Update app.py

app.py

@@ -15,7 +15,7 @@ openai.api_key = "YOUR_OPENAI_API_KEY"
 
 def transcribe_audio(audio_file):
     # Load the audio file
-    audio = AudioSegment.from_file(audio_file.name)
+    audio = AudioSegment.from_file(audio_file)
     # Export as WAV, which Whisper accepts
     buffer = io.BytesIO()
     audio.export(buffer, format="wav")
@@ -79,22 +79,28 @@ def generate_summary(transcription):
 
 def process_lecture(input_type, audio_input, pdf_input, youtube_input, lesson_plan):
     transcription = ""
-    if input_type == "Audio File":
-        if audio_input is not None:
-            transcription = transcribe_audio(audio_input)
-    elif input_type == "YouTube URL":
-        if youtube_input:
-            audio_path = download_youtube_audio(youtube_input)
-            with open(audio_path, "rb") as f:
-                transcription = transcribe_audio(f)
-    elif input_type == "PDF Document":
-        if pdf_input is not None:
-            transcription = extract_text_from_pdf(pdf_input)
+    try:
+        if input_type == "Audio File":
+            if audio_input is not None:
+                transcription = transcribe_audio(audio_input)
+        elif input_type == "YouTube URL":
+            if youtube_input:
+                audio_path = download_youtube_audio(youtube_input)
+                with open(audio_path, "rb") as f:
+                    transcription = transcribe_audio(f)
+        elif input_type == "PDF Document":
+            if pdf_input is not None:
+                transcription = extract_text_from_pdf(pdf_input)
+    except Exception as e:
+        return f"Error during processing: {str(e)}", "No summary available."
     
     if transcription:
-        transcription_text = "\n".join([f"{segment['start']:.2f}-{segment['end']:.2f}: {segment['text']}" for segment in transcription['segments']])
-        summary = generate_summary(transcription)
-        return transcription_text, summary
+        try:
+            transcription_text = "\n".join([f"{segment['start']:.2f}-{segment['end']:.2f}: {segment['text']}" for segment in transcription['segments']])
+            summary = generate_summary(transcription)
+            return transcription_text, summary
+        except Exception as e:
+            return "Transcription generated, but error during summary generation: {str(e)}", "No summary available."
     else:
         return "No transcription available.", "No summary available."