Update LightOnOCR script to use vLLM nightly wheels

LightOnOCR support requires vLLM nightly build from main branch.
Added configuration to use nightly wheels, similar to DeepSeek-OCR script.

Changes:
- Use vLLM nightly wheels from https://wheels.vllm.ai/nightly
- Add prerelease = "allow" for UV
- Update docstring to note nightly requirement
- Remove version constraint from vLLM dependency

This matches the pattern used in deepseek-ocr-vllm.py which also
requires cutting-edge vLLM features.

🤖 Generated with Claude Code

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

lighton-ocr.py

@@ -4,12 +4,17 @@
 #     "datasets",
 #     "huggingface-hub[hf_transfer]",
 #     "pillow",
-#     "vllm>=0.9.1",
+#     "vllm",
 #     "tqdm",
 #     "toolz",
 #     "torch",
 # ]
 #
+# [[tool.uv.index]]
+# url = "https://wheels.vllm.ai/nightly"
+#
+# [tool.uv]
+# prerelease = "allow"
 # ///
 
 """
@@ -18,6 +23,9 @@ Convert document images to markdown using LightOnOCR with vLLM.
 LightOnOCR is a compact 1B multilingual OCR model optimized for production speed.
 Combines Pixtral ViT encoder with Qwen3 language model for efficient document parsing.
 
+NOTE: Requires vLLM nightly wheels for LightOnOCR support. First run may take
+a few minutes to download and install dependencies.
+
 Features:
 - ⚡ Fastest: 5.71 pages/sec on H100 GPU
 - 🎯 Compact: Only 1B parameters
@@ -28,7 +36,7 @@ Features:
 - 🔤 3 vocabulary sizes (151k/32k/16k tokens)
 
 Model: lightonai/LightOnOCR-1B-1025
-vLLM: Officially supported in model registry
+vLLM: Requires nightly build from main branch
 Performance: 76.1% overall benchmark score
 """