import { Type } from "@sinclair/typebox"; import { homedir } from "node:os"; import { join } from "node:path"; export type MemoryConfig = { embedding: { provider: "openai"; model?: string; apiKey: string; }; dbPath?: string; autoCapture?: boolean; autoRecall?: boolean; }; export const MEMORY_CATEGORIES = ["preference", "fact", "decision", "entity", "other"] as const; export type MemoryCategory = (typeof MEMORY_CATEGORIES)[number]; const DEFAULT_MODEL = "text-embedding-3-small"; const DEFAULT_DB_PATH = join(homedir(), ".clawdbot", "memory", "lancedb"); const EMBEDDING_DIMENSIONS: Record = { "text-embedding-3-small": 1536, "text-embedding-3-large": 3072, }; function assertAllowedKeys( value: Record, allowed: string[], label: string, ) { const unknown = Object.keys(value).filter((key) => !allowed.includes(key)); if (unknown.length === 0) return; throw new Error(`${label} has unknown keys: ${unknown.join(", ")}`); } export function vectorDimsForModel(model: string): number { const dims = EMBEDDING_DIMENSIONS[model]; if (!dims) { throw new Error(`Unsupported embedding model: ${model}`); } return dims; } function resolveEnvVars(value: string): string { return value.replace(/\$\{([^}]+)\}/g, (_, envVar) => { const envValue = process.env[envVar]; if (!envValue) { throw new Error(`Environment variable ${envVar} is not set`); } return envValue; }); } function resolveEmbeddingModel(embedding: Record): string { const model = typeof embedding.model === "string" ? embedding.model : DEFAULT_MODEL; vectorDimsForModel(model); return model; } export const memoryConfigSchema = { parse(value: unknown): MemoryConfig { if (!value || typeof value !== "object" || Array.isArray(value)) { throw new Error("memory config required"); } const cfg = value as Record; assertAllowedKeys(cfg, ["embedding", "dbPath", "autoCapture", "autoRecall"], "memory config"); const embedding = cfg.embedding as Record | undefined; if (!embedding || typeof embedding.apiKey !== "string") { throw new Error("embedding.apiKey is required"); } assertAllowedKeys(embedding, ["apiKey", "model"], "embedding config"); const model = resolveEmbeddingModel(embedding); return { embedding: { provider: "openai", model, apiKey: resolveEnvVars(embedding.apiKey), }, dbPath: typeof cfg.dbPath === "string" ? cfg.dbPath : DEFAULT_DB_PATH, autoCapture: cfg.autoCapture !== false, autoRecall: cfg.autoRecall !== false, }; }, uiHints: { "embedding.apiKey": { label: "OpenAI API Key", sensitive: true, placeholder: "sk-proj-...", help: "API key for OpenAI embeddings (or use ${OPENAI_API_KEY})", }, "embedding.model": { label: "Embedding Model", placeholder: DEFAULT_MODEL, help: "OpenAI embedding model to use", }, dbPath: { label: "Database Path", placeholder: "~/.clawdbot/memory/lancedb", advanced: true, }, autoCapture: { label: "Auto-Capture", help: "Automatically capture important information from conversations", }, autoRecall: { label: "Auto-Recall", help: "Automatically inject relevant memories into context", }, }, };