Delete app.py

app.py

@@ -1,59 +0,0 @@
-import os
-import gradio as gr
-import spaces
-from transformers import AutoModelForCausalLM, AutoProcessor, MarianMTModel, MarianTokenizer
-import torch
-from PIL import Image
-import subprocess
-
-# 허깅페이스 API 토큰 환경 변수에서 가져오기
-hf_token = os.getenv("HF_TOKEN")
-
-# 필요한 외부 패키지 설치
-subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
-
-# 번역 모델과 토크나이저 로드
-translator_model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-en-ko")
-translator_tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-ko")
-
-def translate_to_korean(text):
-    # 영어 텍스트를 한국어로 번역
-    inputs = translator_tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)
-    outputs = translator_model.generate(**inputs)
-    translated_text = translator_tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return translated_text
-
-@spaces.GPU
-def run_example(image, text_input=None, model_id="microsoft/Phi-3.5-vision-instruct"):
-    # 모델 로드 시 허깅페이스 토큰 사용
-    model = AutoModelForCausalLM.from_pretrained(model_id, use_auth_token=hf_token)
-    processor = AutoProcessor.from_pretrained(model_id, use_auth_token=hf_token)
-
-    prompt = f"{user_prompt}\n{text_input}{prompt_suffix}{assistant_prompt}"
-    image = Image.fromarray(image).convert("RGB")
-
-    inputs = processor(prompt, image, return_tensors="pt").to("cuda:0")
-    generate_ids = model.generate(**inputs, max_new_tokens=1000, eos_token_id=processor.tokenizer.eos_token_id)
-    generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
-    response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
-
-    # 번역된 텍스트 추가
-    translated_response = translate_to_korean(response)
-    return response, translated_response
-
-# Gradio 인터페이스 설정
-with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo:
-    with gr.Tab(label="Phi-3.5 Input"):
-        with gr.Row():
-            with gr.Column():
-                input_img = gr.Image(label="Input Picture")
-                model_selector = gr.Dropdown(choices=[model_id], label="Model", value=model_id)
-                text_input = gr.Textbox(label="Question")
-                submit_btn = gr.Button(value="Submit")
-            with gr.Column():
-                output_text = gr.Textbox(label="Output Text")
-                translated_text = gr.Textbox(label="Translated Text (Korean)")
-
-        submit_btn.click(run_example, [input_img, text_input, model_selector], [output_text, translated_text])
-
-demo.launch(debug=True)