Using a langchain tool in a Haystack agent

haystack-agent.py

def create_wolfram_alpha_tool():
    from haystack.agents import Tool
    from walpha_tool.tool import WolframAlphaNode

    node = WolframAlphaNode()
    return Tool(name="WolframAlpha",
                pipeline_or_node=node,
                description="A wrapper around Wolfram Alpha. " # Taken verbatim from the langchain code, could be done automatically somehow
                "Useful for when you need to answer questions about Math,"
                "Science, Technology, Culture, Society and Everyday Life."
                "Input should be a search query."
                )

langchain-tool-bridge.py

import os
from langchain.agents import load_tools
from langchain.agents import initialize_agent
from langchain.agents import AgentType
from langchain.llms import OpenAI
from haystack.nodes.base import BaseComponent


class WolframAlphaNode(BaseComponent):
    def __init__(self):
        super(WolframAlphaNode, self).__init__()
        self.agent = self.create_agent()

    outgoing_edges = 1

    def run(
            self,
            query: str = None
    ):
        print("running Wolfram Alpha")
        try:
            return self.agent.run(query)
        except Exception as e:
            print("Error: " + str(e))
            return "Sorry, an error has occured when using the tool."

    def create_agent(self):
        llm = OpenAI(temperature=0.2)

        tools = load_tools(
            ["wolfram-alpha", "llm-math"], wolfram_alpha_appid=os.environ["WOLFRAM_ALPHA_APPID"], llm=llm)
        agent = initialize_agent(
            tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)

        print("running agent")
        return agent

    def run_batch(
            self,
            query: str = None,
            **kwargs
    ):
        pass