interactive codelab

Learn agentu by doing

Master the AI agent runtime - tools, sandboxing, workflows, guardrails, and more. Write and run real Python code directly in your browser.

pip install agentu

Agent + Tools

Create agents, attach tools, execute with type-safe schemas.

Permissions

READONLY / WRITE / DANGEROUS access control for tools.

Memory

SQLite-backed remember/recall with importance-weighted search.

Caching

SHA-256 exact match, semantic, offline, and distributed presets.

Guardrails

NoPII, NoHallucination with automatic self-correction.

Workflows

Sequential, parallel, fan-out/fan-in with operator chaining.

Evaluation

Test suites, validators, accuracy metrics, LLM-as-judge.

Observability

Auto-tracked events, metrics, and full execution traces.

Sandbox

Separate read/write tool buckets with least-privilege defaults.

Sessions

Multi-turn stateful conversations with isolated contexts.

Skills

Progressive-load domain expertise. 3-level context optimization.

LLM Inference

Route queries through Ollama, OpenAI, or Anthropic.

MCP

Discover and use tools from external Model Context Protocol servers.

REST API

Serve agents via HTTP, WebSocket, and SSE with one call.

Rules

Feedforward AGENTS.md rules prepended to every LLM call.

Middleware

CostTracker, Logger, Retry - composable processing pipeline.

16 lessons · ~60 min · zero setup

agentu codelab

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main.py
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Exercise