Delete app.py

app.py

@@ -1,40 +0,0 @@
-# -*- coding: utf-8 -*-
-"""app.py
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1LNqeNTVe-zMc4YfmFi5S5fPJJcv572lx
-"""
-
-import gradio as gr
-import pickle
-import numpy as np
-
-# Load the trained model
-with open("stock_model.pkl", "rb") as file:
-    model = pickle.load(file)
-
-# Define the prediction function
-def predict_stock_price(features):
-    try:
-        # Convert input string to a NumPy array
-        features_array = np.array([float(x) for x in features.split(",")]).reshape(1, -1)
-        # Predict using the model
-        prediction = model.predict(features_array)
-        return f"Predicted Stock Price: {prediction[0]}"
-    except Exception as e:
-        return f"Error: {e}"
-
-# Create a Gradio Interface
-interface = gr.Interface(
-    fn=predict_stock_price,  # Function to call
-    inputs=gr.Textbox(label="Input Features (comma-separated)", placeholder="1.5, 2.3, 0.7, 5.4"),
-    outputs=gr.Textbox(label="Prediction"),
-    title="Stock Price Predictor",
-    description="Enter features as a comma-separated list to predict stock prices."
-)
-
-# Launch the Gradio app
-if __name__ == "__main__":
-    interface.launch()