Update app.py

app.py

@@ -77,7 +77,7 @@ def predict_linear(strain, dose, soil_n, soil_p, soil_k, ph,
     }
     result_df = pd.DataFrame(data)
 
-    return result_df, "✅ Prediction complete!", "\n".join(logs)
+    return result_df, "Prediction complete!", "\n".join(logs)
 
 # -----------------------------
 # 4️⃣ Gradio Interface (Green Theme)
@@ -96,12 +96,12 @@ with gr.Blocks(
         neutral_hue="green"
     )
 ) as demo:
-    gr.Markdown("<h1 style='text-align:center; color:#2E8B57;'>🌿 Linear Regression — Plant Yield Predictor 🌿</h1>")
+    gr.Markdown("<h1 style='text-align:center; color:#2E8B57;'>Linear Regression, Plant Yield Predictor</h1>")
 
     strain_names = ["Tetradesmus nigardi", "Clostroprosis acicularis"]
     with gr.Row():
         with gr.Column(scale=1):
-            gr.Markdown("### 🌱 Plant & Strain")
+            gr.Markdown("### Plant & Strain")
             strain_input = gr.Dropdown(
                 strain_names,
                 label="Select Strain",
@@ -109,14 +109,14 @@ with gr.Blocks(
             )
             row_selector = gr.Dropdown(row_options, label="Select Row", value="None, Enter Manually")
 
-            gr.Markdown("### 🌾 Input Parameters")
+            gr.Markdown("### Input Parameters")
             dose = gr.Number(label="Dose (g/pot)")
             soil_n = gr.Number(label="Soil N (ppm)")
             soil_p = gr.Number(label="Soil P (ppm)")
             soil_k = gr.Number(label="Soil K (ppm)")
             ph = gr.Number(label="pH")
 
-            gr.Markdown("### 📊 Autofilled Actual Metrics (from Excel)")
+            gr.Markdown("### Autofilled Actual Metrics (from Excel)")
             chlorophyll = gr.Number(label="Chlorophyll (SPAD)")
             shoot_len = gr.Number(label="Shoot Length (cm)")
             root_len = gr.Number(label="Root Length (cm)")
@@ -124,10 +124,10 @@ with gr.Blocks(
             root_wt = gr.Number(label="Root Wt (g)")
             yield_gp = gr.Number(label="Yield (g/pot)")
 
-            predict_btn = gr.Button("🌿 Predict", variant="primary")
+            predict_btn = gr.Button("Predict", variant="primary")
 
         with gr.Column(scale=1):
-            gr.Markdown("### 🌼 Prediction Results Table")
+            gr.Markdown("### Prediction Results Table")
             result_table = gr.DataFrame(
                 headers=["Output Metric", "Actual Value", "Predicted Value", "Absolute Error"],
                 label="Results Comparison",