Oracle

app.py

@@ -10,13 +10,11 @@ from PIL import Image
 import logging
 
 # Import the functions from deepfundingoracle
-from Oracle.deepfundingoracle import prepare_dataset, train_predict_weight, create_submission_csv, \
-    normalize_and_clip_weights
+from Oracle.deepfundingoracle import prepare_dataset, train_predict_weight, create_submission_csv, normalize_and_clip_weights
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)
 
-
 def analyze_file(file, progress=gr.Progress(track_tqdm=True)):
     """
     Analyzes the uploaded file and generates results.
@@ -47,8 +45,7 @@ def analyze_file(file, progress=gr.Progress(track_tqdm=True)):
         # Feature distribution plot
         dist_fig = plt.figure(figsize=(15, 10))
         numeric_cols = df.select_dtypes(include=[np.number]).columns
-        plot_cols = [col for col in numeric_cols if
-                     col in ['stars', 'forks', 'watchers', 'contributors', 'pulls', 'final_weight']]
+        plot_cols = [col for col in numeric_cols if col in ['stars', 'forks', 'watchers', 'contributors', 'pulls', 'final_weight']]
 
         if plot_cols:
             df[plot_cols].hist(bins=20, figsize=(15, 10), color="skyblue", edgecolor="black")
@@ -82,10 +79,9 @@ def analyze_file(file, progress=gr.Progress(track_tqdm=True)):
         summary_df = df[['repo', 'parent', 'final_weight']].head(10)
         preview = f"Top 10 Results:\n{summary_df.to_string(index=False)}\n\nTotal repositories analyzed: {len(df)}"
 
-        # Return the path to the generated file for automatic download
         return (
             preview,
-            output_filename,  # This will trigger automatic download
+            output_filename,
             dist_img,
             corr_img,
             f"✅ Analysis completed successfully in {elapsed:.2f} seconds.\n📥 Results file ready for download!"
@@ -100,7 +96,6 @@ def analyze_file(file, progress=gr.Progress(track_tqdm=True)):
         empty_img = Image.new('RGB', (800, 600), color='white')
         return error_msg, None, empty_img, empty_img, error_msg
 
-
 # Custom CSS for better styling
 custom_css = """
     .download-button {
@@ -115,7 +110,7 @@ custom_css = """
     }
 """
 
-# Create Gradio interface with automatic download
+# Create Gradio interface
 with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as iface:
     gr.Markdown("""
     # 🚀 DeepFunding Oracle
@@ -166,37 +161,11 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css) as iface:
         with gr.Column():
             corr_plot = gr.Image(label="Feature Correlation Matrix")
 
-    # JavaScript for automatic download
-    download_js = """
-    () => {
-        setTimeout(() => {
-            const downloadButton = document.querySelector('.download-button a');
-            if (downloadButton) {
-                downloadButton.click();
-            }
-        }, 500);
-    }
-    """
-
-    # Set up the event handler
+    # Set up the event handler (without _js parameter)
     analyze_btn.click(
         fn=analyze_file,
         inputs=[file_input],
         outputs=[preview_output, download_output, dist_plot, corr_plot, status_output]
-    ).then(
-        fn=None,
-        inputs=None,
-        outputs=None,
-        _js=download_js  # This triggers automatic download
-    )
-
-    # Add example usage
-    gr.Examples(
-        examples=[["example_dependencies.csv"]],  # Add your example file here if you have one
-        inputs=file_input,
-        outputs=[preview_output, download_output, dist_plot, corr_plot, status_output],
-        fn=analyze_file,
-        cache_examples=False,
     )
 
 if __name__ == "__main__":