Fu DaiandClaude Opus 4.8
1a585693be
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>
26 lines
883 B
Python
26 lines
883 B
Python
from typing import Dict
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import torch
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from surya.common.predictor import BasePredictor
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from surya.detection import DetectionPredictor
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from surya.layout import LayoutPredictor
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from surya.logging import configure_logging
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from surya.ocr_error import OCRErrorPredictor
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from surya.recognition import RecognitionPredictor
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from surya.table_rec import TableRecPredictor
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configure_logging()
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def load_predictors(
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device: str | torch.device | None = None, dtype: torch.dtype | str | None = None
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) -> Dict[str, BasePredictor]:
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return {
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"layout": LayoutPredictor(device=device, dtype=dtype),
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"ocr_error": OCRErrorPredictor(device=device, dtype=dtype),
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"recognition": RecognitionPredictor(device=device, dtype=dtype),
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"detection": DetectionPredictor(device=device, dtype=dtype),
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"table_rec": TableRecPredictor(device=device, dtype=dtype),
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}
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