@mp-lb/agents-framework

Backend-resolved agent definitions and runtimes for MAP Lab apps.

Code owns the agent contract: agent ids, instruction prompt keys, input prompt keys, required variables, tools, runtime context, and inspectable metadata. The configured backend owns prompt storage, LLM calls, tracing, and prompt/run metadata.

const agents = createAgentRuntime({
  app: "instantagent",
  environment: "local",
  backend: langfuseBackend({
    llm: openAICompatibleLlm({
      apiKey: process.env.OPENROUTER_API_KEY,
      baseUrl: "https://openrouter.ai/api/v1",
      model: "openai/gpt-5.5",
    }),
  }),
  agents: [conciergeAgent],
});

await agents.boot();

const result = await agents.run("concierge", {
  context: {
    PRODUCT_NAME: "InstantAgent",
    userMessage: "Can you check this lease?",
  },
});

Use prompt(...) for backend-resolved instruction and input templates:

export const conciergeAgent = defineAgent({
  id: "concierge",
  name: "Concierge",
  instructions: [
    prompt("instantagent/concierge-system", {
      variables: ["PRODUCT_NAME"],
    }),
  ],
  input: prompt("instantagent/concierge-input", {
    variables: ["userMessage"],
  }),
  tools: [lookupPolicy],
});