server.py

import argparse
import os
import tempfile
from datetime import datetime
from typing import List, Optional, Dict, Any

from fastapi import FastAPI, HTTPException, File, UploadFile
from pydantic import BaseModel

from industry_info import industry_info
from investment_company import investment_company
from similar_investors import SimilarInvestors
from stock_news import StockNews
from stock_price import StockPrice
from theme_info import theme_info
from portfolio import build_final_prompt, chatgpt, read_file_text, load_json

app = FastAPI(title="Portfolio Analysis")

# 데이터 파일 경로 설정
DATA_PATHS = {
    "similar_investors_us": "/work/portfolio/data/SEC_Filing_Manager.csv",
    "similar_investors_ko": "/work/portfolio/data/ETF.csv",
    "investment_company": "/work/portfolio/data/investment_company.jsonl",
    "industry_info": "/work/portfolio/data/industry_info.csv",
    "theme_info":"/work/portfolio/data/theme_info.csv"
}

# Request Models
class IndustryInfoRequest(BaseModel):
    stock: List[str] = ["Meta"]

class InvestmentCompanyRequest(BaseModel):
    name: str = "GEODE CAPITAL MANAGEMENT, LLC"

class SimilarInvestorsRequest(BaseModel):
    csv_text: str = """종목코드,종목명,매입주가,보유주식수\nNVDA,NVIDIA Corporation,159.69,167\nAMZN,"Amazon.com, Inc.",211.58,140"""
    region: str
    top: int = 1

class StockNewsRequest(BaseModel):
    stock: str = "META"
    period: int = 1

class StockPriceRequest(BaseModel):
    stock: str = "META"

class ThemeInfoRequest(BaseModel):
    stock: List[str] = ["Meta"]

class PortfolioRequest(BaseModel):
    date:str = datetime.now().strftime("%Y년 %m월 %d일")
    user_name: str = "이서준"
    csv_text: str = "종목코드,종목명,매입주가,보유주식수\nAAPL,Apple Inc.,150,10"
    json_text: Dict[str, Any] = {"similar_investors":[{"ID":"37833100","NAME":"LAZARI CAPITAL MANAGEMENT, INC.","COMPANY":"APPLE INC","VALUE":33972687.0,"AMOUNT":165583,"PERCENTAGE":12.8}],"stock_price":{"META":[{"Date":"2025-10-20","Name":"Meta Platforms","Open":721.2,"High":733.8,"Low":720.2,"Close":732.2,"Volume":8900200},{"Date":"2025-10-21","Name":"Meta Platforms","Open":736.0,"High":738.5,"Low":728.8,"Close":733.3,"Volume":7647300},{"Date":"2025-10-22","Name":"Meta Platforms","Open":733.8,"High":740.6,"Low":724.0,"Close":733.4,"Volume":8734500}]},"stock_news":{"META":[{"Name":"Meta Platforms","date":"2025-11-20","time":"08:37","news":"딥러닝 거장 얀 르쿤, Meta Platforms 떠나 AI 스타트업 설립 선언\n“오늘날 AI는 인간 수준의 지능을 향해 가기 위해 반드시 새로운 접근이 필요하다.” 딥러닝의 개척자 얀 르쿤(Yann LeCun)이 Meta를 떠나며 남긴 이 코멘트는 AI 업계..."}]},"industry_info":[{"stock":"Meta","description":"Industry: Internet Content & Information | Sector: Communication Services"}],"theme_info":[{"stock":"Meta","desc":"Theme: Artificial Intelligence | Theme 2: \"Social Media\" | Theme 3: \"Virtual Reality\""}]}


# 1. Industry Info API
@app.post("/industry_info")
def get_industry_info(request: IndustryInfoRequest):
    """종목의 산업군/섹터 검색"""
    try:
        print(f"[INFO] Processing stocks: {request.stock}")
        
        # industry_info 객체 생성
        ic = industry_info(DATA_PATHS["industry_info"])
        
        all_records = []
        for stock in request.stock:
            print(f"[INFO] 처리 중: {stock}")
            result = ic.make(stock)
            if not result:
                print(f"[WARN] 종목 처리 실패: {stock}")
                continue

            full_name = result["stock"]
            desc = ic.get(full_name)
            if desc:
                print(f"[INFO] {full_name} 조회 완료")
                all_records.append({
                    "stock": full_name,
                    "description": desc
                })
            else:
                print(f"[WARN] {full_name} description 없음")
        
        return {
            "success": True,
            "data": all_records,
            "count": len(all_records)
        }
    
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# 2. Investment Company API
@app.post("/investment_company")
def get_investment_company(request: InvestmentCompanyRequest):
    """투자회사 정보 조회"""
    try:
        print(f"[INFO] Processing company: {request.name}")
        
        ic = investment_company(DATA_PATHS["investment_company"])
        ic.make()
        desc = ic.get(request.name)
        
        return {
            "success": True,
            "data": {
                "company_name": request.name,
                "description": desc
            }
        }
    
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# 3. Similar Investors API
@app.post("/similar_investors")
def get_similar_investors(request: SimilarInvestorsRequest):
    """사용자와 유사한 투자회사 검색 (CSV 문자열 입력)"""
    try:
        print(f"[INFO] Processing CSV text (length={len(request.csv_text)}), top: {request.top}")
        
        # SimilarInvestors 준비
        si = SimilarInvestors(DATA_PATHS["similar_investors_ko"], DATA_PATHS["similar_investors_us"])
        if request.region == 'ko':
            created_path = si.make_ko()
        elif request.region == 'us':
            created_path = si.make_us()
        else:
            print("[INFO] region 입력 오류.")
            raise HTTPException(status_code=400, detail="region은 'ko' 또는 'us' 여야 합니다.")
        print(f"[INFO] 데이터 경로: {created_path}")

        # 1) csv_text 유효성 검사 (간단)
        header = request.csv_text.strip().splitlines()[0]
        required_cols = ["종목코드", "종목명", "매입주가", "보유주식수"]
        for col in required_cols:
            if col not in header.split(","):
                raise HTTPException(status_code=400, detail=f"CSV 헤더에 '{col}' 컬럼이 없습니다.")
        print("1완료 \n")

        # 2) 임시 파일로 저장하여 기존 si.get 재사용
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as tmp:
            tmp_path = tmp.name
            tmp.write(request.csv_text)
        print(f"[INFO] 임시 CSV 파일 생성: {tmp_path}")

        try:
            result = si.get(tmp_path, request.region, output_path=None, top_n=request.top)
            count = sum(len(rows) for rows in result.values())
        finally:
            # 임시 파일 삭제
            if os.path.exists(tmp_path):
                os.remove(tmp_path)
                print(f"[INFO] 임시 파일 삭제 완료: {tmp_path}")
        
        return {
            "success": True,
            "data": result,
            "count": count,
            "top_n": request.top
        }
    
    except HTTPException as e:
        raise e
    except Exception as e:
        import traceback
        traceback.print_exc()
        raise HTTPException(status_code=500, detail=str(e))


# 4. Stock News API
@app.post("/stock_news")
def get_stock_news(request: StockNewsRequest):
    """기업 뉴스 크롤링"""
    try:
        print(f"[INFO] Processing stock: {request.stock}, period: {request.period}")
        
        data_folder = "data_stock_news"
        sn = StockNews(data_folder)
        
        # make 함수 실행
        created = sn.make(request.stock, request.period)
        print(f"[INFO] 생성된 건수: {len(created) if created is not None else 0}")
        
        # get 함수 실행
        loaded = sn.get(request.stock)
        print(f"[INFO] 로드된 건수: {len(loaded) if loaded is not None else 0}")
        
        stock = sn.normalize_ticker(request.stock)
        records = loaded.to_dict('records') if loaded is not None else []
        
        return {
            "success": True,
            "data": {
                stock: records
            },
            "count": len(records)
        }
    
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# 5. Stock Price API
@app.post("/stock_price")
def get_stock_price(request: StockPriceRequest):
    """주가 데이터 조회"""
    try:
        stocks = [t.strip().upper() for t in request.stock.split(",") if t.strip()]
        print(f"[INFO] Processing {len(stocks)} stocks")
        
        data_folder = "data_stock_price/"
        sp = StockPrice(data_folder)
        
        stock_to_records = {}
        for stock in stocks:
            df = sp.make(stock)
            if df is None:
                print(f"[WARN] 생성 실패: {stock}")
                continue
            df = sp.get(stock)
            stock_to_records[sp.normalize_ticker(stock)] = df.to_dict('records')
        
        return {
            "success": True,
            "data": stock_to_records,
            "stocks_processed": len(stock_to_records)
        }
    
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# 6. Theme Info API
@app.post("/theme_info")
def get_theme_info(request: ThemeInfoRequest):
    """종목의 테마 검색"""
    try:
        print(f"[INFO] Processing stocks: {request.stock}")
        
        ti = theme_info(DATA_PATHS["theme_info"])
        
        # make 함수 실행
        make_results = []
        for stock in request.stock:
            print(f"[INFO] 처리 중: {stock}")
            rows = ti.make(stock)
            if rows:
                make_results.extend(rows)
        
        # get 함수 실행
        all_records = []
        for row in make_results:
            official_name = row["NAME"]
            desc = ti.get(official_name)
            all_records.append({
                "stock": official_name,
                "desc": desc
            })
            print(f"[INFO] {official_name} 조회 완료")
        
        return {
            "success": True,
            "data": all_records,
            "count": len(all_records)
        }
    
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


# 7. Portfolio Report API
@app.post("/report")
def generate_portfolio_report(request: PortfolioRequest):
    try:
        print(f"[INFO] Generating report for user: {request.user_name}")

        csv_text = request.csv_text
        json_obj = request.json_text

        print("[INFO] 입력 데이터 로드 완료")

        final_prompt = build_final_prompt(request.date, request.user_name, csv_text, json_obj)
        print("[INFO] 프롬프트 생성 완료")

        report_text = chatgpt(final_prompt)
        print("[INFO] 리포트 생성 완료")

        return {
            "success": True,
            "data": {
                "user_name": request.user_name,
                "report": report_text
            }
        }

    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument('--port', type=int, default=8080)
    args = parser.parse_args()

    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=args.port)