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重构主控编排与运行时预热链路，统一工作区提示词/专家调度协议并补齐 wiki 记忆注入与写回闭环。
同时收敛启动与运维脚本默认行为（含 wiki worker）、更新 Admin 可观测性与相关测试，降低首轮时延并提高运行稳定性。 Made-with: Cursor
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357
openclaw/extensions/google/embedding-provider.ts
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357
openclaw/extensions/google/embedding-provider.ts
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@ -0,0 +1,357 @@
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import { parseGeminiAuth } from "openclaw/plugin-sdk/image-generation-core";
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import {
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buildRemoteBaseUrlPolicy,
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debugEmbeddingsLog,
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sanitizeAndNormalizeEmbedding,
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withRemoteHttpResponse,
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type EmbeddingInput,
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type MemoryEmbeddingProvider,
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type MemoryEmbeddingProviderCreateOptions,
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} from "openclaw/plugin-sdk/memory-core-host-engine-embeddings";
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import { resolveMemorySecretInputString } from "openclaw/plugin-sdk/memory-core-host-secret";
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import {
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collectProviderApiKeysForExecution,
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executeWithApiKeyRotation,
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requireApiKey,
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resolveApiKeyForProvider,
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} from "openclaw/plugin-sdk/provider-auth-runtime";
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import type { SsrFPolicy } from "openclaw/plugin-sdk/ssrf-runtime";
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import { normalizeOptionalString } from "openclaw/plugin-sdk/text-runtime";
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export type GeminiEmbeddingClient = {
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baseUrl: string;
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headers: Record<string, string>;
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ssrfPolicy?: SsrFPolicy;
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model: string;
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modelPath: string;
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apiKeys: string[];
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outputDimensionality?: number;
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};
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export const DEFAULT_GEMINI_EMBEDDING_MODEL = "gemini-embedding-001";
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const DEFAULT_GOOGLE_API_BASE_URL = "https://generativelanguage.googleapis.com/v1beta";
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const GEMINI_MAX_INPUT_TOKENS: Record<string, number> = {
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"text-embedding-004": 2048,
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"gemini-embedding-001": 2048,
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"gemini-embedding-2-preview": 8192,
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};
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export type GeminiTaskType = NonNullable<MemoryEmbeddingProviderCreateOptions["taskType"]>;
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// --- gemini-embedding-2-preview support ---
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export const GEMINI_EMBEDDING_2_MODELS = new Set([
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"gemini-embedding-2-preview",
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// Add the GA model name here once released.
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]);
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const GEMINI_EMBEDDING_2_DEFAULT_DIMENSIONS = 3072;
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const GEMINI_EMBEDDING_2_VALID_DIMENSIONS = [768, 1536, 3072] as const;
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export type GeminiTextPart = { text: string };
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export type GeminiInlinePart = {
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inlineData: { mimeType: string; data: string };
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};
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export type GeminiPart = GeminiTextPart | GeminiInlinePart;
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export type GeminiEmbeddingRequest = {
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content: { parts: GeminiPart[] };
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taskType: GeminiTaskType;
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outputDimensionality?: number;
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model?: string;
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};
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export type GeminiTextEmbeddingRequest = GeminiEmbeddingRequest;
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/** Builds the text-only Gemini embedding request shape used across direct and batch APIs. */
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export function buildGeminiTextEmbeddingRequest(params: {
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text: string;
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taskType: GeminiTaskType;
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outputDimensionality?: number;
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modelPath?: string;
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}): GeminiTextEmbeddingRequest {
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return buildGeminiEmbeddingRequest({
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input: { text: params.text },
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taskType: params.taskType,
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outputDimensionality: params.outputDimensionality,
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modelPath: params.modelPath,
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});
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}
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export function buildGeminiEmbeddingRequest(params: {
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input: EmbeddingInput;
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taskType: GeminiTaskType;
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outputDimensionality?: number;
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modelPath?: string;
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}): GeminiEmbeddingRequest {
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const request: GeminiEmbeddingRequest = {
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content: {
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parts: params.input.parts?.map((part) =>
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part.type === "text"
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? ({ text: part.text } satisfies GeminiTextPart)
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: ({
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inlineData: { mimeType: part.mimeType, data: part.data },
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} satisfies GeminiInlinePart),
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) ?? [{ text: params.input.text }],
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},
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taskType: params.taskType,
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};
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if (params.modelPath) {
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request.model = params.modelPath;
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}
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if (params.outputDimensionality != null) {
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request.outputDimensionality = params.outputDimensionality;
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}
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return request;
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}
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/**
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* Returns true if the given model name is a gemini-embedding-2 variant that
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* supports `outputDimensionality` and extended task types.
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*/
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export function isGeminiEmbedding2Model(model: string): boolean {
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return GEMINI_EMBEDDING_2_MODELS.has(model);
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}
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/**
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* Validate and return the `outputDimensionality` for gemini-embedding-2 models.
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* Returns `undefined` for older models (they don't support the param).
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*/
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export function resolveGeminiOutputDimensionality(
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model: string,
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requested?: number,
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): number | undefined {
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if (!isGeminiEmbedding2Model(model)) {
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return undefined;
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}
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if (requested == null) {
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return GEMINI_EMBEDDING_2_DEFAULT_DIMENSIONS;
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}
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const valid: readonly number[] = GEMINI_EMBEDDING_2_VALID_DIMENSIONS;
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if (!valid.includes(requested)) {
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throw new Error(
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`Invalid outputDimensionality ${requested} for ${model}. Valid values: ${valid.join(", ")}`,
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);
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}
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return requested;
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}
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function resolveRemoteApiKey(remoteApiKey: unknown): string | undefined {
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const trimmed = resolveMemorySecretInputString({
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value: remoteApiKey,
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path: "agents.*.memorySearch.remote.apiKey",
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});
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if (!trimmed) {
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return undefined;
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}
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if (trimmed === "GOOGLE_API_KEY" || trimmed === "GEMINI_API_KEY") {
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return process.env[trimmed]?.trim();
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}
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return trimmed;
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}
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export function normalizeGeminiModel(model: string): string {
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const trimmed = model.trim();
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if (!trimmed) {
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return DEFAULT_GEMINI_EMBEDDING_MODEL;
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}
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const withoutPrefix = trimmed.replace(/^models\//, "");
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if (withoutPrefix.startsWith("gemini/")) {
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return withoutPrefix.slice("gemini/".length);
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}
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if (withoutPrefix.startsWith("google/")) {
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return withoutPrefix.slice("google/".length);
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}
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return withoutPrefix;
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}
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async function fetchGeminiEmbeddingPayload(params: {
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client: GeminiEmbeddingClient;
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endpoint: string;
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body: unknown;
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}): Promise<{
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embedding?: { values?: number[] };
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embeddings?: Array<{ values?: number[] }>;
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}> {
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return await executeWithApiKeyRotation({
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provider: "google",
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apiKeys: params.client.apiKeys,
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execute: async (apiKey) => {
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const authHeaders = parseGeminiAuth(apiKey);
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const headers = {
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...authHeaders.headers,
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...params.client.headers,
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};
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return await withRemoteHttpResponse({
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url: params.endpoint,
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ssrfPolicy: params.client.ssrfPolicy,
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init: {
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method: "POST",
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headers,
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body: JSON.stringify(params.body),
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},
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onResponse: async (res) => {
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if (!res.ok) {
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const text = await res.text();
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throw new Error(`gemini embeddings failed: ${res.status} ${text}`);
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}
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return (await res.json()) as {
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embedding?: { values?: number[] };
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embeddings?: Array<{ values?: number[] }>;
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};
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},
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});
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},
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});
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}
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function normalizeGeminiBaseUrl(raw: string): string {
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const trimmed = raw.replace(/\/+$/, "");
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const openAiIndex = trimmed.indexOf("/openai");
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if (openAiIndex > -1) {
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return normalizeGoogleApiBaseUrl(trimmed.slice(0, openAiIndex));
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}
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return normalizeGoogleApiBaseUrl(trimmed);
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}
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function buildGeminiModelPath(model: string): string {
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return model.startsWith("models/") ? model : `models/${model}`;
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}
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function normalizeGoogleApiBaseUrl(baseUrl: string): string {
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const trimmed = baseUrl.trim().replace(/\/+$/, "");
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if (!trimmed) {
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return DEFAULT_GOOGLE_API_BASE_URL;
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}
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try {
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const url = new URL(trimmed);
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url.hash = "";
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url.search = "";
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if (
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url.origin.toLowerCase() === "https://generativelanguage.googleapis.com" &&
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url.pathname.replace(/\/+$/, "") === ""
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) {
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url.pathname = "/v1beta";
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}
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return url.toString().replace(/\/+$/, "");
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} catch {
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return trimmed;
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}
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}
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export async function createGeminiEmbeddingProvider(
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options: MemoryEmbeddingProviderCreateOptions,
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): Promise<{ provider: MemoryEmbeddingProvider; client: GeminiEmbeddingClient }> {
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const client = await resolveGeminiEmbeddingClient(options);
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const baseUrl = client.baseUrl.replace(/\/$/, "");
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const embedUrl = `${baseUrl}/${client.modelPath}:embedContent`;
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const batchUrl = `${baseUrl}/${client.modelPath}:batchEmbedContents`;
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const isV2 = isGeminiEmbedding2Model(client.model);
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const outputDimensionality = client.outputDimensionality;
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const embedQuery = async (text: string): Promise<number[]> => {
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if (!text.trim()) {
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return [];
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}
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const payload = await fetchGeminiEmbeddingPayload({
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client,
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endpoint: embedUrl,
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body: buildGeminiTextEmbeddingRequest({
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text,
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taskType: options.taskType ?? "RETRIEVAL_QUERY",
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outputDimensionality: isV2 ? outputDimensionality : undefined,
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}),
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});
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return sanitizeAndNormalizeEmbedding(payload.embedding?.values ?? []);
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};
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const embedBatchInputs = async (inputs: EmbeddingInput[]): Promise<number[][]> => {
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if (inputs.length === 0) {
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return [];
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}
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const payload = await fetchGeminiEmbeddingPayload({
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client,
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endpoint: batchUrl,
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body: {
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requests: inputs.map((input) =>
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buildGeminiEmbeddingRequest({
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input,
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modelPath: client.modelPath,
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taskType: options.taskType ?? "RETRIEVAL_DOCUMENT",
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outputDimensionality: isV2 ? outputDimensionality : undefined,
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}),
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),
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},
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});
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const embeddings = Array.isArray(payload.embeddings) ? payload.embeddings : [];
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return inputs.map((_, index) => sanitizeAndNormalizeEmbedding(embeddings[index]?.values ?? []));
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};
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const embedBatch = async (texts: string[]): Promise<number[][]> => {
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return await embedBatchInputs(
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texts.map((text) => ({
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text,
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})),
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);
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};
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return {
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provider: {
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id: "gemini",
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model: client.model,
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maxInputTokens: GEMINI_MAX_INPUT_TOKENS[client.model],
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embedQuery,
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embedBatch,
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embedBatchInputs,
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},
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client,
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};
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}
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export async function resolveGeminiEmbeddingClient(
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options: MemoryEmbeddingProviderCreateOptions,
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): Promise<GeminiEmbeddingClient> {
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const remote = options.remote;
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const remoteApiKey = resolveRemoteApiKey(remote?.apiKey);
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const remoteBaseUrl = remote?.baseUrl?.trim();
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const apiKey = remoteApiKey
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? remoteApiKey
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: requireApiKey(
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await resolveApiKeyForProvider({
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provider: "google",
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cfg: options.config,
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agentDir: options.agentDir,
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}),
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"google",
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);
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const providerConfig = options.config.models?.providers?.google;
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const rawBaseUrl =
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remoteBaseUrl ||
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normalizeOptionalString(providerConfig?.baseUrl) ||
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DEFAULT_GOOGLE_API_BASE_URL;
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const baseUrl = normalizeGeminiBaseUrl(rawBaseUrl);
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const ssrfPolicy = buildRemoteBaseUrlPolicy(baseUrl);
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const headerOverrides = Object.assign({}, providerConfig?.headers, remote?.headers);
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const headers: Record<string, string> = {
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...headerOverrides,
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};
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const apiKeys = collectProviderApiKeysForExecution({
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provider: "google",
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primaryApiKey: apiKey,
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});
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const model = normalizeGeminiModel(options.model);
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const modelPath = buildGeminiModelPath(model);
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const outputDimensionality = resolveGeminiOutputDimensionality(
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model,
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options.outputDimensionality,
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);
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debugEmbeddingsLog("memory embeddings: gemini client", {
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rawBaseUrl,
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baseUrl,
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model,
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modelPath,
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outputDimensionality,
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embedEndpoint: `${baseUrl}/${modelPath}:embedContent`,
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batchEndpoint: `${baseUrl}/${modelPath}:batchEmbedContents`,
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});
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return { baseUrl, headers, ssrfPolicy, model, modelPath, apiKeys, outputDimensionality };
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}
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