Clean up comments, update README

app/main.py

@@ -23,7 +23,7 @@ from app.schemas import (
     RegressionOutput,
 )
 
-# ─── Logging ──────────────────────────────────────────────────
+# Logging 
 logging.basicConfig(
     level=logging.INFO,
     format="%(asctime)s | %(levelname)-8s | %(name)s | %(message)s",
@@ -31,7 +31,7 @@ logging.basicConfig(
 logger = logging.getLogger(__name__)
 
 
-# ─── Lifespan (load models once at startup) ───────────────────
+# Lifespan (load models once at startup)
 @asynccontextmanager
 async def lifespan(app: FastAPI):
     logger.info("Starting Immo Predictor API...")
@@ -40,7 +40,7 @@ async def lifespan(app: FastAPI):
     logger.info("Shutting down Immo Predictor API.")
 
 
-# ─── App ──────────────────────────────────────────────────────
+# App ────
 app = FastAPI(
     title="Immo Predictor API",
     description=(
@@ -60,13 +60,13 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# ─── Mount Gradio UI at /ui ──────────────────────────────────
+# Mount Gradio UI at /ui
 from app.ui import demo as gradio_demo
 
 app = gr.mount_gradio_app(app, gradio_demo, path="/ui")
 
 
-# ─── Routes ───────────────────────────────────────────────────
+# Routes
 
 
 @app.get("/", tags=["General"], summary="Redirection vers l'interface")
@@ -113,7 +113,7 @@ def models_info():
     }
 
 
-# ─── Regression ───────────────────────────────────────────────
+# Regression
 
 
 @app.post(
@@ -148,7 +148,7 @@ def regression_predict(
         raise HTTPException(status_code=500, detail=f"Prediction error: {exc}")
 
 
-# ─── Classification ───────────────────────────────────────────
+# Classification 
 
 
 @app.post(

app/predictor.py

@@ -12,11 +12,11 @@ import pandas as pd
 
 logger = logging.getLogger(__name__)
 
-# ─── Paths ────────────────────────────────────────────────────
+# Paths ──
 BASE_DIR = Path(__file__).resolve().parent.parent
 MODEL_PATH = BASE_DIR / "models" / "Mes_models.pkl"
 
-# ─── Global state (loaded once) ──────────────────────────────
+# Global state (loaded once) 
 _store: dict[str, Any] | None = None
 
 
@@ -40,7 +40,7 @@ def get_store() -> dict[str, Any]:
     return _store
 
 
-# ─── Regression ───────────────────────────────────────────────
+# Regression 
 
 # The numerical features expected by the regression pipeline
 _REG_NUM_FEATURES = [
@@ -89,7 +89,7 @@ def predict_regression(data: dict, model_name: str = "random_forest") -> float:
     return float(prediction)
 
 
-# ─── Classification ───────────────────────────────────────────
+# Classification 
 
 _CLF_NUM_FEATURES = [
     "GrLivArea", "TotRmsAbvGrd", "OverallQual", "YearBuilt", "GarageCars",

app/schemas.py

@@ -5,7 +5,7 @@ Pydantic schemas for input validation and output formatting.
 from pydantic import BaseModel, Field
 
 
-# ─── Regression ───────────────────────────────────────────────
+# Regression 
 
 class RegressionInput(BaseModel):
     """Input features for house price prediction (regression)."""
@@ -59,7 +59,7 @@ class RegressionOutput(BaseModel):
     currency: str = Field(default="USD", description="Currency of the predicted price")
 
 
-# ─── Classification ───────────────────────────────────────────
+# Classification 
 
 class ClassificationInput(BaseModel):
     """Input features for building type classification."""

app/ui.py

@@ -18,8 +18,7 @@ logger = logging.getLogger(__name__)
 # Ensure models are loaded
 load_models()
 
-# ─── Neighborhood & HouseStyle lists ─────────────────────────
-
+# Neighborhood & HouseStyle lists 
 NEIGHBORHOODS = [
     "Blmngtn", "Blueste", "BrDale", "BrkSide", "ClearCr",
     "CollgCr", "Crawfor", "Edwards", "Gilbert", "IDOTRR",
@@ -33,7 +32,7 @@ HOUSE_STYLES = [
     "2.5Unf", "SFoyer", "SLvl",
 ]
 
-# ─── Chart helpers ────────────────────────────────────────────
+# Chart helpers ─
 
 def create_regression_comparison_chart(data: dict) -> plt.Figure:
     """Compare predictions from both regression models."""
@@ -132,7 +131,7 @@ def create_classification_comparison_chart(data: dict) -> plt.Figure:
     return fig
 
 
-# ─── Regression Prediction ────────────────────────────────────
+# Regression Prediction
 
 def regression_ui(
     GrLivArea, TotalBsmtSF, LotArea, BedroomAbvGr, FullBath,
@@ -168,8 +167,7 @@ def regression_ui(
         return f"Erreur : {str(e)}", None, None
 
 
-# ─── Classification Prediction ────────────────────────────────
-
+# Classification Prediction 
 def classification_ui(
     GrLivArea, TotRmsAbvGrd, OverallQual, YearBuilt,
     GarageCars, Neighborhood, HouseStyle, model_name
@@ -195,8 +193,7 @@ def classification_ui(
         return f"Erreur : {str(e)}", None, None
 
 
-# ─── Build Gradio Interface ──────────────────────────────────
-
+# Build Gradio Interface 
 CUSTOM_CSS = """
 .gradio-container > footer {
     position: fixed !important;