diff --git a/api/alembic/versions/f7b8c9d0e1f2_add_strategy_threshold_override_table.py b/api/alembic/versions/f7b8c9d0e1f2_add_strategy_threshold_override_table.py
new file mode 100644
index 000000000..bd692d873
--- /dev/null
+++ b/api/alembic/versions/f7b8c9d0e1f2_add_strategy_threshold_override_table.py
@@ -0,0 +1,78 @@
+"""Add strategy_threshold_override table
+
+Revision ID: f7b8c9d0e1f2
+Revises: e4a3a439c266
+Create Date: 2026-04-25 00:00:00.000000
+
+"""
+
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = "f7b8c9d0e1f2"
+down_revision: Union[str, Sequence[str], None] = "e4a3a439c266"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    op.create_table(
+        "strategy_threshold_override",
+        sa.Column("id", sa.Uuid(), nullable=False),
+        sa.Column("strategy_name", sa.String(), nullable=False),
+        sa.Column("symbol", sa.String(), nullable=False),
+        sa.Column("buy_trigger_pct", sa.Float(), nullable=False),
+        sa.Column("sell_trigger_pct", sa.Float(), nullable=False),
+        sa.Column("profile", sa.String(), nullable=False),
+        sa.Column("source_provider", sa.String(), nullable=False),
+        sa.Column("market_context_timestamp", sa.Float(), nullable=False),
+        sa.Column("expires_at", sa.Float(), nullable=False),
+        sa.Column("confidence", sa.Float(), nullable=False),
+        sa.Column("reason", sa.String(), nullable=False),
+        sa.Column("raw_model_response", sa.JSON(), nullable=False),
+        sa.Column("created_at", sa.Float(), nullable=False),
+        sa.PrimaryKeyConstraint("id"),
+    )
+    op.create_index(
+        "ix_strategy_threshold_override_id",
+        "strategy_threshold_override",
+        ["id"],
+        unique=True,
+    )
+    op.create_index(
+        "ix_strategy_threshold_override_strategy_name",
+        "strategy_threshold_override",
+        ["strategy_name"],
+        unique=False,
+    )
+    op.create_index(
+        "ix_strategy_threshold_override_symbol",
+        "strategy_threshold_override",
+        ["symbol"],
+        unique=False,
+    )
+    op.create_index(
+        "ix_strategy_threshold_override_source_provider",
+        "strategy_threshold_override",
+        ["source_provider"],
+        unique=False,
+    )
+    op.create_index(
+        "ix_strategy_threshold_override_expires_at",
+        "strategy_threshold_override",
+        ["expires_at"],
+        unique=False,
+    )
+
+
+def downgrade() -> None:
+    op.drop_index("ix_strategy_threshold_override_expires_at", table_name="strategy_threshold_override")
+    op.drop_index("ix_strategy_threshold_override_source_provider", table_name="strategy_threshold_override")
+    op.drop_index("ix_strategy_threshold_override_symbol", table_name="strategy_threshold_override")
+    op.drop_index("ix_strategy_threshold_override_strategy_name", table_name="strategy_threshold_override")
+    op.drop_index("ix_strategy_threshold_override_id", table_name="strategy_threshold_override")
+    op.drop_table("strategy_threshold_override")
diff --git a/api/databases/crud/strategy_threshold_override_crud.py b/api/databases/crud/strategy_threshold_override_crud.py
new file mode 100644
index 000000000..72f8554b5
--- /dev/null
+++ b/api/databases/crud/strategy_threshold_override_crud.py
@@ -0,0 +1,54 @@
+from sqlmodel import Session, select, desc
+from databases.tables.strategy_threshold_override_table import (
+    StrategyThresholdOverrideTable,
+)
+
+
+class StrategyThresholdOverrideCrud:
+    def __init__(self, session: Session):
+        self.session = session
+
+    def create(
+        self,
+        row: StrategyThresholdOverrideTable,
+    ) -> StrategyThresholdOverrideTable:
+        self.session.add(row)
+        self.session.commit()
+        self.session.refresh(row)
+        return row
+
+    def get_active(
+        self,
+        strategy_name: str,
+        symbol: str,
+        now_ts: float,
+    ) -> StrategyThresholdOverrideTable | None:
+        statement = (
+            select(StrategyThresholdOverrideTable)
+            .where(
+                StrategyThresholdOverrideTable.strategy_name == strategy_name,
+                StrategyThresholdOverrideTable.symbol == symbol,
+                StrategyThresholdOverrideTable.expires_at > now_ts,
+            )
+            .order_by(desc(StrategyThresholdOverrideTable.created_at))
+        )
+        return self.session.exec(statement).first()
+
+    def list_for_symbol(
+        self,
+        strategy_name: str,
+        symbol: str,
+        limit: int = 20,
+        offset: int = 0,
+    ) -> list[StrategyThresholdOverrideTable]:
+        statement = (
+            select(StrategyThresholdOverrideTable)
+            .where(
+                StrategyThresholdOverrideTable.strategy_name == strategy_name,
+                StrategyThresholdOverrideTable.symbol == symbol,
+            )
+            .order_by(desc(StrategyThresholdOverrideTable.created_at))
+            .limit(limit)
+            .offset(offset)
+        )
+        return list(self.session.exec(statement).all())
diff --git a/api/databases/tables/__init__.py b/api/databases/tables/__init__.py
index 5c3e52159..705791752 100644
--- a/api/databases/tables/__init__.py
+++ b/api/databases/tables/__init__.py
@@ -8,3 +8,4 @@
 from .symbol_table import *  # noqa
 from .asset_index_table import *  # noqa
 from .symbol_exchange_table import *  # noqa
+from .strategy_threshold_override_table import *  # noqa
diff --git a/api/databases/tables/strategy_threshold_override_table.py b/api/databases/tables/strategy_threshold_override_table.py
new file mode 100644
index 000000000..bfa7cd5c3
--- /dev/null
+++ b/api/databases/tables/strategy_threshold_override_table.py
@@ -0,0 +1,29 @@
+from uuid import UUID, uuid4
+from typing import Optional
+from sqlalchemy import Column, JSON
+from sqlmodel import SQLModel, Field
+from pybinbot import timestamp
+
+
+class StrategyThresholdOverrideTable(SQLModel, table=True):
+    __tablename__ = "strategy_threshold_override"
+
+    id: Optional[UUID] = Field(
+        default_factory=uuid4,
+        primary_key=True,
+        nullable=False,
+        unique=True,
+        index=True,
+    )
+    strategy_name: str = Field(index=True)
+    symbol: str = Field(index=True)
+    buy_trigger_pct: float = Field(ge=0)
+    sell_trigger_pct: float = Field(ge=0)
+    profile: str = Field(default="")
+    source_provider: str = Field(default="manual", index=True)
+    market_context_timestamp: float = Field(default_factory=timestamp)
+    expires_at: float = Field(index=True)
+    confidence: float = Field(default=0, ge=0, le=1)
+    reason: str = Field(default="")
+    raw_model_response: dict = Field(default_factory=dict, sa_column=Column(JSON))
+    created_at: float = Field(default_factory=timestamp)
diff --git a/api/main.py b/api/main.py
index 34bd34d31..9c312cc5b 100644
--- a/api/main.py
+++ b/api/main.py
@@ -18,6 +18,7 @@
 from asset_index.routes import asset_index_blueprint
 from inquiries.routes import inquiries_router
 from portfolio.routes import portfolio_blueprint
+from strategy_thresholds.routes import strategy_threshold_blueprint
 from pybinbot import configure_logging
 from databases.tables import *  # noqa
 
@@ -67,6 +68,7 @@ async def root():
 app.include_router(asset_index_blueprint, prefix="/asset-index")
 app.include_router(inquiries_router)
 app.include_router(portfolio_blueprint)
+app.include_router(strategy_threshold_blueprint)
 
 
 @app.exception_handler(RequestValidationError)
diff --git a/api/openai_api/threshold_advisor.py b/api/openai_api/threshold_advisor.py
new file mode 100644
index 000000000..4c80d6cde
--- /dev/null
+++ b/api/openai_api/threshold_advisor.py
@@ -0,0 +1,61 @@
+import json
+from openai import OpenAI
+
+from tools.config import Config
+from strategy_thresholds.models import MarketContextPayload, ThresholdRecommendation
+
+
+class OpenAiThresholdError(Exception):
+    pass
+
+
+class OpenAiThresholdAdvisor:
+    def __init__(self, model: str | None = None):
+        self.config = Config()
+        self.model = model or self.config.grid_threshold_llm_model
+        self.client = OpenAI(api_key=self.config.openai_api_key)
+        if not self.client.api_key:
+            raise OpenAiThresholdError("OPENAI_API_KEY is not configured")
+
+    def _build_prompt(
+        self,
+        strategy: str,
+        symbol: str,
+        context: MarketContextPayload,
+    ) -> str:
+        return (
+            "Return ONLY valid JSON for a threshold recommendation. "
+            "Use keys: strategy, symbol, profile, buy_trigger_pct, sell_trigger_pct, ttl_minutes, confidence, reason. "
+            "Apply conservative thresholds for range markets and reject unstable trend states.\n"
+            f"Strategy: {strategy}\n"
+            f"Symbol: {symbol}\n"
+            f"Market context: {context.model_dump_json()}"
+        )
+
+    def suggest(
+        self,
+        strategy: str,
+        symbol: str,
+        context: MarketContextPayload,
+    ) -> tuple[ThresholdRecommendation, dict]:
+        prompt = self._build_prompt(strategy=strategy, symbol=symbol, context=context)
+        response = self.client.responses.create(
+            model=self.model,
+            input=prompt,
+            text={"format": {"type": "json_object"}},
+        )
+
+        output_text = response.output_text
+        if not output_text:
+            raise OpenAiThresholdError("OpenAI response did not include output_text")
+
+        try:
+            payload = json.loads(output_text)
+        except json.JSONDecodeError as exc:
+            raise OpenAiThresholdError("OpenAI response was not valid JSON") from exc
+
+        payload.setdefault("strategy", strategy)
+        payload.setdefault("symbol", symbol)
+
+        recommendation = ThresholdRecommendation.model_validate(payload)
+        return recommendation, response.model_dump()
diff --git a/api/pyproject.toml b/api/pyproject.toml
index b95a918e6..4f0534a74 100644
--- a/api/pyproject.toml
+++ b/api/pyproject.toml
@@ -22,7 +22,8 @@ dependencies = [
     "pydantic-settings>=2.10.1",
     "confluent-kafka>=2.11.1",
     "aiokafka>=0.12.0",
-    "pybinbot>=1.3.2",
+    "pybinbot>=1.3.6",
+    "openai>=2.6.1",
 ]
 
 [project.urls]
diff --git a/api/strategy_thresholds/models.py b/api/strategy_thresholds/models.py
new file mode 100644
index 000000000..fbb6ad3c3
--- /dev/null
+++ b/api/strategy_thresholds/models.py
@@ -0,0 +1,121 @@
+from pydantic import BaseModel, Field, model_validator
+from typing import Any
+from tools.handle_error import IResponseBase
+
+
+MIN_TRIGGER = 0.008
+MAX_TRIGGER = 0.05
+MAX_STEP_DELTA = 0.005
+MIN_TTL_MINUTES = 30
+MAX_TTL_MINUTES = 240
+
+
+class ThresholdRecommendation(BaseModel):
+    strategy: str
+    symbol: str
+    buy_trigger_pct: float = Field(ge=MIN_TRIGGER, le=MAX_TRIGGER)
+    sell_trigger_pct: float = Field(ge=MIN_TRIGGER, le=MAX_TRIGGER)
+    ttl_minutes: int = Field(ge=MIN_TTL_MINUTES, le=MAX_TTL_MINUTES)
+    confidence: float = Field(ge=0, le=1)
+    reason: str = Field(min_length=3)
+    profile: str = Field(default="")
+
+
+class MarketContextPayload(BaseModel):
+    market_regime: str
+    coin_regime: str
+    market_stress_score: float = Field(ge=0)
+    atr_pct: float | None = None
+    bb_width: float | None = None
+    extras: dict[str, Any] = Field(default_factory=dict)
+
+
+class SuggestThresholdRequest(BaseModel):
+    strategy: str
+    symbol: str
+    market_context: MarketContextPayload
+    model: str | None = None
+    apply: bool = True
+
+
+class ApplyThresholdRequest(BaseModel):
+    recommendation: ThresholdRecommendation
+    source_provider: str = "manual"
+    market_context_timestamp: float
+    raw_model_response: dict[str, Any] = Field(default_factory=dict)
+
+
+class ThresholdOverrideModel(BaseModel):
+    id: str
+    strategy_name: str
+    symbol: str
+    buy_trigger_pct: float
+    sell_trigger_pct: float
+    profile: str
+    source_provider: str
+    market_context_timestamp: float
+    expires_at: float
+    confidence: float
+    reason: str
+    raw_model_response: dict[str, Any]
+    created_at: float
+
+
+class ThresholdOverrideResponse(IResponseBase):
+    data: ThresholdOverrideModel | None = None
+
+
+class ThresholdOverrideListResponse(IResponseBase):
+    data: list[ThresholdOverrideModel] = Field(default_factory=list)
+
+
+class SuggestThresholdResponse(IResponseBase):
+    data: ThresholdRecommendation | None = None
+
+
+class GuardrailInput(BaseModel):
+    recommendation: ThresholdRecommendation
+    current_buy_trigger_pct: float | None = None
+    current_sell_trigger_pct: float | None = None
+    market_stress_score: float
+    market_regime: str
+    coin_regime: str
+
+    @model_validator(mode="after")
+    def validate_step_delta(self):
+        if self.current_buy_trigger_pct is not None:
+            if (
+                abs(
+                    self.recommendation.buy_trigger_pct
+                    - self.current_buy_trigger_pct
+                )
+                > MAX_STEP_DELTA
+            ):
+                raise ValueError("buy_trigger_pct exceeds max step delta")
+
+        if self.current_sell_trigger_pct is not None:
+            if (
+                abs(
+                    self.recommendation.sell_trigger_pct
+                    - self.current_sell_trigger_pct
+                )
+                > MAX_STEP_DELTA
+            ):
+                raise ValueError("sell_trigger_pct exceeds max step delta")
+
+        if self.market_stress_score >= 0.35:
+            raise ValueError("market stress too high")
+
+        blocked_coin_regimes = {
+            "VOLATILE",
+            "TREND_UP",
+            "TREND_DOWN",
+            "BREAKOUT_UP",
+            "BREAKDOWN",
+        }
+        if self.market_regime.upper() not in {"RANGE", "TRANSITIONAL"}:
+            raise ValueError("market regime does not support threshold updates")
+        if self.coin_regime.upper() in blocked_coin_regimes:
+            raise ValueError("coin regime does not support threshold updates")
+
+        return self
diff --git a/api/strategy_thresholds/routes.py b/api/strategy_thresholds/routes.py
new file mode 100644
index 000000000..bae4b8739
--- /dev/null
+++ b/api/strategy_thresholds/routes.py
@@ -0,0 +1,169 @@
+from fastapi import APIRouter, Depends
+from sqlmodel import Session
+from pybinbot import timestamp
+from user.services.auth import get_current_user
+
+from databases.utils import get_session
+from databases.crud.strategy_threshold_override_crud import (
+    StrategyThresholdOverrideCrud,
+)
+from databases.tables.strategy_threshold_override_table import (
+    StrategyThresholdOverrideTable,
+)
+from strategy_thresholds.models import (
+    ApplyThresholdRequest,
+    GuardrailInput,
+    SuggestThresholdRequest,
+    SuggestThresholdResponse,
+    ThresholdOverrideListResponse,
+    ThresholdOverrideModel,
+    ThresholdOverrideResponse,
+    ThresholdRecommendation,
+)
+from openai_api.threshold_advisor import OpenAiThresholdAdvisor, OpenAiThresholdError
+
+
+strategy_threshold_blueprint = APIRouter(prefix="/strategy-threshold-overrides")
+
+
+def _to_model(row: StrategyThresholdOverrideTable) -> ThresholdOverrideModel:
+    return ThresholdOverrideModel(
+        id=str(row.id),
+        strategy_name=row.strategy_name,
+        symbol=row.symbol,
+        buy_trigger_pct=row.buy_trigger_pct,
+        sell_trigger_pct=row.sell_trigger_pct,
+        profile=row.profile,
+        source_provider=row.source_provider,
+        market_context_timestamp=row.market_context_timestamp,
+        expires_at=row.expires_at,
+        confidence=row.confidence,
+        reason=row.reason,
+        raw_model_response=row.raw_model_response,
+        created_at=row.created_at,
+    )
+
+
+@strategy_threshold_blueprint.get("", response_model=ThresholdOverrideListResponse, tags=["strategy threshold overrides"])
+def list_overrides(
+    strategy_name: str,
+    symbol: str,
+    limit: int = 20,
+    offset: int = 0,
+    session: Session = Depends(get_session),
+    _: dict = Depends(get_current_user),
+):
+    rows = StrategyThresholdOverrideCrud(session).list_for_symbol(
+        strategy_name=strategy_name,
+        symbol=symbol,
+        limit=limit,
+        offset=offset,
+    )
+    return ThresholdOverrideListResponse(
+        message="Successfully found threshold overrides.",
+        data=[_to_model(r) for r in rows],
+    )
+
+
+@strategy_threshold_blueprint.get("/active", response_model=ThresholdOverrideResponse, tags=["strategy threshold overrides"])
+def get_active_override(
+    strategy_name: str,
+    symbol: str,
+    session: Session = Depends(get_session),
+    _: dict = Depends(get_current_user),
+):
+    row = StrategyThresholdOverrideCrud(session).get_active(
+        strategy_name=strategy_name,
+        symbol=symbol,
+        now_ts=timestamp(),
+    )
+    return ThresholdOverrideResponse(
+        message="Successfully found active override.",
+        data=_to_model(row) if row else None,
+    )
+
+
+@strategy_threshold_blueprint.post("/apply", response_model=ThresholdOverrideResponse, tags=["strategy threshold overrides"])
+def apply_override(
+    payload: ApplyThresholdRequest,
+    session: Session = Depends(get_session),
+    _: dict = Depends(get_current_user),
+):
+    expires_at = payload.market_context_timestamp + payload.recommendation.ttl_minutes * 60
+    row = StrategyThresholdOverrideTable(
+        strategy_name=payload.recommendation.strategy,
+        symbol=payload.recommendation.symbol,
+        buy_trigger_pct=payload.recommendation.buy_trigger_pct,
+        sell_trigger_pct=payload.recommendation.sell_trigger_pct,
+        profile=payload.recommendation.profile,
+        source_provider=payload.source_provider,
+        market_context_timestamp=payload.market_context_timestamp,
+        expires_at=expires_at,
+        confidence=payload.recommendation.confidence,
+        reason=payload.recommendation.reason,
+        raw_model_response=payload.raw_model_response,
+    )
+    created = StrategyThresholdOverrideCrud(session).create(row)
+    return ThresholdOverrideResponse(
+        message="Successfully applied threshold override.",
+        data=_to_model(created),
+    )
+
+
+@strategy_threshold_blueprint.post("/suggest", response_model=SuggestThresholdResponse, tags=["strategy threshold overrides"])
+def suggest_override(
+    payload: SuggestThresholdRequest,
+    session: Session = Depends(get_session),
+    _: dict = Depends(get_current_user),
+):
+    client = OpenAiThresholdAdvisor(model=payload.model)
+
+    try:
+        recommendation, raw_model_response = client.suggest(
+            strategy=payload.strategy,
+            symbol=payload.symbol,
+            context=payload.market_context,
+        )
+        recommendation = ThresholdRecommendation.model_validate(recommendation)
+
+        current = StrategyThresholdOverrideCrud(session).get_active(
+            strategy_name=payload.strategy,
+            symbol=payload.symbol,
+            now_ts=timestamp(),
+        )
+
+        GuardrailInput(
+            recommendation=recommendation,
+            current_buy_trigger_pct=current.buy_trigger_pct if current else None,
+            current_sell_trigger_pct=current.sell_trigger_pct if current else None,
+            market_stress_score=payload.market_context.market_stress_score,
+            market_regime=payload.market_context.market_regime,
+            coin_regime=payload.market_context.coin_regime,
+        )
+
+        if payload.apply:
+            row = StrategyThresholdOverrideTable(
+                strategy_name=recommendation.strategy,
+                symbol=recommendation.symbol,
+                buy_trigger_pct=recommendation.buy_trigger_pct,
+                sell_trigger_pct=recommendation.sell_trigger_pct,
+                profile=recommendation.profile,
+                source_provider="openai",
+                market_context_timestamp=timestamp(),
+                expires_at=timestamp() + recommendation.ttl_minutes * 60,
+                confidence=recommendation.confidence,
+                reason=recommendation.reason,
+                raw_model_response=raw_model_response,
+            )
+            StrategyThresholdOverrideCrud(session).create(row)
+
+        return SuggestThresholdResponse(
+            message="Successfully generated threshold recommendation.",
+            data=recommendation,
+        )
+    except (OpenAiThresholdError, ValueError) as error:
+        return SuggestThresholdResponse(
+            message=f"Rejected threshold recommendation: {error}",
+            error=1,
+            data=None,
+        )
diff --git a/api/tests/test_strategy_threshold_overrides.py b/api/tests/test_strategy_threshold_overrides.py
new file mode 100644
index 000000000..c35587e4e
--- /dev/null
+++ b/api/tests/test_strategy_threshold_overrides.py
@@ -0,0 +1,119 @@
+from unittest.mock import patch
+
+
+def test_apply_and_get_active_threshold_override(client):
+    apply_payload = {
+        "recommendation": {
+            "strategy": "coinrule_grid_trading",
+            "symbol": "XBTUSDTM",
+            "buy_trigger_pct": 0.016,
+            "sell_trigger_pct": 0.02,
+            "ttl_minutes": 60,
+            "confidence": 0.72,
+            "reason": "Range regime with compressed volatility.",
+            "profile": "tight_range",
+        },
+        "source_provider": "manual",
+        "market_context_timestamp": 1700000000,
+        "raw_model_response": {"type": "manual"},
+    }
+
+    apply_response = client.post(
+        "/strategy-threshold-overrides/apply", json=apply_payload
+    )
+    assert apply_response.status_code == 200
+    assert apply_response.json()["error"] == 0
+
+    active_response = client.get(
+        "/strategy-threshold-overrides/active",
+        params={"strategy_name": "coinrule_grid_trading", "symbol": "XBTUSDTM"},
+    )
+    assert active_response.status_code == 200
+    assert active_response.json()["error"] == 0
+    assert active_response.json()["data"]["buy_trigger_pct"] == 0.016
+
+
+def test_suggest_override_applies_when_guardrails_pass(client):
+    suggestion_payload = {
+        "strategy": "coinrule_grid_trading",
+        "symbol": "XBTUSDTM",
+        "market_context": {
+            "market_regime": "RANGE",
+            "coin_regime": "RANGE",
+            "market_stress_score": 0.2,
+            "atr_pct": 0.01,
+            "bb_width": 0.02,
+        },
+        "model": "gpt-4.1-mini",
+        "apply": True,
+    }
+
+    with patch(
+        "strategy_thresholds.routes.OpenAiThresholdAdvisor.suggest",
+        return_value=(
+            {
+                "strategy": "coinrule_grid_trading",
+                "symbol": "XBTUSDTM",
+                "buy_trigger_pct": 0.018,
+                "sell_trigger_pct": 0.021,
+                "ttl_minutes": 60,
+                "confidence": 0.8,
+                "reason": "RANGE market and stable volatility.",
+                "profile": "balanced_range",
+            },
+            {"provider": "openai"},
+        ),
+    ):
+        response = client.post(
+            "/strategy-threshold-overrides/suggest", json=suggestion_payload
+        )
+
+    assert response.status_code == 200
+    body = response.json()
+    assert body["error"] == 0
+    assert body["data"]["profile"] == "balanced_range"
+
+    list_response = client.get(
+        "/strategy-threshold-overrides",
+        params={"strategy_name": "coinrule_grid_trading", "symbol": "XBTUSDTM"},
+    )
+    assert list_response.status_code == 200
+    assert len(list_response.json()["data"]) >= 1
+
+
+def test_suggest_override_rejects_high_stress(client):
+    suggestion_payload = {
+        "strategy": "coinrule_grid_trading",
+        "symbol": "XBTUSDTM",
+        "market_context": {
+            "market_regime": "RANGE",
+            "coin_regime": "RANGE",
+            "market_stress_score": 0.45,
+        },
+        "apply": False,
+    }
+
+    with patch(
+        "strategy_thresholds.routes.OpenAiThresholdAdvisor.suggest",
+        return_value=(
+            {
+                "strategy": "coinrule_grid_trading",
+                "symbol": "XBTUSDTM",
+                "buy_trigger_pct": 0.018,
+                "sell_trigger_pct": 0.021,
+                "ttl_minutes": 60,
+                "confidence": 0.8,
+                "reason": "RANGE market and stable volatility.",
+                "profile": "balanced_range",
+            },
+            {"provider": "openai"},
+        ),
+    ):
+        response = client.post(
+            "/strategy-threshold-overrides/suggest", json=suggestion_payload
+        )
+
+    assert response.status_code == 200
+    body = response.json()
+    assert body["error"] == 1
+    assert "market stress too high" in body["message"]
diff --git a/api/tools/config.py b/api/tools/config.py
index 41195c0ac..ca6177a6d 100644
--- a/api/tools/config.py
+++ b/api/tools/config.py
@@ -213,6 +213,15 @@ def kucoin_secret(self) -> str:
     def kucoin_passphrase(self) -> str:
         return self._get_required("KUCOIN_PASSPHRASE")
 
+
+    @property
+    def grid_threshold_llm_model(self) -> str:
+        return self._get_optional("GRID_THRESHOLD_LLM_MODEL", "gpt-4.1-mini")
+
+    @property
+    def openai_api_key(self) -> str:
+        return self._get_optional("OPENAI_API_KEY")
+
     @property
     def service_password(self) -> str:
         return self._get_optional("SERVICE_PASSWORD")
diff --git a/api/uv.lock b/api/uv.lock
index b8ada372e..314d00fe3 100644
--- a/api/uv.lock
+++ b/api/uv.lock
@@ -347,7 +347,7 @@ requires-dist = [
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     { name = "py3cw", specifier = ">=0.0.39" },
     { name = "py4j", specifier = ">=0.10.9" },
-    { name = "pybinbot", specifier = ">=1.3.2" },
+    { name = "pybinbot", specifier = ">=1.3.6" },
     { name = "pydantic-settings", specifier = ">=2.10.1" },
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=9.0.2" },
     { name = "pytest-asyncio", marker = "extra == 'dev'", specifier = ">=1.2.0" },
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