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# ===========================================
# ver01.01-5.workload-----app.py
# ===========================================
import asyncio
import os
import re
import time
import json
import chainlit as cl
from langchain import hub
from langchain_openai import OpenAI
from langchain.chains import LLMChain, APIChain
from langchain_core.prompts import PromptTemplate
from langchain.memory.buffer import ConversationBufferMemory
from api_docs_mck import api_docs_str
from faq_data import ansatte_faq_data, utleiere_faq_data
from personvernspolicy import personvernspolicy_data
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
FAQ_ANSATTE = [
"Hvordan registrerer jeg meg som bruker?",
"Når får jeg leieinstruks for min bestilling? Informasjon om nøkler etc.?",
"Det står barneseng og barnestol under fasiliteter, må dette forhåndsbestilles?",
"Kan jeg ta med hund eller katt?",
"Jeg har lagt inn en bestilling hva skjer videre?",
"Jeg har bestilt firmahytte, men kan ikke reise. Kan jeg endre navn på bestillingen til min kollega eller familiemedlem som vil reise i stedet for meg?",
"Kan jeg avbestille min reservasjon?",
"Jeg har bestilt utvask. Hva må jeg gjøre i tillegg til dette?",
"Jeg er medlem og eier en hytte! Kan jeg bli utleier i DaysOff?",
"Bestille opphold?"
]
FAQ_UTLEIERE = [
"Hva er betingelser for utleie?",
"Hvor lang tid har jeg på å bekrefte en bestilling?",
"Hvilke kanselleringsregler gjelder?",
"Hvem er kundene deres?",
"Kan jeg legge inn rabatterte priser for å lage egne kampanjer?",
"Når mottar jeg betaling for leie?",
"Jeg fikk en e-post om ny bestilling, men jeg finner den ikke i systemet?",
"Hvordan registrerer jeg opptatte perioder i kalenderen?",
"Jeg leier ut i andre kanaler. Hvordan kan jeg synkronisere kalenderne?"
]
PERSONVERNSPOLICY_QUESTIONS = [
"Hvilke personlige opplysninger samler vi inn?",
"Kan dere motta personlig informasjon fra tredjepart?",
"Hvordan bruker vi dine personlige opplysninger?",
"Med hvem deler vi dine personlige opplysninger?",
"Adferdsmessig annonsering?",
"Hvordan reagerer vi på « Spor ikke » forespørsler?",
"Hva er dine rettigheter?",
"Hvordan beskytter vi dataene dine?",
"Hvilke data brudd prosedyrer har vi på plass?",
"Hvem i vårt team har tilgang til dine data?",
"Endringer i denne policyen"
]
# If you do not know the answer, just reply truthfully that you do not have the answer rather than
# giving inaccurate or speculative information.
daysoff_assistant_template = """
You are a customer support assistant (’kundeservice AI assistent’) for Daysoff.no
By default, you respond in Norwegian language, using a warm, direct and professional tone.
You can look up booking information for a booking ID (bestillingskode)
and answer FAQ related to DaysOff firmahytteordning.
Chat History: {chat_history}
Question: {question}
Answer:
"""
daysoff_assistant_prompt = PromptTemplate(
input_variables=['chat_history', 'question'],
template=daysoff_assistant_template
)
api_url_template = """
Given the following API Documentation for Daysoff's official
booking information API: {api_docs}
Your task is to construct the most efficient API URL to answer
the user's question, ensuring the
call is optimized to include only the necessary information.
Question: {question}
API URL:
"""
api_url_prompt = PromptTemplate(input_variables=['api_docs', 'question'],
template=api_url_template)
# If the response includes a booking ID (bestillingskode), consistently present this information
# directly to the user without summarizing it.
api_response_template = """
With the API Documentation for Daysoff's official API: {api_docs} in mind,
and the specific user question: {question},
and given this API URL: {api_url} for querying,
here is the response from Daysoff's API: {api_response}.
If the response includes booking information, provide the information verbatim (do not summarize it.)
For all other cases, please provide a clear and concise summary (in Norwegian) that directly addresses the user's question,
delivered in a manner that reflects the professionalism and warmth of a human customer service agent.
Summary:
"""
api_response_prompt = PromptTemplate(
input_variables=['api_docs', 'question', 'api_url', 'api_response'],
template=api_response_template
)
@cl.on_chat_start
def setup_multiple_chains():
llm = OpenAI(
model='gpt-3.5-turbo-instruct',
temperature=0.7,
openai_api_key=OPENAI_API_KEY,
#max_tokens=512,
top_p=0.9,
frequency_penalty=0.1,
presence_penalty=0.1
)
conversation_memory = ConversationBufferMemory(memory_key="chat_history",
max_len=300,
return_messages=True,
)
llm_chain = LLMChain(llm=llm,
prompt=daysoff_assistant_prompt,
memory=conversation_memory
)
cl.user_session.set("llm_chain", llm_chain)
api_chain = APIChain.from_llm_and_api_docs(
llm=llm,
api_docs=api_docs_str,
api_url_prompt=api_url_prompt,
api_response_prompt=api_response_prompt,
verbose=True,
limit_to_domains=None
)
cl.user_session.set("api_chain", api_chain)
@cl.on_message
async def handle_message(message: cl.Message):
user_message = message.content #.lower()
llm_chain = cl.user_session.get("llm_chain")
api_chain = cl.user_session.get("api_chain")
booking_pattern = r'\b[A-Z]{6}\d{6}\b'
base_url = "https://670dccd0073307b4ee447f2f.mockapi.io/daysoff/api/V1/booking"
#faq_keywords = (
#[key for key in ansatte_faq_data.keys()] +
#[key for key in utleiere_faq_data.keys()] +
#[key for key in personvernspolicy_data.keys()]
#)
if re.search(booking_pattern, user_message):
bestillingskode = re.search(booking_pattern, user_message).group(0)
question = f"Retrieve information for booking ID {base_url}?search={bestillingskode}"
response = await api_chain.acall(
{
"bestillingskode": bestillingskode,
"question": question
},
callbacks=[cl.AsyncLangchainCallbackHandler()])
elif any(keyword in user_message for keyword in (FAQ_ANSATTE + FAQ_UTLEIERE + PERSONVERNSPOLICY_QUESTIONS)):
#elif any(keyword in user_message for keyword in faq_keywords):
response = await api_chain.acall(user_message, callbacks=[cl.AsyncLangchainCallbackHandler()])
else:
response = await llm_chain.acall(user_message, callbacks=[cl.AsyncLangchainCallbackHandler()])
response_key = "output" if "output" in response else "text"
await cl.Message(response.get(response_key, "")).send()
return message.content