Update app.py

app.py

@@ -53,7 +53,7 @@ def process_audio(audio_file, translate=False):
     """Process audio file"""
     transcriber = ChunkedTranscriber(chunk_size=5, overlap=1)
     results = transcriber.transcribe_audio(audio_file, translate=True)
-    return json.dumps(results, indent=4 )
+    return results
     # try:
     #     processor = AudioProcessor()
     #     language_segments, final_segments = processor.process_audio(audio_file, translate)
@@ -92,7 +92,7 @@ def summarize_text(results):
         if summarizer is None:
             return "Summarization model could not be loaded."
         
-        summary = summarizer(''.join(d['translated'] for d in results if 'translated' in d), max_length=150, min_length=50, do_sample=False)[0]['summary_text']
+        summary = summarizer(''.join(item['translated'] for item in results if 'translated' in item), max_length=150, min_length=50, do_sample=False)[0]['summary_text']
         return summary
     except Exception as e:
         logger.error(f"Summarization failed: {str(e)}")
@@ -108,9 +108,10 @@ def answer_question(context, question):
             return "Q&A model could not be loaded."
         if not question : 
             return "Please enter your Question"
+
         messages = [
             {"role": "system", "content": "You are a helpful assistant who can answer questions based on the given context."},
-            {"role": "user", "content": f"Context: {''.join(d['translated'] for d in context if 'translated' in d)}\n\nQuestion: {question}"}
+            {"role": "user", "content": f"Context: {''.join(item['translated'] for item in context if 'translated' in item)}\n\nQuestion: {question}"}
         ]
         
         response = qa_pipeline(messages, max_new_tokens=256)[0]['generated_text']