使用 Agent Development Kit 代理程式

除了使用代理程式的一般操作說明外，本頁還會說明 AdkApp 專屬的功能。

事前準備

本教學課程假設您已閱讀並遵循以下說明：

如要查詢 ADK 應用程式，您必須先建立新的 ADK 應用程式執行個體，或取得現有執行個體。

如要取得與特定資源 ID 對應的 ADK 應用程式，請按照下列步驟操作：

Python 適用的 Vertex AI SDK

請執行下列程式碼：

from vertexai import agent_engines

adk_app = agent_engines.get(RESOURCE_ID)

或者，您也可以提供代理程式的完整資源名稱：

adk_app = agent_engines.get("projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID")

Python 要求程式庫

請執行下列程式碼：

from google import auth as google_auth
from google.auth.transport import requests as google_requests
import requests

def get_identity_token():
    credentials, _ = google_auth.default()
    auth_request = google_requests.Request()
    credentials.refresh(auth_request)
    return credentials.token

response = requests.get(
f"https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID",
    headers={
        "Content-Type": "application/json; charset=utf-8",
        "Authorization": f"Bearer {get_identity_token()}",
    },
)

REST API 

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID

支援的作業

AdkApp 支援下列作業：

如要列出所有支援的作業：

Python 適用的 Vertex AI SDK

請執行下列程式碼：

adk_app.operation_schemas()

Python 要求程式庫

請執行下列程式碼：

import json

json.loads(response.content).get("spec").get("classMethods")

REST API

在 curl 要求的回應中以 spec.class_methods 表示。

管理工作階段

將代理部署至 Vertex AI Agent Engine 後，AdkApp 就會使用雲端管理式工作階段。本節說明如何使用受管理的會話。

建立工作階段

如要為使用者建立工作階段，請按照下列步驟操作：

Python 適用的 Vertex AI SDK

session = adk_app.create_session(user_id="USER_ID")

Python 要求程式庫

請執行下列程式碼：

from google import auth as google_auth
from google.auth.transport import requests as google_requests
import requests
import json

def get_identity_token():
  credentials, _ = google_auth.default()
  auth_request = google_requests.Request()
  credentials.refresh(auth_request)
  return credentials.token

response = requests.post(
  f"https://{adk_app.api_client.api_endpoint}/v1/{adk_app.resource_name}:query",
  headers={
    "Content-Type": "application/json; charset=utf-8",
    "Authorization": f"Bearer {get_identity_token()}",
  },
  data=json.dumps({
    "class_method": "create_session",
    "input": {"user_id": "USER_ID"},
  }),
)
print(response.content)

REST API 

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID:query -d '{"class_method": "create_session", "input": {"user_id": "USER_ID"},}'

其中 USER_ID 是使用者定義的 ID，字元上限為 128 個。

列出工作階段

如要列出使用者的工作階段，請按照下列步驟操作：

Python 適用的 Vertex AI SDK

adk_app.list_sessions(user_id="USER_ID")

要求

請執行下列程式碼：

from google import auth as google_auth
from google.auth.transport import requests as google_requests
import requests
import json

def get_identity_token():
  credentials, _ = google_auth.default()
  auth_request = google_requests.Request()
  credentials.refresh(auth_request)
  return credentials.token

response = requests.post(
  f"https://{adk_app.api_client.api_endpoint}/v1/{adk_app.resource_name}:query",
  headers={
    "Content-Type": "application/json; charset=utf-8",
    "Authorization": f"Bearer {get_identity_token()}",
  },
  data=json.dumps({
    "class_method": "list_sessions",
    "input": {"user_id": "USER_ID"},
  }),
)
print(response.content)

REST 

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID:query -d '{"class_method": "list_sessions", "input": {"user_id": "USER_ID"},}'

其中 USER_ID 是使用者定義的 ID，字元上限為 128 個。

取得工作階段

如要取得特定工作階段，您必須同時提供使用者 ID 和工作階段 ID：

Python 適用的 Vertex AI SDK

session = adk_app.get_session(user_id="USER_ID", session_id="SESSION_ID")

要求

請執行下列程式碼：

from google import auth as google_auth
from google.auth.transport import requests as google_requests
import requests
import json

def get_identity_token():
  credentials, _ = google_auth.default()
  auth_request = google_requests.Request()
  credentials.refresh(auth_request)
  return credentials.token

response = requests.post(
  f"https://{adk_app.api_client.api_endpoint}/v1/{adk_app.resource_name}:query",
  headers={
    "Content-Type": "application/json; charset=utf-8",
    "Authorization": f"Bearer {get_identity_token()}",
  },
  data=json.dumps({
    "class_method": "get_session",
    "input": {"user_id": "USER_ID", "session_id": "SESSION_ID"},
  }),
)
print(response.content)

REST 

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID:query -d '{"class_method": "get_session", "input": {"user_id": "USER_ID", "session_id": "SESSION_ID"},}'

刪除工作階段

如要刪除工作階段，您必須同時提供使用者 ID 和工作階段 ID：

Python 適用的 Vertex AI SDK

adk_app.delete_session(user_id="USER_ID", session_id="SESSION_ID")

要求

請執行下列程式碼：

from google import auth as google_auth
from google.auth.transport import requests as google_requests
import requests
import json

def get_identity_token():
  credentials, _ = google_auth.default()
  auth_request = google_requests.Request()
  credentials.refresh(auth_request)
  return credentials.token

response = requests.post(
  f"https://{adk_app.api_client.api_endpoint}/v1/{adk_app.resource_name}:query",
  headers={
    "Content-Type": "application/json; charset=utf-8",
    "Authorization": f"Bearer {get_identity_token()}",
  },
  data=json.dumps({
    "class_method": "delete_session",
    "input": {"user_id": "USER_ID", "session_id": "SESSION_ID"},
  }),
)
print(response.content)

REST 

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID:query -d '{"class_method": "delete_session", "input": {"user_id": "USER_ID", "session_id": "SESSION_ID"},}'

串流傳送對查詢的回應

如要在會話中串流代理程式的回應，請按照下列步驟操作：

Python 適用的 Vertex AI SDK

for event in adk_app.stream_query(
    user_id="USER_ID",
    session_id="SESSION_ID",  # Optional
    message="What is the exchange rate from US dollars to SEK today?",
):
  print(event)

要求

from google import auth as google_auth
from google.auth.transport import requests as google_requests
import requests

def get_identity_token():
    credentials, _ = google_auth.default()
    auth_request = google_requests.Request()
    credentials.refresh(auth_request)
    return credentials.token

requests.post(
    f"https://{adk_app.api_client.api_endpoint}/v1/{adk_app.resource_name}:streamQuery",
    headers={
        "Content-Type": "application/json",
        "Authorization": f"Bearer {get_identity_token()}",
    },
    data=json.dumps({
        "class_method": "stream_query",
        "input": {
            "user_id": "USER_ID",
            "session_id": "SESSION_ID",
            "message": "What is the exchange rate from US dollars to SEK today?",
        },
    }),
    stream=True,
)

REST 

curl \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
https://LOCATION-aiplatform.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID:streamQuery?alt=sse -d '{
  "class_method": "stream_query",
  "input": {
    "user_id": "USER_ID",
    "session_id": "SESSION_ID",
    "message": "What is the exchange rate from US dollars to SEK today?",
  }
}'

後續步驟