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How to embed a read-only agent in your own Python app with Minimal Local Agent

Import AgentRuntime, set write_policy to deny, and run tasks that return a response plus a receipt hash.

Short answer: Install the package into your project; then load settings with Settings.load("agent.toml") and replace write_policy with deny; call runtime.run with your task. All steps.

Who it is forA backend developer adding an agent step to an internal tool who needs a tamper-evident record.

The problemMost agent frameworks are too large to embed and audit.

The outcomeA few lines of Python that run the agent and return a verifiable receipt.

What you need first

  • Python 3.11
  • Ollama (README example pulls qwen3.5:9b) or a Chat Completions-compatible API

Steps

  1. Install the package into your project
  2. Load settings with Settings.load("agent.toml") and replace write_policy with deny
  3. Call runtime.run with your task
  4. Store outcome.response and outcome.receipt_hash

Prompt for your agent

Using minimal_local_agent's AgentRuntime with write_policy="deny", run "List the workspace files" against <workspace> and print the response and receipt_hash. Verify the run made no writes.

Caveat. Memory, planning and delegation exist only in the unreleased v1.1.0; the published release is v1.0.0.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for MuzeAnisichael/minimal-local-agent and "Embed a read-only agent in your own Python app"

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