langchain/docs/examples/agents/custom_tools.ipynb

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    "# Defining Custom Tools\n",
    "\n",
    "When constructing your own agent, you will need to provide it with a list of Tools that it can use. A Tool is defined as below.\n",
    "\n",
    "```python\n",
    "class Tool(NamedTuple):\n",
    "    \"\"\"Interface for tools.\"\"\"\n",
    "\n",
    "    name: str\n",
    "    func: Callable[[str], str]\n",
    "    description: Optional[str] = None\n",
    "```\n",
    "\n",
    "The two required components of a Tool are the name and then the tool itself. A tool description is optional, as it is needed for some agents but not all."
   ]
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    "# Import things that are needed generically\n",
    "from langchain.agents import initialize_agent, Tool\n",
    "from langchain.llms import OpenAI\n",
    "from langchain import LLMMathChain, SerpAPIWrapper"
   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "Initialize the LLM to use for the agent."
   ]
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   "id": "36ed392e",
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   "source": [
    "llm = OpenAI(temperature=0)"
   ]
  },
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    "# Load the tool configs that are needed.\n",
    "search = SerpAPIWrapper()\n",
    "llm_math_chain = LLMMathChain(llm=llm, verbose=True)\n",
    "tools = [\n",
    "    Tool(\n",
    "        name = \"Search\",\n",
    "        func=search.run,\n",
    "        description=\"useful for when you need to answer questions about current events\"\n",
    "    ),\n",
    "    Tool(\n",
    "        name=\"Calculator\",\n",
    "        func=llm_math_chain.run,\n",
    "        description=\"useful for when you need to answer questions about math\"\n",
    "    )\n",
    "]"
   ]
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   "source": [
    "# Construct the agent. We will use the default agent type here.\n",
    "# See documentation for a full list of options.\n",
    "llm = OpenAI(temperature=0)\n",
    "agent = initialize_agent(tools, llm, agent=\"zero-shot-react-description\", verbose=True)"
   ]
  },
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      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3m I need to find out who Olivia Wilde's boyfriend is and then calculate his age raised to the 0.23 power.\n",
      "Action: Search\n",
      "Action Input: Olivia Wilde's boyfriend\u001b[0m\n",
      "Observation: \u001b[36;1m\u001b[1;3mOlivia Wilde started dating Harry Styles after ending her years-long engagement to Jason Sudeikis — see their relationship timeline.\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I need to find out Harry Styles' age.\n",
      "Action: Search\n",
      "Action Input: Harry Styles age\u001b[0m\n",
      "Observation: \u001b[36;1m\u001b[1;3m28 years\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I need to calculate 28 raised to the 0.23 power.\n",
      "Action: Calculator\n",
      "Action Input: 28^0.23\u001b[0m\n",
      "\n",
      "\u001b[1m> Entering new LLMMathChain chain...\u001b[0m\n",
      "28^0.23\u001b[32;1m\u001b[1;3m\n",
      "\n",
      "```python\n",
      "import math\n",
      "print(math.pow(28, 0.23))\n",
      "```\n",
      "\u001b[0m\n",
      "Answer: \u001b[33;1m\u001b[1;3m2.1520202182226886\n",
      "\u001b[0m\n",
      "\u001b[1m> Finished LLMMathChain chain.\u001b[0m\n",
      "\n",
      "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.1520202182226886\n",
      "\u001b[0m\n",
      "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n",
      "Final Answer: Harry Styles, Olivia Wilde's boyfriend, is 28 years old and his age raised to the 0.23 power is 2.1520202182226886.\u001b[0m\n",
      "\u001b[1m> Finished AgentExecutor chain.\u001b[0m\n"
     ]
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       "\"Harry Styles, Olivia Wilde's boyfriend, is 28 years old and his age raised to the 0.23 power is 2.1520202182226886.\""
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   "source": [
    "agent.run(\"Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?\")"
   ]
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