feat : AI 기능 추가 (#31)

* fix :  deploy.yml 수정

* feat : AI 기능 추가

Author: minhyuk2

.github/workflows/deploy.yml

@@ -46,5 +46,6 @@ jobs:
           key: ${{ secrets.EC2_KEY }}
           script: |
             cd ~/my-app
+            echo "${{ secrets.ENV_FILE }}" > .env
             docker compose pull ai-server
             docker compose up -d ai-server

.gitignore

@@ -0,0 +1,116 @@
+app/.env
+
+# --- allow GitHub Actions workflows ---
+!.github/
+!.github/workflows/
+!.github/workflows/*.yml
+!.github/workflows/*.yaml
+
+
+# ---- Python ----
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+*.so
+*.egg
+*.egg-info/
+.eggs/
+*.manifest
+*.spec
+
+# ---- Virtual Environment ----
+app/.env
+.venv/
+venv/
+ENV/
+env/
+Pipfile.lock
+poetry.lock
+
+# ---- FastAPI / Uvicorn ----
+*.log
+*.db
+*.sqlite3
+server.log
+
+# ---- Config / Secrets ----
+*.ini
+*.toml
+.env.local
+.env.*.local
+.envrc
+/secrets/
+
+# ---- VSCode / PyCharm ----
+.vscode/
+.idea/
+*.iml
+
+# ---- OS Files ----
+.DS_Store
+Thumbs.db
+
+# ---- Tests / Coverage ----
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+pytest_cache/
+.pytest_cache/
+.pytest_results/
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+
+# ---- Test Files (프로젝트 특정) ----
+test_*.py
+*_test.py
+
+# ---- Build / Dist ----
+build/
+dist/
+wheels/
+*.egg-info/
+*.egg
+.installed.cfg
+*.egg-info/
+
+# ---- Notebooks ----
+.ipynb_checkpoints
+*.ipynb
+
+# ---- Misc ----
+.mypy_cache/
+.pyre/
+.dmypy.json
+dmypy.json
+
+# Logs
+logs
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+dev-debug.log
+
+# Dependency directories
+node_modules/
+
+# Environment variables
+# Editor directories and files
+.idea
+.vscode
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
+
+# OS specific
+
+# Task files
+# tasks.json
+# tasks/

.idea/Jugger-AI.iml

@@ -1,10 +1,17 @@
 from fastapi import FastAPI
 from app.routes import skt_classify
+from app.routes import gemini
+from pathlib import Path
+from dotenv import load_dotenv
 
-app = FastAPI(title="SKT KoBERT Text Classification API with URL Extraction")
+BASE_DIR = Path(__file__).resolve().parent
+load_dotenv(BASE_DIR / ".env")
+
+app = FastAPI(title="문장 분석 기능입니다.")
 
 # API 라우터 등록
-app.include_router(skt_classify.router, prefix="/api", tags=["SKT KoBERT Classification"])
+app.include_router(skt_classify.router, prefix="/ai", tags=["SKT KoBERT Classification"])
+app.include_router(gemini.router, prefix="/ai", tags=["GEMINI Classification"])
 
 @app.get("/")
 def root():

.idea/misc.xml

@@ -0,0 +1,45 @@
+from typing import List, Optional
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel, Field, field_validator
+
+from app.services.gemini_category import classify_paragraph_gemini
+
+router = APIRouter()
+
+class GeminiRequest(BaseModel):
+    paragraph: str = Field(..., description="분류 대상 문단")
+    userCategories: Optional[List[str]] = Field(default=None, description="카테고리 후보(선택)")
+    threshold: float = Field(default=0.5, ge=0.0, le=1.0, description="카테고리 매칭 임계값(0~1)")
+    k: int = Field(default=5, ge=1, le=10, description="추천 개수")
+
+    @field_validator("userCategories")
+    @classmethod
+    def _strip_empty(cls, v):
+        if v:
+            v = [s.strip() for s in v if isinstance(s, str) and s.strip()]
+            if not v:
+                return None
+        return v
+
+class SentenceOut(BaseModel):
+    text: str
+    urls: Optional[List[str]] = None
+    invalid_urls: Optional[List[str]] = None
+    schedules: Optional[List[dict]] = None
+
+class GeminiResponse(BaseModel):
+    category: str
+    recommend_category: List[str]
+    sentences: List[SentenceOut]
+
+@router.post("/gemini", response_model=GeminiResponse)
+async def gemini_endpoint(req: GeminiRequest):
+    try:
+        return await classify_paragraph_gemini(
+            paragraph=req.paragraph,
+            user_categories=req.userCategories,
+            threshold=req.threshold,
+            k=req.k
+        )
+    except Exception as e:
+        raise HTTPException(status_code=502, detail=f"Gemini 호출 실패: {e}")

app/main.py

@@ -1,14 +1,33 @@
+from typing import List, Optional
 from fastapi import APIRouter
-from pydantic import BaseModel
-from app.services.skt_text_processing import classify_paragraph_with_user
+from pydantic import BaseModel, Field, validator
+
+from app.services.skt_text_processing import classify_paragraph
 
 router = APIRouter()
 
 class ParagraphRequest(BaseModel):
-    user_uuid: str
-    paragraph: str
+    paragraph: str = Field(..., description="분류할 전체 문단 텍스트")
+    userCategories: Optional[List[str]] = Field(
+        default=None, description="스프링에서 내려주는 카테고리명 리스트"
+    )
+    threshold: Optional[float] = Field(
+        default=0.5, ge=0.0, le=1.0, description="카테고리 매칭 임계값(0~1)"
+    )
+
+    @validator("userCategories")
+    def _strip_empty(cls, v):
+        if v:
+            v = [s.strip() for s in v if isinstance(s, str) and s.strip()]
+            if len(v) == 0:
+                return None
+        return v
 
-@router.post("/ai/classify")
+@router.post("/classify")
 async def classify_paragraph_api(request: ParagraphRequest):
-    result = await classify_paragraph_with_user(request.user_uuid, request.paragraph)
+    result = await classify_paragraph(
+        paragraph=request.paragraph,
+        user_categories=request.userCategories,
+        threshold=request.threshold or 0.5
+    )
     return result