Delete main.py

main.py

@@ -1,222 +0,0 @@
-# import zipfile
-# import os
-# import tempfile
-# import whisper
-
-# # Specify the input PPTX file and output ZIP file names
-# file = '/Users/tushargupta/Downloads/Lecture 1_Definition and conceptualization.pptx'  # Replace with your PPTX file path
-# file = os.path.splitext(file)[0] + '.zip'
-
-# # Create dictionary to store audio files
-# audio_files = {}
-
-# # Create temporary directory for extraction
-# temp_dir = tempfile.mkdtemp()
-
-# # Extract the zip file to temp directory
-# with zipfile.ZipFile(file, 'r') as zip_ref:
-#     zip_ref.extractall(temp_dir)
-
-# # Path to media folder
-# media_path = os.path.join(temp_dir, 'ppt', 'media')
-
-# # Check if media folder exists
-# if os.path.exists(media_path):
-#     # Create temporary directory for converted files
-#     temp_audio_dir = tempfile.mkdtemp()
-    
-#     # Iterate through slide numbers
-#     slide_num = 1
-#     while True:
-#         # Check for either .mp4 or .m4a file for current slide
-#         media_file = None
-#         for ext in ['.mp4', '.m4a']:
-#             filename = f'media{slide_num}{ext}'
-#             file_path = os.path.join(media_path, filename)
-#             if os.path.exists(file_path):
-#                 media_file = file_path
-#                 break
-                
-#         if not media_file:
-#             break
-            
-#         # Create temporary mp3 file
-#         temp_mp3 = os.path.join(temp_audio_dir, f'temp_{slide_num}.mp3')
-        
-#         try:
-#             # Convert to mp3 using ffmpeg
-#             os.system(f'ffmpeg -i "{media_file}" -vn -acodec libmp3lame "{temp_mp3}" -loglevel quiet')
-#             # Store the temp mp3 file path in dictionary
-#             audio_files[slide_num-1] = temp_mp3
-#         except Exception as e:
-#             print(f"Error converting slide {slide_num}: {str(e)}")
-            
-#         slide_num += 1
-
-# # Load Whisper model
-# model = whisper.load_model("base")
-
-# # Dictionary to store transcriptions by slide number
-# slide_transcripts = {}
-
-# # Transcribe each audio file
-# for slide_num, audio_file in audio_files.items():
-#     # Transcribe the audio file
-#     result = model.transcribe(audio_file)
-#     # Store transcription text for this slide
-#     slide_transcripts[slide_num + 1] = result["text"]
-   
-
-# # Display transcription per slide
-# print("\nTranscription by Slide:")
-# for slide_num, text in sorted(slide_transcripts.items()):
-#     print(f"\nSlide {slide_num}:")
-#     print(text)
-
-import streamlit as st
-import zipfile
-import os
-import tempfile
-import whisper
-from pathlib import Path
-
-def process_pptx(uploaded_file):
-    # Create temporary file to save the uploaded file
-    with tempfile.NamedTemporaryFile(delete=False, suffix='.pptx') as tmp_pptx:
-        tmp_pptx.write(uploaded_file.getvalue())
-        pptx_path = tmp_pptx.name
-    
-    # Convert PPTX path to ZIP path
-    zip_path = os.path.splitext(pptx_path)[0] + '.zip'
-    os.rename(pptx_path, zip_path)
-    
-    # Create dictionary to store audio files
-    audio_files = {}
-    
-    # Create temporary directory for extraction
-    temp_dir = tempfile.mkdtemp()
-    
-    with st.spinner('Extracting PPTX contents...'):
-        # Extract the zip file to temp directory
-        with zipfile.ZipFile(zip_path, 'r') as zip_ref:
-            zip_ref.extractall(temp_dir)
-    
-    # Path to media folder
-    media_path = os.path.join(temp_dir, 'ppt', 'media')
-    
-    # Check if media folder exists
-    if os.path.exists(media_path):
-        # Create temporary directory for converted files
-        temp_audio_dir = tempfile.mkdtemp()
-        
-        # Progress bar for audio conversion
-        progress_bar = st.progress(0)
-        status_text = st.empty()
-        
-        # First count total slides with audio
-        total_slides = 0
-        slide_num = 1
-        while True:
-            found = False
-            for ext in ['.mp4', '.m4a']:
-                if os.path.exists(os.path.join(media_path, f'media{slide_num}{ext}')):
-                    total_slides += 1
-                    found = True
-                    break
-            if not found:
-                break
-            slide_num += 1
-        
-        # Process audio files
-        slide_num = 1
-        processed_slides = 0
-        while True:
-            # Check for either .mp4 or .m4a file for current slide
-            media_file = None
-            for ext in ['.mp4', '.m4a']:
-                filename = f'media{slide_num}{ext}'
-                file_path = os.path.join(media_path, filename)
-                if os.path.exists(file_path):
-                    media_file = file_path
-                    break
-                    
-            if not media_file:
-                break
-                
-            # Create temporary mp3 file
-            temp_mp3 = os.path.join(temp_audio_dir, f'temp_{slide_num}.mp3')
-            
-            try:
-                status_text.text(f'Converting audio from slide {slide_num}...')
-                # Convert to mp3 using ffmpeg
-                os.system(f'ffmpeg -i "{media_file}" -vn -acodec libmp3lame "{temp_mp3}" -loglevel quiet')
-                # Store the temp mp3 file path in dictionary
-                audio_files[slide_num-1] = temp_mp3
-                processed_slides += 1
-                progress_bar.progress(processed_slides / total_slides)
-            except Exception as e:
-                st.error(f"Error converting slide {slide_num}: {str(e)}")
-                
-            slide_num += 1
-        
-        progress_bar.empty()
-        status_text.empty()
-        
-        # Load Whisper model
-        with st.spinner('Loading Whisper model...'):
-            model = whisper.load_model("base")
-        
-        # Dictionary to store transcriptions by slide number
-        slide_transcripts = {}
-        
-        # Progress bar for transcription
-        progress_bar = st.progress(0)
-        status_text = st.empty()
-        
-        # Transcribe each audio file
-        for idx, (slide_num, audio_file) in enumerate(audio_files.items()):
-            status_text.text(f'Transcribing slide {slide_num + 1}...')
-            # Transcribe the audio file
-            result = model.transcribe(audio_file)
-            # Store transcription text for this slide
-            slide_transcripts[slide_num + 1] = result["text"]
-            progress_bar.progress((idx + 1) / len(audio_files))
-        
-        progress_bar.empty()
-        status_text.empty()
-        
-        # Clean up temporary files
-        os.unlink(zip_path)
-        
-        return slide_transcripts
-    return None
-
-def main():
-    st.title('Audio2Text')
-    st.write('Upload a PowerPoint file (PPTX) to transcribe its audio content')
-    
-    # File uploader
-    uploaded_file = st.file_uploader("Choose a PPTX file", type="pptx")
-    
-    if uploaded_file is not None:
-        # Check file size (2GB limit)
-        if uploaded_file.size > 2 * 1024 * 1024 * 1024:
-            st.error("File size exceeds 2GB limit")
-            return
-            
-        st.write("Processing... This may take a while depending on the number and length of audio clips.")
-        
-        # Process the file
-        transcripts = process_pptx(uploaded_file)
-        
-        if transcripts:
-            st.subheader("Transcription Results")
-            for slide_num, text in sorted(transcripts.items()):
-                st.markdown(f"**Slide {slide_num}**")
-                st.write(text)
-                st.markdown("---")
-        else:
-            st.warning("No audio content found in the PowerPoint file.")
-
-if __name__ == "__main__":
-    main()