improved reasoning

app.py

@@ -51,7 +51,7 @@ with gr.Blocks(title="AI Size Recommendation Engine") as demo:
             waist = gr.Number(label="Waist (inches)", value=32.0, step=0.5)
             bicep = gr.Number(label="Bicep (inches)", value=13.0, step=0.5)
             shoulder = gr.Number(label="Shoulder (inches)", value=46.0, step=0.5)
-            fit = gr.Dropdown(choices=["tight", "regular", "loose"], label="Fit Preference", value="regular")
+            fit = gr.Dropdown(choices=["Slim", "Regular", "Loose"], label="Fit Preference", value="Regular")
             submit_btn = gr.Button("Predict Size", variant="primary")
             
         with gr.Column():

size_rules.py

@@ -47,7 +47,7 @@ def evaluate_size(measurements):
 def apply_fit_preference(base_size, preference, measurements=None):
     """
     Applies fit preference to the base size.
-    For 'regular', requires measurements to re-evaluate.
+    For 'Regular', requires measurements to re-evaluate.
     Returns: (final_size, reason)
     """
     sizes = ["XS", "S", "M", "L", "XL"]
@@ -57,16 +57,16 @@ def apply_fit_preference(base_size, preference, measurements=None):
 
     idx = sizes.index(base_size)
     
-    if preference == "tight":
-        return base_size, "Fit: Tight (Kept base size)"
+    if preference == "Slim":
+        return base_size, "Fit: Slim (Kept base size)"
         
-    if preference == "loose":
+    if preference == "Loose":
         if idx < len(sizes) - 1:
             return sizes[idx + 1], "Fit: Loose (Moved up one size)"
         else:
             return base_size, "Fit: Loose (Already at max size)"
             
-    if preference == "regular":
+    if preference == "Regular":
         if measurements is None:
             return base_size, "Fit: Regular (No measurements provided for adjustment)"