mirror of
https://github.com/google/adk-docs.git
synced 2026-09-14 16:16:59 +08:00
Ali Adnan
911869c6de
* fix: remove broken relative import in rag_engine example The snippet imported from a non-existent .prompts module and used an undefined return_instructions_root(). Replaced with a self-contained instruction string so the knowledge-engine example runs standalone. * Apply suggestion from @joefernandez --------- Co-authored-by: Joe Fernandez <931947+joefernandez@users.noreply.github.com>
54 lines
1.7 KiB
Python
54 lines
1.7 KiB
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
|
|
|
|
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-flash-latest",
|
|
name="ask_rag_agent",
|
|
instruction=(
|
|
"You are an expert RAG documentation assistant. Use the "
|
|
"retrieve_rag_documentation tool to fetch relevant documentation and "
|
|
"reference materials, then answer the user's question based on them."
|
|
),
|
|
tools=[
|
|
ask_vertex_retrieval,
|
|
],
|
|
)
|