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Aaronwilkowitz/actions library (#1263)
Co-authored-by: Ilan Bigio <ilan@openai.com>
This commit is contained in:
Aaron Wilkowitz
GitHub
parent
fb202f0369
commit
9109a71839
265
examples/gpt_actions_library/.gpt_action_getting_started.ipynb
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265
examples/gpt_actions_library/.gpt_action_getting_started.ipynb
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{
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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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"source": [
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"# GPT Action Library: Getting Started (Weather.gov)"
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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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"source": [
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"## Introduction"
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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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"source": [
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"This page provides an instruction & guide for developers building a GPT Action for a specific application. Before you proceed, make sure to first familiarize yourself with the following information: \n",
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"- [Introduction to GPT Actions](https://platform.openai.com/docs/actions)\n",
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"- [Introduction to GPT Actions Library](https://platform.openai.com/docs/actions-library)\n",
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"- [Example of Buliding a GPT Action from Scratch](https://platform.openai.com/docs/getting-started)"
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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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"source": [
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"This particular GPT Action provides an overview of how to connect to a **Weather.gov** weather forecast. This Action takes a user’s question about a location, converts the lat-long into a weather forecast office (WFO), x, and y coordinates, then converts those 3 values into a weather forecast.\n",
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"\n",
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"Note: When setting up the GPT Action, for authentication, leave it with \"None\". This is a public API and does not require any Authentication"
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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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"source": [
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"## Application Information"
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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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"source": [
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"### Application Key Links"
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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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"source": [
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"Check out these links from the application before you get started:\n",
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"- Application Website: https://www.weather.gov/ \n",
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"- Application API Documentation: https://www.weather.gov/documentation/services-web-api "
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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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"source": [
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"## ChatGPT Steps"
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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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"source": [
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"### Custom GPT Instructions "
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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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"source": [
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"Once you've created a Custom GPT, copy the text below in the Instructions panel. Have questions? Check out [Getting Started Example](https://platform.openai.com/docs/getting-started) to see how this step works in more detail."
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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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"metadata": {
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"vscode": {
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"languageId": "plaintext"
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}
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},
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"outputs": [],
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"source": [
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"**Context**: A user needs information related to a weather forecast of a specific location.\n",
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"\n",
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"**Instructions**:\n",
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"1. The user will provide a lat-long point or a general location or landmark (e.g. New York City, the White House). If the user does not provide one, ask for the relevant location\n",
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"2. If the user provides a general location or landmark, convert that into a lat-long coordinate. If required, browse the web to look up the lat-long point. \n",
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"3. Run the \"getPointData\" API action and retrieve back the gridId, gridX, and gridY parameters.\n",
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"4. Apply those variables as the office, gridX, and gridY variables in the \"getGridpointForecast\" API action to retrieve back a forecast\n",
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"5. Use that forecast to answer the user's question \n",
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"\n",
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"**Additional Notes**: \n",
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"- Assume the user uses US weather units (e.g. Farenheit) unless otherwise specified\n",
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"- If the user says \"Let's get started\" or \"What do I do?\", explain the purpose of this Custom GPT"
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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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"source": [
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"### OpenAPI Schema "
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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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"source": [
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"Once you've created a Custom GPT, copy the text below in the Actions panel. Have questions? Check out [Getting Started Example](https://platform.openai.com/docs/getting-started) to see how this step works in more detail."
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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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"metadata": {
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"vscode": {
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"languageId": "yaml"
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}
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},
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"outputs": [],
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"source": [
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"openapi: 3.1.0\n",
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"info:\n",
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" title: NWS Weather API\n",
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" description: Access to weather data including forecasts, alerts, and observations.\n",
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" version: 1.0.0\n",
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"servers:\n",
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" - url: https://api.weather.gov\n",
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" description: Main API Server\n",
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"paths:\n",
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" /points/{latitude},{longitude}:\n",
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" get:\n",
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" operationId: getPointData\n",
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" summary: Get forecast grid endpoints for a specific location\n",
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" parameters:\n",
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" - name: latitude\n",
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" in: path\n",
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" required: true\n",
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" schema:\n",
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" type: number\n",
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" format: float\n",
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" description: Latitude of the point\n",
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" - name: longitude\n",
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" in: path\n",
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" required: true\n",
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" schema:\n",
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" type: number\n",
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" format: float\n",
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" description: Longitude of the point\n",
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" responses:\n",
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" '200':\n",
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" description: Successfully retrieved grid endpoints\n",
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" content:\n",
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" application/json:\n",
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" schema:\n",
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" type: object\n",
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" properties:\n",
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" properties:\n",
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" type: object\n",
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" properties:\n",
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" forecast:\n",
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" type: string\n",
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" format: uri\n",
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" forecastHourly:\n",
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" type: string\n",
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" format: uri\n",
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" forecastGridData:\n",
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" type: string\n",
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" format: uri\n",
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"\n",
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" /gridpoints/{office}/{gridX},{gridY}/forecast:\n",
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" get:\n",
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" operationId: getGridpointForecast\n",
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" summary: Get forecast for a given grid point\n",
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" parameters:\n",
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" - name: office\n",
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" in: path\n",
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" required: true\n",
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" schema:\n",
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" type: string\n",
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" description: Weather Forecast Office ID\n",
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" - name: gridX\n",
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" in: path\n",
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" required: true\n",
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" schema:\n",
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" type: integer\n",
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" description: X coordinate of the grid\n",
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" - name: gridY\n",
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" in: path\n",
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" required: true\n",
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" schema:\n",
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" type: integer\n",
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" description: Y coordinate of the grid\n",
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" responses:\n",
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" '200':\n",
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" description: Successfully retrieved gridpoint forecast\n",
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" content:\n",
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" application/json:\n",
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" schema:\n",
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" type: object\n",
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" properties:\n",
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" properties:\n",
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" type: object\n",
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" properties:\n",
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" periods:\n",
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" type: array\n",
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" items:\n",
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" type: object\n",
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" properties:\n",
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" number:\n",
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" type: integer\n",
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" name:\n",
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" type: string\n",
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" startTime:\n",
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" type: string\n",
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" format: date-time\n",
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" endTime:\n",
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" type: string\n",
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" format: date-time\n",
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" temperature:\n",
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" type: integer\n",
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" temperatureUnit:\n",
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" type: string\n",
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" windSpeed:\n",
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" type: string\n",
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" windDirection:\n",
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" type: string\n",
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" icon:\n",
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" type: string\n",
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" format: uri\n",
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" shortForecast:\n",
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" type: string\n",
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" detailedForecast:\n",
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" type: string"
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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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"source": [
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"### FAQ & Troubleshooting"
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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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"source": [
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"*Are there integrations that you’d like us to prioritize? Are there errors in our integrations? File a PR or issue in our github, and we’ll take a look.*\n"
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]
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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352
examples/gpt_actions_library/gpt_action_bigquery.ipynb
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352
examples/gpt_actions_library/gpt_action_bigquery.ipynb
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{
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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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"source": [
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"# GPT Action Library: BigQuery"
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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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"source": [
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"## Introduction"
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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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"source": [
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"This page provides an instruction & guide for developers building a GPT Action for a specific application. Before you proceed, make sure to first familiarize yourself with the following information: \n",
|
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"- [Introduction to GPT Actions](https://platform.openai.com/docs/actions)\n",
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"- [Introduction to GPT Actions Library](https://platform.openai.com/docs/actions-library)\n",
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"- [Example of Buliding a GPT Action from Scratch](https://platform.openai.com/docs/getting-started)"
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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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"source": [
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"This particular GPT Action provides an overview of how to connect to **Google BigQuery**, Google Cloud's Analytical Data Warehouse. This Action takes a user’s question, scans the relevant tables to gather the data schema, then writes a SQL query to answer the user’s question. \n",
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"\n",
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"Note: these instructions return back a functioning SQL statement, rather than the result itself. Currently middleware is required to return back a CSV file – we’ll be posting instructions on an example of that soon"
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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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"source": [
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"## Application Information"
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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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"source": [
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"### Application Key Links"
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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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"source": [
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"Check out these links from the application before you get started:\n",
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"- Application Website: https://cloud.google.com/bigquery \n",
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"- Application API Documentation: https://cloud.google.com/bigquery/docs/reference/rest "
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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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"source": [
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"### Application Prerequisites"
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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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"source": [
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"Before you get started, make sure you go through the following steps in your application environment:\n",
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"- Set up a GCP project \n",
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"- Set up a BQ dataset in that GCP project\n",
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"- Ensure that the user authenticating into BigQuery via ChatGPT has access to that BQ dataset "
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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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"source": [
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"## ChatGPT Steps"
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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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"source": [
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"### Custom GPT Instructions "
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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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"source": [
|
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"Once you've created a Custom GPT, copy the text below in the Instructions panel. Have questions? Check out [Getting Started Example](https://platform.openai.com/docs/getting-started) to see how this step works in more detail."
|
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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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"metadata": {
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"vscode": {
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"languageId": "plaintext"
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}
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},
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"outputs": [],
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"source": [
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"**Context**: You are an expert at writing BigQuery SQL queries. A user is going to ask you a question. \n",
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"\n",
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"**Instructions**:\n",
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"1. No matter the user's question, start by running `runQuery` operation using this query: \"SELECT column_name, table_name, data_type, description FROM `{project}.{dataset}.INFORMATION_SCHEMA.COLUMN_FIELD_PATHS`\" \n",
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"-- Assume project = \"<insert your default project here>\", dataset = \"<insert your default dataset here>\", unless the user provides different values \n",
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"-- Remember to include useLegacySql:false in the json output\n",
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"2. Convert the user's question into a SQL statement that leverages the step above and run the `runQuery` operation on that SQL statement to confirm the query works. Add a limit of 100 rows\n",
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"3. Now remove the limit of 100 rows and return back the query for the user to see\n",
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"\n",
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"**Additional Notes**: If the user says \"Let's get started\", explain that the user can provide a project or dataset, along with a question they want answered. If the user has no ideas, suggest that we have a sample flights dataset they can query - ask if they want you to query that"
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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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"source": [
|
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"### OpenAPI Schema "
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]
|
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},
|
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{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Once you've created a Custom GPT, copy the text below in the Actions panel. Have questions? Check out [Getting Started Example](https://platform.openai.com/docs/getting-started) to see how this step works in more detail."
|
||||
]
|
||||
},
|
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{
|
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"vscode": {
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"languageId": "yaml"
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}
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},
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"outputs": [],
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"source": [
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"openapi: 3.1.0\n",
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"info:\n",
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" title: BigQuery API\n",
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" description: API for querying a BigQuery table.\n",
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" version: 1.0.0\n",
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"servers:\n",
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||||
" - url: https://bigquery.googleapis.com/bigquery/v2\n",
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" description: Google BigQuery API server\n",
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||||
"paths:\n",
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||||
" /projects/{projectId}/queries:\n",
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||||
" post:\n",
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" operationId: runQuery\n",
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||||
" summary: Executes a query on a specified BigQuery table.\n",
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||||
" description: Submits a query to BigQuery and returns the results.\n",
|
||||
" parameters:\n",
|
||||
" - name: projectId\n",
|
||||
" in: path\n",
|
||||
" required: true\n",
|
||||
" description: The ID of the Google Cloud project.\n",
|
||||
" schema:\n",
|
||||
" type: string\n",
|
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" requestBody:\n",
|
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" required: true\n",
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" content:\n",
|
||||
" application/json:\n",
|
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" schema:\n",
|
||||
" type: object\n",
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" properties:\n",
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" query:\n",
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" type: string\n",
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" description: The SQL query string.\n",
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" useLegacySql:\n",
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" type: boolean\n",
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" description: Whether to use legacy SQL.\n",
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" default: false\n",
|
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" responses:\n",
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" '200':\n",
|
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" description: Successful query execution.\n",
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" content:\n",
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||||
" application/json:\n",
|
||||
" schema:\n",
|
||||
" type: object\n",
|
||||
" properties:\n",
|
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" kind:\n",
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" type: string\n",
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||||
" example: \"bigquery#queryResponse\"\n",
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" schema:\n",
|
||||
" type: object\n",
|
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" description: The schema of the results.\n",
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" jobReference:\n",
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" type: object\n",
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||||
" properties:\n",
|
||||
" projectId:\n",
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" type: string\n",
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" jobId:\n",
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" type: string\n",
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" rows:\n",
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||||
" type: array\n",
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" items:\n",
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" type: object\n",
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" properties:\n",
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||||
" f:\n",
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||||
" type: array\n",
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||||
" items:\n",
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||||
" type: object\n",
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||||
" properties:\n",
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" v:\n",
|
||||
" type: string\n",
|
||||
" totalRows:\n",
|
||||
" type: string\n",
|
||||
" description: Total number of rows in the query result.\n",
|
||||
" pageToken:\n",
|
||||
" type: string\n",
|
||||
" description: Token for pagination of query results.\n",
|
||||
" '400':\n",
|
||||
" description: Bad request. The request was invalid.\n",
|
||||
" '401':\n",
|
||||
" description: Unauthorized. Authentication is required.\n",
|
||||
" '403':\n",
|
||||
" description: Forbidden. The request is not allowed.\n",
|
||||
" '404':\n",
|
||||
" description: Not found. The specified resource was not found.\n",
|
||||
" '500':\n",
|
||||
" description: Internal server error. An error occurred while processing the request."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Authentication Instructions"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Below are instructions on setting up authentication with this 3rd party application. Have questions? Check out [Getting Started Example](https://platform.openai.com/docs/getting-started) to see how this step works in more detail."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Pre-Action Steps"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Before you set up authentication in ChatGPT, please take the following steps in the application."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"- Go to the Google Cloud Console\n",
|
||||
"- Navigate to API & Services > Credentials\n",
|
||||
"- Create new OAuth credentials (or use an existing one)\n",
|
||||
"- Locate your OAuth Client ID & Client Secret and store both values securely (see screenshot below)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### In ChatGPT"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"In ChatGPT, click on \"Authentication\" and choose **\"OAuth\"**. Enter in the information below. "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"- **Client ID**: use Client ID from steps above \n",
|
||||
"- **Client Secret**: use Client Secret from steps above\n",
|
||||
"- **Authorization URL**: https://accounts.google.com/o/oauth2/auth\n",
|
||||
"- **Token URL**: https://oauth2.googleapis.com/token \n",
|
||||
"- **Scope**: https://www.googleapis.com/auth/bigquery \n",
|
||||
"- **Token**: Default (POST)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### Post-Action Steps"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Once you've set up authentication in ChatGPT, follow the steps below in the application to finalize the Action. "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"- Copy the callback URL from the GPT Action\n",
|
||||
"- In the “Authorized redirect URIs” (see screenshot above), add your callback URL \n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"### FAQ & Troubleshooting"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"- *Callback URL Error:* If you get a callback URL error in ChatGPT, pay close attention to the screenshot above. You need to add the callback URL directly into GCP for the action to authenticate correctly\n",
|
||||
"- *Schema calls the wrong project or dataset:* If ChatGPT calls the wrong project or dataset, consider updating your instructions to make it more explicit either (a) which project / dataset should be called or (b) to require the user provide those exact details before it runs the query"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"*Are there integrations that you’d like us to prioritize? Are there errors in our integrations? File a PR or issue in our github, and we’ll take a look.*\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
BIN
images/gptactions_BigQuery_auth.png
Normal file
BIN
images/gptactions_BigQuery_auth.png
Normal file
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|
After Width: | Height: | Size: 83 KiB |
Loading…
Reference in New Issue
Block a user