File size: 4,874 Bytes
12654ba
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
78b9b84
12654ba
 
 
 
 
 
efdd6c6
12654ba
efdd6c6
 
 
 
 
12654ba
 
efdd6c6
 
 
12654ba
 
 
 
 
 
7e8476d
12654ba
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a77a669
 
 
 
 
12654ba
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
efdd6c6
e7058ea
 
 
 
 
3644676
e7058ea
 
 
 
 
 
 
 
 
efdd6c6
12654ba
 
e7058ea
12654ba
 
 
a77a669
 
 
 
 
 
 
 
 
 
 
4313ed0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
# ===========================================
# !-----app.py
# ===========================================

import json
import asyncio
import os
import re
import requests
from dotenv import load_dotenv
import chainlit as cl
from langchain import hub
from langchain_openai import OpenAI
from langchain.chains import LLMChain
from langchain_core.prompts import PromptTemplate
from langchain.memory.buffer import ConversationBufferMemory


load_dotenv()
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
auth_token = os.environ.get("DAYSOFF_API_TOKEN")

API_URL = "https://aivisions.no/data/daysoff/api/v1/booking/"

daysoff_assistant_template = """
#You are a customer support assistant (โ€™kundeservice AI assistentโ€™) for Daysoff.
#By default, you respond in Norwegian language, using a warm, direct, and professional tone.
Your expertise is exclusively in retrieving booking information for a given booking ID and assistance related to
to this.
#You should always provide a clear and concise answer (in Norwegian) of the booking information retrieved.
#This way you directly address the user's question in a manner that reflects the professionalism and warmth
#of a human customer service agent.
You do not provide information outside of this scope. If a question is not about this topic, adapt to user's query 
and respond with something like
"Jeg driver faktisk kun med henvendelser omkring bestillingsinformasjon. Gjelder det andre henvendelser
mรฅ du nok kontakte kundeservice pรฅ [email protected]๐Ÿ˜Š"
Chat History: {chat_history}
Question: {question}
Answer:
"""
daysoff_assistant_prompt = PromptTemplate(
    input_variables=["chat_history", "question"],
    template=daysoff_assistant_template,
)

# -- async wrapper for requests.post
async def async_post_request(url, headers, data):
    return await asyncio.to_thread(requests.post, url, headers=headers, json=data)

@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=2048,
        top_p=0.9,
        frequency_penalty=0.1,
        presence_penalty=0.1,
    )

    conversation_memory = ConversationBufferMemory(
        memory_key="chat_history",
        input_key="question",  # ?
        output_key="text",     # ?
        max_len=30,
        return_messages=True
    )

    llm_chain = LLMChain(
        llm=llm,
        prompt=daysoff_assistant_prompt,
        memory=conversation_memory,
    )

    cl.user_session.set("llm_chain", llm_chain)

@cl.on_message
async def handle_message(message: cl.Message):
    user_message = message.content
    llm_chain = cl.user_session.get("llm_chain")
    
    booking_pattern = r'\b[A-Z]{6}\d{6}\b'   
    match = re.search(booking_pattern, user_message)

    if match:
        
        bestillingskode = match.group()
        headers = {
            "Authorization": auth_token,
            "Content-Type": "application/json"
        }
        payload = {"booking_id": bestillingskode}

        try:
            
            response = await async_post_request(API_URL, headers, payload)
            response.raise_for_status() 
            booking_data = response.json()

            if "booking_id" in booking_data:
    
                table = (
                    "| Field      | Info                |\n"
                    "|:-----------|:---------------------|\n"
                    f"| Booking ID | {booking_data.get('booking_id', 'N/A')} |\n"
                    f"| Full Name  | {booking_data.get('full_name', 'N/A')} |\n"
                    f"| Amount     | {booking_data.get('amount', 0)} kr |\n"
                    f"| Check-in   | {booking_data.get('checkin', 'N/A')} |\n"
                    f"| Check-out  | {booking_data.get('checkout', 'N/A')} |\n"
                    f"| Address    | {booking_data.get('address', 'N/A')} |\n"
                    f"| User ID    | {booking_data.get('user_id', 0)} |\n"
                    f"| Info Text  | {booking_data.get('infotext', 'N/A')} |\n"
                    f"| Included   | {booking_data.get('included', 'N/A')} |"
                )
                
                await cl.Message(content=table).send()

            else:
                await cl.Message(content="Booking not found or invalid response.").send()
                
        except requests.exceptions.RequestException as e:
            await cl.Message(content=f"Request failed: {str(e)}").send()
    else:
        try:
            response = await llm_chain.ainvoke({
                "question": user_message,
                "chat_history": ""
            }, callbacks=[cl.AsyncLangchainCallbackHandler()])
            
            await cl.Message(content=response["text"]).send()
            
        except Exception as e:
            await cl.Message(content=f"Error: {str(e)}").send()