import gradio as gr
import requests
import json
import os
from datetime import datetime, timedelta
from concurrent.futures import ThreadPoolExecutor, as_completed
from functools import lru_cache
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
from openai import OpenAI
from bs4 import BeautifulSoup
import re
import pathlib
import sqlite3
import pytz

# 한국 기업 리스트
KOREAN_COMPANIES = [
    "NVIDIA",
    "ALPHABET",
    "APPLE",
    "TESLA",
    "AMAZON",
    "MICROSOFT", 
    "META", 
    "INTEL",
    "SAMSUNG",
    "HYNIX",
    "BITCOIN",
    "crypto",
    "stock",
    "Economics",
    "Finance",
    "investing"
]

######################################################################
# 공통 함수: 시간 변환
######################################################################
def convert_to_seoul_time(timestamp_str):
    """
    주어진 'YYYY-MM-DD HH:MM:SS' 형태의 시각(UTC 기준 등)을
    'YYYY-MM-DD HH:MM:SS KST' 형태로 변환하여 반환.
    """
    try:
        dt = datetime.strptime(timestamp_str, '%Y-%m-%d %H:%M:%S')
        seoul_tz = pytz.timezone('Asia/Seoul')
        seoul_time = seoul_tz.localize(dt)
        return seoul_time.strftime('%Y-%m-%d %H:%M:%S KST')
    except Exception as e:
        print(f"시간 변환 오류: {str(e)}")
        return timestamp_str

######################################################################
# 공통 함수: 감성 분석
######################################################################
def analyze_sentiment_batch(articles, client):
    """
    OpenAI API를 통해, 뉴스 기사들의 제목+내용을 종합하여 감성 분석을 수행.
    - 결과를 한국어로 작성하도록 프롬프트 내에 명시.
    """
    try:
        # 기사들의 title/snippet 결합
        combined_text = "\n\n".join([
            f"제목: {article.get('title', '')}\n내용: {article.get('snippet', '')}"
            for article in articles
        ])
        
        # 한국어로 작성할 것을 유도하는 문구
        prompt = f"""다음 뉴스 모음에 대해 전반적인 감성 분석을 수행하세요. (한국어로 작성하세요)

뉴스 내용:
{combined_text}

다음 형식으로 분석해주세요:
1. 전반적 감성: [긍정/부정/중립]
2. 주요 긍정적 요소:
   - [항목1]
   - [항목2]
3. 주요 부정적 요소:
   - [항목1]
   - [항목2]
4. 종합 평가: [상세 설명]
"""

        response = client.chat.completions.create(
            model="CohereForAI/c4ai-command-r-plus-08-2024",
            messages=[{"role": "user", "content": prompt}],
            temperature=0.3,
            max_tokens=1000
        )
        
        return response.choices[0].message.content
    except Exception as e:
        return f"감성 분석 실패: {str(e)}"

######################################################################
# DB 초기화 및 입출력
######################################################################
def init_db():
    """
    SQLite DB 파일(search_results.db)이 없으면 생성,
    'searches' 테이블이 없으면 생성
    """
    db_path = pathlib.Path("search_results.db")
    conn = sqlite3.connect(db_path)
    c = conn.cursor()
    c.execute('''CREATE TABLE IF NOT EXISTS searches
                 (id INTEGER PRIMARY KEY AUTOINCREMENT,
                  keyword TEXT,
                  country TEXT,
                  results TEXT,
                  timestamp DATETIME DEFAULT CURRENT_TIMESTAMP)''')
    conn.commit()
    conn.close()

def save_to_db(keyword, country, results):
    """
    (keyword, country)에 대한 결과(JSON)를 DB에 insert.
    """
    conn = sqlite3.connect("search_results.db")
    c = conn.cursor()

    seoul_tz = pytz.timezone('Asia/Seoul')
    now = datetime.now(seoul_tz)
    timestamp = now.strftime('%Y-%m-%d %H:%M:%S')
    
    c.execute("""INSERT INTO searches
                 (keyword, country, results, timestamp)
                 VALUES (?, ?, ?, ?)""",
              (keyword, country, json.dumps(results), timestamp))
    conn.commit()
    conn.close()

def load_from_db(keyword, country):
    """
    DB에서 (keyword, country)에 해당하는 가장 최근 기록을 로드
    - 성공시 (json.loads(...)된 results, KST 시간)
    - 실패시 (None, None)
    """
    conn = sqlite3.connect("search_results.db")
    c = conn.cursor()
    c.execute("""SELECT results, timestamp
                 FROM searches
                 WHERE keyword=? AND country=?
                 ORDER BY timestamp DESC
                 LIMIT 1""",
              (keyword, country))
    row = c.fetchone()
    conn.close()
    if row:
        return json.loads(row[0]), convert_to_seoul_time(row[1])
    return None, None

######################################################################
# SerpHouse API (검색 함수들)
######################################################################
API_KEY = os.getenv("SERPHOUSE_API_KEY")

def is_english(text):
    """
    텍스트가 전부 ASCII 범위면 True, 아니면 False
    """
    return all(ord(char) < 128 for char in text.replace(' ', '').replace('-', '').replace('_', ''))

@lru_cache(maxsize=100)
def translate_query(query, country):
    """
    query를 해당 country 언어로 번역
    """
    try:
        # 이미 영어면 그냥 반환
        if is_english(query):
            return query
        
        if country in COUNTRY_LANGUAGES:
            target_lang = COUNTRY_LANGUAGES[country]
            
            url = "https://translate.googleapis.com/translate_a/single"
            params = {
                "client": "gtx",
                "sl": "auto",
                "tl": target_lang,
                "dt": "t",
                "q": query
            }
            
            session = requests.Session()
            retries = Retry(total=3, backoff_factor=0.5)
            session.mount('https://', HTTPAdapter(max_retries=retries))
            
            resp = session.get(url, params=params, timeout=(5, 10))
            translated_text = resp.json()[0][0][0]
            return translated_text
            
        return query
    except Exception as e:
        print(f"번역 오류: {str(e)}")
        return query

def search_serphouse(query, country, page=1, num_result=10):
    """
    SerpHouse API 실시간 검색 -> 'news' (sort_by=date)
    """
    url = "https://api.serphouse.com/serp/live"
    
    now = datetime.utcnow()
    yesterday = now - timedelta(days=1)
    date_range = f"{yesterday.strftime('%Y-%m-%d')},{now.strftime('%Y-%m-%d')}"

    translated_query = translate_query(query, country)

    payload = {
        "data": {
            "q": translated_query,
            "domain": "google.com",
            "loc": COUNTRY_LOCATIONS.get(country, "United States"),
            "lang": COUNTRY_LANGUAGES.get(country, "en"),
            "device": "desktop",
            "serp_type": "news",
            "page": str(page),
            "num": "100",
            "date_range": date_range,
            "sort_by": "date"
        }
    }

    headers = {
        "accept": "application/json",
        "content-type": "application/json",
        "authorization": f"Bearer {API_KEY}"
    }

    try:
        session = requests.Session()
        retries = Retry(
            total=5,
            backoff_factor=1,
            status_forcelist=[429, 500, 502, 503, 504],
            allowed_methods=["POST"]
        )
        adapter = HTTPAdapter(max_retries=retries)
        session.mount('http://', adapter)
        session.mount('https://', adapter)
        
        resp = session.post(url, json=payload, headers=headers, timeout=(30, 30))
        resp.raise_for_status()

        # 응답 JSON
        return {
            "results": resp.json(),
            "translated_query": translated_query
        }
    except requests.exceptions.Timeout:
        return {
            "error": "검색 시간이 초과되었습니다. 잠시 후 다시 시도해주세요.",
            "translated_query": query
        }
    except requests.exceptions.RequestException as e:
        return {
            "error": f"검색 중 오류가 발생했습니다: {str(e)}",
            "translated_query": query
        }
    except Exception as e:
        return {
            "error": f"예기치 않은 오류가 발생했습니다: {str(e)}",
            "translated_query": query
        }

def format_results_from_raw(response_data):
    """
    SerpHouse API 응답을 (error_message, articles_list) 형태로 가공
    - 한국 도메인(kr, korea, etc) 제외
    - empty시 "검색 결과가 없습니다."
    """
    if "error" in response_data:
        return "Error: " + response_data["error"], []

    try:
        results = response_data["results"]
        translated_query = response_data["translated_query"]

        # 실제 뉴스 탭 결과
        news_results = results.get('results', {}).get('results', {}).get('news', [])
        if not news_results:
            return "검색 결과가 없습니다.", []
        
        # 한국어 제외
        korean_domains = [
            '.kr', 'korea', 'korean', 'yonhap', 'hankyung', 'chosun',
            'donga', 'joins', 'hani', 'koreatimes', 'koreaherald'
        ]
        korean_keywords = [
            'korea', 'korean', 'seoul', 'busan', 'incheon', 'daegu',
            'gwangju', 'daejeon', 'ulsan', 'sejong'
        ]

        filtered_articles = []
        for idx, result in enumerate(news_results, 1):
            url = result.get("url", result.get("link", "")).lower()
            title = result.get("title", "").lower()
            channel = result.get("channel", result.get("source", "")).lower()

            is_korean_content = (
                any(domain in url or domain in channel for domain in korean_domains)
                or any(keyword in title for keyword in korean_keywords)
            )
            if not is_korean_content:
                filtered_articles.append({
                    "index": idx,
                    "title": result.get("title", "제목 없음"),
                    "link": url,
                    "snippet": result.get("snippet", "내용 없음"),
                    "channel": result.get("channel", result.get("source", "알 수 없음")),
                    "time": result.get("time", result.get("date", "알 수 없는 시간")),
                    "image_url": result.get("img", result.get("thumbnail", "")),
                    "translated_query": translated_query
                })

        return "", filtered_articles
    except Exception as e:
        return f"결과 처리 중 오류 발생: {str(e)}", []

def serphouse_search(query, country):
    """
    전체 파이프라인 (search_serphouse -> format_results_from_raw)
    반환: (error_message, articles_list)
    """
    response_data = search_serphouse(query, country)
    return format_results_from_raw(response_data)

######################################################################
# 뉴스 기사 목록 -> Markdown
######################################################################
def display_results(articles):
    """
    기사 목록을 Markdown 문자열로 변환
    """
    output = ""
    for idx, article in enumerate(articles, 1):
        output += f"### {idx}. {article['title']}\n"
        output += f"출처: {article['channel']}\n"
        output += f"시간: {article['time']}\n"
        output += f"링크: {article['link']}\n"
        output += f"요약: {article['snippet']}\n\n"
    return output

######################################################################
# 한국 기업 목록 (이미 선언됨)
######################################################################

######################################################################
# 검색/출력 함수
######################################################################
def search_company(company):
    """
    미국(United States) 뉴스 검색 -> 감성분석(한국어) -> DB저장 -> Markdown 반환
    """
    error_message, articles = serphouse_search(company, "United States")
    if not error_message and articles:
        analysis = analyze_sentiment_batch(articles, client)
        data_to_store = {
            "articles": articles,
            "analysis": analysis
        }
        save_to_db(company, "United States", data_to_store)

        out = display_results(articles)
        out += f"\n\n### 분석 보고\n{analysis}\n"
        return out
    else:
        if error_message:
            return error_message
        return f"{company}에 대한 검색 결과가 없습니다."

def load_company(company):
    """
    DB에서 (company, United States) 검색 결과를 불러와 기사+분석 출력
    """
    loaded, ts = load_from_db(company, "United States")
    if loaded:
        articles = loaded.get("articles", [])
        analysis = loaded.get("analysis", "")
        out = f"### {company} 검색 결과\n저장 시간: {ts}\n\n"
        out += display_results(articles)
        out += f"\n\n### 분석 보고\n{analysis}\n"
        return out
    return f"{company}에 대한 저장된 결과가 없습니다."

######################################################################
# 통계 (EarnBOT 분석 리포트)
######################################################################
def show_stats():
    """
    KOREAN_COMPANIES 내 모든 기업의 가장 최근 DB 결과 -> 기사수, 분석, timestamp
    """
    conn = sqlite3.connect("search_results.db")
    c = conn.cursor()

    output = "## EarnBOT 분석 리포트\n\n"

    # DB에서 각 기업의 최신 저장 기록
    data_list = []
    for comp in KOREAN_COMPANIES:
        c.execute("""
            SELECT results, timestamp
            FROM searches
            WHERE keyword=?
            ORDER BY timestamp DESC
            LIMIT 1
        """, (comp,))
        row = c.fetchone()
        if row:
            results_json, ts = row
            data_list.append((comp, ts, results_json))
    conn.close()

    def analyze_data(item):
        comp, tstamp, json_str = item
        data_obj = json.loads(json_str)
        articles = data_obj.get("articles", [])
        analysis = data_obj.get("analysis", "")
        count_articles = len(articles)
        return (comp, tstamp, count_articles, analysis)

    results_list = []
    with ThreadPoolExecutor(max_workers=5) as executor:
        futures = [executor.submit(analyze_data, dl) for dl in data_list]
        for future in as_completed(futures):
            results_list.append(future.result())

    for comp, tstamp, count_articles, analysis in results_list:
        kst_time = convert_to_seoul_time(tstamp)
        output += f"### {comp}\n"
        output += f"- 마지막 업데이트: {kst_time}\n"
        output += f"- 저장된 기사 수: {count_articles}건\n\n"
        if analysis:
            output += "#### 뉴스 감성 분석\n"
            output += f"{analysis}\n\n"
        output += "---\n\n"

    return output

######################################################################
# 전체 검색+출력+분석 종합
######################################################################
def search_all_companies():
    """
    모든 기업 병렬 검색+분석 -> DB 저장 -> Markdown 출력
    """
    overall = "# [전체 검색 결과]\n\n"

    def do_search(comp):
        return comp, search_company(comp)

    with ThreadPoolExecutor(max_workers=5) as executor:
        futures = [executor.submit(do_search, c) for c in KOREAN_COMPANIES]
        for future in as_completed(futures):
            comp, res = future.result()
            overall += f"## {comp}\n"
            overall += res + "\n\n"

    return overall

def load_all_companies():
    """
    모든 기업 DB 로드 -> 기사+분석
    """
    overall = "# [전체 출력 결과]\n\n"
    for comp in KOREAN_COMPANIES:
        overall += f"## {comp}\n"
        overall += load_company(comp)
        overall += "\n"
    return overall

def full_summary_report():
    """
    1) 전체 검색+분석 => DB
    2) 전체 DB 로드
    3) 감성 분석 통계
    """
    search_text = search_all_companies()
    load_text = load_all_companies()
    stats_text = show_stats()

    combined = (
        "# 전체 분석 보고 요약\n\n"
        "아래 순서로 실행되었습니다:\n"
        "1. 모든 종목 검색(병렬) + 분석 => 2. 모든 종목 DB 결과 출력 => 3. 전체 감성 분석 통계\n\n"
        f"{search_text}\n\n"
        f"{load_text}\n\n"
        "## [전체 감성 분석 통계]\n\n"
        f"{stats_text}"
    )
    return combined

######################################################################
# 사용자 임의 검색
######################################################################
def search_custom(query, country):
    """
    1) query & country -> 검색+분석
    2) DB 저장
    3) DB 재로드 -> 기사+분석 출력
    """
    error_message, articles = serphouse_search(query, country)
    if error_message:
        return f"오류 발생: {error_message}"
    if not articles:
        return "검색 결과가 없습니다."
    
    analysis = analyze_sentiment_batch(articles, client)
    store = {
        "articles": articles,
        "analysis": analysis
    }
    save_to_db(query, country, store)

    loaded, ts = load_from_db(query, country)
    if not loaded:
        return "DB에서 로드 실패"

    arts = loaded.get("articles", [])
    analy = loaded.get("analysis", "")

    out = f"## [사용자 임의 검색 결과]\n\n"
    out += f"**키워드**: {query}\n\n"
    out += f"**국가**: {country}\n\n"
    out += f"**저장 시간**: {ts}\n\n"
    out += display_results(arts)
    out += f"### 뉴스 감성 분석\n{analy}\n"
    return out

######################################################################
# Hugging Face openai Client
######################################################################
ACCESS_TOKEN = os.getenv("HF_TOKEN")
if not ACCESS_TOKEN:
    raise ValueError("HF_TOKEN environment variable is not set")

client = OpenAI(
    base_url="https://api-inference.huggingface.co/v1/",
    api_key=ACCESS_TOKEN,
)

######################################################################
# 국가 설정
######################################################################
COUNTRY_LANGUAGES = {
    "United States": "en",
    "KOREA": "ko",
    "United Kingdom": "en",
    "Taiwan": "zh-TW",
    "Canada": "en",
    "Australia": "en",
    "Germany": "de",
    "France": "fr",
    "Japan": "ja",
    "China": "zh",
    "India": "hi",
    "Brazil": "pt",
    "Mexico": "es",
    "Russia": "ru",
    "Italy": "it",
    "Spain": "es",
    "Netherlands": "nl",
    "Singapore": "en",
    "Hong Kong": "zh-HK",
    "Indonesia": "id",
    "Malaysia": "ms",
    "Philippines": "tl",
    "Thailand": "th",
    "Vietnam": "vi",
    "Belgium": "nl",
    "Denmark": "da",
    "Finland": "fi",
    "Ireland": "en",
    "Norway": "no",
    "Poland": "pl",
    "Sweden": "sv",
    "Switzerland": "de",
    "Austria": "de",
    "Czech Republic": "cs",
    "Greece": "el",
    "Hungary": "hu",
    "Portugal": "pt",
    "Romania": "ro",
    "Turkey": "tr",
    "Israel": "he",
    "Saudi Arabia": "ar",
    "United Arab Emirates": "ar",
    "South Africa": "en",
    "Argentina": "es",
    "Chile": "es",
    "Colombia": "es",
    "Peru": "es",
    "Venezuela": "es",
    "New Zealand": "en",
    "Bangladesh": "bn",
    "Pakistan": "ur",
    "Egypt": "ar",
    "Morocco": "ar",
    "Nigeria": "en",
    "Kenya": "sw",
    "Ukraine": "uk",
    "Croatia": "hr",
    "Slovakia": "sk",
    "Bulgaria": "bg",
    "Serbia": "sr",
    "Estonia": "et",
    "Latvia": "lv",
    "Lithuania": "lt",
    "Slovenia": "sl",
    "Luxembourg": "Luxembourg",
    "Malta": "Malta",
    "Cyprus": "Cyprus",
    "Iceland": "Iceland"
}

COUNTRY_LOCATIONS = {
    "United States": "United States",
    "KOREA": "kr",
    "United Kingdom": "United Kingdom",
    "Taiwan": "Taiwan",
    "Canada": "Canada",
    "Australia": "Australia",
    "Germany": "Germany",
    "France": "France",
    "Japan": "Japan",
    "China": "China",
    "India": "India",
    "Brazil": "Brazil",
    "Mexico": "Mexico",
    "Russia": "Russia",
    "Italy": "Italy",
    "Spain": "Spain",
    "Netherlands": "Netherlands",
    "Singapore": "Singapore",
    "Hong Kong": "Hong Kong",
    "Indonesia": "Indonesia",
    "Malaysia": "Malaysia",
    "Philippines": "Philippines",
    "Thailand": "Thailand",
    "Vietnam": "Vietnam",
    "Belgium": "Belgium",
    "Denmark": "Denmark",
    "Finland": "Finland",
    "Ireland": "Ireland",
    "Norway": "Norway",
    "Poland": "Poland",
    "Sweden": "Sweden",
    "Switzerland": "Switzerland",
    "Austria": "Austria",
    "Czech Republic": "Czech Republic",
    "Greece": "Greece",
    "Hungary": "Hungary",
    "Portugal": "Portugal",
    "Romania": "Romania",
    "Turkey": "Turkey",
    "Israel": "Israel",
    "Saudi Arabia": "Saudi Arabia",
    "United Arab Emirates": "United Arab Emirates",
    "South Africa": "South Africa",
    "Argentina": "Argentina",
    "Chile": "Chile",
    "Colombia": "Colombia",
    "Peru": "Peru",
    "Venezuela": "Venezuela",
    "New Zealand": "New Zealand",
    "Bangladesh": "Bangladesh",
    "Pakistan": "Pakistan",
    "Egypt": "Egypt",
    "Morocco": "Morocco",
    "Nigeria": "Nigeria",
    "Kenya": "Kenya",
    "Ukraine": "Ukraine",
    "Croatia": "Croatia",
    "Slovakia": "Slovakia",
    "Bulgaria": "Bulgaria",
    "Serbia": "Serbia",
    "Estonia": "et",
    "Latvia": "lv",
    "Lithuania": "lt",
    "Slovenia": "sl",
    "Luxembourg": "Luxembourg",
    "Malta": "Malta",
    "Cyprus": "Cyprus",
    "Iceland": "Iceland"
}

css = """
/* 전역 스타일 */
footer {visibility: hidden;}

/* 레이아웃 스타일, 탭 스타일, 등등 */
#status_area {
    background: rgba(255, 255, 255, 0.9);
    padding: 15px;
    border-bottom: 1px solid #ddd;
    margin-bottom: 20px;
    box-shadow: 0 2px 5px rgba(0,0,0,0.1);
}

#results_area {
    padding: 10px;
    margin-top: 10px;
}

.tabs {
    border-bottom: 2px solid #ddd !important;
    margin-bottom: 20px !important;
}

.tab-nav {
    border-bottom: none !important;
    margin-bottom: 0 !important;
}

.tab-nav button {
    font-weight: bold !important;
    padding: 10px 20px !important;
}

.tab-nav button.selected {
    border-bottom: 2px solid #1f77b4 !important;
    color: #1f77b4 !important;
}

/* 상태 메시지 */
#status_area .markdown-text {
    font-size: 1.1em;
    color: #2c3e50;
    padding: 10px 0;
}

.group {
    border: 1px solid #eee;
    padding: 15px;
    margin-bottom: 15px;
    border-radius: 5px;
    background: white;
}

/* 버튼 스타일 */
.primary-btn {
    background: #1f77b4 !important;
    border: none !important;
}

/* 기타 ... */
"""

import gradio as gr

with gr.Blocks(theme="Yntec/HaleyCH_Theme_Orange", css=css, title="NewsAI 서비스") as iface:
    # DB 초기화
    init_db()
    
    with gr.Tabs():
        # 첫 번째 탭
        with gr.Tab("Earnbot"):
            gr.Markdown("## EarnBot: 글로벌 빅테크 기업 및 투자 전망 AI 자동 분석")
            gr.Markdown(" * '전체 분석 보고 요약' 클릭 시 전체 자동 보고 생성.\n * 아래 개별 종목의 '검색(DB 자동 저장)'과 '출력(DB 자동 호출)'도 가능.\n * 추가로, 원하는 임의 키워드 및 국가로 검색/분석할 수도 있습니다.")
            
            # 사용자 임의 검색 섹션
            with gr.Group():
                gr.Markdown("### 사용자 임의 검색")
                with gr.Row():
                    with gr.Column():
                        user_input = gr.Textbox(
                            label="검색어 입력",
                            placeholder="예) Apple, Samsung 등 자유롭게"
                        )
                    with gr.Column():
                        country_selection = gr.Dropdown(
                            choices=list(COUNTRY_LOCATIONS.keys()),
                            value="United States",
                            label="국가 선택"
                        )
                    with gr.Column():
                        custom_search_btn = gr.Button("실행", variant="primary")

                custom_search_output = gr.Markdown()
                
                # 임의 검색 버튼 클릭
                custom_search_btn.click(
                    fn=search_custom,
                    inputs=[user_input, country_selection],
                    outputs=custom_search_output
                )

            # 전체 분석 보고 버튼
            with gr.Row():
                full_report_btn = gr.Button("전체 분석 보고 요약", variant="primary")
                full_report_display = gr.Markdown()
            
            # 전체 보고 -> full_summary_report
            full_report_btn.click(
                fn=full_summary_report,
                outputs=full_report_display
            )
            
            # 지정된 기업 목록: 검색 / 출력
            with gr.Column():
                for i in range(0, len(KOREAN_COMPANIES), 2):
                    with gr.Row():
                        # 왼쪽
                        with gr.Column():
                            company = KOREAN_COMPANIES[i]
                            with gr.Group():
                                gr.Markdown(f"### {company}")
                                with gr.Row():
                                    search_btn = gr.Button("검색", variant="primary")
                                    load_btn = gr.Button("출력", variant="secondary")
                                result_display = gr.Markdown()
                                
                                # 검색
                                search_btn.click(
                                    fn=lambda c=company: search_company(c),
                                    outputs=result_display
                                )
                                # 출력
                                load_btn.click(
                                    fn=lambda c=company: load_company(c),
                                    outputs=result_display
                                )
                        
                        # 오른쪽
                        if i + 1 < len(KOREAN_COMPANIES):
                            with gr.Column():
                                company = KOREAN_COMPANIES[i + 1]
                                with gr.Group():
                                    gr.Markdown(f"### {company}")
                                    with gr.Row():
                                        search_btn = gr.Button("검색", variant="primary")
                                        load_btn = gr.Button("출력", variant="secondary")
                                    result_display = gr.Markdown()
                                    
                                    search_btn.click(
                                        fn=lambda c=company: search_company(c),
                                        outputs=result_display
                                    )
                                    load_btn.click(
                                        fn=lambda c=company: load_company(c),
                                        outputs=result_display
                                    )

iface.launch(
    server_name="0.0.0.0",
    server_port=7860,
    share=True,
    ssl_verify=False,
    show_error=True
)