82 lines
4.5 KiB
TypeScript
82 lines
4.5 KiB
TypeScript
import axios from "axios";
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import { sanitizeChannelModelCatalogItem, type ChannelModelCatalogItem } from "@/lib/channel-model-catalog";
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import { projectDesktopLocalChannelRuntime } from "@/lib/desktop-local-channel";
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import { channelRequest } from "@/services/api/custom-channel-relay";
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import { readAxiosError, validateGeminiPayload } from "@/services/api/image-response";
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import { geminiApiUrl, geminiHeaders } from "@/services/api/image-transport";
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import { buildApiUrl, resolveBackendApiUrl, type AiConfig, type ModelChannel } from "@/stores/use-config-store";
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const defaultGeminiConfig: Pick<AiConfig, "baseUrl" | "apiKey" | "apiFormat" | "model" | "systemPrompt"> = {
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baseUrl: "https://generativelanguage.googleapis.com",
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apiKey: "",
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apiFormat: "gemini",
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model: "",
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systemPrompt: "",
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};
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type GeminiModelPayload = { models?: Array<{ name?: string }> };
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type OpenAIModelPayload = { data?: Array<{ id?: string }>; error?: { message?: string } };
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export async function fetchImageModels(config: Pick<AiConfig, "baseUrl" | "apiKey" | "apiFormat"> & { allowLocalChannel?: boolean }) {
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try {
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if (config.apiFormat === "gemini") {
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const requestConfig = { ...defaultGeminiConfig, ...config };
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const request = channelRequest(requestConfig, geminiApiUrl(requestConfig), geminiHeaders(requestConfig));
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const response = await axios.get<GeminiModelPayload>(request.url, { headers: request.headers, withCredentials: request.credentials === "include" });
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validateGeminiPayload(response.data);
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return (response.data.models || [])
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.map((model) => model.name?.replace(/^models\//, ""))
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.filter((id): id is string => Boolean(id))
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.sort((a, b) => a.localeCompare(b));
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}
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const request = channelRequest(config, buildApiUrl(config.baseUrl, "/models"), { Authorization: `Bearer ${config.apiKey}` });
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const response = await axios.get<OpenAIModelPayload>(request.url, { headers: request.headers, withCredentials: request.credentials === "include" });
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return (response.data.data || [])
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.map((model) => model.id)
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.filter((id): id is string => Boolean(id))
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.sort((a, b) => a.localeCompare(b));
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} catch (error) {
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throw new Error(readAxiosError(error, "读取模型失败"));
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}
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}
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export type ChannelModelFetchResult = { models: string[]; catalog: ChannelModelCatalogItem[] };
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export async function fetchChannelModels(channel: ModelChannel, viaBackend = false): Promise<ChannelModelFetchResult> {
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const runtimeChannel = projectDesktopLocalChannelRuntime(channel);
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if (!viaBackend) {
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const models = await fetchImageModels({ baseUrl: runtimeChannel.baseUrl, allowLocalChannel: runtimeChannel.allowLocalChannel === true, apiKey: runtimeChannel.apiKey, apiFormat: runtimeChannel.apiFormat });
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return { models, catalog: models.map((id) => ({ id })) };
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}
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try {
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// 登录态由同源后端代取模型目录，避免每个 OpenAI 兼容服务分别维护浏览器 CORS 白名单。
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const response = await axios.post<{ code?: number; data?: { models?: Array<string | ChannelModelCatalogItem> }; msg?: string }>(
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resolveBackendApiUrl("/api/ai/models"),
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{
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baseUrl: runtimeChannel.baseUrl,
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allowLocalChannel: runtimeChannel.allowLocalChannel === true,
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apiKey: runtimeChannel.apiKey,
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apiFormat: runtimeChannel.apiFormat,
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headers: runtimeChannel.headers,
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},
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{ withCredentials: true },
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);
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if (typeof response.data.code === "number" && response.data.code !== 0) {
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throw new Error(response.data.msg || "读取模型失败");
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}
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const catalog = new Map<string, ChannelModelCatalogItem>();
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for (const item of response.data.data?.models || []) {
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const entry = typeof item === "string" ? sanitizeChannelModelCatalogItem({ id: item }) : sanitizeChannelModelCatalogItem(item);
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if (!entry) continue;
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const existing = catalog.get(entry.id);
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catalog.set(entry.id, existing || entry);
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}
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const models = Array.from(catalog.keys()).sort((a, b) => a.localeCompare(b));
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const sortedCatalog = Array.from(catalog.values()).sort((a, b) => a.id.localeCompare(b.id));
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return { models, catalog: sortedCatalog };
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} catch (error) {
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throw new Error(readAxiosError(error, "读取模型失败"));
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}
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}
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