feat(ai): 면접 모드를 mode로 통합해 관리

pswaao88 · pswaao88 · commit 63bb00b2f7d5 · 2026-06-01T19:47:41.000+09:00
diff --git a/ai/src/ai_server/chain/feedback_generation_chain.py b/ai/src/ai_server/chain/feedback_generation_chain.py
@@ -28,7 +28,7 @@ async def generate(
         self,
         *,
         job_category: str,
-        interview_type: str,
+        mode: str,
         total_question_count: int | None,
         end_reason: str | None,
         transcript: str,
@@ -44,7 +44,7 @@ async def generate(
         self,
         *,
         job_category: str,
-        interview_type: str,
+        mode: str,
         total_question_count: int | None,
         end_reason: str | None,
         transcript: str,
@@ -53,7 +53,7 @@ async def generate(
         result = await self._chain.ainvoke(
             {
                 "job_category": job_category,
-                "interview_type": interview_type,
+                "mode": mode,
                 "total_question_count": total_question_count or 0,
                 "end_reason": end_reason or "USER_REQUEST",
                 "transcript": transcript,
diff --git a/ai/src/ai_server/chain/followup_generation_chain.py b/ai/src/ai_server/chain/followup_generation_chain.py
@@ -24,7 +24,7 @@ async def generate(
         self,
         *,
         job_category: str,
-        interview_type: str,
+        mode: str,
         previous_question: str,
         answer_text: str,
     ) -> FollowupResult: ...
@@ -38,14 +38,14 @@ async def generate(
         self,
         *,
         job_category: str,
-        interview_type: str,
+        mode: str,
         previous_question: str,
         answer_text: str,
     ) -> FollowupResult:
         result = await self._chain.ainvoke(
             {
                 "job_category": job_category,
-                "interview_type": interview_type,
+                "mode": mode,
                 "previous_question": previous_question,
                 "answer_text": answer_text,
             }
diff --git a/ai/src/ai_server/chain/prompts/feedback_generation.py b/ai/src/ai_server/chain/prompts/feedback_generation.py
@@ -22,7 +22,7 @@
 
 HUMAN_PROMPT = (
     "직군: {job_category}\n"
-    "면접 유형: {interview_type}\n"
+    "면접 모드: {mode}\n"
     "총 질문 수: {total_question_count}\n"
     "종료 사유: {end_reason}\n\n"
     "=== 메시지 시퀀스 ===\n"
diff --git a/ai/src/ai_server/chain/prompts/followup_generation.py b/ai/src/ai_server/chain/prompts/followup_generation.py
@@ -17,7 +17,7 @@
 
 HUMAN_PROMPT = (
     "직군: {job_category}\n"
-    "면접 유형: {interview_type}\n\n"
+    "면접 모드: {mode}\n\n"
     "직전 질문:\n{previous_question}\n\n"
     "지원자 답변:\n{answer_text}\n\n"
     "{format_instructions}"
diff --git a/ai/src/ai_server/chain/prompts/question_generation.py b/ai/src/ai_server/chain/prompts/question_generation.py
@@ -1,9 +1,9 @@
 # 질문 풀 생성 프롬프트 (US-18)
-# 분석된 이력서/레포 컨텍스트 + 직군 + 면접 유형 → 질문 N개.
+# 분석된 이력서/레포 컨텍스트 + 직군 + 면접 모드 → 질문 N개.
 
 SYSTEM_PROMPT = (
     "당신은 IT 직군 채용을 진행하는 시니어 면접관입니다. "
-    "지원자 컨텍스트(이력서, GitHub 레포 분석)와 면접 유형에 맞춰 면접 질문 풀을 "
+    "지원자 컨텍스트(이력서, GitHub 레포 분석)와 면접 모드에 맞춰 면접 질문 풀을 "
     "생성하세요.\n"
     "- 사실에 근거한 질문만. 자료에 없는 내용은 추측하지 않습니다.\n"
     "- 자료에 명시된 기술 스택과 프로젝트 경험을 적극 인용하세요.\n"
@@ -15,7 +15,7 @@
 
 HUMAN_PROMPT = (
     "직군: {job_category}\n"
-    "면접 유형: {interview_type}\n"
+    "면접 모드: {mode}\n"
     "최대 질문 수: {max_questions}\n\n"
     "지원자 컨텍스트 (이력서/레포 분석):\n"
     "---\n"
@@ -24,7 +24,7 @@
     "요구 사항:\n"
     "1. 정확히 {max_questions}개의 질문을 생성합니다.\n"
     "2. 각 질문에 적절한 category 를 부여합니다.\n"
-    "3. 직군({job_category})·유형({interview_type}) 에 맞는 비중으로 카테고리 분배:\n"
+    "3. 직군({job_category})·면접 모드({mode}) 에 맞는 비중으로 카테고리 분배:\n"
     "   - TECHNICAL: CS_FUNDAMENTAL + TECH_CHOICE + PROJECT_DEEP_DIVE 중심.\n"
     "   - PERSONALITY: BEHAVIORAL 중심.\n"
     "   - INTEGRATED: 모두 균형.\n"
diff --git a/ai/src/ai_server/chain/question_generation_chain.py b/ai/src/ai_server/chain/question_generation_chain.py
@@ -23,7 +23,7 @@ async def generate(
         self,
         *,
         job_category: str,
-        interview_type: str,
+        mode: str,
         max_questions: int,
         context: str,
     ) -> GeneratedQuestionPool: ...
@@ -37,14 +37,14 @@ async def generate(
         self,
         *,
         job_category: str,
-        interview_type: str,
+        mode: str,
         max_questions: int,
         context: str,
     ) -> GeneratedQuestionPool:
         result = await self._chain.ainvoke(
             {
                 "job_category": job_category,
-                "interview_type": interview_type,
+                "mode": mode,
                 "max_questions": max_questions,
                 "context": context,
             }
diff --git a/ai/src/ai_server/messaging/consumers/feedback_consumer.py b/ai/src/ai_server/messaging/consumers/feedback_consumer.py
@@ -87,7 +87,7 @@ async def handle(self, message: AbstractIncomingMessage) -> None:
 
             result = await self._generator.generate(
                 job_category=req.job_category,
-                interview_type=req.interview_type,
+                mode=req.mode,
                 total_question_count=req.total_question_count,
                 end_reason=req.end_reason,
                 transcript=transcript,
diff --git a/ai/src/ai_server/messaging/consumers/followup_consumer.py b/ai/src/ai_server/messaging/consumers/followup_consumer.py
@@ -62,7 +62,7 @@ async def handle(self, message: AbstractIncomingMessage) -> None:
 
             result = await self._generator.generate(
                 job_category=req.job_category,
-                interview_type=req.interview_type,
+                mode=req.mode,
                 previous_question=req.previous_question,
                 answer_text=req.answer_text,
             )
diff --git a/ai/src/ai_server/messaging/consumers/questions_consumer.py b/ai/src/ai_server/messaging/consumers/questions_consumer.py
@@ -71,7 +71,7 @@ async def handle(self, message: AbstractIncomingMessage) -> None:
             context_text = _build_context(req.documents)
             pool = await self._generator.generate(
                 job_category=req.job_category,
-                interview_type=req.interview_type,
+                mode=req.mode,
                 max_questions=effective_pool_size,
                 context=context_text,
             )
diff --git a/ai/src/ai_server/model/messages/feedback.py b/ai/src/ai_server/model/messages/feedback.py
@@ -4,6 +4,8 @@
 
 from ai_server.model._config import camel_config
 
+InterviewMode = Literal["PERSONALITY", "TECHNICAL", "INTEGRATED"]
+
 
 class FeedbackMessageItem(BaseModel):
     """세션 시퀀스 한 줄 (Core 가 통째로 동봉)."""
@@ -21,7 +23,7 @@ class GenerateFeedbackRequest(BaseModel):
     model_config = camel_config()
 
     session_id: int
-    interview_type: Literal["PERSONALITY", "TECHNICAL", "LIVE_CODING", "INTEGRATED"]
+    mode: InterviewMode
     job_category: Literal["FRONTEND", "BACKEND", "INFRA", "DBA"]
     total_question_count: int | None = None
     end_reason: Literal["USER_REQUEST", "MAX_QUESTIONS_REACHED"] | None = None
diff --git a/ai/src/ai_server/model/messages/followup.py b/ai/src/ai_server/model/messages/followup.py
@@ -4,6 +4,8 @@
 
 from ai_server.model._config import camel_config
 
+InterviewMode = Literal["PERSONALITY", "TECHNICAL", "INTEGRATED"]
+
 
 class GenerateFollowupRequest(BaseModel):
     """Core 가 답변 commit 후 발행."""
@@ -14,7 +16,7 @@ class GenerateFollowupRequest(BaseModel):
     answer_message_id: int                  # 답변 메시지 ID
     previous_question: str
     answer_text: str
-    interview_type: Literal["PERSONALITY", "TECHNICAL", "LIVE_CODING", "INTEGRATED"]
+    mode: InterviewMode
     job_category: Literal["FRONTEND", "BACKEND", "INFRA", "DBA"]
 
 
diff --git a/ai/src/ai_server/model/messages/questions.py b/ai/src/ai_server/model/messages/questions.py
@@ -4,7 +4,7 @@
 
 from ai_server.model._config import camel_config
 
-InterviewType = Literal["PERSONALITY", "TECHNICAL", "LIVE_CODING", "INTEGRATED"]
+InterviewMode = Literal["PERSONALITY", "TECHNICAL", "INTEGRATED"]
 JobCategory = Literal["FRONTEND", "BACKEND", "INFRA", "DBA"]
 QuestionCategory = Literal[
     "CS_FUNDAMENTAL",
@@ -30,7 +30,7 @@ class GenerateQuestionsRequest(BaseModel):
     model_config = camel_config()
 
     session_id: int
-    interview_type: InterviewType
+    mode: InterviewMode
     job_category: JobCategory
     documents: list[DocumentContext] = []
     max_questions: int = 10
diff --git a/ai/src/ai_server/model/messages/voice.py b/ai/src/ai_server/model/messages/voice.py
@@ -4,6 +4,8 @@
 
 from ai_server.model._config import camel_config
 
+InterviewMode = Literal["PERSONALITY", "TECHNICAL", "INTEGRATED"]
+
 
 class AnalyzeVoiceRequest(BaseModel):
     """Core 가 음성 답변 업로드 commit 후 발행."""
@@ -15,7 +17,7 @@ class AnalyzeVoiceRequest(BaseModel):
     audio_s3_key: str
     content_type: str
     previous_question_text: str | None = None
-    interview_type: Literal["PERSONALITY", "TECHNICAL", "LIVE_CODING", "INTEGRATED"]
+    mode: InterviewMode
     job_category: Literal["FRONTEND", "BACKEND", "INFRA", "DBA"]
 
 
diff --git a/ai/tests/test_feedback_consumer.py b/ai/tests/test_feedback_consumer.py
@@ -39,7 +39,7 @@ def _envelope(*, context_documents: list[int] | None = None) -> bytes:
         "publisher": "core-server",
         "payload": {
             "sessionId": 50,
-            "interviewType": "TECHNICAL",
+            "mode": "TECHNICAL",
             "jobCategory": "BACKEND",
             "totalQuestionCount": 2,
             "endReason": "MAX_QUESTIONS_REACHED",
diff --git a/ai/tests/test_followup_consumer.py b/ai/tests/test_followup_consumer.py
@@ -45,7 +45,7 @@ def _envelope() -> bytes:
             "answerMessageId": 502,
             "previousQuestion": "결제 outbox 어떻게 구현?",
             "answerText": "RabbitMQ로 보냈습니다.",
-            "interviewType": "TECHNICAL",
+            "mode": "TECHNICAL",
             "jobCategory": "BACKEND",
         },
         "context": {"userId": 42, "sessionId": 99},
diff --git a/ai/tests/test_questions_consumer.py b/ai/tests/test_questions_consumer.py
@@ -73,7 +73,7 @@ async def test_consumer_generates_questions_and_publishes_callback():
     body = _envelope(
         {
             "sessionId": 99,
-            "interviewType": "TECHNICAL",
+            "mode": "TECHNICAL",
             "jobCategory": "BACKEND",
             "documents": [
                 {
@@ -92,7 +92,7 @@ async def test_consumer_generates_questions_and_publishes_callback():
     generator.generate.assert_awaited_once()
     call = generator.generate.await_args
     assert call.kwargs["job_category"] == "BACKEND"
-    assert call.kwargs["interview_type"] == "TECHNICAL"
+    assert call.kwargs["mode"] == "TECHNICAL"
     # envelope.max_questions(=5) 무시하고 initial_pool_size(default 1) 로 강제. Core 가 첫 질문만 사용.
     assert call.kwargs["max_questions"] == 1
     assert "Java" in call.kwargs["context"]
@@ -126,7 +126,7 @@ async def test_consumer_skips_when_message_id_already_seen():
     body = _envelope(
         {
             "sessionId": 99,
-            "interviewType": "TECHNICAL",
+            "mode": "TECHNICAL",
             "jobCategory": "BACKEND",
             "documents": [],
             "maxQuestions": 3,
diff --git a/ai/tests/test_voice_consumer.py b/ai/tests/test_voice_consumer.py
@@ -47,7 +47,7 @@ def _envelope() -> bytes:
             "audioS3Key": "interview/voice/raw/99/501.webm",
             "contentType": "audio/webm",
             "previousQuestionText": "ACID 설명해주세요",
-            "interviewType": "TECHNICAL",
+            "mode": "TECHNICAL",
             "jobCategory": "BACKEND",
         },
         "context": {"userId": 42, "sessionId": 99},

Original file line number	Diff line number	Diff line change
`@@ -62,7 +62,7 @@ async def handle(self, message: AbstractIncomingMessage) -> None:`
`62`	`62`
`63`	`63`	`result = await self._generator.generate(`
`64`	`64`	`job_category=req.job_category,`
`65`		`- interview_type=req.interview_type,`
	`65`	`+ mode=req.mode,`
`66`	`66`	`previous_question=req.previous_question,`
`67`	`67`	`answer_text=req.answer_text,`
`68`	`68`	`)`
Original file line number	Diff line number	Diff line change
`@@ -71,7 +71,7 @@ async def handle(self, message: AbstractIncomingMessage) -> None:`
`71`	`71`	`context_text = _build_context(req.documents)`
`72`	`72`	`pool = await self._generator.generate(`
`73`	`73`	`job_category=req.job_category,`
`74`		`- interview_type=req.interview_type,`
	`74`	`+ mode=req.mode,`
`75`	`75`	`max_questions=effective_pool_size,`
`76`	`76`	`context=context_text,`
`77`	`77`	`)`