mirror of
https://github.com/openclaw/openclaw.git
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254 lines
8.2 KiB
TypeScript
254 lines
8.2 KiB
TypeScript
import fs from "node:fs";
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import { homedir } from "node:os";
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import { join } from "node:path";
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export type MemoryConfig = {
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embedding: {
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provider: string;
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model: string;
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apiKey?: string;
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baseUrl?: string;
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dimensions?: number;
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};
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dreaming?: Record<string, unknown>;
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dbPath?: string;
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autoCapture?: boolean;
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autoRecall?: boolean;
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captureMaxChars?: number;
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recallMaxChars?: number;
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storageOptions?: Record<string, string>;
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};
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export const MEMORY_CATEGORIES = ["preference", "fact", "decision", "entity", "other"] as const;
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export type MemoryCategory = (typeof MEMORY_CATEGORIES)[number];
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const DEFAULT_MODEL = "text-embedding-3-small";
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export const DEFAULT_CAPTURE_MAX_CHARS = 500;
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export const DEFAULT_RECALL_MAX_CHARS = 1000;
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const LEGACY_STATE_DIRS: string[] = [];
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function resolveDefaultDbPath(): string {
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const home = homedir();
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const preferred = join(home, ".openclaw", "memory", "lancedb");
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try {
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if (fs.existsSync(preferred)) {
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return preferred;
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}
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} catch {
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// best-effort
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}
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for (const legacy of LEGACY_STATE_DIRS) {
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const candidate = join(home, legacy, "memory", "lancedb");
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try {
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if (fs.existsSync(candidate)) {
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return candidate;
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}
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} catch {
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// best-effort
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}
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}
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return preferred;
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}
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const DEFAULT_DB_PATH = resolveDefaultDbPath();
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const EMBEDDING_DIMENSIONS: Record<string, number> = {
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"text-embedding-3-small": 1536,
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"text-embedding-3-large": 3072,
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};
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const EMBEDDING_CONFIG_KEYS = ["provider", "apiKey", "model", "baseUrl", "dimensions"] as const;
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function assertAllowedKeys(value: Record<string, unknown>, allowed: string[], label: string) {
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const unknown = Object.keys(value).filter((key) => !allowed.includes(key));
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if (unknown.length === 0) {
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return;
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}
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throw new Error(`${label} has unknown keys: ${unknown.join(", ")}`);
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}
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export function vectorDimsForModel(model: string): number {
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const dims = EMBEDDING_DIMENSIONS[model];
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if (!dims) {
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throw new Error(`Unsupported embedding model: ${model}`);
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}
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return dims;
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}
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function resolveEnvVars(value: string): string {
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return value.replace(/\$\{([^}]+)\}/g, (_, envVar) => {
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const envValue = process.env[envVar];
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if (!envValue) {
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throw new Error(`Environment variable ${envVar} is not set`);
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}
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return envValue;
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});
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}
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function resolveEmbeddingModel(embedding: Record<string, unknown>): string {
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const model = typeof embedding.model === "string" ? embedding.model : DEFAULT_MODEL;
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if (typeof embedding.dimensions !== "number") {
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vectorDimsForModel(model);
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}
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return model;
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}
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export const memoryConfigSchema = {
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parse(value: unknown): MemoryConfig {
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if (!value || typeof value !== "object" || Array.isArray(value)) {
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throw new Error("memory config required");
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}
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const cfg = value as Record<string, unknown>;
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assertAllowedKeys(
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cfg,
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[
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"embedding",
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"dreaming",
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"dbPath",
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"autoCapture",
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"autoRecall",
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"captureMaxChars",
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"recallMaxChars",
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"storageOptions",
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],
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"memory config",
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);
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const embedding = cfg.embedding as Record<string, unknown> | undefined;
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if (!embedding || typeof embedding !== "object" || Array.isArray(embedding)) {
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throw new Error("embedding config required");
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}
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assertAllowedKeys(embedding, [...EMBEDDING_CONFIG_KEYS], "embedding config");
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if (Object.keys(embedding).length === 0) {
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throw new Error("embedding config must include at least one setting");
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}
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const model = resolveEmbeddingModel(embedding);
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const provider = typeof embedding.provider === "string" ? embedding.provider.trim() : "openai";
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if (!provider) {
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throw new Error("embedding.provider must not be empty");
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}
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const captureMaxChars =
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typeof cfg.captureMaxChars === "number" ? Math.floor(cfg.captureMaxChars) : undefined;
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const recallMaxChars =
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typeof cfg.recallMaxChars === "number" ? Math.floor(cfg.recallMaxChars) : undefined;
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if (
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typeof captureMaxChars === "number" &&
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(captureMaxChars < 100 || captureMaxChars > 10_000)
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) {
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throw new Error("captureMaxChars must be between 100 and 10000");
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}
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if (typeof recallMaxChars === "number" && (recallMaxChars < 100 || recallMaxChars > 10_000)) {
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throw new Error("recallMaxChars must be between 100 and 10000");
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}
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const dreaming =
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cfg.dreaming === undefined
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? undefined
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: cfg.dreaming && typeof cfg.dreaming === "object" && !Array.isArray(cfg.dreaming)
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? (cfg.dreaming as Record<string, unknown>)
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: (() => {
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throw new Error("dreaming config must be an object");
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})();
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// Parse storageOptions (object with string values)
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let storageOptions: Record<string, string> | undefined;
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const storageOpts = cfg.storageOptions as Record<string, unknown> | undefined;
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if (storageOpts !== undefined && storageOpts !== null) {
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if (!storageOpts || typeof storageOpts !== "object" || Array.isArray(storageOpts)) {
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throw new Error("storageOptions must be an object");
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}
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storageOptions = {};
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// Validate all values are strings
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for (const [key, value] of Object.entries(storageOpts)) {
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if (typeof value !== "string") {
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throw new Error(`storageOptions.${key} must be a string`);
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}
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storageOptions[key] = resolveEnvVars(value);
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}
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}
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return {
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embedding: {
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provider,
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model,
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apiKey: typeof embedding.apiKey === "string" ? resolveEnvVars(embedding.apiKey) : undefined,
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baseUrl:
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typeof embedding.baseUrl === "string" ? resolveEnvVars(embedding.baseUrl) : undefined,
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dimensions: typeof embedding.dimensions === "number" ? embedding.dimensions : undefined,
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},
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dreaming,
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dbPath: typeof cfg.dbPath === "string" ? cfg.dbPath : DEFAULT_DB_PATH,
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autoCapture: cfg.autoCapture === true,
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autoRecall: cfg.autoRecall !== false,
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captureMaxChars: captureMaxChars ?? DEFAULT_CAPTURE_MAX_CHARS,
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recallMaxChars: recallMaxChars ?? DEFAULT_RECALL_MAX_CHARS,
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...(storageOptions ? { storageOptions } : {}),
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};
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},
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uiHints: {
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"embedding.provider": {
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label: "Embedding Provider",
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placeholder: "openai",
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help: "Memory embedding provider adapter to use (for example openai, github-copilot, ollama)",
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},
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"embedding.apiKey": {
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label: "OpenAI API Key",
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sensitive: true,
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placeholder: "sk-proj-...",
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help: "Optional API key override for OpenAI-compatible embeddings; omit to use configured provider auth",
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},
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"embedding.baseUrl": {
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label: "Base URL",
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placeholder: "https://api.openai.com/v1",
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help: "Optional provider or OpenAI-compatible embedding endpoint base URL",
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advanced: true,
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},
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"embedding.dimensions": {
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label: "Dimensions",
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placeholder: "1536",
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help: "Vector dimensions for custom models (required for non-standard models)",
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advanced: true,
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},
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"embedding.model": {
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label: "Embedding Model",
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placeholder: DEFAULT_MODEL,
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help: "OpenAI embedding model to use",
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},
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dbPath: {
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label: "Database Path",
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placeholder: "~/.openclaw/memory/lancedb",
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advanced: true,
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help: "Local filesystem path or cloud storage URI (s3://, gs://) for LanceDB database",
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},
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autoCapture: {
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label: "Auto-Capture",
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help: "Automatically capture important information from conversations",
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},
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autoRecall: {
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label: "Auto-Recall",
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help: "Automatically inject relevant memories into context",
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},
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captureMaxChars: {
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label: "Capture Max Chars",
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help: "Maximum message length eligible for auto-capture",
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advanced: true,
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placeholder: String(DEFAULT_CAPTURE_MAX_CHARS),
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},
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recallMaxChars: {
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label: "Recall Query Max Chars",
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help: "Maximum prompt/query length embedded for memory recall. Lower for small local embedding models.",
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advanced: true,
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placeholder: String(DEFAULT_RECALL_MAX_CHARS),
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},
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storageOptions: {
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label: "Storage Options",
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sensitive: true,
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advanced: true,
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help: "Storage configuration options (access_key, secret_key, endpoint, etc.); supports ${ENV_VAR} values",
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},
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},
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};
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