feat: chatbot

backend/main.py

@@ -114,6 +114,14 @@ def startup():
         _log.info("[Startup] Instrument models seeded")
     except Exception as _e:
         _log.warning(f"[Startup] Instrument models seed failed: {_e}")
+    # Backfill wavelet_engine/extremum/level_threshold defaults onto the Technical
+    # Desk so the AI Desks toggle UI matches what's actually computed each cycle
+    try:
+        from services.database import backfill_wavelet_desk_defaults
+        backfill_wavelet_desk_defaults()
+        _log.info("[Startup] Wavelet desk defaults backfilled")
+    except Exception as _e:
+        _log.warning(f"[Startup] Wavelet desk defaults backfill failed: {_e}")
     # Auto-bootstrap désactivé — utiliser les boutons dans Cycle Actions / Timeline
     # Start auto-cycle scheduler if enabled
     from services.auto_cycle import start_scheduler

backend/routers/ai_chat.py

@@ -1,6 +1,8 @@
 """
-Free-form, read-only chat with GPT-4o about the current cockpit state.
-No function-calling — this endpoint can never trigger an action.
+Free-form chat with GPT-4o about the current cockpit state.
+The only tool the model can call (propose_trade) just writes a pending row to
+ai_trade_proposals — it never touches the real portfolio. Confirm/reject below
+are the only way a proposal turns into (or is discarded from) a real position.
 """
 from typing import List, Optional
 
@@ -58,3 +60,50 @@ def clear_session(body: ClearBody):
     clear_chat_session(body.session_id)
     clear_context_cache(body.session_id)
     return {"cleared": body.session_id}
+
+
+@router.get("/trade-proposals")
+def list_trade_proposals(status: str = "pending"):
+    from services.database import get_ai_trade_proposals
+    return {"proposals": get_ai_trade_proposals(status=status)}
+
+
+@router.post("/trade-proposals/{proposal_id}/confirm")
+def confirm_trade_proposal(proposal_id: str):
+    """Promotes a pending AI proposal into a real open position, reusing the
+    same enrichment (live price, Black-Scholes leg pricing) as a manual add."""
+    from services.database import get_ai_trade_proposal, resolve_ai_trade_proposal
+    from routers.portfolio import add_pos, AddPositionRequest
+
+    proposal = get_ai_trade_proposal(proposal_id)
+    if not proposal:
+        raise HTTPException(404, "Proposition introuvable.")
+    if proposal["status"] != "pending":
+        raise HTTPException(400, f"Proposition deja {proposal['status']}.")
+
+    req = AddPositionRequest(
+        title=proposal["title"],
+        underlying=proposal["underlying"],
+        strategy=proposal["strategy"],
+        asset_class=proposal.get("asset_class") or "indices",
+        expiry_days=proposal.get("expiry_days") or 90,
+        legs=proposal.get("legs") or [],
+        capital_invested=proposal["capital_invested"],
+        geo_trigger=proposal.get("geo_trigger") or "",
+        rationale=proposal.get("rationale") or "",
+    )
+    result = add_pos(req)
+    resolve_ai_trade_proposal(proposal_id, "confirmed", portfolio_id=result["id"])
+    return {"status": "confirmed", "portfolio_id": result["id"]}
+
+
+@router.post("/trade-proposals/{proposal_id}/reject")
+def reject_trade_proposal(proposal_id: str):
+    from services.database import get_ai_trade_proposal, resolve_ai_trade_proposal
+    proposal = get_ai_trade_proposal(proposal_id)
+    if not proposal:
+        raise HTTPException(404, "Proposition introuvable.")
+    if proposal["status"] != "pending":
+        raise HTTPException(400, f"Proposition deja {proposal['status']}.")
+    resolve_ai_trade_proposal(proposal_id, "rejected")
+    return {"status": "rejected"}

backend/routers/ai_desks.py

@@ -89,6 +89,84 @@ SIGNAL_CATALOG: List[Dict[str, Any]] = [
             "signal": {"type": "int", "label": "Signal",     "default": 9,  "min": 3,  "max": 20},
         },
     },
+    # ── Wavelets — décomposition en bandes de fréquence sur la watchlist ────
+    {
+        "id":          "wavelet_engine",
+        "label":       "Ondelettes — moteur",
+        "description": "Paramètres partagés du calcul (désactive tous les signaux ondelettes si décoché)",
+        "desk_type":   "technical",
+        "params": {
+            "num_levels":    {"type": "int",    "label": "Nb bandes",    "default": 4,    "min": 2,   "max": 6},
+            "wavelet":       {"type": "select",  "label": "Famille",     "default": "gmw", "options": ["gmw", "morlet", "bump"]},
+            "method":        {"type": "select",  "label": "Méthode",     "default": "cwt", "options": ["cwt", "ssq"]},
+            "lookback_days": {"type": "int",    "label": "Lookback (j)", "default": 120,  "min": 60,  "max": 250},
+        },
+    },
+    {
+        "id":          "wavelet_extremum",
+        "label":       "Ondelettes — extremum",
+        "description": "Pic ou creux confirmé sur une bande",
+        "desk_type":   "technical",
+        "params": {},
+    },
+    {
+        "id":          "wavelet_level_threshold",
+        "label":       "Ondelettes — seuil de niveau",
+        "description": "La bande dépasse un seuil de z-score causal (sur/sous-achetée)",
+        "desk_type":   "technical",
+        "params": {
+            "threshold_k": {"type": "float", "label": "Seuil (écarts-type)", "default": 2.0, "min": 1.0, "max": 4.0},
+        },
+    },
+    {
+        "id":          "wavelet_trend_flatten",
+        "label":       "Ondelettes — tendance puis tassement",
+        "description": "Forte pente suivie d'un aplatissement — signal de fin de mouvement",
+        "desk_type":   "technical",
+        "params": {
+            "trend_days":          {"type": "int",   "label": "Jours tendance",   "default": 10,  "min": 3,  "max": 30},
+            "flatten_days":        {"type": "int",   "label": "Jours tassement",  "default": 5,   "min": 2,  "max": 15},
+            "trend_threshold_k":   {"type": "float", "label": "Seuil tendance",   "default": 1.0, "min": 0.3, "max": 3.0},
+            "flatten_threshold_k": {"type": "float", "label": "Seuil tassement",  "default": 0.3, "min": 0.1, "max": 1.5},
+        },
+    },
+    {
+        "id":          "wavelet_acceleration",
+        "label":       "Ondelettes — déceleration/accélération",
+        "description": "Accélération soutenue en sens inverse de la pente — signal de retournement",
+        "desk_type":   "technical",
+        "params": {
+            "accel_days":       {"type": "int",   "label": "Jours consécutifs", "default": 3,   "min": 1,  "max": 10},
+            "accel_threshold_k":{"type": "float", "label": "Seuil (écarts-type)", "default": 1.5, "min": 0.5, "max": 4.0},
+        },
+    },
+    {
+        "id":          "wavelet_band_cross",
+        "label":       "Ondelettes — croisement de bandes",
+        "description": "Une bande croise une bande secondaire",
+        "desk_type":   "technical",
+        "params": {
+            "secondary_band": {"type": "int", "label": "Index bande secondaire", "default": 1, "min": 0, "max": 5},
+        },
+    },
+    {
+        "id":          "wavelet_ridge_shift",
+        "label":       "Ondelettes — bascule de ridge",
+        "description": "Le cycle dominant (ridge SSQ) dévie de sa moyenne — nécessite méthode = ssq",
+        "desk_type":   "technical",
+        "params": {
+            "threshold_k": {"type": "float", "label": "Seuil (écarts-type)", "default": 2.0, "min": 1.0, "max": 4.0},
+        },
+    },
+    {
+        "id":          "wavelet_energy_threshold",
+        "label":       "Ondelettes — seuil d'énergie",
+        "description": "L'énergie d'une bande dépasse un seuil — nécessite méthode = ssq",
+        "desk_type":   "technical",
+        "params": {
+            "threshold_k": {"type": "float", "label": "Seuil (écarts-type)", "default": 2.0, "min": 1.0, "max": 4.0},
+        },
+    },
     # ── Sentiment signals ───────────────────────────────────────────────────
     {
         "id":          "vix_level",

backend/services/ai_chat.py

@@ -1,11 +1,14 @@
 """
-Free-form, read-only chat with GPT-4o about the current cockpit state.
+Free-form chat with GPT-4o about the current cockpit state.
 
-Deliberately has NO function-calling/tools wired up — a plain text-completion
-call physically cannot trigger any action (no trade, no cycle, no DB write
-beyond persisting the conversation itself). The system prompt also tells the
-model explicitly not to claim it can act, so it doesn't mislead the user.
+The only action the model can trigger is `propose_trade` — even then, it never
+touches the real portfolio: the tool call just writes a 'pending' row to
+ai_trade_proposals. The user has to explicitly confirm from the Trade Ideas UI
+(POST /api/ai-chat/trade-proposals/{id}/confirm) before anything becomes a real
+position. No other tool is wired up, so nothing else can ever be triggered from
+here (no cycle, no data mutation, no close/edit of existing positions).
 """
+import json
 import re
 import time
 from typing import Dict, List, Optional
@@ -18,7 +21,8 @@ Tu as acces ci-dessous a un instantane en lecture seule de la situation actuelle
 
 REGLES IMPORTANTES :
 - Quand on te demande une idee ou un conseil de trade, PROPOSE quelque chose de concret (biais directionnel, instrument, montage d'options avec strikes/echeance si pertinent, niveaux techniques, justification tiree du contexte) - exactement comme le ferait le cycle automatique dans ses recommandations. Ne te contente pas d'observations vagues ni de renvoyer la question : prends position a partir du contexte fourni.
-- La seule limite reelle est que tu ne peux EXECUTER aucune action toi-meme (aucun trade n'est passe, aucun cycle n'est declenche, aucune donnee n'est modifiee) - tes idees sont des suggestions que l'utilisateur doit valider et executer lui-meme ailleurs dans le cockpit. Ne le precise que si l'utilisateur semble croire que tu peux agir directement (ex. "achete X pour moi").
+- Tu disposes de l'outil propose_trade pour enregistrer une idee concrete. Utilise-le UNIQUEMENT quand l'utilisateur demande explicitement un conseil de trade ou valide clairement une idee que tu viens de suggerer - jamais de maniere systematique a chaque message. Chaque appel cree une proposition EN ATTENTE dans Trade Ideas ; rien n'est jamais execute automatiquement.
+- La seule limite reelle est que tu ne peux EXECUTER aucune action toi-meme (aucun trade n'est passe directement, aucun cycle n'est declenche, aucune position existante n'est modifiee) - tes idees sont des suggestions que l'utilisateur doit valider lui-meme. Ne le precise que si l'utilisateur semble croire que tu peux agir directement (ex. "achete X pour moi").
 - Reponds en francais, de facon concise et directe, en t'appuyant sur le contexte fourni. Si une donnee demandee n'est pas dans le contexte ci-dessous, dis-le plutot que d'inventer.
 
 === CONTEXTE ACTUEL ===
@@ -26,11 +30,55 @@ REGLES IMPORTANTES :
 === FIN DU CONTEXTE ===
 """
 
+TRADE_PROPOSAL_TOOL = {
+    "type": "function",
+    "function": {
+        "name": "propose_trade",
+        "description": (
+            "Enregistre une idee de trade concrete EN ATTENTE dans Trade Ideas. "
+            "N'execute RIEN et n'ouvre AUCUNE position — l'utilisateur doit explicitement "
+            "confirmer depuis l'interface pour que ca devienne un trade reel dans le portefeuille. "
+            "N'appelle cet outil que lorsque l'utilisateur demande explicitement un conseil de trade "
+            "ou valide clairement une idee que tu as suggeree — jamais de maniere systematique."
+        ),
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "title": {"type": "string", "description": "Titre court de l'idee"},
+                "underlying": {"type": "string", "description": "Ticker Yahoo Finance du sous-jacent (ex: EURUSD=X, CL=F, SPY, GC=F)"},
+                "strategy": {"type": "string", "description": "Nom de la strategie (ex: long call, put spread, straddle, short strangle, directionnel spot)"},
+                "asset_class": {"type": "string", "enum": ["indices", "forex", "commodities", "rates", "crypto", "equities"]},
+                "expiry_days": {"type": "integer", "description": "Horizon en jours jusqu'a l'echeance"},
+                "capital_invested": {"type": "number", "description": "Capital alloue en EUR"},
+                "legs": {
+                    "type": "array",
+                    "description": "Legs optionnelles du montage (liste vide pour un trade directionnel simple sans options)",
+                    "items": {
+                        "type": "object",
+                        "properties": {
+                            "strike": {"type": "number"},
+                            "option_type": {"type": "string", "enum": ["call", "put"]},
+                            "quantity": {"type": "integer"},
+                            "position": {"type": "string", "enum": ["long", "short"]},
+                        },
+                        "required": ["strike", "option_type", "quantity", "position"],
+                    },
+                },
+                "geo_trigger": {"type": "string", "description": "Evenement/catalyseur declencheur, si pertinent"},
+                "rationale": {"type": "string", "description": "Justification concise, appuyee sur le contexte fourni"},
+            },
+            "required": ["title", "underlying", "strategy", "capital_invested", "rationale"],
+        },
+    },
+}
 
-def _chat_messages(system: str, messages: List[Dict], model: str = "gpt-4o", max_tokens: int = 1200) -> str:
+
+def _chat_messages(system: str, messages: List[Dict], model: str = "gpt-4o", max_tokens: int = 1200, tools: Optional[List[Dict]] = None):
     """Multi-turn variant of ai_analyzer._chat() — accepts a full message history
-    instead of a single system+user pair. Same client/retry/backoff logic, kept
-    independent so it never risks the well-tested cycle-facing _chat()."""
+    instead of a single system+user pair, and optionally OpenAI tool schemas.
+    Returns the raw SDK message object (not just its text) so callers can
+    inspect tool_calls. Same client/retry/backoff logic, kept independent so it
+    never risks the well-tested cycle-facing _chat()."""
     client = get_client()
     if not client:
         raise RuntimeError("OpenAI API key not configured")
@@ -41,12 +89,14 @@ def _chat_messages(system: str, messages: List[Dict], model: str = "gpt-4o", max
         "temperature": 0.4,
         "max_tokens": max_tokens,
     }
+    if tools:
+        kwargs["tools"] = tools
 
     last_exc: Optional[Exception] = None
     for attempt in range(4):
         try:
             resp = client.chat.completions.create(**kwargs)
-            return resp.choices[0].message.content or ""
+            return resp.choices[0].message
         except Exception as e:
             last_exc = e
             err_str = str(e)
@@ -59,6 +109,27 @@ def _chat_messages(system: str, messages: List[Dict], model: str = "gpt-4o", max
     raise last_exc  # type: ignore[misc]
 
 
+def _handle_tool_call(tc, session_id: str) -> tuple:
+    """Executes one tool call. Returns (tool_result_text, trade_proposal_or_None)."""
+    from services.database import save_ai_trade_proposal
+
+    if tc.function.name != "propose_trade":
+        return "Outil inconnu.", None
+
+    try:
+        args = json.loads(tc.function.arguments or "{}")
+        proposal_id = save_ai_trade_proposal({**args, "session_id": session_id})
+        trade_proposal = {
+            "id": proposal_id,
+            "title": args.get("title"),
+            "underlying": args.get("underlying"),
+            "strategy": args.get("strategy"),
+        }
+        return f"Proposition enregistree (id={proposal_id}), EN ATTENTE dans Trade Ideas. Rien n'a ete execute.", trade_proposal
+    except Exception as e:
+        return f"Erreur lors de l'enregistrement de la proposition: {e}", None
+
+
 def send_chat_message(
     session_id: str,
     message: str,
@@ -77,7 +148,29 @@ def send_chat_message(
     messages.append({"role": "user", "content": message})
 
     save_chat_message(session_id, "user", message)
-    reply = _chat_messages(system, messages)
-    save_chat_message(session_id, "assistant", reply)
 
-    return {"reply": reply, "blocks_included": list(blocks.keys())}
+    reply_msg = _chat_messages(system, messages, tools=[TRADE_PROPOSAL_TOOL])
+    trade_proposal = None
+
+    if reply_msg.tool_calls:
+        messages.append({
+            "role": "assistant",
+            "content": reply_msg.content,
+            "tool_calls": [
+                {"id": tc.id, "type": "function", "function": {"name": tc.function.name, "arguments": tc.function.arguments}}
+                for tc in reply_msg.tool_calls
+            ],
+        })
+        for tc in reply_msg.tool_calls:
+            tool_result, proposal = _handle_tool_call(tc, session_id)
+            trade_proposal = proposal or trade_proposal
+            messages.append({"role": "tool", "tool_call_id": tc.id, "content": tool_result})
+
+        final_msg = _chat_messages(system, messages)  # no tools this round — forces a final text reply
+        reply_text = final_msg.content or ""
+    else:
+        reply_text = reply_msg.content or ""
+
+    save_chat_message(session_id, "assistant", reply_text)
+
+    return {"reply": reply_text, "blocks_included": list(blocks.keys()), "trade_proposal": trade_proposal}

backend/services/ai_chat_context.py

@@ -87,13 +87,29 @@ def _block_tech_indicators() -> str:
 
 
 def _block_wavelet_signals() -> str:
-    from services.database import get_latest_wavelet_signals
-    signals = get_latest_wavelet_signals()
-    if not signals:
-        return "## WAVELET SIGNALS\nNo wavelet signal detected yet (computed each auto-cycle)."
-    lines = ["## WAVELET SIGNALS (watchlist, latest cycle scan)"]
-    for s in signals[:20]:
-        lines.append(f"- {s['ticker']}: band {s['band_label']} · {s['signal_kind']} · {s['direction']} @ {s.get('price_at_signal')}")
+    from services.database import get_latest_wavelet_state
+    rows = get_latest_wavelet_state()
+    if not rows:
+        return "## WAVELET SIGNALS\nNo wavelet state computed yet (computed each auto-cycle for the watchlist instruments)."
+
+    by_ticker: Dict[str, List[Dict]] = {}
+    for r in rows:
+        by_ticker.setdefault(r["ticker"], []).append(r)
+
+    lines = ["## WAVELET SIGNALS (watchlist, latest cycle — slope/energy/ridge state + any active trigger)"]
+    for ticker, band_rows in list(by_ticker.items())[:12]:
+        lines.append(f"### {ticker}")
+        for r in band_rows:
+            tag = f" -> SIGNAL {r['signal_kind']} ({r['direction']})" if r.get("signal_kind") else ""
+            if r["band_label"] == "ridge":
+                if r.get("ridge_period_days") is not None:
+                    lines.append(f"- ridge (cycle dominant): {r['ridge_period_days']:.1f}j{tag}")
+                continue
+            period = f"{r['period_low_days']}-{r['period_high_days']}j" if r.get("period_low_days") is not None else r["band_label"]
+            slope = r.get("slope")
+            slope_txt = f"pente {'+' if slope >= 0 else ''}{slope:.4f}" if slope is not None else "pente n/a"
+            energy_txt = f", energie {r['energy']:.4f}" if r.get("energy") is not None else ""
+            lines.append(f"- {r['band_label']} [{period}]: valeur {r.get('value')}, {slope_txt}{energy_txt}{tag}")
     return "\n".join(lines)
 
 

backend/services/database.py

@@ -143,6 +143,32 @@ def init_db():
             content TEXT NOT NULL,
             created_at TEXT DEFAULT (datetime('now'))
         )""",
+        # AI Chat widget — trade ideas proposed by the AI via function-calling, pending
+        # user confirmation before they ever touch the real portfolio table
+        """CREATE TABLE IF NOT EXISTS ai_trade_proposals (
+            id TEXT PRIMARY KEY,
+            session_id TEXT NOT NULL,
+            created_at TEXT DEFAULT (datetime('now')),
+            status TEXT DEFAULT 'pending',
+            title TEXT NOT NULL,
+            underlying TEXT NOT NULL,
+            strategy TEXT NOT NULL,
+            asset_class TEXT DEFAULT 'indices',
+            expiry_days INTEGER DEFAULT 90,
+            capital_invested REAL NOT NULL,
+            legs_json TEXT NOT NULL,
+            geo_trigger TEXT DEFAULT '',
+            rationale TEXT DEFAULT '',
+            portfolio_id TEXT,
+            resolved_at TEXT
+        )""",
+        # Wavelets — richer per-cycle state (slope/energy/ridge), one row per (ticker, band)
+        # every cycle regardless of whether a signal fired (was: only on firing)
+        "ALTER TABLE wavelet_watchlist_signals ADD COLUMN slope REAL",
+        "ALTER TABLE wavelet_watchlist_signals ADD COLUMN value REAL",
+        "ALTER TABLE wavelet_watchlist_signals ADD COLUMN energy REAL",
+        "ALTER TABLE wavelet_watchlist_signals ADD COLUMN ridge_period_days REAL",
+        "ALTER TABLE wavelet_watchlist_signals ADD COLUMN params_json TEXT",
     ]:
         try:
             c.execute(_sql)
@@ -153,6 +179,10 @@ def init_db():
         c.execute("CREATE INDEX IF NOT EXISTS idx_wws_ticker_date ON wavelet_watchlist_signals(ticker, computed_at DESC)")
     except Exception:
         pass
+    try:
+        c.execute("CREATE INDEX IF NOT EXISTS idx_atp_session_status ON ai_trade_proposals(session_id, status)")
+    except Exception:
+        pass
 
     try:
         c.execute("CREATE INDEX IF NOT EXISTS idx_chat_session_date ON ai_chat_messages(session_id, created_at)")
@@ -3192,25 +3222,51 @@ def save_wavelet_signals(run_id: str, signals: List[Dict]) -> None:
     for s in signals:
         conn.execute(
             "INSERT INTO wavelet_watchlist_signals "
-            "(run_id, ticker, band_label, period_low_days, period_high_days, signal_kind, direction, price_at_signal) "
-            "VALUES (?, ?, ?, ?, ?, ?, ?, ?)",
+            "(run_id, ticker, band_label, period_low_days, period_high_days, signal_kind, direction, price_at_signal, "
+            "slope, value, energy, ridge_period_days, params_json) "
+            "VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
             (run_id, s.get("ticker"), s.get("band_label"), s.get("period_low_days"), s.get("period_high_days"),
-             s.get("signal_kind"), s.get("direction"), s.get("price_at_signal")),
+             s.get("signal_kind"), s.get("direction"), s.get("price_at_signal"),
+             s.get("slope"), s.get("value"), s.get("energy"), s.get("ridge_period_days"), s.get("params_json")),
         )
     conn.commit()
     conn.close()
 
 
+def _latest_wavelet_run_id() -> Optional[str]:
+    conn = get_conn()
+    row = conn.execute(
+        "SELECT run_id FROM wavelet_watchlist_signals ORDER BY computed_at DESC LIMIT 1"
+    ).fetchone()
+    conn.close()
+    return row["run_id"] if row else None
+
+
 def get_latest_wavelet_signals() -> List[Dict]:
-    """Most recent signal per ticker (one row per ticker, its latest computed_at)."""
+    """Fired signals only (signal_kind IS NOT NULL) from the most recent cycle
+    scan — feeds the Dashboard 'Wavelets Signal' card, unchanged behavior."""
+    run_id = _latest_wavelet_run_id()
+    if not run_id:
+        return []
     conn = get_conn()
     rows = conn.execute(
-        """SELECT w.* FROM wavelet_watchlist_signals w
-           INNER JOIN (
-               SELECT ticker, MAX(computed_at) AS max_computed_at
-               FROM wavelet_watchlist_signals GROUP BY ticker
-           ) latest ON w.ticker = latest.ticker AND w.computed_at = latest.max_computed_at
-           ORDER BY w.computed_at DESC"""
+        "SELECT * FROM wavelet_watchlist_signals WHERE run_id=? AND signal_kind IS NOT NULL ORDER BY computed_at DESC",
+        (run_id,),
+    ).fetchall()
+    conn.close()
+    return [dict(r) for r in rows]
+
+
+def get_latest_wavelet_state() -> List[Dict]:
+    """Every (ticker, band) row from the most recent cycle scan — signal or
+    not. Used for the rich AI chat context block (slope/energy/ridge state)."""
+    run_id = _latest_wavelet_run_id()
+    if not run_id:
+        return []
+    conn = get_conn()
+    rows = conn.execute(
+        "SELECT * FROM wavelet_watchlist_signals WHERE run_id=? ORDER BY ticker, band_label",
+        (run_id,),
     ).fetchall()
     conn.close()
     return [dict(r) for r in rows]
@@ -3255,6 +3311,72 @@ def clear_chat_session(session_id: str) -> None:
     conn.close()
 
 
+# ── AI Chat widget — trade proposals (pending confirmation) ────────────────────
+
+def save_ai_trade_proposal(proposal: Dict[str, Any]) -> str:
+    import uuid
+    proposal_id = uuid.uuid4().hex
+    conn = get_conn()
+    conn.execute(
+        """INSERT INTO ai_trade_proposals (
+            id, session_id, status, title, underlying, strategy, asset_class,
+            expiry_days, capital_invested, legs_json, geo_trigger, rationale
+        ) VALUES (?, ?, 'pending', ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
+        (
+            proposal_id, proposal["session_id"], proposal["title"], proposal["underlying"],
+            proposal["strategy"], proposal.get("asset_class", "indices"),
+            proposal.get("expiry_days", 90), proposal["capital_invested"],
+            json.dumps(proposal.get("legs", [])), proposal.get("geo_trigger", ""),
+            proposal.get("rationale", ""),
+        ),
+    )
+    conn.commit()
+    conn.close()
+    return proposal_id
+
+
+def get_ai_trade_proposal(proposal_id: str) -> Optional[Dict[str, Any]]:
+    conn = get_conn()
+    row = conn.execute("SELECT * FROM ai_trade_proposals WHERE id=?", (proposal_id,)).fetchone()
+    conn.close()
+    if not row:
+        return None
+    d = dict(row)
+    try:
+        d["legs"] = json.loads(d.pop("legs_json") or "[]")
+    except Exception:
+        d["legs"] = []
+    return d
+
+
+def get_ai_trade_proposals(status: str = "pending") -> List[Dict[str, Any]]:
+    conn = get_conn()
+    rows = conn.execute(
+        "SELECT * FROM ai_trade_proposals WHERE status=? ORDER BY created_at DESC",
+        (status,),
+    ).fetchall()
+    conn.close()
+    out = []
+    for r in rows:
+        d = dict(r)
+        try:
+            d["legs"] = json.loads(d.pop("legs_json") or "[]")
+        except Exception:
+            d["legs"] = []
+        out.append(d)
+    return out
+
+
+def resolve_ai_trade_proposal(proposal_id: str, status: str, portfolio_id: Optional[str] = None) -> None:
+    conn = get_conn()
+    conn.execute(
+        "UPDATE ai_trade_proposals SET status=?, portfolio_id=?, resolved_at=datetime('now') WHERE id=?",
+        (status, portfolio_id, proposal_id),
+    )
+    conn.commit()
+    conn.close()
+
+
 # ── System Logs ───────────────────────────────────────────────────────────────
 
 def log_system_event(
@@ -5498,6 +5620,32 @@ def get_ai_desk_by_type(desk_type: str) -> Optional[Dict[str, Any]]:
     return next((d for d in desks if d["type"] == desk_type and d.get("active")), None)
 
 
+def backfill_wavelet_desk_defaults() -> None:
+    """One-time idempotent patch for Technical Desks created before the wavelet
+    signal catalog existed: wavelet_signals.py treats wavelet_engine/
+    wavelet_extremum/wavelet_level_threshold as enabled when absent from
+    config.signals (preserves the always-on pre-desk-config behavior), but the
+    AI Desks toggle UI shows a missing key as OFF — writing the explicit
+    defaults here keeps what the UI displays honest about what's computed."""
+    desk = get_ai_desk_by_type("technical")
+    if not desk:
+        return
+    signals = (desk.get("config") or {}).get("signals") or {}
+    defaults = {
+        "wavelet_engine": {"enabled": True, "num_levels": 4, "wavelet": "gmw", "method": "cwt", "lookback_days": 120},
+        "wavelet_extremum": {"enabled": True},
+        "wavelet_level_threshold": {"enabled": True, "threshold_k": 2.0},
+    }
+    changed = False
+    for key, val in defaults.items():
+        if key not in signals:
+            signals[key] = val
+            changed = True
+    if changed:
+        desk["config"]["signals"] = signals
+        update_ai_desk_by_id(desk["id"], desk)
+
+
 def upsert_ai_desk(desk: Dict[str, Any]) -> int:
     conn = get_conn()
     try:

backend/services/wavelet_signals.py

@@ -2,17 +2,53 @@
 Automated wavelet signal detection for the watchlist — run once per cycle.
 
 Ported (Python subset) from the trigger-signal detectors in
-c:\\DataS\\InstrumentSimulator\\frontend\\src\\main.tsx (lines 180-280, TypeScript).
-Only `extremum` and `level_threshold` are ported here: they're self-contained
-(single curve, no secondary curve/config needed) and robust enough for an
-unattended scan. The richer configurable trigger set (trend_flatten,
-acceleration, band_cross, ridge_shift, energy_threshold) stays exclusive to the
-interactive Wavelets Simulation page (frontend/src/lib/waveletTrade.ts), where a
-user picks and tunes them explicitly.
+c:\\DataS\\InstrumentSimulator\\frontend\\src\\main.tsx / frontend/src/lib/waveletTrade.ts.
+All 7 trigger kinds from the interactive Wavelets Simulation page are now
+available here: extremum, level_threshold, trend_flatten, acceleration,
+band_cross, ridge_shift (ssq only), energy_threshold (ssq only).
+
+Parameters (engine + per-signal enable/thresholds) come from the "Technical
+Desk" (services.database.get_ai_desk_by_type("technical"), config.signals.wavelet_*)
+so they're editable from the existing AI Desks config UI — no hardcoded
+defaults here beyond a safe fallback when the desk/key is absent. The
+instrument scope stays get_instruments_watchlist() (the desk's own
+`instruments` list is NOT used, to avoid reintroducing a second overlapping
+instrument-list source).
+
+Every (ticker, band) gets a row every cycle now — signal or not — so the AI
+chat context always has fresh slope/energy/ridge state, not just firing
+events (see ai_chat_context.py:_block_wavelet_signals).
 """
+import json
 from typing import Dict, List, Optional
 
 
+def _compute_slope(series: List[float]) -> List[float]:
+    n = len(series)
+    slope = [0.0] * n
+    for i in range(1, n):
+        slope[i] = series[i] - series[i - 1]
+    if n > 1:
+        slope[0] = slope[1]
+    return slope
+
+
+def _compute_acceleration(slope: List[float]) -> List[float]:
+    n = len(slope)
+    accel = [0.0] * n
+    for i in range(1, n):
+        accel[i] = slope[i] - slope[i - 1]
+    if n > 1:
+        accel[0] = accel[1]
+    return accel
+
+
+def _avg_slope_range(slope: List[float], frm: int, to: int) -> Optional[float]:
+    if frm < 0 or to > len(slope) - 1 or to <= frm:
+        return None
+    return sum(slope[frm + 1:to + 1]) / (to - frm)
+
+
 def _build_extremum_signal(series: List[float], direction: str) -> List[bool]:
     n = len(series)
     raw = [False] * n
@@ -52,6 +88,88 @@ def _build_level_threshold_signal(series: List[float], direction: str, threshold
     return signal
 
 
+def _build_trend_flatten_signal(series: List[float], direction: str, trend_days: int, flatten_days: int,
+                                 trend_threshold_k: float, flatten_threshold_k: float) -> List[bool]:
+    n = len(series)
+    slope = _compute_slope(series)
+    signal = [False] * n
+    s = 0.0
+    sq = 0.0
+    for t in range(1, n):
+        s += slope[t]
+        sq += slope[t] * slope[t]
+        count = t
+        if t < trend_days + flatten_days or count < 20:
+            continue
+        mean = s / count
+        variance = max(0.0, sq / count - mean * mean)
+        std = variance ** 0.5
+        trend_thresh = trend_threshold_k * std
+        flatten_thresh = flatten_threshold_k * std
+        trend = _avg_slope_range(slope, t - flatten_days - trend_days, t - flatten_days)
+        flat = _avg_slope_range(slope, t - flatten_days, t)
+        if trend is None or flat is None:
+            continue
+        if direction == "up" and trend > trend_thresh and abs(flat) <= flatten_thresh:
+            signal[t] = True
+        if direction == "down" and trend < -trend_thresh and abs(flat) <= flatten_thresh:
+            signal[t] = True
+    return signal
+
+
+def _build_acceleration_signal(series: List[float], direction: str, days: int, threshold_k: float) -> List[bool]:
+    n = len(series)
+    slope = _compute_slope(series)
+    accel = _compute_acceleration(slope)
+    signal = [False] * n
+    s = 0.0
+    sq = 0.0
+    for t in range(2, n):
+        s += accel[t]
+        sq += accel[t] * accel[t]
+        count = t - 1
+        if t < days or count < 20:
+            continue
+        mean = s / count
+        variance = max(0.0, sq / count - mean * mean)
+        std = variance ** 0.5
+        thresh = threshold_k * std
+        if direction == "up":
+            if slope[t] <= 0:
+                continue
+            ok = True
+            for d in range(days):
+                idx = t - d
+                if idx < 0 or not (accel[idx] < -thresh):
+                    ok = False
+                    break
+            signal[t] = ok
+        else:
+            if slope[t] >= 0:
+                continue
+            ok = True
+            for d in range(days):
+                idx = t - d
+                if idx < 0 or not (accel[idx] > thresh):
+                    ok = False
+                    break
+            signal[t] = ok
+    return signal
+
+
+def _build_band_cross_signal(primary: List[float], secondary: List[float], direction: str) -> List[bool]:
+    n = min(len(primary), len(secondary))
+    signal = [False] * n
+    for t in range(1, n):
+        prev_diff = primary[t - 1] - secondary[t - 1]
+        curr_diff = primary[t] - secondary[t]
+        if direction == "down" and prev_diff >= 0 and curr_diff < 0:
+            signal[t] = True
+        if direction == "up" and prev_diff <= 0 and curr_diff > 0:
+            signal[t] = True
+    return signal
+
+
 def detect_extremum_signal(series: List[float]) -> Optional[str]:
     """Returns 'up' (confirmed peak) or 'down' (confirmed trough) if the most
     recent point is a signal, else None."""
@@ -76,16 +194,73 @@ def detect_level_threshold_signal(series: List[float], threshold_k: float = 2.0)
     return None
 
 
-def scan_watchlist_wavelet_signals(num_levels: int = 4, wavelet: str = "gmw", lookback: int = 120, method: str = "cwt") -> List[Dict]:
+def detect_trend_flatten_signal(series: List[float], trend_days: int = 10, flatten_days: int = 5,
+                                 trend_threshold_k: float = 1.0, flatten_threshold_k: float = 0.3) -> Optional[str]:
+    if len(series) < trend_days + flatten_days + 20:
+        return None
+    if _build_trend_flatten_signal(series, "up", trend_days, flatten_days, trend_threshold_k, flatten_threshold_k)[-1]:
+        return "up"
+    if _build_trend_flatten_signal(series, "down", trend_days, flatten_days, trend_threshold_k, flatten_threshold_k)[-1]:
+        return "down"
+    return None
+
+
+def detect_acceleration_signal(series: List[float], accel_days: int = 3, accel_threshold_k: float = 1.5) -> Optional[str]:
+    if len(series) < accel_days + 20:
+        return None
+    if _build_acceleration_signal(series, "up", accel_days, accel_threshold_k)[-1]:
+        return "up"
+    if _build_acceleration_signal(series, "down", accel_days, accel_threshold_k)[-1]:
+        return "down"
+    return None
+
+
+def detect_band_cross_signal(primary: List[float], secondary: List[float]) -> Optional[str]:
+    if len(primary) < 2 or len(secondary) < 2:
+        return None
+    if _build_band_cross_signal(primary, secondary, "up")[-1]:
+        return "up"
+    if _build_band_cross_signal(primary, secondary, "down")[-1]:
+        return "down"
+    return None
+
+
+def _technical_desk_wavelet_config() -> Dict:
+    from services.database import get_ai_desk_by_type
+    desk = get_ai_desk_by_type("technical") or {}
+    return (desk.get("config") or {}).get("signals") or {}
+
+
+def scan_watchlist_wavelet_signals() -> List[Dict]:
     """Compute a causal (no-look-ahead) band decomposition for each watchlist
-    instrument and flag any band whose most recent point is a signal. Only the
-    trailing ~60 output points are computed (not the whole history) — this scan
-    only needs to know about *today*, unlike the interactive Simulation page's
-    full-range backtest."""
+    instrument. Every (ticker, band) gets a row every cycle — current slope/
+    value/energy state always, plus signal_kind/direction/params_json when one
+    of the enabled trigger kinds fires on the most recent point (first match
+    wins, evaluated extremum -> level_threshold -> trend_flatten ->
+    acceleration -> band_cross -> energy_threshold). ridge_shift is evaluated
+    once per ticker (not per band — the ridge is a single track for the whole
+    decomposition) and stored as an extra band_label="ridge" row."""
     from services.database import get_instruments_watchlist
     from services.data_fetcher import get_historical
     from services.wavelet_engine import rolling_causal_bands, rolling_causal_bands_ssq
 
+    sig_cfg = _technical_desk_wavelet_config()
+    engine_cfg = sig_cfg.get("wavelet_engine") or {}
+    if not engine_cfg.get("enabled", True):
+        return []
+    num_levels = int(engine_cfg.get("num_levels", 4))
+    wavelet = engine_cfg.get("wavelet", "gmw")
+    method = engine_cfg.get("method", "cwt")
+    lookback = int(engine_cfg.get("lookback_days", 120))
+
+    extremum_cfg = sig_cfg.get("wavelet_extremum") or {"enabled": True}
+    level_cfg = sig_cfg.get("wavelet_level_threshold") or {"enabled": True, "threshold_k": 2.0}
+    trend_cfg = sig_cfg.get("wavelet_trend_flatten") or {"enabled": False}
+    accel_cfg = sig_cfg.get("wavelet_acceleration") or {"enabled": False}
+    cross_cfg = sig_cfg.get("wavelet_band_cross") or {"enabled": False}
+    ridge_cfg = sig_cfg.get("wavelet_ridge_shift") or {"enabled": False}
+    energy_cfg = sig_cfg.get("wavelet_energy_threshold") or {"enabled": False}
+
     results: List[Dict] = []
     decomposer = rolling_causal_bands_ssq if method == "ssq" else rolling_causal_bands
 
@@ -106,23 +281,94 @@ def scan_watchlist_wavelet_signals(num_levels: int = 4, wavelet: str = "gmw", lo
             if not decomposed["dates"]:
                 continue
             price_at_signal = decomposed["original"][-1]
+            bands = decomposed["bands"]
 
-            for band in decomposed["bands"]:
+            for i, band in enumerate(bands):
                 series = band["series"]
-                direction = detect_extremum_signal(series)
-                kind = "extremum" if direction else None
-                if not direction:
-                    direction = detect_level_threshold_signal(series)
-                    kind = "level_threshold" if direction else None
-                if kind and direction:
+                if not series:
+                    continue
+                slope = _compute_slope(series)
+                energy = band.get("energy")
+
+                kind: Optional[str] = None
+                direction: Optional[str] = None
+                params: Optional[Dict] = None
+
+                if extremum_cfg.get("enabled", True):
+                    direction = detect_extremum_signal(series)
+                    kind = "extremum" if direction else None
+                if not direction and level_cfg.get("enabled", True):
+                    threshold_k = level_cfg.get("threshold_k", 2.0)
+                    direction = detect_level_threshold_signal(series, threshold_k)
+                    if direction:
+                        kind, params = "level_threshold", {"threshold_k": threshold_k}
+                if not direction and trend_cfg.get("enabled"):
+                    direction = detect_trend_flatten_signal(
+                        series,
+                        trend_cfg.get("trend_days", 10), trend_cfg.get("flatten_days", 5),
+                        trend_cfg.get("trend_threshold_k", 1.0), trend_cfg.get("flatten_threshold_k", 0.3),
+                    )
+                    if direction:
+                        kind = "trend_flatten"
+                        params = {k: trend_cfg.get(k) for k in ("trend_days", "flatten_days", "trend_threshold_k", "flatten_threshold_k")}
+                if not direction and accel_cfg.get("enabled"):
+                    accel_days = accel_cfg.get("accel_days", 3)
+                    accel_threshold_k = accel_cfg.get("accel_threshold_k", 1.5)
+                    direction = detect_acceleration_signal(series, accel_days, accel_threshold_k)
+                    if direction:
+                        kind, params = "acceleration", {"accel_days": accel_days, "accel_threshold_k": accel_threshold_k}
+                if not direction and cross_cfg.get("enabled"):
+                    sec_idx = int(cross_cfg.get("secondary_band", 1))
+                    if 0 <= sec_idx < len(bands) and sec_idx != i:
+                        direction = detect_band_cross_signal(series, bands[sec_idx]["series"])
+                        if direction:
+                            kind, params = "band_cross", {"secondary_band": sec_idx}
+                if not direction and energy_cfg.get("enabled") and energy:
+                    threshold_k = energy_cfg.get("threshold_k", 2.0)
+                    direction = detect_level_threshold_signal(energy, threshold_k)
+                    if direction:
+                        kind, params = "energy_threshold", {"threshold_k": threshold_k}
+
+                results.append({
+                    "ticker": ticker,
+                    "band_label": band["label"],
+                    "period_low_days": band.get("period_low_days"),
+                    "period_high_days": band.get("period_high_days"),
+                    "signal_kind": kind,
+                    "direction": direction,
+                    "price_at_signal": price_at_signal,
+                    "slope": slope[-1],
+                    "value": series[-1],
+                    "energy": energy[-1] if energy else None,
+                    "ridge_period_days": None,
+                    "params_json": json.dumps(params) if params else None,
+                })
+
+            # Ridge — one row per ticker (ssq only), not per band
+            if method == "ssq" and decomposed.get("ridge_period_days"):
+                ridge_series = [v for v in decomposed["ridge_period_days"] if v is not None]
+                if ridge_series:
+                    ridge_kind = None
+                    ridge_direction = None
+                    ridge_params = None
+                    if ridge_cfg.get("enabled"):
+                        threshold_k = ridge_cfg.get("threshold_k", 2.0)
+                        ridge_direction = detect_level_threshold_signal(ridge_series, threshold_k)
+                        if ridge_direction:
+                            ridge_kind, ridge_params = "ridge_shift", {"threshold_k": threshold_k}
                     results.append({
                         "ticker": ticker,
-                        "band_label": band["label"],
-                        "period_low_days": band.get("period_low_days"),
-                        "period_high_days": band.get("period_high_days"),
-                        "signal_kind": kind,
-                        "direction": direction,
+                        "band_label": "ridge",
+                        "period_low_days": None,
+                        "period_high_days": None,
+                        "signal_kind": ridge_kind,
+                        "direction": ridge_direction,
                         "price_at_signal": price_at_signal,
+                        "slope": None,
+                        "value": None,
+                        "energy": None,
+                        "ridge_period_days": ridge_series[-1],
+                        "params_json": json.dumps(ridge_params) if ridge_params else None,
                     })
         except Exception:
             continue  # one bad ticker must not abort the whole scan

frontend/src/components/ChatWidget.tsx

@@ -84,7 +84,7 @@ export default function ChatWidget() {
         refresh_context: pendingRefresh,
       })
       setPendingRefresh(false)
-      setMessages(prev => [...prev, { role: 'assistant', content: res.reply }])
+      setMessages(prev => [...prev, { role: 'assistant', content: res.reply, trade_proposal: res.trade_proposal }])
     } catch (e: any) {
       const msg = e?.response?.data?.detail ?? 'Erreur — vérifie la clé API OpenAI dans Configuration.'
       setMessages(prev => [...prev, { role: 'assistant', content: `⚠️ ${msg}` }])
@@ -164,13 +164,18 @@ export default function ChatWidget() {
             </div>
           )}
           {messages.map((m, i) => (
-            <div key={i} className={clsx('flex', m.role === 'user' ? 'justify-end' : 'justify-start')}>
+            <div key={i} className={clsx('flex flex-col', m.role === 'user' ? 'items-end' : 'items-start')}>
               <div className={clsx(
                 'max-w-[85%] rounded-lg px-3 py-2 text-xs whitespace-pre-wrap leading-relaxed',
                 m.role === 'user' ? 'bg-blue-600 text-white' : 'bg-dark-700/80 border border-slate-700/40 text-slate-200',
               )}>
                 {m.content}
               </div>
+              {m.trade_proposal && (
+                <div className="mt-1 text-[10px] px-2 py-1 rounded bg-emerald-900/30 border border-emerald-700/40 text-emerald-400">
+                  ✅ Idée ajoutée → Trade Ideas ({m.trade_proposal.title})
+                </div>
+              )}
             </div>
           ))}
           {isPending && (

frontend/src/components/TradeIdeas.tsx

@@ -2,11 +2,11 @@ import { useState, useMemo, useEffect, Fragment } from 'react'
 import {
   useAllPatterns, useLastScores, useScorePatterns, useAiStatus,
   usePortfolioPositions, useTradeMtm, useRiskProfiles, useMacroRegime, useAddPosition,
-  useConfig,
+  useConfig, useAiTradeProposals, useConfirmAiTradeProposal, useRejectAiTradeProposal,
 } from '../hooks/useApi'
 import {
   Target, Brain, Plus, RefreshCw, ChevronDown, ChevronUp, CheckCircle2,
-  LayoutGrid, List, Terminal,
+  LayoutGrid, List, Terminal, Bot, Check, X as XIcon,
 } from 'lucide-react'
 import clsx from 'clsx'
 import { format } from 'date-fns'
@@ -683,6 +683,72 @@ export function TradeRow({ item, onAdd, macroInfo, addedInfo, profiles, rank }:
   )
 }
 
+// ── AI-proposed trades — awaiting explicit user confirmation ──────────────────
+// Created by the chat widget's propose_trade tool call. Deliberately kept
+// separate from TradeCard/TradeItem (those are derived from scored patterns —
+// grafting an AI-sourced item onto that shape would be fragile).
+function AiProposedTradesSection() {
+  const { data: proposals } = useAiTradeProposals('pending')
+  const { mutate: confirmProposal, isPending: confirming } = useConfirmAiTradeProposal()
+  const { mutate: rejectProposal, isPending: rejecting } = useRejectAiTradeProposal()
+  const [pendingId, setPendingId] = useState<string | null>(null)
+  const [error, setError] = useState<string | null>(null)
+
+  if (!proposals || proposals.length === 0) return null
+
+  const handleConfirm = (id: string) => {
+    setPendingId(id); setError(null)
+    confirmProposal(id, {
+      onError: (e: any) => setError(e?.response?.data?.detail ?? 'Erreur lors de la confirmation.'),
+      onSettled: () => setPendingId(null),
+    })
+  }
+  const handleReject = (id: string) => {
+    setPendingId(id)
+    rejectProposal(id, { onSettled: () => setPendingId(null) })
+  }
+
+  return (
+    <div className="card border-blue-500/30">
+      <h3 className="section-title flex items-center gap-1.5 mb-3">
+        <Bot className="w-3.5 h-3.5 text-blue-400" /> Idées proposées par l'IA
+        <span className="text-slate-600 font-normal">({proposals.length} en attente)</span>
+      </h3>
+      {error && <div className="text-xs text-red-400 mb-2">{error}</div>}
+      <div className="grid grid-cols-1 md:grid-cols-2 gap-3">
+        {proposals.map(p => (
+          <div key={p.id} className="rounded-lg border border-slate-700/40 bg-dark-900/60 p-3 space-y-2">
+            <div className="flex items-start justify-between gap-2">
+              <div>
+                <div className="text-sm font-semibold text-white">{p.title}</div>
+                <div className="text-[11px] text-slate-500">{p.underlying} · {p.strategy} · {p.capital_invested.toLocaleString('fr-FR')} €</div>
+              </div>
+              <span className="text-[10px] px-1.5 py-0.5 rounded bg-blue-900/40 text-blue-300 shrink-0">🤖 IA</span>
+            </div>
+            {p.rationale && <div className="text-[11px] text-slate-400 leading-snug">{p.rationale}</div>}
+            <div className="flex items-center gap-2 pt-1">
+              <button
+                onClick={() => handleConfirm(p.id)}
+                disabled={confirming && pendingId === p.id}
+                className="flex-1 flex items-center justify-center gap-1 text-xs px-2 py-1.5 rounded bg-emerald-600/20 text-emerald-400 hover:bg-emerald-600/30 disabled:opacity-40 transition-colors"
+              >
+                <Check className="w-3 h-3" /> Confirmer
+              </button>
+              <button
+                onClick={() => handleReject(p.id)}
+                disabled={rejecting && pendingId === p.id}
+                className="flex-1 flex items-center justify-center gap-1 text-xs px-2 py-1.5 rounded bg-slate-700/40 text-slate-400 hover:bg-slate-700/60 disabled:opacity-40 transition-colors"
+              >
+                <XIcon className="w-3 h-3" /> Rejeter
+              </button>
+            </div>
+          </div>
+        ))}
+      </div>
+    </div>
+  )
+}
+
 // ── Self-contained Trade Ideas Tab ────────────────────────────────────────────
 export function TradeIdeasTab() {
   const { data: allPatternsData } = useAllPatterns()
@@ -862,6 +928,8 @@ export function TradeIdeasTab() {
 
   return (
     <div className="space-y-4">
+      <AiProposedTradesSection />
+
       {/* Toolbar */}
       <div className="flex items-center justify-between gap-3 flex-wrap">
         <div className="flex items-center gap-2 flex-wrap">

frontend/src/hooks/useApi.ts

@@ -1429,7 +1429,7 @@ export function useScoreText() {
 
 // ── AI Chat widget — free-form, read-only, context-aware conversation ────────
 
-export interface ChatMessage { role: 'user' | 'assistant'; content: string; created_at?: string }
+export interface ChatMessage { role: 'user' | 'assistant'; content: string; created_at?: string; trade_proposal?: TradeProposalRef | null }
 
 export const useChatContextBlocks = () =>
   useQuery({
@@ -1446,13 +1446,61 @@ export const useChatHistory = (sessionId: string) =>
     staleTime: Infinity,
   })
 
+export interface TradeProposalRef { id: string; title?: string; underlying?: string; strategy?: string }
+
 export const useSendChatMessage = () =>
   useMutation({
     mutationFn: (body: { session_id: string; message: string; enabled_blocks?: string[]; refresh_context?: boolean }) =>
-      api.post('/ai-chat/', body).then(r => r.data as { reply: string; blocks_included: string[] }),
+      api.post('/ai-chat/', body).then(r => r.data as { reply: string; blocks_included: string[]; trade_proposal: TradeProposalRef | null }),
   })
 
 export const useClearChatSession = () =>
   useMutation({
     mutationFn: (sessionId: string) => api.post('/ai-chat/clear', { session_id: sessionId }).then(r => r.data),
   })
+
+// ── AI Chat widget — trade proposals (pending confirmation) ──────────────────
+
+export interface AiTradeProposal {
+  id: string
+  session_id: string
+  created_at: string
+  status: 'pending' | 'confirmed' | 'rejected'
+  title: string
+  underlying: string
+  strategy: string
+  asset_class: string
+  expiry_days: number
+  capital_invested: number
+  legs: Array<{ strike: number; option_type: string; quantity: number; position: string }>
+  geo_trigger: string
+  rationale: string
+  portfolio_id?: string | null
+}
+
+export const useAiTradeProposals = (status: string = 'pending') =>
+  useQuery({
+    queryKey: ['ai-trade-proposals', status],
+    queryFn: () => api.get('/ai-chat/trade-proposals', { params: { status } }).then(r => r.data.proposals as AiTradeProposal[]),
+    refetchInterval: 30000,
+  })
+
+export const useConfirmAiTradeProposal = () => {
+  const qc = useQueryClient()
+  return useMutation({
+    mutationFn: (proposalId: string) => api.post(`/ai-chat/trade-proposals/${proposalId}/confirm`).then(r => r.data),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: ['ai-trade-proposals'] })
+      qc.invalidateQueries({ queryKey: ['portfolio'] })
+      qc.invalidateQueries({ queryKey: ['portfolio-summary'] })
+    },
+  })
+}
+
+export const useRejectAiTradeProposal = () => {
+  const qc = useQueryClient()
+  return useMutation({
+    mutationFn: (proposalId: string) => api.post(`/ai-chat/trade-proposals/${proposalId}/reject`).then(r => r.data),
+    onSuccess: () => qc.invalidateQueries({ queryKey: ['ai-trade-proposals'] }),
+  })
+}

frontend/src/pages/AIDesks.tsx

@@ -5,9 +5,9 @@ import clsx from 'clsx'
 // ── Types ─────────────────────────────────────────────────────────────────────
 
 interface SignalParam {
-  type: 'int' | 'float' | 'pairs'
+  type: 'int' | 'float' | 'pairs' | 'select'
   label: string
-  default: number | number[][]
+  default: number | number[][] | string
   min?: number
   max?: number
   options?: string[]
@@ -263,6 +263,20 @@ function SignalToggle({
                 </div>
               )
             }
+            if (p.type === 'select') {
+              return (
+                <div key={key} className="flex items-center gap-3">
+                  <label className="text-xs text-slate-400 w-28 shrink-0">{p.label}</label>
+                  <select
+                    value={value[key] ?? p.default}
+                    onChange={e => update(key, e.target.value)}
+                    className="w-32 bg-dark-900 border border-slate-700/40 rounded px-2 py-1 text-xs text-white"
+                  >
+                    {(p.options ?? []).map(o => <option key={o} value={o}>{o}</option>)}
+                  </select>
+                </div>
+              )
+            }
             return (
               <div key={key} className="flex items-center gap-3">
                 <label className="text-xs text-slate-400 w-28 shrink-0">{p.label}</label>