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README.md

@@ -65,7 +65,7 @@ _Sorted by model size:_
 | `abot-ocr.py` | [ABot-OCR](https://huggingface.co/acvlab/ABot-OCR) | 2B | vLLM | Qwen3-VL based, doc→Markdown (text/LaTeX/HTML tables). Needs `vllm/vllm-openai` image. [paper](https://arxiv.org/abs/2605.27978) |
 | `nanonets-ocr.py` | [Nanonets-OCR-s](https://huggingface.co/nanonets/Nanonets-OCR-s) | 2B | vLLM | LaTeX, tables, forms |
 | `dots-mocr.py` | [dots.mocr](https://huggingface.co/rednote-hilab/dots.mocr) | 3B | vLLM | 8 prompt modes incl. SVG generation, layout + bbox, 100+ languages |
-| `nanonets-ocr2.py` | [Nanonets-OCR2-3B](https://huggingface.co/nanonets/Nanonets-OCR2-s) | 3B | vLLM | Next-gen, Qwen2.5-VL base |
+| `nanonets-ocr2.py` | [Nanonets-OCR2-3B](https://huggingface.co/nanonets/Nanonets-OCR2-3B) | 3B | vLLM | Next-gen, Qwen2.5-VL base. **Pin `--image vllm/vllm-openai:v0.10.2`** (vLLM ≥0.11 breaks Qwen2.5-VL → all `!`) |
 | `deepseek-ocr-vllm.py` | [DeepSeek-OCR](https://huggingface.co/deepseek-ai/DeepSeek-OCR) | 4B | vLLM | 5 resolution + 5 prompt modes |
 | `deepseek-ocr.py` | [DeepSeek-OCR](https://huggingface.co/deepseek-ai/DeepSeek-OCR) | 4B | Transformers | Same model, Transformers backend |
 | `deepseek-ocr2-vllm.py` | [DeepSeek-OCR-2](https://huggingface.co/deepseek-ai/DeepSeek-OCR-2) | 3B | vLLM | Newer; needs nightly vLLM **+ the `vllm/vllm-openai` image** ([why](#if-a-vllm-script-crashes-at-startup-the-nvcc--nvrtc-error)) |

nanonets-ocr2.py

@@ -4,10 +4,8 @@
 #     "datasets>=4.0.0",
 #     "huggingface-hub",
 #     "pillow",
-#     "vllm>=0.15.1",
 #     "tqdm",
 #     "toolz",
-#     "torch",
 # ]
 #
 # ///
@@ -26,6 +24,20 @@ Features:
 - Signature and watermark detection
 - Checkbox recognition
 - Multilingual support
+
+⚠️ Pinned vLLM image required. Nanonets-OCR2-3B is a Qwen2.5-VL model, and vLLM
+>=0.11 regressed Qwen2.5-VL decoding to a stream of "!" (vllm-project/vllm#27775,
+#14126); 0.10.2 is the last known-good. So `vllm` and `torch` are intentionally
+omitted from the deps above and come from the `vllm/vllm-openai:v0.10.2` image at
+runtime via PYTHONPATH. Run it like:
+
+    hf jobs uv run --flavor a10g-small -s HF_TOKEN \
+        --image vllm/vllm-openai:v0.10.2 --python /usr/bin/python3 \
+        -e PYTHONPATH=/usr/local/lib/python3.12/dist-packages \
+        nanonets-ocr2.py INPUT_DATASET OUTPUT_DATASET --max-samples 10 --shuffle
+
+Re-test the pin when a newer vLLM ships a Qwen2.5-VL decode fix; it can then move
+back to a plain `vllm>=...` dep on the default image.
 """
 
 import argparse
@@ -38,15 +50,32 @@ import sys
 from typing import Any, Dict, List, Union
 from datetime import datetime
 
+# Preflight: torch/vllm are deliberately NOT PEP 723 deps (see docstring) — they come from
+# the pinned vllm/vllm-openai:v0.10.2 image. On the bare uv image the imports below would
+# die with a raw ModuleNotFoundError; fail fast naming the exact flags instead.
+import importlib.util
+
+if importlib.util.find_spec("vllm") is None or importlib.util.find_spec("torch") is None:
+    sys.stderr.write(
+        "ERROR: vllm/torch not importable — this recipe cannot run on the bare uv image.\n"
+        "Nanonets-OCR2-3B needs vLLM 0.10.2 (>=0.11 regresses Qwen2.5-VL decoding to '!').\n"
+        "Re-run with the pinned image + interpreter flags:\n"
+        "    hf jobs uv run --flavor a10g-small -s HF_TOKEN \\\n"
+        "        --image vllm/vllm-openai:v0.10.2 --python /usr/bin/python3 \\\n"
+        "        -e PYTHONPATH=/usr/local/lib/python3.12/dist-packages \\\n"
+        "        nanonets-ocr2.py INPUT_DATASET OUTPUT_DATASET ...\n"
+    )
+    sys.exit(1)
+
 import torch
 from datasets import load_dataset
 from huggingface_hub import DatasetCard, login
 from PIL import Image
 from toolz import partition_all
 from tqdm.auto import tqdm
-# Disable vLLM's FlashInfer sampler: it JIT-compiles a CUDA kernel needing nvcc, which the
-# default uv-script image lacks (engine init then crashes). Greedy OCR doesn't use it; this
-# lets the plain default-image command work. On the vllm/vllm-openai image it's a harmless no-op.
+# Disable vLLM's FlashInfer sampler (JIT-compiles a CUDA kernel; greedy OCR doesn't use it).
+# Harmless no-op on the pinned vllm/vllm-openai image; kept in case the pin is ever relaxed
+# back to an environment without nvcc.
 os.environ.setdefault("VLLM_USE_FLASHINFER_SAMPLER", "0")
 from vllm import LLM, SamplingParams
 
@@ -64,6 +93,28 @@ def check_cuda_availability():
         logger.info(f"CUDA is available. GPU: {torch.cuda.get_device_name(0)}")
 
 
+def ensure_output_columns_free(dataset, columns, overwrite=False):
+    """Fail fast if an output column would collide with an existing input column.
+
+    Adding a column that already exists silently overwrites it (e.g. a ground-truth
+    `text`/`markdown` column) or crashes on push with a duplicate-column error only
+    *after* inference has run. Catch it up front. With overwrite=True, drop the clashing
+    column(s) here instead (logged) so the later add_column is clean.
+    """
+    clash = [c for c in columns if c in dataset.column_names]
+    if not clash:
+        return dataset
+    if overwrite:
+        logger.warning(f"--overwrite: replacing existing column(s) {clash}")
+        return dataset.remove_columns(clash)
+    logger.error(
+        f"Output column(s) {clash} already exist in the input dataset "
+        f"(columns: {dataset.column_names})."
+    )
+    logger.error("Choose a different --output-column, or pass --overwrite to replace them.")
+    sys.exit(1)
+
+
 def make_ocr_message(
     image: Union[Image.Image, Dict[str, Any], str],
     prompt: str = "Extract the text from the above document as if you were reading it naturally. Return the tables in html format. Return the equations in LaTeX representation. If there is an image in the document and image caption is not present, add a small description of the image inside the <img></img> tag; otherwise, add the image caption inside <img></img>. Watermarks should be wrapped in brackets. Ex: <watermark>OFFICIAL COPY</watermark>. Page numbers should be wrapped in brackets. Ex: <page_number>14</page_number> or <page_number>9/22</page_number>. Prefer using ☐ and ☑ for check boxes.",
@@ -214,7 +265,7 @@ def main(
     image_column: str = "image",
     batch_size: int = 16,
     model: str = "nanonets/Nanonets-OCR2-3B",
-    max_model_len: int = 8192,
+    max_model_len: int = 32768,
     max_tokens: int = 15000,
     gpu_memory_utilization: float = 0.8,
     hf_token: str = None,
@@ -223,6 +274,8 @@ def main(
     private: bool = False,
     shuffle: bool = False,
     seed: int = 42,
+    output_column: str = "markdown",
+    overwrite: bool = False,
     verbose: bool = False,
 ):
     """Process images from HF dataset through Nanonets-OCR2-3B model."""
@@ -251,6 +304,9 @@ def main(
             f"Column '{image_column}' not found. Available: {dataset.column_names}"
         )
 
+    # Fail fast if the output column would collide with an existing input column
+    dataset = ensure_output_columns_free(dataset, [output_column], overwrite=overwrite)
+
     # Shuffle if requested
     if shuffle:
         logger.info(f"Shuffling dataset with seed {seed}")
@@ -307,9 +363,9 @@ def main(
             # Add error placeholders for failed batch
             all_markdown.extend(["[OCR FAILED]"] * len(batch_images))
 
-    # Add markdown column to dataset
-    logger.info("Adding markdown column to dataset")
-    dataset = dataset.add_column("markdown", all_markdown)
+    # Add output column to dataset
+    logger.info(f"Adding '{output_column}' column to dataset")
+    dataset = dataset.add_column(output_column, all_markdown)
 
     # Handle inference_info tracking
     logger.info("Updating inference_info...")
@@ -317,7 +373,7 @@ def main(
     inference_entry = {
         "model_id": model,
         "model_name": "Nanonets-OCR2-3B",
-        "column_name": "markdown",
+        "column_name": output_column,
         "timestamp": datetime.now().isoformat(),
         "batch_size": batch_size,
         "max_tokens": max_tokens,
@@ -476,8 +532,8 @@ Examples:
     parser.add_argument(
         "--max-model-len",
         type=int,
-        default=8192,
-        help="Maximum model context length (default: 8192)",
+        default=32768,
+        help="Maximum model context length (default: 32768)",
     )
     parser.add_argument(
         "--max-tokens",
@@ -514,6 +570,17 @@ Examples:
         default=42,
         help="Random seed for shuffling (default: 42)",
     )
+    parser.add_argument(
+        "--output-column",
+        default="markdown",
+        help="Column name for the OCR output text (default: markdown)",
+    )
+    parser.add_argument(
+        "--overwrite",
+        action="store_true",
+        help="Replace the output column if it already exists in the input dataset "
+        "(default: error out to avoid clobbering an existing column).",
+    )
     parser.add_argument(
         "--verbose",
         action="store_true",
@@ -537,5 +604,7 @@ Examples:
         private=args.private,
         shuffle=args.shuffle,
         seed=args.seed,
+        output_column=args.output_column,
+        overwrite=args.overwrite,
         verbose=args.verbose,
     )