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[OpenAI] Add a sample for global batch (#31278)
Add batch sample
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,63 @@ | ||
| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT License. | ||
|
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| /** | ||
| * Demonstrates how to use Azure OpenAI global batch deployment. | ||
| * | ||
| * @summary create and retrieve batch content. | ||
| * @azsdk-weight 100 | ||
| */ | ||
|
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| import { AzureOpenAI, toFile } from "openai"; | ||
| import { DefaultAzureCredential, getBearerTokenProvider } from "@azure/identity"; | ||
|
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| // Set AZURE_OPENAI_ENDPOINT to the endpoint of your | ||
| // OpenAI resource. You can find this in the Azure portal. | ||
| // Load the .env file if it exists | ||
| import "dotenv/config"; | ||
|
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| export async function main() { | ||
| console.log("== Batch Chat Completions Sample =="); | ||
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| const scope = "https://cognitiveservices.azure.com/.default"; | ||
| const azureADTokenProvider = getBearerTokenProvider(new DefaultAzureCredential(), scope); | ||
| const deployment = "gpt-4-turbo"; | ||
| const apiVersion = "2024-08-01-preview"; | ||
| const client = new AzureOpenAI({ azureADTokenProvider, deployment, apiVersion }); | ||
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| const batchContent = `{ "custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": { "model": "${deployment}", "messages": [{ "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is 2+2?" }] } }`; | ||
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| // Upload a file with "batch" purpose | ||
| const file = await client.files.create({ | ||
| file: await toFile(Buffer.from(batchContent), "batch.jsonl"), | ||
| purpose: "batch", | ||
| }); | ||
|
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| // Create the batch | ||
| const batch = await client.batches.create({ | ||
| endpoint: "/v1/chat/completions", | ||
| input_file_id: file.id, | ||
| completion_window: "24h", | ||
| }); | ||
| console.log(batch); | ||
|
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| // Checking batch status | ||
| const retrievedBatch = await client.batches.retrieve(batch.id); | ||
| console.log(retrievedBatch); | ||
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| // Retrieve the batch output | ||
| const outputFileId = retrievedBatch.output_file_id ?? retrievedBatch.error_file_id; | ||
| if (outputFileId) { | ||
| const fileResponse = await client.files.content(outputFileId); | ||
| const fileContent = await fileResponse.text(); | ||
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| console.log(fileContent); | ||
| } | ||
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| // Clean up file | ||
| await client.files.del(file.id); | ||
| } | ||
|
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| main().catch((err) => { | ||
| console.error("The sample encountered an error:", err); | ||
| }); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,64 @@ | ||
| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT License. | ||
|
|
||
| /** | ||
| * Demonstrates how to use Azure OpenAI global batch deployment. | ||
| * | ||
| * @summary create and retrieve batch content. | ||
| */ | ||
|
|
||
| const { AzureOpenAI, toFile } = require("openai"); | ||
| const { DefaultAzureCredential, getBearerTokenProvider } = require("@azure/identity"); | ||
|
|
||
| // Set AZURE_OPENAI_ENDPOINT to the endpoint of your | ||
| // OpenAI resource. You can find this in the Azure portal. | ||
| // Load the .env file if it exists | ||
| require("dotenv/config"); | ||
|
|
||
| async function main() { | ||
| console.log("== Batch Chat Completions Sample =="); | ||
|
|
||
| const scope = "https://cognitiveservices.azure.com/.default"; | ||
| const azureADTokenProvider = getBearerTokenProvider(new DefaultAzureCredential(), scope); | ||
| const deployment = "gpt-4-turbo"; | ||
| const apiVersion = "2024-08-01-preview"; | ||
| const client = new AzureOpenAI({ azureADTokenProvider, deployment, apiVersion }); | ||
|
|
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| const batchContent = `{ "custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": { "model": "${deployment}", "messages": [{ "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is 2+2?" }] } }`; | ||
|
|
||
| // Upload a file with "batch" purpose | ||
| const file = await client.files.create({ | ||
| file: await toFile(Buffer.from(batchContent), "batch.jsonl"), | ||
| purpose: "batch", | ||
| }); | ||
|
|
||
| // Create the batch | ||
| const batch = await client.batches.create({ | ||
| endpoint: "/v1/chat/completions", | ||
| input_file_id: file.id, | ||
| completion_window: "24h", | ||
| }); | ||
| console.log(batch); | ||
|
|
||
| // Checking batch status | ||
| const retrievedBatch = await client.batches.retrieve(batch.id); | ||
| console.log(retrievedBatch); | ||
|
|
||
| // Retrieve the batch output | ||
| const outputFileId = retrievedBatch.output_file_id ?? retrievedBatch.error_file_id; | ||
| if (outputFileId) { | ||
| const fileResponse = await client.files.content(outputFileId); | ||
| const fileContent = await fileResponse.text(); | ||
|
|
||
| console.log(fileContent); | ||
| } | ||
|
|
||
| // Clean up file | ||
| await client.files.del(file.id); | ||
| } | ||
|
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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 |
|---|---|---|
| @@ -0,0 +1,62 @@ | ||
| // Copyright (c) Microsoft Corporation. | ||
| // Licensed under the MIT License. | ||
|
|
||
| /** | ||
| * Demonstrates how to use Azure OpenAI global batch deployment. | ||
| * | ||
| * @summary create and retrieve batch content. | ||
| */ | ||
|
|
||
| import { AzureOpenAI, toFile } from "openai"; | ||
| import { DefaultAzureCredential, getBearerTokenProvider } from "@azure/identity"; | ||
|
|
||
| // Set AZURE_OPENAI_ENDPOINT to the endpoint of your | ||
| // OpenAI resource. You can find this in the Azure portal. | ||
| // Load the .env file if it exists | ||
| import "dotenv/config"; | ||
|
|
||
| export async function main() { | ||
| console.log("== Batch Chat Completions Sample =="); | ||
|
|
||
| const scope = "https://cognitiveservices.azure.com/.default"; | ||
| const azureADTokenProvider = getBearerTokenProvider(new DefaultAzureCredential(), scope); | ||
| const deployment = "gpt-4-turbo"; | ||
| const apiVersion = "2024-08-01-preview"; | ||
| const client = new AzureOpenAI({ azureADTokenProvider, deployment, apiVersion }); | ||
|
|
||
| const batchContent = `{ "custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": { "model": "${deployment}", "messages": [{ "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is 2+2?" }] } }`; | ||
|
|
||
| // Upload a file with "batch" purpose | ||
| const file = await client.files.create({ | ||
| file: await toFile(Buffer.from(batchContent), "batch.jsonl"), | ||
| purpose: "batch", | ||
| }); | ||
|
|
||
| // Create the batch | ||
| const batch = await client.batches.create({ | ||
| endpoint: "/v1/chat/completions", | ||
| input_file_id: file.id, | ||
| completion_window: "24h", | ||
| }); | ||
| console.log(batch); | ||
|
|
||
| // Checking batch status | ||
| const retrievedBatch = await client.batches.retrieve(batch.id); | ||
| console.log(retrievedBatch); | ||
|
|
||
| // Retrieve the batch output | ||
| const outputFileId = retrievedBatch.output_file_id ?? retrievedBatch.error_file_id; | ||
| if (outputFileId) { | ||
| const fileResponse = await client.files.content(outputFileId); | ||
| const fileContent = await fileResponse.text(); | ||
|
|
||
| console.log(fileContent); | ||
| } | ||
|
|
||
| // Clean up file | ||
| await client.files.del(file.id); | ||
| } | ||
|
|
||
| main().catch((err) => { | ||
| console.error("The sample encountered an error:", err); | ||
| }); |