Update app.py

app.py

@@ -63,22 +63,22 @@ def get_full_context(input):
       index = doc.metadata['index']
       context += str(data.iloc[[index]])
 
-  return str(context)
+  return context
 
 
 is_first_run = True  # Flag to check if it's the first run
 
 # Here is the langchain
 def predict(history, input):
-    
+
     global is_first_run  # Use the global flag
     if is_first_run:
         context = get_full_context(input)
-        print(f"Context is as follows: {context}")  # For debugging
+        print(context)  # For debugging
         is_first_run = False  # Set the flag to False after the first run
     else:
         context = ""
-    
+
     history_langchain_format = []
     history_langchain_format.append(SystemMessage(content=f"{ORIG_SYSTEM_MESSAGE_PROMPT}, here is the user information: {user_info_simulated}"))
     for human, ai in history:
@@ -121,64 +121,35 @@ def bot(chatbot_history):
         time.sleep(0.05)
         yield chatbot_history
 
-def log_to_csv(question, answer):
-    """Append a line to a CSV. Create a new file if needed."""
-    now = datetime.today().strftime("%Y%m%d_%H:%M:%S")
-    if not os.path.isfile(PERSISTENT_LOG_PATH):
-        # Add the column names to the CSV
-        with open(PERSISTENT_LOG_PATH, "w+") as csv_file:
-            writer = csv.writer(csv_file)
-            writer.writerow(["datetime", "user_question", "bot_response"])
-
-    # Write the disliked message to the CSV
-    with open(PERSISTENT_LOG_PATH, "a") as csv_file:
-        writer = csv.writer(csv_file)
-        writer.writerow([now, question, answer])
-
-    # Copy file from persistent storage to local repo
-    shutil.copyfile(PERSISTENT_LOG_PATH, LOCAL_LOG_PATH)
-
-def get_voted_qa_pair(history, voted_answer):
-    """Return the question-answer pair from the chat history, given a 
-    particular bot answer. Note: This is required because the 'vote'
-    event handler only has access to the answer that was liked/disliked.
-    """
-    for question, answer in history:
-        if answer == voted_answer:
-            return question, answer
-
-def vote(data: gr.LikeData, history):
-    """This is a function to do something with the voted information"""
-    print(history)
+# This is a function to do something with the voted information (TODO: Save this info somewhere?)
+def vote(data: gr.LikeData):
     if data.liked:
         print("You upvoted this response: " + data.value)
     else:
         print("You downvoted this response: " + data.value)
-        # Find Q/A pair that was disliked
-        question, answer = get_voted_qa_pair(history, data.value)
-        log_to_csv(question, answer)
-        
+        with open("output.txt", "a") as text_file:
+          print(f"Disliked content: {data.value}", file=text_file)
+
 def reset_flag():
     global is_first_run
     is_first_run = True
 
 # The Gradio App interface
 with gr.Blocks() as demo:
-    gr.Markdown("""<h1><center>Troubleshooting Bot by CIONIC</center></h1>""")
-    gr.Markdown("""<p><center>Create a new case by clicking the "Clear" button.</center></p>""")
-    chatbot = gr.Chatbot(label="DylanAI")
-    textbox = gr.Textbox(label="Type your question here")
+    gr.Markdown("""<h1><center>TROUBLESHOOTING Bot by CIONIC</center></h1>""")
+    gr.Markdown("""<p><center>To start a new case, press clear.</center></p>""")
+    chatbot = gr.Chatbot("CIONIC")
+    textbox = gr.Textbox("Please describe your issue in 1-3 sentences")
     clear_button = gr.ClearButton(components=[chatbot])
     clear_button.click(reset_flag, None, None)
-    
+
     # Chain user and bot functions with `.then()`
     textbox.submit(user, [textbox, chatbot], [textbox, chatbot], queue=False).then(
         bot, chatbot, chatbot,
     )
-    chatbot.like(vote, chatbot, None)
+    # chatbot.like(vote, None, None)
 
 # Enable queuing
 demo.queue()
-demo.launch(debug=True, share=True)
-
+demo.launch(debug=True)