streamlit initial app

app.py

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+import streamlit as st
+import pandas as pd
+import os
+import fnmatch
+import json
+
+class MultiURLData:
+    def __init__(self):
+        self.data = self.process_data()
+
+    def process_data(self):
+        dataframes = []
+
+        def find_files(directory, pattern):
+            for root, dirs, files in os.walk(directory):
+                for basename in files:
+                    if fnmatch.fnmatch(basename, pattern):
+                        filename = os.path.join(root, basename)
+                        yield filename
+
+        for filename in find_files('results', 'results*.json'):
+            model_name = filename.split('/')[2]
+            with open(filename) as f:
+                data = json.load(f)
+                df = pd.DataFrame(data['results']).T
+
+                df = df.rename(columns={'acc': model_name})
+
+                df.index = df.index.str.replace('hendrycksTest-', '')
+
+                df.index = df.index.str.replace('harness\\|', '')
+
+                dataframes.append(df[[model_name]])
+
+        data = pd.concat(dataframes, axis=1)
+
+        data = data.transpose()
+        data['Model Name'] = data.index
+        cols = data.columns.tolist()
+        cols = cols[-1:] + cols[:-1]
+        data = data[cols]
+
+        return data
+
+    def get_data(self, selected_models):
+        filtered_data = self.data[self.data['Model Name'].isin(selected_models)]
+        return filtered_data
+
+data_provider = MultiURLData()
+
+# Create checkboxes for each column
+selected_columns = st.multiselect(
+    'Select Columns',
+    data_provider.data.columns.tolist(),
+    default=data_provider.data.columns.tolist()
+)
+
+selected_models = st.multiselect(
+    'Select Models',
+    data_provider.data['Model Name'].tolist(),
+    default=data_provider.data['Model Name'].tolist()
+)
+
+
+# Get the filtered data and display it in a table
+filtered_data = data_provider.get_data(selected_models)
+st.dataframe(filtered_data)