langchain/docs/extras/modules/agents/how_to/custom-functions-with-openai-functions-agent.ipynb
seamusp afd96b2460
docs: agents & callbacks fixes (#10066)
Various improvements to the Agents & Callbacks sections of the
documentation including formatting, spelling, and grammar fixes to
improve readability.
2023-09-01 13:28:55 -07:00

389 lines
11 KiB
Plaintext

{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "g9EmNu5DD9YI"
},
"source": [
"# Custom functions with OpenAI Functions Agent\n",
"\n",
"This notebook goes through how to integrate custom functions with OpenAI Functions agent."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "LFKylC3CPtTl"
},
"source": [
"Install libraries which are required to run this example notebook:\n",
"\n",
"```bash\n",
"pip install -q openai langchain yfinance\n",
"```\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "E2DqzmEGDPak"
},
"source": [
"## Define custom functions"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "SiucthMs6SIK"
},
"outputs": [],
"source": [
"import yfinance as yf\n",
"from datetime import datetime, timedelta\n",
"\n",
"\n",
"def get_current_stock_price(ticker):\n",
" \"\"\"Method to get current stock price\"\"\"\n",
"\n",
" ticker_data = yf.Ticker(ticker)\n",
" recent = ticker_data.history(period=\"1d\")\n",
" return {\"price\": recent.iloc[0][\"Close\"], \"currency\": ticker_data.info[\"currency\"]}\n",
"\n",
"\n",
"def get_stock_performance(ticker, days):\n",
" \"\"\"Method to get stock price change in percentage\"\"\"\n",
"\n",
" past_date = datetime.today() - timedelta(days=days)\n",
" ticker_data = yf.Ticker(ticker)\n",
" history = ticker_data.history(start=past_date)\n",
" old_price = history.iloc[0][\"Close\"]\n",
" current_price = history.iloc[-1][\"Close\"]\n",
" return {\"percent_change\": ((current_price - old_price) / old_price) * 100}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "vRLINGvQR1rO",
"outputId": "68230a4b-dda2-4273-b956-7439661e3785"
},
"outputs": [
{
"data": {
"text/plain": [
"{'price': 334.57000732421875, 'currency': 'USD'}"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"get_current_stock_price(\"MSFT\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "57T190q235mD",
"outputId": "c6ee66ec-0659-4632-85d1-263b08826e68"
},
"outputs": [
{
"data": {
"text/plain": [
"{'percent_change': 1.014466941163018}"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"get_stock_performance(\"MSFT\", 30)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "MT8QsdyBDhwg"
},
"source": [
"## Make custom tools"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "NvLOUv-XP3Ap"
},
"outputs": [],
"source": [
"from typing import Type\n",
"from pydantic import BaseModel, Field\n",
"from langchain.tools import BaseTool\n",
"\n",
"\n",
"class CurrentStockPriceInput(BaseModel):\n",
" \"\"\"Inputs for get_current_stock_price\"\"\"\n",
"\n",
" ticker: str = Field(description=\"Ticker symbol of the stock\")\n",
"\n",
"\n",
"class CurrentStockPriceTool(BaseTool):\n",
" name = \"get_current_stock_price\"\n",
" description = \"\"\"\n",
" Useful when you want to get current stock price.\n",
" You should enter the stock ticker symbol recognized by the yahoo finance\n",
" \"\"\"\n",
" args_schema: Type[BaseModel] = CurrentStockPriceInput\n",
"\n",
" def _run(self, ticker: str):\n",
" price_response = get_current_stock_price(ticker)\n",
" return price_response\n",
"\n",
" def _arun(self, ticker: str):\n",
" raise NotImplementedError(\"get_current_stock_price does not support async\")\n",
"\n",
"\n",
"class StockPercentChangeInput(BaseModel):\n",
" \"\"\"Inputs for get_stock_performance\"\"\"\n",
"\n",
" ticker: str = Field(description=\"Ticker symbol of the stock\")\n",
" days: int = Field(description=\"Timedelta days to get past date from current date\")\n",
"\n",
"\n",
"class StockPerformanceTool(BaseTool):\n",
" name = \"get_stock_performance\"\n",
" description = \"\"\"\n",
" Useful when you want to check performance of the stock.\n",
" You should enter the stock ticker symbol recognized by the yahoo finance.\n",
" You should enter days as number of days from today from which performance needs to be check.\n",
" output will be the change in the stock price represented as a percentage.\n",
" \"\"\"\n",
" args_schema: Type[BaseModel] = StockPercentChangeInput\n",
"\n",
" def _run(self, ticker: str, days: int):\n",
" response = get_stock_performance(ticker, days)\n",
" return response\n",
"\n",
" def _arun(self, ticker: str):\n",
" raise NotImplementedError(\"get_stock_performance does not support async\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PVKoqeCyFKHF"
},
"source": [
"## Create Agent"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"id": "yY7qNB7vSQGh"
},
"outputs": [],
"source": [
"from langchain.agents import AgentType\n",
"from langchain.chat_models import ChatOpenAI\n",
"from langchain.agents import initialize_agent\n",
"\n",
"llm = ChatOpenAI(model=\"gpt-3.5-turbo-0613\", temperature=0)\n",
"\n",
"tools = [CurrentStockPriceTool(), StockPerformanceTool()]\n",
"\n",
"agent = initialize_agent(tools, llm, agent=AgentType.OPENAI_FUNCTIONS, verbose=True)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 321
},
"id": "4X96xmgwRkcC",
"outputId": "a91b13ef-9643-4f60-d067-c4341e0b285e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m\n",
"Invoking: `get_current_stock_price` with `{'ticker': 'MSFT'}`\n",
"\n",
"\n",
"\u001b[0m\u001b[36;1m\u001b[1;3m{'price': 334.57000732421875, 'currency': 'USD'}\u001b[0m\u001b[32;1m\u001b[1;3m\n",
"Invoking: `get_stock_performance` with `{'ticker': 'MSFT', 'days': 180}`\n",
"\n",
"\n",
"\u001b[0m\u001b[33;1m\u001b[1;3m{'percent_change': 40.163963297187905}\u001b[0m\u001b[32;1m\u001b[1;3mThe current price of Microsoft stock is $334.57 USD. \n",
"\n",
"Over the past 6 months, Microsoft stock has performed well with a 40.16% increase in its price.\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"'The current price of Microsoft stock is $334.57 USD. \\n\\nOver the past 6 months, Microsoft stock has performed well with a 40.16% increase in its price.'"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"agent.run(\n",
" \"What is the current price of Microsoft stock? How it has performed over past 6 months?\"\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 285
},
"id": "nkZ_vmAcT7Al",
"outputId": "092ebc55-4d28-4a4b-aa2a-98ae47ceec20"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m\n",
"Invoking: `get_current_stock_price` with `{'ticker': 'GOOGL'}`\n",
"\n",
"\n",
"\u001b[0m\u001b[36;1m\u001b[1;3m{'price': 118.33000183105469, 'currency': 'USD'}\u001b[0m\u001b[32;1m\u001b[1;3m\n",
"Invoking: `get_current_stock_price` with `{'ticker': 'META'}`\n",
"\n",
"\n",
"\u001b[0m\u001b[36;1m\u001b[1;3m{'price': 287.04998779296875, 'currency': 'USD'}\u001b[0m\u001b[32;1m\u001b[1;3mThe recent stock price of Google (GOOGL) is $118.33 USD and the recent stock price of Meta (META) is $287.05 USD.\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"'The recent stock price of Google (GOOGL) is $118.33 USD and the recent stock price of Meta (META) is $287.05 USD.'"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"agent.run(\"Give me recent stock prices of Google and Meta?\")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 466
},
"id": "jLU-HjMq7n1o",
"outputId": "a42194dd-26ed-4b5a-d4a2-1038420045c4"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m\n",
"Invoking: `get_stock_performance` with `{'ticker': 'MSFT', 'days': 90}`\n",
"\n",
"\n",
"\u001b[0m\u001b[33;1m\u001b[1;3m{'percent_change': 18.043096235165596}\u001b[0m\u001b[32;1m\u001b[1;3m\n",
"Invoking: `get_stock_performance` with `{'ticker': 'GOOGL', 'days': 90}`\n",
"\n",
"\n",
"\u001b[0m\u001b[33;1m\u001b[1;3m{'percent_change': 17.286155760642853}\u001b[0m\u001b[32;1m\u001b[1;3mIn the past 3 months, Microsoft (MSFT) has performed better than Google (GOOGL). Microsoft's stock price has increased by 18.04% while Google's stock price has increased by 17.29%.\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"\"In the past 3 months, Microsoft (MSFT) has performed better than Google (GOOGL). Microsoft's stock price has increased by 18.04% while Google's stock price has increased by 17.29%.\""
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"agent.run(\n",
" \"In the past 3 months, which stock between Microsoft and Google has performed the best?\"\n",
")"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"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": "3.9.16"
}
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"nbformat": 4,
"nbformat_minor": 1
}