newe

app.py

@@ -1,14 +1,21 @@
 import gradio as gr
+import pandas as pd
 import numpy as np
 from sklearn.linear_model import LinearRegression
 import matplotlib.pyplot as plt
 import io
 from PIL import Image
 
-def linear_regression(x_values, y_values):
-    # Convert string inputs to numpy arrays
-    X = np.array([float(x) for x in x_values.split(',')]).reshape(-1, 1)
-    y = np.array([float(y) for y in y_values.split(',')])
+def linear_regression(input_csv):
+    # Load dataset from binary
+    df = pd.read_csv(io.BytesIO(input_csv))
+
+    # Assume the first column is X and the second column is Y
+    if len(df.columns) < 2:
+        return None, "CSV file must contain at least two columns."
+
+    X = df.iloc[:, 0].values.reshape(-1, 1)
+    y = df.iloc[:, 1].values
 
     # Perform linear regression
     model = LinearRegression()
@@ -21,8 +28,8 @@ def linear_regression(x_values, y_values):
     plt.figure(figsize=(10, 6))
     plt.scatter(X, y, color='blue')
     plt.plot(X, y_pred, color='red')
-    plt.xlabel("X Values")
-    plt.ylabel("Y Values")
+    plt.xlabel(df.columns[0])
+    plt.ylabel(df.columns[1])
     plt.title('Linear Regression')
 
     # Save plot to a buffer and convert to PIL Image
@@ -36,20 +43,29 @@ def linear_regression(x_values, y_values):
 
     return image, coef_info
 
+# Tutorial Markdown
+tutorial_markdown = """
+## Tutorial
+
+Follow these steps to use the application:
+
+1. Prepare a CSV file with two columns. The first column should be your independent variable (X), and the second column your dependent variable (Y).
+2. Upload the CSV file using the 'File Upload' field.
+3. The application will automatically process the file, perform linear regression, and display the results and a plot.
+"""
+
 # Gradio interface
 iface = gr.Interface(
     fn=linear_regression,
-    inputs=[
-        gr.components.Textbox(placeholder="Enter X values separated by commas (e.g., 1,2,3)", label="X Values"),
-        gr.components.Textbox(placeholder="Enter Y values separated by commas (e.g., 2,4,6)", label="Y Values")
-    ],
+    inputs=[gr.components.File(type="binary")],
     outputs=[
         gr.components.Image(type="pil"),
         gr.components.Textbox(label="Regression Info")
     ],
     title="Automatic Linear Regression Modeling",
-    description="Enter X and Y values as comma-separated lists to perform linear regression."
-)
+    description="Upload a CSV file with two columns. The first column will be used as X (independent variable) and the second as Y (dependent variable).",
+    layout="vertical"
+).add_instructions(tutorial_markdown)
 
 # Launch the app
 if __name__ == "__main__":