import gradio as gr import requests import json import base64 from PIL import Image import io import os css = """ footer { visibility: hidden; } """ app_id = os.getenv("app_id") app_key = os.getenv("app_key") app_url = os.getenv("app_url") def get_latex_from_image_all_formats(image): buffered = io.BytesIO() image.save(buffered, format="JPEG") image_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8') headers = { "app_id": app_id, "app_key": app_key, "Content-Type": "application/json" } # 해당 부분을 ["text"]로 변경하여 formats를 리스트로 설정 data = { "src": f"data:image/jpeg;base64,{image_base64}", "formats": ["text"] } response = requests.post(app_url, headers=headers, json=data) response.raise_for_status() result = response.json() # formats_results 변수는 사용하지 않으므로 제거하여 코드를 단순화 return result def build_gradio_app(css=css): demo = gr.Blocks(css=css) with demo: gr.Markdown("# ArXivGPT LaTeX Tool") gr.Markdown("This comprehensive solution...") image_input = gr.Image(type="pil", label="이미지 업로드") submit_button = gr.Button("변환하기") examples = gr.Examples(examples=[["ko.png"], ["en.png"], ["hand.jpg"]], inputs=image_input, fn=process_and_output, outputs=output_text) output_text = gr.Textbox(label="결과") latex_iframe = gr.HTML(value='', elem_id="latex_iframe") def process_and_output(image): latex_result = get_latex_from_image_all_formats(image) text_result = latex_result.get("text", "No result") return text_result submit_button.click(fn=process_and_output, inputs=image_input, outputs=output_text) return demo if __name__ == "__main__": app = build_gradio_app() app.launch()