Update app.py

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from audio_processing import process_audio, print_results, load_models
+from audio_processing import process_audio, load_models
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForQuestionAnswering
 import spaces
 import torch
@@ -19,6 +19,7 @@ qa_model = AutoModelForQuestionAnswering.from_pretrained("distilbert-base-cased-
 qa_tokenizer = AutoTokenizer.from_pretrained("distilbert-base-cased-distilled-squad")
 print("Models loaded successfully.")
 
+
 @spaces.GPU
 def transcribe_audio(audio_file, translate, model_size):
     language_segments, final_segments = process_audio(audio_file, translate=translate, model_size=model_size)
@@ -42,6 +43,7 @@ def transcribe_audio(audio_file, translate, model_size):
     
     return output, full_text
 
+
 @spaces.GPU
 def summarize_text(text):
     inputs = summarizer_tokenizer(text, max_length=1024, truncation=True, return_tensors="pt").to(device)
@@ -49,6 +51,7 @@ def summarize_text(text):
     summary = summarizer_tokenizer.decode(summary_ids[0], skip_special_tokens=True)
     return summary
 
+
 @spaces.GPU
 def answer_question(context, question):
     inputs = qa_tokenizer(question, context, return_tensors="pt").to(device)
@@ -58,18 +61,21 @@ def answer_question(context, question):
     answer = qa_tokenizer.decode(inputs["input_ids"][0][answer_start:answer_end])
     return answer
 
+
 @spaces.GPU
 def process_and_summarize(audio_file, translate, model_size):
     transcription, full_text = transcribe_audio(audio_file, translate, model_size)
     summary = summarize_text(full_text)
     return transcription, summary
 
+
 @spaces.GPU
 def qa_interface(audio_file, translate, model_size, question):
     _, full_text = transcribe_audio(audio_file, translate, model_size)
     answer = answer_question(full_text, question)
     return answer
 
+    
 # Main interface
 with gr.Blocks() as iface:
     gr.Markdown("# WhisperX Audio Transcription, Translation, Summarization, and QA (with ZeroGPU support)")