Suya OCR API — vLLM-backed, OpenAI-compatible OCR service

FastAPI service wrapping the Surya-OCR-2 model (datalab-to) served through vLLM:
legacy /v1/api/ai/* endpoints, an OpenAI-compatible /v1/chat/completions endpoint,
a coalescing request batcher, a local OCR CLI, Docker packaging, multilingual
example outputs, and quantization/concurrency benchmarks.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

scripts/capture_ocr_text.py

@@ -0,0 +1,54 @@
+"""Post one or more images to an OCR endpoint and save text_lines per image.
+
+Used to freeze the accuracy baseline and to capture candidate outputs for CER.
+
+Usage:
+    python scripts/capture_ocr_text.py \
+        --url http://127.0.0.1:5002/v1/api/ai/suya_ocr_vllm/ \
+        --out-dir baseline_outputs \
+        temp_image_c3c56948-282e-453b-8fac-6c482243d1e5.jpg
+"""
+from __future__ import annotations
+
+import argparse
+import base64
+from pathlib import Path
+
+import requests
+
+
+def _payload(image_path: Path) -> dict:
+    suffix = image_path.suffix.lstrip(".").lower() or "png"
+    return {
+        "file": base64.b64encode(image_path.read_bytes()).decode("utf-8"),
+        "type": "jpg" if suffix == "jpeg" else suffix,
+        "skip_text_detection": False,
+        "skip_table_detection": False,
+        "recognize_math": False,
+        "ocr_with_boxes": True,
+    }
+
+
+def capture(url: str, image_path: Path, out_dir: Path, timeout: float) -> str:
+    resp = requests.post(url, json=_payload(image_path), timeout=timeout)
+    body = resp.json()
+    text = (body.get("data") or {}).get("text_lines", "") if isinstance(body.get("data"), dict) else ""
+    out_dir.mkdir(parents=True, exist_ok=True)
+    (out_dir / (image_path.stem + ".txt")).write_text(text, encoding="utf-8")
+    return text
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Capture OCR text_lines per image.")
+    parser.add_argument("images", nargs="+", type=Path)
+    parser.add_argument("--url", required=True)
+    parser.add_argument("--out-dir", type=Path, required=True)
+    parser.add_argument("--timeout", type=float, default=900)
+    args = parser.parse_args()
+    for image in args.images:
+        capture(args.url, image, args.out_dir, args.timeout)
+        print(f"captured {image.name} -> {args.out_dir}")
+
+
+if __name__ == "__main__":
+    main()