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| # Import necessary libraries | |
| import openai | |
| import streamlit as st | |
| import time | |
| import csv | |
| from datetime import datetime | |
| from util import check_password | |
| import feedback_saver | |
| # Set your OpenAI Assistant ID here | |
| assistant_id = 'asst_t8r4OXz30mxH1vIUFVXAMoTH' | |
| instruction = """ | |
| ## Strictly do not give any response based on an assumption, and make sure the response should be from the documents provided or the knowledge base specific to ASAP Tickets and Trevolution | |
| ## Strictly avoid referring words like document, file, knowledge.pdf in the response. | |
| ## Add links from the knowledge and instructions if necessary to assist the customer. | |
| ## If you do not have clear information in the document of the question asked, respond with | |
| - **Unfortunately, I could not find a specific answer to your question at the moment as I am still learning. I apologize for any inconvenience. | |
| If you still need assistance, please contact our 24x7 customer service for personalized help:** | |
| - **Email: customerservice@asaptickets.com** | |
| - **USA & Canada: +1-800-750-2238** | |
| - **Philippines: +632-8672-7896** | |
| - **Spain: +34-911-881-607** | |
| - **Italy: +39-06-94809637** | |
| - **Israel: +972-3-7219252** | |
| - **UK: +44-203-695-0964** | |
| - **Let me know if there's anything else I can assist you with.** | |
| """ | |
| openai.api_key = st.secrets["API_KEY"] | |
| access_key = "*****" | |
| secret_access_key="****" | |
| bucket_name = "feedbackchatbot" | |
| object_key = "feedback_data.csv" | |
| # Initialize the OpenAI client (ensure to set your API key in the sidebar within the app) | |
| client = openai | |
| feedback_saver = feedback_saver.FeedbackSaverWithPandas(access_key, secret_access_key) | |
| # Assuming your OpenAI setup and other necessary imports are done earlier in the code | |
| def apply_custom_css(): | |
| st.markdown(""" | |
| <style> | |
| /* General page settings for better visibility */ | |
| html, body, [class*="css"] { | |
| font-family: "Arial", sans-serif; | |
| } | |
| /* Adjusted style for buttons to ensure visibility */ | |
| .stButton>button { | |
| border: 2px solid #4CAF50; /* Green border */ | |
| color: white; /* White text */ | |
| background-color: #4CAF50; /* Green background */ | |
| padding: 10px 24px; /* Some padding */ | |
| cursor: pointer; /* Pointer/hand icon */ | |
| border-radius: 8px; /* Rounded corners */ | |
| font-size: 16px; /* Larger font size */ | |
| display: inline-block; /* Ensure it displays inline */ | |
| margin: 5px 0; /* Add some margin */ | |
| transition: background-color 0.3s, box-shadow 0.3s; /* Smooth transition for hover effect */ | |
| } | |
| .stButton>button:hover { | |
| background-color: #367c39; /* Darker shade on hover */ | |
| box-shadow: 0 2px 10px rgba(0,0,0,0.1); /* Soft shadow on hover */ | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| apply_custom_css() | |
| # Check the password and stop the app if it's incorrect | |
| if not check_password(): | |
| st.stop() | |
| # Streamlit App Layout | |
| st.title("Customer Support Bot - ASAP Tickets") | |
| # Custom greeting or instructions | |
| st.markdown(""" | |
| Welcome to our Customer Support chatbot interface for ASAP Tickets! 👋 | |
| - Type your question or message below. | |
| - Use the thumbs up/down buttons to provide feedback on responses. | |
| """) | |
| # Initialize session state variables for file IDs and chat control | |
| if "file_id_list" not in st.session_state: | |
| st.session_state.file_id_list = [] | |
| if "start_chat" not in st.session_state: | |
| st.session_state.start_chat = False | |
| if "thread_id" not in st.session_state: | |
| st.session_state.thread_id = None | |
| # Ensure feedback-related session state variables are defined | |
| if "feedback_given" not in st.session_state: | |
| st.session_state.feedback_given = False | |
| if "feedback_question" not in st.session_state: | |
| st.session_state.feedback_question = "" | |
| if "feedback_response" not in st.session_state: | |
| st.session_state.feedback_response = "" | |
| if "feedback_type" not in st.session_state: | |
| st.session_state.feedback_type = "" | |
| st.session_state.start_chat = True | |
| # Initialize a session state variable for feedback button visibility | |
| if "show_feedback_buttons" not in st.session_state: | |
| st.session_state.show_feedback_buttons = False | |
| # Create a thread once and store its ID in session state | |
| thread = client.beta.threads.create() | |
| st.session_state.thread_id = thread.id | |
| #st.write("thread id: ", thread.id) | |
| # Define the function to process messages with citations | |
| def process_message_with_citations(message): | |
| """Extract content and annotations from the message and format citations as footnotes.""" | |
| message_content = message.content[0].text | |
| annotations = message_content.annotations if hasattr(message_content, 'annotations') else [] | |
| citations = [] | |
| # Iterate over the annotations and add footnotes | |
| for index, annotation in enumerate(annotations): | |
| # Replace the text with a footnote | |
| message_content.value = message_content.value.replace(annotation.text, f' [{index + 1}]') | |
| # Gather citations based on annotation attributes | |
| if (file_citation := getattr(annotation, 'file_citation', None)): | |
| cited_file = {'filename': 'knowledge.pdf'} # Actual file retrieval logic needed | |
| citations.append(f'[{index + 1}] {file_citation.quote} from {cited_file["filename"]}') | |
| elif (file_path := getattr(annotation, 'file_path', None)): | |
| cited_file = {'filename': 'knowledge.pdf'} # Actual file retrieval logic needed | |
| citations.append(f'[{index + 1}] Click [here](#) to download {cited_file["filename"]}') # Actual download link needed | |
| if citations: | |
| full_response = message_content.value + '\n\nREFERENCES FROM KNOWLEDGE BASE:\n\n' + '\n'.join(citations) | |
| # Add footnotes to the end of the message content | |
| else: | |
| full_response = message_content.value | |
| return full_response | |
| def openai_api_calculate_cost(usage,model="gpt-4-0125-preview"): | |
| pricing = { | |
| 'gpt-3.5-turbo-1106': { | |
| 'prompt': 0.001, | |
| 'completion': 0.002, | |
| }, | |
| 'gpt-4-0125-preview': { | |
| 'prompt': 0.01, | |
| 'completion': 0.03, | |
| }, | |
| 'gpt-4': { | |
| 'prompt': 0.03, | |
| 'completion': 0.06, | |
| } | |
| } | |
| try: | |
| model_pricing = pricing[model] | |
| except KeyError: | |
| raise ValueError("Invalid model specified") | |
| prompt_cost = usage['prompt_tokens'] * model_pricing['prompt'] / 1000 | |
| completion_cost = usage['completion_tokens'] * model_pricing['completion'] / 1000 | |
| total_cost = prompt_cost + completion_cost | |
| # round to 6 decimals | |
| total_cost = round(total_cost, 6) | |
| #print(f"\nTokens used: {usage['prompt_tokens']:,} prompt + {usage['completion_tokens']:,} completion = {usage['total_tokens']:,} tokens") | |
| #print(f"Total cost for {model}: ${total_cost:.4f}\n") | |
| return total_cost | |
| def handle_feedback_positive(): | |
| st.session_state.feedback_question = prompt | |
| st.session_state.feedback_response = full_responses | |
| st.session_state.feedback_type = "Positive" | |
| feedback_saver.save_feedback_to_s3(prompt, full_responses, "Positive", bucket_name, object_key) | |
| def handle_feedback_negative(): | |
| st.session_state.feedback_question = prompt | |
| st.session_state.feedback_response = full_responses | |
| st.session_state.feedback_type = "Negative" | |
| feedback_saver.save_feedback_to_s3(prompt, full_responses, "Negative", bucket_name, object_key) | |
| # Additional function to save feedback | |
| # Additional function to save feedback into a CSV file | |
| def save_feedback(question, response, feedback): | |
| filename = "feedback_data.csv" # Specify your desired filename | |
| # Check if the file exists and determine if headers are needed | |
| try: | |
| with open(filename, "r") as csvfile: | |
| # Try to read the header | |
| reader = csv.reader(csvfile, delimiter='~') | |
| headers = next(reader, None) | |
| headers_needed = not bool(headers) | |
| except FileNotFoundError: | |
| headers_needed = True | |
| with open(filename, "a", newline='') as csvfile: | |
| writer = csv.writer(csvfile, delimiter='~') | |
| # If the file is new or empty, write the header | |
| if headers_needed: | |
| writer.writerow(["Index", "Date", "Question", "Response", "Feedback"]) | |
| # Write the feedback data | |
| # Fetch the last index if file is not empty/new and increment, else start from 1 | |
| last_index = 0 | |
| if not headers_needed: | |
| with open(filename, "r", newline='') as f: | |
| last_line = list(csv.reader(f, delimiter='~'))[-1] | |
| if last_line: # Check if the last line is not empty | |
| last_index = int(last_line[0]) | |
| index = last_index + 1 | |
| current_date = datetime.now().strftime("%Y-%m-%d %H:%M:%S") | |
| writer.writerow([index, current_date, question, response, feedback]) | |
| # Only show the chat interface if the chat has been started | |
| if st.session_state.start_chat: | |
| # Initialize the model and messages list if not already in session state | |
| if "openai_model" not in st.session_state: | |
| st.session_state.openai_model = "gpt-4-0125-preview" | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| # Display existing messages in the chat | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| # Chat input for the user | |
| if prompt := st.chat_input("Hi! I'm Olivia Trevolution's assistant. How can I help you today?"): | |
| # Add user message to the state and display it | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| with st.chat_message("user"): | |
| st.session_state.show_feedback_buttons = True | |
| st.markdown(prompt) | |
| start_time = time.time() | |
| thinking_message = st.empty() | |
| thinking_message.text("Processing...") | |
| # Add the user's message to the existing thread | |
| client.beta.threads.messages.create( | |
| thread_id=st.session_state.thread_id, | |
| role="user", | |
| content=prompt | |
| ) | |
| # Create a run with additional instructions | |
| run = client.beta.threads.runs.create( | |
| thread_id=st.session_state.thread_id, | |
| assistant_id=assistant_id, | |
| instructions= instruction | |
| ) | |
| # Initialize a timeout mechanism | |
| timeout = 60 # seconds | |
| response_received = False | |
| # Poll for the run to complete with timeout | |
| while time.time() - start_time <= timeout: | |
| # Poll for the run to complete and retrieve the assistant's messages | |
| run = client.beta.threads.runs.retrieve( | |
| thread_id=st.session_state.thread_id, | |
| run_id=run.id | |
| ) | |
| if run.status == 'completed': | |
| response_received = True | |
| break | |
| time.sleep(1) | |
| if response_received: | |
| # Retrieve messages added by the assistant | |
| messages = client.beta.threads.messages.list( | |
| thread_id=st.session_state.thread_id | |
| ) | |
| # Process and display assistant messages | |
| assistant_messages_for_run = [ | |
| message for message in messages | |
| if message.run_id == run.id and message.role == "assistant" | |
| ] | |
| with st.chat_message("assistant"): | |
| # Display thumbs up and thumbs down buttons for feedback | |
| message_placeholder = st.empty() | |
| full_responses = '' | |
| # Calculate the time taken | |
| end_time = time.time() | |
| time_taken = end_time - start_time | |
| for message in assistant_messages_for_run: | |
| full_response = process_message_with_citations(message) | |
| full_responses += (f"Response received in {time_taken:.2f} seconds. \n") | |
| usage = client.beta.threads.runs.list(thread_id=st.session_state.thread_id).data[0].usage | |
| #cost = openai_api_calculate_cost(usage, ) | |
| full_responses += "\t \t"+f"\nTokens used: {usage['prompt_tokens']:,} prompt + {usage['completion_tokens']:,} completion = {usage['total_tokens']:,} tokens\n" | |
| full_responses += '\n \n' | |
| #full_responses += "\t \t"+f"Total cost for {st.session_state.openai_model}: ${cost:.4f}\n" | |
| full_responses += '\n \n' | |
| for response in full_response: | |
| full_responses += response | |
| message_placeholder.markdown(full_responses + "▌", unsafe_allow_html=True) | |
| time.sleep(0.001) | |
| message_placeholder.empty() | |
| thinking_message.empty() | |
| message_placeholder.markdown(full_responses, unsafe_allow_html=True) | |
| st.session_state.show_feedback_buttons = True | |
| # Before your main app loop | |
| if "feedback_given" not in st.session_state: | |
| st.session_state.feedback_given = None | |
| st.session_state.feedback_type = "" | |
| if st.session_state.show_feedback_buttons: | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| thumbs_up = st.button("👍", key="thumbs_up", on_click=handle_feedback_positive) | |
| if thumbs_up: | |
| handle_feedback_positive() | |
| st.session_state.show_feedback_buttons = False | |
| with col2: | |
| thumbs_down = st.button("👎", key="thumbs_down", on_click=handle_feedback_negative) | |
| if thumbs_down: | |
| handle_feedback_negative() | |
| st.session_state.show_feedback_buttons = False | |
| st.session_state.messages.append({"role": "assistant", "content": full_responses}) | |
| else: | |
| # Fallback message if response takes more than 60 seconds | |
| fallback_message = """ | |
| <b>Sorry, it's taking longer than expected to get a response. Please try again later or contact customer service for immediate assistance.</b><br><br> | |
| Unfortunately, I could not find a specific answer to your question at the moment as I am still learning. I apologize for any inconvenience.<br><br> | |
| If you still need assistance, please contact our 24x7 customer service for personalized help:<br> | |
| - Email: <a href="mailto:customerservice@asaptickets.com">customerservice@asaptickets.com</a><br> | |
| - USA & Canada: +1-800-750-2238<br> | |
| - Philippines: +632-8672-7896<br> | |
| - Spain: +34-911-881-607<br> | |
| - Italy: +39-06-94809637<br> | |
| - Israel: +972-3-7219252<br> | |
| - UK: +44-203-695-0964<br><br> | |
| Let me know if there's anything else I can assist you with. | |
| """ | |
| thinking_message.empty() # Clear the "Thinking..." message | |
| st.markdown(fallback_message, unsafe_allow_html=True) | |