Pin nanonets-ocr.py to stable vLLM (>=0.15.1) + datasets>=4.0.0

Nanonets-OCR-s (Qwen2.5-VL fine-tune) is in stable vLLM.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

nanonets-ocr.py

@@ -1,10 +1,10 @@
 # /// script
 # requires-python = ">=3.11"
 # dependencies = [
-#     "datasets",
+#     "datasets>=4.0.0",
 #     "huggingface-hub",
 #     "pillow",
-#     "vllm",
+#     "vllm>=0.15.1",
 #     "tqdm",
 #     "toolz",
 #     "torch",  # Added for CUDA check
@@ -205,7 +205,7 @@ def main(
     batch_size: int = 32,
     model: str = "nanonets/Nanonets-OCR-s",
     max_model_len: int = 8192,
-    max_tokens: int = 4096,
+    max_tokens: int = 15000,
     gpu_memory_utilization: float = 0.8,
     hf_token: str = None,
     split: str = "train",
@@ -213,6 +213,7 @@ def main(
     private: bool = False,
     shuffle: bool = False,
     seed: int = 42,
+    verbose: bool = False,
 ):
     """Process images from HF dataset through OCR model."""
 
@@ -303,38 +304,39 @@ def main(
     # Handle inference_info tracking
     logger.info("Updating inference_info...")
 
-    # Check for existing inference_info
-    if "inference_info" in dataset.column_names:
-        # Parse existing info from first row (all rows have same info)
-        try:
-            existing_info = json.loads(dataset[0]["inference_info"])
-            if not isinstance(existing_info, list):
-                existing_info = [existing_info]  # Convert old format to list
-        except (json.JSONDecodeError, TypeError):
-            existing_info = []
-        # Remove old column to update it
-        dataset = dataset.remove_columns(["inference_info"])
-    else:
-        existing_info = []
-
-    # Add new inference info
-    new_info = {
-        "column_name": "markdown",
+    inference_entry = {
         "model_id": model,
-        "processing_date": datetime.now().isoformat(),
+        "model_name": "Nanonets-OCR-s",
+        "column_name": "markdown",
+        "timestamp": datetime.now().isoformat(),
         "batch_size": batch_size,
         "max_tokens": max_tokens,
         "gpu_memory_utilization": gpu_memory_utilization,
         "max_model_len": max_model_len,
         "script": "nanonets-ocr.py",
-        "script_version": "1.0.0",
         "script_url": "https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr.py",
     }
-    existing_info.append(new_info)
 
-    # Add updated inference_info column
-    info_json = json.dumps(existing_info, ensure_ascii=False)
-    dataset = dataset.add_column("inference_info", [info_json] * len(dataset))
+    if "inference_info" in dataset.column_names:
+        logger.info("Updating existing inference_info column")
+
+        def update_inference_info(example):
+            try:
+                existing_info = (
+                    json.loads(example["inference_info"])
+                    if example["inference_info"]
+                    else []
+                )
+            except (json.JSONDecodeError, TypeError):
+                existing_info = []
+            existing_info.append(inference_entry)
+            return {"inference_info": json.dumps(existing_info)}
+
+        dataset = dataset.map(update_inference_info)
+    else:
+        logger.info("Creating new inference_info column")
+        inference_list = [json.dumps([inference_entry])] * len(dataset)
+        dataset = dataset.add_column("inference_info", inference_list)
 
     # Push to hub
     logger.info(f"Pushing to {output_dataset}")
@@ -369,6 +371,17 @@ def main(
         f"Dataset available at: https://huggingface.co/datasets/{output_dataset}"
     )
 
+    if verbose:
+        import importlib.metadata
+
+        logger.info("--- Resolved package versions ---")
+        for pkg in ["vllm", "transformers", "torch", "datasets", "pyarrow", "pillow"]:
+            try:
+                logger.info(f"  {pkg}=={importlib.metadata.version(pkg)}")
+            except importlib.metadata.PackageNotFoundError:
+                logger.info(f"  {pkg}: not installed")
+        logger.info("--- End versions ---")
+
 
 if __name__ == "__main__":
     # Show example usage if no arguments
@@ -455,8 +468,8 @@ Examples:
     parser.add_argument(
         "--max-tokens",
         type=int,
-        default=4096,
-        help="Maximum tokens to generate (default: 4096)",
+        default=15000,
+        help="Maximum tokens to generate (default: 15000, per model card recommendation)",
     )
     parser.add_argument(
         "--gpu-memory-utilization",
@@ -487,6 +500,11 @@ Examples:
         default=42,
         help="Random seed for shuffling (default: 42)",
     )
+    parser.add_argument(
+        "--verbose",
+        action="store_true",
+        help="Log resolved package versions after processing (useful for pinning deps)",
+    )
 
     args = parser.parse_args()
 
@@ -505,4 +523,5 @@ Examples:
         private=args.private,
         shuffle=args.shuffle,
         seed=args.seed,
+        verbose=args.verbose,
     )