Upload app.py

app.py

@@ -236,6 +236,7 @@ def attach_market_state(payload: dict) -> dict:
     # we forcefully load it directly from app.py's relative path.
     mfe_summary_fallback = {}
     mfe_latest_fallback = {}
+    mfe_history_fallback = []
     try:
         models_dir = Path(__file__).resolve().parent / "models"
         mfe_out = models_dir / "nifty_opening_mfe_regressor" / "outputs"
@@ -244,6 +245,27 @@ def attach_market_state(payload: dict) -> dict:
         if (mfe_out / "latest_prediction.csv").exists():
             row = pd.read_csv(mfe_out / "latest_prediction.csv").iloc[-1].to_dict()
             mfe_latest_fallback = {k: (None if pd.isna(v) else v) for k, v in row.items()}
+        if (mfe_out / "test_predictions.csv").exists():
+            hist_df = pd.read_csv(mfe_out / "test_predictions.csv")
+            hist_records = []
+            for _, r in hist_df.iterrows():
+                try:
+                    dt = str(r["date"])
+                    f5c = float(r["first5_close"])
+                    pred_up = float(r["predicted_up_points"])
+                    pred_dn = float(r["predicted_down_points"])
+                    act_hi = float(r["day_high"])
+                    act_lo = float(r["day_low"])
+                    hist_records.append({
+                        "date": dt,
+                        "actual_high": act_hi,
+                        "predicted_high": f5c + pred_up,
+                        "actual_low": act_lo,
+                        "predicted_low": f5c - pred_dn
+                    })
+                except Exception:
+                    continue
+            mfe_history_fallback = hist_records
     except Exception as exc:
         print(f"Fallback MFE load failed: {exc}", flush=True)
 
@@ -252,6 +274,7 @@ def attach_market_state(payload: dict) -> dict:
     tplus1_latest = payload.get("predictions", {}).get("tplus1", {}).get("latest") or payload.get("tplus1_latest") or {}
     mfe_latest = payload.get("predictions", {}).get("mfe", {}).get("latest") or mfe_latest_fallback
     mfe_summary = payload.get("predictions", {}).get("mfe", {}).get("summary") or mfe_summary_fallback
+    mfe_history = payload.get("predictions", {}).get("mfe", {}).get("history") or mfe_history_fallback
     t5_available = bool(state["t5_available"] and t5_latest.get("prediction"))
     tplus1_available = bool(state["tplus1_available"] and tplus1_latest.get("prediction"))
     tomorrow_available = bool(tomorrow_latest.get("prediction"))
@@ -313,6 +336,7 @@ def attach_market_state(payload: dict) -> dict:
             "reason": None if t5_available else state["t5_detail"],
             "latest": mfe_latest,
             "summary": mfe_summary,
+            "history": mfe_history,
         },
     }
     return payload