feat(memory): add gemini embeddings + auto select providers
Co-authored-by: Gustavo Madeira Santana <gumadeiras@gmail.com>
This commit is contained in:
Peter Steinberger
145
src/memory/embeddings-gemini.ts
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145
src/memory/embeddings-gemini.ts
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@@ -0,0 +1,145 @@
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import { resolveApiKeyForProvider } from "../agents/model-auth.js";
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import { createSubsystemLogger } from "../logging.js";
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import type { EmbeddingProvider, EmbeddingProviderOptions } from "./embeddings.js";
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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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model: string;
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modelPath: string;
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};
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const DEFAULT_GEMINI_BASE_URL = "https://generativelanguage.googleapis.com/v1beta";
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export const DEFAULT_GEMINI_EMBEDDING_MODEL = "gemini-embedding-001";
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const debugEmbeddings = process.env.CLAWDBOT_DEBUG_MEMORY_EMBEDDINGS === "1";
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const log = createSubsystemLogger("memory/embeddings");
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const debugLog = (message: string, meta?: Record<string, unknown>) => {
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if (!debugEmbeddings) return;
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const suffix = meta ? ` ${JSON.stringify(meta)}` : "";
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log.raw(`${message}${suffix}`);
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};
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function resolveRemoteApiKey(remoteApiKey?: string): string | undefined {
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const trimmed = remoteApiKey?.trim();
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if (!trimmed) return undefined;
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if (trimmed === "GOOGLE_API_KEY" || trimmed === "GEMINI_API_KEY") {
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return process.env[trimmed]?.trim();
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}
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return trimmed;
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}
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function normalizeGeminiModel(model: string): string {
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const trimmed = model.trim();
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if (!trimmed) return DEFAULT_GEMINI_EMBEDDING_MODEL;
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const withoutPrefix = trimmed.replace(/^models\//, "");
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if (withoutPrefix.startsWith("gemini/")) return withoutPrefix.slice("gemini/".length);
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if (withoutPrefix.startsWith("google/")) return withoutPrefix.slice("google/".length);
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return withoutPrefix;
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}
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function normalizeGeminiBaseUrl(raw: string): string {
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const trimmed = raw.replace(/\/+$/, "");
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const openAiIndex = trimmed.indexOf("/openai");
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if (openAiIndex > -1) return trimmed.slice(0, openAiIndex);
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return trimmed;
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}
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function buildGeminiModelPath(model: string): string {
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return model.startsWith("models/") ? model : `models/${model}`;
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}
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export async function createGeminiEmbeddingProvider(
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options: EmbeddingProviderOptions,
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): Promise<{ provider: EmbeddingProvider; client: GeminiEmbeddingClient }> {
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const client = await resolveGeminiEmbeddingClient(options);
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const baseUrl = client.baseUrl.replace(/\/$/, "");
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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 embedQuery = async (text: string): Promise<number[]> => {
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if (!text.trim()) return [];
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const res = await fetch(embedUrl, {
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method: "POST",
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headers: client.headers,
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body: JSON.stringify({
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content: { parts: [{ text }] },
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taskType: "RETRIEVAL_QUERY",
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}),
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});
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if (!res.ok) {
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const payload = await res.text();
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throw new Error(`gemini embeddings failed: ${res.status} ${payload}`);
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}
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const payload = (await res.json()) as { embedding?: { values?: number[] } };
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return payload.embedding?.values ?? [];
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};
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const embedBatch = async (texts: string[]): Promise<number[][]> => {
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if (texts.length === 0) return [];
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const requests = texts.map((text) => ({
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model: client.modelPath,
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content: { parts: [{ text }] },
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taskType: "RETRIEVAL_DOCUMENT",
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}));
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const res = await fetch(batchUrl, {
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method: "POST",
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headers: client.headers,
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body: JSON.stringify({ requests }),
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});
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if (!res.ok) {
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const payload = await res.text();
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throw new Error(`gemini embeddings failed: ${res.status} ${payload}`);
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}
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const payload = (await res.json()) as { embeddings?: Array<{ values?: number[] }> };
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const embeddings = Array.isArray(payload.embeddings) ? payload.embeddings : [];
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return texts.map((_, index) => embeddings[index]?.values ?? []);
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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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embedQuery,
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embedBatch,
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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: EmbeddingProviderOptions,
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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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? { apiKey: remoteApiKey }
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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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const providerConfig = options.config.models?.providers?.google;
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const rawBaseUrl = remoteBaseUrl || providerConfig?.baseUrl?.trim() || DEFAULT_GEMINI_BASE_URL;
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const baseUrl = normalizeGeminiBaseUrl(rawBaseUrl);
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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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"Content-Type": "application/json",
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"x-goog-api-key": apiKey,
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...headerOverrides,
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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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debugLog("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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embedEndpoint: `${baseUrl}/${modelPath}:embedContent`,
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batchEndpoint: `${baseUrl}/${modelPath}:batchEmbedContents`,
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});
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return { baseUrl, headers, model, modelPath };
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}
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83
src/memory/embeddings-openai.ts
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83
src/memory/embeddings-openai.ts
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@@ -0,0 +1,83 @@
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import { resolveApiKeyForProvider } from "../agents/model-auth.js";
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import type { EmbeddingProvider, EmbeddingProviderOptions } from "./embeddings.js";
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export type OpenAiEmbeddingClient = {
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baseUrl: string;
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headers: Record<string, string>;
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model: string;
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};
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export const DEFAULT_OPENAI_EMBEDDING_MODEL = "text-embedding-3-small";
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const DEFAULT_OPENAI_BASE_URL = "https://api.openai.com/v1";
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export function normalizeOpenAiModel(model: string): string {
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const trimmed = model.trim();
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if (!trimmed) return DEFAULT_OPENAI_EMBEDDING_MODEL;
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if (trimmed.startsWith("openai/")) return trimmed.slice("openai/".length);
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return trimmed;
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}
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export async function createOpenAiEmbeddingProvider(
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options: EmbeddingProviderOptions,
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): Promise<{ provider: EmbeddingProvider; client: OpenAiEmbeddingClient }> {
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const client = await resolveOpenAiEmbeddingClient(options);
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const url = `${client.baseUrl.replace(/\/$/, "")}/embeddings`;
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const embed = async (input: string[]): Promise<number[][]> => {
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if (input.length === 0) return [];
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const res = await fetch(url, {
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method: "POST",
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headers: client.headers,
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body: JSON.stringify({ model: client.model, input }),
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});
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if (!res.ok) {
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const text = await res.text();
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throw new Error(`openai embeddings failed: ${res.status} ${text}`);
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}
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const payload = (await res.json()) as {
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data?: Array<{ embedding?: number[] }>;
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};
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const data = payload.data ?? [];
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return data.map((entry) => entry.embedding ?? []);
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};
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return {
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provider: {
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id: "openai",
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model: client.model,
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embedQuery: async (text) => {
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const [vec] = await embed([text]);
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return vec ?? [];
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},
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embedBatch: embed,
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},
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client,
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};
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}
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export async function resolveOpenAiEmbeddingClient(
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options: EmbeddingProviderOptions,
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): Promise<OpenAiEmbeddingClient> {
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const remote = options.remote;
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const remoteApiKey = remote?.apiKey?.trim();
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const remoteBaseUrl = remote?.baseUrl?.trim();
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const { apiKey } = remoteApiKey
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? { apiKey: remoteApiKey }
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: await resolveApiKeyForProvider({
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provider: "openai",
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cfg: options.config,
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agentDir: options.agentDir,
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});
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const providerConfig = options.config.models?.providers?.openai;
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const baseUrl = remoteBaseUrl || providerConfig?.baseUrl?.trim() || DEFAULT_OPENAI_BASE_URL;
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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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"Content-Type": "application/json",
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Authorization: `Bearer ${apiKey}`,
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...headerOverrides,
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};
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const model = normalizeOpenAiModel(options.model);
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return { baseUrl, headers, model };
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}
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@@ -108,7 +108,7 @@ describe("embedding provider remote overrides", () => {
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expect(headers.Authorization).toBe("Bearer provider-key");
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});
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it("uses gemini embedContent endpoint with x-goog-api-key", async () => {
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it("builds Gemini embeddings requests with api key header", async () => {
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const fetchMock = vi.fn(async () => ({
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ok: true,
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status: 200,
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@@ -119,29 +119,94 @@ describe("embedding provider remote overrides", () => {
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const { createEmbeddingProvider } = await import("./embeddings.js");
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const authModule = await import("../agents/model-auth.js");
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vi.mocked(authModule.resolveApiKeyForProvider).mockResolvedValue({
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apiKey: "gemini-key",
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apiKey: "provider-key",
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});
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const cfg = {
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models: {
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providers: {
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google: {
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baseUrl: "https://generativelanguage.googleapis.com/v1beta",
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},
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},
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},
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};
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const result = await createEmbeddingProvider({
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config: {} as never,
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config: cfg as never,
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provider: "gemini",
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remote: {
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baseUrl: "https://gemini.example/v1beta",
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apiKey: "gemini-key",
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},
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model: "gemini-embedding-001",
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model: "text-embedding-004",
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fallback: "openai",
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});
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await result.provider.embedQuery("hello");
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const [url, init] = fetchMock.mock.calls[0] ?? [];
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expect(url).toBe("https://gemini.example/v1beta/models/gemini-embedding-001:embedContent");
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expect(url).toBe(
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"https://generativelanguage.googleapis.com/v1beta/models/text-embedding-004:embedContent",
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);
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const headers = (init?.headers ?? {}) as Record<string, string>;
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expect(headers["x-goog-api-key"]).toBe("gemini-key");
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expect(headers["Content-Type"]).toBe("application/json");
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});
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});
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describe("embedding provider auto selection", () => {
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afterEach(() => {
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vi.resetAllMocks();
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vi.resetModules();
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vi.unstubAllGlobals();
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});
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it("prefers openai when a key resolves", async () => {
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const { createEmbeddingProvider } = await import("./embeddings.js");
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const authModule = await import("../agents/model-auth.js");
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vi.mocked(authModule.resolveApiKeyForProvider).mockImplementation(async ({ provider }) => {
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if (provider === "openai") {
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return { apiKey: "openai-key", source: "env: OPENAI_API_KEY" };
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}
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throw new Error(`No API key found for provider "${provider}".`);
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});
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const result = await createEmbeddingProvider({
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config: {} as never,
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provider: "auto",
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model: "",
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fallback: "none",
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});
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expect(result.requestedProvider).toBe("auto");
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expect(result.provider.id).toBe("openai");
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});
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it("uses gemini when openai is missing", async () => {
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const { createEmbeddingProvider } = await import("./embeddings.js");
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const authModule = await import("../agents/model-auth.js");
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vi.mocked(authModule.resolveApiKeyForProvider).mockImplementation(async ({ provider }) => {
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if (provider === "openai") {
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throw new Error('No API key found for provider "openai".');
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}
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if (provider === "google") {
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return { apiKey: "gemini-key", source: "env: GEMINI_API_KEY" };
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}
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throw new Error(`Unexpected provider ${provider}`);
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});
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const result = await createEmbeddingProvider({
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config: {} as never,
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provider: "auto",
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model: "",
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fallback: "none",
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});
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expect(result.requestedProvider).toBe("auto");
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expect(result.provider.id).toBe("gemini");
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});
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});
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describe("embedding provider local fallback", () => {
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afterEach(() => {
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vi.resetAllMocks();
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@@ -1,8 +1,21 @@
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import fsSync from "node:fs";
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import type { Llama, LlamaEmbeddingContext, LlamaModel } from "node-llama-cpp";
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import { resolveApiKeyForProvider } from "../agents/model-auth.js";
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import type { ClawdbotConfig } from "../config/config.js";
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import { resolveUserPath } from "../utils.js";
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import {
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createGeminiEmbeddingProvider,
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type GeminiEmbeddingClient,
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} from "./embeddings-gemini.js";
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import {
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createOpenAiEmbeddingProvider,
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type OpenAiEmbeddingClient,
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} from "./embeddings-openai.js";
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import { importNodeLlamaCpp } from "./node-llama.js";
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export type { GeminiEmbeddingClient } from "./embeddings-gemini.js";
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export type { OpenAiEmbeddingClient } from "./embeddings-openai.js";
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|
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export type EmbeddingProvider = {
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id: string;
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model: string;
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@@ -12,230 +25,49 @@ export type EmbeddingProvider = {
|
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|
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export type EmbeddingProviderResult = {
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provider: EmbeddingProvider;
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requestedProvider: "openai" | "gemini" | "local";
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fallbackFrom?: "local";
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requestedProvider: "openai" | "local" | "gemini" | "auto";
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fallbackFrom?: "openai" | "local" | "gemini";
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fallbackReason?: string;
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openAi?: OpenAiEmbeddingClient;
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gemini?: GeminiEmbeddingClient;
|
||||
};
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|
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export type OpenAiEmbeddingClient = {
|
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baseUrl: string;
|
||||
headers: Record<string, string>;
|
||||
model: string;
|
||||
};
|
||||
|
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export type GeminiEmbeddingClient = {
|
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baseUrl: string;
|
||||
headers: Record<string, string>;
|
||||
model: string;
|
||||
};
|
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|
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export type EmbeddingProviderOptions = {
|
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config: ClawdbotConfig;
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agentDir?: string;
|
||||
provider: "openai" | "gemini" | "local";
|
||||
provider: "openai" | "local" | "gemini" | "auto";
|
||||
remote?: {
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||||
baseUrl?: string;
|
||||
apiKey?: string;
|
||||
headers?: Record<string, string>;
|
||||
};
|
||||
model: string;
|
||||
fallback: "openai" | "none";
|
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fallback: "openai" | "gemini" | "local" | "none";
|
||||
local?: {
|
||||
modelPath?: string;
|
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modelCacheDir?: string;
|
||||
};
|
||||
};
|
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|
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const DEFAULT_OPENAI_BASE_URL = "https://api.openai.com/v1";
|
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const DEFAULT_LOCAL_MODEL = "hf:ggml-org/embeddinggemma-300M-GGUF/embeddinggemma-300M-Q8_0.gguf";
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const DEFAULT_GEMINI_BASE_URL = "https://generativelanguage.googleapis.com/v1beta";
|
||||
const DEFAULT_GEMINI_MODEL = "gemini-embedding-001";
|
||||
|
||||
function normalizeOpenAiModel(model: string): string {
|
||||
const trimmed = model.trim();
|
||||
if (!trimmed) return "text-embedding-3-small";
|
||||
if (trimmed.startsWith("openai/")) return trimmed.slice("openai/".length);
|
||||
return trimmed;
|
||||
}
|
||||
|
||||
function normalizeGeminiModel(model: string): string {
|
||||
const trimmed = model.trim();
|
||||
if (!trimmed) return DEFAULT_GEMINI_MODEL;
|
||||
if (trimmed.startsWith("models/")) return trimmed.slice("models/".length);
|
||||
if (trimmed.startsWith("google/")) return trimmed.slice("google/".length);
|
||||
return trimmed;
|
||||
}
|
||||
|
||||
async function createOpenAiEmbeddingProvider(
|
||||
options: EmbeddingProviderOptions,
|
||||
): Promise<{ provider: EmbeddingProvider; client: OpenAiEmbeddingClient }> {
|
||||
const client = await resolveOpenAiEmbeddingClient(options);
|
||||
const url = `${client.baseUrl.replace(/\/$/, "")}/embeddings`;
|
||||
|
||||
const embed = async (input: string[]): Promise<number[][]> => {
|
||||
if (input.length === 0) return [];
|
||||
const res = await fetch(url, {
|
||||
method: "POST",
|
||||
headers: client.headers,
|
||||
body: JSON.stringify({ model: client.model, input }),
|
||||
});
|
||||
if (!res.ok) {
|
||||
const text = await res.text();
|
||||
throw new Error(`openai embeddings failed: ${res.status} ${text}`);
|
||||
}
|
||||
const payload = (await res.json()) as {
|
||||
data?: Array<{ embedding?: number[] }>;
|
||||
};
|
||||
const data = payload.data ?? [];
|
||||
return data.map((entry) => entry.embedding ?? []);
|
||||
};
|
||||
|
||||
return {
|
||||
provider: {
|
||||
id: "openai",
|
||||
model: client.model,
|
||||
embedQuery: async (text) => {
|
||||
const [vec] = await embed([text]);
|
||||
return vec ?? [];
|
||||
},
|
||||
embedBatch: embed,
|
||||
},
|
||||
client,
|
||||
};
|
||||
}
|
||||
|
||||
function extractGeminiEmbeddingValues(entry: unknown): number[] {
|
||||
if (!entry || typeof entry !== "object") return [];
|
||||
const record = entry as { values?: unknown; embedding?: { values?: unknown } };
|
||||
const values = record.values ?? record.embedding?.values;
|
||||
if (!Array.isArray(values)) return [];
|
||||
return values.filter((value): value is number => typeof value === "number");
|
||||
}
|
||||
|
||||
function parseGeminiEmbeddings(payload: unknown): number[][] {
|
||||
if (!payload || typeof payload !== "object") return [];
|
||||
const data = payload as { embedding?: unknown; embeddings?: unknown[] };
|
||||
if (Array.isArray(data.embeddings)) {
|
||||
return data.embeddings.map((entry) => extractGeminiEmbeddingValues(entry));
|
||||
function canAutoSelectLocal(options: EmbeddingProviderOptions): boolean {
|
||||
const modelPath = options.local?.modelPath?.trim();
|
||||
if (!modelPath) return false;
|
||||
if (/^(hf:|https?:)/i.test(modelPath)) return false;
|
||||
const resolved = resolveUserPath(modelPath);
|
||||
try {
|
||||
return fsSync.statSync(resolved).isFile();
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
if (data.embedding) {
|
||||
return [extractGeminiEmbeddingValues(data.embedding)];
|
||||
}
|
||||
return [];
|
||||
}
|
||||
|
||||
async function createGeminiEmbeddingProvider(
|
||||
options: EmbeddingProviderOptions,
|
||||
): Promise<{ provider: EmbeddingProvider; client: GeminiEmbeddingClient }> {
|
||||
const client = await resolveGeminiEmbeddingClient(options);
|
||||
const baseUrl = client.baseUrl.replace(/\/$/, "");
|
||||
const model = `models/${client.model}`;
|
||||
|
||||
const embedContent = async (input: string): Promise<number[]> => {
|
||||
const res = await fetch(`${baseUrl}/${model}:embedContent`, {
|
||||
method: "POST",
|
||||
headers: client.headers,
|
||||
body: JSON.stringify({
|
||||
model,
|
||||
content: { parts: [{ text: input }] },
|
||||
}),
|
||||
});
|
||||
if (!res.ok) {
|
||||
const text = await res.text();
|
||||
throw new Error(`gemini embeddings failed: ${res.status} ${text}`);
|
||||
}
|
||||
const payload = await res.json();
|
||||
const embeddings = parseGeminiEmbeddings(payload);
|
||||
return embeddings[0] ?? [];
|
||||
};
|
||||
|
||||
const embedBatch = async (input: string[]): Promise<number[][]> => {
|
||||
if (input.length === 0) return [];
|
||||
const res = await fetch(`${baseUrl}/${model}:batchEmbedContents`, {
|
||||
method: "POST",
|
||||
headers: client.headers,
|
||||
body: JSON.stringify({
|
||||
requests: input.map((text) => ({
|
||||
model,
|
||||
content: { parts: [{ text }] },
|
||||
})),
|
||||
}),
|
||||
});
|
||||
if (!res.ok) {
|
||||
const text = await res.text();
|
||||
throw new Error(`gemini embeddings failed: ${res.status} ${text}`);
|
||||
}
|
||||
const payload = await res.json();
|
||||
const embeddings = parseGeminiEmbeddings(payload);
|
||||
return embeddings;
|
||||
};
|
||||
|
||||
return {
|
||||
provider: {
|
||||
id: "gemini",
|
||||
model: client.model,
|
||||
embedQuery: embedContent,
|
||||
embedBatch,
|
||||
},
|
||||
client,
|
||||
};
|
||||
function isMissingApiKeyError(err: unknown): boolean {
|
||||
const message = formatError(err);
|
||||
return message.includes("No API key found for provider");
|
||||
}
|
||||
|
||||
async function resolveOpenAiEmbeddingClient(
|
||||
options: EmbeddingProviderOptions,
|
||||
): Promise<OpenAiEmbeddingClient> {
|
||||
const remote = options.remote;
|
||||
const remoteApiKey = remote?.apiKey?.trim();
|
||||
const remoteBaseUrl = remote?.baseUrl?.trim();
|
||||
|
||||
const { apiKey } = remoteApiKey
|
||||
? { apiKey: remoteApiKey }
|
||||
: await resolveApiKeyForProvider({
|
||||
provider: "openai",
|
||||
cfg: options.config,
|
||||
agentDir: options.agentDir,
|
||||
});
|
||||
|
||||
const providerConfig = options.config.models?.providers?.openai;
|
||||
const baseUrl = remoteBaseUrl || providerConfig?.baseUrl?.trim() || DEFAULT_OPENAI_BASE_URL;
|
||||
const headerOverrides = Object.assign({}, providerConfig?.headers, remote?.headers);
|
||||
const headers: Record<string, string> = {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
...headerOverrides,
|
||||
};
|
||||
const model = normalizeOpenAiModel(options.model);
|
||||
return { baseUrl, headers, model };
|
||||
}
|
||||
|
||||
async function resolveGeminiEmbeddingClient(
|
||||
options: EmbeddingProviderOptions,
|
||||
): Promise<GeminiEmbeddingClient> {
|
||||
const remote = options.remote;
|
||||
const remoteApiKey = remote?.apiKey?.trim();
|
||||
const remoteBaseUrl = remote?.baseUrl?.trim();
|
||||
|
||||
const { apiKey } = remoteApiKey
|
||||
? { apiKey: remoteApiKey }
|
||||
: await resolveApiKeyForProvider({
|
||||
provider: "google",
|
||||
cfg: options.config,
|
||||
agentDir: options.agentDir,
|
||||
});
|
||||
|
||||
const providerConfig = options.config.models?.providers?.google;
|
||||
const baseUrl = remoteBaseUrl || providerConfig?.baseUrl?.trim() || DEFAULT_GEMINI_BASE_URL;
|
||||
const headerOverrides = Object.assign({}, providerConfig?.headers, remote?.headers);
|
||||
const headers: Record<string, string> = {
|
||||
"Content-Type": "application/json",
|
||||
"x-goog-api-key": apiKey,
|
||||
...headerOverrides,
|
||||
};
|
||||
const model = normalizeGeminiModel(options.model);
|
||||
return { baseUrl, headers, model };
|
||||
}
|
||||
|
||||
async function createLocalEmbeddingProvider(
|
||||
options: EmbeddingProviderOptions,
|
||||
@@ -289,35 +121,80 @@ export async function createEmbeddingProvider(
|
||||
options: EmbeddingProviderOptions,
|
||||
): Promise<EmbeddingProviderResult> {
|
||||
const requestedProvider = options.provider;
|
||||
if (options.provider === "gemini") {
|
||||
const { provider, client } = await createGeminiEmbeddingProvider(options);
|
||||
return { provider, requestedProvider, gemini: client };
|
||||
}
|
||||
if (options.provider === "local") {
|
||||
try {
|
||||
const fallback = options.fallback;
|
||||
|
||||
const createProvider = async (id: "openai" | "local" | "gemini") => {
|
||||
if (id === "local") {
|
||||
const provider = await createLocalEmbeddingProvider(options);
|
||||
return { provider, requestedProvider };
|
||||
} catch (err) {
|
||||
const reason = formatLocalSetupError(err);
|
||||
if (options.fallback === "openai") {
|
||||
try {
|
||||
const { provider, client } = await createOpenAiEmbeddingProvider(options);
|
||||
return {
|
||||
provider,
|
||||
requestedProvider,
|
||||
fallbackFrom: "local",
|
||||
fallbackReason: reason,
|
||||
openAi: client,
|
||||
};
|
||||
} catch (fallbackErr) {
|
||||
throw new Error(`${reason}\n\nFallback to OpenAI failed: ${formatError(fallbackErr)}`);
|
||||
}
|
||||
}
|
||||
throw new Error(reason);
|
||||
return { provider };
|
||||
}
|
||||
if (id === "gemini") {
|
||||
const { provider, client } = await createGeminiEmbeddingProvider(options);
|
||||
return { provider, gemini: client };
|
||||
}
|
||||
const { provider, client } = await createOpenAiEmbeddingProvider(options);
|
||||
return { provider, openAi: client };
|
||||
};
|
||||
|
||||
const formatPrimaryError = (err: unknown, provider: "openai" | "local" | "gemini") =>
|
||||
provider === "local" ? formatLocalSetupError(err) : formatError(err);
|
||||
|
||||
if (requestedProvider === "auto") {
|
||||
const missingKeyErrors: string[] = [];
|
||||
let localError: string | null = null;
|
||||
|
||||
if (canAutoSelectLocal(options)) {
|
||||
try {
|
||||
const local = await createProvider("local");
|
||||
return { ...local, requestedProvider };
|
||||
} catch (err) {
|
||||
localError = formatLocalSetupError(err);
|
||||
}
|
||||
}
|
||||
|
||||
for (const provider of ["openai", "gemini"] as const) {
|
||||
try {
|
||||
const result = await createProvider(provider);
|
||||
return { ...result, requestedProvider };
|
||||
} catch (err) {
|
||||
const message = formatPrimaryError(err, provider);
|
||||
if (isMissingApiKeyError(err)) {
|
||||
missingKeyErrors.push(message);
|
||||
continue;
|
||||
}
|
||||
throw new Error(message);
|
||||
}
|
||||
}
|
||||
|
||||
const details = [...missingKeyErrors, localError].filter(Boolean) as string[];
|
||||
if (details.length > 0) {
|
||||
throw new Error(details.join("\n\n"));
|
||||
}
|
||||
throw new Error("No embeddings provider available.");
|
||||
}
|
||||
|
||||
try {
|
||||
const primary = await createProvider(requestedProvider);
|
||||
return { ...primary, requestedProvider };
|
||||
} catch (primaryErr) {
|
||||
const reason = formatPrimaryError(primaryErr, requestedProvider);
|
||||
if (fallback && fallback !== "none" && fallback !== requestedProvider) {
|
||||
try {
|
||||
const fallbackResult = await createProvider(fallback);
|
||||
return {
|
||||
...fallbackResult,
|
||||
requestedProvider,
|
||||
fallbackFrom: requestedProvider,
|
||||
fallbackReason: reason,
|
||||
};
|
||||
} catch (fallbackErr) {
|
||||
throw new Error(
|
||||
`${reason}\n\nFallback to ${fallback} failed: ${formatError(fallbackErr)}`,
|
||||
);
|
||||
}
|
||||
}
|
||||
throw new Error(reason);
|
||||
}
|
||||
const { provider, client } = await createOpenAiEmbeddingProvider(options);
|
||||
return { provider, requestedProvider, openAi: client };
|
||||
}
|
||||
|
||||
function formatError(err: unknown): string {
|
||||
|
||||
Reference in New Issue
Block a user