Merge pull request #41 from 9git9git/SCRUM-55-BE-Storage-API-개발

[SCRUM-55] Storage, Chat API 연동   (구 Branch 사용(be storage api 개발))

Author: GideokKim

app/api/v1/endpoints/chat.py

@@ -5,7 +5,7 @@
 
 from app.db.session import get_db
 from app.schemas.base import ResponseBase
-from app.schemas.chat import ChatCreate, ChatUpdate, ChatResponse
+from app.schemas.chat import ChatCreate, ChatUpdate, ChatResponse, ChatWithModelResponse
 from app.services.chat import (
     select_chat,
     select_chats_by_user,
@@ -86,17 +86,17 @@ async def get_chat(
         )
 
 
-@router.post("/", response_model=ResponseBase[ChatResponse])
+@router.post("/", response_model=ResponseBase[ChatWithModelResponse])
 async def post_chat(
     user_id: UUID,
     storage_id: UUID,
     category_id: UUID,
     chat_data: ChatCreate,
     db: AsyncSession = Depends(get_db),
-) -> ResponseBase[ChatResponse]:
+) -> ResponseBase[ChatWithModelResponse]:
     try:
-        chat = await add_chat(db, user_id, storage_id, category_id, chat_data)
-        return ResponseBase(status_code=status.HTTP_201_CREATED, data=chat)
+        chat_result = await add_chat(db, user_id, storage_id, category_id, chat_data)
+        return ResponseBase(status_code=status.HTTP_201_CREATED, data=chat_result)
     except HTTPException as e:
         return ResponseBase(status_code=e.status_code, error=e.detail)
     except Exception as e:

app/crud/category.py

@@ -70,8 +70,8 @@ async def update_category(
 
 
 # 카테고리 삭제
-async def delete_category(db: AsyncSession, db_category: Category) -> bool:
-    delete_stmt = delete(Category).where(Category.id == db_category.id)
+async def delete_category(db: AsyncSession, category_id: UUID) -> bool:
+    delete_stmt = delete(Category).where(Category.id == category_id)
     try:
         await db.execute(delete_stmt)
         await db.commit()

app/crud/chat.py

@@ -1,10 +1,22 @@
 from uuid import UUID
 from typing import List
-from sqlalchemy import select, delete
+from sqlalchemy import select, delete, text
+from sqlalchemy.orm import joinedload
 from sqlalchemy.ext.asyncio import AsyncSession
 from app.models.chat import Chat
-from app.schemas.chat import ChatCreate, ChatUpdate, ChatResponse
+from app.models.category import Category
+from app.schemas.chat import (
+    ChatCreate,
+    ChatUpdate,
+    ChatResponse,
+    ModelResponse,
+    ChatWithModelResponse,
+)
+from app.enum.chat import RoleEnum
 from app.utils.to_snake_case import camel_to_snake
+from app.utils.chat_model_selector import route_to_model
+from app.enum.category import CategoryNameEnum
+from app.models.category import Category
 
 
 # 생성
@@ -14,20 +26,62 @@ async def create_chat(
     storage_id: UUID,
     category_id: UUID,
     chat_data: ChatCreate,
-) -> ChatResponse:
+) -> ChatWithModelResponse:
 
-    new_chat = Chat(
+    user_chat = Chat(
         user_id=user_id,
         storage_id=storage_id,
         category_id=category_id,
         role=chat_data.role,
         content=chat_data.content,
+        created_at=chat_data.created_at,
     )
-
-    db.add(new_chat)
+    db.add(user_chat)
     await db.commit()
-    await db.refresh(new_chat)
-    return new_chat
+    await db.refresh(user_chat)
+
+    # ✅ 카테고리 이름 직접 SQL로 조회 (ENUM)
+    result = await db.execute(
+        text(
+            """
+        SELECT category_name
+        FROM categories
+        WHERE id = :category_id
+        """
+        ),
+        {"category_id": str(category_id)},
+    )
+    row = result.first()
+
+    if row is None:
+        raise ValueError("❌ 해당 category_id에 대한 카테고리를 찾을 수 없습니다.")
+
+    category_enum = CategoryNameEnum[row.category_name]
+
+    # ✅ GPT 호출
+    if chat_data.role == RoleEnum.USER:
+        model_func = route_to_model(category_enum)
+        gpt_response = model_func(chat_data.content)
+
+        assistant_chat = Chat(
+            user_id=user_id,
+            storage_id=storage_id,
+            category_id=category_id,
+            role=RoleEnum.ASSISTANT,
+            content=gpt_response,
+        )
+        db.add(assistant_chat)
+        await db.commit()
+        await db.refresh(assistant_chat)
+
+        return ChatWithModelResponse(
+            chat=user_chat, model_response=ModelResponse(content=gpt_response)
+        )
+
+    # assistant role이 아닌 경우
+    return ChatWithModelResponse(
+        chat=user_chat, model_response=ModelResponse(content="")
+    )
 
 
 # 단일 채팅 조회

app/crud/storage.py

@@ -8,12 +8,21 @@
 
 
 async def create_storage(
-    db: AsyncSession, user_id: UUID, category_id: UUID, storage_data: StorageCreate
+    db: AsyncSession,
+    user_id: UUID,
+    category_id: UUID,
+    storage_data: StorageCreate,
 ) -> StorageResponse:
+    title = (
+        storage_data.title
+        or f"[{storage_data.created_at.strftime('%Y-%m-%d')}] New Chat"
+    )
+
     db_storage = Storage(
         user_id=user_id,
         category_id=category_id,
-        title=storage_data.title,
+        title=title,
+        created_at=storage_data.created_at,
     )
 
     db.add(db_storage)

app/gpt/.gitignore

@@ -0,0 +1,32 @@
+# .gitignore
+
+# ✅ 민감정보 (절대 Git에 올라가면 안 됨)
+.env
+
+# ✅ 파이썬 캐시 (자동 생성되며 필요 없음)
+__pycache__/
+*.pyc
+
+# ✅ 주피터 노트북 관련 캐시
+.ipynb_checkpoints/
+
+# ✅ VSCode 사용자 설정 (개인별 설정이므로 공유 불필요)
+.vscode/
+
+# ✅ 운영체제별 임시파일
+.DS_Store      # macOS
+Thumbs.db      # Windows
+
+# ✅ 패키지 설치 후 생성되는 항목
+*.egg-info/
+dist/
+build/
+
+# ✅ 테스트/로깅 결과물
+*.log
+*.tmp
+*.bak
+
+# ✅ 가상환경 디렉토리 (만약 프로젝트에 포함되어 있다면)
+venv/
+.env/

app/gpt/handlers/category_router.py

@@ -0,0 +1,25 @@
+# handlers/category_router.py
+
+from app.gpt.handlers.english_tutor import handle_english_tutor
+from app.gpt.handlers.coding_tutor import handle_coding_tutor
+from app.gpt.handlers.exercise_tutor import handle_exercise_tutor
+from app.enum.category import CategoryNameEnum
+
+
+def handle_tutor(user_input: str, category: str) -> str:
+    """
+    category: CategoryNameEnum.name 문자열 ("ENGLISH", "CODING", "EXERCISE")
+    """
+    try:
+        category_enum = CategoryNameEnum[category.upper()]
+    except KeyError:
+        raise ValueError(f"[❌] 잘못된 카테고리 이름: {category}")
+
+    if category_enum == CategoryNameEnum.ENGLISH:
+        return handle_english_tutor(user_input)
+    elif category_enum == CategoryNameEnum.CODING:
+        return handle_coding_tutor(user_input)
+    elif category_enum == CategoryNameEnum.EXERCISE:
+        return handle_exercise_tutor(user_input)
+    else:
+        raise ValueError(f"[❌] 지원하지 않는 category: {category_enum}")

app/gpt/handlers/coding_tutor.py

@@ -0,0 +1,57 @@
+# handlers/coding_tutor.py
+
+import os
+from uuid import uuid4
+from datetime import datetime, timezone
+
+from app.gpt.services.gpt_client import call_gpt
+from app.gpt.services.ai_search import upload_to_index, search_notice
+from app.gpt.utils.prompts_loader import load_combined_prompt, format_prompt
+from app.enum.category import CategoryNameEnum
+
+
+# ✅ 코딩 튜터 전용 핸들러
+def handle_coding_tutor(user_input: str) -> str:
+    category = CategoryNameEnum.CODING
+    index_name = os.getenv("AZURE_SEARCH_INDEX_CODING")
+    question = user_input.strip()
+
+    # 🔹 Notice 기반 RAG 검색 (향후 codingnoticeindex 연동 예정)
+    rag_context = search_notice(query=question, category_enum=category)
+
+    # 🔹 프롬프트 로딩 및 메시지 구성
+    system_prompt, user_template = load_combined_prompt(category)
+    user_message = format_prompt(user_template, rag_context, question)
+
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_message},
+    ]
+
+    # 🔹 GPT 호출
+    result = call_gpt(messages=messages, category=category)
+
+    # 🔹 요약 생성 및 저장
+    summary_prompt = [
+        {
+            "role": "system",
+            "content": "다음 응답을 한 문장으로 요약해 주세요. 반드시 한국어로.",
+        },
+        {"role": "user", "content": result},
+    ]
+    summary = call_gpt(summary_prompt, category)
+
+    upload_to_index(
+        index_name,
+        {
+            "id": f"{category.name}-{str(uuid4())}",
+            "mode": "summary",
+            "category": category.name,
+            "original": question,
+            "summary": summary,
+            "created_at": datetime.now(timezone.utc).isoformat(),
+            "user_choice": "",
+        },
+    )
+
+    return result

app/gpt/handlers/english_tutor.py

@@ -0,0 +1,59 @@
+# handlers/english_tutor.py
+
+import os
+from uuid import uuid4
+from datetime import datetime, timezone
+
+from app.gpt.services.gpt_client import call_gpt
+from app.gpt.services.ai_search import upload_to_index, search_notice
+from app.gpt.utils.prompts_loader import load_combined_prompt, format_prompt
+from app.enum.category import CategoryNameEnum
+
+
+# ✅ 영어 튜터 전용 핸들러
+def handle_english_tutor(user_input: str) -> str:
+    category = CategoryNameEnum.ENGLISH
+    index_name = os.getenv("AZURE_SEARCH_INDEX_ENGLISH")
+
+    # 1. 사용자 입력 수신
+    question = user_input.strip()
+
+    # 2. Notice 인덱스에서 관련 정보 검색 (시험 정보 등)
+    rag_context = search_notice(query=question, category_enum=category)
+    print("🧾 검색 결과 (RAG):", rag_context)
+    # 3. 프롬프트 로딩 및 메시지 생성
+    system_prompt, user_template = load_combined_prompt(category)
+    user_message = format_prompt(user_template, rag_context, question)
+
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_message},
+    ]
+
+    # 4. GPT 응답 생성
+    result = call_gpt(messages=messages, category=category)
+
+    # 5. 응답 요약 후 AI Search 저장
+    summary_prompt = [
+        {
+            "role": "system",
+            "content": "다음 응답을 한 문장으로 요약해 주세요. 반드시 한국어로.",
+        },
+        {"role": "user", "content": result},
+    ]
+    summary = call_gpt(summary_prompt, category=category)
+
+    upload_to_index(
+        index_name,
+        {
+            "id": f"{category.name}-{str(uuid4())}",
+            "mode": "summary",
+            "category": category.name,
+            "original": question,
+            "summary": summary,
+            "created_at": datetime.now(timezone.utc).isoformat(),
+            "user_choice": "",
+        },
+    )
+
+    return result

app/gpt/handlers/exercise_tutor.py

@@ -0,0 +1,57 @@
+# handlers/exercise_tutor.py
+
+import os
+from uuid import uuid4
+from datetime import datetime, timezone
+
+from app.gpt.services.gpt_client import call_gpt
+from app.gpt.services.ai_search import upload_to_index, search_notice
+from app.gpt.utils.prompts_loader import load_combined_prompt, format_prompt
+from app.enum.category import CategoryNameEnum
+
+
+# ✅ 운동 튜터 전용 핸들러
+def handle_exercise_tutor(user_input: str) -> str:
+    category = CategoryNameEnum.EXERCISE
+    index_name = os.getenv("AZURE_SEARCH_INDEX_EXERCISE")
+    question = user_input.strip()
+
+    # 🔹 Notice 기반 RAG 검색 (향후 exercisenoticeindex 연동 예정)
+    rag_context = search_notice(query=question, category_enum=category)
+
+    # 🔹 프롬프트 로딩 및 메시지 구성
+    system_prompt, user_template = load_combined_prompt(category)
+    user_message = format_prompt(user_template, rag_context, question)
+
+    messages = [
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": user_message},
+    ]
+
+    # 🔹 GPT 호출
+    result = call_gpt(messages, category)
+
+    # 🔹 요약 생성 및 저장
+    summary_prompt = [
+        {
+            "role": "system",
+            "content": "다음 응답을 한 문장으로 요약해 주세요. 반드시 한국어로.",
+        },
+        {"role": "user", "content": result},
+    ]
+    summary = call_gpt(summary_prompt, category)
+
+    upload_to_index(
+        index_name,
+        {
+            "id": f"{category.name}-{str(uuid4())}",
+            "mode": "summary",
+            "category": category.name,
+            "original": question,
+            "summary": summary,
+            "created_at": datetime.now(timezone.utc).isoformat(),
+            "user_choice": "",
+        },
+    )
+
+    return result