add annotation for # models and days till crossover

app.py

@@ -15,6 +15,8 @@ from utils import (
     get_constants,
     update_release_date_mapping,
     format_data,
+    get_trendlines,
+    find_crossover_point,
 )
 
 ###################
@@ -145,6 +147,7 @@ def filter_df(min_score, max_models_per_month, set_selector, org_selector):
         .apply(lambda x: x.nlargest(max_models_per_month, "rating"))
         .reset_index(drop=True)
     )
+
     return filtered_df
 
 
@@ -175,6 +178,27 @@ def build_plot(toggle_annotations, filtered_df):
 
     fig.update_traces(marker=dict(size=10, opacity=0.6))
 
+    # calculate days until crossover
+    trend1, trend2 = get_trendlines(fig)
+    crossover = find_crossover_point(
+        b1=trend1[0], m1=trend1[1], b2=trend2[0], m2=trend2[1]
+    )
+    days_til_crossover = (
+        pd.to_datetime(crossover, unit="s") - pd.Timestamp.today()
+    ).days
+
+    # add annotation with number of models and days til crossover
+    fig.add_annotation(
+        xref="paper",
+        yref="paper",  # use paper coordinates
+        x=-0.05,
+        y=1.13,
+        text=f"Number of models: {len(filtered_df)}<br>Days til crossover: {days_til_crossover}",
+        showarrow=False,
+        font=dict(size=14, color="white"),
+        bgcolor="rgba(0,0,0,0.5)",
+    )
+
     if toggle_annotations:
         # get the points to annotate (only the highest rated model per month per license)
         idx_to_annotate = filtered_df.groupby(["Month-Year", "License"])[
@@ -285,7 +309,7 @@ with gr.Blocks(
     filtered_df = gr.State()
     with gr.Group():
         with gr.Tab("Plot"):
-            plot = gr.Plot()
+            plot = gr.Plot(show_label=False)
         with gr.Tab("Raw Data"):
 
             display_df = gr.DataFrame()

utils.py

@@ -4,6 +4,7 @@ from datetime import datetime
 from typing import Literal, List
 
 import pandas as pd
+import plotly.express as px
 from huggingface_hub import HfFileSystem, hf_hub_download
 
 # from: https://github.com/lm-sys/FastChat/blob/main/fastchat/serve/monitor/monitor.py#L389
@@ -174,3 +175,33 @@ def format_data(df):
     df["Month-Year"] = df["Release Date"].dt.to_period("M")
     df["rating"] = df["rating"].round()
     return df.reset_index(drop=True)
+
+
+def get_trendlines(fig):
+
+    trend_lines = px.get_trendline_results(fig)
+
+    return [
+        trend_lines.iloc[i]["px_fit_results"].params.tolist()
+        for i in range(len(trend_lines))
+    ]
+
+
+def find_crossover_point(b1, m1, b2, m2):
+    """
+    Determine the X value at which two trendlines will cross over.
+
+    Parameters:
+    m1 (float): Slope of the first trendline.
+    b1 (float): Intercept of the first trendline.
+    m2 (float): Slope of the second trendline.
+    b2 (float): Intercept of the second trendline.
+
+    Returns:
+    float: The X value where the two trendlines cross.
+    """
+    if m1 == m2:
+        raise ValueError("The trendlines are parallel and do not cross.")
+
+    x_crossover = (b2 - b1) / (m1 - m2)
+    return x_crossover