Update app.py

app.py

@@ -156,9 +156,11 @@ def process_inputs(llm, file, relevance, diversity):
         # Extract the first column
         questions_list = df.iloc[:, 0]
 
+        # Initialize lists to store the expanded data
         # Initialize lists to store the expanded data
         expanded_questions = []
         expanded_prompts = []
+        expanded_answers = []
 
         # Generate prompts for each question and expand the data
         for question in questions_list:
@@ -166,10 +168,15 @@ def process_inputs(llm, file, relevance, diversity):
             expanded_questions.extend([question] * len(prompts))
             expanded_prompts.extend(prompts)
 
+            # Generate answers for each prompt
+            answers = [answer_question(prompt) for prompt in prompts]
+            expanded_answers.extend(answers)
+
         # Combine the expanded data into a DataFrame
         output_df = pd.DataFrame({
             'Questions': expanded_questions,
-            'Generated Prompts': expanded_prompts
+            'Generated Prompts': expanded_prompts,
+            'Answers': expanded_answers
         })
 
         # Save the DataFrame to a new Excel file
@@ -295,8 +302,10 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
                 ("Alpaca", "TheBloke/LeoScorpius-GreenNode-Alpaca-7B-v1-GGUF")], 
                 label="Large Language Model")
         file_upload = gr.File(label="Upload an Excel File with Questions", file_types=[".xlsx"])
-        relevance_slider = gr.Slider(0, 100, value=70, step=1, label="Relevance")
-        diversity_slider = gr.Slider(0, 100, value=25, step=1, label="Diversity")
+        with gr.Row():
+            Relevance = gr.Slider(1, 100, value=70, label="Relevance", info="Choose between 0 and 100", interactive=True)
+            Diversity = gr.Slider(1, 100, value=25, label="Diversity", info="Choose between 0 and 100", interactive=True) 
+
             
         submit_button = gr.Button("Submit")
         output_textbox = gr.Textbox(label="Output")