How to create a tool from a langchain toolkit that runs using initialize agent?

[ad3sai]

I am working on creating a library of tool for my personal use. One tool I am working on is to get data using an OpenAPI. Below is getting an error "Too many arguments". Any workaround or suggestions?

import os, yaml
import requests
from langchain.llms.openai import OpenAI
from langchain.agents.agent_toolkits.openapi import planner
from langchain.chat_models import ChatOpenAI, ChatAnthropic
from langchain.agents import load_tools, initialize_agent, AgentType, Tool
from langchain.chains.conversation.memory import ConversationBufferWindowMemory
from langchain.tools.python.tool import PythonREPLTool
from langchain.python import PythonREPL
from langchain.requests import RequestsWrapper
from langchain.agents.agent_toolkits.openapi.spec import reduce_openapi_spec

# openai api tool
url = "https://raw.githubusercontent.com/openai/openai-openapi/master/openapi.yaml"
file_name = "openai_openapi.yaml"

response = requests.get(url, verify=False)
with open(file_name, "wb") as file:
    file.write(response.content)
    
with open("openai_openapi.yaml") as f:
    raw_openai_api_spec = yaml.load(f, Loader=yaml.Loader)
openai_api_spec = reduce_openapi_spec(raw_openai_api_spec)

headers = {
    "Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}"
}
openai_requests_wrapper=RequestsWrapper(headers=headers)
llm = ChatOpenAI(temperature=0) #OpenAI(model_name="gpt-4", temperature=0.25)
openai_agent = planner.create_openapi_agent(openai_api_spec, openai_requests_wrapper, llm)

def open_api_response(user_query, **kwargs):
    response = openai_agent.run(user_query)
    return response

openai_api_tool = Tool(
    name = "OpenAI API",
    func = open_api_response,
    description = """Useful when you need information directly from OpenAI regarding any topic.
    """
    
)

# Define available tools
available_tools = {
    'Math': "llm-math",
    'Open AI API Tool': openai_api_tool
}

# model selection
llm = ChatOpenAI(temperature=0)

# loading selected tools
tools = load_tools([available_tools[tool] for tool in available_tools.keys()
                    if isinstance(available_tools[tool], str) == True], llm=llm)
tools += [available_tools[tool] for tool in available_tools.keys()
                    if isinstance(available_tools[tool], str) != True]

# conversational agent memory
memory = ConversationBufferWindowMemory(
    memory_key='chat_history',
    k=5,
    return_messages=True
)

# Initialize agent 
agent = initialize_agent(
    tools=tools, 
    llm=llm, 
    agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
    memory=memory,
    handle_parsing_errors=True,
    verbose = True)

query = "get me a very short random paragraph using openai"

agent(query)