請求標記

利用 Databricks-Ai-Gateway-Request-Tags HTTP 標頭為個別請求附加自訂的鍵值標籤。 Unity Gateway 日誌會將請求標籤記錄到request_tags欄，以及使用追蹤系統表和推論表中，讓你能追蹤成本、歸因使用情況，並依專案、團隊、環境或其他維度過濾分析。

在服務政策執行的請求中，自訂策略也能將這些標籤評估為 event:context.request_tags。 例如，政策可以要求標籤必須先存在，才能允許請求。 請參閱 服務政策中的請求標籤。

標頭值必須是 JSON 物件，將字串鍵對應到字串值。 例如：

{ "project": "chatbot", "team": "ml-platform", "environment": "production" }

為模型服務請求加上標籤

使用extra_headers參數（Python）或直接傳遞標頭（REST API）將標籤附加於模型服務請求：

Python（OpenAI SDK）

from openai import OpenAI
import json
import os

DATABRICKS_TOKEN = os.environ.get('DATABRICKS_TOKEN')

client = OpenAI(
  api_key=DATABRICKS_TOKEN,
  base_url="https://<workspace-url>/ai-gateway/mlflow/v1"
)

request_tags = {"project": "chatbot", "team": "ml-platform"}

chat_completion = client.chat.completions.create(
  messages=[
    {"role": "user", "content": "What is Databricks?"},
  ],
  model="<model-service>",
  max_tokens=256,
  extra_headers={
    "Databricks-Ai-Gateway-Request-Tags": json.dumps(request_tags)
  }
)

Python（Anthropic SDK）

import anthropic
import json
import os

DATABRICKS_TOKEN = os.environ.get('DATABRICKS_TOKEN')

request_tags = {"project": "chatbot", "team": "ml-platform"}

client = anthropic.Anthropic(
  api_key="unused",
  base_url="https://<workspace-url>/ai-gateway/anthropic",
  default_headers={
    "Authorization": f"Bearer {DATABRICKS_TOKEN}",
    "Databricks-Ai-Gateway-Request-Tags": json.dumps(request_tags),
  },
)

message = client.messages.create(
  model="<model-service>",
  max_tokens=256,
  messages=[
    {"role": "user", "content": "What is Databricks?"},
  ],
)

REST API

curl \
  -u token:$DATABRICKS_TOKEN \
  -X POST \
  -H "Content-Type: application/json" \
  -H 'Databricks-Ai-Gateway-Request-Tags: {"project": "chatbot", "team": "ml-platform"}' \
  -d '{
    "model": "<model-service>",
    "max_tokens": 256,
    "messages": [
      {"role": "user", "content": "What is Databricks?"}
    ]
  }' \
  https://<workspace-url>/ai-gateway/mlflow/v1/chat/completions

將 <workspace-url> 替換為您的 Azure Databricks 工作區 URL，並將 <model-service> 替換為模型服務的完整限定名稱。

標記模型提供者服務請求

當您直接查詢模型提供者服務時，請將標籤標頭與 Databricks-Model-Provider-Service 標頭一同傳送：

Python

from openai import OpenAI
import json

client = OpenAI(
    api_key="<databricks-token>",
    base_url="https://<workspace-url>/ai-gateway/openai/v1",
    default_headers={"Databricks-Model-Provider-Service": "main.default.openai_prod"},
)

request_tags = {"project": "chatbot", "team": "ml-platform"}

response = client.chat.completions.create(
    model="gpt-5.5",
    messages=[{"role": "user", "content": "What is Databricks?"}],
    extra_headers={"Databricks-Ai-Gateway-Request-Tags": json.dumps(request_tags)},
)

REST

curl https://<workspace-url>/ai-gateway/openai/v1/chat/completions \
  -H "Authorization: Bearer $DATABRICKS_TOKEN" \
  -H "Databricks-Model-Provider-Service: main.default.openai_prod" \
  -H "Content-Type: application/json" \
  -H 'Databricks-Ai-Gateway-Request-Tags: {"project": "chatbot", "team": "ml-platform"}' \
  -d '{
    "model": "gpt-5.5",
    "messages": [{"role": "user", "content": "What is Databricks?"}]
  }'