Specific request to detect names.

copienator/commands/cutleft.py

@@ -224,6 +224,11 @@ def save_results(
     for index in range(1, len(splits) + 1):
         print(f"Saved: {base_name}_{index:02d}.jpg")
     print(f"Saved schema: {base_name}_schema.json")
+    if pdf_path.is_file():
+        from copienator.name_grids import save_crop, build_grids
+        pages = get_pdf_pages(pdf_path)
+        save_crop(pages[0], pdf_path, output_dir / "Names", RENDER_DPI)
+        build_grids(output_dir / "Names", pdf_path.parent)
 
 
 def regenerate_full_page_image(workspace: EvaluationWorkspace, image_path: Path) -> None:

copienator/commands/gemini_for_labels.py

@@ -16,6 +16,7 @@ from pydantic import BaseModel, Field, model_validator
 
 from copienator import configuration as config
 from copienator.gemini_config import fresh_seed, thinking_config
+from copienator.name_grids import identify_names, MISSING
 from copienator.copy_errors import marked_copy_paths
 from copienator.orientation import record_detection, reports as orientation_reports
 from copienator import (
@@ -145,11 +146,27 @@ be missing.
 Since this copy isn't the first part of a sequence, simply set the
 name to `\"Continued\"`."""
 
+
+def labels_only_prompt(template: str) -> str:
+    """Keep label instructions/context, removing every name-related instruction."""
+    start = template.index("You also need to give me the student name.")
+    end = template.index("You may find the same label", start)
+    template = template[:start] + """Answer with a JSON object containing a `list` of bounding boxes and labels.
+The box_2d is [ymin, xmin, ymax, xmax] normalized to 0-1000.
+Example: {"list": [{"box_2d": [10, 20, 30, 40], "label": "Ex 1 : 1)"}]}
+Order boxes column by column, top to bottom within each column.
+
+""" + template[end:]
+    for ending in ("Here's a list of the names", "Since this copy isn't the first part"):
+        template = template.split(ending)[0]
+    return template
+
+
 class BoxItem(BaseModel):
     box_2d: list[int] = Field(description="Bounding box coordinates (e.g., [ymin, xmin, ymax, xmax])")
     label: str = Field(description="The label associated with the specific box")
 
-class AnnotationData(BaseModel):
+class LabelData(BaseModel):
     upside_down_pages: typing.List[typing.Annotated[int, Field(strict=True, ge=1)]] = Field(
         default_factory=list,
         description='1-based column numbers in this image that appear upside down (180 degrees)',
@@ -158,11 +175,20 @@ class AnnotationData(BaseModel):
         default=None, description="Report insufficient_crop when the crop hides information needed to identify labels"
     )
     error_reason: str | None = Field(default=None, description="Explanation of the crop error")
-    name: str = Field(default="Unknown", description="The name identifier")
     list: typing.List[BoxItem] = Field(  # noqa: UP006 - field name shadows list
         default_factory=list, description="List of bounding box items"
     )
 
+    @model_validator(mode="after")
+    def require_labels(self):
+        if self.error is None and not self.upside_down_pages and "list" not in self.model_fields_set:
+            raise ValueError("Successful detection must include list")
+        return self
+
+
+class AnnotationData(LabelData):
+    name: str = Field(default="Unknown", description="The name identifier")
+
     @model_validator(mode="after")
     def require_success_payload(self):
         if self.error is None and not self.upside_down_pages and not {"name", "list"} <= self.model_fields_set:
@@ -232,6 +258,7 @@ def generate_request(
     *,
     retry: bool = False,
     full_pages: bool = False,
+    known_name: str | None = None,
 ):
     """Generates request for Gemini with context."""
 
@@ -241,10 +268,10 @@ def generate_request(
     context_str = ", ".join([f'"{l}"' for l in context_labels]) if context_labels else "No previous context"
 
     if context_labels == []:
-        text = my_prompt.replace("##labels##", labels)\
+        text = (labels_only_prompt(my_prompt) if known_name else my_prompt).replace("##labels##", labels)\
                         .replace("##names##", names)
     else:
-        text = my_prompt2.replace("##labels##", labels)\
+        text = (labels_only_prompt(my_prompt2) if known_name else my_prompt2).replace("##labels##", labels)\
                          .replace("##prev_context##", context_str)
     if wrong_labels:
         formatted_wrong_labels = "\n".join(f'- "{label}"' for label in wrong_labels)
@@ -297,6 +324,9 @@ students may skip questions. On success, return error=null.
              'you may return name="Unknown", list=[] and error=null. Orientation '
              'reporting takes priority over insufficient_crop.')
 
+    if known_name:
+        text = text.replace('name="Unknown", list=[]', 'list=[]')
+
     contents = [
         types.Content(
             role="user",
@@ -320,7 +350,7 @@ students may skip questions. On success, return error=null.
         seed=fresh_seed() if seed is None else seed,
         max_output_tokens=65535,
         response_mime_type= "application/json",
-        response_json_schema= AnnotationData.model_json_schema(),
+        response_json_schema=(LabelData if known_name else AnnotationData).model_json_schema(),
     )
     return (contents, generate_content_config)
 
@@ -461,11 +491,13 @@ def process_copy_group(
     valid_labels: set[str],
     valid_names: set[str],
     overwrite: bool,
+    known_name: str | None = None,
     sleep: Sleep = time.sleep,
     target_interval: float = TARGET_INTERVAL,
     progress: Callable[[str, str, float], None] | None = None,
 ) -> int:
     """Process one student's image parts sequentially to preserve context."""
+    known_name = known_name if known_name in valid_names and known_name not in {"Missing", "Unknown", "Continued"} else None
     accumulated_labels: list[str] = []
     generated = 0
     for image_index, image_file in enumerate(files):
@@ -518,13 +550,21 @@ def process_copy_group(
                     seed=request_seed,
                     retry=attempt > 0 or full_page_fallback,
                     full_pages=full_page_fallback,
+                    known_name=known_name,
                 )
                 response = client.models.generate_content(
                     model=MODEL_ID,
                     contents=contents,
                     config=request_config,
                 )
-                annotation = AnnotationData.model_validate_json(response.text)
+                if known_name:
+                    detected = LabelData.model_validate_json(response.text)
+                    # Preserve the established downstream first-part/continuation contract.
+                    part = re.search(r"_(\d+)$", image_file.stem)
+                    saved_name = "Continued" if part and int(part.group(1)) > 1 else known_name
+                    annotation = AnnotationData(**detected.model_dump(), name=saved_name)
+                else:
+                    annotation = AnnotationData.model_validate_json(response.text)
                 if record_detection(workspace, image_file, annotation.upside_down_pages):
                     output_json.unlink(missing_ok=True)
                     print(f'[{group_key}] Orientation à vérifier avant de valider les labels.')
@@ -575,7 +615,7 @@ def process_copy_group(
                         label_retry_count += 1
                         attempt += 1
                         continue
-                if annotation.name not in valid_names:
+                if not known_name and annotation.name not in valid_names:
                     print(
                         f"Error: {image_file.name} returned unknown name: "
                         f"{annotation.name}"
@@ -653,6 +693,14 @@ def run(
         client = genai.Client(api_key=api_key)
 
     groups = group_images(images)
+    pending_groups = {key: files for key, files in groups.items()
+                      if overwrite or any(not (workspace.copies_dir / f"{image.stem}.json").exists()
+                                          for image in files)}
+    identified_names = identify_names(
+        workspace, pending_groups, client=client, model=config.MODEL_FOR_NAME_ID,
+        names_text=names_text, overwrite=overwrite,
+        thinking_level=config.THINKING_LEVEL_FOR_NAME,
+    )
     total_groups = len(groups)
     active: dict[str, tuple[str, float]] = {}
     progress_lock = Lock()
@@ -682,6 +730,7 @@ def run(
                 valid_labels=set(all_labels),
                 valid_names=valid_names,
                 overwrite=overwrite,
+                known_name=(identified_names.get(group_key) if identified_names.get(group_key) != MISSING else None),
                 sleep=sleep,
                 progress=report_progress,
             ): group_key

copienator/configuration.py

@@ -34,6 +34,8 @@ else:
 # Keep new optional settings compatible with older personal configuration files.
 THINKING_LEVEL_LITE = "low"
 THINKING_LEVEL_FOR_LABEL = "medium"
+MODEL_FOR_NAME_ID = getattr(_configuration, "MODEL_FOR_LABEL_ID", "gemini-3.8-flash")
+THINKING_LEVEL_FOR_NAME = "low"
 THINKING_LEVEL_FLASH = "medium"
 THINKING_LEVEL_PRO = "high"
 ALWAYS_CROP = False

copienator/name_grids.py

@@ -0,0 +1,155 @@
+"""First-page name crops, numbered contact sheets, and roster-checked recognition."""
+from __future__ import annotations
+
+from pathlib import Path
+
+from google.genai import types
+from PIL import Image, ImageDraw
+from pydantic import BaseModel, Field
+
+from copienator import atomic_write_json, read_json
+from copienator.annotation_layout import fingerprint
+from copienator.filesystem import staged_files
+from copienator.gemini_config import fresh_seed, thinking_config
+from copienator.utils import natural_key
+
+COLUMNS, ROWS = 6, 4
+MARGIN_MM = 28
+MISSING = "Missing"
+
+
+def save_crop(page: Image.Image, pdf: Path, directory: Path, dpi: int) -> None:
+    """Crop independently of the adjustable label strip, from the true top left."""
+    width = min(page.width, max(1, round(MARGIN_MM * dpi / 25.4)))
+    crop = page.crop((0, 0, width, max(1, page.height // 4)))
+    with staged_files(directory) as staging:
+        crop.save(staging / f"{pdf.stem}.jpg", "JPEG", quality=95)
+        atomic_write_json(staging / f"{pdf.stem}.json", {
+            "source_sha256": fingerprint(pdf), "width_mm": MARGIN_MM,
+            "height_fraction": 0.25,
+        })
+
+
+def build_grids(directory: Path, copies_dir: Path) -> list[dict]:
+    """Rebuild deterministic 6-by-4 sheets, excluding deleted or changed copies."""
+    crops = []
+    for path in sorted(directory.glob("*.jpg"), key=natural_key):
+        pdf = copies_dir / f"{path.stem}.pdf"
+        try:
+            if pdf.is_file() and read_json(path.with_suffix('.json'))['source_sha256'] == fingerprint(pdf):
+                crops.append(path)
+        except (OSError, ValueError, KeyError, TypeError):
+            continue
+    grids_dir = directory / "Grids"
+    grids = []
+    with staged_files(grids_dir, remove=[p.name for p in grids_dir.glob('*') if p.is_file()]) as staging:
+        for offset in range(0, len(crops), COLUMNS * ROWS):
+            batch = crops[offset:offset + COLUMNS * ROWS]
+            images = []
+            for path in batch:
+                with Image.open(path) as image:
+                    images.append(image.convert('RGB'))
+            width = max(image.width for image in images)
+            height = max(image.height for image in images)
+            border, header = 6, 32
+            cell_width, cell_height = width + border, height + header + border
+            sheet = Image.new('RGB', (COLUMNS * cell_width + border, ROWS * cell_height + border), 'black')
+            draw = ImageDraw.Draw(sheet)
+            cells = []
+            for index in range(COLUMNS * ROWS):
+                row, column = divmod(index, COLUMNS)
+                x, y = border + column * cell_width, border + row * cell_height
+                draw.rectangle((x, y, x + width - 1, y + height + header - 1), fill='white')
+                if index < len(images):
+                    sheet.paste(images[index], (x, y + header))
+                    draw.text((x + 5, y + 5), f"R{row + 1} C{column + 1} | {index + 1}", fill='black')
+                    cells.append({'cell': index + 1, 'row': row + 1, 'column': column + 1,
+                                  'copy': batch[index].stem})
+                else:
+                    draw.text((x + 5, y + 5), 'EMPTY', fill='black')
+            filename = f"grid_{len(grids) + 1:03d}.jpg"
+            sheet.save(staging / filename, 'JPEG', quality=95)
+            grids.append({'image': filename, 'columns': COLUMNS, 'rows': ROWS, 'cells': cells})
+        atomic_write_json(staging / 'manifest.json', grids)
+    return grids
+
+
+class NameCell(BaseModel):
+    cell: int = Field(strict=True, ge=1, le=24)
+    name: str
+
+
+class NameResponse(BaseModel):
+    cells: list[NameCell]
+
+
+def identify_names(workspace, groups, *, client, model: str, names_text: str, overwrite: bool,
+                   thinking_level: str | None = "low") -> dict[str, str]:
+    """Identify pending copies before label requests; safely fall back on any failure."""
+    directory = workspace.cutleft_dir / 'Names'
+    result = {stem: MISSING for stem in groups}
+    if not groups or not directory.is_dir():
+        return result  # Older workspaces retain their existing label/name workflow.
+    grids = build_grids(directory, workspace.copies_dir)
+    roster = {line.strip() for line in names_text.splitlines() if line.strip()} - {MISSING, 'Unknown', 'Continued'}
+    for grid in grids:
+        selected = {cell['copy']: cell for cell in grid['cells'] if cell['copy'] in groups}
+        pending = {}
+        for stem, cell in selected.items():
+            crop_hash = fingerprint(directory / f'{stem}.jpg')
+            cache_path = directory / f'{stem}_result.json'
+            try:
+                cached = read_json(cache_path)
+                if (not overwrite and cached['crop_sha256'] == crop_hash
+                        and cached['names_text'] == names_text
+                        and cached['name'] in roster | {MISSING}):
+                    result[stem] = cached['name']
+                    continue
+            except (OSError, ValueError, KeyError, TypeError):
+                pass
+            pending[stem] = (cell, crop_hash, cache_path)
+        if not pending:
+            continue
+        positions = '\n'.join(f"Cell {c['cell']}: row {c['row']}, column {c['column']}" for c in grid['cells'])
+        prompt = f"""Identify student names from the top-left corners of exam first pages.
+The image is a grid with exactly 6 columns and 4 rows. Read rows left to right,
+then top to bottom. Thick black borders separate cells; headers show row, column,
+and cell number. Each cell belongs to a DIFFERENT student. Never carry a name
+from one cell into another. Ignore class names such as MPSI 3.
+Occupied cells are exactly:
+{positions}
+All other cells are EMPTY padding: do not return them.
+Return JSON {{"cells": [{{"cell": 1, "name": "exact authorized name"}}]}}.
+Return one entry per occupied cell, using its cell number. Match only confidently
+readable handwriting to an exact authorized name below. Do not guess or assign
+names by elimination. Return "Missing" for an unreadable, absent, or ambiguous name.
+Authorized names:
+{names_text}"""
+        print(f"Identifying student names: {grid['image']} ({len(grid['cells'])} occupied cells, model={model}, thinking={thinking_level or 'default'}).", flush=True)
+        try:
+            response = client.models.generate_content(
+                model=model,
+                contents=[types.Content(role='user', parts=[
+                    types.Part.from_bytes(data=(directory / 'Grids' / grid['image']).read_bytes(), mime_type='image/jpeg'),
+                    types.Part.from_text(text=prompt),
+                ])],
+                config=types.GenerateContentConfig(
+                    http_options=types.HttpOptions(timeout=80_000, retry_options=types.HttpRetryOptions(attempts=1)),
+                    automatic_function_calling=types.AutomaticFunctionCallingConfig(disable=True),
+                    thinking_config=thinking_config(thinking_level), seed=fresh_seed(),
+                    response_mime_type='application/json', response_json_schema=NameResponse.model_json_schema(),
+                ),
+            )
+            entries = NameResponse.model_validate_json(response.text).cells
+            by_cell = {}
+            for entry in entries:
+                by_cell.setdefault(entry.cell, []).append(entry.name)
+            for stem, (cell, crop_hash, cache_path) in pending.items():
+                candidates = by_cell.get(cell['cell'], [])
+                name = candidates[0] if len(candidates) == 1 and candidates[0] in roster else MISSING
+                result[stem] = name
+                atomic_write_json(cache_path, {'name': name, 'crop_sha256': crop_hash, 'names_text': names_text})
+        except Exception as exc:  # Remote failures must preserve the existing fallback.
+            print(f"Name recognition failed for {grid['image']}: {type(exc).__name__}: {exc}; using label/name fallback.")
+            # Do not cache transport/schema failures: a resumed run should retry.
+    return result

default_config.py

@@ -50,6 +50,11 @@ THINKING_LEVEL_LITE = "low"
 MODEL_FOR_LABEL_ID = "gemini-3.8-flash"
 THINKING_LEVEL_FOR_LABEL = "low"
 
+# Modèle pour reconnaître les noms sur les grilles de premières pages.
+MODEL_FOR_NAME_ID = "gemini-3.8-flash"
+THINKING_LEVEL_FOR_NAME = "low"
+
+
 # Modèle pour des choses normales
 MODEL_FLASH_ID = "gemini-3.8-flash"
 THINKING_LEVEL_FLASH = "medium"

docs/guide_utilisateur_gui.md

@@ -134,6 +134,25 @@ son propre signalement ; un signalement de vérification des labels reste actif.
 
 ## Labels et regroupement
 
+La validation enregistre aussi le coin supérieur gauche de la première page :
+28 mm de large et un quart de la hauteur. Ces images sont conservées dans
+`Cutleft/Names`, puis assemblées en grilles de 6 colonnes et 4 lignes dans
+`Cutleft/Names/Grids`. Des bordures noires et des numéros identifient chaque case ;
+les cases inutilisées portent la mention `EMPTY`.
+
+La détection des labels commence par reconnaître les noms sur ces grilles avec
+Gemini, configuré par `MODEL_FOR_NAME_ID` et `THINKING_LEVEL_FOR_NAME` dans
+`config.py` (réflexion `low` par défaut), indépendamment du modèle de détection
+des labels. Le modèle reçoit les positions des cases occupées et
+la liste des noms autorisés. Un nom absent, illisible, ambigu ou hors liste est
+conservé comme `Missing` dans le résultat de cette première passe. Dans ce cas,
+la détection habituelle des labels recherche aussi le nom. Si le nom a été
+reconnu, les requêtes de labels ne demandent plus de nom et ne transmettent plus
+la liste des élèves. Les résultats de noms sont réutilisés à la reprise tant
+que les images et la liste des noms restent identiques ; une relance avec
+écrasement les recalcule. Pour les anciennes découpes sans grilles, le
+fonctionnement antérieur reste disponible ; relancer la découpe crée les grilles.
+
 ### Détecter les labels avec Gemini
 
 **Effet :** reconnaît les identifiants de questions et leur position dans les copies.

tests/test_marked_copies.py

@@ -39,9 +39,14 @@ class MarkedCopiesTests(unittest.TestCase):
         review.current_width_offset = 0
         review.default_max_per_file = 5
         review.current_max_per_file = 1
+        review.review_settings = {}
         review.root = Mock()
         review.stop_prefetch = threading.Event()
-        review.load_current_image = Mock()
+        def load_current_image():
+            review.current_shift, review.current_width_offset, review.current_max_per_file = (
+                review.review_settings.get(review.index, (0, 0, review.default_max_per_file))
+            )
+        review.load_current_image = Mock(side_effect=load_current_image)
         review.update_display = Mock()
         image = Image.new("RGB", (8, 8), "white")
         review.current_result = (image, [image], {"total_pages": 1, "columns_per_file": [1]})
@@ -79,7 +84,8 @@ class MarkedCopiesTests(unittest.TestCase):
         for path in self.files:
             mark_copy_error(self.workspace, path, "Review needed")
         review = self.reviewer()
-        review.on_next(None)
+        with patch.object(cutleft, "get_pdf_pages", return_value=[review.current_result[0]]):
+            review.on_next(None)
         self.assertTrue((review.output_dir / "Copie01_01.jpg").is_file())
         self.assertEqual(set(copy_errors(self.workspace)), {"Copie02.pdf"})
         self.assertEqual(review.index, 1)

tests/test_name_grids.py

@@ -0,0 +1,145 @@
+import json
+import tempfile
+import unittest
+from pathlib import Path
+from unittest.mock import Mock, patch
+
+from PIL import Image
+
+from copienator import EvaluationWorkspace, ExitCode, read_json
+from copienator import name_grids as names
+from copienator.commands import cutleft, gemini_for_labels as labels
+
+
+class NameGridTests(unittest.TestCase):
+    def setUp(self):
+        temporary = tempfile.TemporaryDirectory()
+        self.addCleanup(temporary.cleanup)
+        self.workspace = EvaluationWorkspace(Path(temporary.name))
+        self.workspace.copies_dir.mkdir()
+        self.workspace.cutleft_dir.mkdir()
+        self.directory = self.workspace.cutleft_dir / 'Names'
+        (self.workspace.root / 'names').write_text('Alice\nBob\n')
+        (self.workspace.root / 'labels').write_text('Ex 1\n')
+        self.client = Mock()
+
+    def crop(self, number):
+        pdf = self.workspace.copies_dir / f'Copie{number:02d}.pdf'
+        pdf.write_bytes(b'pdf')
+        page = Image.new('RGB', (1654, 2338), 'white')
+        page.putpixel((0, 0), (0, 0, 0))
+        names.save_crop(page, pdf, self.directory, 200)
+        (self.workspace.cutleft_dir / f'{pdf.stem}_01.jpg').write_bytes(b'image')
+        return pdf
+
+    def identify(self, groups, overwrite=False):
+        return names.identify_names(self.workspace, groups, client=self.client, model='test',
+                                    names_text='Alice\nBob\n', overwrite=overwrite)
+
+    def test_crop_geometry_and_partial_grid_mapping(self):
+        for number in range(1, 26):
+            self.crop(number)
+        with Image.open(self.directory / 'Copie01.jpg') as crop:
+            self.assertEqual(crop.size, (220, 584))
+            self.assertLess(crop.getpixel((0, 0))[0], 80)
+        grids = names.build_grids(self.directory, self.workspace.copies_dir)
+        self.assertEqual([len(grid['cells']) for grid in grids], [24, 1])
+        self.assertEqual(grids[0]['cells'][6], {'cell': 7, 'row': 2, 'column': 1, 'copy': 'Copie07'})
+        self.assertEqual(grids[1]['cells'][0]['copy'], 'Copie25')
+        with Image.open(self.directory / 'Grids' / grids[1]['image']) as grid:
+            self.assertEqual(grid.size, (1362, 2494))
+            self.assertLess(grid.getpixel((228, 500))[0], 40)
+        # Deleted/stale PDFs cannot be assigned names from old crops.
+        (self.workspace.copies_dir / 'Copie25.pdf').unlink()
+        (self.workspace.copies_dir / 'Copie24.pdf').write_bytes(b'changed')
+        grids = names.build_grids(self.directory, self.workspace.copies_dir)
+        self.assertEqual(len(grids), 1)
+        self.assertEqual(len(grids[0]['cells']), 23)
+        self.assertFalse((self.directory / 'Grids' / 'grid_002.jpg').exists())
+
+    def test_validation_cache_and_roster_changes(self):
+        for number in range(1, 5):
+            self.crop(number)
+        self.client.models.generate_content.return_value = Mock(text=json.dumps({'cells': [
+            {'cell': 1, 'name': 'Alice'}, {'cell': 2, 'name': 'Outsider'},
+            {'cell': 3, 'name': 'Bob'}, {'cell': 3, 'name': 'Alice'},
+            {'cell': 24, 'name': 'Bob'},
+        ]}))
+        groups = {f'Copie{i:02d}': [] for i in range(1, 5)}
+        expected = {'Copie01': 'Alice', **{f'Copie{i:02d}': 'Missing' for i in range(2, 5)}}
+        self.assertEqual(self.identify(groups), expected)
+        request = self.client.models.generate_content.call_args.kwargs
+        self.assertEqual(request['config'].thinking_config.thinking_level.value, 'LOW')
+        text = request['contents'][0].parts[1].text
+        self.assertIn('6 columns and 4 rows', text)
+        self.assertIn('Cell 4: row 1, column 4', text)
+        self.assertNotIn('Cell 5:', text)
+        self.assertEqual(self.identify(groups), expected)
+        self.assertEqual(self.client.models.generate_content.call_count, 1)
+        self.identify(groups, overwrite=True)
+        self.assertEqual(self.client.models.generate_content.call_count, 2)
+        names.identify_names(self.workspace, groups, client=self.client, model='test',
+                             names_text='Bob\n', overwrite=False)
+        self.assertEqual(read_json(self.directory / 'Copie01_result.json')['name'], 'Missing')
+
+    def test_api_failure_is_retried_on_resume(self):
+        self.crop(1)
+        self.client.models.generate_content.side_effect = TimeoutError()
+        self.assertEqual(self.identify({'Copie01': []}), {'Copie01': 'Missing'})
+        self.assertFalse((self.directory / 'Copie01_result.json').exists())
+        self.identify({'Copie01': []})
+        self.assertEqual(self.client.models.generate_content.call_count, 2)
+
+    def test_known_and_missing_names_choose_different_label_requests(self):
+        for number in (1, 2):
+            self.crop(number)
+        (self.workspace.cutleft_dir / 'Copie01_02.jpg').write_bytes(b'image')
+        self.client.models.generate_content.side_effect = [
+            Mock(text='{"cells":[{"cell":1,"name":"Alice"},{"cell":2,"name":"Missing"}]}'),
+            Mock(text='{"list":[{"box_2d":[1,2,3,4],"label":"Ex 1"}]}'), Mock(text='{"list":[]}'),
+            Mock(text='{"name":"Bob","list":[]}'),
+        ]
+        with patch.object(labels.config, 'MODEL_FOR_NAME_ID', 'custom-name-model'), \
+                patch.object(labels.config, 'THINKING_LEVEL_FOR_NAME', 'medium'):
+            status = labels.run(self.workspace, [self.workspace.root], client=self.client,
+                                sleep=lambda _: None, max_workers=1)
+        self.assertEqual(status, ExitCode.SUCCESS)
+        requests = self.client.models.generate_content.call_args_list
+        self.assertEqual(len(requests), 4)
+        self.assertEqual(requests[0].kwargs['model'], 'custom-name-model')
+        self.assertEqual(requests[0].kwargs['config'].thinking_config.thinking_level.value, 'MEDIUM')
+        self.assertEqual(requests[1].kwargs['model'], labels.MODEL_ID)
+        for request in requests[1:3]:
+            text = request.kwargs['contents'][0].parts[1].text
+            self.assertNotIn('Alice', text)
+            self.assertNotIn('Bob', text)
+            self.assertNotIn('student name', text)
+            self.assertNotIn('name', request.kwargs['config'].response_json_schema['properties'])
+        self.assertIn('Alice', requests[3].kwargs['contents'][0].parts[1].text)
+        for stem, expected in [('Copie01_01', 'Alice'), ('Copie01_02', 'Continued'), ('Copie02_01', 'Bob')]:
+            self.assertEqual(read_json(self.workspace.copies_dir / f'{stem}.json')['name'], expected)
+        self.client.models.generate_content.reset_mock()
+        labels.run(self.workspace, [self.workspace.root], client=self.client, sleep=lambda _: None)
+        self.client.models.generate_content.assert_not_called()
+
+    def test_save_label_crops_also_saves_name_grid(self):
+        pdf = self.workspace.copies_dir / 'Copie01.pdf'
+        pdf.write_bytes(b'pdf')
+        page = Image.new('RGB', (1654, 2338), 'white')
+        with patch.object(cutleft, 'get_pdf_pages', return_value=[page]):
+            result = cutleft.process_single_pdf(pdf, automatic_margin=False)
+            cutleft.save_results(result, pdf, self.workspace.cutleft_dir)
+        self.assertTrue((self.directory / 'Copie01.jpg').is_file())
+        self.assertEqual(read_json(self.directory / 'Grids' / 'manifest.json')[0]['cells'][0]['copy'], 'Copie01')
+
+    def test_known_name_survives_label_retry(self):
+        self.crop(1)
+        image = self.workspace.cutleft_dir / 'Copie01_01.jpg'
+        self.client.models.generate_content.side_effect = [TimeoutError(), Mock(text='{"list":[]}')]
+        labels.process_copy_group(self.workspace, 'Copie01', [image], client=self.client,
+                                  labels_text='Ex 1', names_text='Alice\nBob', valid_labels={'Ex 1'},
+                                  valid_names={'Alice', 'Bob'}, overwrite=False, known_name='Alice',
+                                  sleep=lambda _: None, target_interval=0)
+        self.assertEqual(read_json(self.workspace.copies_dir / 'Copie01_01.json')['name'], 'Alice')
+        for call in self.client.models.generate_content.call_args_list:
+            self.assertNotIn('Alice', call.kwargs['contents'][0].parts[1].text)