langchain/docs/modules/agents/plan_and_execute.ipynb

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"## Plan and Execute\n",
"\n",
"Plan and execute agents accomplish an objective by first planning what to do, then executing the sub tasks. This idea is largely inspired by [BabyAGI](https://github.com/yoheinakajima/babyagi) and then the [\"Plan-and-Solve\" paper](https://arxiv.org/abs/2305.04091).\n",
"\n",
"The planning is almost always done by an LLM.\n",
"\n",
"The execution is usually done by a separate agent (equipped with tools)."
]
},
{
"attachments": {},
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"cell_type": "markdown",
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"source": [
"## Imports"
]
},
{
"cell_type": "code",
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"source": [
"from langchain.chat_models import ChatOpenAI\n",
"from langchain.experimental.plan_and_execute import PlanAndExecute, load_agent_executor, load_chat_planner\n",
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"from langchain.llms import OpenAI\n",
"from langchain import SerpAPIWrapper\n",
"from langchain.agents.tools import Tool\n",
"from langchain import LLMMathChain"
]
},
{
"attachments": {},
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"cell_type": "markdown",
"id": "0b10d200",
"metadata": {},
"source": [
"## Tools"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3c00f724",
"metadata": {},
"outputs": [],
"source": [
"search = SerpAPIWrapper()\n",
"llm = OpenAI(temperature=0)\n",
"llm_math_chain = LLMMathChain.from_llm(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",
"]"
]
},
{
"attachments": {},
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"cell_type": "markdown",
"id": "ce38ae84",
"metadata": {},
"source": [
"## Planner, Executor, and Agent"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0ab2cadd",
"metadata": {},
"outputs": [],
"source": [
"model = ChatOpenAI(temperature=0)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "7b2419f2",
"metadata": {},
"outputs": [],
"source": [
"planner = load_chat_planner(model)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ed9f518b",
"metadata": {},
"outputs": [],
"source": [
"executor = load_agent_executor(model, tools, verbose=True)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "36943178",
"metadata": {},
"outputs": [],
"source": [
"agent = PlanAndExecute(planner=planner, executor=executor, verbose=True)"
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]
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{
"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
"source": [
"## Run Example"
]
},
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"cell_type": "code",
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"scrolled": false
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"text": [
"\n",
"\n",
"\u001b[1m> Entering new PlanAndExecute chain...\u001b[0m\n",
"steps=[Step(value=\"Search for Leo DiCaprio's girlfriend on the internet.\"), Step(value='Find her current age.'), Step(value='Raise her current age to the 0.43 power using a calculator or programming language.'), Step(value='Output the result.'), Step(value=\"Given the above steps taken, respond to the user's original question.\\n\\n\")]\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mAction:\n",
"```\n",
"{\n",
" \"action\": \"Search\",\n",
" \"action_input\": \"Who is Leo DiCaprio's girlfriend?\"\n",
"}\n",
"``` \n",
"\n",
"\u001b[0m\n",
"Observation: \u001b[36;1m\u001b[1;3mDiCaprio broke up with girlfriend Camila Morrone, 25, in the summer of 2022, after dating for four years. He's since been linked to another famous supermodel Gigi Hadid. The power couple were first supposedly an item in September after being spotted getting cozy during a party at New York Fashion Week.\u001b[0m\n",
"Thought:\u001b[32;1m\u001b[1;3mBased on the previous observation, I can provide the answer to the current objective. \n",
"Action:\n",
"```\n",
"{\n",
" \"action\": \"Final Answer\",\n",
" \"action_input\": \"Leo DiCaprio is currently linked to Gigi Hadid.\"\n",
"}\n",
"```\n",
"\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n",
"*****\n",
"\n",
"Step: Search for Leo DiCaprio's girlfriend on the internet.\n",
"\n",
"Response: Leo DiCaprio is currently linked to Gigi Hadid.\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mAction:\n",
"```\n",
"{\n",
" \"action\": \"Search\",\n",
" \"action_input\": \"What is Gigi Hadid's current age?\"\n",
"}\n",
"```\n",
"\u001b[0m\n",
"Observation: \u001b[36;1m\u001b[1;3m28 years\u001b[0m\n",
"Thought:\u001b[32;1m\u001b[1;3mPrevious steps: steps=[(Step(value=\"Search for Leo DiCaprio's girlfriend on the internet.\"), StepResponse(response='Leo DiCaprio is currently linked to Gigi Hadid.'))]\n",
"\n",
"Current objective: value='Find her current age.'\n",
"\n",
"Action:\n",
"```\n",
"{\n",
" \"action\": \"Search\",\n",
" \"action_input\": \"What is Gigi Hadid's current age?\"\n",
"}\n",
"```\n",
"\n",
"\u001b[0m\n",
"Observation: \u001b[36;1m\u001b[1;3m28 years\u001b[0m\n",
"Thought:\u001b[32;1m\u001b[1;3mPrevious steps: steps=[(Step(value=\"Search for Leo DiCaprio's girlfriend on the internet.\"), StepResponse(response='Leo DiCaprio is currently linked to Gigi Hadid.')), (Step(value='Find her current age.'), StepResponse(response='28 years'))]\n",
"\n",
"Current objective: None\n",
"\n",
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"Action:\n",
"```\n",
"{\n",
" \"action\": \"Final Answer\",\n",
" \"action_input\": \"Gigi Hadid's current age is 28 years.\"\n",
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"}\n",
"```\n",
"\n",
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"\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n",
"*****\n",
"\n",
"Step: Find her current age.\n",
"\n",
"Response: Gigi Hadid's current age is 28 years.\n",
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"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mAction:\n",
"```\n",
"{\n",
" \"action\": \"Calculator\",\n",
" \"action_input\": \"28 ** 0.43\"\n",
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"}\n",
"```\n",
"\u001b[0m\n",
"\n",
"\u001b[1m> Entering new LLMMathChain chain...\u001b[0m\n",
"28 ** 0.43\u001b[32;1m\u001b[1;3m\n",
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"```text\n",
"28 ** 0.43\n",
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"```\n",
"...numexpr.evaluate(\"28 ** 0.43\")...\n",
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"\u001b[0m\n",
"Answer: \u001b[33;1m\u001b[1;3m4.1906168361987195\u001b[0m\n",
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"\u001b[1m> Finished chain.\u001b[0m\n",
"\n",
"Observation: \u001b[33;1m\u001b[1;3mAnswer: 4.1906168361987195\u001b[0m\n",
"Thought:\u001b[32;1m\u001b[1;3mThe next step is to provide the answer to the user's question.\n",
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"\n",
"Action:\n",
"```\n",
"{\n",
" \"action\": \"Final Answer\",\n",
" \"action_input\": \"Gigi Hadid's current age raised to the 0.43 power is approximately 4.19.\"\n",
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"}\n",
"```\n",
"\n",
"\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n",
"*****\n",
"\n",
"Step: Raise her current age to the 0.43 power using a calculator or programming language.\n",
"\n",
"Response: Gigi Hadid's current age raised to the 0.43 power is approximately 4.19.\n",
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"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mAction:\n",
"```\n",
"{\n",
" \"action\": \"Final Answer\",\n",
" \"action_input\": \"The result is approximately 4.19.\"\n",
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"}\n",
"```\n",
"\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n",
"*****\n",
"\n",
"Step: Output the result.\n",
"\n",
"Response: The result is approximately 4.19.\n",
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"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mAction:\n",
"```\n",
"{\n",
" \"action\": \"Final Answer\",\n",
" \"action_input\": \"Gigi Hadid's current age raised to the 0.43 power is approximately 4.19.\"\n",
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"}\n",
"```\n",
"\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n",
"*****\n",
"\n",
"Step: Given the above steps taken, respond to the user's original question.\n",
"\n",
"\n",
"\n",
"Response: Gigi Hadid's current age raised to the 0.43 power is approximately 4.19.\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
]
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