Update app.py

app.py

@@ -10,7 +10,7 @@ import base64
 import zipfile
 from PIL import Image
 from io import BytesIO
-
+import tempfile
 
 # Input data with links to Hugging Face repositories
 data_full = [
@@ -67,8 +67,10 @@ def plot_average_scores():
     plt.close()
 
     pil_image = Image.open(BytesIO(base64.b64decode(img_base64)))
-    return pil_image, "average_performance.png"
 
+    temp_image_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+    pil_image.save(temp_image_file.name)
+    return pil_image, temp_image_file.name
 
 def plot_task_performance():
     df_full_melted = df_full.melt(id_vars=["Model Configuration", "Model Link"], var_name="Task", value_name="Score")
@@ -91,8 +93,11 @@ def plot_task_performance():
     img_buffer.seek(0)
     img_base64 = base64.b64encode(img_buffer.read()).decode('utf-8')
     plt.close()
+
     pil_image = Image.open(BytesIO(base64.b64decode(img_base64)))
-    return pil_image, "task_performance.png"
+    temp_image_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+    pil_image.save(temp_image_file.name)
+    return pil_image, temp_image_file.name
 
 def plot_task_specific_top_models():
     top_models = df_full.iloc[:, 2:].idxmax()
@@ -114,7 +119,9 @@ def plot_task_specific_top_models():
     img_base64 = base64.b64encode(img_buffer.read()).decode('utf-8')
     plt.close()
     pil_image = Image.open(BytesIO(base64.b64decode(img_base64)))
-    return pil_image, "task_specific_top_models.png"
+    temp_image_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+    pil_image.save(temp_image_file.name)
+    return pil_image, temp_image_file.name
 
 def scrape_mergekit_config(model_name):
     """
@@ -143,8 +150,9 @@ def plot_heatmap():
     img_base64 = base64.b64encode(img_buffer.read()).decode('utf-8')
     plt.close()
     pil_image = Image.open(BytesIO(base64.b64decode(img_base64)))
-    return pil_image, "performance_heatmap.png"
-
+    temp_image_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
+    pil_image.save(temp_image_file.name)
+    return pil_image, temp_image_file.name
 
 def download_yaml(yaml_content, model_name):
     """
@@ -185,7 +193,6 @@ def download_all_data():
             image_bytes.seek(0)
             zf.writestr(filename, image_bytes.read())
 
-
         for model_name in df_full["Model Configuration"].to_list():
             yaml_content = scrape_mergekit_config(model_name)
             if "No YAML configuration found" not in yaml_content and "Failed to fetch model page" not in yaml_content: