llmPlugin

import { llmPlugin } from '@routecraft/ai'

Registers LLM provider credentials in the context store. Required when any capability uses llm(). Configure once; all llm() calls in the context share it.

import { llmPlugin } from '@routecraft/ai'
import type { CraftConfig } from '@routecraft/routecraft'

const config: CraftConfig = {
  plugins: [
    llmPlugin({
      providers: {
        anthropic: { apiKey: process.env.ANTHROPIC_API_KEY },
        openai: { apiKey: process.env.OPENAI_API_KEY },
      },
    }),
  ],
}

export default config

Options:

Providers:

LM Studio

LM Studio serves an OpenAI-compatible chat-completions API, so the lmstudio provider needs no API key. Start the local server in LM Studio, load a model, then reference it by the loaded model id:

llmPlugin({ providers: { lmstudio: {} } })
// llm("lmstudio:qwen2.5-7b-instruct")

Requires the @ai-sdk/openai-compatible peer (bun add @ai-sdk/openai-compatible); a missing peer raises a clear install error. Token usage is reported on both buffered and streaming responses.

Custom (bring your own model)

The custom provider is an escape hatch for running llm() or agent() against a model the built-in providers do not cover, including a deterministic in-process model for tests or offline demos. Supply an AI SDK LanguageModel directly, or a factory that receives the model name:

import { MockLanguageModelV3 } from 'ai/test'

llmPlugin({
  providers: {
    custom: {
      model: new MockLanguageModelV3({
        doGenerate: async () => ({
          finishReason: 'stop',
          usage: { inputTokens: 0, outputTokens: 0 },
          content: [{ type: 'text', text: 'Hello from a local model' }],
          warnings: [],
        }),
      }),
    },
  },
})
// llm("custom:local")

See llm adapter for usage.