add uniapi
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@ -74,7 +74,7 @@ export default function AdminModelsPage() {
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const [selectedPlan, setSelectedPlan] = useState<string>('')
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const [selectedModels, setSelectedModels] = useState<string[]>([])
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const [showAvailableModels, setShowAvailableModels] = useState(false)
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const [selectedServiceProvider, setSelectedServiceProvider] = useState<'openrouter' | 'replicate'>('openrouter')
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const [selectedServiceProvider, setSelectedServiceProvider] = useState<'openrouter' | 'replicate' | 'uniapi'>('openrouter')
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useEffect(() => {
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loadInitialData()
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@ -309,7 +309,7 @@ export default function AdminModelsPage() {
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<select
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value={selectedServiceProvider}
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onChange={(e) => {
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setSelectedServiceProvider(e.target.value as 'openrouter' | 'replicate')
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setSelectedServiceProvider(e.target.value as 'openrouter' | 'replicate' | 'uniapi')
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setShowAvailableModels(false)
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setSelectedModels([])
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}}
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@ -317,6 +317,7 @@ export default function AdminModelsPage() {
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>
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<option value="openrouter">OpenRouter (Text Models)</option>
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<option value="replicate">Replicate (Image/Video/Audio Models)</option>
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<option value="uniapi">UniAPI (Multi-modal Models)</option>
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</select>
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</div>
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)}
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@ -362,7 +363,7 @@ export default function AdminModelsPage() {
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</Button>
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</div>
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<div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-3 max-h-96 overflow-y-auto">
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<div className="grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4 max-h-96 overflow-y-auto">
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{availableModels.map(model => {
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const isSelected = selectedModels.includes(model.modelId)
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const isAlreadyAdded = models.some(m =>
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@ -372,7 +373,7 @@ export default function AdminModelsPage() {
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return (
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<div
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key={model.modelId}
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className={`border rounded-lg p-3 cursor-pointer transition-colors ${
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className={`border rounded-lg p-4 cursor-pointer transition-colors ${
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isAlreadyAdded
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? 'border-yellow-300 bg-yellow-50 dark:bg-yellow-900/20'
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: isSelected
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@ -383,17 +384,19 @@ export default function AdminModelsPage() {
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>
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<div className="flex items-center justify-between">
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<div className="flex-1 min-w-0">
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<div className="flex items-center space-x-2 mb-1">
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<h4 className="font-medium text-sm truncate">{model.name}</h4>
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<Badge variant="secondary" className="text-xs">
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{model.provider}
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</Badge>
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<Badge variant="outline" className="text-xs">
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{model.outputType}
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</Badge>
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<Badge variant="outline" className="text-xs">
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{model.serviceProvider}
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</Badge>
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<div className="mb-2">
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<h4 className="font-medium text-base truncate mb-2">{model.name}</h4>
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<div className="flex flex-wrap gap-1">
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<Badge variant="secondary" className="text-xs">
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{model.provider}
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</Badge>
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<Badge variant="outline" className="text-xs">
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{model.outputType}
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</Badge>
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<Badge variant="outline" className="text-xs">
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{model.serviceProvider}
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</Badge>
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</div>
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</div>
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<div className="flex items-center space-x-2 text-xs text-muted-foreground">
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{model.maxTokens && (
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@ -2,6 +2,7 @@ import { NextRequest, NextResponse } from 'next/server'
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import { prisma } from '@/lib/prisma'
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import { OpenRouterService } from '@/lib/openrouter'
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import { ReplicateService } from '@/lib/replicate'
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import { UniAPIService } from '@/lib/uniapi'
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// GET /api/admin/models - 获取所有模型（按套餐分组）
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export async function GET() {
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@ -95,6 +96,13 @@ export async function POST(request: NextRequest) {
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...transformedVideoModels,
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...transformedAudioModels
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]
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} else if (provider === 'uniapi') {
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// 从 UniAPI 获取可用模型
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const uniAPIService = new UniAPIService()
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const uniAPIModels = await uniAPIService.getAvailableModels()
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availableModels = uniAPIModels
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.map(model => uniAPIService.transformModelForDB(model))
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.filter(model => model !== null) // 过滤掉可能的 null 值
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}
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return NextResponse.json({
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@ -113,6 +121,40 @@ export async function POST(request: NextRequest) {
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)
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}
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// 检查模型 ID 的唯一性
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const modelIds = selectedModels.map(model => model.modelId)
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const existingModels = await prisma.model.findMany({
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where: {
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modelId: {
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in: modelIds
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},
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subscriptionPlanId: {
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not: planId // 排除当前套餐，允许同一套餐内更新
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}
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},
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include: {
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subscriptionPlan: {
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select: {
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displayName: true
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}
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}
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}
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})
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if (existingModels.length > 0) {
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const conflicts = existingModels.map(model => ({
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modelId: model.modelId,
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existingPlan: model.subscriptionPlan.displayName,
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existingServiceProvider: model.serviceProvider
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}))
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return NextResponse.json({
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error: 'Model ID conflicts detected',
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conflicts: conflicts,
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message: `The following model IDs are already used by other service providers: ${conflicts.map(c => `${c.modelId} (used by ${c.existingServiceProvider} in ${c.existingPlan})`).join(', ')}`
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}, { status: 409 })
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}
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// 批量创建模型记录
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const results = []
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for (const modelData of selectedModels) {
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@ -3,6 +3,7 @@ import { createServerSupabaseClient } from "@/lib/supabase-server";
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import { prisma } from "@/lib/prisma";
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import { getPromptContent, calculateCost } from "@/lib/simulator-utils";
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import { consumeCreditForSimulation, getUserBalance } from "@/lib/services/credit";
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import { UniAPIService } from "@/lib/uniapi";
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export async function POST(
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request: NextRequest,
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@ -58,40 +59,115 @@ export async function POST(
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const promptContent = getPromptContent(run);
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const finalPrompt = `${promptContent}\n\nUser Input: ${run.userInput}`;
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const requestBody = {
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model: run.model.modelId,
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messages: [
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{
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role: "user",
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content: finalPrompt,
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}
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],
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temperature: run.temperature || 0.7,
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...(run.maxTokens && { max_tokens: run.maxTokens }),
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...(run.topP && { top_p: run.topP }),
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...(run.frequencyPenalty && { frequency_penalty: run.frequencyPenalty }),
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...(run.presencePenalty && { presence_penalty: run.presencePenalty }),
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stream: true,
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};
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let apiResponse: Response;
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const openRouterResponse = await fetch("https://openrouter.ai/api/v1/chat/completions", {
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method: "POST",
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headers: {
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"Authorization": `Bearer ${process.env.OPENROUTER_API_KEY}`,
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"Content-Type": "application/json",
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"HTTP-Referer": process.env.NEXT_PUBLIC_APP_URL || "http://localhost:3000",
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"X-Title": "Prmbr - AI Prompt Studio",
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},
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body: JSON.stringify(requestBody),
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});
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// 根据服务提供商选择不同的API
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if (run.model.serviceProvider === 'openrouter') {
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const requestBody = {
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model: run.model.modelId,
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messages: [
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{
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role: "user",
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content: finalPrompt,
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}
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],
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temperature: run.temperature || 0.7,
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...(run.maxTokens && { max_tokens: run.maxTokens }),
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...(run.topP && { top_p: run.topP }),
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...(run.frequencyPenalty && { frequency_penalty: run.frequencyPenalty }),
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...(run.presencePenalty && { presence_penalty: run.presencePenalty }),
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stream: true,
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};
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if (!openRouterResponse.ok) {
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const errorText = await openRouterResponse.text();
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apiResponse = await fetch("https://openrouter.ai/api/v1/chat/completions", {
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method: "POST",
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headers: {
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"Authorization": `Bearer ${process.env.OPENROUTER_API_KEY}`,
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"Content-Type": "application/json",
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"HTTP-Referer": process.env.NEXT_PUBLIC_APP_URL || "http://localhost:3000",
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"X-Title": "Prmbr - AI Prompt Studio",
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},
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body: JSON.stringify(requestBody),
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});
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} else if (run.model.serviceProvider === 'uniapi') {
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const uniAPIService = new UniAPIService();
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if (run.model.outputType === 'text' || run.model.outputType === 'multimodal') {
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// 使用聊天完成API
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const requestBody = {
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model: run.model.modelId,
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messages: [
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{
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role: "user",
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content: finalPrompt,
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}
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],
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temperature: run.temperature || 0.7,
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...(run.maxTokens && { max_tokens: run.maxTokens }),
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...(run.topP && { top_p: run.topP }),
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...(run.frequencyPenalty && { frequency_penalty: run.frequencyPenalty }),
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...(run.presencePenalty && { presence_penalty: run.presencePenalty }),
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};
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// 注意：UniAPI 可能不支持流式响应，这里需要调整
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const response = await uniAPIService.createChatCompletion(requestBody);
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// 创建模拟的流式响应
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const mockStream = new ReadableStream({
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start(controller) {
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const content = response.choices?.[0]?.message?.content || '';
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const usage = response.usage || { prompt_tokens: 0, completion_tokens: 0 };
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// 模拟流式数据
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controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify({
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choices: [{
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delta: { content: content }
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}]
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})}\n\n`));
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controller.enqueue(new TextEncoder().encode(`data: ${JSON.stringify({
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usage: usage
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})}\n\n`));
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controller.enqueue(new TextEncoder().encode(`data: [DONE]\n\n`));
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controller.close();
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}
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});
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apiResponse = new Response(mockStream, {
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headers: {
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'Content-Type': 'text/event-stream',
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}
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});
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} else {
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// 对于非文本模型，返回错误
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await prisma.simulatorRun.update({
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where: { id },
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data: {
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status: "failed",
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error: `Unsupported model type: ${run.model.outputType}`,
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},
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});
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return NextResponse.json({ error: "Unsupported model type" }, { status: 400 });
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}
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} else {
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await prisma.simulatorRun.update({
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where: { id },
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data: {
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status: "failed",
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error: `OpenRouter API error: ${openRouterResponse.status} - ${errorText}`,
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error: `Unsupported service provider: ${run.model.serviceProvider}`,
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},
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});
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return NextResponse.json({ error: "Unsupported service provider" }, { status: 400 });
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}
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if (!apiResponse.ok) {
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const errorText = await apiResponse.text();
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await prisma.simulatorRun.update({
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where: { id },
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data: {
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status: "failed",
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error: `API error: ${apiResponse.status} - ${errorText}`,
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},
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});
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return NextResponse.json({ error: "AI API request failed" }, { status: 500 });
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@ -100,7 +176,7 @@ export async function POST(
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// 创建流式响应
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const stream = new ReadableStream({
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async start(controller) {
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const reader = openRouterResponse.body?.getReader();
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const reader = apiResponse.body?.getReader();
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if (!reader) {
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controller.close();
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return;
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@ -38,6 +38,8 @@ export async function GET() {
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modelId: model.modelId,
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name: model.name,
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provider: model.provider,
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serviceProvider: model.serviceProvider,
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outputType: model.outputType,
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description: model.description,
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maxTokens: model.maxTokens,
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inputCostPer1k: model.inputCostPer1k,
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204
src/lib/uniapi.ts
Normal file
204
src/lib/uniapi.ts
Normal file
@ -0,0 +1,204 @@
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interface UniAPIModel {
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id: string
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name: string
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description?: string
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provider?: string
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context_length?: number
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pricing?: {
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input: number
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output: number
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}
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features?: string[]
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type?: 'text' | 'image' | 'audio' | 'video' | 'multimodal'
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}
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interface UniAPIResponse {
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data: UniAPIModel[]
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error?: string
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}
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export class UniAPIService {
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private apiKey: string
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private baseUrl = 'https://api.uniapi.io/v1'
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constructor() {
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this.apiKey = process.env.UNIAPI_API_KEY || ''
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if (!this.apiKey) {
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throw new Error('UNIAPI_API_KEY environment variable is required')
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}
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}
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async getAvailableModels(): Promise<UniAPIModel[]> {
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try {
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const response = await fetch(`${this.baseUrl}/models`, {
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headers: {
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'Authorization': `Bearer ${this.apiKey}`,
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'Content-Type': 'application/json',
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},
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})
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if (!response.ok) {
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const errorText = await response.text()
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throw new Error(`UniAPI error: ${response.status} ${response.statusText}`)
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}
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const data = await response.json()
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// 检查不同可能的响应格式
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let models: UniAPIModel[] = []
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if (data.data && Array.isArray(data.data)) {
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models = data.data
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} else if (Array.isArray(data)) {
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models = data
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} else if (data.models && Array.isArray(data.models)) {
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models = data.models
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} else {
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throw new Error('Unexpected response format from UniAPI')
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}
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if (data.error) {
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throw new Error(`UniAPI API error: ${data.error}`)
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}
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return models
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} catch (error) {
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console.error('Error fetching UniAPI models:', error)
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throw error
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}
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}
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// 将 UniAPI 模型转换为我们数据库的格式
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transformModelForDB(model: UniAPIModel) {
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// 确保模型有基本的属性
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if (!model.id) {
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return null
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}
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return {
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modelId: model.id,
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name: model.name || model.id || 'Unnamed Model', // 如果没有名称，使用模型ID作为后备
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provider: model.provider || this.extractProvider(model.id),
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serviceProvider: 'uniapi',
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outputType: model.type || 'text',
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description: model.description || null,
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maxTokens: model.context_length || null,
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inputCostPer1k: model.pricing?.input ? model.pricing.input * 1000 : null,
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outputCostPer1k: model.pricing?.output ? model.pricing.output * 1000 : null,
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supportedFeatures: {
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type: model.type,
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features: model.features || [],
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},
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metadata: {
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original: model,
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},
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}
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}
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private extractProvider(modelId: string): string {
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// 从模型 ID 中提取提供商名称
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const providerMap: Record<string, string> = {
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'openai': 'OpenAI',
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'anthropic': 'Anthropic',
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'claude': 'Anthropic',
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'google': 'Google',
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'gemini': 'Google',
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'meta': 'Meta',
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'llama': 'Meta',
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'microsoft': 'Microsoft',
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'mistral': 'Mistral AI',
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'cohere': 'Cohere',
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'stability': 'Stability AI',
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'midjourney': 'Midjourney',
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'dall-e': 'OpenAI',
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'gpt': 'OpenAI',
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}
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const modelLower = modelId.toLowerCase()
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// 尝试从 ID 中匹配提供商
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for (const [key, value] of Object.entries(providerMap)) {
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if (modelLower.includes(key)) {
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return value
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}
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}
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// 如果包含斜杠，取斜杠前的部分
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if (modelId.includes('/')) {
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const provider = modelId.split('/')[0]
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return providerMap[provider.toLowerCase()] ||
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provider.charAt(0).toUpperCase() + provider.slice(1)
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}
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// 如果包含连字符，取第一个部分
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if (modelId.includes('-')) {
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const provider = modelId.split('-')[0]
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return providerMap[provider.toLowerCase()] ||
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provider.charAt(0).toUpperCase() + provider.slice(1)
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}
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return 'UniAPI'
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}
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// 执行聊天完成请求
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async createChatCompletion(params: {
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model: string
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messages: Array<{role: string, content: string}>
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temperature?: number
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max_tokens?: number
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top_p?: number
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frequency_penalty?: number
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presence_penalty?: number
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}) {
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try {
|
||||
const response = await fetch(`${this.baseUrl}/chat/completions`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Authorization': `Bearer ${this.apiKey}`,
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify(params),
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
const errorData = await response.json().catch(() => ({}))
|
||||
throw new Error(`UniAPI API error: ${response.status} ${response.statusText} - ${errorData.error || ''}`)
|
||||
}
|
||||
|
||||
return await response.json()
|
||||
} catch (error) {
|
||||
console.error('Error calling UniAPI chat completion:', error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
// 执行图像生成请求
|
||||
async createImageGeneration(params: {
|
||||
model: string
|
||||
prompt: string
|
||||
size?: string
|
||||
quality?: string
|
||||
n?: number
|
||||
}) {
|
||||
try {
|
||||
const response = await fetch(`${this.baseUrl}/images/generations`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Authorization': `Bearer ${this.apiKey}`,
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify(params),
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
const errorData = await response.json().catch(() => ({}))
|
||||
throw new Error(`UniAPI API error: ${response.status} ${response.statusText} - ${errorData.error || ''}`)
|
||||
}
|
||||
|
||||
return await response.json()
|
||||
} catch (error) {
|
||||
console.error('Error calling UniAPI image generation:', error)
|
||||
throw error
|
||||
}
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user