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46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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from google.adk.agents.llm_agent import LlmAgent
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from google.adk.integrations.api_registry import ApiRegistry
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# TODO: Fill in with your GCloud project id and MCP server name
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PROJECT_ID = "your-google-cloud-project-id"
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MCP_SERVER_NAME = "your-mcp-server-name"
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api_registry = ApiRegistry(PROJECT_ID)
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registry_tools = api_registry.get_toolset(
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mcp_server_name=MCP_SERVER_NAME,
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)
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root_agent = LlmAgent(
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name="bigquery_assistant",
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instruction=f"""
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You are a helpful data analyst assistant with access to BigQuery. The project ID is: {PROJECT_ID}
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When users ask about data:
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- Use the project ID {PROJECT_ID} when calling BigQuery tools.
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- First, explore available datasets and tables to understand what data exists.
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- Check table schemas to understand the structure before querying.
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- Write clear, efficient SQL queries to answer their questions.
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- Explain your findings in simple, non-technical language.
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Mandatory Requirements:
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- Always use the BigQuery tools to fetch real data rather than making assumptions.
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- For all BigQuery operations, use project_id: {PROJECT_ID}.
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""",
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tools=[registry_tools],
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)
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