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def agent_executor(): |
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from dotenv import load_dotenv |
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load_dotenv(); |
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from agent.toolset import tools |
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from agent.prompt import prompt |
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from langchain_openai import ChatOpenAI |
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llm = ChatOpenAI(model="gpt-4", temperature=0) |
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from langchain_community.tools.convert_to_openai import format_tool_to_openai_function |
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llm_with_tools = llm.bind(functions=[format_tool_to_openai_function(t) for t in tools]) |
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from langchain.agents.format_scratchpad import format_to_openai_function_messages |
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from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser |
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agent = ( |
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{ |
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"input": lambda x: x["input"], |
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"agent_scratchpad": lambda x: format_to_openai_function_messages( |
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x["intermediate_steps"] |
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), |
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} |
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| prompt |
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| llm_with_tools |
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| OpenAIFunctionsAgentOutputParser() |
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) |
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from langchain.agents import AgentExecutor |
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agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) |
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return agent_executor.invoke({"input": "What is Rise?"})['output'] |
