change

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+import pandas as pd
+import joblib
+import requests
+import os
+
+MODEL_URL = "https://huggingface.co/munnabhaimbbsfail/linear_regression_model/resolve/main/model.pkl"
+MODEL_PATH = "model.pkl"
+
+# Download the model if not already present
+if not os.path.exists(MODEL_PATH):
+    response = requests.get(MODEL_URL)
+    with open(MODEL_PATH, "wb") as f:
+        f.write(response.content)
+
+# Load model
+model = joblib.load(MODEL_PATH)
+
+# Define prediction function
+def predict(x_values: str):
+    try:
+        x_list = [float(x.strip()) for x in x_values.split(",")]
+        df = pd.DataFrame({"x": x_list})
+        preds = model.predict(df)
+        return {"predictions": preds.tolist()}
+    except Exception as e:
+        return {"error": str(e)}
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(label="Enter x values (comma-separated)", placeholder="e.g., 5, 10, 15"),
+    outputs="json",
+    title="Linear Regression Predictor 2",
+    description="Enter a list of x values to get predictions from the trained model."
+)
+
+iface.launch()
+

requirements.txt

@@ -0,0 +1,6 @@
+gradio
+pandas
+joblib
+scikit-learn
+requests
+