question promt added

app.py

@@ -5,7 +5,7 @@ from PIL import Image
 import matplotlib.pyplot as plt
 
 
-def process_inputs(audio, option):
+def process_inputs(audio, option, question=None):
    # Process inputs and return results
    if option == "Translate":
       generated_text = generate_text_from_audio(audio), None
@@ -18,7 +18,7 @@ def process_inputs(audio, option):
       return "", text_classification(generated_text)
    elif option == "Ask a Question":
       generated_text = generate_text_from_audio(audio)
-      return ask_ques_from_text(generated_text), None
+      return ask_ques_from_text(generated_text, question), None
 
 def generate_text_from_audio(audio):
    device = "cuda:0" if torch.cuda.is_available() else "cpu"
@@ -78,14 +78,14 @@ def text_classification(text):
    return "classification_plot.png"
 
 
-def ask_ques_from_text(text):
+def ask_ques_from_text(text, ques):
    model_name = "deepset/roberta-base-squad2"
 
    # Get predictions
    nlp = pipeline('question-answering', model=model_name, tokenizer=model_name, device=0)
 
    QA_input = {
-      'question': 'who did not recognize?',
+      'question': ques,
       'context': text  # Your context text from audio_text_result
    }
 
@@ -98,9 +98,11 @@ demo = gr.Interface(
    fn=process_inputs,
    inputs=[
        gr.Audio(label="Upload audio in .mp3 format", type="filepath"),  # Audio input
-       gr.Dropdown(choices=["Translate", "Summarize", "text-classification", "Ask a Question"], label="Choose an Option")
+       gr.Dropdown(choices=["Translate", "Summarize", "text-classification", "Ask a Question"], label="Choose an Option"),
+       gr.Textbox(label="Enter your question if you chose Ask a question in dropdown", placeholder="Enter your question here", visible=True)
    ],
    outputs=[gr.Textbox(label="Result"), gr.Image(label="Classification Plot")],
 )
 
+
 demo.launch()