_to_voice[speaker] != 'None':
-            make_voice_gradio(text, speaker_to_voice[speaker], filename)
+            make_voice_gradio(text, speaker_to_voice[speaker], filename, TRANSLATE_AUDIO_TO)
         elif speaker == "SPEAKER_99":
             try:
                 tts = gTTS(text, lang=TRANSLATE_AUDIO_TO)
@@ -202,7 +277,7 @@ def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
             except:
                 tts = gTTS('a', lang=TRANSLATE_AUDIO_TO)
                 tts.save(filename)
-                print('ERROR AUDIO GTTS')
+                print('Error: Audio will be replaced.')
 
         # duration
         duration_true = end - start
@@ -212,7 +287,7 @@ def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
         porcentaje = duration_tts / duration_true
 
         if porcentaje > 2.1:
-            porcentaje = 2.1  
+            porcentaje = 2.1
         elif porcentaje <= 1.2 and porcentaje >= 0.8:
             porcentaje = 1.0
         elif porcentaje <= 0.79:
@@ -231,25 +306,26 @@ def translate_from_video(video, WHISPER_MODEL_SIZE, batch_size, compute_type,
     os.system("mv -f audio2/audio/*.ogg audio/")
 
     os.system(f"rm {Output_name_file}")
-
     create_translated_audio(result_diarize, audio_files, Output_name_file)
 
-    os.system("rm audio_dub_stereo.wav")                        
-    os.system("ffmpeg -i audio_dub_solo.wav -ac 1 audio_dub_stereo.wav")
-                             
-    #os.system(f"ffmpeg -i Video.mp4 -i {Output_name_file} -c:v copy -c:a copy -map 0:v -map 1:a -shortest {video_output}")
-
     os.system(f"rm {mix_audio}")
-    #os.system(f'''ffmpeg -i {audio_wav} -i audio_dub_stereo.wav -filter_complex "[1:a]asplit=2[sc][mix];[0:a][sc]sidechaincompress=threshold=0.003:ratio=20[bg]; [bg][mix]amerge[final]" -map [final] {mix_audio}''')
-    #os.system(f'ffmpeg -y -i {audio_wav} -i audio_dub_stereo.wav -filter_complex "[0:0][1:0] amix=inputs=2:duration=longest" -c:a libmp3lame {mix_audio}')
-    os.system(f'ffmpeg -y -i audio.wav -i audio_dub_stereo.wav -filter_complex "[0:0]volume=0.15[a];[1:0]volume=1.90[b];[a][b]amix=inputs=2:duration=longest" -c:a libmp3lame {mix_audio}')
-                             
+
+    # TYPE MIX AUDIO
+    if AUDIO_MIX_METHOD == 'Adjusting volumes and mixing audio':
+        # volume mix
+        os.system(f'ffmpeg -y -i {audio_wav} -i {Output_name_file} -filter_complex "[0:0]volume=0.15[a];[1:0]volume=1.90[b];[a][b]amix=inputs=2:duration=longest" -c:a libmp3lame {mix_audio}')
+    else:
+        try:
+            # background mix
+            os.system(f'ffmpeg -i {audio_wav} -i {Output_name_file} -filter_complex "[1:a]asplit=2[sc][mix];[0:a][sc]sidechaincompress=threshold=0.003:ratio=20[bg]; [bg][mix]amerge[final]" -map [final] {mix_audio}')
+        except:
+            # volume mix except
+            os.system(f'ffmpeg -y -i {audio_wav} -i {Output_name_file} -filter_complex "[0:0]volume=0.15[a];[1:0]volume=1.90[b];[a][b]amix=inputs=2:duration=longest" -c:a libmp3lame {mix_audio}')
+
     os.system(f"rm {video_output}")
     os.system(f"ffmpeg -i {OutputFile} -i {mix_audio} -c:v copy -c:a copy -map 0:v -map 1:a -shortest {video_output}")
-        
-    return video_output
-
 
+    return video_output
 
 import sys
 
@@ -276,52 +352,79 @@ def read_logs():
     with open("output.log", "r") as f:
         return f.read()
 
+# max tts
+MAX_TTS = 6
 
-with gr.Blocks() as demo:
+theme='Taithrah/Minimal'
+
+with gr.Blocks(theme=theme) as demo:
     gr.Markdown(title)
     gr.Markdown(description)
-    gr.Markdown(tutorial)
 
+#### video
     with gr.Tab("Translate audio from video"):
         with gr.Row():
             with gr.Column():
                 video_input = gr.Video() # height=300,width=300
-                
-                gr.Markdown("Select the target language, and make sure to select the language corresponding to the speakers of the target language to avoid errors in the process.")  
-                TRANSLATE_AUDIO_TO = gr.inputs.Dropdown(['en', 'fr', 'de', 'es', 'it', 'ja', 'zh', 'nl', 'uk', 'pt'], default='en',label = 'Translate audio to')
-    
+                SOURCE_LANGUAGE = gr.Dropdown(['Automatic detection', 'English (en)', 'French (fr)', 'German (de)', 'Spanish (es)', 'Italian (it)', 'Japanese (ja)', 'Chinese (zh)', 'Dutch (nl)', 'Ukrainian (uk)', 'Portuguese (pt)'], value='Automatic detection',label = 'Source language', info="This is the original language of the video")
+                TRANSLATE_AUDIO_TO = gr.Dropdown(['English (en)', 'French (fr)', 'German (de)', 'Spanish (es)', 'Italian (it)', 'Japanese (ja)', 'Chinese (zh)', 'Dutch (nl)', 'Ukrainian (uk)', 'Portuguese (pt)'], value='English (en)',label = 'Translate audio to', info="Select the target language, and make sure to select the language corresponding to the speakers of the target language to avoid errors in the process.")
+
+                line_ = gr.HTML("<hr></h2>")
                 gr.Markdown("Select how many people are speaking in the video.")
-                min_speakers = gr.inputs.Slider(1, 6, default=1, label="min_speakers", step=1)
-                max_speakers = gr.inputs.Slider(1, 6, default=2, label="max_speakers",step=1) 
-                  
+                min_speakers = gr.Slider(1, MAX_TTS, default=1, label="min_speakers", step=1, visible=False)
+                max_speakers = gr.Slider(1, MAX_TTS, value=2, step=1, label="Max speakers", interative=True)
                 gr.Markdown("Select the voice you want for each speaker.")
-                tts_voice00 = gr.inputs.Dropdown(list_tts, default='en-AU-WilliamNeural-Male', label = 'TTS Speaker 1')
-                tts_voice01 = gr.inputs.Dropdown(list_tts, default='en-CA-ClaraNeural-Female', label = 'TTS Speaker 2')
-                tts_voice02 = gr.inputs.Dropdown(list_tts, default='en-GB-ThomasNeural-Male', label = 'TTS Speaker 3')
-                tts_voice03 = gr.inputs.Dropdown(list_tts, default='en-GB-SoniaNeural-Female', label = 'TTS Speaker 4')
-                tts_voice04 = gr.inputs.Dropdown(list_tts, default='en-NZ-MitchellNeural-Male', label = 'TTS Speaker 5')
-                tts_voice05 = gr.inputs.Dropdown(list_tts, default='en-GB-MaisieNeural-Female', label = 'TTS Speaker 6')
-    
-                gr.Markdown("Default configuration of Whisper.")
-                WHISPER_MODEL_SIZE = gr.inputs.Dropdown(['tiny', 'base', 'small', 'medium', 'large-v1', 'large-v2'], default=whisper_model_default, label="Whisper model")
-                batch_size = gr.inputs.Slider(1, 32, default=16, label="Batch size", step=1)
-                compute_type = gr.inputs.Dropdown(list_compute_type, default=compute_type_default, label="Compute type")  
-        
-            with gr.Column(variant='compact'): 
+                def submit(value):
+                    visibility_dict = {
+                        f'tts_voice{i:02d}': gr.update(visible=i < value) for i in range(6)
+                    }
+                    return [value for value in visibility_dict.values()]
+                tts_voice00 = gr.Dropdown(list_tts, value='en-AU-WilliamNeural-Male', label = 'TTS Speaker 1', visible=True, interactive= True)
+                tts_voice01 = gr.Dropdown(list_tts, value='en-CA-ClaraNeural-Female', label = 'TTS Speaker 2', visible=True, interactive= True)
+                tts_voice02 = gr.Dropdown(list_tts, value='en-GB-ThomasNeural-Male', label = 'TTS Speaker 3', visible=False, interactive= True)
+                tts_voice03 = gr.Dropdown(list_tts, value='en-GB-SoniaNeural-Female', label = 'TTS Speaker 4', visible=False, interactive= True)
+                tts_voice04 = gr.Dropdown(list_tts, value='en-NZ-MitchellNeural-Male', label = 'TTS Speaker 5', visible=False, interactive= True)
+                tts_voice05 = gr.Dropdown(list_tts, value='en-GB-MaisieNeural-Female', label = 'TTS Speaker 6', visible=False, interactive= True)
+                max_speakers.change(submit, max_speakers, [tts_voice00, tts_voice01, tts_voice02, tts_voice03, tts_voice04, tts_voice05])
+
+                with gr.Column():
+                      with gr.Accordion("Advanced Settings", open=False):
+                        
+                          AUDIO_MIX = gr.Dropdown(['Mixing audio with sidechain compression', 'Adjusting volumes and mixing audio'], value='Adjusting volumes and mixing audio', label = 'Audio Mixing Method', info="Mix original and translated audio files to create a customized, balanced output with two available mixing modes.")
+                          
+                          gr.HTML("<hr></h2>")
+                          gr.Markdown("Default configuration of Whisper.")
+                          WHISPER_MODEL_SIZE = gr.inputs.Dropdown(['tiny', 'base', 'small', 'medium', 'large-v1', 'large-v2'], default=whisper_model_default, label="Whisper model")
+                          batch_size = gr.inputs.Slider(1, 32, default=16, label="Batch size", step=1)
+                          compute_type = gr.inputs.Dropdown(list_compute_type, default=compute_type_default, label="Compute type")
+                          
+                          gr.HTML("<hr></h2>")
+                          VIDEO_OUTPUT_NAME = gr.Textbox(label="Translated file name" ,value="video_output.mp4", info="The name of the output file")
+                          PREVIEW = gr.Checkbox(label="Preview", info="Preview cuts the video to only 10 seconds for testing purposes. Please deactivate it to retrieve the full video duration.")
+
+            with gr.Column(variant='compact'):
                 with gr.Row():
                     video_button = gr.Button("TRANSLATE", )
                 with gr.Row():
                     video_output = gr.Video()
 
+                line_ = gr.HTML("<hr></h2>")
+                if os.getenv("YOUR_HF_TOKEN") == None or os.getenv("YOUR_HF_TOKEN") == "":
+                  HFKEY = gr.Textbox(visible= True, label="HF Token", info="One important step is to accept the license agreement for using Pyannote. You need to have an account on Hugging Face and accept the license to use the models: https://huggingface.co/pyannote/speaker-diarization and https://huggingface.co/pyannote/segmentation. Get your KEY TOKEN here: https://hf.co/settings/tokens", placeholder="Token goes here...")
+                else:
+                  HFKEY = gr.Textbox(visible= False, label="HF Token", info="One important step is to accept the license agreement for using Pyannote. You need to have an account on Hugging Face and accept the license to use the models: https://huggingface.co/pyannote/speaker-diarization and https://huggingface.co/pyannote/segmentation. Get your KEY TOKEN here: https://hf.co/settings/tokens", placeholder="Token goes here...")
 
                 gr.Examples(
                     examples=[
                         [
-                            "./assets/Video_subtitled.mp4",
+                            "./assets/Video_main.mp4",
+                            "",
+                            True,
                             "base",
                             16,
                             "float32",
-                            "en",
+                            "Spanish (es)",
+                            "English (en)",
                             1,
                             2,
                             'en-AU-WilliamNeural-Male',
@@ -330,15 +433,20 @@ with gr.Blocks() as demo:
                             'en-GB-SoniaNeural-Female',
                             'en-NZ-MitchellNeural-Male',
                             'en-GB-MaisieNeural-Female',
+                            "video_output.mp4",
+                            'Adjusting volumes and mixing audio',
                         ],
                     ],
                     fn=translate_from_video,
                     inputs=[
                     video_input,
-                    WHISPER_MODEL_SIZE, 
+                    HFKEY,
+                    PREVIEW,
+                    WHISPER_MODEL_SIZE,
                     batch_size,
-                    compute_type, 
-                    TRANSLATE_AUDIO_TO, 
+                    compute_type,
+                    SOURCE_LANGUAGE,
+                    TRANSLATE_AUDIO_TO,
                     min_speakers,
                     max_speakers,
                     tts_voice00,
@@ -347,58 +455,119 @@ with gr.Blocks() as demo:
                     tts_voice03,
                     tts_voice04,
                     tts_voice05,
+                    VIDEO_OUTPUT_NAME,
+                    AUDIO_MIX,
                     ],
                     outputs=[video_output],
-                    cache_examples=True,
+                    cache_examples=False,
                 )
 
+### link
 
     with gr.Tab("Translate audio from video link"):
         with gr.Row():
             with gr.Column():
-                
-                link_input = gr.Textbox(label="Media link. Example: www.youtube.com/watch?v=g_9rPvbENUw", placeholder="URL goes here...")
-                #filename = gr.Textbox(label="File name", placeholder="best-vid")
-                
-                gr.Markdown("Select the target language, and make sure to select the language corresponding to the speakers of the target language to avoid errors in the process.")
-                bTRANSLATE_AUDIO_TO = gr.inputs.Dropdown(['en', 'fr', 'de', 'es', 'it', 'ja', 'zh', 'nl', 'uk', 'pt'], default='en',label = 'Translate audio to')
-        
+
+                blink_input = gr.Textbox(label="Media link.", info="Example: www.youtube.com/watch?v=g_9rPvbENUw", placeholder="URL goes here...")
+                # bSOURCE_LANGUAGE = gr.Dropdown(['Automatic detection', 'en', 'fr', 'de', 'es', 'it', 'ja', 'zh', 'nl', 'uk', 'pt'], value='en',label = 'Source language')
+
+                # gr.HTML("<hr></h2>")
+
+                # bHFKEY = gr.Textbox(label="HF Token", info="One important step is to accept the license agreement for using Pyannote. You need to have an account on Hugging Face and accept the license to use the models: https://huggingface.co/pyannote/speaker-diarization and https://huggingface.co/pyannote/segmentation. Get your KEY TOKEN here: https://hf.co/settings/tokens", placeholder="Token goes here...")
+
+                # gr.Markdown("Select the target language, and make sure to select the language corresponding to the speakers of the target language to avoid errors in the process.")
+                # bTRANSLATE_AUDIO_TO = gr.inputs.Dropdown(['en', 'fr', 'de', 'es', 'it', 'ja', 'zh', 'nl', 'uk', 'pt'], default='en',label = 'Translate audio to')
+
+                # gr.Markdown("Select how many people are speaking in the video.")
+                # bmin_speakers = gr.inputs.Slider(1, 6, default=1, label="min_speakers", step=1, )
+                # bmax_speakers = gr.inputs.Slider(1, 6, default=2, label="max_speakers",step=1)
+
+                # gr.Markdown("Select the voice you want for each speaker.")
+                # btts_voice00 = gr.inputs.Dropdown(list_tts, default='en-AU-WilliamNeural-Male', label = 'TTS Speaker 1')
+                # btts_voice01 = gr.inputs.Dropdown(list_tts, default='en-CA-ClaraNeural-Female', label = 'TTS Speaker 2')
+                # btts_voice02 = gr.inputs.Dropdown(list_tts, default='en-GB-ThomasNeural-Male', label = 'TTS Speaker 3')
+                # btts_voice03 = gr.inputs.Dropdown(list_tts, default='en-GB-SoniaNeural-Female', label = 'TTS Speaker 4')
+                # btts_voice04 = gr.inputs.Dropdown(list_tts, default='en-NZ-MitchellNeural-Male', label = 'TTS Speaker 5')
+                # btts_voice05 = gr.inputs.Dropdown(list_tts, default='en-GB-MaisieNeural-Female', label = 'TTS Speaker 6')
+
+                # with gr.Column():
+                #       with gr.Accordion("Advanced Settings", open=False):
+                #           gr.Markdown("Default configuration of Whisper.")
+                #           bWHISPER_MODEL_SIZE = gr.inputs.Dropdown(['tiny', 'base', 'small', 'medium', 'large-v1', 'large-v2'], default=whisper_model_default, label="Whisper model")
+                #           bbatch_size = gr.inputs.Slider(1, 32, default=16, label="Batch size", step=1)
+                #           bcompute_type = gr.inputs.Dropdown(list_compute_type, default=compute_type_default, label="Compute type")
+
+                #           bPREVIEW = gr.inputs.Checkbox(label="Preview cuts the video to only 10 seconds for testing purposes. Please deactivate it to retrieve the full video duration.")
+                #           bVIDEO_OUTPUT_NAME = gr.Textbox(label="Translated file name" ,value="video_output.mp4")
+
+                bSOURCE_LANGUAGE = gr.Dropdown(['Automatic detection', 'English (en)', 'French (fr)', 'German (de)', 'Spanish (es)', 'Italian (it)', 'Japanese (ja)', 'Chinese (zh)', 'Dutch (nl)', 'Ukrainian (uk)', 'Portuguese (pt)'], value='Automatic detection',label = 'Source language', info="This is the original language of the video")
+                bTRANSLATE_AUDIO_TO = gr.Dropdown(['English (en)', 'French (fr)', 'German (de)', 'Spanish (es)', 'Italian (it)', 'Japanese (ja)', 'Chinese (zh)', 'Dutch (nl)', 'Ukrainian (uk)', 'Portuguese (pt)'], value='English (en)',label = 'Translate audio to', info="Select the target language, and make sure to select the language corresponding to the speakers of the target language to avoid errors in the process.")
+
+                bline_ = gr.HTML("<hr></h2>")
                 gr.Markdown("Select how many people are speaking in the video.")
-                bmin_speakers = gr.inputs.Slider(1, 6, default=1, label="min_speakers", step=1)
-                bmax_speakers = gr.inputs.Slider(1, 6, default=2, label="max_speakers",step=1) 
-                  
+                bmin_speakers = gr.Slider(1, MAX_TTS, default=1, label="min_speakers", step=1, visible=False)
+                bmax_speakers = gr.Slider(1, MAX_TTS, value=2, step=1, label="Max speakers", interative=True)
                 gr.Markdown("Select the voice you want for each speaker.")
-                btts_voice00 = gr.inputs.Dropdown(list_tts, default='en-AU-WilliamNeural-Male', label = 'TTS Speaker 1')
-                btts_voice01 = gr.inputs.Dropdown(list_tts, default='en-CA-ClaraNeural-Female', label = 'TTS Speaker 2')
-                btts_voice02 = gr.inputs.Dropdown(list_tts, default='en-GB-ThomasNeural-Male', label = 'TTS Speaker 3')
-                btts_voice03 = gr.inputs.Dropdown(list_tts, default='en-GB-SoniaNeural-Female', label = 'TTS Speaker 4')
-                btts_voice04 = gr.inputs.Dropdown(list_tts, default='en-NZ-MitchellNeural-Male', label = 'TTS Speaker 5')
-                btts_voice05 = gr.inputs.Dropdown(list_tts, default='en-GB-MaisieNeural-Female', label = 'TTS Speaker 6')
-        
-                gr.Markdown("Default configuration of Whisper.")
-                bWHISPER_MODEL_SIZE = gr.inputs.Dropdown(['tiny', 'base', 'small', 'medium', 'large-v1', 'large-v2'], default=whisper_model_default, label="Whisper model")
-                bbatch_size = gr.inputs.Slider(1, 32, default=16, label="Batch size", step=1)
-                bcompute_type = gr.inputs.Dropdown(list_compute_type, default=compute_type_default, label="Compute type")
-                
+                def bsubmit(value):
+                    visibility_dict = {
+                        f'btts_voice{i:02d}': gr.update(visible=i < value) for i in range(6)
+                    }
+                    return [value for value in visibility_dict.values()]
+                btts_voice00 = gr.Dropdown(list_tts, value='en-AU-WilliamNeural-Male', label = 'TTS Speaker 1', visible=True, interactive= True)
+                btts_voice01 = gr.Dropdown(list_tts, value='en-CA-ClaraNeural-Female', label = 'TTS Speaker 2', visible=True, interactive= True)
+                btts_voice02 = gr.Dropdown(list_tts, value='en-GB-ThomasNeural-Male', label = 'TTS Speaker 3', visible=False, interactive= True)
+                btts_voice03 = gr.Dropdown(list_tts, value='en-GB-SoniaNeural-Female', label = 'TTS Speaker 4', visible=False, interactive= True)
+                btts_voice04 = gr.Dropdown(list_tts, value='en-NZ-MitchellNeural-Male', label = 'TTS Speaker 5', visible=False, interactive= True)
+                btts_voice05 = gr.Dropdown(list_tts, value='en-GB-MaisieNeural-Female', label = 'TTS Speaker 6', visible=False, interactive= True)
+                bmax_speakers.change(bsubmit, bmax_speakers, [btts_voice00, btts_voice01, btts_voice02, btts_voice03, btts_voice04, btts_voice05])
+
+
+                with gr.Column():
+                      with gr.Accordion("Advanced Settings", open=False):
+                          
+                          bAUDIO_MIX = gr.Dropdown(['Mixing audio with sidechain compression', 'Adjusting volumes and mixing audio'], value='Adjusting volumes and mixing audio', label = 'Audio Mixing Method', info="Mix original and translated audio files to create a customized, balanced output with two available mixing modes.")
+
+                          gr.HTML("<hr></h2>")
+                          gr.Markdown("Default configuration of Whisper.")
+                          bWHISPER_MODEL_SIZE = gr.inputs.Dropdown(['tiny', 'base', 'small', 'medium', 'large-v1', 'large-v2'], default=whisper_model_default, label="Whisper model")
+                          bbatch_size = gr.inputs.Slider(1, 32, default=16, label="Batch size", step=1)
+                          bcompute_type = gr.inputs.Dropdown(list_compute_type, default=compute_type_default, label="Compute type")
+
+                          gr.HTML("<hr></h2>")
+                          bVIDEO_OUTPUT_NAME = gr.Textbox(label="Translated file name" ,value="video_output.mp4", info="The name of the output file")
+                          bPREVIEW = gr.Checkbox(label="Preview", info="Preview cuts the video to only 10 seconds for testing purposes. Please deactivate it to retrieve the full video duration.")
+
+
+
                 # text_button = gr.Button("Translate audio of video")
                 # link_output = gr.Video() #gr.outputs.File(label="Download!")
 
 
 
-            with gr.Column(variant='compact'): 
+            with gr.Column(variant='compact'):
                 with gr.Row():
                     text_button = gr.Button("TRANSLATE")
                 with gr.Row():
-                    link_output = gr.Video() #gr.outputs.File(label="Download!") # gr.Video()
+                    blink_output = gr.Video() #gr.outputs.File(label="Download!") # gr.Video()
+
+
+                bline_ = gr.HTML("<hr></h2>")
+                if os.getenv("YOUR_HF_TOKEN") == None or os.getenv("YOUR_HF_TOKEN") == "":
+                  bHFKEY = gr.Textbox(visible= True, label="HF Token", info="One important step is to accept the license agreement for using Pyannote. You need to have an account on Hugging Face and accept the license to use the models: https://huggingface.co/pyannote/speaker-diarization and https://huggingface.co/pyannote/segmentation. Get your KEY TOKEN here: https://hf.co/settings/tokens", placeholder="Token goes here...")
+                else:
+                  bHFKEY = gr.Textbox(visible= False, label="HF Token", info="One important step is to accept the license agreement for using Pyannote. You need to have an account on Hugging Face and accept the license to use the models: https://huggingface.co/pyannote/speaker-diarization and https://huggingface.co/pyannote/segmentation. Get your KEY TOKEN here: https://hf.co/settings/tokens", placeholder="Token goes here...")
 
                 gr.Examples(
                     examples=[
                         [
                             "https://www.youtube.com/watch?v=5ZeHtRKHl7Y",
+                            "",
+                            True,
                             "base",
                             16,
                             "float32",
-                            "en",
+                            "Japanese (ja)",
+                            "English (en)",
                             1,
                             2,
                             'en-CA-ClaraNeural-Female',
@@ -407,15 +576,20 @@ with gr.Blocks() as demo:
                             'en-GB-SoniaNeural-Female',
                             'en-NZ-MitchellNeural-Male',
                             'en-GB-MaisieNeural-Female',
+                            "video_output.mp4",
+                            'Adjusting volumes and mixing audio',
                         ],
                     ],
                     fn=translate_from_video,
                     inputs=[
-                    link_input,
-                    bWHISPER_MODEL_SIZE, 
+                    blink_input,
+                    bHFKEY,
+                    bPREVIEW,
+                    bWHISPER_MODEL_SIZE,
                     bbatch_size,
-                    bcompute_type, 
-                    bTRANSLATE_AUDIO_TO, 
+                    bcompute_type,
+                    bSOURCE_LANGUAGE,
+                    bTRANSLATE_AUDIO_TO,
                     bmin_speakers,
                     bmax_speakers,
                     btts_voice00,
@@ -424,24 +598,34 @@ with gr.Blocks() as demo:
                     btts_voice03,
                     btts_voice04,
                     btts_voice05,
+                    bVIDEO_OUTPUT_NAME,
+                    bAUDIO_MIX
                     ],
-                    outputs=[link_output],
-                    cache_examples=True,
+                    outputs=[blink_output],
+                    cache_examples=False,
                 )
 
 
-    
-    with gr.Accordion("Logs"):
+
+
+    with gr.Tab("Help"):
+        gr.Markdown(news)
+        gr.Markdown(tutorial)
+
+    with gr.Accordion("Logs", open = False):
         logs = gr.Textbox()
         demo.load(read_logs, None, logs, every=1)
 
     # run
     video_button.click(translate_from_video, inputs=[
-        video_input, 
-        WHISPER_MODEL_SIZE, 
+        video_input,
+        HFKEY,
+        PREVIEW,
+        WHISPER_MODEL_SIZE,
         batch_size,
-        compute_type, 
-        TRANSLATE_AUDIO_TO, 
+        compute_type,
+        SOURCE_LANGUAGE,
+        TRANSLATE_AUDIO_TO,
         min_speakers,
         max_speakers,
         tts_voice00,
@@ -449,13 +633,19 @@ with gr.Blocks() as demo:
         tts_voice02,
         tts_voice03,
         tts_voice04,
-        tts_voice05,], outputs=video_output)
+        tts_voice05,
+        VIDEO_OUTPUT_NAME,
+        AUDIO_MIX,
+        ], outputs=video_output)
     text_button.click(translate_from_video, inputs=[
-        link_input,
-        bWHISPER_MODEL_SIZE, 
+        blink_input,
+        bHFKEY,
+        bPREVIEW,
+        bWHISPER_MODEL_SIZE,
         bbatch_size,
-        bcompute_type, 
-        bTRANSLATE_AUDIO_TO, 
+        bcompute_type,
+        bSOURCE_LANGUAGE,
+        bTRANSLATE_AUDIO_TO,
         bmin_speakers,
         bmax_speakers,
         btts_voice00,
@@ -463,11 +653,10 @@ with gr.Blocks() as demo:
         btts_voice02,
         btts_voice03,
         btts_voice04,
-        btts_voice05,], outputs=link_output)
-
+        btts_voice05,
+        bVIDEO_OUTPUT_NAME,
+        bAUDIO_MIX,
+        ], outputs=blink_output)
 
 demo.launch(enable_queue=True)
-
-
-
-
+#demo.launch()