Add config-driven system.yaml and multi-window indicators

- Create config/system.yaml with full master prompt template
- Create src/config_loader.py to load YAML config and .env
- Update data_engine.build_all_features() to support lists of windows
  (e.g. sma_windows: [3, 20] produces sma_3 and sma_20 columns)
- Rewrite get_candles.py to loop over all instruments × granularities
  from config instead of hardcoding EUR_USD/M5
- Fix supabase_upload.py indentation bug and wire up config for table name

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/get_candles.py

@@ -0,0 +1,56 @@
+# src/get_candles.py
+"""
+Fetch OANDA candles for every instrument × granularity defined in
+config/system.yaml, build indicator features, and print the result.
+"""
+
+import os
+import requests
+from config_loader import load_config
+from data_engine import candles_to_df, build_all_features
+
+
+def fetch_candles(instrument, granularity, count, base_url, api_key):
+    """Pull raw candle dicts from the OANDA v20 REST API."""
+    url = (
+        f"{base_url}/v3/instruments/{instrument}/candles"
+        f"?count={count}&granularity={granularity}"
+    )
+    headers = {"Authorization": f"Bearer {api_key}"}
+    r = requests.get(url, headers=headers)
+    r.raise_for_status()
+    return r.json()["candles"]
+
+
+def main():
+    cfg = load_config()
+
+    # OANDA credentials (loaded into env by config_loader)
+    api_key = os.getenv("OANDA_API_KEY")
+    env = os.getenv("OANDA_ENV", "practice")
+    base_url = (
+        "https://api-fxpractice.oanda.com"
+        if env == "practice"
+        else "https://api-fxtrade.oanda.com"
+    )
+
+    # Config-driven parameters
+    broker = cfg["brokers"][0]
+    instruments = broker["instruments"]
+    granularities = cfg["data"]["candle_granularities"]
+    count = cfg["data"]["candle_count"]
+    feature_cfg = cfg.get("features", {})
+
+    for instrument in instruments:
+        for granularity in granularities:
+            print(f"\n--- {instrument} | {granularity} ---")
+            candles = fetch_candles(
+                instrument, granularity, count, base_url, api_key
+            )
+            df = candles_to_df(candles)
+            df = build_all_features(df, config=feature_cfg)
+            print(df.tail(10).to_string())
+
+
+if __name__ == "__main__":
+    main()