Update app.py

app.py

@@ -1,6 +1,55 @@
 import gradio as gr
 from datetime import datetime
 import random
+from transformers import pipeline
+from transformers.pipelines.audio_utils import ffmpeg_read
+
+# Initialize the Whisper pipeline
+whisper_pipeline = pipeline("automatic-speech-recognition", model="openai/whisper-medium")
+
+def transcribe_audio_from_file(file_path):
+    """
+    Transcribes audio from a local file using the Whisper pipeline.
+
+    Args:
+        file_path (str): Path to the local media file.
+
+    Returns:
+        str: Transcription text if successful, otherwise None.
+    """
+    try:
+        # Transcribe the audio using Whisper
+        transcription = whisper_pipeline(file_path, return_timestamps=True)
+        logger.debug(f"Transcription: {transcription['text']}")
+        return transcription["text"]
+    except Exception as e:
+        logger.error(f"An error occurred during transcription: {e}")
+        return None
+
+# Initialize the translation pipeline
+translation_pipeline = pipeline("translation", model="Helsinki-NLP/opus-mt-en-{target_language}")
+
+def translate_text(text, target_language):
+    """
+    Translates the given text into the specified target language.
+
+    Args:
+        text (str): The text to translate.
+        target_language (str): The target language code (e.g., 'es' for Spanish, 'fr' for French).
+
+    Returns:
+        str: Translated text if successful, otherwise None.
+    """
+    try:
+        # Instantiate the pipeline for the target language dynamically
+        translator = pipeline("translation", model=f"Helsinki-NLP/opus-mt-en-{target_language}")
+        translation = translator(text, max_length=1000)
+        translated_text = translation[0]["translation_text"]
+        logger.debug(f"Translation to {target_language}: {translated_text}")
+        return translated_text
+    except Exception as e:
+        logger.error(f"An error occurred during translation: {e}")
+        return None
 
 # Mock functions for platform actions and analytics
 def mock_post_to_platform(platform, content_title):
@@ -17,9 +66,11 @@ def upload_and_manage(file, platform, language):
     if file is None:
         return "Please upload a video/audio file.", None, None, None
 
-    # Mock transcription and translation process
-    transcription = "This is a sample transcription of the uploaded content."
-    translation = f"[{language}] This is a sample translation of the content."
+    # Transcribe audio from uploaded media file
+    transcription = transcribe_audio_from_media_file(file.name)
+
+    # Translate transcription to the selected language
+    translation = translate_text(transcription, language)
 
     # Mock posting action
     post_message = mock_post_to_platform(platform, file.name)
@@ -48,7 +99,7 @@ def build_interface():
             with gr.Row():
                 file_input = gr.File(label="Upload Video/Audio File")
                 platform_input = gr.Dropdown(["YouTube", "Instagram"], label="Select Platform")
-                language_input = gr.Dropdown(["English", "Spanish", "French", "Chinese"], label="Select Language")
+                language_input = gr.Dropdown(["en", "es", "fr", "zh"], label="Select Language")  # Language codes
             
             submit_button = gr.Button("Post and Process")