Select date

app.py

@@ -29,7 +29,7 @@ from utils import (
 
 def restart_space():
     HfApi(token=os.getenv("HF_TOKEN", None)).restart_space(
-        repo_id="andrewrreed/closed-vs-open-arena-elo"
+        repo_id="m-ric/llm-race-to-the-top"
     )
     print(f"Space restarted on {datetime.now()}")
 
@@ -181,9 +181,13 @@ org_info = {
     "Zhipu AI": ("#FFC300", "🇨🇳"),
 }
 
-def make_figure(df):
+def make_figure(original_df, start_time_gradio):
     fig = go.Figure()
 
+    start_date = pd.to_datetime(start_time_gradio, unit='s')
+    original_df["Release Date"] = pd.to_datetime(original_df["Release Date"])
+    df = original_df.copy()
+
     for i, org in enumerate(
         df.groupby("Organization")["rating"]
         .max()
@@ -276,13 +280,15 @@ def make_figure(df):
             legend_title="Ranking as of November 2024",
             title="The race for the best LLM",
         )
+        print("START TIME:", start_time)
+    margin = 30
     fig.update_layout(
         xaxis_title="Date",
         hovermode="closest",
-        xaxis_range=[pd.Timestamp("2024-01-01"), current_date],  # Extend x-axis for labels
-        yaxis_range=[best_models_df["rating"].min() - 10, df["rating"].max() + 30],
+        xaxis_range=[start_date, current_date],  # Extend x-axis for labels
+        yaxis_range=[df.loc[df["Release Date"] >= start_date]["rating"].min() - margin, df["rating"].max() + margin],
     )
-    apply_template(fig, annotation_text="Aymeric Roucher")
+    apply_template(fig, annotation_text="Aymeric Roucher", height=500)
 
     fig.update_xaxes(
         tickformat="%m-%Y",
@@ -290,8 +296,8 @@ def make_figure(df):
     return fig, df
 
 def filter_df(top_n_orgs=11, minimum_rating=1000):
-    top_orgs = ratings_df.groupby("Organization")["rating"].max().nlargest(top_n_orgs).index.tolist()
-    return ratings_df.loc[(ratings_df["Organization"].isin(top_orgs)) & (ratings_df["rating"] > minimum_rating)]
+    top_orgs = ratings_df.groupby("Organization")["rating"].max().nlargest(int(top_n_orgs)).index.tolist()
+    return ratings_df.loc[(ratings_df["Organization"].isin(top_orgs))]
 
 with gr.Blocks(
     theme=gr.themes.Soft(
@@ -310,8 +316,9 @@ with gr.Blocks(
 
     filtered_df = gr.State()
     with gr.Row():
-        top_n_orgs = gr.Slider(minimum=1, maximum=30, value=10, label="View top N companies")
-        minimum_rating = gr.Slider(minimum=800, maximum=1300, value=1000, label="Restrict to ELO scores above N")
+        top_n_orgs = gr.Slider(minimum=1, maximum=30, value=10, step=1, label="View top N companies")
+        # minimum_rating = gr.Slider(minimum=800, maximum=1300, value=1000, step=1, label="Restrict to ELO scores above N")
+        start_time = gr.DateTime(value="2024-01-01 00:00:00")
     with gr.Group():
         with gr.Tab("Plot"):
             plot = gr.Plot(show_label=False)
@@ -333,31 +340,27 @@ with gr.Blocks(
 
     demo.load(
         fn=filter_df,
-        inputs=[top_n_orgs, minimum_rating],
+        inputs=[top_n_orgs],
         outputs=filtered_df,
     ).then(
         fn=make_figure,
-        inputs=[filtered_df],
+        inputs=[filtered_df, start_time],
         outputs=[plot, display_df],
     )
 
-    minimum_rating.change(
-        fn=filter_df,
-        inputs=[top_n_orgs, minimum_rating],
-        outputs=filtered_df,
-    ).then(
-        fn=make_figure,
-        inputs=[filtered_df],
-        outputs=[plot, display_df],
-    )
-
-    top_n_orgs.change(
-        fn=filter_df,
-        inputs=[top_n_orgs, minimum_rating],
-        outputs=filtered_df,
-    ).then(
+    # minimum_rating.change(
+    #     fn=filter_df,
+    #     inputs=[top_n_orgs, minimum_rating],
+    #     outputs=filtered_df,
+    # ).then(
+    #     fn=make_figure,
+    #     inputs=[filtered_df],
+    #     outputs=[plot, display_df],
+    # )
+
+    start_time.change(
         fn=make_figure,
-        inputs=[filtered_df],
+        inputs=[filtered_df, start_time],
         outputs=[plot, display_df],
     )