Update api.py

api.py

@@ -44,6 +44,8 @@ from ta.trend import ADXIndicator, MACD
 from ta.volatility import AverageTrueRange
 from chronos import Chronos2Pipeline
 from dotenv import load_dotenv
+from yahooquery import Ticker
+
 
 load_dotenv()
 
@@ -625,62 +627,105 @@ INSTRUMENT_CATALOG = [
 ]
 
 
-def _get_api_key():
-    key = os.getenv("TWELVEDATA_API_KEY", "").strip()
-    if not key or key == "your_api_key_here":
-        return None
-    return key
+# Symbol mappings from Frontend symbols to Yahoo Finance symbols
+SYMBOL_MAP = {
+    "NIFTY50": "^NSEI",
+    "SENSEX": "^BSESN",
+    "RELIANCE": "RELIANCE.NS",
+    "TCS": "TCS.NS",
+    "HDFCBANK": "HDFCBANK.NS",
+    "INFY": "INFY.NS",
+    "ICICIBANK": "ICICIBANK.NS",
+    "SBIN": "SBIN.NS",
+    "AAPL": "AAPL",
+    "TSLA": "TSLA",
+    "MSFT": "MSFT",
+    "GOOGL": "GOOGL",
+    "AMZN": "AMZN",
+    "NVDA": "NVDA",
+    "META": "META",
+    "BTC/USD": "BTC-USD",
+    "ETH/USD": "ETH-USD",
+    "SOL/USD": "SOL-USD",
+    "XRP/USD": "XRP-USD",
+    "EUR/USD": "EURUSD=X",
+    "GBP/USD": "GBPUSD=X",
+    "USD/JPY": "USDJPY=X",
+    "USD/INR": "USDINR=X",
+    "XAU/USD": "GC=F",
+    "XAG/USD": "SI=F",
+}
 
 
 def fetch_live_data(symbol: str, exchange: str = "", interval: str = "5min",
                     outputsize: int = 5000) -> pd.DataFrame:
     """
-    Fetch OHLCV time-series from Twelve Data.
+    Fetch OHLCV time-series from Yahoo Finance via yahooquery.
     Returns a pandas DataFrame with columns: date, open, high, low, close, volume.
-    Raises ValueError on API errors.
     """
-    api_key = _get_api_key()
-    if not api_key:
-        raise ValueError(
-            "TWELVEDATA_API_KEY not set. Add your free API key to .env file. "
-            "Sign up at https://twelvedata.com (free, 30 seconds)."
-        )
-
-    params = {
-        "symbol":     symbol,
-        "interval":   interval,
-        "outputsize": outputsize,
-        "apikey":     api_key,
-        "format":     "JSON",
-        "order":      "ASC",
+    yf_symbol = SYMBOL_MAP.get(symbol, symbol)
+    if not yf_symbol:
+        yf_symbol = symbol
+
+    # Map frontend intervals to yahooquery intervals
+    intervals_map = {
+        "1min": "1m",
+        "5min": "5m",
+        "15min": "15m",
+        "1h": "1h",
+        "4h": "1h",  # We download 1h and resample to 4h
+        "1day": "1d",
     }
-    if exchange:
-        params["exchange"] = exchange
-
-    resp = http_requests.get(f"{TWELVEDATA_BASE}/time_series", params=params, timeout=30)
-    data = resp.json()
-
-    if data.get("status") == "error" or "code" in data:
-        msg = data.get("message", str(data))
-        raise ValueError(f"Twelve Data API error: {msg}")
-
-    values = data.get("values", [])
-    if not values:
-        raise ValueError(f"No data returned for symbol '{symbol}'. Check the symbol is valid.")
-
-    df = pd.DataFrame(values)
-    df = df.rename(columns={"datetime": "date"})
-
+    yq_interval = intervals_map.get(interval, "5m")
+
+    # Select history period based on interval
+    if yq_interval == "1m":
+        period = "5d"
+    elif yq_interval in ["5m", "15m"]:
+        period = "1mo"
+    elif yq_interval == "1h":
+        period = "3mo" if interval == "4h" else "1mo"
+    else:
+        period = "1y"
+
+    t = Ticker(yf_symbol)
+    df = t.history(period=period, interval=yq_interval)
+
+    if isinstance(df, dict):
+        error_msg = df.get(yf_symbol, {}).get("description", str(df))
+        raise ValueError(f"Yahoo Finance error: {error_msg}")
+
+    if df is None or df.empty:
+        raise ValueError(f"No data returned for symbol '{symbol}' (Yahoo Symbol: '{yf_symbol}')")
+
+    # Reset MultiIndex to convert index level 1 to column 'date'
+    df = df.reset_index()
+    if 'symbol' in df.columns:
+        df = df.drop(columns=['symbol'])
+
+    # Standardize columns
+    df = df.rename(columns={"date": "date"})
     for col in ["open", "high", "low", "close", "volume"]:
         if col in df.columns:
             df[col] = pd.to_numeric(df[col], errors="coerce")
 
-    if "date" in df.columns:
-        df["date"] = pd.to_datetime(df["date"])
-        df = df.sort_values("date").reset_index(drop=True)
-
     df = df.dropna(subset=["open", "high", "low", "close"]).reset_index(drop=True)
 
+    # Sort by date
+    df["date"] = pd.to_datetime(df["date"])
+    df = df.sort_values("date").reset_index(drop=True)
+
+    # Resample 1h data to 4h if requested
+    if interval == "4h":
+        df.set_index("date", inplace=True)
+        df = df.resample("4h").agg({
+            "open": "first",
+            "high": "max",
+            "low": "min",
+            "close": "last",
+            "volume": "sum"
+        }).dropna().reset_index()
+
     # Remove flat candles
     flat = ((df["open"]==df["high"]) & (df["high"]==df["low"]) & (df["low"]==df["close"]))
     df = df[~flat].copy().reset_index(drop=True)
@@ -689,20 +734,17 @@ def fetch_live_data(symbol: str, exchange: str = "", interval: str = "5min",
 
 
 def fetch_current_price(symbol: str, exchange: str = ""):
-    """Quick price lookup — 1 API credit."""
-    api_key = _get_api_key()
-    if not api_key:
-        return None
-
-    params = {"symbol": symbol, "apikey": api_key}
-    if exchange:
-        params["exchange"] = exchange
-
+    """Quick price lookup via yahooquery — 1 call, no API keys."""
+    yf_symbol = SYMBOL_MAP.get(symbol, symbol)
     try:
-        resp = http_requests.get(f"{TWELVEDATA_BASE}/price", params=params, timeout=10)
-        data = resp.json()
-        if "price" in data:
-            return float(data["price"])
+        t = Ticker(yf_symbol)
+        price_dict = t.price
+        if isinstance(price_dict, dict) and yf_symbol in price_dict:
+            details = price_dict[yf_symbol]
+            if isinstance(details, dict):
+                price = details.get("regularMarketPrice")
+                if price is not None:
+                    return float(price)
     except Exception:
         pass
     return None
@@ -713,9 +755,8 @@ def fetch_current_price(symbol: str, exchange: str = ""):
 @app.get("/instruments")
 def list_instruments():
     """Return the catalog of supported instruments with categories."""
-    api_ready = _get_api_key() is not None
     return {
-        "api_ready":   api_ready,
+        "api_ready":   True,
         "instruments": INSTRUMENT_CATALOG,
         "categories":  sorted(set(i["category"] for i in INSTRUMENT_CATALOG)),
         "timeframes":  ["1min","5min","15min","1h","4h","1day"],
@@ -727,7 +768,7 @@ def get_price(symbol: str, exchange: str = Query(default="")):
     """Quick current-price lookup for a symbol."""
     price = fetch_current_price(symbol, exchange)
     if price is None:
-        return {"error": "Could not fetch price. Check API key and symbol."}
+        return {"error": "Could not fetch price. Check symbol."}
     return {"symbol": symbol, "price": price}
 
 
@@ -736,7 +777,7 @@ def live_analyse(symbol: str, exchange: str = Query(default=""),
                  name: str = Query(default=""),
                  interval: str = Query(default="5min")):
     """
-    Fetch live OHLCV data from Twelve Data and run the full analysis pipeline:
+    Fetch live OHLCV data from Yahoo Finance and run the full analysis pipeline:
       indicators → Chronos forecast → 3 XGBoost models → signal + backtest.
     Returns the same JSON structure as POST /analyse.
     Supports intervals: 1min, 5min, 15min, 1h, 4h, 1day.
@@ -782,7 +823,7 @@ def live_analyse(symbol: str, exchange: str = Query(default=""),
                 "current": round(float(df["close"].iloc[-1]), 4),
             },
             "avg_atr_pct": round(float((df["ATR"]/df["close"]*100).median()), 4),
-            "source":      "Twelve Data API (live)",
+            "source":      "Yahoo Finance (live)",
         }
 
         return {