diff --git a/__pycache__/main.cpython-310.pyc b/__pycache__/main.cpython-310.pyc
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index 0000000..7c691ad
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diff --git a/main.py b/main.py
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+++ b/main.py
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+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from typing import List
+import os
+from paddlenlp import Taskflow
+import logging
+
+# FastAPI 애플리케이션 초기화
+app = FastAPI()
+
+# PaddleNLP Taskflow 번역기 및 형태소 분석기 초기화
+machine_translation = Taskflow("text2text_generation", source_lang="zh", target_lang="ko", from_hf_hub=True)
+word_segmentation = Taskflow("word_segmentation")
+
+# 로거 설정
+logger = logging.getLogger('default_logger')
+
+# Pydantic 모델 정의 (API 요청과 응답을 위한 데이터 구조)
+class OptionRequest(BaseModel):
+    options: List[str]
+
+class OptionResponse(BaseModel):
+    translated_options: List[str]
+
+# 특수문자와 대체할 문자 정의
+allowed_special_chars = "!$~()._-=+/"
+special_char_replacements = {
+    "*" : "X",  # '*' 특수문자를 'X'로 대체
+    "【" : "(",
+    "】" : ")",
+    "[" : "(",
+    "]" : ")",
+    "," : ".",
+}
+
+# 옵션명을 처리하고 번역하는 API
+@app.post("/process_options", response_model=OptionResponse)
+async def process_options(option_request: OptionRequest):
+    options = option_request.options
+
+    # 1. 특수문자 처리
+    cleaned_option_names = [clean_special_characters(option, allowed_special_chars, special_char_replacements) for option in options]
+    logger.debug(f"특수문자 처리 후 옵션명: {cleaned_option_names}")
+    
+    # 2. 옵션명 형태소 분석
+    segmented_options = segment_option_names(cleaned_option_names)
+    logger.debug(f"형태소 분석 결과: {segmented_options}")
+    
+    # 3. 공통 단어 제거
+    unique_options = remove_common_words(segmented_options)
+    logger.debug(f"공통 단어 제거 후 고유한 옵션: {unique_options}")
+    
+    # 4. 번역
+    translated_options = translate_options(unique_options)
+    logger.debug(f"번역된 옵션: {translated_options}")
+    
+    return OptionResponse(translated_options=translated_options)
+
+# 특수문자 처리 함수
+def clean_special_characters(option_name, allowed_special_chars, special_char_replacements):
+    for char, replacement in special_char_replacements.items():
+        option_name = option_name.replace(char, replacement)
+    cleaned_name = ''.join([char for char in option_name if char.isalnum() or char in allowed_special_chars or char == ' '])
+    return cleaned_name
+
+# 형태소 분석 함수
+def segment_option_names(option_names):
+    segmented_options = []
+    for option in option_names:
+        segmented_words = word_segmentation(option)
+        segmented_options.append(segmented_words)
+    return segmented_options
+
+# 공통 단어 제거 함수
+def remove_common_words(segmented_options):
+    word_sets = [set(option) for option in segmented_options]
+    common_words = set.intersection(*word_sets)
+    unique_options = [[word for word in option if word not in common_words] for option in segmented_options]
+    return unique_options
+
+# 번역 함수
+def translate_options(unique_options):
+    translated_options = []
+    for option in unique_options:
+        translated_text = machine_translation(' '.join(option))
+        translated_options.append(translated_text)
+    return translated_options
diff --git a/requirements.txt b/requirements.txt
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+++ b/requirements.txt
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+paddlepaddle
+paddleocr
+paddlenlp
+uvicorn
+guvicorn
+fastapi
diff --git a/server.py b/server.py
deleted file mode 100755
index 8949525..0000000
--- a/server.py
+++ /dev/null
@@ -1,15 +0,0 @@
-# server.py
-from fastapi import FastAPI, Request
-from paddlenlp import Taskflow
-
-app = FastAPI()
-
-# 모델 로드 (ChatGLM 등 대형 모델)
-machine_translation = Taskflow("text2text_generation", source_lang="zh", target_lang="ko")
-
-@app.post("/translate")
-async def translate(request: Request):
-    body = await request.json()
-    text = body["text"]
-    result = machine_translation(text)
-    return {"translated_text": result}