FastAPI

Dockerfile

@@ -0,0 +1,21 @@
+# Mulai dari base image Python
+FROM python:3.10-slim
+
+# Tetapkan direktori kerja di dalam container
+WORKDIR /code
+
+# Salin file requirements terlebih dahulu untuk caching layer Docker
+COPY ./requirements.txt /code/requirements.txt
+
+# Instal dependensi
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Salin semua file proyek Anda ke dalam direktori kerja
+COPY . /code/
+
+# Beri tahu Docker bahwa container berjalan di port 7860
+EXPOSE 7860
+
+# Perintah untuk menjalankan aplikasi saat container dimulai
+# Kita menggunakan port 7860 agar sesuai dengan default Hugging Face
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -3,12 +3,13 @@ title: Smart Studio 554
 emoji: 🌖
 colorFrom: yellow
 colorTo: indigo
-sdk: gradio
-sdk_version: 5.49.1
+sdk: docker
 app_file: app.py
-pinned: false
+app_port: 7860
+hardware: gpu
+gpu_duration: 120
 tags:
 - anycoder
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,6 +1,8 @@
-import gradio as gr
-import pandas as pd
+import warnings
 import yfinance as yf
+from fastapi import FastAPI, HTTPException, Query
+from fastapi.responses import JSONResponse
+import uvicorn
 from utils import (
     calculate_technical_indicators,
     generate_trading_signals,
@@ -10,12 +12,16 @@ from utils import (
     create_technical_chart,
     create_prediction_chart,
 )
-import warnings
 
 warnings.filterwarnings("ignore")
 
+app = FastAPI(
+    title="IDX Stock Analysis API",
+    description="API untuk analisis teknikal, fundamental, dan prediksi AI untuk saham IDX.",
+    version="1.0.0"
+)
 
-def analyze_stock(symbol, prediction_days=30):
+def analyze_stock_logic(symbol, prediction_days=30):
     try:
         if not symbol.strip():
             raise ValueError("Please enter a valid stock symbol.")
@@ -27,7 +33,7 @@ def analyze_stock(symbol, prediction_days=30):
         data = stock.history(period="6mo", interval="1d")
 
         if data.empty:
-            raise ValueError("No price data available for this stock.")
+            raise ValueError(f"No price data available for stock: {symbol}")
 
         indicators = calculate_technical_indicators(data)
         signals = generate_trading_signals(data, indicators)
@@ -52,134 +58,66 @@ def analyze_stock(symbol, prediction_days=30):
 
     except Exception as e:
         print(f"Error analyzing {symbol}: {e}")
-        empty_fig = gr.Plot.update(value=None)
-        empty_predictions = {
-            "high_30d": 0,
-            "low_30d": 0,
-            "change_pct": 0,
-            "summary": "Prediction unavailable.",
-        }
-        return {}, {}, {}, empty_fig, empty_fig, empty_fig, empty_predictions
-
-
-def update_analysis(symbol, prediction_days):
-    (
-        fundamental_info,
-        indicators,
-        signals,
-        fig_price,
-        fig_technical,
-        fig_prediction,
-        predictions,
-    ) = analyze_stock(symbol, prediction_days)
-
-    if not fundamental_info:
-        return (
-            "Unable to fetch stock data.",
-            gr.Plot.update(value=None),
-            gr.Plot.update(value=None),
-            gr.Plot.update(value=None),
-        )
-
-    fundamentals = f"""
-    <h4>COMPANY FUNDAMENTALS</h4>
-    <b>Name:</b> {fundamental_info.get('name', 'N/A')} ({symbol.upper()})<br>
-    <b>Current Price:</b> Rp{fundamental_info.get('current_price', 0):,.2f}<br>
-    <b>Market Cap:</b> {fundamental_info.get('market_cap', 0):,}<br>
-    <b>P/E Ratio:</b> {fundamental_info.get('pe_ratio', 0):.2f}<br>
-    <b>Dividend Yield:</b> {fundamental_info.get('dividend_yield', 0):.2f}%<br>
-    <b>Volume:</b> {fundamental_info.get('volume', 0):,}<br>
-    """
+        raise HTTPException(status_code=404, detail=str(e))
 
-    details_list = "".join(
-        [f"<li>{line.strip()}</li>" for line in signals.get("details", "").split("\n") if line.strip()]
-    )
-
-    trading_signal = f"""
-    <h4>TECHNICAL SIGNAL SUMMARY</h4>
-    <b>Overall Trend:</b> {signals.get('overall', 'N/A')}<br>
-    <b>Signal Strength:</b> {signals.get('strength', 0):.2f}%<br>
-    <b>Support:</b> Rp{signals.get('support', 0):,.2f}<br>
-    <b>Resistance:</b> Rp{signals.get('resistance', 0):,.2f}<br>
-    <b>Stop Loss:</b> Rp{signals.get('stop_loss', 0):,.2f}<br><br>
-    <b>Detailed Signals:</b>
-    <ul style="margin-top: 8px; padding-left: 20px; line-height: 1.6;">
-    {details_list}
-    </ul>
-    """
 
-    prediction = f"""
-    <h4>30-DAY AI FORECAST (CHRONOS-BOLT)</h4>
-    <b>Predicted High:</b> Rp{predictions.get('high_30d', 0):,.2f}<br>
-    <b>Predicted Low:</b> Rp{predictions.get('low_30d', 0):,.2f}<br>
-    <b>Expected Change:</b> {predictions.get('change_pct', 0):.2f}%<br><br>
-    <b>TP1:</b> Rp{predictions.get('tp1', 0):,.2f}<br>
-    <b>TP2:</b> Rp{predictions.get('tp2', 0):,.2f}<br>
-    <b>Stop Loss:</b> Rp{predictions.get('sl', 0):,.2f}<br><br>
-    <b>Model Insight:</b><br>{predictions.get('summary', 'No analysis available')}
+@app.get("/analyze/")
+async def get_stock_analysis(
+    symbol: str = Query(..., description="Simbol saham IDX (contoh: BBCA, TLKM)"),
+    prediction_days: int = Query(30, ge=5, le=60, description="Jumlah hari untuk prediksi ke depan")
+):
     """
+    Menjalankan analisis lengkap untuk simbol saham yang diberikan.
+    """
+    try:
+        (
+            fundamental_info,
+            indicators,
+            signals,
+            fig_price,
+            fig_technical,
+            fig_prediction,
+            predictions,
+        ) = analyze_stock_logic(symbol, prediction_days)
+
+        # Ubah figur Plotly menjadi JSON agar bisa dikirim via API
+        charts_json = {
+            "price_chart": fig_price.to_json(),
+            "technical_chart": fig_technical.to_json(),
+            "prediction_chart": fig_prediction.to_json()
+        }
+
+        # Hapus data 'values' yang besar dari indicators agar response tidak terlalu besar
+        # Klien bisa membuat chart ini dari data chart utama jika perlu
+        if 'rsi' in indicators:
+            indicators['rsi'].pop('values', None)
+        if 'macd' in indicators:
+            indicators['macd'].pop('macd_values', None)
+            indicators['macd'].pop('signal_values', None)
+        if 'bollinger' in indicators:
+            indicators['bollinger'].pop('upper_values', None)
+            indicators['bollinger'].pop('middle_values', None)
+            indicators['bollinger'].pop('lower_values', None)
+        if 'moving_averages' in indicators:
+            indicators['moving_averages'].pop('sma_20_values', None)
+            indicators['moving_averages'].pop('sma_50_values', None)
+
+
+        return JSONResponse(content={
+            "symbol": symbol.upper() + ".JK",
+            "fundamentals": fundamental_info,
+            "technical_indicators": indicators,
+            "trading_signals": signals,
+            "ai_predictions": predictions,
+            "charts_json": charts_json
+        })
+
+    except HTTPException as http_exc:
+        raise http_exc
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"An internal error occurred: {str(e)}")
 
-    # Karena custom CSS dihapus, kita akan menggunakan div sederhana tanpa class 'panel-box' dan 'triple-panel'
-    # Gradio secara otomatis akan menata elemen-elemen ini dengan lebih standar
-    return (
-        f"""
-        <div style="display: flex; flex-direction: row; gap: 16px;">
-            <div style="flex: 1; min-width: 30%; border: 1px solid #ccc; padding: 10px; border-radius: 5px;">{fundamentals}</div>
-            <div style="flex: 1; min-width: 30%; border: 1px solid #ccc; padding: 10px; border-radius: 5px;">{trading_signal}</div>
-            <div style="flex: 1; min-width: 30%; border: 1px solid #ccc; padding: 10px; border-radius: 5px;">{prediction}</div>
-        </div>
-        """,
-        fig_price,
-        fig_technical,
-        fig_prediction,
-    )
-
-
-# --- Perubahan utama di sini ---
-with gr.Blocks(
-    title="REXPRO FINANCIAL AI DASHBOARD"
-    # Parameter theme dan css dihapus untuk kembali ke default Gradio
-) as app:
-    gr.Markdown("# REXPRO FINANCIAL AI DASHBOARD")
-    gr.Markdown(
-        "Comprehensive stock analytics powered by **AI forecasting and technical analysis.**"
-    )
-
-    with gr.Row():
-        symbol = gr.Textbox(
-            label="STOCK SYMBOL (IDX)",
-            value="BBCA",
-            placeholder="Example: BBCA, TLKM, ADRO, BMRI",
-            interactive=True,
-        )
-        prediction_days = gr.Slider(
-            label="FORECAST PERIOD (DAYS)",
-            minimum=5,
-            maximum=60,
-            step=5,
-            value=30,
-            interactive=True,
-        )
-        analyze_button = gr.Button("RUN ANALYSIS")
-
-    gr.Markdown("---")
-    # Bagian report_section diubah agar lebih kompatibel dengan tema default,
-    # menggunakan sedikit inline CSS untuk meniru tata letak tiga kolom dasar.
-    report_section = gr.HTML() 
-    gr.Markdown("---")
-
-    with gr.Tab("MARKET CHARTS"):
-        with gr.Row():
-            price_chart = gr.Plot(label="PRICE & MOVING AVERAGES")
-            technical_chart = gr.Plot(label="TECHNICAL INDICATORS OVERVIEW")
-        gr.Markdown("---")
-        prediction_chart = gr.Plot(label="AI FORECAST PROJECTION")
-
-    analyze_button.click(
-        fn=update_analysis,
-        inputs=[symbol, prediction_days],
-        outputs=[report_section, price_chart, technical_chart, prediction_chart],
-    )
 
 if __name__ == "__main__":
-    app.launch(server_name="0.0.0.0", server_port=7860, ssr_mode=True)
+    # Gunakan port 7860 yang merupakan default untuk Hugging Face Spaces
+    uvicorn.run(app, host="0.0.0.0", port=7860)

requirements.txt

@@ -1,4 +1,3 @@
-gradio>=4.0.0
 yfinance>=0.2.0
 pandas>=1.5.0
 numpy>=1.24.0
@@ -10,3 +9,5 @@ accelerate>=0.20.0
 tiktoken
 sentencepiece
 chronos-forecasting
+fastapi>=0.100.0
+uvicorn[standard]>=0.20.0