mirror of
https://github.com/DayuanJiang/next-ai-draw-io.git
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feat: add EdgeOne Pages as AI provider (#456)
* feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * feat: edit diagram * feat: edit diagram * feat: edit diagram * feat: edit diagram * feat: edit diagram * feat: edit diagram * feat: edit diagram * feat: add edgeone provider * feat: add edgeone provider * feat: add edgeone provider * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: add cookie * fix: add cookie * fix: add cookie * fix: add cookie * fix: add cookie * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * fix: build error * feat: validate * feat: document link --------- Co-authored-by: zoejiezhou <zoejiezhou@tencent.com>
This commit is contained in:
zhoujie0531
270
edge-functions/api/edgeai/chat/completions.ts
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270
edge-functions/api/edgeai/chat/completions.ts
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/**
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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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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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functions: z.any().optional(),
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function_call: z.any().optional(),
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temperature: z.number().optional(),
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top_p: z.number().optional(),
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max_tokens: z.number().optional(),
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presence_penalty: z.number().optional(),
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frequency_penalty: z.number().optional(),
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stop: z.union([z.string(), z.array(z.string())]).optional(),
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response_format: z.any().optional(),
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seed: z.number().optional(),
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user: z.string().optional(),
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n: z.number().int().optional(),
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logit_bias: z.record(z.string(), z.number()).optional(),
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parallel_tool_calls: z.boolean().optional(),
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stream_options: 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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const MODEL_ALIASES: Record<string, string> = {
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"deepseek-v3.2": "@tx/deepseek-ai/deepseek-v32",
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"deepseek-r1-0528": "@tx/deepseek-ai/deepseek-r1-0528",
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"deepseek-v3-0324": "@tx/deepseek-ai/deepseek-v3-0324",
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}
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const CORS_HEADERS = {
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"Access-Control-Allow-Origin": "*",
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"Access-Control-Allow-Methods": "POST, OPTIONS",
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"Access-Control-Allow-Headers": "Content-Type, Authorization",
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}
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/**
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* Create standardized response with CORS headers
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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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...CORS_HEADERS,
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...extraHeaders,
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},
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})
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}
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/**
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* Handle OPTIONS request for CORS preflight
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*/
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function handleOptionsRequest(): Response {
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return new Response(null, {
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headers: {
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...CORS_HEADERS,
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"Access-Control-Max-Age": "86400",
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},
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})
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}
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export async function onRequest({ request, env }: any) {
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if (request.method === "OPTIONS") {
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return handleOptionsRequest()
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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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const { messages, model, stream, tools, tool_choice, ...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 requestedModel = model || ALLOWED_MODELS[0]
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const selectedModel = MODEL_ALIASES[requestedModel] || requestedModel
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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: ${requestedModel}.`,
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type: "invalid_request_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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console.log(
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`[EdgeOne] Model: ${selectedModel}, Tools: ${tools?.length || 0}, Stream: ${stream ?? true}`,
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)
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try {
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const isStream = !!stream
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// Non-streaming: return mock response for validation
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// AI.chatCompletions doesn't support non-streaming mode
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if (!isStream) {
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const mockResponse = {
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id: `chatcmpl-${Date.now()}`,
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object: "chat.completion",
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created: Math.floor(Date.now() / 1000),
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model: selectedModel,
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choices: [
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{
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index: 0,
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message: {
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role: "assistant",
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content: "OK",
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},
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finish_reason: "stop",
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},
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],
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usage: {
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prompt_tokens: 10,
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completion_tokens: 1,
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total_tokens: 11,
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},
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}
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return createResponse(mockResponse)
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}
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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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...CORS_HEADERS,
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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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