55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
from langchain import hub
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from langchain.agents import AgentExecutor, create_react_agent, load_tools
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from langchain.tools import tool
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from langchain_openai import ChatOpenAI
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from langchain_community.utilities.dalle_image_generator import DallEAPIWrapper
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from langchain_community.tools.google_jobs import GoogleJobsQueryRun
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from langchain_community.utilities.google_jobs import GoogleJobsAPIWrapper
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from dotenv import load_dotenv
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from tools import lookup_ip, lookup_name, search_ksp
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# from langsmith import Client
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"""
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This is the main runner of the custom agent. Custom agent tools are defined seperatly and imported from tools.py
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Adapted from https://github.com/wu4f/cs410g-src/blob/main/04_Agents/07_tools_custom_agent.py
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Langsmith code can be uncommeted for testing/debugging
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"""
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load_dotenv()
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# os.environ["LANGCHAIN_TRACING_V2"] = "true"
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# os.environ["LANGCHAIN_PROJECT"] = f"LangSmith Introduction"
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# os.environ["LANGCHAIN_ENDPOINT"] = "https://api.smith.langchain.com"
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# client = Client()
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llm = ChatOpenAI(model_name="gpt-4-turbo", temperature=0)
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tools = load_tools(
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["serpapi", "terminal", "dalle-image-generator", "google-jobs"],
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allow_dangerous_tools=True,
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llm=llm,
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)
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tools.extend([lookup_name, lookup_ip, search_ksp])
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base_prompt = hub.pull("langchain-ai/react-agent-template")
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prompt = base_prompt.partial(
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instructions="Answer the user's request utilizing at most 8 tool calls"
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)
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agent = create_react_agent(llm, tools, prompt)
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agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)
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print("Welcome to my application. I am configured with these tools:")
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for tool in agent_executor.tools:
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print(f" Tool: {tool.name} = {tool.description}")
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while True:
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line = input("llm>> ")
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try:
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if line:
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result = agent_executor.invoke({"input": line})
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print(result)
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else:
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break
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except Exception as e:
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print(e)
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