modified app.py to show progress bar

app.py

@@ -9,12 +9,59 @@ Gradio front-end for the UCI Phonotactic Calculator
 from pathlib import Path
 import tempfile, os, pandas as pd, gradio as gr
 
+# --- Gradio progress adapter for Rich-style progress ---
+class _GradioProgressAdapter:
+    """
+    Drop-in replacement for uci_phonotactic_calculator.progress.progress()
+    that streams status into the Gradio UI.
+
+    It only implements the bits the library actually calls:
+        with progress(...) as bar:
+            tid = bar.add_task("Training", total=N)
+            ...
+            bar.update(tid, advance=1)
+    """
+    def __init__(self, enabled: bool = True):
+        self.enabled = enabled
+        self._g_prog = None        # gr.Progress instance
+        self._tasks  = {}          # local id ➜ (current, total)
+
+    def __enter__(self):
+        if self.enabled:
+            # keep both the CM *and* the callable tracker
+            self._cm      = gr.Progress()          # context-manager
+            self._g_prog  = self._cm.__enter__()   # callable returned by __enter__
+        return self
+
+    def __exit__(self, exc_type, exc, tb):
+        if getattr(self, "_cm", None):
+            self._cm.__exit__(exc_type, exc, tb)
+
+    # ─── Rich-look-alike API ─────────────────────────────────────────
+    def add_task(self, description: str, total: int | None = None):
+        task_id = len(self._tasks) + 1
+        self._tasks[task_id] = [0, total or 0]
+        if self._g_prog:
+            # The callable has set_description() only on Gradio ≥4.3
+            if hasattr(self._g_prog, "set_description"):
+                self._g_prog.set_description(description)
+            self._g_prog(0, total or 0)
+        return task_id
+
+    def update(self, task_id: int, advance: int = 1):
+        cur, tot = self._tasks[task_id]
+        cur += advance
+        self._tasks[task_id][0] = cur
+        if self._g_prog:
+            self._g_prog(cur, tot)
+
 # ---> public, documented API wrapper around the CLI
 from uci_phonotactic_calculator.ngram_calculator import run as ngram_run
 from uci_phonotactic_calculator.plugins import PluginRegistry
 from uci_phonotactic_calculator.cli_demo_data import get_demo_paths
 
 TMP_DIR = Path(tempfile.gettempdir())
+from uuid import uuid4, uuid1
 
 # ---------------------------------------------------------------------
 # Back-end helper
@@ -40,31 +87,45 @@ def score(
             raise gr.Error("Upload BOTH training & test CSVs *or* tick the demo-data box.")
         train_path, test_path = train_csv.name, test_csv.name
 
-    out_file = TMP_DIR / "scores.csv"
+    out_file = TMP_DIR / f"scores_{uuid4().hex}.csv"
+    import atexit, functools
+    atexit.register(functools.partial(out_file.unlink, missing_ok=True))
 
     # -------------------- translate filters -------------------------
     filters = {}
-    if filter_string.strip():
-        for tok in filter_string.split():
+    tokens = filter_string.split()
+    if tokens and tokens[0] == "--filter":
+        tokens = tokens[1:]  # drop the flag if present
+    if tokens:
+        for tok in tokens:
             if "=" not in tok:
                 raise gr.Error(f"Filter “{tok}” must look like key=value")
             k, v = tok.split("=", 1)
             filters[k] = v
 
-    # -------------------- invoke library ---------------------------
-    ngram_run(
-        train_file=train_path,
-        test_file=test_path,
-        output_file=str(out_file),
-        model=None if run_full_grid else model,
-        run_all=run_full_grid,
-        filters=filters,
-        show_progress=not hide_progress,
-        extra_args=["-n", str(ngram_order)],
+    # -------------------- invoke library with Gradio progress patch ---------------------------
+    import uci_phonotactic_calculator.progress as _p
+    _orig_progress = _p.progress  # keep to restore later
+    _p.progress = lambda enabled=True: _GradioProgressAdapter(
+        enabled=enabled and not hide_progress
     )
+    try:
+        ngram_run(
+            train_file=train_path,
+            test_file=test_path,
+            output_file=str(out_file),
+            model=None if run_full_grid else model,
+            run_all=run_full_grid,
+            filters=filters,
+            show_progress=not hide_progress,   # still disables library chatter
+            extra_args=["-n", str(ngram_order)],
+        )
+    finally:
+        _p.progress = _orig_progress  # guarantee cleanup
 
     df = pd.read_csv(out_file)
-    return df, str(out_file)
+    df_preview = df.head(50).iloc[:, :30]    # show only first 50 rows, 30 cols in UI
+    return df_preview, str(out_file)
 
 # ---------------------------------------------------------------------
 # Gradio UI
@@ -91,17 +152,24 @@ with gr.Blocks(title="UCI Phonotactic Calculator") as demo:
             run_grid = gr.Checkbox(label="Run full variant grid", value=False)
             n_slider = gr.Slider(1, 4, step=1, value=2, label="n-gram order")
 
+            # Disable model dropdown when 'Run full grid' is checked
+            run_grid.change(
+                lambda g: gr.update(interactive=not g),
+                inputs=run_grid,
+                outputs=model_dd
+            )
+
             with gr.Accordion("Advanced", open=False):
                 filt_txt = gr.Textbox(
-                    label="--filter (space-separated key=value ...)",
+                    label="Filter (space-separated key=value …)",
                     placeholder="example: weight_mode=raw prob_mode=joint"
                 )
-                hide_prog = gr.Checkbox(label="Hide progress bars", value=False)
+                hide_prog = gr.Checkbox(label="Hide progress indicator", value=False)
 
             go_btn = gr.Button("Score")
 
         with gr.Column():
-            out_df  = gr.Dataframe(label="Scores (preview)")
+            out_df  = gr.Dataframe(label="Scores (preview)", interactive=False, height=350)
             out_csv = gr.File(label="Download full CSV")
 
     go_btn.click(