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fix(api): fix evaluation and exam endpoints for A.U pipeline

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This commit is contained in:
Jay
2026-04-16 18:43:23 +09:00
parent 239ed7381f
commit 9700670bef
1 changed files with 28 additions and 27 deletions
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src/extension.ts
+28 -27
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@@ -127,39 +127,40 @@ console.log('Connect AI extension activated.');
else if (req.method === 'POST' && req.url === '/api/exam') {
let body = '';
req.on('data', chunk => body += chunk.toString());
req.on('end', () => {
req.on('end', async () => {
try {
const parsed = JSON.parse(body);
// 웹사이트에서 전송된 문제를 Connect AI 채팅창으로 바로 전송
provider.sendPromptFromExtension(parsed.prompt || "자동 접수된 문제");
// 웹사이트에서 전송된 문제를 Connect AI 채팅창으로 실시간 보고
provider.sendPromptFromExtension(`[A.U 입학시험 수신] ${parsed.prompt || '자동 접수된 문제'}`);
// 실제 AI 엔진으로 문제를 전달하여 답안을 받아옴
const config = getConfig();
const isLMStudio = config.ollamaBase.includes('1234') || config.ollamaBase.includes('v1');
let base = config.ollamaBase;
if (base.endsWith('/')) base = base.slice(0, -1);
if (isLMStudio && !base.endsWith('/v1')) base += '/v1';
const targetUrl = isLMStudio ? base + '/chat/completions' : base + '/api/chat';
const payload = {
model: config.defaultModel,
messages: [{ role: 'user', content: parsed.prompt || '자동 접수된 문제' }],
stream: false
};
const ollamaRes = await axios.post(targetUrl, payload, { timeout: 120000 });
const responseText = isLMStudio
? ollamaRes.data.choices?.[0]?.message?.content || ''
: ollamaRes.data.message?.content || '';
res.writeHead(200, { 'Content-Type': 'application/json' });
res.end(JSON.stringify({
success: true,
message: '시험 문제가 접수되었습니다. VS Code의 Connect AI를 확인하세요!',
logicScore: 95.5,
formatScore: 100
}));
res.end(JSON.stringify({ success: true, rawOutput: responseText }));
} catch (e: any) {
res.writeHead(500);
res.end(JSON.stringify({ error: e.message }));
}
});
}
else if (req.method === 'POST' && req.url === '/api/exam') {
let body = '';
req.on('data', chunk => body += chunk.toString());
req.on('end', () => {
try {
const parsed = JSON.parse(body);
provider.sendPromptFromExtension(parsed.prompt);
res.writeHead(200, { 'Content-Type': 'application/json' });
res.end(JSON.stringify({ success: true }));
} catch (e: any) {
res.writeHead(500);
res.writeHead(500, { 'Content-Type': 'application/json' });
res.end(JSON.stringify({ error: e.message }));
}
});
}
else if (req.method === 'POST' && req.url === '/api/evaluate') {
let body = '';
req.on('data', chunk => body += chunk.toString());
@@ -201,8 +202,8 @@ console.log('Connect AI extension activated.');
? ollamaRes.data.choices?.[0]?.message?.content || ""
: ollamaRes.data.message?.content || "";
} catch (apiErr: any) {
res.writeHead(200, { 'Content-Type': 'application/json' });
res.end(JSON.stringify({ score: 85, reason: "네트워크 안정화 모드 (기본 85점 배점)" }));
res.writeHead(500, { 'Content-Type': 'application/json' });
res.end(JSON.stringify({ error: `오프라인: AI 엔진에 연결할 수 없습니다. (${apiErr.message})` }));
return;
}