Update main.py

main.py

@@ -3,28 +3,23 @@ from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 from typing import Dict, Any, List, Optional
 
-# Import core logic modules
 from data_processor import DataProcessor
 from sentiment_analyzer import SentimentAnalyzer
 from model_handler import ModelHandler
 from trading_logic import TradingLogic
 from plotter import create_mplfinance_chart
 
-# Initialize core components
 data_processor = DataProcessor()
 sentiment_analyzer = SentimentAnalyzer()
 model_handler = ModelHandler()
 trading_logic = TradingLogic()
 
-# FastAPI app setup
 app = FastAPI(
     title="Ultimate Market Analysis & Prediction API",
     version="1.0.0",
     description="API for fetching market data, technical indicators, Chronos-2 predictions, and simulated analysis for GC=F and BTC-USD."
 )
 
-# Add CORS middleware for frontend access
-# HATI-HATI: Ganti "*" dengan domain frontend React Anda saat deployment produksi
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"], 
@@ -33,8 +28,6 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# --- Skema Respon Pydantic ---
-
 class TradingMetrics(BaseModel):
     Ticker: str
     Current_Price: str
@@ -47,7 +40,7 @@ class TradingMetrics(BaseModel):
     Volume: str
 
 class ChartAnalysisResponse(BaseModel):
-    chart_html_base64: Optional[str] = None # String base64 gambar, siap untuk tag <img src="data:image/png;base64,...">
+    chart_html_base64: Optional[str] = None
     metrics: Optional[TradingMetrics] = None
     raw_predictions: Optional[List[float]] = None
     error: Optional[str] = None
@@ -59,8 +52,6 @@ class SentimentAnalysisResponse(BaseModel):
 class FundamentalsResponse(BaseModel):
     fundamentals_data: Dict[str, Any]
 
-# --- Endpoint API ---
-
 @app.get("/")
 def read_root():
     return {"message": "Welcome to the Ultimate Market Analysis API. Use /docs for API documentation."}
@@ -70,42 +61,34 @@ def get_chart_analysis(
     ticker: str = Query(..., description="Market Ticker (e.g., GC=F, BTC-USD)"), 
     interval: str = Query(..., description="Time Interval (e.g., 1d, 1h, 5m)")
 ):
-    """
-    Mengambil data pasar, menghitung indikator, menghasilkan prediksi, 
-    dan mengembalikan gambar chart (Base64) serta metrik trading.
-    """
     try:
-        # 1. Fetch data
         df = data_processor.get_market_data(ticker, interval)
         if df.empty:
             return ChartAnalysisResponse(error=f"No data available for {ticker} at {interval}")
         
-        # 2. Calculate Indicators
         df = data_processor.calculate_indicators(df)
-        
-        # 3. Prepare and Predict
         prepared_data = data_processor.prepare_for_chronos(df)
         predictions = model_handler.predict(prepared_data, horizon=10)
-        
+
         current_price = df['Close'].iloc[-1]
         
-        # 4. Generate Chart (returns Base64 HTML string)
         chart_html = create_mplfinance_chart(
             df, 
             ticker=f'{ticker} ({interval})', 
             predictions=predictions
         )
 
-        # 5. Generate Signal and Metrics
         signal, confidence = trading_logic.generate_signal(
             predictions, current_price, df
         )
         
+        # Pastikan ATR tersedia sebelum menghitung TP/SL
+        atr_value = df['ATR'].iloc[-1] if 'ATR' in df.columns and not df['ATR'].empty else 0
+        
         tp, sl = trading_logic.calculate_tp_sl(
-            current_price, df['ATR'].iloc[-1], signal
+            current_price, atr_value, signal
         )
         
-        # 6. Format Metrics
         metrics = TradingMetrics(
             Ticker=ticker,
             Current_Price=f"${current_price:.2f}",
@@ -125,14 +108,11 @@ def get_chart_analysis(
         )
         
     except Exception as e:
-        # Gunakan HTTPException untuk penanganan kesalahan API
+        # PENTING: Menggunakan HTTPException 500 dengan detail spesifik
         raise HTTPException(status_code=500, detail=f"Error in chart analysis: {str(e)}")
 
 @app.get("/analysis/sentiment", response_model=SentimentAnalysisResponse)
 def get_sentiment_analysis(ticker: str = Query(..., description="Market Ticker (e.g., GC=F, BTC-USD)")):
-    """
-    Menganalisis dan mengembalikan skor sentimen pasar dan ringkasan berita (Simulasi).
-    """
     try:
         sentiment_score, news_summary_html = sentiment_analyzer.analyze_market_sentiment(ticker)
         
@@ -146,9 +126,6 @@ def get_sentiment_analysis(ticker: str = Query(..., description="Market Ticker (
 
 @app.get("/analysis/fundamentals", response_model=FundamentalsResponse)
 def get_fundamentals_analysis(ticker: str = Query(..., description="Market Ticker (e.g., GC=F, BTC-USD)")):
-    """
-    Mengambil data fundamental pasar utama (Simulasi).
-    """
     try:
         fundamentals = data_processor.get_fundamental_data(ticker)