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>
2026-06-17 10:20:02 +04:00
commit 1a585693be
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+import time
+import click
+import copy
+import json
+from collections import defaultdict
+
+from surya.inference import SuryaInferenceManager
+from surya.layout import LayoutPredictor
+from surya.debug.draw import draw_polys_on_image
+from surya.logging import configure_logging, get_logger
+from surya.scripts.config import CLILoader
+import os
+
+configure_logging()
+logger = get_logger()
+
+
+@click.command(help="Detect layout of an input file or folder (PDFs or image).")
+@CLILoader.common_options
+def detect_layout_cli(input_path: str, **kwargs):
+    loader = CLILoader(input_path, kwargs)
+
+    manager = SuryaInferenceManager()
+    layout_predictor = LayoutPredictor(manager)
+
+    start = time.time()
+    layout_predictions = layout_predictor(loader.images)
+
+    if loader.debug:
+        logger.debug(f"Layout took {time.time() - start} seconds")
+
+    if loader.save_images:
+        for idx, (image, layout_pred, name) in enumerate(
+            zip(loader.images, layout_predictions, loader.names)
+        ):
+            polygons = [p.polygon for p in layout_pred.bboxes]
+            labels = [f"{p.label}-{p.position}" for p in layout_pred.bboxes]
+            bbox_image = draw_polys_on_image(
+                polygons, copy.deepcopy(image), labels=labels
+            )
+            bbox_image.save(
+                os.path.join(loader.result_path, f"{name}_{idx}_layout.png")
+            )
+
+    predictions_by_page = defaultdict(list)
+    for idx, (pred, name, image) in enumerate(
+        zip(layout_predictions, loader.names, loader.images)
+    ):
+        out_pred = pred.model_dump()
+        out_pred["page"] = len(predictions_by_page[name]) + 1
+        predictions_by_page[name].append(out_pred)
+
+    with open(
+        os.path.join(loader.result_path, "results.json"), "w+", encoding="utf-8"
+    ) as f:
+        json.dump(predictions_by_page, f, ensure_ascii=False)
+
+    logger.info(f"Wrote results to {loader.result_path}")
+
+
+if __name__ == "__main__":
+    detect_layout_cli()