forked from Archives/langchain
145 lines
4.1 KiB
Plaintext
145 lines
4.1 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "87455ddb",
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"metadata": {},
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"source": [
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"# Multi-Input Tools\n",
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"\n",
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"This notebook shows how to use a tool that requires multiple inputs with an agent.\n",
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"\n",
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"The difficulty in doing so comes from the fact that an agent decides its next step from a language model, which outputs a string. So if that step requires multiple inputs, they need to be parsed from that. Therefore, the currently supported way to do this is to write a smaller wrapper function that parses a string into multiple inputs.\n",
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"\n",
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"For a concrete example, let's work on giving an agent access to a multiplication function, which takes as input two integers. In order to use this, we will tell the agent to generate the \"Action Input\" as a comma-separated list of length two. We will then write a thin wrapper that takes a string, splits it into two around a comma, and passes both parsed sides as integers to the multiplication function."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "291149b6",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.llms import OpenAI\n",
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"from langchain.agents import initialize_agent, Tool\n",
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"from langchain.agents import AgentType"
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]
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},
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{
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"cell_type": "markdown",
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"id": "71b6bead",
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"metadata": {},
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"source": [
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"Here is the multiplication function, as well as a wrapper to parse a string as input."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "f0b82020",
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"metadata": {},
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"outputs": [],
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"source": [
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"def multiplier(a, b):\n",
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" return a * b\n",
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"\n",
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"def parsing_multiplier(string):\n",
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" a, b = string.split(\",\")\n",
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" return multiplier(int(a), int(b))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "6db1d43f",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = OpenAI(temperature=0)\n",
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"tools = [\n",
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" Tool(\n",
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" name = \"Multiplier\",\n",
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" func=parsing_multiplier,\n",
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" description=\"useful for when you need to multiply two numbers together. The input to this tool should be a comma separated list of numbers of length two, representing the two numbers you want to multiply together. For example, `1,2` would be the input if you wanted to multiply 1 by 2.\"\n",
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" )\n",
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"]\n",
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"mrkl = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "aa25d0ca",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3m I need to multiply two numbers\n",
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"Action: Multiplier\n",
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"Action Input: 3,4\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3m12\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
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"Final Answer: 3 times 4 is 12\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'3 times 4 is 12'"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"mrkl.run(\"What is 3 times 4\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7ea340c0",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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},
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"vscode": {
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"interpreter": {
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"hash": "b1677b440931f40d89ef8be7bf03acb108ce003de0ac9b18e8d43753ea2e7103"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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