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[OpenAI] Prepare beta.5 release (#26941)
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70 changes: 70 additions & 0 deletions
70
sdk/openai/openai/samples/v1-beta/javascript/bringYourOwnData.js
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| Original file line number | Diff line number | Diff line change |
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| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT License. | ||
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| /** | ||
| * Demonstrates how to use Azure's Bring Your Own Data with Azure OpenAI Chat Completions. | ||
| * | ||
| * @summary chat completions with your own data. | ||
| */ | ||
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| const { OpenAIClient, AzureKeyCredential } = require("@azure/openai"); | ||
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| // Load the .env file if it exists | ||
| require("dotenv").config(); | ||
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| // You will need to set these environment variables or edit the following values | ||
| // The endpoint you will use to access your Azure OpenAI instance | ||
| const endpoint = process.env["ENDPOINT"] || "<endpoint>"; | ||
| // Your Azure OpenAI API key | ||
| const azureApiKey = process.env["AZURE_API_KEY"] || "<api key>"; | ||
| // Your Azure Cognitive Search endpoint, admin key, and index name | ||
| const azureSearchEndpoint = process.env["AZURE_SEARCH_ENDPOINT"] || "<search endpoint>"; | ||
| const azureSearchAdminKey = process.env["AZURE_SEARCH_KEY"] || "<search key>"; | ||
| const azureSearchIndexName = process.env["AZURE_SEARCH_INDEX"] || "<search index>"; | ||
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| const messages = [ | ||
| { | ||
| role: "user", | ||
| content: "What's the most common feedback we received from our customers about the product?", | ||
| }, | ||
| ]; | ||
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| async function main() { | ||
| console.log("== Bring Your Own Data Sample =="); | ||
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| const client = new OpenAIClient(endpoint, new AzureKeyCredential(azureApiKey)); | ||
| const deploymentId = "gpt-35-turbo"; | ||
| const events = client.listChatCompletions(deploymentId, messages, { | ||
| maxTokens: 128, | ||
| /** | ||
| * The `azureExtensionOptions` property is used to configure the | ||
| * Azure-specific extensions. In this case, we are using the | ||
| * Azure Cognitive Search extension with a vector index to provide | ||
| * the model with additional context. | ||
| */ | ||
| azureExtensionOptions: { | ||
| extensions: [ | ||
| { | ||
| type: "AzureCognitiveSearch", | ||
| parameters: { | ||
| endpoint: azureSearchEndpoint, | ||
| key: azureSearchAdminKey, | ||
| indexName: azureSearchIndexName, | ||
| }, | ||
| }, | ||
| ], | ||
| }, | ||
| }); | ||
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| for await (const event of events) { | ||
| for (const choice of event.choices) { | ||
| console.log(choice.delta?.content); | ||
| } | ||
| } | ||
| } | ||
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| main().catch((err) => { | ||
| console.error("The sample encountered an error:", err); | ||
| }); | ||
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| module.exports = { main }; |
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sdk/openai/openai/samples/v1-beta/javascript/completionsRest.js
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| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT License. | ||
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| /** | ||
| * Demonstrates how to get completions for the provided prompt. | ||
| * | ||
| * @summary get completions. | ||
| */ | ||
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| const { AzureKeyCredential } = require("@azure/core-auth"); | ||
| const OpenAIClient = require("@azure/openai/rest").default, | ||
| { isUnexpected } = require("@azure/openai/rest"); | ||
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| // Load the .env file if it exists | ||
| require("dotenv").config(); | ||
|
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| // You will need to set these environment variables or edit the following values | ||
| const endpoint = process.env["ENDPOINT"] || "<endpoint>"; | ||
| const azureApiKey = process.env["AZURE_API_KEY"] || "<api key>"; | ||
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| const prompt = ["What is Azure OpenAI?"]; | ||
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| async function main() { | ||
| console.log("== Get completions Sample =="); | ||
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| const client = OpenAIClient(endpoint, new AzureKeyCredential(azureApiKey)); | ||
| const deploymentId = "text-davinci-003"; | ||
| const result = await client.path("/deployments/{deploymentId}/completions", deploymentId).post({ | ||
| body: { prompt, max_tokens: 128 }, | ||
| }); | ||
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| if (isUnexpected(result)) { | ||
| throw result; | ||
| } | ||
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| for (const choice of result.body.choices) { | ||
| console.log(choice.text); | ||
| } | ||
| } | ||
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| main().catch((err) => { | ||
| console.error("The sample encountered an error:", err); | ||
| }); | ||
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| module.exports = { main }; |
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| Original file line number | Diff line number | Diff line change |
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| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT License. | ||
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| /** | ||
| * Demonstrates how to define and call functions with chat completions. | ||
| * | ||
| * @summary get chat completions with functions. | ||
| */ | ||
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| const { OpenAIClient, AzureKeyCredential } = require("@azure/openai"); | ||
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| // Load the .env file if it exists | ||
| require("dotenv").config(); | ||
|
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| // You will need to set these environment variables or edit the following values | ||
| const endpoint = process.env["ENDPOINT"] || "<endpoint>"; | ||
| const azureApiKey = process.env["AZURE_API_KEY"] || "<api key>"; | ||
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| const messages = [{ role: "user", content: "What's the weather like in Boston?" }]; | ||
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| const getCurrentWeather = { | ||
| name: "get_current_weather", | ||
| description: "Get the current weather in a given location", | ||
| parameters: { | ||
| type: "object", | ||
| properties: { | ||
| location: { | ||
| type: "string", | ||
| description: "The city and state, e.g. San Francisco, CA", | ||
| }, | ||
| unit: { | ||
| type: "string", | ||
| enum: ["celsius", "fahrenheit"], | ||
| }, | ||
| }, | ||
| required: ["location"], | ||
| }, | ||
| }; | ||
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| async function main() { | ||
| console.log("== Chat Completions Sample With Functions =="); | ||
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| const client = new OpenAIClient(endpoint, new AzureKeyCredential(azureApiKey)); | ||
| const deploymentId = "gpt-4"; | ||
| const result = await client.getChatCompletions(deploymentId, messages, { | ||
| functions: [getCurrentWeather], | ||
| }); | ||
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| for (const choice of result.choices) { | ||
| console.log(choice.message?.functionCall); | ||
| } | ||
| } | ||
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| main().catch((err) => { | ||
| console.error("The sample encountered an error:", err); | ||
| }); | ||
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| module.exports = { main }; |
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| @@ -0,0 +1,41 @@ | ||
| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT License. | ||
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| /** | ||
| * Demonstrates how to generate images from prompts using Azure OpenAI Batch Image Generation. | ||
| * | ||
| * @summary generates images from prompts using Azure OpenAI Batch Image Generation. | ||
| */ | ||
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| const { OpenAIClient, AzureKeyCredential } = require("@azure/openai"); | ||
|
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| // Load the .env file if it exists | ||
| require("dotenv").config(); | ||
|
|
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| // You will need to set these environment variables or edit the following values | ||
| const endpoint = process.env["ENDPOINT"] || "<endpoint>"; | ||
| const azureApiKey = process.env["AZURE_API_KEY"] || "<api key>"; | ||
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| // The prompt to generate images from | ||
| const prompt = "a monkey eating a banana"; | ||
| const size = "256x256"; | ||
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| // The number of images to generate | ||
| const n = 3; | ||
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| async function main() { | ||
| console.log("== Batch Image Generation =="); | ||
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| const client = new OpenAIClient(endpoint, new AzureKeyCredential(azureApiKey)); | ||
| const results = await client.getImages(prompt, { n, size }); | ||
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| for (const image of results.data) { | ||
| console.log(`Image generation result URL: ${image.url}`); | ||
| } | ||
| } | ||
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| main().catch((err) => { | ||
| console.error("The sample encountered an error:", err); | ||
| }); | ||
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| module.exports = { main }; |
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