Add --output-column parameter to olmocr2-vllm.py

- Allow users to specify custom output column name
- Default remains "markdown" for consistency
- Matches pattern from dots-ocr.py and rolm-ocr.py

🤖 Generated with [Claude Code](https://claude.com/claude-code)

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

olmocr2-vllm.py

@@ -259,6 +259,7 @@ def main(
     input_dataset: str,
     output_dataset: str,
     image_column: str = "image",
+    output_column: str = "markdown",
     batch_size: int = 16,
     model: str = "allenai/olmOCR-2-7B-1025-FP8",
     max_model_len: int = 16384,
@@ -279,6 +280,7 @@ def main(
         input_dataset: HuggingFace dataset ID containing images
         output_dataset: HuggingFace dataset ID for output
         image_column: Column name containing images
+        output_column: Column name for markdown output
         batch_size: Number of images to process at once
         model: HuggingFace model ID for olmOCR
         max_model_len: Maximum context length
@@ -319,9 +321,9 @@ def main(
         ds = ds.select(range(min(max_samples, len(ds))))
 
     logger.info(f"Processing {len(ds)} samples")
+    logger.info(f"Output will be written to column: {output_column}")
 
-    # Check if output column already exists with inference info
-    output_column_name = "markdown"
+    # Set column names
     metadata_column_name = "olmocr_metadata"
     inference_info_column = "inference_info"
 
@@ -363,7 +365,7 @@ def main(
             all_metadata.append(json.dumps(metadata))
 
     # Add results to dataset
-    ds = ds.add_column(output_column_name, all_outputs)
+    ds = ds.add_column(output_column, all_outputs)
     ds = ds.add_column(metadata_column_name, all_metadata)
 
     # Add inference information
@@ -482,6 +484,11 @@ Examples:
         default="image",
         help="Column name containing images (default: image)",
     )
+    parser.add_argument(
+        "--output-column",
+        default="markdown",
+        help="Column name for markdown output (default: markdown)",
+    )
     parser.add_argument(
         "--batch-size",
         type=int,
@@ -553,6 +560,7 @@ Examples:
         input_dataset=args.input_dataset,
         output_dataset=args.output_dataset,
         image_column=args.image_column,
+        output_column=args.output_column,
         batch_size=args.batch_size,
         model=args.model,
         max_model_len=args.max_model_len,