Update app.py

app.py

@@ -137,26 +137,33 @@ def answer_question(prompt):
     return generated_answer
 
 
-def process_file(file_obj):
-    # Open the uploaded file
-    with open(file_obj.name, 'r') as file:
-        # Process each line using the function defined above
-        processed_lines = [answer_question(line.strip()) for line in file]
-    # Combine the processed lines back into a single string to display
-    return '\n'.join(processed_lines)
-
-def send_email(receiver_email, subject, body):
-    sender_email = "[email protected]" 
-    sender_password = "opri fcxx crkh bvfj" 
-    
+def process_inputs(llm, questions, relevance, diversity, email):
+    # Save questions to a CSV file
+    questions_list = questions.split('\n')
+    df = pd.DataFrame(questions_list, columns=["Questions"])
+    csv_file = "/mnt/data/questions.csv"
+    df.to_csv(csv_file, index=False)
+
+    # Email the CSV file
+    sender_email = "[email protected]"
+    sender_password = "opri fcxx crkh bvfj"
+    receiver_email = email
+    subject = "Your Submitted Questions"
+    body = "Thank you for your submission. Please find attached the CSV file containing your questions."
+
     message = MIMEMultipart()
     message['From'] = sender_email
     message['To'] = receiver_email
     message['Subject'] = subject
-    
     message.attach(MIMEText(body, 'plain'))
-    
-    # Setup the SMTP server and send the email
+
+    attachment = open(csv_file, "rb")
+    part = MIMEBase('application', 'octet-stream')
+    part.set_payload((attachment).read())
+    encoders.encode_base64(part)
+    part.add_header('Content-Disposition', f"attachment; filename= questions.csv")
+    message.attach(part)
+
     server = smtplib.SMTP('smtp.gmail.com', 587)
     server.starttls()
     server.login(sender_email, sender_password)
@@ -164,24 +171,8 @@ def send_email(receiver_email, subject, body):
     server.sendmail(sender_email, receiver_email, text)
     server.quit()
 
+    return f"Submitted questions:\n\n{questions}\n\nRelevance: {relevance}\nDiversity: {diversity}\nEmail: {email}"
 
-def process_and_email(file_info, email_address):
-    # Process the file
-    processed_text = process_file(file_info['path'])
-
-    answered_text = answer_question(processed_text)  # Assuming 'answer' is a function defined elsewhere
-    
-    # Save the answered_text as CSV format
-    processed = 'processed_results.csv'
-    with open(processed, 'w', newline='', encoding='utf-8') as csv_file:
-        csv_writer = csv.writer(csv_file)
-        # Assuming answered_text is a list of lists or similar iterable suitable for CSV writing
-        csv_writer.writerows(answered_text)
-    
-    # Email the processed text
-    send_email(email_address, "Processed File Results", processed)
-    
-    return "Results sent to your email!"
     
 text_list = []
 
@@ -283,31 +274,21 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         </div>
         """)
 
-        with gr.Row():
-            model_name_input2 = gr.Dropdown([("Llama", "TheBloke/Llama-2-7B-Chat-GGML"), ("Falcon", "TheBloke/Falcon-180B-Chat-GGUF"), ("Zephyr", "TheBloke/zephyr-quiklang-3b-4K-GGUF"), ("Vicuna", "TheBloke/vicuna-33B-GGUF"), ("Claude", "TheBloke/claude2-alpaca-13B-GGUF"), ("Alpaca", "TheBloke/LeoScorpius-GreenNode-Alpaca-7B-v1-GGUF")], label="Large Language Model")
-        
-        with gr.Row():
-            prompt_input2 = gr.Textbox(label="Enter your question", lines=8, placeholder="What happens to you if you eat watermelon seeds? \n\n How long should you wait between eating a meal and going swimming? \n\n Are vampires real? \n\n Who is a famous person from the Galapagos Islands?\n\nHow were the sun and the stars created?")
-        
-        with gr.Row():
-            file = gr.File(file_types=["text"], file_count="multiple", label="Or You Can Click to Upload a File")
-        
-        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) 
-        
-        with gr.Row():
-            email = gr.Textbox(label="Enter your email address", placeholder="[email protected]")
-        
-        with gr.Row():
-            submit_button = gr.Button("Submit", variant="primary")
+        gr.Markdown("## Batch Mode Auditing LLMs")
+            gr.Markdown("In batch auditing mode, you have the capability to probe the LLM. To begin, you must first select the LLM you wish to audit and then input the questions you intend to explore. For each question submitted, the model will generate five prompts, each accompanied by its respective answers.")
+            gr.Markdown("To tailor the generation of these five prompts from your original question, you can adjust the relevance and diversity scores. The relevance score determines how closely the generated prompts should align with the original question, while the diversity score dictates the variance among the prompts themselves.")
+            gr.Markdown("Upon completion, please provide your email address. We will compile and send the answers to you promptly.")
+            
+            llm_dropdown = gr.Dropdown([("Llama", "TheBloke/Llama-2-7B-Chat-GGML"), ("Falcon", "TheBloke/Falcon-180B-Chat-GGUF"), ("Zephyr", "TheBloke/zephyr-quiklang-3b-4K-GGUF"), ("Vicuna", "TheBloke/vicuna-33B-GGUF"), ("Claude", "TheBloke/claude2-alpaca-13B-GGUF"), ("Alpaca", "TheBloke/LeoScorpius-GreenNode-Alpaca-7B-v1-GGUF")], label="Large Language Model")
+            questions_textbox = gr.Textbox(label="Enter your question", placeholder="Enter your questions here...")
+            file_upload = gr.File(label="Or You Can Click to Upload a File")
+            relevance_slider = gr.Slider(0, 100, value=70, step=1, label="Relevance")
+            diversity_slider = gr.Slider(0, 100, value=25, step=1, label="Diversity")
+            email_input = gr.Textbox(label="Enter your email address", placeholder="[email protected]")
+            
+            submit_button = gr.Button("Submit")
+            submit_button.click(fn=process_inputs, inputs=[llm_dropdown, questions_textbox, relevance_slider, diversity_slider, email_input], outputs="text")
 
-    # Define the function to be executed when the submit button is pressed
-    submit_button.click(
-        fn=process_and_email, 
-        inputs=[file, email], 
-        outputs=[]
-    )
 
     
 # Launch the Gradio app