feat: 前端组件准备

2026-05-22 15:02:31 +08:00
parent 397ccdca13
commit 5e05bf4f63
62 changed files with 6903 additions and 878 deletions
@@ -0,0 +1,226 @@
+// server/utils/openai.ts - OpenAI Chat Completions 流式调用工具
+import { serverEnv } from "~~/server/utils/env";
+
+/** 旧项目的 `OPENAI_API_BASE` 语义是完整 base，例如 `https://api.openai.com/v1` */
+const CHAT_COMPLETIONS_URL = `${serverEnv.openAiApiBase}/chat/completions`;
+/** 复用编码器计算 SSE data 字节长度，避免循环里频繁创建对象 */
+const textEncoder = new TextEncoder();
+
+/** Chat Completions SSE 每个 `data:` chunk 的最小结构 */
+interface ChatCompletionStreamChunk {
+  id?: string;
+  object?: string;
+  created?: number;
+  model?: string;
+  choices?: Array<{
+    delta?: {
+      content?: string;
+      role?: string;
+    };
+    finish_reason?: string | null;
+    index?: number;
+  }>;
+  usage?: unknown;
+}
+
+/** 读取完整 SSE 后汇总出的信息；只在服务端日志或内部状态中使用 */
+interface ChatCompletionStreamResult {
+  /** 累积的 `choices[].delta.content` 文本 */
+  content: string;
+  /** content 字符长度，方便排查模型是否返回了异常长文本 */
+  contentLength: number;
+  /** 实际解析到的 SSE JSON chunk 数量 */
+  chunkCount: number;
+  /** 模型返回的结束原因，例如 stop、length；可能不存在 */
+  finishReason?: string | null;
+  /** 上游如果返回 usage，则保留下来供内部排查 */
+  usage?: unknown;
+}
+
+/** 答题调用结果：对外只用 answer，upstreamResponse 留给服务端排查 */
+export interface AskAnswerStreamResult {
+  answer: string;
+  upstreamResponse: ChatCompletionStreamResult;
+}
+
+/**
+ * 通过 Chat Completions 流式接口生成答案
+ *
+ * 对 OCS 客户端仍返回普通 JSON；流式只发生在服务端到 OpenAI 之间
+ * 这样既能更早读取上游内容，又不破坏 AnswererWrapper 的 handler 契约
+ */
+export const askAnswerStream = async ({
+  prompt,
+  systemPrompt
+}: {
+  prompt: string;
+  systemPrompt: string;
+}): Promise<AskAnswerStreamResult> => {
+  if (!serverEnv.openAiApiKey) {
+    throw new Error("OPENAI_API_KEY is not set.");
+  }
+
+  // 这里不要记录 request body：其中包含完整题目和可能的选项文本
+  const response = await fetch(CHAT_COMPLETIONS_URL, {
+    method: "POST",
+    headers: {
+      Authorization: `Bearer ${serverEnv.openAiApiKey}`,
+      "Content-Type": "application/json"
+    },
+    body: JSON.stringify({
+      model: serverEnv.openAiModel,
+      temperature: serverEnv.temperature,
+      max_tokens: serverEnv.maxTokens,
+      stream: true,
+      messages: [
+        {
+          role: "system",
+          content: systemPrompt
+        },
+        {
+          role: "user",
+          content: prompt
+        }
+      ]
+    })
+  });
+
+  if (!response.ok) {
+    throw new Error(`OpenAI request failed with status ${response.status}.`);
+  }
+
+  if (!response.body) {
+    throw new Error("OpenAI stream body is empty.");
+  }
+
+  // 将 SSE delta 读完后再返回给 API handler，由 handler 统一做答案清洗和缓存
+  const upstreamResponse = await readChatCompletionStream(response.body);
+
+  return {
+    answer: upstreamResponse.content.trim(),
+    upstreamResponse
+  };
+};
+
+/**
+ * 读取 Chat Completions SSE 流
+ *
+ * 上游返回形如：
+ * `data: {"choices":[{"delta":{"content":"..."}}]}`
+ * `data: [DONE]`
+ *
+ * 网络 chunk 不一定按行对齐，所以用 buffer 保存尚未拼完整的一行
+ */
+export const readChatCompletionStream = async (
+  stream: ReadableStream<Uint8Array>
+): Promise<ChatCompletionStreamResult> => {
+  const reader = stream.getReader();
+  const decoder = new TextDecoder();
+  let buffer = "";
+  let content = "";
+  let chunkCount = 0;
+  let finishReason: string | null | undefined;
+  let usage: unknown;
+
+  /** 把一个已解析 JSON chunk 合并进最终结果 */
+  const collectChunk = (chunk: ChatCompletionStreamChunk) => {
+    chunkCount += 1;
+
+    const deltaContent = collectDeltaContent(chunk);
+    if (deltaContent) {
+      content += deltaContent;
+    }
+
+    if (chunk.usage) {
+      usage = chunk.usage;
+    }
+
+    finishReason =
+      chunk.choices?.find((choice) => choice.finish_reason)?.finish_reason ??
+      finishReason;
+  };
+
+  while (true) {
+    const { done, value } = await reader.read();
+    if (done) break;
+
+    // stream: true 可以正确处理跨 chunk 的多字节字符，例如中文
+    buffer += decoder.decode(value, { stream: true });
+    assertSseBufferSize(buffer, serverEnv.maxSseLineBytes);
+
+    // 只处理已经遇到换行的完整 SSE 行，最后一段留到下次 chunk 再拼
+    const lines = buffer.split(/\r?\n/u);
+    buffer = lines.pop() ?? "";
+
+    for (const line of lines) {
+      const chunk = parseSseDataLine(line, serverEnv.maxSseLineBytes);
+      if (chunk) collectChunk(chunk);
+    }
+  }
+
+  // 处理流结束时仍留在 buffer 中的最后一行
+  const finalText = buffer + decoder.decode();
+  for (const line of finalText.split(/\r?\n/u)) {
+    const chunk = parseSseDataLine(line, serverEnv.maxSseLineBytes);
+    if (chunk) collectChunk(chunk);
+  }
+
+  return {
+    content,
+    contentLength: content.length,
+    chunkCount,
+    finishReason,
+    usage
+  };
+};
+
+/**
+ * 解析单行 SSE data
+ *
+ * 空行、event 行和 `[DONE]` 都不包含业务内容，直接跳过
+ * 超过大小限制的 data 行视为异常，防止上游或代理故障导致内存压力
+ */
+export const parseSseDataLine = (
+  line: string,
+  maxDataLineBytes: number
+): ChatCompletionStreamChunk | null => {
+  const trimmed = line.trim();
+  if (!trimmed.startsWith("data:")) return null;
+
+  const data = trimmed.slice("data:".length).trim();
+  if (!data || data === "[DONE]") return null;
+
+  if (textEncoder.encode(data).byteLength > maxDataLineBytes) {
+    throw new Error("OpenAI stream data line is too large.");
+  }
+
+  return JSON.parse(data) as ChatCompletionStreamChunk;
+};
+
+/** 收集一个 chunk 中所有 choice 的增量文本 */
+export const collectDeltaContent = (chunk: ChatCompletionStreamChunk) => {
+  return (
+    chunk.choices
+      ?.map((choice) => choice.delta?.content || "")
+      .filter(Boolean)
+      .join("") || ""
+  );
+};
+
+/**
+ * 限制尚未出现换行的 SSE 缓冲区大小
+ *
+ * 正常 SSE 会频繁换行；如果一直没有换行且持续变大，说明可能不是合法 SSE
+ * 或上游返回了异常长单行，应该尽早失败
+ */
+export const assertSseBufferSize = (
+  buffer: string,
+  maxDataLineBytes: number
+) => {
+  if (
+    !buffer.includes("\n") &&
+    textEncoder.encode(buffer).byteLength > maxDataLineBytes
+  ) {
+    throw new Error("OpenAI stream buffer is too large.");
+  }
+};