### title: 010125-daysoff-assistant-api ### file: app.py import asyncio import os import re import time import json import torch from api_docs_mck import api_docs_str #from daysoff import daysoff_str ## make daysoff.py, put json info in dict. #from personvernpolicy import personvernpolicy_str ## make personvernpolicy.py, put json info in dict. import chainlit as cl from langchain import hub from langchain.chains import LLMChain, APIChain from langchain_core.prompts import PromptTemplate #from langchain_community.llms import HuggingFaceHub from langchain_huggingface import HuggingFaceEndpoint from langchain.memory.buffer import ConversationBufferMemory HUGGINGFACEHUB_API_TOKEN = os.environ.get("HUGGINGFACEHUB_API_TOKEN") BOOKING_ID = re.compile(r'\b[A-Z]{6}\d{6}\b') BOOKING_KEYWORDS = [ "booking", "bestillingsnummer", "bookingen", "ordrenummer", "reservation", "rezerwacji", "bookingreferanse", "rezerwacja", "booket", "reservation number", "bestilling", "order number", "booking ID", "identyfikacyjny płatności" ] daysoff_assistant_template = """ You are a customer support assistant for Daysoff named "Agrippa". Your expertise is in retrieving booking details for a given booking ID and answering questions about Daysoff's personvernspolicy and firmahytteordning. You do not provide information outside of this scope. By default, you respond in Norwegian language. 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 {question} contains an alphanumeric identifier consisting of 6 letters followed by 6 digits (e.g., DAGHNS116478) api_response_template = """ With the API Documentation for Daysoff's official API: {api_docs} in mind, and user question: {question}, and given this API URL: {api_url} for querying, here is the response from Daysoff's API: {api_response}. Please provide an summary that directly addresses the user's question, omitting technical details like response format, and focusing on delivering the answer with clarity and conciseness, as if a human customer service agent is providing this information. 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 = HuggingFaceEndpoint( repo_id="google/gemma-2-2b-it", #"norallm/normistral-7b-warm-instruct", huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN, #max_new_tokens=512, temperature=0.7, task="text-generation" ) conversation_memory = ConversationBufferMemory(memory_key="chat_history", max_len=200, 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=["https://670dccd0073307b4ee447f2f.mockapi.io/daysoff/api/V1"] ) 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") #if any(keyword in user_message for keyword in ["firmahytteordning","personvernpolicy"]): #def is_booking_query(user_message): #match = re.search(r'\b[A-Z]{6}\d{6}\b', user_message) #return match is not None # --works boolean #booked = is_booking_query(user_message) #if booked: if re.search(r'\b[A-Z]{6}\d{6}\b', user_message): # ex., "Hei, har du booking info for EQJLCQ362149?" 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