app.py

from flask import Flask, request, render_template
from twilio.twiml.voice_response import VoiceResponse, Gather
import openai
import csv
import os
from simple_salesforce import Salesforce
from langchain import OpenAI
from langchain.chat_models import ChatOpenAI
from langchain.chains import LLMChain, ConversationChain
from langchain import PromptTemplate
from langchain import HuggingFaceHub
from langchain.chains.conversation.memory import (ConversationBufferMemory, 
                                                  ConversationSummaryMemory, 
                                                  ConversationBufferWindowMemory,
                                                  ConversationKGMemory,ConversationSummaryBufferMemory)

app = Flask(__name__)

# Set up the LangChain

template = """Answer the question based on the context below.

Context: You are Lisa, a loyal helpful service agent, appointed for SuperFoods Petcare Company. 
No introduction required.
Your goal ask one question at a time and remember them and provide a friendly conversational responses to the customer.
For Product Complaint: Ask questions about product they purchased, when they bought it, what issue occured with it. Query for any adverse reaction happened to his pet due to the product. 
For Returns: Ask for the cause of return, if not asked aready, then tell him about the 10-day return policy, after which it's non-returnable. 
For Refunds: Ask about the product amd the mode of refund hw wants, clarify the refunds will happen within 2-3 business days. 
A case for will be created for all scenarios, and the caller will be notified over Email/WhatApp. Ask for image uploads for product investigations.
Do not answer anything outside your role, and apologize for any unknown questions. 

Past Conversations: {chat_history}
Human: {input}
AI: 

"""

prompt = PromptTemplate(
    input_variables=["chat_history", "input"],
    template=template
)

llm35 = ChatOpenAI(
    temperature=0.2, 
    openai_api_key='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',
    model_name='gpt-3.5-turbo',
    max_tokens=128
)

llm30 = OpenAI(
    temperature=0.1, 
    openai_api_key='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',
    max_tokens=128
)

memory = ConversationBufferMemory(memory_key="chat_history")

conversations = ConversationChain(
    prompt=prompt,
    llm=llm35,
    memory=memory,
    verbose=False
)

# Set up the Salesforce API
sf = Salesforce(username='soumyabrata.das2@cognizant.com.sandbox1', password='April-2023', security_token='1nic31g1YZ2V3dQRhCzXheAa',instance_url='https://marketing-comm.lightning.force.com')
#print(sf.headers)
print("Successfully Connected to Salesforce")

# Define a function to handle incoming calls
def handle_incoming_call():
    response = VoiceResponse()
    gather = Gather(input='speech', speechTimeout='auto', action='/process_input')
    gather.say("Welcome to the SuperFood Voice Services !")
    gather.pause(length=1)
    gather.say("Hi, I am Lisa, from customer service")
    gather.pause(length=0)
    gather.say("May i know who i am talking to?")
    response.append(gather)
    return str(response)

# Define a route to handle incoming calls
@app.route("/incoming_call", methods=["POST"])
def incoming_call():
    return handle_incoming_call()

# Define a route to handle user input
@app.route('/process_input', methods=['POST'])
def process_input():
    user_input = request.form['SpeechResult']
    print("Rob : " +user_input)
    conversation_id = request.form['CallSid']
    #print("Conversation Id: " + conversation_id)

    if user_input.lower() in ''['thank you', 'thanks.', 'bye.', 'goodbye.','no thanks.','no, thank you.','i m good.','no, i m good.','same to you.','no, thanks.','thank you.']:
        response = VoiceResponse()
        response.say("Thank you for using our service. Goodbye!")
        
        response.hangup()
        print("Hanged-up")
        
        create_case(conversations.memory.buffer)
        
        print("Case created successfully !!")
        
    else:       
        response = VoiceResponse()
        ai_response=conversations.predict(input=user_input)
        response.say(ai_response)
        print("Bot: " + ai_response)
        gather = Gather(input='speech', speechTimeout='auto', action='/process_input')
        response.append(gather)
   
    return str(response)

# For Case Summary and Subject
openai.api_key = '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'

def get_case_summary(conv_detail):
    chatresponse_desc = openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[
        {"role": "system", "content": "You are an Text Summarizer."},
        {"role": "user", "content": "You need to summarise the conversation between an agent and customer mentioned below. Remember to keep the Product Name, Customer Tone and other key elements from the convsersation"},
        {"role": "user", "content": conv_detail}
    ]
    )
    case_desc = chatresponse_desc.choices[0].message.content
    return case_desc

def get_case_subject(conv_detail):     
    chatresponse_subj = openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[
        {"role": "system", "content": "You are an Text Summarizer."},
        {"role": "user", "content": "You need to summarise the conversation between an agent and customer in 10 words mentioned below for case subject."},
        {"role": "user", "content": conv_detail}
    ]
    )
    case_subj = chatresponse_subj.choices[0].message.content
    return case_subj

# Define a function to create a case record in Salesforce
def create_case(conv_hist):
    desc = get_case_summary(conv_hist)
    subj = get_case_subject(conv_hist)
    case_data = {
            'Subject': 'Voice Bot Case for Rob :' + subj ,
            'Description': desc,
            'Status': 'New',
            'Origin': 'Voice Bot',
            'Voice_Call_Conversation__c': conv_hist ,
            'Voice_Call_Id__c': conversation_id,
            'ContactId': '003B000000NLHQ1IAP'
        }   
    sf.Case.create(case_data)        
        

@app.route('/')
def index():
    return """Flask Server running with Twilio Voice & ChatGPT integrated with Salesforce for Case Creation. Call +1-320-313-9061 to talk to the AI Voice Bot."""

if __name__ == '__main__':
    app.run(debug=False,host='0.0.0.0',port=5050)
    uvicorn.run(app,host='0.0.0.0', port=5050)