Tutorial Lengkap Azure OpenAI Service: GPT dan LLM di Azure

# Tutorial Lengkap Azure OpenAI Service: Enterprise AI dengan Model GPT Azure OpenAI Service menyediakan akses REST API ke model bahasa powerful dari OpenAI termasuk GPT-4, GPT-3.5-Turbo, dan model e...

By Ruby Abdullah · · tutorial
AzureOpenAIGPTLLMGenerative AIAPI

Tutorial Lengkap Azure OpenAI Service: Enterprise AI dengan Model GPT

Azure OpenAI Service menyediakan akses REST API ke model bahasa powerful dari OpenAI termasuk GPT-4, GPT-3.5-Turbo, dan model embedding. Layanan ini menggabungkan kemampuan OpenAI dengan security dan compliance enterprise Azure.

Mengapa Azure OpenAI?

Manfaat Utama:
  • Enterprise security: Security dan compliance Azure
  • Data privacy: Data Anda tetap di subscription Azure Anda
  • Ketersediaan regional: Deploy di multiple region Azure
  • Integration: Integrasi native dengan layanan Azure
  • Responsible AI: Built-in content filtering

Model Tersedia:
  • GPT-4 dan GPT-4 Turbo
  • GPT-3.5-Turbo
  • DALL-E 3
  • Embeddings (text-embedding-ada-002)
  • Whisper

Prerequisites

pip install openai azure-identity

Azure CLI

az login

Setup

1. Buat Azure OpenAI Resource

from azure.mgmt.cognitiveservices import CognitiveServicesManagementClient

from azure.identity import DefaultAzureCredential

credential = DefaultAzureCredential()

client = CognitiveServicesManagementClient(

credential=credential,

subscriptionid="your-subscription-id"

)

Buat resource

resource = client.accounts.begincreate(

resourcegroupname="my-resource-group",

accountname="my-openai-resource",

account={

"location": "eastus",

"kind": "OpenAI",

"sku": {"name": "S0"},

"properties": {}

}

).result()

print(f"Resource dibuat: {resource.name}")

2. Deploy Model

# Deploy model GPT-4

deployment = client.deployments.begincreateorupdate(

resourcegroupname="my-resource-group",

accountname="my-openai-resource",

deploymentname="gpt-4-deployment",

deployment={

"sku": {"name": "Standard", "capacity": 10},

"properties": {

"model": {

"format": "OpenAI",

"name": "gpt-4",

"version": "0613"

}

}

}

).result()

print(f"Deployment dibuat: {deployment.name}")

3. Koneksi ke Azure OpenAI

from openai import AzureOpenAI

client = AzureOpenAI(

apikey="your-api-key",

apiversion="2024-02-01",

azureendpoint="https://my-openai-resource.openai.azure.com"

)

Atau gunakan Azure Identity

from azure.identity import DefaultAzureCredential, getbearertokenprovider

tokenprovider = getbearertokenprovider(

DefaultAzureCredential(),

"https://cognitiveservices.azure.com/.default"

)

client = AzureOpenAI(

azureadtokenprovider=tokenprovider,

apiversion="2024-02-01",

azureendpoint="https://my-openai-resource.openai.azure.com"

)

Chat Completions

1. Basic Chat

response = client.chat.completions.create(

model="gpt-4-deployment",

messages=[

{"role": "system", "content": "Anda adalah asisten yang membantu."},

{"role": "user", "content": "Apa itu machine learning?"}

]

)

print(response.choices[0].message.content)

2. Multi-turn Conversation

class ChatBot:

def init(self, client, deploymentname, systemprompt):

self.client = client

self.deploymentname = deploymentname

self.messages = [{"role": "system", "content": systemprompt}]

def chat(self, usermessage):

self.messages.append({"role": "user", "content": usermessage})

response = self.client.chat.completions.create(

model=self.deploymentname,

messages=self.messages,

temperature=0.7,

maxtokens=1000

)

assistantmessage = response.choices[0].message.content

self.messages.append({"role": "assistant", "content": assistantmessage})

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