Update app.py

app.py

@@ -8,6 +8,9 @@ from functools import cache
 from io import StringIO
 from yall import create_yall
 import plotly.graph_objs as go
+from huggingface_hub import ModelCard
+
+
 
 def calculate_pages(df, items_per_page):
     return -(-len(df) // items_per_page)  # Equivalent to math.ceil(len(df) / items_per_page)
@@ -145,6 +148,35 @@ def create_bar_chart(df, category):
     # Adjust the height of the chart based on the number of rows in the DataFrame
     st.plotly_chart(fig, use_container_width=True, height=len(df) * 35)
 
+def fetch_merge_configs(df):
+    # Sort the DataFrame
+    df_sorted = df.sort_values(by='Average', ascending=False).head(20)
+    configurations = []
+    matches = []
+
+    # Get model cards for the top 20 entries
+    for index, row in df_sorted.iterrows():
+        model_name = row['Model'].rstrip()
+        try:
+            card = ModelCard.load(model_name)
+            configurations.append({
+                "Model Name": model_name,
+                "Scores": row["Average"],
+                "AGIEval": row["AGIEval"],
+                "GPT4All": row["GPT4All"],
+                "TruthfulQA": row["TruthfulQA"],
+                "Bigbench": row["Bigbench"],
+                "Model Card": str(card)
+                })
+            match = re.findall(r'yaml(.*?)```', str(card), re.DOTALL)
+            if match:
+                matches.append(match[0])
+        except Exception as e:
+            print(f"Failed to load model card for {model_name}. Error: {e}")
+
+                    # Assuming you will display the configurations in some way in your app
+    return configurations, matchescsv_data = df.to_csv(index=False)    
+
 # Main function to run the Streamlit app
 def main():
     # Set page configuration and title
@@ -235,7 +267,7 @@ def main():
                 # Add a button to export data to CSV
                 if st.button("Export to CSV"):
                     # Export the DataFrame to CSV
-                    csv_data = full_df.to_csv(index=False)
+                    csv_data = df.to_csv(index=False)
 
                     # Create a link to download the CSV file
                     st.download_button(
@@ -245,7 +277,23 @@ def main():
                         key="download-csv",
                         help="Click to download the CSV file",
                     )
+                if st.button("Fetch Merge-Configs"):
+                    # Call the function with the current DataFrame
+                    configurations, matches = fetch_merge_configs(full_df)  # Assuming full_df is your DataFrame
+
+                    # You can then display the configurations or matches as needed, or write them to a file
+                    # For example, displaying the configurations:
+                    for config in configurations:
+                        st.text(f"Model Name: {config['Model Name']}\nScores: {config['Scores']}\nAGIEval: {config['AGIEval']}\nGPT4All: {config['GPT4All']}\nTruthfulQA: {config['TruthfulQA']}\nBigbench: {config['Bigbench']}\nModel Card: {config['Model Card']}\n\n")
+                    st.download_button(
+                        label="Download Configurations",
+                        data=configurations,
+                        file_name="configurations.csv",
+                        key="download-csv",
+                        help="Click to download the CSV file",
+                    )
 
+                
                 # Full-width plot for the first category
                 create_bar_chart(df, score_columns[0])