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Cloud Based Coding Agents

AI agents can write, test, and execute code entirely in cloud sandboxes, removing the need for local development environments, dependency management, or system configuration. Sandboxes provide isolated execution environments where agents can safely run code, test implementations, and iterate without affecting local systems or requiring complex setup.

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Power of Sandboxes

Sandboxes provide complete cloud-based execution environments that are pre-configured and ready to use. Agents can write code and execute it immediately without installing dependencies, configuring environments, or managing system requirements. Each sandbox is isolated, ensuring that code execution doesn’t interfere with other processes or require cleanup. This enables agents to work with any programming language, framework, or library without local constraints.

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Why It Makes Agents Better

Without cloud sandboxes, agents would need to either execute code locally (requiring complex setup and risking system security) or rely on limited execution environments. With sandboxes, agents can:

• Write and execute anywhere: Generate and run code without local development environments or dependencies
• Test safely: Execute untrusted code in isolated environments without security risks
• Work with any stack: Support any programming language, framework, or library without local installation
• Iterate quickly: Test code changes immediately without environment setup overhead
• Scale execution: Run multiple code executions in parallel across different sandboxes

This enables truly cloud-native coding agents that can work with any codebase, test any implementation, and execute code safely without local infrastructure requirements.

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Use Cases

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Code Generation Agents

Agents that generate code based on user requirements can write, test, and execute code in sandboxes, providing immediate feedback and validation without requiring users to set up local environments.

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Code Review Agents

Agents that review and analyze code can execute code in sandboxes to test functionality, check for bugs, and validate behavior without needing access to the original development environment.

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Automated Testing Agents

Agents that create and run test suites can execute tests in isolated sandboxes, ensuring consistent test environments and preventing interference between different test runs.

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Scenario: Code Generation and Execution

An agent receives a request to create a data processing script. It generates Python code, creates a sandbox, uploads the code, executes it with sample data, validates the output, and provides the results—all without requiring any local setup or dependencies from the user.

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Implementation: Cloud-Based Code Execution

1. Generate Code
   Agent generates code based on requirements using LLM.

2. Create Sandbox
   Agent creates a sandbox with appropriate resources for the code.

3. Upload Code
   Agent uploads generated code files to the sandbox.

4. Install Dependencies
   Agent installs required dependencies in the sandbox environment.

5. Execute Code
   Agent runs the code with test inputs in the isolated sandbox.

6. Validate Output
   Agent checks execution results and validates correctness.

7. Provide Results
   Agent returns execution results and validated code to the user.

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Example (TypeScript)

import SandboxSDK from '@avmcodes/sandbox-sdk';

const client = new SandboxSDK({
  apiKey: process.env['SANDBOX_SDK_API_KEY'],
});

async function executeGeneratedCode(code: string, dependencies: string[]) {
  // Create sandbox for code execution
  const sandbox = await client.sandboxes.create({
    name: 'Code Execution Sandbox',
    resources: {
      cpus: 2,
      memory: 1024,
    },
  });

  try {
    // Install dependencies if needed
    if (dependencies.length > 0) {
      await client.sandboxes.execute(sandbox.id, {
        command: `pip install ${dependencies.join(' ')}`,
        timeout: 120,
      });
    }

    // Write code to file in sandbox
    await client.sandboxes.execute(sandbox.id, {
      command: `cat > /tmp/script.py << 'EOF'\n${code}\nEOF`,
    });

    // Execute the code
    const result = await client.sandboxes.execute(sandbox.id, {
      command: 'python /tmp/script.py',
      timeout: 300,
    });

    // Return execution results
    return {
      success: result.status === 'completed' && result.exit_code === 0,
      stdout: result.stdout,
      stderr: result.stderr,
      exitCode: result.exit_code,
    };
  } finally {
    // Clean up sandbox
    // Sandbox cleanup would happen here
  }
}

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Next Steps

• Add support for multiple programming languages and frameworks
• Implement code file upload and management APIs
• Build dependency detection and automatic installation
• Create code execution result caching and sharing