From 6d3db1374b02dc764797cbf0901d33f2fe53612b Mon Sep 17 00:00:00 2001 From: simonpfish Date: Tue, 17 Oct 2023 13:15:23 -0700 Subject: [PATCH] Update title and reformat with prettier --- ...How_to_build_an_agent_with_the_node_sdk.md | 250 +++++++++--------- registry.yaml | 3 +- 2 files changed, 130 insertions(+), 123 deletions(-) diff --git a/examples/How_to_build_an_agent_with_the_node_sdk.md b/examples/How_to_build_an_agent_with_the_node_sdk.md index dd1dd717..fa2a2816 100644 --- a/examples/How_to_build_an_agent_with_the_node_sdk.md +++ b/examples/How_to_build_an_agent_with_the_node_sdk.md @@ -1,4 +1,4 @@ -# How to build an agent with the Node.js SDK and function-calling +# How to build an agent with the Node.js SDK OpenAI functions enable your app to take action based on user inputs. This means that it can, e.g., search the web, send emails, or book tickets on behalf of your users, making it more powerful than a regular chatbot. @@ -13,7 +13,7 @@ If you prefer watching screencasts over reading, then you can check out [this sc Our app is a simple agent that helps you find activities in your area. It has access to two functions, `getLocation()` and `getCurrentWeather()`, which means it can figure out where you’re located and what the weather -is at the moment. +is at the moment. At this point, it's important to understand that OpenAI doesn't execute any code for you. It just tells your app which @@ -27,12 +27,12 @@ internal knowledge to suggest suitable local activities for you. We start by importing the OpenAI SDK at the top of our JavaScript file and authenticate with our API key, which we have stored as an environment variable. -``` js +```js import OpenAI from "openai"; const openai = new OpenAI({ - apiKey: process.env.OPENAI_API_KEY, - dangerouslyAllowBrowser: true + apiKey: process.env.OPENAI_API_KEY, + dangerouslyAllowBrowser: true, }); ``` @@ -44,11 +44,11 @@ Next, we'll create the two functions. The first one - `getLocation` - uses the [IP API](https://ipapi.co/) to get the location of the user. -``` js +```js async function getLocation() { - const response = await fetch('https://ipapi.co/json/'); - const locationData = await response.json(); - return locationData; + const response = await fetch("https://ipapi.co/json/"); + const locationData = await response.json(); + return locationData; } ``` @@ -58,12 +58,12 @@ function `getCurrentWeather`. It uses the [Open Meteo API](https://open-meteo.com/) to get the current weather data, like this: -``` js +```js async function getCurrentWeather(latitude, longitude) { - const url = `https://api.open-meteo.com/v1/forecast?latitude=${latitude}&longitude=${longitude}&hourly=apparent_temperature`; - const response = await fetch(url); - const weatherData = await response.json(); - return weatherData; + const url = `https://api.open-meteo.com/v1/forecast?latitude=${latitude}&longitude=${longitude}&hourly=apparent_temperature`; + const response = await fetch(url); + const weatherData = await response.json(); + return weatherData; } ``` @@ -74,49 +74,51 @@ describe them using a specific schema. We'll create an array called `functionDefinitions` that contains one object per function. Each object will have three keys: `name`, `description`, and `parameters`. -``` js +```js const functionDefinitions = [ - { - name: "getCurrentWeather", - description: "Get the current weather in a given location", - parameters: { - type: "object", - properties: { - longitude: { - type: "string", - }, - latitude: { - type: "string", - } - }, - required: ["longitude", "latitude"] - } + { + name: "getCurrentWeather", + description: "Get the current weather in a given location", + parameters: { + type: "object", + properties: { + longitude: { + type: "string", + }, + latitude: { + type: "string", + }, + }, + required: ["longitude", "latitude"], }, - { - name: "getLocation", - description: "Get the user's location based on their IP address", - parameters: { - type: "object", - properties: {} - } - } -] + }, + { + name: "getLocation", + description: "Get the user's location based on their IP address", + parameters: { + type: "object", + properties: {}, + }, + }, +]; ``` ## Setting up the messages array -We also need to define a `messages` array. This will keep track of all of the messages back and forth between our app and OpenAI. +We also need to define a `messages` array. This will keep track of all of the messages back and forth between our app and OpenAI. The first object in the array should always have the `role` property set to `"system"`, which tells OpenAI that this is how we want it to behave. -``` js -const messages = [{ - role: "system", - content: "You are a helpful assistant. Only use the functions you have been provided with." -}]; +```js +const messages = [ + { + role: "system", + content: + "You are a helpful assistant. Only use the functions you have been provided with.", + }, +]; ``` - ## Creating the agent function We are now ready to build the logic of our app, which lives in the @@ -125,18 +127,20 @@ We are now ready to build the logic of our app, which lives in the We start by pushing the `userInput` to the messages array. This time, we set the `role` to `"user"`, so that OpenAI knows that this is the input from the user. -``` js +```js async function agent(userInput) { - messages.push([{ + messages.push([ + { role: "user", content: userInput, - }]); - const response = await openai.chat.completions.create({ - model: "gpt-4", - messages: messages, - functions: functionDefinitions - }); - console.log(response); + }, + ]); + const response = await openai.chat.completions.create({ + model: "gpt-4", + messages: messages, + functions: functionDefinitions, + }); + console.log(response); } ``` @@ -145,47 +149,46 @@ Next, we'll send a request to the Chat completions endpoint via the configuration object as an argument. In it, we'll specify three properties: -- `model` - Decides which AI model we want to use (in our case, - GPT-4). -- `messages` - The entire history of messages between the user and the - AI up until this point. -- `functions` - A description of the functions our app has access to. - Here, we'll we use the `functionDefinitions` array we created - earlier. - +- `model` - Decides which AI model we want to use (in our case, + GPT-4). +- `messages` - The entire history of messages between the user and the + AI up until this point. +- `functions` - A description of the functions our app has access to. + Here, we'll we use the `functionDefinitions` array we created + earlier. ## Running our app with a simple input Let's try to run the `agent` with an input that requires a function call to give a suitable reply. -``` js +```js agent("Where am I located right now?"); ``` When we run the code above, we see the response from OpenAI logged out to the console like this: -``` js +```js { id: "chatcmpl-84ojoEJtyGnR6jRHK2Dl4zTtwsa7O", - object: "chat.completion", - created: 1696159040, - model: "gpt-4-0613", + object: "chat.completion", + created: 1696159040, + model: "gpt-4-0613", choices: [{ - index: 0, + index: 0, message: { - role: "assistant", - content: null, + role: "assistant", + content: null, function_call: { name: "getLocation", // The function OpenAI wants us to call arguments: "{}" } - }, + }, finish_reason: "function_call" // OpenAI wants us to call a function }], usage: { - prompt_tokens: 134, - completion_tokens: 6, + prompt_tokens: 134, + completion_tokens: 6, total_tokens: 140 } } @@ -203,10 +206,10 @@ Now that we have the name of the function as a string, we'll need to translate that into a function call. To help us with that, we'll gather both of our functions in an object called `availableFunctions`: -``` js +```js const availableFunctions = { - getCurrentWeather, - getLocation + getCurrentWeather, + getLocation, }; ``` @@ -214,17 +217,16 @@ This is handy because we'll be able to access the `getLocation` function via bracket notation and the string we got back from OpenAI, like this: `availableFunctions["getLocation"]`. -``` js - +```js const { finish_reason, message } = response.choices[0]; if (finish_reason === "function_call") { - const functionName = message.function_call.name; - const functionToCall = availableFunctions[functionName]; - const functionArgs = JSON.parse(message.function_call.arguments); - const functionArgsArr = Object.values(functionArgs); - const functionResponse = await functionToCall.apply(null, functionArgsArr); - console.log(functionResponse); + const functionName = message.function_call.name; + const functionToCall = availableFunctions[functionName]; + const functionArgs = JSON.parse(message.function_call.arguments); + const functionArgsArr = Object.values(functionArgs); + const functionResponse = await functionToCall.apply(null, functionArgsArr); + console.log(functionResponse); } ``` @@ -232,25 +234,26 @@ We're also grabbing ahold of any arguments OpenAI wants us to pass into the function: `message.function_call.arguments`. However, we won't need any arguments for this first function call. - If we run the code again with the same input (`"Where am I located right now?"`), we'll see that `functionResponse` is an object filled with location about where the user is located right now. In my case, that is Oslo, Norway. -``` js +```js {ip: "193.212.60.170", network: "193.212.60.0/23", version: "IPv4", city: "Oslo", region: "Oslo County", region_code: "03", country: "NO", country_name: "Norway", country_code: "NO", country_code_iso3: "NOR", country_capital: "Oslo", country_tld: ".no", continent_code: "EU", in_eu: false, postal: "0026", latitude: 59.955, longitude: 10.859, timezone: "Europe/Oslo", utc_offset: "+0200", country_calling_code: "+47", currency: "NOK", currency_name: "Krone", languages: "no,nb,nn,se,fi", country_area: 324220, country_population: 5314336, asn: "AS2119", org: "Telenor Norge AS"} ``` We'll add this data to a new item in the `messages` array, where we also specify the name of the function we called. -``` js +```js messages.push({ role: "function", name: functionName, - content: `The result of the last function was this: ${JSON.stringify(functionResponse)} - ` + content: `The result of the last function was this: ${JSON.stringify( + functionResponse + )} + `, }); ``` @@ -279,33 +282,34 @@ the next iteration of the loop, triggering a new request. If we get `finish_reason: "stop"` back, then GPT has found a suitable answer, so we'll return the function and cancel the loop. -``` js - +```js for (let i = 0; i < 5; i++) { const response = await openai.chat.completions.create({ - model: "gpt-4", - messages: messages, - functions: functionDefinitions + model: "gpt-4", + messages: messages, + functions: functionDefinitions, }); const { finish_reason, message } = response.choices[0]; - + if (finish_reason === "function_call") { - const functionName = message.function_call.name; - const functionToCall = availableFunctions[functionName]; - const functionArgs = JSON.parse(message.function_call.arguments); - const functionArgsArr = Object.values(functionArgs); - const functionResponse = await functionToCall.apply(null, functionArgsArr); - - messages.push({ - role: "function", - name: functionName, - content: ` - The result of the last function was this: ${JSON.stringify(functionResponse)} - ` - }); - } else if (finish_reason === "stop") { + const functionName = message.function_call.name; + const functionToCall = availableFunctions[functionName]; + const functionArgs = JSON.parse(message.function_call.arguments); + const functionArgsArr = Object.values(functionArgs); + const functionResponse = await functionToCall.apply(null, functionArgsArr); + + messages.push({ + role: "function", + name: functionName, + content: ` + The result of the last function was this: ${JSON.stringify( + functionResponse + )} + `, + }); + } else if (finish_reason === "stop") { messages.push(message); - return message.content; + return message.content; } } return "The maximum number of iterations has been met without a suitable answer. Please try again with a more specific input."; @@ -319,22 +323,24 @@ we'll return a message saying we couldn’t find a suitable answer. At this point, we are ready to try our app! I'll ask the agent to suggest some activities based on my location and the current weather. -``` js -const response = await agent("Please suggest some activities based on my location and the current weather."); +```js +const response = await agent( + "Please suggest some activities based on my location and the current weather." +); console.log(response); ``` Here's what we see in the console (formatted to make it easier to read): -``` js -Based on your current location in Oslo, Norway and the weather (15°C and snowy), -here are some activity suggestions: +```js +Based on your current location in Oslo, Norway and the weather (15°C and snowy), +here are some activity suggestions: -1. A visit to the Oslo Winter Park for skiing or snowboarding. -2. Enjoy a cosy day at a local café or restaurant. -3. Visit one of Oslo's many museums. The Fram Museum or Viking Ship Museum offer interesting insights into Norway’s seafaring history. -4. Take a stroll in the snowy streets and enjoy the beautiful winter landscape. -5. Enjoy a nice book by the fireplace in a local library. +1. A visit to the Oslo Winter Park for skiing or snowboarding. +2. Enjoy a cosy day at a local café or restaurant. +3. Visit one of Oslo's many museums. The Fram Museum or Viking Ship Museum offer interesting insights into Norway’s seafaring history. +4. Take a stroll in the snowy streets and enjoy the beautiful winter landscape. +5. Enjoy a nice book by the fireplace in a local library. 6. Take a fjord sightseeing cruise to enjoy the snowy landscapes. Always remember to bundle up and stay warm. Enjoy your day! @@ -349,7 +355,7 @@ to call the `getCurrentWeather` function with `"longitude": "10.859", "latitude": "59.955"` passed in as the arguments. This is data it got back from the first function call we did. -``` js +```js {role: "assistant", content: null, function_call: {name: "getLocation", arguments: "{}"}} {role: "assistant", content: null, function_call: {name: "getCurrentWeather", arguments: " { "longitude": "10.859", "latitude": "59.955" }"}} ``` diff --git a/registry.yaml b/registry.yaml index e4c61ffd..19d2fd49 100644 --- a/registry.yaml +++ b/registry.yaml @@ -1029,13 +1029,14 @@ - tiktoken - completions -- title: How to build an agent with the Node.js SDK and function-calling +- title: How to build an agent with the Node.js SDK path: examples/How_to_build_an_agent_with_the_node_sdk.md date: 2023-10-05 authors: - perborgen tags: - completions + - functions - title: What makes documentation good path: articles/what_makes_documentation_good.md