uP

app.py

@@ -3,14 +3,17 @@ from huggingface_hub import HfApi, hf_hub_download
 from huggingface_hub.repocard import metadata_load
 
 import pandas as pd
-import gradio as gr
+import streamlit as st
 
 METRICS_TO_NOT_DISPLAY = set(["ser"])
 NO_LANGUAGE_MODELS = []
 
-api = HfApi()
-models = api.list_models(filter="robust-speech-event")
-model_ids = [x.modelId for x in models]
+
+def get_model_ids():
+    api = HfApi()
+    models = api.list_models(filter="robust-speech-event")
+    model_ids = [x.modelId for x in models]
+    return model_ids
 
 
 def get_metadatas(model_ids):
@@ -114,58 +117,46 @@ def retrieve_dataframes(
             data = all_datasets_results[dataset][metric]
             data_frame = pd.DataFrame.from_dict(data, orient="index")
             data_frame.fillna("", inplace=True)
-            data_frame = data_frame.sort_index().transpose()
+            data_frame = data_frame.sort_index()
             pandas_datasets[dataset][metric] = data_frame
     return pandas_datasets
 
 
-# 1. Retrieve metadatas
-metadatas = get_metadatas(model_ids)
+@st.cache(persist=True)
+def main():
+    # 0. Get model ids
+    model_ids = get_model_ids()
 
-# 2. Parse to results
-all_model_results, model_language_map = get_model_results_and_language_map(metadatas)
+    # 1. Retrieve metadatas
+    metadatas = get_metadatas(model_ids)
 
-# 3. Get datasets and langs
-all_datasets, all_langs, all_metrics = get_datasets_metrics_langs(
-    all_model_results, model_language_map
-)
+    # 2. Parse to results
+    all_model_results, model_language_map = get_model_results_and_language_map(metadatas)
+
+    # 3. Get datasets and langs
+    all_datasets, all_langs, all_metrics = get_datasets_metrics_langs(
+        all_model_results, model_language_map
+    )
+
+    # 4. Get dataframes
+    all_dataframes = retrieve_dataframes(
+        all_model_results, model_language_map, all_datasets, all_langs, all_metrics
+    )
+
+    return all_dataframes, all_datasets, all_metrics
 
-# 4. Get dataframes
-all_dataframes = retrieve_dataframes(
-    all_model_results, model_language_map, all_datasets, all_langs, all_metrics
-)
 
+all_dataframes, all_datasets, all_metrics = main()
+
+
+dataset = st.selectbox(
+     'Dataset',
+     tuple(all_datasets),
+)
 
-def select(dataset, metric):
-    return all_dataframes[dataset][metric]
-
-
-iface = gr.Interface(
-    select,
-    [
-        gr.inputs.Dropdown(
-            list(all_datasets),
-            type="value",
-            default="mozilla-foundation/common_voice_7_0",
-            label="dataset",
-        ),
-        gr.inputs.Dropdown(
-            list(all_metrics), type="value", default="wer", label="metric"
-        ),
-    ],
-    gr.outputs.Dataframe(
-        headers=None,
-        max_rows=3,
-        max_cols=10,
-        overflow_row_behaviour="paginate",
-        type="pandas",
-        label=None,
-    ),
-    examples=[
-        ["mozilla-foundation/common_voice_7_0", "wer"],
-    ],
-    allow_flagging=False,
-    allow_screenshot=False,
+metric = st.selectbox(
+     'Metric',
+     tuple(all_metrics),
 )
 
-iface.launch()
+st.dataframe(all_dataframes[dataset][metric])