ADK 的 Vertex AI RAG Engine 工具

Supported in ADKPython v0.1.0Java v0.2.0

vertex_ai_rag_retrieval 工具允许智能体使用 Vertex AI RAG Engine 执行私有数据检索。

当你使用 Vertex AI RAG Engine 基础功能时，你需要事先准备一个 RAG 语料库。请参阅 RAG ADK 智能体示例 或 Vertex AI RAG Engine 页面 以设置它。

警告：每个智能体单个工具限制

此工具在智能体实例中只能单独使用。 有关此限制和解决方法的更多信息,请参阅 ADK 工具的限制。

Python

# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os

from google.adk.agents import Agent
from google.adk.tools.retrieval.vertex_ai_rag_retrieval import VertexAiRagRetrieval
from vertexai.preview import rag

from dotenv import load_dotenv
from .prompts import return_instructions_root

load_dotenv()

ask_vertex_retrieval = VertexAiRagRetrieval(
    name='retrieve_rag_documentation',
    description=(
        'Use this tool to retrieve documentation and reference materials for the question from the RAG corpus,'
    ),
    rag_resources=[
        rag.RagResource(
            # please fill in your own rag corpus
            # here is a sample rag corpus for testing purpose
            # e.g. projects/123/locations/us-central1/ragCorpora/456
            rag_corpus=os.environ.get("RAG_CORPUS")
        )
    ],
    similarity_top_k=10,
    vector_distance_threshold=0.6,
)

root_agent = Agent(
    model='gemini-2.0-flash-001',
    name='ask_rag_agent',
    instruction=return_instructions_root(),
    tools=[
        ask_vertex_retrieval,
    ]
)