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83 lines
2.2 KiB
83 lines
2.2 KiB
from typing import List, Optional
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from langchain.agents import AgentExecutor, LLMSingleActionAgent, Tool
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from langchain.chains import LLMChain
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from langchain.llms import OpenAI
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from langchain.prompts import StringPromptTemplate
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from langchain.tools import DuckDuckGoSearchRun
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from swarms import Agent
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class LangchainAgentWrapper(Agent):
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"""
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Initialize the LangchainAgentWrapper.
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Args:
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name (str): The name of the agent.
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tools (List[Tool]): The list of tools available to the agent.
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llm (Optional[OpenAI], optional): The OpenAI language model to use. Defaults to None.
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"""
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def __init__(
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self,
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name: str,
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tools: List[Tool],
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llm: Optional[OpenAI] = None,
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*args,
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**kwargs,
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):
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super().__init__(*args, **kwargs)
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self.name = name
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self.tools = tools
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self.llm = llm or OpenAI(temperature=0)
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prompt = StringPromptTemplate.from_template(
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"You are {name}, an AI assistant. Answer the following question: {question}"
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)
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llm_chain = LLMChain(llm=self.llm, prompt=prompt)
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tool_names = [tool.name for tool in self.tools]
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self.agent = LLMSingleActionAgent(
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llm_chain=llm_chain,
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output_parser=None,
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stop=["\nObservation:"],
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allowed_tools=tool_names,
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)
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self.agent_executor = AgentExecutor.from_agent_and_tools(
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agent=self.agent, tools=self.tools, verbose=True
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)
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def run(self, task: str, *args, **kwargs):
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"""
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Run the agent with the given task.
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Args:
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task (str): The task to be performed by the agent.
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Returns:
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Any: The result of the agent's execution.
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"""
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try:
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return self.agent_executor.run(task)
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except Exception as e:
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print(f"An error occurred: {e}")
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# Usage example
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search_tool = DuckDuckGoSearchRun()
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tools = [
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Tool(
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name="Search",
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func=search_tool.run,
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description="Useful for searching the internet",
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)
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]
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langchain_wrapper = LangchainAgentWrapper("LangchainAssistant", tools)
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result = langchain_wrapper.run("What is the capital of France?")
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print(result)
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