playbook

import { createConfigSchematics } from "@lmstudio/sdk";
import { homedir } from "os";
import path from "path";

const DEFAULTS = {
  playbookDirectory: path.join(homedir(), "Documents", "Playbook"),
};

export const configSchematics = createConfigSchematics()
  .field(
    "playbookDirectory",
    "string",
    {
      displayName: "Playbook Directory",
      subtitle: "Absolute path to the directory containing your Markdown knowledge files.",
      placeholder: path.join(homedir(), "Documents", "Playbook"),
    },
    DEFAULTS.playbookDirectory,
  )
  .field(
    "embeddingModel",
    "string",
    {
      displayName: "Embedding Model",
      subtitle: "Name of the embedding model loaded in LM Studio. Leave empty to use BM25-only search.",
    },
    "text-embedding-nomic-embed-text-v1.5",
  )
  .field(
    "lmStudioBaseUrl",
    "string",
    {
      displayName: "LM Studio Base URL",
      subtitle: "Base URL for the LM Studio local API.",
    },
    "http://127.0.0.1:1234",
  )
  .field(
    "maxRecallDocuments",
    "numeric",
    {
      int: true,
      min: 1,
      max: 20,
      displayName: "Max Recall Documents",
      subtitle: "Maximum number of documents returned by a single recall call.",
      slider: { min: 1, max: 20, step: 1 },
    },
    5,
  )
  .field(
    "minRecallScore",
    "numeric",
    {
      int: true,
      min: 0,
      max: 100,
      displayName: "Min Recall Score",
      subtitle: "Minimum relevance score (0–100) for a document to appear in recall results.",
      slider: { min: 0, max: 100, step: 5 },
    },
    60,
  )
  .build();