first-update

easy-dataset-main/app/api/projects/[projectId]/datasets/generate-eval-variant/route.js

@@ -0,0 +1,44 @@
+import { NextResponse } from 'next/server';
+import { getDatasetsById } from '@/lib/db/datasets';
+import LLMClient from '@/lib/llm/core/index';
+import { getEvalQuestionPrompt } from '@/lib/llm/prompts/evalQuestion';
+import { extractJsonFromLLMOutput } from '@/lib/llm/common/util';
+
+export async function POST(request, { params }) {
+  try {
+    const { projectId } = params;
+    const { datasetId, model, language, questionType = 'open_ended', count = 1 } = await request.json();
+
+    if (!datasetId || !model) {
+      return NextResponse.json({ error: 'Missing required parameters' }, { status: 400 });
+    }
+
+    // 1. 获取原数据集
+    const dataset = await getDatasetsById(datasetId);
+    if (!dataset) {
+      return NextResponse.json({ error: 'Dataset not found' }, { status: 404 });
+    }
+
+    // 2. 构建提示词
+    // 将原问题和答案合并作为上下文文本
+    const text = `Question: ${dataset.question}\nAnswer: ${dataset.answer}`;
+
+    const prompt = await getEvalQuestionPrompt(language || 'zh-CN', questionType, { text, number: count }, projectId);
+
+    // 3. 调用 LLM
+    const client = new LLMClient(model);
+
+    const response = await client.getResponse(prompt);
+    const result = extractJsonFromLLMOutput(response);
+
+    // 结果应该是一个数组
+    if (!result || !Array.isArray(result)) {
+      throw new Error('Failed to parse LLM output or output is not an array');
+    }
+
+    return NextResponse.json({ success: true, data: result });
+  } catch (error) {
+    console.error('Generate eval variant failed:', error);
+    return NextResponse.json({ error: error.message || 'Internal Server Error' }, { status: 500 });
+  }
+}