Update frontend to use Hugging Face Space as backend

frontend/src/App.jsx

@@ -1,7 +1,7 @@
 import { useState, useEffect } from 'react'
 import './App.css'
 
-const API_BASE = (import.meta.env.VITE_API_URL || 'https://6efb-85-206-120-41.ngrok-free.app') + '/api';
+const API_BASE = (import.meta.env.VITE_API_URL || 'https://vycka12-binance-data-backend.hf.space') + '/api';
 
 function App() {
   const [symbols, setSymbols] = useState(['BTC/USDT']);

hf_space/Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+# HF Spaces expects port 7860
+EXPOSE 7860
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", "--timeout-keep-alive", "600"]

hf_space/app.py

@@ -0,0 +1,97 @@
+import os
+import sys
+
+sys.stdout.reconfigure(encoding='utf-8')
+
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+import ccxt
+from typing import Optional
+import modal
+
+app = FastAPI(title="Binance Data Dashboard API")
+
+# CORS - allow all origins for Vercel frontend
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Binance client for symbol list only
+try:
+    binance = ccxt.binance()
+except Exception as e:
+    print(f"Warning: Could not init Binance client: {e}")
+    binance = None
+
+class DownloadRequest(BaseModel):
+    symbol: str
+    interval: str
+    data_type: str
+    start_date: str
+    end_date: str
+    threshold: Optional[float] = 1_000_000
+    agg_mode: Optional[str] = "Standard (Klines + Liq)"
+    datasetType: Optional[str] = None
+
+@app.get("/")
+def health():
+    return {"status": "ok", "message": "Binance Data Dashboard API on Hugging Face"}
+
+@app.get("/api/symbols")
+def get_symbols():
+    try:
+        if binance is None:
+            raise Exception("Binance client not initialized")
+        markets = binance.load_markets()
+        symbols = sorted(list(markets.keys()))
+        return {"symbols": symbols}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/api/download")
+def download_data(request: DownloadRequest):
+    print(f"\n{'='*60}")
+    print(f"[CLOUD] Download request:")
+    print(f"   Symbol: {request.symbol}")
+    print(f"   Interval: {request.interval}")
+    print(f"   Data Type: {request.data_type}")
+    print(f"   Start: {request.start_date}")
+    print(f"   End: {request.end_date}")
+    print(f"   Threshold: {request.threshold}")
+    print(f"{'='*60}")
+    
+    try:
+        if request.data_type == 'Klines (OHLCV)':
+            print("[CLOUD] Calling fetch_klines_cloud...")
+            fn = modal.Function.from_name("binance-data-dashboard", "fetch_klines_cloud")
+            result = fn.remote(request.symbol, request.interval, request.start_date, request.end_date)
+            
+        elif request.data_type == 'Liquidations':
+            print("[CLOUD] Calling fetch_liquidations_cloud...")
+            fn = modal.Function.from_name("binance-data-dashboard", "fetch_liquidations_cloud")
+            result = fn.remote(request.symbol, request.start_date, request.end_date)
+
+        elif request.data_type == 'AggTrades':
+            print("[CLOUD] Calling fetch_aggtrades_cloud...")
+            fn = modal.Function.from_name("binance-data-dashboard", "fetch_aggtrades_cloud")
+            result = fn.remote(request.symbol, request.start_date, request.end_date)
+
+        elif request.data_type == 'Dollar Bars (ML Ready)':
+            print(f"[CLOUD] Calling fetch_dollar_bars_cloud (threshold: {request.threshold})...")
+            fn = modal.Function.from_name("binance-data-dashboard", "fetch_dollar_bars_cloud")
+            result = fn.remote(request.symbol, request.start_date, request.end_date, request.threshold)
+
+        else:
+            raise HTTPException(status_code=400, detail="Unknown data type.")
+
+        print(f"[CLOUD] Result received: success={result.get('success')}, rows={result.get('row_count', 0)}")
+        return result
+            
+    except Exception as e:
+        print(f"KLAIDA: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))

hf_space/requirements.txt

@@ -0,0 +1,5 @@
+fastapi
+uvicorn[standard]
+ccxt
+modal
+pydantic