{ "cells": [ { "cell_type": "markdown", "id": "ba5f8741", "metadata": {}, "source": [ "# Custom Agent\n", "\n", "This notebook goes through how to create your own custom agent.\n", "\n", "An agent consists of three parts:\n", " \n", " - Tools: The tools the agent has available to use.\n", " - The agent class itself: this decides which action to take.\n", " \n", " \n", "In this notebook we walk through how to create a custom agent." ] }, { "cell_type": "code", "execution_count": 1, "id": "9af9734e", "metadata": {}, "outputs": [], "source": [ "from langchain.agents import Tool, AgentExecutor, BaseSingleActionAgent\n", "from langchain import OpenAI, SerpAPIWrapper" ] }, { "cell_type": "code", "execution_count": 2, "id": "becda2a1", "metadata": {}, "outputs": [], "source": [ "search = SerpAPIWrapper()\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", " return_direct=True\n", " )\n", "]" ] }, { "cell_type": "code", "execution_count": 4, "id": "a33e2f7e", "metadata": {}, "outputs": [], "source": [ "from typing import List, Tuple, Any, Union\n", "from langchain.schema import AgentAction, AgentFinish\n", "\n", "class FakeAgent(BaseSingleActionAgent):\n", " \"\"\"Fake Custom Agent.\"\"\"\n", " \n", " @property\n", " def input_keys(self):\n", " return [\"input\"]\n", " \n", " def plan(\n", " self, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any\n", " ) -> Union[AgentAction, AgentFinish]:\n", " \"\"\"Given input, decided what to do.\n", "\n", " Args:\n", " intermediate_steps: Steps the LLM has taken to date,\n", " along with observations\n", " **kwargs: User inputs.\n", "\n", " Returns:\n", " Action specifying what tool to use.\n", " \"\"\"\n", " return AgentAction(tool=\"Search\", tool_input=\"foo\", log=\"\")\n", "\n", " async def aplan(\n", " self, intermediate_steps: List[Tuple[AgentAction, str]], **kwargs: Any\n", " ) -> Union[AgentAction, AgentFinish]:\n", " \"\"\"Given input, decided what to do.\n", "\n", " Args:\n", " intermediate_steps: Steps the LLM has taken to date,\n", " along with observations\n", " **kwargs: User inputs.\n", "\n", " Returns:\n", " Action specifying what tool to use.\n", " \"\"\"\n", " return AgentAction(tool=\"Search\", tool_input=\"foo\", log=\"\")" ] }, { "cell_type": "code", "execution_count": 5, "id": "655d72f6", "metadata": {}, "outputs": [], "source": [ "agent = FakeAgent()" ] }, { "cell_type": "code", "execution_count": 6, "id": "490604e9", "metadata": {}, "outputs": [], "source": [ "agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)" ] }, { "cell_type": "code", "execution_count": 7, "id": "653b1617", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", "\u001b[32;1m\u001b[1;3m\u001b[0m\u001b[36;1m\u001b[1;3mFoo Fighters is an American rock band formed in Seattle in 1994. Foo Fighters was initially formed as a one-man project by former Nirvana drummer Dave Grohl. Following the success of the 1995 eponymous debut album, Grohl recruited a band consisting of Nate Mendel, William Goldsmith, and Pat Smear.\u001b[0m\u001b[32;1m\u001b[1;3m\u001b[0m\n", "\n", "\u001b[1m> Finished chain.\u001b[0m\n" ] }, { "data": { "text/plain": [ "'Foo Fighters is an American rock band formed in Seattle in 1994. Foo Fighters was initially formed as a one-man project by former Nirvana drummer Dave Grohl. Following the success of the 1995 eponymous debut album, Grohl recruited a band consisting of Nate Mendel, William Goldsmith, and Pat Smear.'" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "agent_executor.run(\"How many people live in canada as of 2023?\")" ] }, { "cell_type": "code", "execution_count": null, "id": "adefb4c2", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.1" }, "vscode": { "interpreter": { "hash": "18784188d7ecd866c0586ac068b02361a6896dc3a29b64f5cc957f09c590acef" } } }, "nbformat": 4, "nbformat_minor": 5 }