Test Test

app.py

@@ -66,8 +66,7 @@ def process_audio(audio_path, models):
             # Use return_timestamps=True for long audio files
             transcription = models['transcriber'](
                 temp_wav_path,
-                return_timestamps=True,
-                generate_kwargs={"task": "transcribe"}
+                return_timestamps=True  # Remove task specification for English-only model
             )
             
             # Extract full text from chunks
@@ -89,8 +88,9 @@ def process_audio(audio_path, models):
             
             # Summarize each chunk
             summaries = []
+            progress_text = st.empty()
             for i, chunk in enumerate(chunks):
-                st.progress((i + 1) / len(chunks))
+                progress_text.text(f"Summarizing chunk {i+1} of {len(chunks)}")
                 
                 summary = models['summarizer'](
                     chunk,
@@ -105,6 +105,7 @@ def process_audio(audio_path, models):
             
             # Final summarization if multiple chunks exist
             if len(summaries) > 1:
+                progress_text.text("Creating final summary...")
                 combined_summary = models['summarizer'](
                     combined_summary,
                     max_length=200,
@@ -112,6 +113,7 @@ def process_audio(audio_path, models):
                     truncation=True
                 )[0]['summary_text']
             
+            progress_text.empty()
             results['summary'] = combined_summary
             
             # Clean up summary