Integrate Zapier Tool in main.py

main.py

@@ -1,99 +1,9 @@
+
 from flask import Flask, request, jsonify
 import os
 from twilio.twiml.messaging_response import MessagingResponse
 from langchain.agents import initialize_agent, AgentType
 from langchain_community.chat_models import ChatOpenAI
 from langchain.schema import SystemMessage
 from langchain.prompts import MessagesPlaceholder
-from langchain.memory import ConversationSummaryBufferMemory
-from Agent_Tools.tools import ExtractTillInformationTool, ExtractQrCodeInformationTool
-from Functions.Browsing.functions import SearchTool
-# from Functions.Apify.functions import CrawlWebsiteTool
-from Functions.Mpesa.till.functions import PaymentTillTool
-from Functions.Mpesa.paybill.functions import PaymentPaybillTool
-from Functions.Mpesa.qr_code.functions import QrCodeTool
-from dotenv import load_dotenv
-
-app = Flask(__name__)
-
-load_dotenv()
-
-llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-16k-0613")
-
-system_message = SystemMessage(content="""
-    " You are Bee, a helpful Assistant!",
-    " As a wordlclass helpful assistant with more than 40 years of experience, you make sure users have a seamless conversation with you.",
-    " Your will be helping users using the tools available for you, the tools include:",
-
-    "- ExtractInformationTool() -> Use this when extracting the required information from users query",
-    "- PaymentTillTool() -> Use this to initiate payments to till accounts",
-    "- PaymentPaybillTool()-> Use this to initiate payments to paybill accounts"
-    "- ExtractQrCodeInformationTool() -> Use this to extract qrcode informations
-    "- QrCodeTool() -> use this to generate qrcode" 
-    "- SearchTool() -> Use this to do a search on the web using googleserper",
-    "- CrawlWebsiteTool, -> Use this to crawl websites"
-    " Your goal is to interpret user input, understand their intentions, and categorize them to streamline a smooth conversation",
-    " You are capable of browsing the web using the search tool and making payments .",
-    " Use the  search to add Emojis in your conversation"
-    " Respond with the language the user uses. If the uses texts in 'English' respond in 'English, If the user texts in 'Sheng' respond in 'Sheng'."
-    " Don't make thinbs up"
-    """)
-
-
-tools = [
-    ExtractTillInformationTool(), 
-    PaymentTillTool(),
-    PaymentPaybillTool(), 
-    ExtractQrCodeInformationTool(), 
-    QrCodeTool(),
-    SearchTool(),
-    # CrawlWebsiteTool(),
-]
-
-agent_kwargs = {
-    "extra_prompt_message": [MessagesPlaceholder(variable_name="memory")],
-    "system_message": system_message,
-}
-
-memory = ConversationSummaryBufferMemory(memory_key="memory",
-                                         return_messages=True,
-                                         llm=llm,
-                                         max_token_limit=250)
-
-
-agent = initialize_agent(
-    tools,
-    llm,
-    agent=AgentType.OPENAI_FUNCTIONS,
-    verbose=True,
-    agent_kwargs=agent_kwargs,
-    memory=memory,
-    user_input_key="input"
-)
-
-# Continuous conversation loop
-@app.route("/chat", methods=["POST"])
-def chat():
-    try:
-        user_input = request.form["Body"]
-    except Exception as e:
-        return jsonify({"error": str(e)}), 400  
-    if user_input.lower() == "end":
-        return jsonify({
-            "message": "Have a good day!"
-        })
-
-    agent_response = agent({"input": user_input})
-    print("Agent Response:", agent_response)  
-
-    assistant_message_content = agent_response.get(
-        "output", "No response from the assistant.")
-
-    twilio_resp = MessagingResponse()
-    twilio_resp.message(assistant_message_content)
-
-    return str(twilio_resp)
-
-
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=5000, debug=True)
+from langchain.memory import ConversationSummaryBufferM