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Quickstart

This guide uses alquimia-core directly — no runtime service required. You will create a local agentspace, define a simple agent, and chat with it.

Prerequisites

Section titled “Prerequisites”
  • Python 3.12 installed.
  • An API key for an OpenAI-compatible LLM provider.
  • The alquimia-core package installed. See Installation for options.

Run your first agent

Section titled “Run your first agent”

  1. Create an agentspace. An agentspace is a namespace that holds agent configurations, secrets, and parameters.

  2. Register your API key as a secret in the agentspace. Secrets are referenced by name in the agent spec, never embedded directly.

  3. Create an agent configuration that declares the agent’s identity, system prompt, model connector, and memory strategy.

  4. Register the agent in the local registry.

  5. Start a conversation using the CLI and ask a question. The agent loads the spec, resolves the secret, calls the model, and returns an answer.

What happens under the hood

Section titled “What happens under the hood”
  1. The CLI loads the agent spec from the local registry.
  2. The core engine resolves the secret reference to your API key.
  3. The agent sends the conversation to the configured LLM.
  4. The response is returned and the session is persisted.

Next steps

Section titled “Next steps”