使用 LlamaIndex Query Pipeline 代理

准备工作

本教程假定您已阅读并遵循以下说明:

获取代理的实例

如需查询 LlamaIndexQueryPipelineAgent,您需要先创建新实例获取现有实例

如需获取与特定资源 ID 对应的 LlamaIndexQueryPipelineAgent,请执行以下操作:

Vertex AI SDK for Python

运行以下代码:

import vertexai

client = vertexai.Client(  # For service interactions via client.agent_engines
    project="PROJECT_ID",
    location="LOCATION",
)

agent = client.agent_engines.get(name="projects/PROJECT_ID/locations/LOCATION/reasoningEngines/RESOURCE_ID")

print(agent)

其中

Python 请求库

运行以下代码:

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

使用 Vertex AI SDK for Python 时,agent 对象对应于包含以下内容的 AgentEngine 类:

  • 包含所部署智能体相关信息的 agent.api_resource。您还可以调用 agent.operation_schemas() 来返回智能体所支持操作的列表。如需了解详情,请参阅支持的操作
  • 允许同步服务交互的 agent.api_client
  • 允许异步服务交互的 agent.async_api_client

本部分的其余内容假定您有一个名为 agentAgentEngine 实例。

支持的操作

LlamaIndexQueryPipelineAgent 支持以下操作:

  • query:用于同步获取对查询的响应。

query 方法支持以下类型的参数:

  • input:要发送给智能体的消息。

查询智能体

命令:

agent.query(input="What is Paul Graham's life in college?")

它相当于以下内容(完整形式):

agent.query(input={"input": "What is Paul Graham's life in college?"})

如需自定义输入字典,请参阅自定义提示模板

您还可以通过向 query() 传递其他关键字参数,来自定义智能体在 input 之外的行为。

response = agent.query(
    input={
      "input" = [
        "What is Paul Graham's life in college?",
        "How did Paul Graham's college experience shape his career?",
        "How did Paul Graham's college experience shape his entrepreneurial mindset?",
      ],
    },
    batch=True  # run the pipeline in batch mode and pass a list of inputs.
)
print(response)

如需查看可用参数的完整列表,请参阅 QueryPipeline.run 代码

后续步骤