diff --git a/apps/pre-processing-service/app/core/config.py b/apps/pre-processing-service/app/core/config.py
index ed54cc69..69e29d35 100644
--- a/apps/pre-processing-service/app/core/config.py
+++ b/apps/pre-processing-service/app/core/config.py
@@ -80,6 +80,9 @@ class BaseSettingsConfig(BaseSettings):
     # MeCab 사전 경로 (자동 감지)
     mecab_path: Optional[str] = None
 
+    # 테스트/추가용 필드
+    openai_api_key: Optional[str] = None  # << 이 부분 추가
+
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
 
diff --git a/apps/pre-processing-service/app/service/keyword_service.py b/apps/pre-processing-service/app/service/keyword_service.py
index 575767ee..f8065fa3 100644
--- a/apps/pre-processing-service/app/service/keyword_service.py
+++ b/apps/pre-processing-service/app/service/keyword_service.py
@@ -1,4 +1,3 @@
-# Pydantic 모델을 가져오기 위해 schemas 파일 import
 import json
 import random
 
diff --git a/apps/pre-processing-service/app/service/product_blog_posting_service.py b/apps/pre-processing-service/app/service/product_blog_posting_service.py
new file mode 100644
index 00000000..129c4666
--- /dev/null
+++ b/apps/pre-processing-service/app/service/product_blog_posting_service.py
@@ -0,0 +1,387 @@
+import json
+import logging
+import os
+from datetime import datetime
+from typing import Dict, List, Optional, Any
+from dataclasses import dataclass
+from enum import Enum
+
+from openai import OpenAI
+from dotenv import load_dotenv
+
+from app.service.blog.blogger_blog_post_adapter import BloggerBlogPostAdapter
+from app.errors.BlogPostingException import *
+
+# 환경변수 로드
+load_dotenv(".env.dev")
+
+client = OpenAI()
+
+
+class PostingStatus(Enum):
+    PENDING = "pending"
+    PROCESSING = "processing"
+    SUCCESS = "success"
+    FAILED = "failed"
+    RETRY = "retry"
+
+
+@dataclass
+class ProductData:
+    """크롤링된 상품 데이터 모델"""
+
+    tag: str
+    product_url: str
+    title: str
+    price: int
+    rating: float
+    options: List[Dict[str, Any]]
+    material_info: Dict[str, str]
+    product_images: List[str]
+    crawled_at: str
+
+    @classmethod
+    def from_dict(cls, data: Dict) -> "ProductData":
+        """딕셔너리에서 ProductData 객체 생성"""
+        product_detail = data.get("product_detail", {})
+        return cls(
+            tag=data.get("tag", ""),
+            product_url=product_detail.get("url", ""),
+            title=product_detail.get("title", ""),
+            price=product_detail.get("price", 0),
+            rating=product_detail.get("rating", 0.0),
+            options=product_detail.get("options", []),
+            material_info=product_detail.get("material_info", {}),
+            product_images=product_detail.get("product_images", []),
+            crawled_at=data.get("crawled_at", ""),
+        )
+
+
+@dataclass
+class BlogPostContent:
+    """생성된 블로그 포스트 콘텐츠"""
+
+    title: str
+    content: str
+    tags: List[str]
+
+
+@dataclass
+class BlogContentRequest:
+    """블로그 콘텐츠 생성 요청"""
+
+    content_style: str = "informative"  # "informative", "promotional", "review"
+    target_keywords: List[str] = None
+    include_pricing: bool = True
+    include_specifications: bool = True
+    content_length: str = "medium"  # "short", "medium", "long"
+
+
+class ProductContentGenerator:
+    """GPT를 활용한 상품 블로그 콘텐츠 생성"""
+
+    def __init__(self):
+        # 환경변수에서 OpenAI API 키 로드
+        self.openai_api_key = os.getenv("OPENAI_API_KEY")
+        if not self.openai_api_key:
+            raise ValueError("OPENAI_API_KEY가 .env.dev 파일에 설정되지 않았습니다.")
+
+        client.api_key = self.openai_api_key
+
+    def generate_blog_content(
+        self, product_data: ProductData, request: BlogContentRequest
+    ) -> BlogPostContent:
+        """상품 데이터를 기반으로 블로그 콘텐츠 생성"""
+
+        # 1. 상품 정보 정리
+        product_info = self._format_product_info(product_data, request)
+
+        # 2. 프롬프트 생성
+        prompt = self._create_blog_prompt(product_info, request)
+
+        # 3. GPT를 통한 콘텐츠 생성
+        try:
+
+            response = client.chat.completions.create(
+                model="gpt-4o-mini",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": "당신은 전문적인 블로그 콘텐츠 작성자입니다. 상품 리뷰와 정보성 콘텐츠를 매력적이고 SEO 친화적으로 작성합니다.",
+                    },
+                    {"role": "user", "content": prompt},
+                ],
+                temperature=0.7,
+                max_tokens=2000,
+            )
+
+            generated_content = response.choices[0].message.content
+
+            # 4. 콘텐츠 파싱 및 구조화
+            return self._parse_generated_content(
+                generated_content, product_data, request
+            )
+
+        except Exception as e:
+            logging.error(f"콘텐츠 생성 실패: {e}")
+            return self._create_fallback_content(product_data, request)
+
+    def _format_product_info(
+        self, product_data: ProductData, request: BlogContentRequest
+    ) -> str:
+        """상품 정보를 텍스트로 포맷팅"""
+        info_parts = [
+            f"상품명: {product_data.title}",
+        ]
+
+        # 가격 정보 추가
+        if request.include_pricing and product_data.price:
+            info_parts.append(f"가격: {product_data.price:,}원")
+
+        # 평점 정보 추가
+        if product_data.rating:
+            info_parts.append(f"평점: {product_data.rating}/5.0")
+
+        # 사양 정보 추가
+        if request.include_specifications and product_data.material_info:
+            info_parts.append("\n상품 사양:")
+            for key, value in product_data.material_info.items():
+                info_parts.append(f"- {key}: {value}")
+
+        # 옵션 정보 추가
+        if product_data.options:
+            info_parts.append(f"\n구매 옵션 ({len(product_data.options)}개):")
+            for i, option in enumerate(product_data.options[:5], 1):  # 처음 5개만
+                info_parts.append(f"{i}. {option.get('name', 'N/A')}")
+
+        # 구매 링크
+        if product_data.product_url:
+            info_parts.append(f"\n구매 링크: {product_data.product_url}")
+
+        return "\n".join(info_parts)
+
+    def _create_blog_prompt(
+        self, product_info: str, request: BlogContentRequest
+    ) -> str:
+        """블로그 작성용 프롬프트 생성"""
+
+        # 스타일별 가이드라인
+        style_guidelines = {
+            "informative": "객관적이고 상세한 정보 제공 중심으로, 독자가 제품을 이해할 수 있도록 전문적으로 작성",
+            "promotional": "제품의 장점과 매력을 강조하며, 구매 의욕을 자극할 수 있도록 매력적으로 작성",
+            "review": "실제 사용 경험을 바탕으로 한 솔직한 평가와 추천 중심으로 작성",
+        }
+
+        # 길이별 가이드라인
+        length_guidelines = {
+            "short": "800자 내외의 간결한 내용",
+            "medium": "1200자 내외의 적당한 길이",
+            "long": "1500자 이상의 상세한 내용",
+        }
+
+        style_guide = style_guidelines.get(
+            request.content_style, style_guidelines["informative"]
+        )
+        length_guide = length_guidelines.get(
+            request.content_length, length_guidelines["medium"]
+        )
+
+        # 키워드 정보
+        keywords_text = ""
+        if request.target_keywords:
+            keywords_text = f"\n포함할 키워드: {', '.join(request.target_keywords)}"
+
+        prompt = f"""
+다음 상품 정보를 바탕으로 매력적인 블로그 포스트를 작성해주세요.
+
+상품 정보:
+{product_info}
+
+작성 가이드라인:
+- 스타일: {style_guide}
+- 길이: {length_guide}
+- 톤: 친근하면서도 신뢰할 수 있는, 정보 제공 중심{keywords_text}
+
+작성 요구사항:
+1. SEO 친화적이고 클릭하고 싶은 매력적인 제목
+2. 독자의 관심을 끄는 도입부
+3. 상품의 핵심 특징과 장점을 구체적으로 설명
+4. 실제 사용 시나리오나 활용 팁
+5. 구매 결정에 도움이 되는 정보
+
+⚠️ 주의:
+- 절대로 마지막에 '이 HTML 구조는…' 같은 자기 평가 문장을 추가하지 마세요.
+- 출력 시 ```나 ```html 같은 코드 블록 구문을 포함하지 마세요.
+- 오직 HTML 태그만 사용하여 구조화된 콘텐츠를 작성해주세요.
+(예: <h2>, <h3>, <p>, <ul>, <li> 등)
+"""
+
+        return prompt
+
+    def _parse_generated_content(
+        self, content: str, product_data: ProductData, request: BlogContentRequest
+    ) -> BlogPostContent:
+        """생성된 콘텐츠를 파싱하여 구조화"""
+
+        # 제목 추출 (첫 번째 h1이나 강조된 줄)
+        lines = content.strip().split("\n")
+        title = product_data.title  # 기본값
+
+        for line in lines[:10]:  # 처음 10줄에서 제목 찾기
+            clean_line = (
+                line.strip().replace("#", "").replace("<h1>", "").replace("</h1>", "")
+            )
+            if (
+                clean_line
+                and len(clean_line) > 5
+                and ("제목" in line or "<h1>" in line or line.startswith("#"))
+            ):
+                title = clean_line
+                break
+            elif clean_line and len(clean_line) > 10 and len(clean_line) < 100:
+                # 적당한 길이의 첫 번째 줄을 제목으로
+                title = clean_line
+                break
+
+        # 태그 생성
+        tags = self._generate_tags_from_product(product_data, request)
+
+        return BlogPostContent(title=title, content=content, tags=tags)
+
+    def _generate_tags_from_product(
+        self, product_data: ProductData, request: BlogContentRequest
+    ) -> List[str]:
+        """상품 정보 기반 태그 생성"""
+        tags = []
+
+        # 사용자 지정 키워드가 있으면 우선 추가
+        if request.target_keywords:
+            tags.extend(request.target_keywords[:5])
+
+        # 기본 태그 추가
+        if product_data.tag:
+            tags.append(product_data.tag)
+
+        # 제품 타입 추론해서 태그 추가
+        title_lower = product_data.title.lower()
+        if any(word in title_lower for word in ["iphone", "아이폰", "phone"]):
+            tags.extend(["아이폰", "스마트폰"])
+        if any(word in title_lower for word in ["필름", "보호", "강화"]):
+            tags.extend(["보호필름", "강화필름"])
+        if any(word in title_lower for word in ["케이스", "커버"]):
+            tags.extend(["폰케이스", "액세서리"])
+
+        # 재료 정보에서 태그 생성
+        if product_data.material_info:
+            for key, value in product_data.material_info.items():
+                if value and len(value.strip()) <= 20:  # 너무 긴 값은 제외
+                    clean_value = value.strip()
+                    if clean_value not in tags:
+                        tags.append(clean_value)
+
+        # 중복 제거 및 개수 제한
+        unique_tags = []
+        for tag in tags:
+            if tag not in unique_tags and len(unique_tags) < 10:
+                unique_tags.append(tag)
+
+        return unique_tags
+
+    def _create_fallback_content(
+        self, product_data: ProductData, request: BlogContentRequest
+    ) -> BlogPostContent:
+        """콘텐츠 생성 실패 시 대안 콘텐츠 생성"""
+        title = f"{product_data.title} - 상품 정보 및 구매 가이드"
+
+        content = f"""
+<h1>{product_data.title}</h1>
+
+<h2>상품 소개</h2>
+<p>{product_data.title}에 대한 상세한 정보를 소개합니다.</p>
+
+<h2>가격 정보</h2>
+<p>판매가: <strong>{product_data.price:,}원</strong></p>
+"""
+
+        if product_data.material_info:
+            content += "<h2>상품 사양</h2>\n<ul>\n"
+            for key, value in product_data.material_info.items():
+                content += f"<li><strong>{key}:</strong> {value}</li>\n"
+            content += "</ul>\n"
+
+        if product_data.options:
+            content += f"<h2>구매 옵션 ({len(product_data.options)}가지)</h2>\n<ul>\n"
+            for option in product_data.options[:5]:
+                content += f"<li>{option.get('name', 'N/A')}</li>\n"
+            content += "</ul>\n"
+
+        content += f"""
+<h2>구매 안내</h2>
+<p>상품 구매는 <a href="{product_data.product_url}" target="_blank">여기</a>에서 가능합니다.</p>
+"""
+
+        return BlogPostContent(
+            title=title,
+            content=content,
+            tags=[product_data.tag] if product_data.tag else ["상품정보"],
+        )
+
+
+class ProductBlogPostingService:
+    """상품 데이터를 Blogger에 포스팅하는 메인 서비스"""
+
+    def __init__(self):
+        self.content_generator = ProductContentGenerator()
+        self.blogger_service = BloggerBlogPostAdapter()
+
+    def post_product_to_blogger(
+        self, product_data: ProductData, request: BlogContentRequest
+    ) -> dict:
+        """상품 데이터를 Blogger에 포스팅"""
+        try:
+            # 1. GPT를 통한 콘텐츠 생성
+            blog_content = self.content_generator.generate_blog_content(
+                product_data, request
+            )
+
+            # 2. Blogger에 포스팅
+            self.blogger_service.post_content(
+                title=blog_content.title,
+                content=blog_content.content,
+                tags=blog_content.tags,
+            )
+
+            # 3. 성공 결과 반환
+            return {
+                "status": "success",
+                "platform": "blogger",
+                "title": blog_content.title,
+                "tags": blog_content.tags,
+                "posted_at": datetime.now().isoformat(),
+                "product_tag": product_data.tag,
+            }
+
+        except Exception as e:
+            logging.error(f"Blogger 포스팅 실패: {e}")
+            # ProductData 객체 기준으로 처리
+            return {
+                "status": "failed",
+                "error": str(e),
+                "platform": "blogger",
+                "attempted_at": datetime.now().isoformat(),
+                "product_tag": getattr(product_data, "tag", "unknown"),
+            }
+
+    # def batch_post_products(self, products_data: List[Dict], request: BlogContentRequest) -> List[Dict[str, Any]]:
+    #     """여러 상품을 일괄 포스팅"""
+    #     results = []
+    #
+    #     for product_data in products_data:
+    #         result = self.post_product_to_blogger(product_data, request)
+    #         results.append(result)
+    #
+    #         # API 호출 제한을 고려한 딜레이
+    #         import time
+    #         time.sleep(3)  # 3초 대기
+    #
+    #     return results
diff --git a/apps/pre-processing-service/app/test/test_product_blog_posting_service.py b/apps/pre-processing-service/app/test/test_product_blog_posting_service.py
new file mode 100644
index 00000000..c5b1efde
--- /dev/null
+++ b/apps/pre-processing-service/app/test/test_product_blog_posting_service.py
@@ -0,0 +1,87 @@
+import pytest
+from app.service.product_blog_posting_service import (
+    ProductBlogPostingService,
+    BlogContentRequest,
+    ProductData,
+)
+
+# 샘플 데이터
+sample_product_data = {
+    "tag": "test001",
+    "product_url": "https://ssadagu.kr/shop/view.php?platform=1688&num_iid=902500949447",
+    "status": "success",
+    "product_detail": {
+        "url": "https://ssadagu.kr/shop/view.php?platform=1688&num_iid=902500949447",
+        "title": "코닝 적용 가능한 애플 13 강화 필름 iphone16/15promax 휴대 전화 필름 애플 11 안티-peep 및 먼지없는 빈",
+        "price": 430,
+        "rating": 5.0,
+        "options": [
+            {"name": "먼지 없는 창고 2차 필름 [코닝글라스 방폭丨초투명]", "stock": 0},
+            {
+                "name": "먼지 없는 창고 2차 필름 [코닝글라스 방폭丨훔쳐보기 방지]",
+                "stock": 0,
+            },
+        ],
+        "material_info": {
+            "상표": "다른",
+            "재료": "강화 유리",
+            "필름 종류": "전막",
+            "크기": "애플 16프로맥스( 6.9inch )",
+            "적용 모델": "iPhone13 Pro Max",
+        },
+        "product_images": [],
+    },
+    "crawled_at": "2025-09-16 11:49:24",
+}
+
+
+@pytest.fixture
+def blog_service():
+    return ProductBlogPostingService()
+
+
+def test_generate_blog_content(blog_service):
+    """GPT를 통한 블로그 콘텐츠 생성 테스트"""
+    request = BlogContentRequest(
+        content_style="informative",
+        target_keywords=["아이폰", "강화필름", "보호필름", "스마트폰액세서리"],
+        include_pricing=True,
+        content_length="medium",
+    )
+
+    product_obj = ProductData.from_dict(sample_product_data)
+
+    # 순수 콘텐츠 생성만 테스트
+    blog_content = blog_service.content_generator.generate_blog_content(
+        product_obj, request
+    )
+
+    assert blog_content.title
+    assert "<h2>" in blog_content.content
+    assert len(blog_content.tags) > 0
+
+
+def test_post_product_to_blogger(blog_service, monkeypatch):
+    """Blogger 포스팅 테스트 (실제 API 호출을 막고 mock)"""
+
+    class MockBloggerAdapter:
+        def post_content(self, title, content, tags):
+            return {"mock": True}
+
+    monkeypatch.setattr(blog_service, "blogger_service", MockBloggerAdapter())
+
+    request = BlogContentRequest(
+        content_style="informative",
+        target_keywords=["아이폰", "강화필름", "보호필름", "스마트폰액세서리"],
+        include_pricing=True,
+        content_length="medium",
+    )
+
+    product_obj = ProductData.from_dict(sample_product_data)
+
+    result = blog_service.post_product_to_blogger(product_obj, request)
+
+    assert result["status"] == "success"
+    assert result["platform"] == "blogger"
+    assert "title" in result
+    assert "tags" in result
diff --git a/apps/pre-processing-service/app/utils/crawling_util.py b/apps/pre-processing-service/app/utils/crawling_util.py
index 315df32a..5e50528d 100644
--- a/apps/pre-processing-service/app/utils/crawling_util.py
+++ b/apps/pre-processing-service/app/utils/crawling_util.py
@@ -10,7 +10,7 @@ class CrawlingUtil:
     블로그 포스팅과 상품 크롤링 모두 지원
     """
 
-    def __init__(self, headless: bool = False, for_blog_posting: bool = False):
+    def __init__(self, headless: bool = True, for_blog_posting: bool = False):
         """
         :param headless: 헤드리스 모드 사용 여부
         :param for_blog_posting: 블로그 포스팅용 설정 사용 여부
diff --git a/apps/pre-processing-service/poetry.lock b/apps/pre-processing-service/poetry.lock
index 49d36b65..d47e6783 100644
--- a/apps/pre-processing-service/poetry.lock
+++ b/apps/pre-processing-service/poetry.lock
@@ -473,6 +473,18 @@ docs = ["docutils"]
 pg = ["PyGreSQL (>=5)"]
 tests = ["pytest (>=7)", "ruff"]
 
+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+groups = ["main"]
+files = [
+    {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+    {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
 [[package]]
 name = "fastapi"
 version = "0.116.1"
@@ -856,6 +868,94 @@ files = [
     {file = "iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7"},
 ]
 
+[[package]]
+name = "jiter"
+version = "0.11.0"
+description = "Fast iterable JSON parser."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+]
+
 [[package]]
 name = "joblib"
 version = "1.5.2"
@@ -1107,6 +1207,34 @@ packaging = "*"
 protobuf = "*"
 sympy = "*"
 
+[[package]]
+name = "openai"
+version = "1.107.3"
+description = "The official Python library for the openai API"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "openai-1.107.3-py3-none-any.whl", hash = "sha256:4ca54a847235ac04c6320da70fdc06b62d71439de9ec0aa40d5690c3064d4025"},
+    {file = "openai-1.107.3.tar.gz", hash = "sha256:69bb8032b05c5f00f7660e422f70f9aabc94793b9a30c5f899360ed21e46314f"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+jiter = ">=0.4.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tqdm = ">4"
+typing-extensions = ">=4.11,<5"
+
+[package.extras]
+aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"]
+datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
+realtime = ["websockets (>=13,<16)"]
+voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"]
+
 [[package]]
 name = "outcome"
 version = "1.3.0.post0"
@@ -1181,14 +1309,14 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "poetry-core"
-version = "2.1.3"
+version = "2.2.0"
 description = "Poetry PEP 517 Build Backend"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "poetry_core-2.1.3-py3-none-any.whl", hash = "sha256:2c704f05016698a54ca1d327f46ce2426d72eaca6ff614132c8477c292266771"},
-    {file = "poetry_core-2.1.3.tar.gz", hash = "sha256:0522a015477ed622c89aad56a477a57813cace0c8e7ff2a2906b7ef4a2e296a4"},
+    {file = "poetry_core-2.2.0-py3-none-any.whl", hash = "sha256:0edea81d07e88cbd407369eef753c722da8ff1338f554788dc04636e756318fc"},
+    {file = "poetry_core-2.2.0.tar.gz", hash = "sha256:b4033b71b99717a942030e074fec7e3082e5fde7a8ed10f02cd2413bdf940b1f"},
 ]
 
 [[package]]
@@ -1348,14 +1476,14 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.11.7"
+version = "2.11.9"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "pydantic-2.11.7-py3-none-any.whl", hash = "sha256:dde5df002701f6de26248661f6835bbe296a47bf73990135c7d07ce741b9623b"},
-    {file = "pydantic-2.11.7.tar.gz", hash = "sha256:d989c3c6cb79469287b1569f7447a17848c998458d49ebe294e975b9baf0f0db"},
+    {file = "pydantic-2.11.9-py3-none-any.whl", hash = "sha256:c42dd626f5cfc1c6950ce6205ea58c93efa406da65f479dcb4029d5934857da2"},
+    {file = "pydantic-2.11.9.tar.gz", hash = "sha256:6b8ffda597a14812a7975c90b82a8a2e777d9257aba3453f973acd3c032a18e2"},
 ]
 
 [package.dependencies]
@@ -1537,14 +1665,14 @@ rsa = ["cryptography"]
 
 [[package]]
 name = "pyparsing"
-version = "3.2.3"
-description = "pyparsing module - Classes and methods to define and execute parsing grammars"
+version = "3.2.4"
+description = "pyparsing - Classes and methods to define and execute parsing grammars"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "pyparsing-3.2.3-py3-none-any.whl", hash = "sha256:a749938e02d6fd0b59b356ca504a24982314bb090c383e3cf201c95ef7e2bfcf"},
-    {file = "pyparsing-3.2.3.tar.gz", hash = "sha256:b9c13f1ab8b3b542f72e28f634bad4de758ab3ce4546e4301970ad6fa77c38be"},
+    {file = "pyparsing-3.2.4-py3-none-any.whl", hash = "sha256:91d0fcde680d42cd031daf3a6ba20da3107e08a75de50da58360e7d94ab24d36"},
+    {file = "pyparsing-3.2.4.tar.gz", hash = "sha256:fff89494f45559d0f2ce46613b419f632bbb6afbdaed49696d322bcf98a58e99"},
 ]
 
 [package.extras]
@@ -2019,6 +2147,28 @@ files = [
     {file = "threadpoolctl-3.6.0.tar.gz", hash = "sha256:8ab8b4aa3491d812b623328249fab5302a68d2d71745c8a4c719a2fcaba9f44e"},
 ]
 
+[[package]]
+name = "tqdm"
+version = "4.67.1"
+description = "Fast, Extensible Progress Meter"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"},
+    {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["nbval", "pytest (>=6)", "pytest-asyncio (>=0.24)", "pytest-cov", "pytest-timeout"]
+discord = ["requests"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
 [[package]]
 name = "trio"
 version = "0.30.0"
@@ -2186,4 +2336,4 @@ h11 = ">=0.9.0,<1"
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.11,<3.14"
-content-hash = "9ca2813b1931948bd0600aa974faba9311a7cf00ea632ea4db5f9fcc80ebc518"
+content-hash = "a2a9a376c855a2599db8f932f42029ee9f016babdf0f004cb53690caa8f5a330"
diff --git a/apps/pre-processing-service/pyproject.toml b/apps/pre-processing-service/pyproject.toml
index f8cabbff..42997650 100644
--- a/apps/pre-processing-service/pyproject.toml
+++ b/apps/pre-processing-service/pyproject.toml
@@ -34,6 +34,7 @@ google-api-python-client = "^2.181.0"
 poetry-core=">=2.1.3,<3.0.0"
 dbutils=">=3.1.2,<4.0.0"
 onnxruntime = "^1.22.1"
+openai = "^1.107.3"
 
 [build-system]
 requires = ["poetry-core>=2.0.0,<3.0.0"]