Deploy CodeMode via Agent

app.py

@@ -332,7 +332,35 @@ def analyze_embeddings_baseline():
             "topic": [m.get("file_name", "unknown") for m in data['metadatas']]
         })
         
-        return metrics, gr.ScatterPlot(value=plot_df, x="x", y="y", color="topic", title="Baseline Semantic Space", tooltip="topic")
+        import matplotlib.pyplot as plt
+        import io
+        from PIL import Image
+        
+        # Create matplotlib figure with proper spacing
+        fig, ax = plt.subplots(figsize=(10, 8))
+        fig.subplots_adjust(top=0.92)  # Add space for title
+        
+        # Plot each file with different color
+        unique_topics = plot_df["topic"].unique()
+        for topic in unique_topics:
+            mask = plot_df["topic"] == topic
+            ax.scatter(plot_df[mask]["x"], plot_df[mask]["y"], label=topic, alpha=0.6, s=50)
+        
+        ax.set_xlabel("PC1")
+        ax.set_ylabel("PC2")
+        ax.set_title("Baseline Semantic Space (PCA)", fontsize=14, pad=20)
+        ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize=8)
+        ax.grid(True, alpha=0.3)
+        plt.tight_layout()
+        
+        # Convert to image for Gradio
+        buf = io.BytesIO()
+        plt.savefig(buf, format='png', dpi=100, bbox_inches='tight')
+        buf.seek(0)
+        img = Image.open(buf)
+        plt.close()
+        
+        return metrics, img
     except Exception as e:
         import traceback
         traceback.print_exc()
@@ -374,7 +402,35 @@ def analyze_embeddings_finetuned():
             "topic": [m.get("file_name", "unknown") for m in data['metadatas']]
         })
         
-        return metrics, gr.ScatterPlot(value=plot_df, x="x", y="y", color="topic", title="Fine-tuned Semantic Space", tooltip="topic")
+        import matplotlib.pyplot as plt
+        import io
+        from PIL import Image
+        
+        # Create matplotlib figure with proper spacing
+        fig, ax = plt.subplots(figsize=(10, 8))
+        fig.subplots_adjust(top=0.92)  # Add space for title
+        
+        # Plot each file with different color
+        unique_topics = plot_df["topic"].unique()
+        for topic in unique_topics:
+            mask = plot_df["topic"] == topic
+            ax.scatter(plot_df[mask]["x"], plot_df[mask]["y"], label=topic, alpha=0.6, s=50)
+        
+        ax.set_xlabel("PC1")
+        ax.set_ylabel("PC2")
+        ax.set_title("Fine-tuned Semantic Space (PCA)", fontsize=14, pad=20)
+        ax.legend(bbox_to_anchor=(1.05, 1), loc='upper left', fontsize=8)
+        ax.grid(True, alpha=0.3)
+        plt.tight_layout()
+        
+        # Convert to image for Gradio
+        buf = io.BytesIO()
+        plt.savefig(buf, format='png', dpi=100, bbox_inches='tight')
+        buf.seek(0)
+        img = Image.open(buf)
+        plt.close()
+        
+        return metrics, img
     except Exception as e:
         import traceback
         traceback.print_exc()
@@ -641,14 +697,14 @@ with gr.Blocks(theme=theme, css=css, title="CodeMode - Baseline vs Fine-tuned")
                     gr.Markdown("#### Baseline Model")
                     analyze_baseline_btn = gr.Button("Analyze Baseline Embeddings", variant="secondary")
                     baseline_metrics = gr.Textbox(label="Baseline Metrics")
-                    baseline_plot = gr.ScatterPlot(label="Baseline Semantic Space (PCA)")
+                    baseline_plot = gr.Image(label="Baseline Semantic Space (PCA)")
                     analyze_baseline_btn.click(analyze_embeddings_baseline, inputs=[], outputs=[baseline_metrics, baseline_plot])
                 
                 with gr.Column():
                     gr.Markdown("#### Fine-tuned Model")
                     analyze_finetuned_btn = gr.Button("Analyze Fine-tuned Embeddings", variant="secondary")
                     finetuned_metrics = gr.Textbox(label="Fine-tuned Metrics")
-                    finetuned_plot = gr.ScatterPlot(label="Fine-tuned Semantic Space (PCA)")
+                    finetuned_plot = gr.Image(label="Fine-tuned Semantic Space (PCA)")
                     analyze_finetuned_btn.click(analyze_embeddings_finetuned, inputs=[], outputs=[finetuned_metrics, finetuned_plot])
             
             gr.Markdown("---")

requirements.txt

@@ -11,3 +11,5 @@ beautifulsoup4>=4.11.0
 huggingface_hub<1.0.0
 tree-sitter>=0.20.0
 tree-sitter-python>=0.20.0
+matplotlib>=3.5.0
+Pillow>=9.0.0