带有流式输出的接地生成

带有流式输出的接地生成

深入探索

如需查看包含此代码示例的详细文档，请参阅以下内容：

代码示例

Python

如需了解详情，请参阅 Vertex AI Agent Builder Python API 参考文档。

如需向 Vertex AI Agent Builder 进行身份验证，请设置应用默认凭据。 如需了解详情，请参阅为本地开发环境设置身份验证。 

from google.cloud import discoveryengine_v1 as discoveryengine

# TODO(developer): Uncomment these variables before running the sample.
# project_id = "YOUR_PROJECT_ID"

client = discoveryengine.GroundedGenerationServiceClient()

request = discoveryengine.GenerateGroundedContentRequest(
    # The full resource name of the location.
    # Format: projects/{project_number}/locations/{location}
    location=client.common_location_path(project=project_number, location="global"),
    generation_spec=discoveryengine.GenerateGroundedContentRequest.GenerationSpec(
        model_id="gemini-1.5-flash",
    ),
    # Conversation between user and model
    contents=[
        discoveryengine.GroundedGenerationContent(
            role="user",
            parts=[
                discoveryengine.GroundedGenerationContent.Part(
                    text="Summarize how to delete a data store in Vertex AI Agent Builder?"
                )
            ],
        )
    ],
    grounding_spec=discoveryengine.GenerateGroundedContentRequest.GroundingSpec(
        grounding_sources=[
            discoveryengine.GenerateGroundedContentRequest.GroundingSource(
                google_search_source=discoveryengine.GenerateGroundedContentRequest.GroundingSource.GoogleSearchSource()
            ),
        ]
    ),
)
responses = client.stream_generate_grounded_content(iter([request]))

for response in responses:
    # Handle the response
    print(response)

后续步骤

如需搜索和过滤其他 Google Cloud 产品的代码示例，请参阅 Google Cloud 示例浏览器。