Default to the newest backbone and show when it was pushed

The startup model was repos[0] of an alphabetically sorted list, so the
default never moved off breakdown-risk-granite-* however recently another
backbone had trained. model_repos now returns {repo: last_modified}, keyed
alphabetically so the dropdown stays scannable, and the initial value is
max() over the timestamps. Revision default is unchanged, so the pair is
"newest backbone @ its tip".

A line under the pickers names that date and follows the selection, which
makes the default legible -- and exposes the caveat that last_modified is
repo-level, so a README push moves the default too.

list_models sort is what makes the Hub populate last_modified at all, but
newest() uses max() rather than trusting the response order, since hub 1.x
dropped the direction argument. That API is also why the floor moves to
huggingface-hub>=1: on 0.x the key was "lastModified" and descending order
needed direction=-1. Resolved versions are untouched, hub stays at 1.25.1.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

README.md

@@ -56,6 +56,14 @@ listés au démarrage, et chaque commit du dépôt choisi est proposé comme
 révision — de quoi comparer deux entraînements successifs sans redéployer. `↻`
 recharge la liste après un nouveau push de `train.py`.
 
+La liste reste triée par nom, pour qu'un dépôt garde sa place quand on la
+parcourt, mais la sélection initiale est le dépôt poussé le plus récemment,
+sur `main` : au démarrage la démo montre donc le dernier entraînement, quel
+que soit le backbone. La date de ce dernier push est affichée sous les deux
+menus et suit le dépôt sélectionné, ce qui rend le choix par défaut lisible.
+Attention, `last_modified` vaut pour le dépôt entier — une correction de
+README suffit à déplacer le choix par défaut, et la date affichée le montre.
+
 Les deux sorties de `train.py` sont acceptées : la présence de `model_head.pkl`
 sélectionne le chemin SetFit, sinon le modèle est chargé comme un
 `AutoModelForSequenceClassification`.

app/handlers.py

@@ -7,9 +7,9 @@ import gradio as gr
 
 from . import evaluation
 from .config import display
-from .hub import model_repos, revisions
+from .hub import model_repos, newest, revisions
 from .predictors import load
-from .text import LOADING, NO_MODEL, SCORING
+from .text import LOADING, NO_MODEL, SCORING, pushed_at
 from .turns import window
 
 EXAMPLES = json.loads((Path(__file__).parent / "examples.json").read_text(encoding="utf-8"))
@@ -49,18 +49,22 @@ def evaluate(repo: str, revision: str, progress=gr.Progress()):
     return summary(report), report.confusion, report.cases
 
 
-def pick_revision(repo: str) -> gr.Dropdown:
+def pick_revision(repo: str) -> tuple[gr.Dropdown, str]:
     choices = revisions(repo)
-    return gr.Dropdown(choices=choices, value=choices[0][1] if choices else None)
+    return (
+        gr.Dropdown(choices=choices, value=choices[0][1] if choices else None),
+        pushed_at(model_repos().get(repo)),
+    )
 
 
-def refresh(repo: str, revision: str) -> tuple[gr.Dropdown, gr.Dropdown]:
-    repos = model_repos()
-    chosen = repo if repo in repos else (repos[0] if repos else None)
+def refresh(repo: str, revision: str) -> tuple[gr.Dropdown, gr.Dropdown, str]:
+    pushes = model_repos()
+    chosen = repo if repo in pushes else newest(pushes)
     choices = revisions(chosen) if chosen else []
     shas = [sha for _, sha in choices]
     keep = revision if revision in shas else (shas[0] if shas else None)
     return (
-        gr.Dropdown(choices=repos, value=chosen),
+        gr.Dropdown(choices=list(pushes), value=chosen),
         gr.Dropdown(choices=choices, value=keep),
+        pushed_at(pushes[chosen] if chosen else None),
     )

app/hub.py

@@ -1,4 +1,5 @@
 import re
+from datetime import datetime
 from pathlib import Path
 
 from huggingface_hub import HfApi, hf_hub_download
@@ -17,8 +18,14 @@ def resolve(repo: str, revision: str, repo_type: str = "model") -> str:
     return info.sha
 
 
-def model_repos() -> list[str]:
-    return sorted(model.id for model in api.list_models(author=ORG, search=MODEL_SEARCH))
+def model_repos() -> dict[str, datetime]:
+    """Every backbone with the date of its last push, keyed alphabetically."""
+    models = api.list_models(author=ORG, search=MODEL_SEARCH, sort="last_modified")
+    return {model.id: model.last_modified for model in sorted(models, key=lambda m: m.id)}
+
+
+def newest(pushes: dict[str, datetime]) -> str | None:
+    return max(pushes, key=lambda repo: pushes[repo], default=None)
 
 
 def revisions(repo: str) -> list[tuple[str, str]]:

app/text.py

@@ -1,3 +1,5 @@
+from datetime import datetime
+
 from .config import CALLER_TURNS, DATASET_REPO, ORG
 
 HEADER = f"""
@@ -22,3 +24,10 @@ TRANSCRIPT_INFO = (
 NO_MODEL = "Aucun modèle sélectionné."
 LOADING = "Chargement du modèle"
 SCORING = "Classement du split de test"
+
+
+def pushed_at(when: datetime | None) -> str:
+    """Line under the pickers: when the selected repo was last touched."""
+    if when is None:
+        return ""
+    return f"<sub>Dépôt mis à jour le {when:%d/%m/%Y à %H:%M} UTC</sub>"

app/ui.py

@@ -4,24 +4,26 @@ import gradio as gr
 
 from .config import REFRESH_SECONDS, display
 from .handlers import EXAMPLES, classify, evaluate, pick_revision, refresh
-from .hub import model_repos, revisions
-from .text import HEADER, PLACEHOLDER, TRANSCRIPT_INFO
+from .hub import model_repos, newest, revisions
+from .text import HEADER, PLACEHOLDER, TRANSCRIPT_INFO, pushed_at
 
 CMD_ENTER_JS = (Path(__file__).parent / "cmd_enter.js").read_text(encoding="utf-8")
 
 
-def selectors() -> tuple[gr.Dropdown, gr.Dropdown, gr.Button]:
-    repos = model_repos()
-    repo = repos[0] if repos else None
+def selectors() -> tuple[gr.Dropdown, gr.Dropdown, gr.Button, gr.Markdown]:
+    pushes = model_repos()
+    repo = newest(pushes)
     revs = revisions(repo) if repo else []
-    model = gr.Dropdown(label="Modèle", choices=repos, value=repo, scale=3)
-    revision = gr.Dropdown(
-        label="Révision",
-        choices=revs,
-        value=revs[0][1] if revs else None,
-        scale=4,
-    )
-    return model, revision, gr.Button("↻", scale=0, min_width=48)
+    with gr.Row():
+        model = gr.Dropdown(label="Modèle", choices=list(pushes), value=repo, scale=3)
+        revision = gr.Dropdown(
+            label="Révision",
+            choices=revs,
+            value=revs[0][1] if revs else None,
+            scale=4,
+        )
+        reload_button = gr.Button("↻", scale=0, min_width=48)
+    return model, revision, reload_button, gr.Markdown(pushed_at(pushes[repo] if repo else None))
 
 
 def classify_tab() -> tuple[gr.Textbox, gr.Button, list]:
@@ -77,8 +79,7 @@ def build() -> gr.Blocks:
     with gr.Blocks(title="Risque d'immobilisation") as demo:
         gr.Markdown(HEADER)
 
-        with gr.Row():
-            model, revision, refresh_button = selectors()
+        model, revision, refresh_button, pushed = selectors()
         selection = [model, revision]
 
         with gr.Tab("Classer"):
@@ -88,9 +89,9 @@ def build() -> gr.Blocks:
             evaluate_button, report, progress_target = evaluation_tab()
 
         timer = gr.Timer(REFRESH_SECONDS)
-        timer.tick(refresh, selection, selection, show_progress="hidden")
-        refresh_button.click(refresh, selection, selection)
-        model.change(pick_revision, model, revision)
+        timer.tick(refresh, selection, [*selection, pushed], show_progress="hidden")
+        refresh_button.click(refresh, selection, [*selection, pushed])
+        model.change(pick_revision, model, [revision, pushed])
         gr.on(
             [run.click, transcript.submit],
             classify,

pyproject.toml

@@ -11,7 +11,7 @@ dependencies = [
     "datasets>=3",
     "scikit-learn>=1.5",
     "joblib>=1.4",
-    "huggingface-hub>=0.30",
+    "huggingface-hub>=1",
     "torch>=2.2",
     "numpy>=2",
 ]

uv.lock

@@ -127,7 +127,7 @@ dependencies = [
 requires-dist = [
     { name = "datasets", specifier = ">=3" },
     { name = "gradio", specifier = "==6.20.0" },
-    { name = "huggingface-hub", specifier = ">=0.30" },
+    { name = "huggingface-hub", specifier = ">=1" },
     { name = "joblib", specifier = ">=1.4" },
     { name = "numpy", specifier = ">=2" },
     { name = "scikit-learn", specifier = ">=1.5" },