feat: AI Desks — configurable agent system for news/technical/eco processing
- New ai_desks table with CRUD (get_all/by_type/upsert/delete) - ai_desks router: REST API + GET /signal-catalog (7 extensible signals) - News Desk: semantic dedup via AI (±N days window, system_prompt hint) - Technical Desk: 4 signal detectors driven by desk config (ma_cross, rsi_extreme, bb_squeeze, new_52w_extreme) - 3 more signals in catalog ready to enable: price_gap, volume_spike, macd_crossover - market_event_detector.py loads desk configs at runtime, falls back to legacy params - AIDesks.tsx: full editor UI with signal toggles, param sliders, instrument multi-select - Sidebar: Bot icon + /ai-desks route Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
OpenSquared
@@ -961,6 +961,87 @@ def init_db():
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except Exception:
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pass
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# ── AI Desks ──────────────────────────────────────────────────────────────
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c.execute("""CREATE TABLE IF NOT EXISTS ai_desks (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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name TEXT UNIQUE NOT NULL,
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type TEXT NOT NULL,
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active INTEGER DEFAULT 1,
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system_prompt TEXT DEFAULT '',
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instruments TEXT DEFAULT '[]',
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config TEXT DEFAULT '{}',
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created_at TEXT DEFAULT (datetime('now')),
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updated_at TEXT DEFAULT (datetime('now'))
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)""")
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# Seed default desks (idempotent)
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_AI_DESK_DEFAULTS = [
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{
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"name": "News Desk — Géopolitique",
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"type": "news",
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"active": 1,
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"system_prompt": (
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"Tu es un analyste géopolitique et macro senior. Tu évalues si une news représente "
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"un événement marché STRUCTURANT qui mérite un enregistrement permanent.\n"
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"Sois exigeant : préfère ignorer une news douteuse plutôt qu'enregistrer du bruit.\n"
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"Points d'attention :\n"
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"- Al Jazeera, RT et certains médias régionaux publient souvent plusieurs articles "
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"redondants sur le même fait — vérifie toujours si un événement similaire existe déjà.\n"
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"- Une rumeur ou spéculation sans source officielle ne qualifie pas.\n"
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"- Privilégie les faits avérés avec impact macro ou géopolitique mesurable."
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),
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"instruments": json.dumps(["SPY","GLD","USO","TLT","VXX","EURUSD=X","BTC-USD","XOM"]),
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"config": json.dumps({
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"min_impact": 0.55,
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"lookback_hours": 48,
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"max_evaluate": 15,
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"dedup_enabled": True,
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"dedup_lookback_days": 2,
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"dedup_categories": ["geopolitical","fundamental","report"],
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}),
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},
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{
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"name": "Technical Desk",
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"type": "technical",
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"active": 1,
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"system_prompt": (
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"Tu détectes des signaux techniques structurants sur les marchés financiers. "
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"Concentre-toi sur les signaux qui ont une signification macro claire."
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),
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"instruments": json.dumps([
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"SPY","QQQ","IWM","EEM","GLD","USO","TLT",
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"EURUSD=X","VXX","BTC-USD","NVDA","XOM","HYG"
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]),
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"config": json.dumps({
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"lookback_days": 7,
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"signals": {
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"ma_cross": {"enabled": True, "pairs": [["MA50","MA200"],["MA50","MA100"]]},
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"rsi_extreme": {"enabled": True, "period": 14, "oversold": 30, "overbought": 70},
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"bb_squeeze": {"enabled": True, "period": 20, "std": 2.0, "width_threshold": 0.05},
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"new_52w_extreme":{"enabled": True, "buffer_pct": 0.5},
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},
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}),
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},
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{
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"name": "Eco Desk — FRED",
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"type": "eco",
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"active": 1,
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"system_prompt": "Tu analyses les surprises économiques des données macro US (FRED).",
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"instruments": json.dumps(["SPY","TLT","GLD","EURUSD=X","USO","HYG"]),
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"config": json.dumps({"z_threshold": 1.5, "days": 7}),
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},
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]
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for _desk in _AI_DESK_DEFAULTS:
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try:
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c.execute(
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"INSERT OR IGNORE INTO ai_desks (name, type, active, system_prompt, instruments, config) "
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"VALUES (?,?,?,?,?,?)",
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(_desk["name"], _desk["type"], _desk["active"],
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_desk["system_prompt"], _desk["instruments"], _desk["config"])
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)
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except Exception:
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pass
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conn.commit()
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conn.close()
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@@ -4850,3 +4931,93 @@ def get_weekly_impact_sources(days: int = 7, min_score: float = 0.3) -> List[Dic
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return result
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finally:
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conn.close()
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# ── AI Desks ──────────────────────────────────────────────────────────────────
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def get_all_ai_desks() -> List[Dict[str, Any]]:
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conn = get_conn()
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try:
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rows = conn.execute("SELECT * FROM ai_desks ORDER BY type, name").fetchall()
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result = []
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for r in rows:
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d = dict(r)
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for f in ("instruments", "config"):
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try:
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d[f] = json.loads(d.get(f) or "[]" if f == "instruments" else "{}")
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except Exception:
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d[f] = [] if f == "instruments" else {}
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result.append(d)
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return result
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finally:
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conn.close()
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def get_ai_desk_by_type(desk_type: str) -> Optional[Dict[str, Any]]:
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"""Return the first active desk of given type, or None."""
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desks = get_all_ai_desks()
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return next((d for d in desks if d["type"] == desk_type and d.get("active")), None)
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def upsert_ai_desk(desk: Dict[str, Any]) -> int:
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conn = get_conn()
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try:
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instr = desk.get("instruments", [])
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cfg = desk.get("config", {})
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if isinstance(instr, list):
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instr = json.dumps(instr)
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if isinstance(cfg, dict):
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cfg = json.dumps(cfg)
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conn.execute("""
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INSERT INTO ai_desks (name, type, active, system_prompt, instruments, config, updated_at)
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VALUES (?,?,?,?,?,?, datetime('now'))
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ON CONFLICT(name) DO UPDATE SET
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type=excluded.type, active=excluded.active,
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system_prompt=excluded.system_prompt,
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instruments=excluded.instruments, config=excluded.config,
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updated_at=datetime('now')
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""", (desk["name"], desk["type"], int(desk.get("active", 1)),
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desk.get("system_prompt", ""), instr, cfg))
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row = conn.execute("SELECT id FROM ai_desks WHERE name=?", (desk["name"],)).fetchone()
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conn.commit()
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return row["id"] if row else -1
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finally:
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conn.close()
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def delete_ai_desk(name: str) -> bool:
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conn = get_conn()
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try:
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conn.execute("DELETE FROM ai_desks WHERE name=?", (name,))
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conn.commit()
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return True
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finally:
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conn.close()
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def get_market_events_near_date(date_str: str, days: int = 2,
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categories: Optional[List[str]] = None) -> List[Dict[str, Any]]:
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"""Fetch market_events within ±days of date_str, optionally filtered by category."""
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conn = get_conn()
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try:
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from datetime import datetime, timedelta
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dt = datetime.fromisoformat(date_str[:10])
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d_from = (dt - timedelta(days=days)).strftime("%Y-%m-%d")
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d_to = (dt + timedelta(days=days)).strftime("%Y-%m-%d")
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if categories:
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placeholders = ",".join("?" * len(categories))
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rows = conn.execute(
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f"SELECT id, name, start_date, category, description FROM market_events "
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f"WHERE start_date BETWEEN ? AND ? AND category IN ({placeholders}) "
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f"ORDER BY start_date DESC LIMIT 30",
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[d_from, d_to] + list(categories)
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).fetchall()
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else:
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rows = conn.execute(
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"SELECT id, name, start_date, category, description FROM market_events "
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"WHERE start_date BETWEEN ? AND ? ORDER BY start_date DESC LIMIT 30",
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(d_from, d_to)
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).fetchall()
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return [dict(r) for r in rows]
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finally:
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conn.close()
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