app.py

import gradio as gr
from transformers import AutoModel, AutoTokenizer
from PIL import Image
import torch
import os

model_name = "deepseek-ai/DeepSeek-OCR"

print("Loading tokenizer...")
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)

print("Loading model...")
model = AutoModel.from_pretrained(
    model_name,
    trust_remote_code=True,
    use_safetensors=True,
    low_cpu_mem_usage=True
).cuda().eval()

def ocr_infer(image):
    image.save("input.png")

    prompt = "<image>\nFree OCR."

    result = model.infer(
        tokenizer,
        prompt=prompt,
        image_file="input.png",
        output_path=".",
        image_size=640,
        crop_mode=True
    )

    return result["text"]

demo = gr.Interface(
    fn=ocr_infer,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="DeepSeek-OCR (HF Space)",
    description="GPU OCR API"
)

demo.launch()