mirror of
https://github.com/DayuanJiang/next-ai-draw-io.git
synced 2026-10-12 12:39:52 +08:00
- lib/system-prompts.ts: delete the extended prompt kept only to reach the 4096-token cache threshold of two old Claude models; describe the current canvas-first UI in the App Features section - app/api/chat/route.ts: remove the server-side example cache (the browser answers examples itself), the ENABLE_HISTORY_XML_REPLACE option and its helper, the unread messageMetadata fields; the DEBUG_LLM_PAYLOAD blocks become one describeMessages summary - app/api/log-feedback and log-save share scoreLatestTrace in lib/langfuse.ts - app/api/admin/test-model and validate-model call a shared testModelConnection() instead of one route faking a request to the other and passing trust through the body - lib/dynamo-quota-manager.ts reads the failing item from the conditional update instead of a second GetItem - lib/ai-providers.ts: geminiThinkingOptions helper for the google and vertexai cases, drop the unused fourth resolveBaseURL parameter - edge-functions: always stream, shrink messageSchema, drop model aliases nothing sends - delete app/api/chat/xml_guide.md, parseOutputTokenLimit, unused type exports and export keywords on file-internal symbols - env.example: drop variables nothing reads, document the quota, validation and analytics variables, mention the apiKeyEnv array form (also in docs/*/ai-providers.md)
251 lines
7.7 KiB
TypeScript
251 lines
7.7 KiB
TypeScript
/**
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* EdgeOne Pages Edge Function for OpenAI-compatible Chat Completions API
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*
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* This endpoint provides an OpenAI-compatible API that can be used with
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* AI SDK's createOpenAI({ baseURL: '/api/edgeai' })
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*
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* Uses EdgeOne Edge AI's AI.chatCompletions() which now supports native tool calling.
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*/
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import { z } from "zod"
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// EdgeOne Pages global AI object
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declare const AI: {
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chatCompletions(options: {
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model: string
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messages: Array<{ role: string; content: string | null }>
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stream?: boolean
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max_tokens?: number
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temperature?: number
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tools?: any
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tool_choice?: any
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}): Promise<ReadableStream<Uint8Array> | any>
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}
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const messageItemSchema = z
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.object({
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role: z.enum(["user", "assistant", "system", "tool", "function"]),
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content: z.string().nullable().optional(),
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})
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.passthrough()
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// The fields read here; every other field is passed on to AI.chatCompletions
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const messageSchema = z
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.object({
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messages: z.array(messageItemSchema),
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model: z.string().optional(),
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stream: z.boolean().optional(),
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tools: z.any().optional(),
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tool_choice: z.any().optional(),
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})
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.passthrough()
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// Model configuration
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const ALLOWED_MODELS = [
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"@tx/deepseek-ai/deepseek-v32",
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"@tx/deepseek-ai/deepseek-r1-0528",
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"@tx/deepseek-ai/deepseek-v3-0324",
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]
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/**
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* Create standardized JSON response
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*/
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function createResponse(body: any, status = 200, extraHeaders = {}): Response {
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return new Response(JSON.stringify(body), {
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status,
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headers: {
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"Content-Type": "application/json",
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...extraHeaders,
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},
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})
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}
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// Only the app's own server (/api/chat, /api/validate-model) calls this
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// function, so no CORS headers are sent: other sites' pages can't call it
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// from a browser and spend the deployment's Edge AI quota.
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// Same rule as lib/access-code.ts, but reading the edge function's env.
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// No codes configured (or env unavailable) means no check.
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function hasValidAccessCode(request: Request, env: any): boolean {
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const accessCodes: string[] =
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env?.ACCESS_CODE_LIST?.split(",")
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.map((code: string) => code.trim())
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.filter(Boolean) || []
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if (accessCodes.length === 0) return true
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const accessCode = request.headers.get("x-access-code")
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return !!accessCode && accessCodes.includes(accessCode)
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}
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export async function onRequest({ request, env }: any) {
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// Requiring JSON also makes any cross-site browser request need a CORS
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// preflight, which fails without CORS headers. Only the type before any
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// parameters counts: "text/plain; x=application/json" needs none.
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const mediaType = (request.headers.get("content-type") ?? "")
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.split(";")[0]
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.trim()
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.toLowerCase()
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if (request.method !== "POST" || mediaType !== "application/json") {
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return createResponse(
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{
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error: {
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message: "Expected a POST request with a JSON body",
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type: "invalid_request_error",
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},
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},
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400,
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)
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}
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if (!hasValidAccessCode(request, env)) {
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return createResponse(
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{
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error: {
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message: "Invalid or missing access code",
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type: "invalid_request_error",
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},
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},
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401,
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)
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}
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request.headers.delete("accept-encoding")
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try {
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const json = await request.clone().json()
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const parseResult = messageSchema.safeParse(json)
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if (!parseResult.success) {
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return createResponse(
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{
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error: {
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message: parseResult.error.message,
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type: "invalid_request_error",
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},
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},
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400,
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)
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}
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// stream is taken out so it is not passed on: AI.chatCompletions
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// only streams, and every caller reads a stream
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const {
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messages,
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model,
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stream: _,
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tools,
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tool_choice,
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...extraParams
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} = parseResult.data
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// Validate messages
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const userMessages = messages.filter(
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(message) => message.role === "user",
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)
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if (!userMessages.length) {
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return createResponse(
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{
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error: {
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message: "No user message found",
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type: "invalid_request_error",
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},
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},
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400,
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)
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}
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// Resolve model
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const selectedModel = model || ALLOWED_MODELS[0]
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if (!ALLOWED_MODELS.includes(selectedModel)) {
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return createResponse(
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{
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error: {
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message: `Invalid model: ${selectedModel}.`,
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type: "invalid_request_error",
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},
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},
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400,
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)
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}
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console.log(
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`[EdgeOne] Model: ${selectedModel}, Tools: ${tools?.length || 0}`,
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)
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try {
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// Build AI.chatCompletions options for streaming
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const aiOptions: any = {
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...extraParams,
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model: selectedModel,
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messages,
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stream: true,
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}
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// Add tools if provided
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if (tools && tools.length > 0) {
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aiOptions.tools = tools
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}
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if (tool_choice !== undefined) {
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aiOptions.tool_choice = tool_choice
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}
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const aiResponse = await AI.chatCompletions(aiOptions)
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// Streaming response
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return new Response(aiResponse, {
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headers: {
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"Content-Type": "text/event-stream; charset=utf-8",
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"Cache-Control": "no-cache, no-store, no-transform",
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"X-Accel-Buffering": "no",
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Connection: "keep-alive",
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},
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})
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} catch (error: any) {
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// Handle EdgeOne specific errors
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try {
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const message = JSON.parse(error.message)
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if (message.code === 14020) {
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return createResponse(
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{
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error: {
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message:
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"The daily public quota has been exhausted. After deployment, you can enjoy a personal daily exclusive quota.",
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type: "rate_limit_error",
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},
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},
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429,
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)
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}
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return createResponse(
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{ error: { message: error.message, type: "api_error" } },
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500,
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)
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} catch {
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// Not a JSON error message
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}
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console.error("[EdgeOne] AI error:", error.message)
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return createResponse(
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{
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error: {
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message: error.message || "AI service error",
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type: "api_error",
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},
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},
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500,
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)
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}
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} catch (error: any) {
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console.error("[EdgeOne] Request error:", error.message)
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return createResponse(
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{
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error: {
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message: "Request processing failed",
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type: "server_error",
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details: error.message,
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},
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},
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500,
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)
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}
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}
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