From 5992e07a12d49ff19fc69c661249ccc0a88ec76c Mon Sep 17 00:00:00 2001 From: haranrk Date: Tue, 21 Jul 2026 03:49:37 +0000 Subject: [PATCH] docs: remove Agent Config page Removes the Agent Config documentation page (docs/agents/config.md) and its navigation entry in mkdocs.yml. --- docs/agents/config.md | 310 ------------------------------------------ mkdocs.yml | 1 - 2 files changed, 311 deletions(-) delete mode 100644 docs/agents/config.md diff --git a/docs/agents/config.md b/docs/agents/config.md deleted file mode 100644 index 6249931601..0000000000 --- a/docs/agents/config.md +++ /dev/null @@ -1,310 +0,0 @@ -# Build agents with Agent Config - -
- Supported in ADKPython v1.11.0Java v0.3.0Go v0.3.0Experimental -
- -The ADK Agent Config feature lets you build an ADK workflow without writing -code. An Agent Config uses a YAML format text file with a brief description of -the agent, allowing just about anyone to assemble and run an ADK agent. The -following is a simple example of a basic Agent Config definition: - -```yaml -name: assistant_agent -model: gemini-flash-latest -description: A helper agent that can answer users' questions. -instruction: You are an agent to help answer users' various questions. -``` - -You can use Agent Config files to build more complex agents which can -incorporate Functions, Tools, Sub-Agents, and more. This page describes how to -build and run ADK workflows with the Agent Config feature. For detailed -information on the syntax and settings supported by the Agent Config format, -see the -[Agent Config syntax reference](/api-reference/agentconfig/). - -!!! example "Experimental" - The Agent Config feature is experimental and has some - [known limitations](#known-limitations). We welcome your - [feedback](https://github.com/google/adk-python/issues/new?template=feature_request.md&labels=agent%20config)! - -## Get started - -This section describes how to set up and start building agents with the ADK and -the Agent Config feature, including installation setup, building an agent, and -running your agent. - -### Setup - -You need to install the Google Agent Development Kit libraries, and provide an -access key for a generative AI model such as Gemini API. This section provides -details on what you must install and configure before you can run agents with -the Agent Config files. - -!!! note - The Agent Config feature currently only supports Gemini models. For more - information about additional; functional restrictions, see - [Known limitations](#known-limitations). - -To set up ADK for use with Agent Config: - -1. Install the ADK Python libraries by following the - [Installation](/get-started/installation/#python) - instructions. *Python is currently required.* For more information, see the - [Known limitations](#known-limitations). -1. Verify that ADK is installed by running the following command in your - terminal: - - adk --version - - This command should show the ADK version you have installed. - -!!! Tip - If the `adk` command fails to run and the version is not listed in step 2, make - sure your Python environment is active. Execute `source .venv/bin/activate` in - your terminal on Mac and Linux. For other platform commands, see the - [Installation](/get-started/installation/#python) - page. - -### Build an agent - -You build an agent with Agent Config using the `adk create` command to create -the project files for an agent, and then editing the `root_agent.yaml` file it -generates for you. - -To create an ADK project for use with Agent Config: - -1. In your terminal window, run the following command to create a - config-based agent: - - adk create --type=config my_agent - - This command generates a `my_agent/` folder, containing a - `root_agent.yaml` file and an `.env` file. - -1. In the `my_agent/.env` file, set environment variables for your agent to - access generative AI models and other services: - - 1. For Gemini model access through Google API, add a line to the - file with your API key: - - GOOGLE_GENAI_USE_ENTERPRISE=0 - GOOGLE_API_KEY= - - You can get an API key from the Google AI Studio - [API Keys](https://aistudio.google.com/app/apikey) page. - - 1. For Gemini model access through Google Cloud, add these lines to the file: - - GOOGLE_GENAI_USE_ENTERPRISE=1 - GOOGLE_CLOUD_PROJECT= - GOOGLE_CLOUD_LOCATION=us-central1 - - For information on creating a Cloud Project, see the Google Cloud docs for - [Creating and managing projects](https://cloud.google.com/resource-manager/docs/creating-managing-projects). - For more information on connecting to Google Cloud from ADK agents, see - [Connect to Google Cloud and Agent Platform](/get-started/google-cloud/). - -1. Using text editor, edit the Agent Config file - `my_agent/root_agent.yaml`, as shown below: - -``` -# yaml-language-server: $schema=https://raw.githubusercontent.com/google/adk-python/refs/heads/main/src/google/adk/agents/config_schemas/AgentConfig.json -name: assistant_agent -model: gemini-flash-latest -description: A helper agent that can answer users' questions. -instruction: You are an agent to help answer users' various questions. -``` - -You can discover more configuration options for your `root_agent.yaml` agent -configuration file by referring to the ADK -[samples repository](https://github.com/search?q=repo%3Agoogle%2Fadk-python+path%3A%2F%5Econtributing%5C%2Fsamples%5C%2F%2F+.yaml&type=code) -or the -[Agent Config syntax](/api-reference/agentconfig/) -reference. - -### Run the agent - -Once you have completed editing your Agent Config, you can run your agent using -the web interface, command line terminal execution, or API server mode. - -To run your Agent Config-defined agent: - -1. In your terminal, navigate to the `my_agent/` directory containing the - `root_agent.yaml` file. -1. Type one of the following commands to run your agent: - - `adk web` - Run web UI interface for your agent. - - `adk run` - Run your agent in the terminal without a user - interface. - - `adk api_server` - Run your agent as a service that can be - used by other applications. - -For more information on the ways to run your agent, see -[Agent Runtime](/runtime/#ways-to-run-agents). -For more information about the ADK command line options, see the -[ADK CLI reference](/api-reference/cli/). - -### Run programmatically - -You can also bypass the CLI and dynamically load and execute a configuration-based agent directly in your code. The utility loads the configuration and instantiates the proper agent class (such as `LlmAgent`) transparently as a `BaseAgent` subclass. - -=== "Python" - - ```python - import asyncio - from google.adk.agents import config_agent_utils - from google.adk.runners import Runner - - async def main(): - # Load the agent directly from the YAML config file - agent = config_agent_utils.from_config("my_agent/root_agent.yaml") - # ... - - if __name__ == "__main__": - asyncio.run(main()) - ``` - -=== "Java" - - ```java - import com.google.adk.agents.BaseAgent; - import com.google.adk.agents.ConfigAgentUtils; - - public class AgentApp { - public static void main(String[] args) throws Exception { - // Load the agent directly from the YAML config file - BaseAgent agent = ConfigAgentUtils.fromConfig("my_agent/root_agent.yaml"); - // ... - } - } - ``` - -## Example configs - -This section shows examples of Agent Config files to get you started building -agents. For additional and more complete examples, see the ADK -[samples repository](https://github.com/search?q=repo%3Agoogle%2Fadk-python+path%3A%2F%5Econtributing%5C%2Fsamples%5C%2F%2F+root_agent.yaml&type=code). - -### Built-in tool example - -The following example uses a built-in ADK tool function for using google search -to provide functionality to the agent. This agent automatically uses the search -tool to reply to user requests. - -``` -# yaml-language-server: $schema=https://raw.githubusercontent.com/google/adk-python/refs/heads/main/src/google/adk/agents/config_schemas/AgentConfig.json -name: search_agent -model: gemini-flash-latest -description: 'an agent whose job it is to perform Google search queries and answer questions about the results.' -instruction: You are an agent whose job is to perform Google search queries and answer questions about the results. -tools: - - name: google_search -``` - -For more details, see the full code for this sample in the -[ADK sample repository](https://github.com/google/adk-python/blob/main/contributing/samples/tools/tool_builtin_config/root_agent.yaml). - -### Custom tool example - -The following example uses a custom tool built with Python code and listed in -the `tools:` section of the config file. The agent uses this tool to check if a -list of numbers provided by the user are prime numbers. - -``` -# yaml-language-server: $schema=https://raw.githubusercontent.com/google/adk-python/refs/heads/main/src/google/adk/agents/config_schemas/AgentConfig.json -agent_class: LlmAgent -model: gemini-flash-latest -name: prime_agent -description: Handles checking if numbers are prime. -instruction: | - You are responsible for checking whether numbers are prime. - When asked to check primes, you must call the check_prime tool with a list of integers. - Never attempt to determine prime numbers manually. - Return the prime number results to the root agent. -tools: - - name: ma_llm.check_prime -``` - -For more details, see the full code for this sample in the -[ADK sample repository](https://github.com/google/adk-python/blob/main/contributing/samples/multi_agent/multi_agent_llm_config/prime_agent.yaml). - -### Sub-agents example - -The following example shows an agent defined with two sub-agents in the -`sub_agents:` section, and an example tool in the `tools:` section of the config -file. This agent determines what the user wants, and delegates to one of the -sub-agents to resolve the request. The sub-agents are defined using Agent Config -YAML files. - -``` -# yaml-language-server: $schema=https://raw.githubusercontent.com/google/adk-python/refs/heads/main/src/google/adk/agents/config_schemas/AgentConfig.json -agent_class: LlmAgent -model: gemini-flash-latest -name: root_agent -description: Learning assistant that provides tutoring in code and math. -instruction: | - You are a learning assistant that helps students with coding and math questions. - - You delegate coding questions to the code_tutor_agent and math questions to the math_tutor_agent. - - Follow these steps: - 1. If the user asks about programming or coding, delegate to the code_tutor_agent. - 2. If the user asks about math concepts or problems, delegate to the math_tutor_agent. - 3. Always provide clear explanations and encourage learning. -sub_agents: - - config_path: code_tutor_agent.yaml - - config_path: math_tutor_agent.yaml -``` - -For more details, see the full code for this sample in the -[ADK sample repository](https://github.com/google/adk-python/blob/main/contributing/samples/multi_agent/multi_agent_basic_config/root_agent.yaml). - -## Deploy agent configs - -You can deploy Agent Config agents with -[Cloud Run](/deploy/cloud-run/) and -[Agent Runtime](/deploy/agent-runtime/), -using the same procedure as code-based agents. For more information on how -to prepare and deploy Agent Config-based agents, see the -[Cloud Run](/deploy/cloud-run/) and -[Agent Runtime](/deploy/agent-runtime/) -deployment guides. - -## Known limitations {#known-limitations} - -The Agent Config feature is experimental and includes the following -limitations: - -- **Model support:** Only Gemini models are currently supported. - Integration with third-party models is in progress. -- **Programming language:** The Agent Config feature currently supports - Python and Java code for tools and other functionality requiring programming code. -- **ADK Tool support:** The following ADK tools are supported by the Agent - Config feature, but *not all tools are fully supported*: - - `google_search` - - `google_maps_grounding` - - `load_artifacts` - - `url_context` - - `exit_loop` - - `preload_memory` - - `get_user_choice` - - `enterprise_web_search` - - `load_web_page`: Requires a fully-qualified path to access web - pages. - - `AgentTool`: Allows an agent to call another agent. - - `LongRunningFunctionTool`: Supports long-running functions. - - `McpToolset`: Connects to Model Context Protocol (MCP) servers. - - `ExampleTool`: Provides example-based few-shot learning for tools. -- **Agent Type Support:** The `LangGraphAgent` and `A2aAgent` types are - not yet supported. -- **Agent Search:** The `VertexAiSearchTool` is currently supported in - Python and Java Agent Configs. - -## Next steps - -For ideas on how and what to build with ADK Agent Configs, see the yaml-based -agent definitions in the ADK -[adk-samples](https://github.com/search?q=repo:google/adk-python+path:/%5Econtributing%5C/samples%5C//+root_agent.yaml&type=code) -repository. For detailed information on the syntax and settings supported by -the Agent Config format, see the -[Agent Config syntax reference](/api-reference/agentconfig/). diff --git a/mkdocs.yml b/mkdocs.yml index c632259df7..3ef1d106f6 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -285,7 +285,6 @@ nav: - Python: get-started/streaming/quickstart-streaming.md - Java: get-started/streaming/quickstart-streaming-java.md - Code with AI: tutorials/coding-with-ai.md - - Agent Config: agents/config.md - Agents: - agents/index.md - Simple agents: agents/llm-agents.md