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README.md

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---
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## ✨ What's new
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- **Agent Config**: Build agents without code. Check out the
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[Agent Config](https://google.github.io/adk-docs/agents/config/) feature.
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## ✨ Key Features
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- **Rich Tool Ecosystem**: Utilize pre-built tools, custom functions,

autoformat.sh

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echo '| Auto-formatting src/...'
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echo '---------------------------------------'
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find -L src/ -type f -name "*.py" -exec pyink --config pyproject.toml {} +
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find -L src/ -not -path "*/.*" -type f -name "*.py" -exec pyink --config pyproject.toml {} +
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echo '---------------------------------------'
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echo '| Auto-formatting tests/...'
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echo '---------------------------------------'
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find -L tests/ -type f -name "*.py" -exec pyink --config pyproject.toml {} +
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find -L tests/ -not -path "*/.*" -type f -name "*.py" -exec pyink --config pyproject.toml {} +
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echo '---------------------------------------'
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echo '| Auto-formatting contributing/...'
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echo '---------------------------------------'
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find -L contributing/ -type f -name "*.py" -exec pyink --config pyproject.toml {} +
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find -L contributing/ -not -path "*/.*" -type f -name "*.py" -exec pyink --config pyproject.toml {} +

contributing/samples/adk_pr_triaging_agent/agent.py

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"documentation": "polong-lin",
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"services": "DeanChensj",
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"tools": "seanzhou1023",
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"mcp": "seanzhou1023",
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"eval": "ankursharmas",
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"live": "hangfei",
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"models": "genquan9",
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- If it's about model support(non-Gemini, like Litellm, Ollama, OpenAI models), label it with "models".
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- If it's about tracing, label it with "tracing".
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- If it's agent orchestration, agent definition, label it with "core".
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- If it's about Model Context Protocol (e.g. MCP tool, MCP toolset, MCP session management etc.), label it with "mcp".
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- If you can't find a appropriate labels for the PR, follow the previous instruction that starts with "IMPORTANT:".
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Here is the contribution guidelines:

contributing/samples/adk_triaging_agent/agent.py

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"documentation": "polong-lin",
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"services": "DeanChensj",
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"question": "",
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"mcp": "seanzhou1023",
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"tools": "seanzhou1023",
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"eval": "ankursharmas",
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"live": "hangfei",
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- If it's about tracing, label it with "tracing".
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- If it's agent orchestration, agent definition, label it with "core".
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- If it's about agent engine, label it with "agent engine".
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- If it's about Model Context Protocol (e.g. MCP tool, MCP toolset, MCP session management etc.), label it with "mcp".
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- If you can't find a appropriate labels for the issue, follow the previous instruction that starts with "IMPORTANT:".
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Call the `add_label_and_owner_to_issue` tool to label the issue, which will also assign the issue to the owner of the label.

contributing/samples/bigquery/README.md

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Runs a SQL query in BigQuery.
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1. `ask_data_insights`
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Natural language-in, natural language-out tool that answers questions
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about structured data in BigQuery. Provides a one-stop solution for generating
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insights from data.
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**Note**: This tool requires additional setup in your project. Please refer to
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the official [Conversational Analytics API documentation](https://cloud.google.com/gemini/docs/conversational-analytics-api/overview)
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for instructions.
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## How to use
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Set up environment variables in your `.env` file for using

contributing/samples/live_bidi_streaming_single_agent/agent.py

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root_agent = Agent(
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model='gemini-2.0-flash-live-preview-04-09', # for Vertex project
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# model='gemini-2.0-flash-live-001', # for AI studio key
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# model='gemini-2.0-flash-live-preview-04-09', # for Vertex project
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model='gemini-2.0-flash-live-001', # for AI studio key
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name='hello_world_agent',
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description=(
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'hello world agent that can roll a dice of 8 sides and check prime'
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# Config-based Agent Sample - LLM multi-agent
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http://google3/third_party/py/google/adk/open_source_workspace/contributing/samples/hello_world_ma/
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From contributing/samples/hello_world_ma/
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# Config-based Agent Sample - Human-In-The-Loop
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http://google3/third_party/py/google/adk/open_source_workspace/contributing/samples/human_in_loop/
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From contributing/samples/human_in_loop/
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# Config-based Agent Sample - MCP Toolset with Notion MCP Server
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This sample demonstrates how to configure an ADK agent to use the Notion MCP server for interacting with Notion pages and databases.
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## Setup Instructions
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### 1. Create a Notion Integration
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1. Go to [Notion Integrations](https://www.notion.so/my-integrations)
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2. Click "New integration"
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3. Give it a name and select your workspace
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4. Copy the "Internal Integration Secret" (starts with `ntn_`)
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For detailed setup instructions, see the [Notion MCP Server documentation](https://www.npmjs.com/package/@notionhq/notion-mcp-server).
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### 2. Configure the Agent
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Replace `<your_notion_token>` in `root_agent.yaml` with your actual Notion integration token:
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```yaml
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env:
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OPENAPI_MCP_HEADERS: '{"Authorization": "Bearer secret_your_actual_token_here", "Notion-Version": "2022-06-28"}'
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```
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### 3. Grant Integration Access
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**Important**: After creating the integration, you must grant it access to specific pages and databases:
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1. Go to `Access` tab in [Notion Integrations](https://www.notion.so/my-integrations) page
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2. Click "Edit access"
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3. Add pages or databases as needed
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### 4. Run the Agent
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Use the `adk web` to run the agent and interact with your Notion workspace.
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## Example Queries
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- "What can you do for me?"
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- "Search for 'project' in my pages"
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- "Create a new page called 'Meeting Notes'"
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- "List all my databases"
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## Troubleshooting
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- If you get "Unauthorized" errors, check that your token is correct
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- If you get "Object not found" errors, ensure you've granted the integration access to the specific pages/databases
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- Make sure the Notion API version in the headers matches what the MCP server expects

contributing/samples/tool_mcp_stdio_notion_config/root_agent.yaml

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OPENAPI_MCP_HEADERS: "{'Authorization': 'Bearer fake_notion_api_key', 'Notion-Version': '2022-06-28'}"
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OPENAPI_MCP_HEADERS: '{"Authorization": "Bearer <your_notion_token>", "Notion-Version": "2022-06-28"}'

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