feat(阶段3): oj 侧端点铺开(基线提交,未经评审)
由外部 agent (Codex) 在本会话额度中断期间完成。原样提交作为基线, 后续修复单独成 commit,便于区分与回退。 覆盖 oj 侧 65 个端点,新增 9 组路由(account/achievement/ai/classroom/ content/contest/flowchart/problemset/site)与对应 Zod 契约。 已核验:tsc --noEmit 退出码 0;API 可启动;/api/problems 返回真实数据; judge 与 flowchart worker 均 ready。 未核验:权限边界与数据泄露,评审进行中。 Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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@@ -0,0 +1,105 @@
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import { config } from "../config"
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interface ChatMessage {
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role: "system" | "user"
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content: string
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}
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function requestBody(messages: ChatMessage[], stream: boolean) {
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return {
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model: config.aiModel,
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messages,
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stream,
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temperature: 0,
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thinking: { type: "disabled" },
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}
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}
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export async function completeChat(system: string, user: string) {
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if (!config.aiKey) throw new Error("缺少 AI_KEY")
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const response = await fetch(new URL("/chat/completions", config.aiBaseUrl), {
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method: "POST",
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headers: { "content-type": "application/json", authorization: `Bearer ${config.aiKey}` },
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body: JSON.stringify(requestBody([
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{ role: "system", content: system },
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{ role: "user", content: user },
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], false)),
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})
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if (!response.ok) throw new Error(`AI provider returned HTTP ${response.status}: ${await response.text()}`)
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const payload = await response.json() as { choices?: Array<{ message?: { content?: string } }> }
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return payload.choices?.[0]?.message?.content?.trim() ?? ""
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}
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export function streamChat(
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system: string,
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user: string,
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onComplete?: (value: string) => Promise<void>,
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) {
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const encoder = new TextEncoder()
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const body = new ReadableStream<Uint8Array>({
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async start(controller) {
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const send = (value: string) => controller.enqueue(encoder.encode(value))
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if (!config.aiKey) {
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send(`data: ${JSON.stringify({ type: "error", message: "缺少 AI_KEY" })}\n\n`)
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send("event: end\n\n")
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controller.close()
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return
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}
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try {
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const response = await fetch(new URL("/chat/completions", config.aiBaseUrl), {
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method: "POST",
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headers: { "content-type": "application/json", authorization: `Bearer ${config.aiKey}` },
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body: JSON.stringify(requestBody([
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{ role: "system", content: system },
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{ role: "user", content: user },
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], true)),
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})
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if (!response.ok || !response.body) throw new Error(`AI provider returned HTTP ${response.status}: ${await response.text()}`)
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send("event: start\n\n")
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const reader = response.body.getReader()
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const decoder = new TextDecoder()
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let buffer = ""
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const chunks: string[] = []
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while (true) {
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const { done, value } = await reader.read()
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buffer += decoder.decode(value, { stream: !done })
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const lines = buffer.split("\n")
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buffer = lines.pop() ?? ""
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for (const raw of lines) {
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const line = raw.trim()
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if (!line.startsWith("data:")) continue
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const data = line.slice(5).trim()
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if (data === "[DONE]") continue
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try {
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const item = JSON.parse(data) as { choices?: Array<{ delta?: { content?: string }; finish_reason?: string | null }> }
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const choice = item.choices?.[0]
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const content = choice?.delta?.content
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if (content) {
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chunks.push(content)
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send(`data: ${JSON.stringify({ type: "delta", content })}\n\n`)
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}
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} catch {
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// Provider keepalive or a partial non-data line.
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}
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}
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if (done) break
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}
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const full = chunks.join("").trim()
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if (onComplete) await onComplete(full)
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send(`data: ${JSON.stringify({ type: "done" })}\n\n`)
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} catch (error) {
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send(`data: ${JSON.stringify({ type: "error", message: error instanceof Error ? error.message : String(error) })}\n\n`)
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} finally {
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send("event: end\n\n")
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controller.close()
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}
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},
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})
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return new Response(body, {
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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",
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"x-accel-buffering": "no",
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},
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})
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}
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