chore: sync local modifications

- active.json: updated days_elapsed from hypothesis runner
- hypotheses.py: black formatting applied by pre-commit hook
- .gitignore: local additions

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

.gitignore

@@ -12,3 +12,11 @@ eval_data/
 .env
 memory_db/
 .worktrees/
+
+# Playwright
+node_modules/
+/test-results/
+/playwright-report/
+/blob-report/
+/playwright/.cache/
+/playwright/.auth/

docs/iterations/hypotheses/active.json

@@ -5,7 +5,7 @@
       "id": "insider_buying-min-txn-100k",
       "scanner": "insider_buying",
       "title": "Raise min_transaction_value to $100K",
-      "description": "Hypothesis: filtering to insider purchases ≥$100K (vs. current $25K) produces higher-quality picks by excluding routine small-lot grants and focusing on high-conviction, out-of-pocket capital deployment. Research (Lakonishok & Lee 2001; Cohen et al. 2012) shows large-value insider buys predict forward returns; small ones do not.",
+      "description": "Hypothesis: filtering to insider purchases \u2265$100K (vs. current $25K) produces higher-quality picks by excluding routine small-lot grants and focusing on high-conviction, out-of-pocket capital deployment. Research (Lakonishok & Lee 2001; Cohen et al. 2012) shows large-value insider buys predict forward returns; small ones do not.",
       "branch": "hypothesis/insider_buying-min-txn-100k",
       "pr_number": 529,
       "status": "running",
@@ -14,10 +14,12 @@
       "hypothesis_type": "implementation",
       "created_at": "2026-04-10",
       "min_days": 21,
-      "days_elapsed": 0,
-      "picks_log": [],
+      "days_elapsed": 1,
+      "picks_log": [
+        "2026-04-10"
+      ],
       "baseline_scanner": "insider_buying",
       "conclusion": null
     }
   ]
-}
+}

tradingagents/ui/pages/hypotheses.py

@@ -12,7 +12,7 @@ from typing import Any, Dict, List
 
 import streamlit as st
 
-from tradingagents.ui.theme import COLORS, page_header
+from tradingagents.ui.theme import page_header
 
 _REPO_ROOT = Path(__file__).parent.parent.parent.parent
 _ACTIVE_JSON = _REPO_ROOT / "docs/iterations/hypotheses/active.json"
@@ -50,13 +50,15 @@ def load_concluded_hypotheses(concluded_dir: str = str(_CONCLUDED_DIR)) -> List[
             scanner = _extract_md_field(text, r"^\*\*Scanner:\*\* (.+)$")
             period = _extract_md_field(text, r"^\*\*Period:\*\* (.+)$")
             outcome = _extract_md_field(text, r"^\*\*Outcome:\*\* (.+)$")
-            results.append({
-                "filename": md_file.name,
-                "title": title or md_file.stem,
-                "scanner": scanner or "—",
-                "period": period or "—",
-                "outcome": outcome or "—",
-            })
+            results.append(
+                {
+                    "filename": md_file.name,
+                    "title": title or md_file.stem,
+                    "scanner": scanner or "—",
+                    "period": period or "—",
+                    "outcome": outcome or "—",
+                }
+            )
         except Exception:
             continue
     return results
@@ -85,7 +87,7 @@ def render() -> None:
 
     if not hypotheses and not concluded:
         st.info(
-            "No hypotheses yet. Run `/backtest-hypothesis \"<description>\"` to start an experiment."
+            'No hypotheses yet. Run `/backtest-hypothesis "<description>"` to start an experiment.'
         )
         return
 
@@ -100,20 +102,23 @@ def render() -> None:
 
     if running or pending:
         import pandas as pd
+
         active_rows = []
         for h in sorted(running + pending, key=lambda x: -x.get("priority", 0)):
             days_left = days_until_ready(h)
             ready_str = "concluding soon" if days_left == 0 else f"{days_left}d left"
-            active_rows.append({
-                "ID": h["id"],
-                "Title": h.get("title", "—"),
-                "Scanner": h.get("scanner", "—"),
-                "Status": h["status"],
-                "Progress": f"{h.get('days_elapsed', 0)}/{h.get('min_days', 14)}d",
-                "Picks": len(h.get("picks_log", [])),
-                "Ready": ready_str,
-                "Priority": h.get("priority", "—"),
-            })
+            active_rows.append(
+                {
+                    "ID": h["id"],
+                    "Title": h.get("title", "—"),
+                    "Scanner": h.get("scanner", "—"),
+                    "Status": h["status"],
+                    "Progress": f"{h.get('days_elapsed', 0)}/{h.get('min_days', 14)}d",
+                    "Picks": len(h.get("picks_log", [])),
+                    "Ready": ready_str,
+                    "Priority": h.get("priority", "—"),
+                }
+            )
         df = pd.DataFrame(active_rows)
         st.dataframe(
             df,
@@ -143,17 +148,20 @@ def render() -> None:
 
     if concluded:
         import pandas as pd
+
         concluded_rows = []
         for c in concluded:
             outcome = c["outcome"]
             emoji = "✅" if "accepted" in outcome else "❌"
-            concluded_rows.append({
-                "Date": c["filename"][:10],
-                "Title": c["title"],
-                "Scanner": c["scanner"],
-                "Period": c["period"],
-                "Outcome": emoji,
-            })
+            concluded_rows.append(
+                {
+                    "Date": c["filename"][:10],
+                    "Title": c["title"],
+                    "Scanner": c["scanner"],
+                    "Period": c["period"],
+                    "Outcome": emoji,
+                }
+            )
         cdf = pd.DataFrame(concluded_rows)
         st.dataframe(
             cdf,