Create app.py

app.py

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+# ---------------------------------------------------for backend looks-------------------------------------------------
+
+#with open('/usr/local/lib/python3.10/site-packages/transformers/utils/chat_template_utils.py', 'r') as file:
+    #content = file.read()
+    #print("base.py:", content)
+# ------------------------------------------------------the end--------------------------------------------------------
+
+
+
+# ===========================================
+# ver1(get)_app.py
+# ===========================================
+
+import asyncio
+import os
+import re
+import time
+import json
+
+import chainlit as cl
+from dotenv import load_dotenv
+
+from langchain import hub
+from langchain_openai import OpenAI
+from tiktoken import encoding_for_model
+from langchain.chains import LLMChain, APIChain
+from langchain_core.prompts import PromptTemplate
+from langchain.memory.buffer import ConversationBufferMemory
+#from langchain.memory import ConversationTokenBufferMemory
+#from langchain.memory import ConversationSummaryMemory
+
+
+from api_docs_mck import api_docs_str
+
+load_dotenv()
+OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
+
+#auth_token = os.environ.get("CHAINLIT_AUTH_SECRET")
+#if not auth_token.startswith("Bearer "):
+    #auth_token = f"Bearer {auth_token}"
+
+daysoff_assistant_template = """
+#You are a customer support assistant (’kundeservice AI assistent’) 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 assistance related to
+to this.
+You do not provide information outside of this scope. If a question is not about this topic, respond with
+"Jeg driver faktisk kun med henvendelser omkring bestillingsinformasjon. Gjelder det andre henvendelser
+må du nok kontakte kundeservice på [email protected]😊"
+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)
+
+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,
+and response from Daysoff's API: {api_response},
+never refer the user to the API URL as your answer!
+You should always provide a clear and concise summary (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.
+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=2048,
+        top_p=0.9,
+        frequency_penalty=0.1,
+        presence_penalty=0.1
+    )
+
+    conversation_memory = ConversationBufferMemory(memory_key="chat_history",
+                                                   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)
+
+    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")
+
+    base_url = "https://670dccd0073307b4ee447f2f.mockapi.io/daysoff/api/V1/booking"
+    booking_pattern = r'\b[A-Z]{6}\d{6}\b'
+    match = re.search(booking_pattern, user_message)
+
+    try:
+
+        if match:
+        bestillingskode = match.group()
+        question = f"Retrieve information for booking ID {base_url}?search={bestillingskode}"
+
+        response = await api_chain.acall(
+            {
+                "bestillingskode": bestillingskode,
+                "question": question
+
+            },
+            callbacks=[cl.AsyncLangchainCallbackHandler()])
+
+        booking_info = json.loads(response.get("output", "{}"))
+
+        formatted_response = f"""
+        Her er informasjon for bestillingskode: {bestillingskode}
+
+        | Felt        | Detaljer                               |
+        |-------------|----------------------------------------|
+        | Navn:       | {booking_info.get('Navn', 'N/A')} |
+        | Beløp:      | {booking_info.get('Beløp', 'N/A')} NOK |
+        | Check-In:   | {booking_info.get('Checkin', 'N/A')} |
+        | Check-Out:  | {booking_info.get('Checkout', 'N/A')} |
+        | Addresse:   | {booking_info.get('Addresse', 'N/A')} |
+        | Bruker ID:  | {booking_info.get('Bruker ID', 'N/A')} |
+        | Viktig informasjon:  | {booking_info.get('Viktig informasjon', 'N/A')} |
+        | Message:  | {booking_info.get('Message', 'N/A')} |
+        """
+
+        await cl.Message(content=formatted_response).send()
+
+            else:
+                await cl.Message("Jeg kan desverre ikke finne noen informasjon for det oppgitte bookingnummeret.").send()
+
+        else:
+            response = await llm_chain.acall(user_message, callbacks=[cl.AsyncLangchainCallbackHandler()])
+
+    except Exception as e:
+        response = {"output": "Jeg får desverre ikke fram noe informasjon akkurat nå."}
+
+    response_key = "output" if "output" in response else "text"
+
+    return message.content
+
+
+
+
+"""
+ if match:
+        bestillingskode = match.group()
+        question = f"Retrieve information for booking ID"
+
+            api_url = f"{base_url}?search={booking_id}"
+
+            response = await api_chain.acall(
+                {
+                    "booking_id": bestillingskode,
+                    "question": question,
+                    "api_url": api_url
+                },
+                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
+
+
+
+"""