fix: validation history wiped after execute + today's OHLCV fallback

prune_validated_snapshots now keeps the last 14 days instead of deleting
all VALIDATED rows — the old behaviour cleared every validated record
immediately after each execute run, leaving the history tab and hit-rate
stat cards empty on the next page load.

For same-day (1D/3D/5D) predictions whose target_date == today, the six
daily OHLCV sources only carry yesterday's close (today's bar is published
hours after session end). Added two extra fallback layers in _fetch_window:
1. _fetch_intraday_window_capped with 15:30 IST cutoff (yfinance 15m bars,
available right after the session)
2. fetch_live_price (NSE→BSE→jugaad→Yahoo chain) for actual_price when
even intraday bars are unavailable

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

app.py

@@ -2309,6 +2309,8 @@ def validation_execute():
             continue
         actionable.append(snap)
 
+    today_str = today_ist.isoformat()
+
     def _fetch_window(snap):
         """Return (snap, window_high, window_low, actual_price) — None prices on failure."""
         timeframe = (snap.get("timeframe") or "").upper()
@@ -2323,6 +2325,23 @@ def validation_execute():
                 except ValueError:
                     ws = target_date_str
                 wh, wl, ap = _fetch_price_window(snap["ticker"], ws, target_date_str)
+                # Fallback: for today's target date, all 6 daily OHLCV sources may only
+                # carry yesterday's close (today's bar is published hours after session
+                # end, sometimes not until next morning).  Try intraday 15m bars first
+                # (yfinance — only source for sub-daily NSE data), then fall back to
+                # fetch_live_price which has its own NSE→BSE→jugaad→Yahoo chain.
+                if ap is None and target_date_str == today_str:
+                    wh, wl, ap = _fetch_intraday_window_capped(
+                        snap["ticker"], target_date_str,
+                        cutoff_hour=15, cutoff_minute=30,
+                    )
+                    if ap is None:
+                        from data_sources import fetch_live_price
+                        live = fetch_live_price(snap["ticker"], allow_delayed=True)
+                        if live and live > 0:
+                            ap = live
+                            wh = wh if wh is not None else live
+                            wl = wl if wl is not None else live
             return snap, wh, wl, ap
         except Exception as e:
             logging.warning(f"_fetch_window({snap.get('ticker')}): {e}")

database.py

@@ -1033,11 +1033,19 @@ def get_validation_history(timeframe: Optional[str] = None, limit: int = 100) ->
     return [dict(r) for r in rows]
 
 
-def prune_validated_snapshots() -> int:
-    """Delete all VALIDATED prediction_snapshots. Called after learnings.json is written."""
+def prune_validated_snapshots(keep_days: int = 14) -> int:
+    """Delete VALIDATED prediction_snapshots older than keep_days.
+
+    Keeps recent validations in the DB so the history tab and hit-rate stat cards
+    remain populated after a validation run.  Self-learning already captures the
+    key insights in learnings.json, so the older rows are safe to remove.
+    """
     with _conn() as conn:
         cur = conn.execute(
-            "DELETE FROM prediction_snapshots WHERE validation_status = 'VALIDATED'"
+            "DELETE FROM prediction_snapshots "
+            "WHERE validation_status = 'VALIDATED' "
+            "AND datetime(validated_at) < datetime('now', ?)",
+            (f"-{int(keep_days)} days",),
         )
         return cur.rowcount