google--adk-python/contributing/samples/managed_agent/code_execution

Managed Agent - Code Execution

For setup, authentication, backends, and background on ManagedAgent, see the ManagedAgent guide.

Overview

This sample runs a ManagedAgent configured with the built-in code execution tool so it can write and run code server-side to compute answers.

Unlike a regular LlmAgent (which enables code execution via code_executor=BuiltInCodeExecutor()), ManagedAgent has no code_executor field. Instead you pass the raw built-in tool config types.Tool(code_execution=types.ToolCodeExecution()) in tools -- the same config BuiltInCodeExecutor produces under the hood. This makes the sample a demonstration of the raw types.Tool server-side tool path.

Sample Inputs

• What is the sum of the first 50 prime numbers? Use code to compute it.

  The model writes and runs code server-side; the answer (5117) comes from the executed code rather than the model guessing.

• Now do the same for the first 100 primes.

  A follow-up turn that reuses the recovered remote sandbox and the previous interaction (answer: 24133), demonstrating multi-turn chaining.

Graph

graph LR
    User -->|message| ManagedAgent
    ManagedAgent -->|interactions.create| ManagedAgentsAPI
    ManagedAgentsAPI -->|server-side code execution| ManagedAgentsAPI
    ManagedAgentsAPI -->|streamed events| ManagedAgent
    ManagedAgent -->|answer| User

How To

• Create the agent: instantiate ManagedAgent with an agent_id, an environment spec, and tools=[types.Tool(code_execution=types.ToolCodeExecution())]. No model is set -- the model is part of the managed agent on the server.
• Enable code execution: ManagedAgent has no code_executor field, so the raw types.Tool(code_execution=...) config is passed in tools. The interactions converter turns it into the server-side code_execution tool.
• Provision a sandbox: environment={'type': 'remote'} requests a fresh remote sandbox. The resulting environment id is stored on emitted events, so subsequent turns automatically recover and reuse it.
• Multi-turn chaining: the agent recovers the previous_interaction_id from the session events, so follow-up turns continue the same interaction without any extra wiring.
• Drive it: a ManagedAgent is a BaseAgent, so a standard Runner runs it just like any other agent.