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<!-- Thank you for contributing to LangChain! Replace this comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced and you'd like a mention, we'll gladly shout you out! If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. Maintainer responsibilities: - General / Misc / if you don't know who to tag: @dev2049 - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev - Models / Prompts: @hwchase17, @dev2049 - Memory: @hwchase17 - Agents / Tools / Toolkits: @vowelparrot - Tracing / Callbacks: @agola11 - Async: @agola11 If no one reviews your PR within a few days, feel free to @-mention the same people again. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md -->
387 lines
11 KiB
Plaintext
387 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "g9EmNu5DD9YI"
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},
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"source": [
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"# Custom functions with OpenAI Functions Agent\n",
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"\n",
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"This notebook goes through how to integrate custom functions with OpenAI Functions agent."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "LFKylC3CPtTl"
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},
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"source": [
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"Install libraries which are required to run this example notebook\n",
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"\n",
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"`pip install -q openai langchain yfinance`"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "E2DqzmEGDPak"
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},
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"source": [
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"## Define custom functions"
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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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"metadata": {
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"id": "SiucthMs6SIK"
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},
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"outputs": [],
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"source": [
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"import yfinance as yf\n",
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"from datetime import datetime, timedelta\n",
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"\n",
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"def get_current_stock_price(ticker):\n",
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" \"\"\"Method to get current stock price\"\"\"\n",
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"\n",
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" ticker_data = yf.Ticker(ticker)\n",
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" recent = ticker_data.history(period='1d')\n",
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" return {\n",
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" 'price': recent.iloc[0]['Close'],\n",
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" 'currency': ticker_data.info['currency']\n",
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" }\n",
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"\n",
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"def get_stock_performance(ticker, days):\n",
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" \"\"\"Method to get stock price change in percentage\"\"\"\n",
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"\n",
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" past_date = datetime.today() - timedelta(days=days)\n",
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" ticker_data = yf.Ticker(ticker)\n",
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" history = ticker_data.history(start=past_date)\n",
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" old_price = history.iloc[0]['Close']\n",
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" current_price = history.iloc[-1]['Close']\n",
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" return {\n",
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" 'percent_change': ((current_price - old_price)/old_price)*100\n",
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" }"
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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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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "vRLINGvQR1rO",
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"outputId": "68230a4b-dda2-4273-b956-7439661e3785"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'price': 334.57000732421875, 'currency': 'USD'}"
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]
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},
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"execution_count": 3,
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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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"get_current_stock_price('MSFT')"
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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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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "57T190q235mD",
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"outputId": "c6ee66ec-0659-4632-85d1-263b08826e68"
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'percent_change': 1.014466941163018}"
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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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"get_stock_performance('MSFT', 30)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "MT8QsdyBDhwg"
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},
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"source": [
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"## Make custom tools"
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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": 5,
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"metadata": {
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"id": "NvLOUv-XP3Ap"
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},
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"outputs": [],
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"source": [
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"from typing import Type\n",
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"from pydantic import BaseModel, Field\n",
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"from langchain.tools import BaseTool\n",
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"\n",
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"class CurrentStockPriceInput(BaseModel):\n",
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" \"\"\"Inputs for get_current_stock_price\"\"\"\n",
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" ticker: str = Field(description=\"Ticker symbol of the stock\")\n",
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"\n",
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"class CurrentStockPriceTool(BaseTool):\n",
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" name = \"get_current_stock_price\"\n",
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" description = \"\"\"\n",
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" Useful when you want to get current stock price.\n",
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" You should enter the stock ticker symbol recognized by the yahoo finance\n",
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" \"\"\"\n",
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" args_schema: Type[BaseModel] = CurrentStockPriceInput\n",
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"\n",
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" def _run(self, ticker: str):\n",
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" price_response = get_current_stock_price(ticker)\n",
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" return price_response\n",
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"\n",
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" def _arun(self, ticker: str):\n",
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" raise NotImplementedError(\"get_current_stock_price does not support async\")\n",
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"\n",
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"\n",
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"class StockPercentChangeInput(BaseModel):\n",
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" \"\"\"Inputs for get_stock_performance\"\"\"\n",
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" ticker: str = Field(description=\"Ticker symbol of the stock\")\n",
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" days: int = Field(description='Timedelta days to get past date from current date')\n",
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"\n",
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"class StockPerformanceTool(BaseTool):\n",
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" name = \"get_stock_performance\"\n",
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" description = \"\"\"\n",
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" Useful when you want to check performance of the stock.\n",
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" You should enter the stock ticker symbol recognized by the yahoo finance.\n",
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" You should enter days as number of days from today from which performance needs to be check.\n",
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" output will be the change in the stock price represented as a percentage.\n",
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" \"\"\"\n",
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" args_schema: Type[BaseModel] = StockPercentChangeInput\n",
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"\n",
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" def _run(self, ticker: str, days: int):\n",
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" response = get_stock_performance(ticker, days)\n",
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" return response\n",
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"\n",
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" def _arun(self, ticker: str):\n",
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" raise NotImplementedError(\"get_stock_performance does not support async\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "PVKoqeCyFKHF"
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},
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"source": [
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"## Create Agent"
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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": 6,
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"metadata": {
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"id": "yY7qNB7vSQGh"
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},
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"outputs": [],
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"source": [
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"from langchain.agents import AgentType\n",
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"from langchain.chat_models import ChatOpenAI\n",
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"from langchain.agents import initialize_agent\n",
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"\n",
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"llm = ChatOpenAI(\n",
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" model=\"gpt-3.5-turbo-0613\",\n",
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" temperature=0\n",
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")\n",
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"\n",
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"tools = [\n",
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" CurrentStockPriceTool(),\n",
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" StockPerformanceTool()\n",
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"]\n",
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"\n",
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"agent = initialize_agent(tools, llm, agent=AgentType.OPENAI_FUNCTIONS, 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": 7,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 321
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},
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"id": "4X96xmgwRkcC",
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"outputId": "a91b13ef-9643-4f60-d067-c4341e0b285e"
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},
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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 chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3m\n",
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"Invoking: `get_current_stock_price` with `{'ticker': 'MSFT'}`\n",
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"\n",
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"\n",
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"\u001b[0m\u001b[36;1m\u001b[1;3m{'price': 334.57000732421875, 'currency': 'USD'}\u001b[0m\u001b[32;1m\u001b[1;3m\n",
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"Invoking: `get_stock_performance` with `{'ticker': 'MSFT', 'days': 180}`\n",
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"\n",
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"\n",
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"\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",
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"\n",
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"Over the past 6 months, Microsoft stock has performed well with a 40.16% increase in its price.\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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"'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.'"
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]
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},
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"execution_count": 7,
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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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"agent.run(\"What is the current price of Microsoft stock? How it has performed over past 6 months?\")"
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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": 9,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 285
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},
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"id": "nkZ_vmAcT7Al",
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"outputId": "092ebc55-4d28-4a4b-aa2a-98ae47ceec20"
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},
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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 chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3m\n",
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"Invoking: `get_current_stock_price` with `{'ticker': 'GOOGL'}`\n",
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"\n",
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"\n",
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"\u001b[0m\u001b[36;1m\u001b[1;3m{'price': 118.33000183105469, 'currency': 'USD'}\u001b[0m\u001b[32;1m\u001b[1;3m\n",
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"Invoking: `get_current_stock_price` with `{'ticker': 'META'}`\n",
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"\n",
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"\n",
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"\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",
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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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"'The recent stock price of Google (GOOGL) is $118.33 USD and the recent stock price of Meta (META) is $287.05 USD.'"
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]
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},
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"execution_count": 9,
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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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"agent.run(\"Give me recent stock prices of Google and Meta?\")"
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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": 11,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 466
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},
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"id": "jLU-HjMq7n1o",
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"outputId": "a42194dd-26ed-4b5a-d4a2-1038420045c4"
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},
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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 chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3m\n",
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"Invoking: `get_stock_performance` with `{'ticker': 'MSFT', 'days': 90}`\n",
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"\n",
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"\n",
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"\u001b[0m\u001b[33;1m\u001b[1;3m{'percent_change': 18.043096235165596}\u001b[0m\u001b[32;1m\u001b[1;3m\n",
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"Invoking: `get_stock_performance` with `{'ticker': 'GOOGL', 'days': 90}`\n",
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"\n",
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"\n",
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"\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",
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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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"\"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%.\""
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]
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},
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"execution_count": 11,
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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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"agent.run('In the past 3 months, which stock between Microsoft and Google has performed the best?')"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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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": "3.9.16"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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