Update app.py

app.py

@@ -1,89 +1,38 @@
-from datasets import load_dataset
-from huggingface_hub import ModelCard
-from huggingface_hub import HfApi
-
 import gradio as gr
+import altair as alt
+from datasets import load_dataset
 import pandas as pd
 
-api = HfApi()
-
-repo_id = "librarian-bots/model_cards_with_metadata"
-
-dataset = load_dataset(repo_id, split='train')
-dataset = dataset.filter(lambda x: x['library_name']=='transformers')
-
-list_commits = api.list_repo_commits(repo_id, repo_type="dataset")
-commits_date_dict = {commit.created_at.strftime("%m/%d/%Y"):commit.commit_id for commit in list_commits}
-current_date = "latest"
-
-def get_data(commit_date="latest"):
-    ds_kwargs = {}
-    if commit_date != "latest":
-        current_date = commit_date
-        commit_id = commits_date_dict[commit_date]
-        ds_kwargs = {"revision": commit_id}
-
-    dataset = load_dataset(repo_id, split='train', **ds_kwargs)
-    dataset = dataset.filter(lambda x: x['library_name']=='transformers')
-
-    def pipeline_tag_not_in_card(card):
-        try:
-            model_card_data = ModelCard(card).data
-            if model_card_data.library_name is None:
-                return True
-            return False
-        except AttributeError:
-            return False
-        except Exception:
-            return False
-
-    ds = dataset.map(lambda x: {"missing_library_name": pipeline_tag_not_in_card(x['card'])}, num_proc=4)
-
-
-    data = pd.DataFrame(
-        {
-            "name": ["Total Number of transformers Model", "Total number of models with missing 'library_name: transformers' in model card."],
-            "count": [len(ds), sum(ds["missing_library_name"])],
-        }
-    )
-    return data
-
-def fetch_fn(commit_date="latest"):
-    data = get_data(commit_date=commit_date)
-    return gr.BarPlot(
-        data,
-        x="name",
-        y="count",
-        title="Count of Model cards with the correct library_name tag",
-        height=256,
-        width=1024,
-        tooltip=["name", "count"],
-        vertical=False
-    )
-
-data = get_data()
-
-with gr.Blocks() as bar_plot:
-    with gr.Column():
-        with gr.Row():
-            plot = gr.BarPlot(
-                data,
-                x="name",
-                y="count",
-                title=f"Count of Model cards with the correct library_name tag at the date {current_date}",
-                height=256,
-                width=1024,
-                tooltip=["name", "count"],
-                vertical=False
-            )
-        with gr.Column():
-            display = gr.Dropdown(
-                choices=list(commits_date_dict.keys()),
-                value="latest",
-                label="Type of Bar Plot",
-                
-            )
-        
-        display.change(fetch_fn, inputs=display, outputs=plot)
-
-bar_plot.launch()
+model_id = "ybelkada/model_cards_correct_tag"
+dataset = load_dataset(model_id, split="train").to_pandas()
+
+# Convert dataset to a pandas DataFrame and sort by commit_dates
+df = pd.DataFrame(dataset)
+df["commit_dates"] = pd.to_datetime(df["commit_dates"])  # Convert commit_dates to datetime format
+df = df.sort_values(by="commit_dates")
+
+def plot_fn():
+    line_chart = alt.Chart(df).mark_line().encode(
+        x=alt.X('commit_dates:T', axis=alt.Axis(title='Date')),
+        y=alt.Y('total_transformers_model:Q', axis=alt.Axis(title='Count'), scale=alt.Scale(zero=False)),
+        color=alt.value('blue'),
+        tooltip=['commit_dates:T', 'total_transformers_model:Q'],
+    ).properties(width=600, height=400)
+
+    line_chart_missing_library = alt.Chart(df).mark_line().encode(
+        x=alt.X('commit_dates:T', axis=alt.Axis(title='Date')),
+        y=alt.Y('missing_library_name:Q', axis=alt.Axis(title='Count'), scale=alt.Scale(zero=False)),
+        color=alt.value('orange'),
+        tooltip=['commit_dates:T', 'missing_library_name:Q'],
+    ).properties(width=600, height=400)
+    
+    chart = (line_chart + line_chart_missing_library).properties(width=600, height=400)
+
+    return chart
+
+with gr.Blocks() as demo:
+    plot = gr.Plot(label="Plot")
+    demo.load(plot_fn, inputs=[], outputs=[plot])
+
+if __name__ == "__main__":
+    demo.launch()