Add multi-factor conviction gate to activation

Make "qualified" mean an edge candidate, not just R:R + confidence.
The gate now also requires (all admin-configurable, defaults on):
- high conviction: recommended_action LONG_HIGH / SHORT_HIGH only
- clean read: risk_level Low (no contradicting signals)
- probable primary target: best target probability >= min (default 60)

- Shared predicate: app/services/qualification.py +
  frontend/src/lib/qualification.ts (mirrored)
- Activation config extended (min_target_probability,
  require_high_conviction, exclude_conflicts) with bool-aware
  get/update + validation
- /trades/performance switched to ?qualified_only=true, applying
  the full gate server-side; confidence breakdown stays unfiltered
- Dashboard "Qualified", Signals "Qualified only" toggle, and
  Track Record all use the one gate; Admin gains the new controls

Sentiment provider runtime config (prior change) included.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

app/routers/admin.py

@@ -14,6 +14,8 @@ from app.schemas.admin import (
     DataCleanupRequest,
     JobToggle,
     RecommendationConfigUpdate,
+    SentimentConfigUpdate,
+    SentimentTestRequest,
     PasswordReset,
     RegistrationToggle,
     SystemSettingUpdate,
@@ -22,6 +24,7 @@ from app.schemas.admin import (
 )
 from app.schemas.common import APIEnvelope
 from app.services import admin_service
+from app.services import sentiment_provider_service
 from app.services import ticker_universe_service
 
 router = APIRouter(tags=["admin"])
@@ -171,6 +174,41 @@ async def update_activation_settings(
     return APIEnvelope(status="success", data=updated)
 
 
+@router.get("/admin/settings/sentiment", response_model=APIEnvelope)
+async def get_sentiment_settings(
+    _admin: User = Depends(require_admin),
+    db: AsyncSession = Depends(get_db),
+):
+    config = await sentiment_provider_service.get_sentiment_config(db)
+    return APIEnvelope(status="success", data=config)
+
+
+@router.put("/admin/settings/sentiment", response_model=APIEnvelope)
+async def update_sentiment_settings(
+    body: SentimentConfigUpdate,
+    _admin: User = Depends(require_admin),
+    db: AsyncSession = Depends(get_db),
+):
+    config = await sentiment_provider_service.update_sentiment_config(
+        db,
+        provider=body.provider,
+        model=body.model,
+        api_key=body.api_key,
+    )
+    return APIEnvelope(status="success", data=config)
+
+
+@router.post("/admin/settings/sentiment/test", response_model=APIEnvelope)
+async def test_sentiment_settings(
+    body: SentimentTestRequest,
+    _admin: User = Depends(require_admin),
+    db: AsyncSession = Depends(get_db),
+):
+    """Live credentials check: fetch sentiment for one ticker with current config."""
+    result = await sentiment_provider_service.test_sentiment_provider(db, body.ticker)
+    return APIEnvelope(status="success", data=result)
+
+
 @router.get("/admin/settings/ticker-universe", response_model=APIEnvelope)
 async def get_ticker_universe_setting(
     _admin: User = Depends(require_admin),

app/routers/ingestion.py

@@ -23,8 +23,8 @@ from app.models.ticker import Ticker
 from app.models.user import User
 from app.providers.alpaca import AlpacaOHLCVProvider
 from app.providers.fundamentals_chain import build_fundamental_provider_chain
-from app.providers.openai_sentiment import OpenAISentimentProvider
 from app.services.rr_scanner_service import scan_ticker
+from app.services.sentiment_provider_service import build_sentiment_provider
 from app.schemas.common import APIEnvelope
 from app.services import (
     fundamental_service,
@@ -99,11 +99,14 @@ async def fetch_symbol(
         sources["ohlcv"] = {"status": "error", "records": 0, "message": str(exc)}
 
     # --- Sentiment ---
-    if settings.openai_api_key:
+    try:
+        sent_provider = await build_sentiment_provider(db)
+    except ProviderError as exc:
+        sent_provider = None
+        sources["sentiment"] = {"status": "skipped", "message": str(exc)}
+
+    if sent_provider is not None:
         try:
-            sent_provider = OpenAISentimentProvider(
-                settings.openai_api_key, settings.openai_model
-            )
             data = await sent_provider.fetch_sentiment(symbol_upper)
             await sentiment_service.store_sentiment(
                 db,
@@ -124,11 +127,6 @@ async def fetch_symbol(
         except Exception as exc:
             logger.error("Sentiment fetch failed for %s: %s", symbol_upper, exc)
             sources["sentiment"] = {"status": "error", "message": str(exc)}
-    else:
-        sources["sentiment"] = {
-            "status": "skipped",
-            "message": "OpenAI API key not configured",
-        }
 
     # --- Fundamentals ---
     if settings.fmp_api_key or settings.finnhub_api_key or settings.alpha_vantage_api_key:

app/routers/trades.py

@@ -67,9 +67,8 @@ async def get_activation_thresholds(
 
 @router.get("/trades/performance", response_model=APIEnvelope)
 async def get_trade_performance(
-    min_rr: float | None = Query(None, ge=0, description="Only setups with R:R >= this"),
-    min_confidence: float | None = Query(
-        None, ge=0, le=100, description="Only setups with confidence >= this"
+    qualified_only: bool = Query(
+        False, description="Restrict overall/direction/action stats to setups that clear the activation gate"
     ),
     _user=Depends(require_access),
     db: AsyncSession = Depends(get_db),
@@ -78,11 +77,12 @@ async def get_trade_performance(
 
     Outcomes are written by the nightly outcome_evaluator job (win = target
     hit first, loss = stop hit first, expired = neither within the window).
-    Optional min_rr / min_confidence filters apply to the overall, direction
-    and action breakdowns; the confidence breakdown always covers all setups
-    so thresholds can be validated against it.
+    With qualified_only, the overall/direction/action breakdowns cover only
+    setups clearing the activation gate; the confidence breakdown always
+    covers all setups so the gate can be validated against it.
     """
-    stats = await get_performance_stats(db, min_rr=min_rr, min_confidence=min_confidence)
+    config = await admin_service.get_activation_config(db) if qualified_only else None
+    stats = await get_performance_stats(db, config=config)
     return APIEnvelope(status="success", data=stats)
 
 

app/scheduler.py

@@ -29,13 +29,14 @@ from app.models.ohlcv import OHLCVRecord
 from app.models.settings import SystemSetting
 from app.models.sentiment import SentimentScore
 from app.models.ticker import Ticker
+from app.exceptions import ProviderError
 from app.providers.alpaca import AlpacaOHLCVProvider
 from app.providers.fundamentals_chain import build_fundamental_provider_chain
-from app.providers.openai_sentiment import OpenAISentimentProvider
 from app.providers.protocol import SentimentData
 from app.services import fundamental_service, ingestion_service, sentiment_service
 from app.services.outcome_service import evaluate_pending_setups
 from app.services.rr_scanner_service import scan_all_tickers
+from app.services.sentiment_provider_service import build_sentiment_provider
 from app.services.ticker_universe_service import bootstrap_universe
 
 logger = logging.getLogger(__name__)
@@ -407,13 +408,13 @@ async def collect_sentiment() -> None:
         total = len(symbols)
         _runtime_progress(job_name, processed=0, total=total)
 
-        if not settings.openai_api_key:
-            logger.warning(json.dumps({"event": "job_skipped", "job": job_name, "reason": "openai key not configured"}))
-            _runtime_finish(job_name, "skipped", processed=0, total=total, message="OpenAI key not configured")
-            return
-
         try:
-            provider = OpenAISentimentProvider(settings.openai_api_key, settings.openai_model)
+            async with async_session_factory() as cfg_db:
+                provider = await build_sentiment_provider(cfg_db)
+        except ProviderError as exc:
+            logger.warning(json.dumps({"event": "job_skipped", "job": job_name, "reason": str(exc)}))
+            _runtime_finish(job_name, "skipped", processed=0, total=total, message=str(exc))
+            return
         except Exception as exc:
             logger.error(json.dumps({"event": "job_error", "job": job_name, "error_type": type(exc).__name__, "message": str(exc)}))
             _runtime_finish(job_name, "error", processed=0, total=total, message=str(exc))

app/schemas/admin.py

@@ -59,6 +59,21 @@ class TickerUniverseUpdate(BaseModel):
 
 
 class ActivationConfigUpdate(BaseModel):
-    """Activation thresholds: what counts as an actionable signal."""
+    """Activation gate: what counts as an actionable signal."""
     min_rr: float | None = Field(default=None, ge=0)
     min_confidence: float | None = Field(default=None, ge=0, le=100)
+    min_target_probability: float | None = Field(default=None, ge=0, le=100)
+    require_high_conviction: bool | None = None
+    exclude_conflicts: bool | None = None
+
+
+class SentimentConfigUpdate(BaseModel):
+    """Runtime sentiment LLM config. api_key is write-only; omit/empty to keep
+    the stored key."""
+    provider: Literal["openai", "gemini"] | None = None
+    model: str | None = Field(default=None, max_length=100)
+    api_key: str | None = Field(default=None, max_length=400)
+
+
+class SentimentTestRequest(BaseModel):
+    ticker: str = Field(default="AAPL", max_length=10)

app/services/admin_service.py

@@ -31,14 +31,29 @@ RECOMMENDATION_CONFIG_DEFAULTS: dict[str, float] = {
 DEFAULT_TICKER_UNIVERSE = "sp500"
 SUPPORTED_TICKER_UNIVERSES = {"sp500", "nasdaq100", "nasdaq_all"}
 
-# Activation thresholds: what counts as a signal worth acting on.
-# Used as Signals-page default filters, the Dashboard's qualified-setup
-# metrics, and the Track Record's "qualified only" view. The outcome
-# evaluator deliberately ignores these — every setup gets evaluated so the
-# thresholds themselves can be validated against outcomes.
-ACTIVATION_DEFAULTS: dict[str, float] = {
-    "activation_min_rr": 2.0,
-    "activation_min_confidence": 70.0,
+# Activation gate: what counts as a signal worth acting on. Used by the
+# Dashboard's "Qualified" metric, the Signals "Qualified only" view, and the
+# Track Record's qualified stats. The outcome evaluator deliberately ignores
+# these — every setup is evaluated so the gate itself can be validated.
+#
+# Beyond raw R:R and confidence, the gate demands conviction: a high-conviction
+# action (LONG_HIGH / SHORT_HIGH), a clean read (risk Low / no conflicts), and a
+# probable primary target.
+_ACTIVATION_FLOAT_KEYS: dict[str, str] = {
+    "min_rr": "activation_min_rr",
+    "min_confidence": "activation_min_confidence",
+    "min_target_probability": "activation_min_target_probability",
+}
+_ACTIVATION_BOOL_KEYS: dict[str, str] = {
+    "require_high_conviction": "activation_require_high_conviction",
+    "exclude_conflicts": "activation_exclude_conflicts",
+}
+ACTIVATION_DEFAULTS: dict[str, float | bool] = {
+    "min_rr": 2.0,
+    "min_confidence": 70.0,
+    "min_target_probability": 60.0,
+    "require_high_conviction": True,
+    "exclude_conflicts": True,
 }
 
 
@@ -157,40 +172,43 @@ async def update_setting(db: AsyncSession, key: str, value: str) -> SystemSettin
 # Activation thresholds
 # ---------------------------------------------------------------------------
 
-async def get_activation_config(db: AsyncSession) -> dict[str, float]:
-    """Return activation thresholds with public keys (min_rr, min_confidence)."""
+async def get_activation_config(db: AsyncSession) -> dict[str, float | bool]:
+    """Return the activation gate config with public keys."""
     result = await db.execute(
         select(SystemSetting).where(SystemSetting.key.like("activation_%"))
     )
-    config = dict(ACTIVATION_DEFAULTS)
-    for setting in result.scalars().all():
-        if setting.key in config:
+    stored = {s.key: s.value for s in result.scalars().all()}
+
+    config: dict[str, float | bool] = dict(ACTIVATION_DEFAULTS)
+    for public_key, storage_key in _ACTIVATION_FLOAT_KEYS.items():
+        if storage_key in stored:
             try:
-                config[setting.key] = float(setting.value)
+                config[public_key] = float(stored[storage_key])
             except (TypeError, ValueError):
                 pass
-    return {
-        "min_rr": config["activation_min_rr"],
-        "min_confidence": config["activation_min_confidence"],
-    }
+    for public_key, storage_key in _ACTIVATION_BOOL_KEYS.items():
+        if storage_key in stored:
+            config[public_key] = str(stored[storage_key]).strip().lower() == "true"
+    return config
 
 
 async def update_activation_config(
-    db: AsyncSession, updates: dict[str, float]
-) -> dict[str, float]:
-    """Update activation thresholds. Accepts public keys min_rr / min_confidence."""
+    db: AsyncSession, updates: dict[str, float | bool]
+) -> dict[str, float | bool]:
+    """Update the activation gate. Accepts public keys; only supplied keys change."""
     if "min_rr" in updates and updates["min_rr"] < 0:
         raise ValidationError("min_rr must be >= 0")
     if "min_confidence" in updates and not 0 <= updates["min_confidence"] <= 100:
         raise ValidationError("min_confidence must be between 0 and 100")
+    if "min_target_probability" in updates and not 0 <= updates["min_target_probability"] <= 100:
+        raise ValidationError("min_target_probability must be between 0 and 100")
 
-    key_map = {
-        "min_rr": "activation_min_rr",
-        "min_confidence": "activation_min_confidence",
-    }
-    for public_key, storage_key in key_map.items():
-        if public_key in updates:
+    for public_key, storage_key in _ACTIVATION_FLOAT_KEYS.items():
+        if public_key in updates and updates[public_key] is not None:
             await update_setting(db, storage_key, str(float(updates[public_key])))
+    for public_key, storage_key in _ACTIVATION_BOOL_KEYS.items():
+        if public_key in updates and updates[public_key] is not None:
+            await update_setting(db, storage_key, "true" if updates[public_key] else "false")
 
     return await get_activation_config(db)
 

app/services/outcome_service.py

@@ -23,6 +23,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.models.ohlcv import OHLCVRecord
 from app.models.trade_setup import TradeSetup
+from app.services.qualification import setup_qualifies
 
 logger = logging.getLogger(__name__)
 
@@ -180,8 +181,7 @@ def _confidence_bucket(score: float | None) -> str | None:
 
 async def get_performance_stats(
     db: AsyncSession,
-    min_rr: float | None = None,
-    min_confidence: float | None = None,
+    config: dict | None = None,
 ) -> dict:
     """Aggregate outcome statistics over all evaluated trade setups.
 
@@ -189,9 +189,10 @@ async def get_performance_stats(
     loss = -1R, expired = 0R). A positive avg_r means the signals have
     been profitable on a risk-adjusted basis.
 
-    min_rr / min_confidence filter the overall, direction and action
-    breakdowns. The confidence breakdown deliberately stays unfiltered:
-    it is the instrument for validating the thresholds themselves.
+    When ``config`` (an activation-gate dict) is supplied, the overall,
+    direction and action breakdowns cover only qualified setups. The
+    confidence breakdown deliberately stays unfiltered: it is the
+    instrument for validating the gate itself.
     """
     result = await db.execute(
         select(TradeSetup).where(TradeSetup.actual_outcome.is_not(None))
@@ -203,14 +204,10 @@ async def get_performance_stats(
     )
     pending_count = len(pending_result.scalars().all())
 
-    def qualifies(setup: TradeSetup) -> bool:
-        if min_rr is not None and setup.rr_ratio < min_rr:
-            return False
-        if min_confidence is not None and (setup.confidence_score or 0.0) < min_confidence:
-            return False
-        return True
-
-    qualified = [s for s in evaluated if qualifies(s)]
+    if config is not None:
+        qualified = [s for s in evaluated if setup_qualifies(s, config)]
+    else:
+        qualified = evaluated
 
     by_direction: dict[str, list[TradeSetup]] = {}
     by_action: dict[str, list[TradeSetup]] = {}

app/services/qualification.py

@@ -0,0 +1,42 @@
+"""Shared definition of a 'qualified' (actionable) trade setup.
+
+A single predicate, driven by the admin activation config, used by the
+performance stats (server) and mirrored on the frontend. Beyond raw R:R and
+confidence, an actionable setup must show genuine conviction: a high-conviction
+recommended action, a clean (conflict-free) read, and a probable primary target.
+"""
+
+from __future__ import annotations
+
+from typing import Any
+
+HIGH_CONVICTION_ACTIONS = {"LONG_HIGH", "SHORT_HIGH"}
+
+
+def best_target_probability(setup: Any) -> float:
+    """Highest probability among a setup's targets, 0 if none."""
+    targets = getattr(setup, "targets", None) or []
+    probs = [float(t.get("probability", 0.0)) for t in targets if isinstance(t, dict)]
+    return max(probs, default=0.0)
+
+
+def setup_qualifies(setup: Any, config: dict) -> bool:
+    """Whether a setup clears the activation gate.
+
+    ``setup`` is duck-typed: any object exposing rr_ratio, confidence_score,
+    recommended_action, risk_level and a ``targets`` list of dicts.
+    """
+    if setup.rr_ratio < config["min_rr"]:
+        return False
+    if (setup.confidence_score or 0.0) < config["min_confidence"]:
+        return False
+    if config.get("require_high_conviction"):
+        if (setup.recommended_action or "") not in HIGH_CONVICTION_ACTIONS:
+            return False
+    if config.get("exclude_conflicts"):
+        if (setup.risk_level or "") != "Low":
+            return False
+    min_tp = float(config.get("min_target_probability", 0.0))
+    if min_tp > 0 and best_target_probability(setup) < min_tp:
+        return False
+    return True

app/services/sentiment_provider_service.py

@@ -0,0 +1,164 @@
+"""Runtime-configurable sentiment provider.
+
+Lets an admin switch the sentiment LLM (provider, model, API key) at runtime
+via SystemSetting, without a redeploy. Precedence for each value:
+    DB setting  >  environment variable  >  hardcoded default.
+
+The API key is write-only: it is persisted but never returned through any
+read path. Reads report only whether a key is configured and its source.
+"""
+
+from __future__ import annotations
+
+import logging
+
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.config import settings
+from app.exceptions import ProviderError, ValidationError
+from app.models.settings import SystemSetting
+from app.services.admin_service import update_setting
+
+logger = logging.getLogger(__name__)
+
+VALID_PROVIDERS = {"openai", "gemini"}
+
+PROVIDER_DEFAULT_MODELS: dict[str, str] = {
+    "openai": "gpt-4o-mini",
+    "gemini": "gemini-2.0-flash",
+}
+
+# SystemSetting keys
+KEY_PROVIDER = "sentiment_provider"
+KEY_MODEL = "sentiment_model"
+KEY_API_KEY = "sentiment_api_key"
+
+
+async def _get_settings_map(db: AsyncSession) -> dict[str, str]:
+    result = await db.execute(
+        select(SystemSetting).where(
+            SystemSetting.key.in_([KEY_PROVIDER, KEY_MODEL, KEY_API_KEY])
+        )
+    )
+    return {s.key: s.value for s in result.scalars().all()}
+
+
+def _env_key_for(provider: str) -> str:
+    if provider == "openai":
+        return settings.openai_api_key or ""
+    if provider == "gemini":
+        return settings.gemini_api_key or ""
+    return ""
+
+
+def _env_model_for(provider: str) -> str:
+    if provider == "openai":
+        return settings.openai_model or PROVIDER_DEFAULT_MODELS["openai"]
+    if provider == "gemini":
+        return settings.gemini_model or PROVIDER_DEFAULT_MODELS["gemini"]
+    return PROVIDER_DEFAULT_MODELS.get(provider, "")
+
+
+async def _resolve(db: AsyncSession) -> tuple[str, str, str, str]:
+    """Resolve (provider, model, api_key, api_key_source) from DB > env > default."""
+    stored = await _get_settings_map(db)
+
+    provider = (stored.get(KEY_PROVIDER) or "").strip().lower()
+    if provider not in VALID_PROVIDERS:
+        # Default to whichever env key is present, else openai
+        provider = "openai" if settings.openai_api_key or not settings.gemini_api_key else "gemini"
+
+    model = (stored.get(KEY_MODEL) or "").strip() or _env_model_for(provider)
+
+    db_key = (stored.get(KEY_API_KEY) or "").strip()
+    if db_key:
+        return provider, model, db_key, "database"
+    env_key = _env_key_for(provider)
+    if env_key:
+        return provider, model, env_key, "environment"
+    return provider, model, "", "none"
+
+
+async def get_sentiment_config(db: AsyncSession) -> dict:
+    """Public config — never includes the raw API key."""
+    provider, model, api_key, source = await _resolve(db)
+    return {
+        "provider": provider,
+        "model": model,
+        "api_key_configured": bool(api_key),
+        "api_key_source": source,
+        "valid_providers": sorted(VALID_PROVIDERS),
+        "default_models": PROVIDER_DEFAULT_MODELS,
+    }
+
+
+async def update_sentiment_config(
+    db: AsyncSession,
+    provider: str | None = None,
+    model: str | None = None,
+    api_key: str | None = None,
+) -> dict:
+    """Persist provider/model/key. An empty/omitted api_key leaves the stored
+    key untouched (so saving other fields does not wipe credentials)."""
+    if provider is not None:
+        provider = provider.strip().lower()
+        if provider not in VALID_PROVIDERS:
+            raise ValidationError(
+                f"Unknown sentiment provider '{provider}'. Valid: {', '.join(sorted(VALID_PROVIDERS))}"
+            )
+        await update_setting(db, KEY_PROVIDER, provider)
+
+    if model is not None:
+        model = model.strip()
+        if model:
+            await update_setting(db, KEY_MODEL, model)
+
+    if api_key:  # only overwrite when a non-empty key is supplied
+        await update_setting(db, KEY_API_KEY, api_key.strip())
+
+    return await get_sentiment_config(db)
+
+
+async def build_sentiment_provider(db: AsyncSession):
+    """Construct the active sentiment provider from current config.
+
+    Raises ProviderError if no API key is available for the chosen provider.
+    """
+    provider, model, api_key, _source = await _resolve(db)
+    if not api_key:
+        raise ProviderError(f"No API key configured for sentiment provider '{provider}'")
+
+    if provider == "openai":
+        from app.providers.openai_sentiment import OpenAISentimentProvider
+        return OpenAISentimentProvider(api_key, model)
+    if provider == "gemini":
+        from app.providers.gemini_sentiment import GeminiSentimentProvider
+        return GeminiSentimentProvider(api_key, model)
+
+    raise ProviderError(f"Unsupported sentiment provider '{provider}'")
+
+
+async def test_sentiment_provider(db: AsyncSession, ticker: str = "AAPL") -> dict:
+    """Build the active provider and fetch one ticker as a live credentials check."""
+    provider, model, _key, _source = await _resolve(db)
+    try:
+        prov = await build_sentiment_provider(db)
+        data = await prov.fetch_sentiment(ticker.strip().upper())
+        return {
+            "ok": True,
+            "provider": provider,
+            "model": model,
+            "ticker": ticker.strip().upper(),
+            "classification": data.classification,
+            "confidence": data.confidence,
+            "reasoning": data.reasoning or None,
+        }
+    except Exception as exc:
+        logger.warning("Sentiment provider test failed: %s", exc)
+        return {
+            "ok": False,
+            "provider": provider,
+            "model": model,
+            "error": str(exc),
+        }

frontend/src/api/admin.ts

@@ -4,6 +4,8 @@ import type {
   AdminUser,
   PipelineReadiness,
   RecommendationConfig,
+  SentimentProviderConfig,
+  SentimentTestResult,
   SystemSetting,
   TickerUniverse,
   TickerUniverseBootstrapResult,
@@ -81,6 +83,28 @@ export function updateActivationSettings(payload: Partial<ActivationConfig>) {
     .then((r) => r.data);
 }
 
+export function getSentimentSettings() {
+  return apiClient
+    .get<SentimentProviderConfig>('admin/settings/sentiment')
+    .then((r) => r.data);
+}
+
+export function updateSentimentSettings(payload: {
+  provider?: string;
+  model?: string;
+  api_key?: string;
+}) {
+  return apiClient
+    .put<SentimentProviderConfig>('admin/settings/sentiment', payload)
+    .then((r) => r.data);
+}
+
+export function testSentimentSettings(ticker: string) {
+  return apiClient
+    .post<SentimentTestResult>('admin/settings/sentiment/test', { ticker })
+    .then((r) => r.data);
+}
+
 export function getTickerUniverseSetting() {
   return apiClient
     .get<TickerUniverseSetting>('admin/settings/ticker-universe')

frontend/src/api/performance.ts

@@ -2,8 +2,7 @@ import apiClient from './client';
 import type { PerformanceStats } from '../lib/types';
 
 export interface PerformanceParams {
-  min_rr?: number;
-  min_confidence?: number;
+  qualified_only?: boolean;
 }
 
 export function getPerformance(params?: PerformanceParams) {

frontend/src/components/admin/ActivationSettings.tsx

@@ -6,6 +6,9 @@ import { SkeletonTable } from '../ui/Skeleton';
 const DEFAULTS: ActivationConfig = {
   min_rr: 2,
   min_confidence: 70,
+  min_target_probability: 60,
+  require_high_conviction: true,
+  exclude_conflicts: true,
 };
 
 export function ActivationSettings() {
@@ -19,12 +22,12 @@ export function ActivationSettings() {
   }, [data]);
 
   const onSave = () => {
-    update.mutate(form as unknown as Record<string, number>);
+    update.mutate(form);
   };
 
   const onReset = () => {
     setForm(DEFAULTS);
-    update.mutate(DEFAULTS as unknown as Record<string, number>);
+    update.mutate(DEFAULTS);
   };
 
   if (isLoading) return <SkeletonTable rows={2} cols={2} />;
@@ -33,16 +36,16 @@ export function ActivationSettings() {
   return (
     <div className="glass p-5 space-y-4">
       <div>
-        <h3 className="text-sm font-semibold text-gray-200">Activation Thresholds</h3>
+        <h3 className="text-sm font-semibold text-gray-200">Activation Gate</h3>
         <p className="mt-1 text-xs text-gray-500">
-          What counts as a signal worth acting on. Used as the default Signals filters, the
-          Dashboard's qualified-setup metrics, and the Track Record's "qualified only" view.
-          All setups are still evaluated regardless, so these thresholds can be validated
-          against the confidence breakdown.
+          What counts as a signal worth acting on. Drives the Dashboard's "Qualified" metric, the
+          Signals "Qualified only" view, and the Track Record's qualified stats. All setups are
+          still evaluated regardless — tighten the gate, then watch qualified expectancy in the
+          Track Record to find what actually wins.
         </p>
       </div>
 
-      <div className="grid gap-4 md:grid-cols-2">
+      <div className="grid gap-4 md:grid-cols-3">
         <label className="block space-y-1">
           <span className="text-xs text-gray-400">Min Risk:Reward (1 : x)</span>
           <input
@@ -53,6 +56,7 @@ export function ActivationSettings() {
             onChange={(e) => setForm((prev) => ({ ...prev, min_rr: Number(e.target.value) }))}
             className="w-full input-glass px-3 py-2 text-sm"
           />
+          <span className="text-[11px] text-gray-600">Set above your scanner floor or it does nothing.</span>
         </label>
         <label className="block space-y-1">
           <span className="text-xs text-gray-400">Min Confidence (%)</span>
@@ -66,6 +70,50 @@ export function ActivationSettings() {
             className="w-full input-glass px-3 py-2 text-sm"
           />
         </label>
+        <label className="block space-y-1">
+          <span className="text-xs text-gray-400">Min Target Probability (%)</span>
+          <input
+            type="number"
+            min={0}
+            max={100}
+            step={1}
+            value={form.min_target_probability}
+            onChange={(e) => setForm((prev) => ({ ...prev, min_target_probability: Number(e.target.value) }))}
+            className="w-full input-glass px-3 py-2 text-sm"
+          />
+          <span className="text-[11px] text-gray-600">Best target's probability must clear this. 0 disables.</span>
+        </label>
+      </div>
+
+      <div className="grid gap-3 md:grid-cols-2">
+        <label className="flex cursor-pointer items-start gap-2.5 text-sm text-gray-300">
+          <input
+            type="checkbox"
+            checked={form.require_high_conviction}
+            onChange={(e) => setForm((prev) => ({ ...prev, require_high_conviction: e.target.checked }))}
+            className="mt-0.5 h-4 w-4 cursor-pointer accent-blue-400"
+          />
+          <span>
+            Require high conviction
+            <span className="mt-0.5 block text-[11px] text-gray-500">
+              Only LONG (High) / SHORT (High) — the signals must clearly pick a side.
+            </span>
+          </span>
+        </label>
+        <label className="flex cursor-pointer items-start gap-2.5 text-sm text-gray-300">
+          <input
+            type="checkbox"
+            checked={form.exclude_conflicts}
+            onChange={(e) => setForm((prev) => ({ ...prev, exclude_conflicts: e.target.checked }))}
+            className="mt-0.5 h-4 w-4 cursor-pointer accent-blue-400"
+          />
+          <span>
+            Exclude conflicted setups
+            <span className="mt-0.5 block text-[11px] text-gray-500">
+              Risk level must be Low — drops setups with contradicting signals.
+            </span>
+          </span>
+        </label>
       </div>
 
       <div className="flex items-center gap-2">

frontend/src/components/admin/SentimentProviderSettings.tsx

@@ -0,0 +1,154 @@
+import { useEffect, useState } from 'react';
+import {
+  useSentimentSettings,
+  useUpdateSentimentSettings,
+  useTestSentimentProvider,
+} from '../../hooks/useAdmin';
+import { Select } from '../ui/Field';
+import { SkeletonTable } from '../ui/Skeleton';
+import type { SentimentTestResult } from '../../lib/types';
+
+const SOURCE_LABEL: Record<string, string> = {
+  database: 'configured here',
+  environment: 'from environment (.env)',
+  none: 'not configured',
+};
+
+export function SentimentProviderSettings() {
+  const { data, isLoading, isError, error } = useSentimentSettings();
+  const update = useUpdateSentimentSettings();
+  const test = useTestSentimentProvider();
+
+  const [provider, setProvider] = useState('openai');
+  const [model, setModel] = useState('');
+  const [apiKey, setApiKey] = useState('');
+  const [testResult, setTestResult] = useState<SentimentTestResult | null>(null);
+
+  useEffect(() => {
+    if (data) {
+      setProvider(data.provider);
+      setModel(data.model);
+    }
+  }, [data]);
+
+  if (isLoading) return <SkeletonTable rows={3} cols={2} />;
+  if (isError) return <p className="text-sm text-red-400">{(error as Error)?.message || 'Failed to load sentiment settings'}</p>;
+  if (!data) return null;
+
+  const onProviderChange = (next: string) => {
+    setProvider(next);
+    // Auto-fill the model with the new provider's default unless the user has a
+    // custom value that isn't the previous provider's default.
+    const defaults = data.default_models;
+    if (!model || Object.values(defaults).includes(model)) {
+      setModel(defaults[next] ?? '');
+    }
+  };
+
+  const onSave = () => {
+    setTestResult(null);
+    update.mutate({
+      provider,
+      model,
+      ...(apiKey ? { api_key: apiKey } : {}),
+    });
+    setApiKey('');
+  };
+
+  const onTest = () => {
+    test.mutate('AAPL', { onSuccess: (res) => setTestResult(res) });
+  };
+
+  const keyConfigured = data.api_key_configured;
+
+  return (
+    <div className="glass p-5 space-y-4">
+      <div>
+        <h3 className="text-sm font-semibold text-gray-200">Sentiment LLM Provider</h3>
+        <p className="mt-1 text-xs text-gray-500">
+          Switch the model that powers sentiment analysis without redeploying. Applies to the
+          scheduled sentiment job and manual fetches on the next run.
+        </p>
+      </div>
+
+      <div className="grid gap-4 md:grid-cols-2">
+        <label className="block space-y-1">
+          <span className="text-xs text-gray-400">Provider</span>
+          <Select value={provider} onChange={(e) => onProviderChange(e.target.value)} className="w-full !py-2">
+            {data.valid_providers.map((p) => (
+              <option key={p} value={p}>{p}</option>
+            ))}
+          </Select>
+        </label>
+
+        <label className="block space-y-1">
+          <span className="text-xs text-gray-400">Model</span>
+          <input
+            type="text"
+            value={model}
+            onChange={(e) => setModel(e.target.value)}
+            placeholder={data.default_models[provider] ?? ''}
+            className="w-full input-glass px-3 py-2 text-sm"
+          />
+        </label>
+      </div>
+
+      <label className="block space-y-1">
+        <span className="text-xs text-gray-400">API Key</span>
+        <input
+          type="password"
+          value={apiKey}
+          onChange={(e) => setApiKey(e.target.value)}
+          autoComplete="new-password"
+          placeholder={keyConfigured ? '•••••••••• (leave blank to keep current)' : 'Paste API key…'}
+          className="w-full input-glass px-3 py-2 text-sm"
+        />
+        <span className="text-[11px] text-gray-500">
+          Key status:{' '}
+          <span className={keyConfigured ? 'text-emerald-400' : 'text-amber-400'}>
+            {SOURCE_LABEL[data.api_key_source] ?? data.api_key_source}
+          </span>
+          {' '}· write-only, never displayed
+        </span>
+      </label>
+
+      <div className="flex flex-wrap items-center gap-2">
+        <button className="btn-primary px-4 py-2 text-sm" onClick={onSave} disabled={update.isPending}>
+          {update.isPending ? 'Saving…' : 'Save Provider'}
+        </button>
+        <button
+          className="px-4 py-2 text-sm rounded border border-white/[0.1] text-gray-300 hover:text-white disabled:opacity-50"
+          onClick={onTest}
+          disabled={test.isPending}
+        >
+          {test.isPending ? 'Testing (AAPL)…' : 'Test Connection'}
+        </button>
+        <span className="text-[11px] text-gray-500">Test fetches live sentiment for AAPL with the saved config.</span>
+      </div>
+
+      {testResult && (
+        <div
+          className={`rounded-lg border px-4 py-3 text-sm ${
+            testResult.ok
+              ? 'border-emerald-500/20 bg-emerald-500/10 text-emerald-300'
+              : 'border-red-500/20 bg-red-500/10 text-red-400'
+          }`}
+        >
+          {testResult.ok ? (
+            <>
+              <span className="font-medium">✓ {testResult.provider} / {testResult.model}</span> — {testResult.ticker}:{' '}
+              <span className="font-semibold">{testResult.classification}</span>{' '}
+              <span className="num">({testResult.confidence}%)</span>
+              {testResult.reasoning && <p className="mt-1 text-xs text-emerald-300/80">{testResult.reasoning}</p>}
+            </>
+          ) : (
+            <>
+              <span className="font-medium">✗ Test failed</span>
+              <p className="mt-1 text-xs">{testResult.error}</p>
+            </>
+          )}
+        </div>
+      )}
+    </div>
+  );
+}

frontend/src/components/signals/SetupsPanel.tsx

@@ -2,6 +2,7 @@ import { useMemo, useState } from 'react';
 import { useMutation, useQueryClient } from '@tanstack/react-query';
 import { useActivation } from '../../hooks/useActivation';
 import { useTrades } from '../../hooks/useTrades';
+import { qualifiesSetup, activationSummary } from '../../lib/qualification';
 import { TradeTable, type SortColumn, type SortDirection, computeTradeAnalysis } from '../scanner/TradeTable';
 import { SkeletonTable } from '../ui/Skeleton';
 import { useToast } from '../ui/Toast';
@@ -99,18 +100,16 @@ export function SetupsPanel() {
   const queryClient = useQueryClient();
   const toast = useToast();
 
-  // null = user hasn't touched the filter; falls back to admin-configured
-  // activation thresholds once loaded
-  const [minRROverride, setMinRROverride] = useState<number | null>(null);
-  const [minConfidenceOverride, setMinConfidenceOverride] = useState<number | null>(null);
+  // "Qualified only" applies the admin activation gate; the manual filters
+  // below refine within whatever is shown.
+  const [qualifiedOnly, setQualifiedOnly] = useState(true);
+  const [minRR, setMinRR] = useState(0);
+  const [minConfidence, setMinConfidence] = useState(0);
   const [directionFilter, setDirectionFilter] = useState<DirectionFilter>('both');
   const [actionFilter, setActionFilter] = useState<ActionFilter>('all');
   const [sortColumn, setSortColumn] = useState<SortColumn>('rr_ratio');
   const [sortDirection, setSortDirection] = useState<SortDirection>('desc');
 
-  const minRR = minRROverride ?? activation.data?.min_rr ?? 0;
-  const minConfidence = minConfidenceOverride ?? activation.data?.min_confidence ?? 0;
-
   const scanMutation = useMutation({
     mutationFn: () => triggerJob('rr_scanner'),
     onSuccess: () => {
@@ -133,12 +132,35 @@ export function SetupsPanel() {
 
   const processed = useMemo(() => {
     if (!trades) return [];
-    const filtered = filterTrades(trades, minRR, directionFilter, minConfidence, actionFilter);
+    let base = trades;
+    if (qualifiedOnly && activation.data) {
+      base = base.filter((t) => qualifiesSetup(t, activation.data!));
+    }
+    const filtered = filterTrades(base, minRR, directionFilter, minConfidence, actionFilter);
     return sortTrades(filtered, sortColumn, sortDirection);
-  }, [trades, minRR, directionFilter, minConfidence, actionFilter, sortColumn, sortDirection]);
+  }, [trades, qualifiedOnly, activation.data, minRR, directionFilter, minConfidence, actionFilter, sortColumn, sortDirection]);
 
   return (
     <div className="space-y-6">
+      {/* Qualified gate toggle */}
+      <div className="glass-sm flex flex-wrap items-center justify-between gap-3 px-4 py-3">
+        <label className="flex cursor-pointer items-center gap-2.5 text-sm text-gray-300">
+          <input
+            type="checkbox"
+            checked={qualifiedOnly}
+            onChange={(e) => setQualifiedOnly(e.target.checked)}
+            className="h-4 w-4 cursor-pointer accent-blue-400"
+          />
+          <span>
+            Qualified only
+            {activation.data && (
+              <span className="num ml-2 text-xs text-gray-500">{activationSummary(activation.data)}</span>
+            )}
+          </span>
+        </label>
+        <span className="text-xs text-gray-500">Manual filters below refine within this.</span>
+      </div>
+
       {/* Filter toolbar */}
       <div className="glass-sm flex flex-wrap items-end gap-4 p-4">
         <Field label="Min Risk:Reward" htmlFor="min-rr">
@@ -150,7 +172,7 @@ export function SetupsPanel() {
               min={0}
               step={0.1}
               value={minRR}
-              onChange={(e) => setMinRROverride(Number(e.target.value) || 0)}
+              onChange={(e) => setMinRR(Number(e.target.value) || 0)}
               className="w-20"
             />
           </div>
@@ -174,7 +196,7 @@ export function SetupsPanel() {
             max={100}
             step={1}
             value={minConfidence}
-            onChange={(e) => setMinConfidenceOverride(Number(e.target.value) || 0)}
+            onChange={(e) => setMinConfidence(Number(e.target.value) || 0)}
             className="w-24"
           />
         </Field>

frontend/src/components/signals/TrackRecordPanel.tsx

@@ -1,6 +1,7 @@
 import { useState } from 'react';
 import { useMutation, useQueryClient } from '@tanstack/react-query';
 import { useActivation } from '../../hooks/useActivation';
+import { activationSummary } from '../../lib/qualification';
 import { usePerformance } from '../../hooks/usePerformance';
 import { triggerJob } from '../../api/admin';
 import { Button } from '../ui/Button';
@@ -94,11 +95,9 @@ export function TrackRecordPanel() {
   const [qualifiedOnly, setQualifiedOnly] = useState(true);
   const activation = useActivation();
 
-  const params = qualifiedOnly && activation.data
-    ? { min_rr: activation.data.min_rr, min_confidence: activation.data.min_confidence }
-    : undefined;
-
-  const { data, isLoading, isError, error } = usePerformance(params);
+  const { data, isLoading, isError, error } = usePerformance(
+    qualifiedOnly ? { qualified_only: true } : undefined,
+  );
   const queryClient = useQueryClient();
   const toast = useToast();
 
@@ -126,9 +125,7 @@ export function TrackRecordPanel() {
           <span>
             Qualified signals only
             {activation.data && (
-              <span className="num ml-2 text-xs text-gray-500">
-                R:R ≥ {activation.data.min_rr.toFixed(1)} · conf ≥ {activation.data.min_confidence.toFixed(0)}%
-              </span>
+              <span className="num ml-2 text-xs text-gray-500">{activationSummary(activation.data)}</span>
             )}
           </span>
         </label>

frontend/src/hooks/useAdmin.ts

@@ -126,13 +126,13 @@ export function useUpdateActivationSettings() {
   const { addToast } = useToast();
 
   return useMutation({
-    mutationFn: (payload: Record<string, number>) =>
+    mutationFn: (payload: Partial<import('../lib/types').ActivationConfig>) =>
       adminApi.updateActivationSettings(payload),
     onSuccess: () => {
       qc.invalidateQueries({ queryKey: ['admin', 'activation-settings'] });
       qc.invalidateQueries({ queryKey: ['activation'] });
       qc.invalidateQueries({ queryKey: ['performance'] });
-      addToast('success', 'Activation thresholds updated');
+      addToast('success', 'Activation gate updated');
     },
     onError: (error: Error) => {
       addToast('error', error.message || 'Failed to update activation thresholds');
@@ -140,6 +140,41 @@ export function useUpdateActivationSettings() {
   });
 }
 
+export function useSentimentSettings() {
+  return useQuery({
+    queryKey: ['admin', 'sentiment-settings'],
+    queryFn: () => adminApi.getSentimentSettings(),
+  });
+}
+
+export function useUpdateSentimentSettings() {
+  const qc = useQueryClient();
+  const { addToast } = useToast();
+
+  return useMutation({
+    mutationFn: (payload: { provider?: string; model?: string; api_key?: string }) =>
+      adminApi.updateSentimentSettings(payload),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: ['admin', 'sentiment-settings'] });
+      addToast('success', 'Sentiment provider updated');
+    },
+    onError: (error: Error) => {
+      addToast('error', error.message || 'Failed to update sentiment provider');
+    },
+  });
+}
+
+export function useTestSentimentProvider() {
+  const { addToast } = useToast();
+
+  return useMutation({
+    mutationFn: (ticker: string) => adminApi.testSentimentSettings(ticker),
+    onError: (error: Error) => {
+      addToast('error', error.message || 'Sentiment test failed');
+    },
+  });
+}
+
 export function useTickerUniverseSetting() {
   return useQuery({
     queryKey: ['admin', 'ticker-universe'],

frontend/src/lib/qualification.ts

@@ -0,0 +1,33 @@
+import type { ActivationConfig, TradeSetup } from './types';
+
+const HIGH_CONVICTION_ACTIONS = new Set(['LONG_HIGH', 'SHORT_HIGH']);
+
+export function bestTargetProbability(setup: TradeSetup): number {
+  return setup.targets?.length ? Math.max(...setup.targets.map((t) => t.probability)) : 0;
+}
+
+/**
+ * Whether a setup clears the activation gate. Mirrors the backend predicate in
+ * app/services/qualification.py — keep the two in sync.
+ */
+export function qualifiesSetup(setup: TradeSetup, config: ActivationConfig): boolean {
+  if (setup.rr_ratio < config.min_rr) return false;
+  if ((setup.confidence_score ?? 0) < config.min_confidence) return false;
+  if (config.require_high_conviction && !HIGH_CONVICTION_ACTIONS.has(setup.recommended_action ?? '')) {
+    return false;
+  }
+  if (config.exclude_conflicts && (setup.risk_level ?? '') !== 'Low') return false;
+  if (config.min_target_probability > 0 && bestTargetProbability(setup) < config.min_target_probability) {
+    return false;
+  }
+  return true;
+}
+
+/** Short human summary of the active gate, e.g. for tooltips/labels. */
+export function activationSummary(config: ActivationConfig): string {
+  const parts = [`R:R ≥ ${config.min_rr.toFixed(1)}`, `conf ≥ ${config.min_confidence.toFixed(0)}%`];
+  if (config.require_high_conviction) parts.push('high-conviction');
+  if (config.exclude_conflicts) parts.push('clean');
+  if (config.min_target_probability > 0) parts.push(`target ≥ ${config.min_target_probability.toFixed(0)}%`);
+  return parts.join(' · ');
+}

frontend/src/lib/types.ts

@@ -152,10 +152,34 @@ export interface PerformanceStats {
   by_confidence: Record<string, OutcomeBucketStats>;
 }
 
-// Activation thresholds: what counts as an actionable signal
+// Activation gate: what counts as an actionable signal
 export interface ActivationConfig {
   min_rr: number;
   min_confidence: number;
+  min_target_probability: number;
+  require_high_conviction: boolean;
+  exclude_conflicts: boolean;
+}
+
+// Runtime sentiment LLM configuration
+export interface SentimentProviderConfig {
+  provider: string;
+  model: string;
+  api_key_configured: boolean;
+  api_key_source: 'database' | 'environment' | 'none';
+  valid_providers: string[];
+  default_models: Record<string, string>;
+}
+
+export interface SentimentTestResult {
+  ok: boolean;
+  provider: string;
+  model: string;
+  ticker?: string;
+  classification?: string;
+  confidence?: number;
+  reasoning?: string | null;
+  error?: string;
 }
 
 export interface TradeTarget {

frontend/src/pages/AdminPage.tsx

@@ -1,5 +1,6 @@
 import { useState } from 'react';
 import { ActivationSettings } from '../components/admin/ActivationSettings';
+import { SentimentProviderSettings } from '../components/admin/SentimentProviderSettings';
 import { DataCleanup } from '../components/admin/DataCleanup';
 import { JobControls } from '../components/admin/JobControls';
 import { PipelineReadinessPanel } from '../components/admin/PipelineReadinessPanel';
@@ -30,6 +31,7 @@ export default function AdminPage() {
         {activeTab === 'Settings' && (
           <div className="space-y-4">
             <ActivationSettings />
+            <SentimentProviderSettings />
             <TickerUniverseBootstrap />
             <RecommendationSettings />
             <SettingsForm />

frontend/src/pages/DashboardPage.tsx

@@ -9,6 +9,7 @@ import { Section } from '../components/ui/Section';
 import { SkeletonCard, SkeletonTable } from '../components/ui/Skeleton';
 import { formatPrice } from '../lib/format';
 import { recommendationActionLabel } from '../lib/recommendation';
+import { qualifiesSetup, activationSummary } from '../lib/qualification';
 import type { TradeSetup } from '../lib/types';
 
 function fmtR(value: number | null): string {
@@ -55,15 +56,12 @@ export default function DashboardPage() {
   const activation = useActivation();
   const performance = usePerformance();
 
-  const minRR = activation.data?.min_rr ?? 2;
-  const minConfidence = activation.data?.min_confidence ?? 70;
-
   const qualifiedSetups = useMemo(
     () =>
-      (trades.data ?? []).filter(
-        (t) => t.rr_ratio >= minRR && (t.confidence_score ?? 0) >= minConfidence,
-      ),
-    [trades.data, minRR, minConfidence],
+      activation.data
+        ? (trades.data ?? []).filter((t) => qualifiesSetup(t, activation.data!))
+        : [],
+    [trades.data, activation.data],
   );
 
   // Show qualified setups first; fall back to the full list when none qualify
@@ -112,7 +110,7 @@ export default function DashboardPage() {
           <Metric
             label="Qualified"
             value={String(qualifiedSetups.length)}
-            sub={`R:R ≥ ${minRR.toFixed(1)} & conf ≥ ${minConfidence.toFixed(0)}%`}
+            sub={activation.data ? activationSummary(activation.data) : 'clears the activation gate'}
             valueClass={qualifiedSetups.length > 0 ? 'text-blue-300' : 'text-gray-100'}
           />
           <Metric

frontend/tsconfig.tsbuildinfo

@@ -1 +1 @@
-{"root":["./src/app.tsx","./src/main.tsx","./src/vite-env.d.ts","./src/api/activation.ts","./src/api/admin.ts","./src/api/auth.ts","./src/api/client.ts","./src/api/fundamentals.ts","./src/api/health.ts","./src/api/indicators.ts","./src/api/ingestion.ts","./src/api/ohlcv.ts","./src/api/performance.ts","./src/api/scores.ts","./src/api/sentiment.ts","./src/api/sr-levels.ts","./src/api/tickers.ts","./src/api/trades.ts","./src/api/watchlist.ts","./src/components/admin/activationsettings.tsx","./src/components/admin/datacleanup.tsx","./src/components/admin/jobcontrols.tsx","./src/components/admin/pipelinereadinesspanel.tsx","./src/components/admin/recommendationsettings.tsx","./src/components/admin/settingsform.tsx","./src/components/admin/tickermanagement.tsx","./src/components/admin/tickeruniversebootstrap.tsx","./src/components/admin/usertable.tsx","./src/components/auth/protectedroute.tsx","./src/components/charts/candlestickchart.tsx","./src/components/layout/appshell.tsx","./src/components/layout/mobilenav.tsx","./src/components/layout/sidebar.tsx","./src/components/rankings/rankingstable.tsx","./src/components/rankings/weightsform.tsx","./src/components/scanner/tradetable.tsx","./src/components/signals/setupspanel.tsx","./src/components/signals/trackrecordpanel.tsx","./src/components/ticker/dimensionbreakdownpanel.tsx","./src/components/ticker/fundamentalspanel.tsx","./src/components/ticker/indicatorselector.tsx","./src/components/ticker/recommendationpanel.tsx","./src/components/ticker/sroverlay.tsx","./src/components/ticker/sentimentpanel.tsx","./src/components/ui/badge.tsx","./src/components/ui/button.tsx","./src/components/ui/callout.tsx","./src/components/ui/confirmdialog.tsx","./src/components/ui/disclosure.tsx","./src/components/ui/field.tsx","./src/components/ui/pageheader.tsx","./src/components/ui/scorecard.tsx","./src/components/ui/section.tsx","./src/components/ui/skeleton.tsx","./src/components/ui/tabs.tsx","./src/components/ui/toast.tsx","./src/components/watchlist/addtickerform.tsx","./src/components/watchlist/watchlisttable.tsx","./src/hooks/useactivation.ts","./src/hooks/useadmin.ts","./src/hooks/useauth.ts","./src/hooks/usefetchsymboldata.ts","./src/hooks/useperformance.ts","./src/hooks/usescores.ts","./src/hooks/usetickerdetail.ts","./src/hooks/usetickers.ts","./src/hooks/usetrades.ts","./src/hooks/usewatchlist.ts","./src/lib/format.ts","./src/lib/ingestionstatus.ts","./src/lib/recommendation.ts","./src/lib/types.ts","./src/pages/adminpage.tsx","./src/pages/dashboardpage.tsx","./src/pages/loginpage.tsx","./src/pages/marketpage.tsx","./src/pages/registerpage.tsx","./src/pages/signalspage.tsx","./src/pages/tickerdetailpage.tsx","./src/stores/authstore.ts"],"version":"5.6.3"}
+{"root":["./src/app.tsx","./src/main.tsx","./src/vite-env.d.ts","./src/api/activation.ts","./src/api/admin.ts","./src/api/auth.ts","./src/api/client.ts","./src/api/fundamentals.ts","./src/api/health.ts","./src/api/indicators.ts","./src/api/ingestion.ts","./src/api/ohlcv.ts","./src/api/performance.ts","./src/api/scores.ts","./src/api/sentiment.ts","./src/api/sr-levels.ts","./src/api/tickers.ts","./src/api/trades.ts","./src/api/watchlist.ts","./src/components/admin/activationsettings.tsx","./src/components/admin/datacleanup.tsx","./src/components/admin/jobcontrols.tsx","./src/components/admin/pipelinereadinesspanel.tsx","./src/components/admin/recommendationsettings.tsx","./src/components/admin/sentimentprovidersettings.tsx","./src/components/admin/settingsform.tsx","./src/components/admin/tickermanagement.tsx","./src/components/admin/tickeruniversebootstrap.tsx","./src/components/admin/usertable.tsx","./src/components/auth/protectedroute.tsx","./src/components/charts/candlestickchart.tsx","./src/components/layout/appshell.tsx","./src/components/layout/mobilenav.tsx","./src/components/layout/sidebar.tsx","./src/components/rankings/rankingstable.tsx","./src/components/rankings/weightsform.tsx","./src/components/scanner/tradetable.tsx","./src/components/signals/setupspanel.tsx","./src/components/signals/trackrecordpanel.tsx","./src/components/ticker/dimensionbreakdownpanel.tsx","./src/components/ticker/fundamentalspanel.tsx","./src/components/ticker/indicatorselector.tsx","./src/components/ticker/recommendationpanel.tsx","./src/components/ticker/sroverlay.tsx","./src/components/ticker/sentimentpanel.tsx","./src/components/ui/badge.tsx","./src/components/ui/button.tsx","./src/components/ui/callout.tsx","./src/components/ui/confirmdialog.tsx","./src/components/ui/disclosure.tsx","./src/components/ui/field.tsx","./src/components/ui/pageheader.tsx","./src/components/ui/scorecard.tsx","./src/components/ui/section.tsx","./src/components/ui/skeleton.tsx","./src/components/ui/tabs.tsx","./src/components/ui/toast.tsx","./src/components/watchlist/addtickerform.tsx","./src/components/watchlist/watchlisttable.tsx","./src/hooks/useactivation.ts","./src/hooks/useadmin.ts","./src/hooks/useauth.ts","./src/hooks/usefetchsymboldata.ts","./src/hooks/useperformance.ts","./src/hooks/usescores.ts","./src/hooks/usetickerdetail.ts","./src/hooks/usetickers.ts","./src/hooks/usetrades.ts","./src/hooks/usewatchlist.ts","./src/lib/format.ts","./src/lib/ingestionstatus.ts","./src/lib/qualification.ts","./src/lib/recommendation.ts","./src/lib/types.ts","./src/pages/adminpage.tsx","./src/pages/dashboardpage.tsx","./src/pages/loginpage.tsx","./src/pages/marketpage.tsx","./src/pages/registerpage.tsx","./src/pages/signalspage.tsx","./src/pages/tickerdetailpage.tsx","./src/stores/authstore.ts"],"version":"5.6.3"}

tests/unit/test_activation_settings.py

@@ -24,16 +24,24 @@ async def session() -> AsyncSession:
 class TestActivationConfig:
     async def test_defaults_when_unset(self, session: AsyncSession):
         config = await get_activation_config(session)
-        assert config == {"min_rr": 2.0, "min_confidence": 70.0}
+        assert config == {
+            "min_rr": 2.0,
+            "min_confidence": 70.0,
+            "min_target_probability": 60.0,
+            "require_high_conviction": True,
+            "exclude_conflicts": True,
+        }
 
     async def test_update_and_read_back(self, session: AsyncSession):
         updated = await update_activation_config(
             session, {"min_rr": 1.5, "min_confidence": 60.0}
         )
-        assert updated == {"min_rr": 1.5, "min_confidence": 60.0}
+        assert updated["min_rr"] == 1.5
+        assert updated["min_confidence"] == 60.0
 
         config = await get_activation_config(session)
-        assert config == {"min_rr": 1.5, "min_confidence": 60.0}
+        assert config["min_rr"] == 1.5
+        assert config["min_confidence"] == 60.0
 
     async def test_partial_update_keeps_other_value(self, session: AsyncSession):
         await update_activation_config(session, {"min_confidence": 80.0})
@@ -41,6 +49,16 @@ class TestActivationConfig:
         assert config["min_rr"] == 2.0  # default untouched
         assert config["min_confidence"] == 80.0
 
+    async def test_conviction_flags_round_trip(self, session: AsyncSession):
+        await update_activation_config(
+            session,
+            {"require_high_conviction": False, "exclude_conflicts": False, "min_target_probability": 45.0},
+        )
+        config = await get_activation_config(session)
+        assert config["require_high_conviction"] is False
+        assert config["exclude_conflicts"] is False
+        assert config["min_target_probability"] == 45.0
+
     async def test_rejects_negative_rr(self, session: AsyncSession):
         with pytest.raises(ValidationError):
             await update_activation_config(session, {"min_rr": -1.0})
@@ -48,3 +66,7 @@ class TestActivationConfig:
     async def test_rejects_out_of_range_confidence(self, session: AsyncSession):
         with pytest.raises(ValidationError):
             await update_activation_config(session, {"min_confidence": 120.0})
+
+    async def test_rejects_out_of_range_target_probability(self, session: AsyncSession):
+        with pytest.raises(ValidationError):
+            await update_activation_config(session, {"min_target_probability": 150.0})

tests/unit/test_outcome_service.py

@@ -289,7 +289,15 @@ class TestGetPerformanceStats:
         ))
         await db_session.flush()
 
-        stats = await get_performance_stats(db_session, min_rr=2.0, min_confidence=70.0)
+        # Gate on R:R + confidence only (conviction filters off for this test)
+        config = {
+            "min_rr": 2.0,
+            "min_confidence": 70.0,
+            "min_target_probability": 0.0,
+            "require_high_conviction": False,
+            "exclude_conflicts": False,
+        }
+        stats = await get_performance_stats(db_session, config=config)
 
         # Overall covers only the qualified setup
         assert stats["overall"]["total"] == 1

tests/unit/test_qualification.py

@@ -0,0 +1,81 @@
+"""Unit tests for the activation qualification predicate."""
+
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+from app.services.qualification import best_target_probability, setup_qualifies
+
+FULL_GATE = {
+    "min_rr": 2.0,
+    "min_confidence": 70.0,
+    "min_target_probability": 60.0,
+    "require_high_conviction": True,
+    "exclude_conflicts": True,
+}
+
+
+def _setup(**kwargs):
+    base = dict(
+        rr_ratio=3.0,
+        confidence_score=80.0,
+        recommended_action="LONG_HIGH",
+        risk_level="Low",
+        targets=[{"probability": 65.0}],
+    )
+    base.update(kwargs)
+    return SimpleNamespace(**base)
+
+
+class TestSetupQualifies:
+    def test_clean_high_conviction_setup_passes(self):
+        assert setup_qualifies(_setup(), FULL_GATE) is True
+
+    def test_low_rr_fails(self):
+        assert setup_qualifies(_setup(rr_ratio=1.5), FULL_GATE) is False
+
+    def test_low_confidence_fails(self):
+        assert setup_qualifies(_setup(confidence_score=60.0), FULL_GATE) is False
+
+    def test_moderate_action_fails_when_high_conviction_required(self):
+        assert setup_qualifies(_setup(recommended_action="LONG_MODERATE"), FULL_GATE) is False
+
+    def test_neutral_action_fails(self):
+        assert setup_qualifies(_setup(recommended_action="NEUTRAL"), FULL_GATE) is False
+
+    def test_short_high_passes(self):
+        assert setup_qualifies(_setup(recommended_action="SHORT_HIGH"), FULL_GATE) is True
+
+    def test_non_low_risk_fails_when_excluding_conflicts(self):
+        assert setup_qualifies(_setup(risk_level="Medium"), FULL_GATE) is False
+        assert setup_qualifies(_setup(risk_level="High"), FULL_GATE) is False
+
+    def test_low_target_probability_fails(self):
+        assert setup_qualifies(_setup(targets=[{"probability": 40.0}]), FULL_GATE) is False
+
+    def test_no_targets_fails_when_probability_required(self):
+        assert setup_qualifies(_setup(targets=[]), FULL_GATE) is False
+
+    def test_conviction_filters_can_be_disabled(self):
+        relaxed = {
+            "min_rr": 2.0,
+            "min_confidence": 70.0,
+            "min_target_probability": 0.0,
+            "require_high_conviction": False,
+            "exclude_conflicts": False,
+        }
+        # Moderate action, medium risk, no targets — still passes on rr+confidence alone
+        s = _setup(recommended_action="LONG_MODERATE", risk_level="Medium", targets=[])
+        assert setup_qualifies(s, relaxed) is True
+
+    def test_missing_confidence_treated_as_zero(self):
+        assert setup_qualifies(_setup(confidence_score=None), FULL_GATE) is False
+
+
+class TestBestTargetProbability:
+    def test_returns_max(self):
+        s = _setup(targets=[{"probability": 40.0}, {"probability": 72.0}, {"probability": 55.0}])
+        assert best_target_probability(s) == 72.0
+
+    def test_empty_is_zero(self):
+        assert best_target_probability(_setup(targets=[])) == 0.0

tests/unit/test_sentiment_provider_service.py

@@ -0,0 +1,94 @@
+"""Unit tests for runtime sentiment provider configuration."""
+
+from __future__ import annotations
+
+import pytest
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.exceptions import ProviderError, ValidationError
+from app.models.settings import SystemSetting
+from app.services import sentiment_provider_service as sps
+
+
+@pytest.fixture
+async def session() -> AsyncSession:
+    from tests.conftest import _test_session_factory
+
+    async with _test_session_factory() as session:
+        yield session
+
+
+@pytest.fixture(autouse=True)
+def _clear_env_keys(monkeypatch):
+    """Default: no env keys, so DB-only behavior is deterministic."""
+    monkeypatch.setattr(sps.settings, "openai_api_key", "")
+    monkeypatch.setattr(sps.settings, "gemini_api_key", "")
+
+
+class TestGetConfig:
+    async def test_defaults_no_key(self, session: AsyncSession):
+        config = await sps.get_sentiment_config(session)
+        assert config["provider"] == "openai"
+        assert config["model"] == "gpt-4o-mini"
+        assert config["api_key_configured"] is False
+        assert config["api_key_source"] == "none"
+        assert set(config["valid_providers"]) == {"openai", "gemini"}
+
+    async def test_never_returns_raw_key(self, session: AsyncSession):
+        await sps.update_sentiment_config(session, api_key="sk-secret-123")
+        config = await sps.get_sentiment_config(session)
+        # No field should leak the key
+        assert "sk-secret-123" not in str(config)
+        assert config["api_key_configured"] is True
+        assert config["api_key_source"] == "database"
+
+    async def test_env_fallback_reported(self, session: AsyncSession, monkeypatch):
+        monkeypatch.setattr(sps.settings, "openai_api_key", "sk-from-env")
+        config = await sps.get_sentiment_config(session)
+        assert config["api_key_configured"] is True
+        assert config["api_key_source"] == "environment"
+
+
+class TestUpdateConfig:
+    async def test_update_provider_and_model(self, session: AsyncSession):
+        result = await sps.update_sentiment_config(
+            session, provider="gemini", model="gemini-2.0-flash"
+        )
+        assert result["provider"] == "gemini"
+        assert result["model"] == "gemini-2.0-flash"
+
+    async def test_empty_key_does_not_overwrite(self, session: AsyncSession):
+        await sps.update_sentiment_config(session, api_key="sk-original")
+        # Subsequent save without a key must keep the original
+        await sps.update_sentiment_config(session, provider="openai", api_key="")
+        result = await session.execute(
+            select(SystemSetting).where(SystemSetting.key == sps.KEY_API_KEY)
+        )
+        assert result.scalar_one().value == "sk-original"
+
+    async def test_rejects_invalid_provider(self, session: AsyncSession):
+        with pytest.raises(ValidationError):
+            await sps.update_sentiment_config(session, provider="anthropic")
+
+
+class TestBuildProvider:
+    async def test_raises_without_key(self, session: AsyncSession):
+        with pytest.raises(ProviderError):
+            await sps.build_sentiment_provider(session)
+
+    async def test_builds_openai(self, session: AsyncSession):
+        await sps.update_sentiment_config(session, provider="openai", api_key="sk-x")
+        provider = await sps.build_sentiment_provider(session)
+        assert type(provider).__name__ == "OpenAISentimentProvider"
+
+    async def test_builds_gemini(self, session: AsyncSession):
+        await sps.update_sentiment_config(session, provider="gemini", api_key="g-x")
+        provider = await sps.build_sentiment_provider(session)
+        assert type(provider).__name__ == "GeminiSentimentProvider"
+
+    async def test_uses_env_key_when_db_empty(self, session: AsyncSession, monkeypatch):
+        monkeypatch.setattr(sps.settings, "openai_api_key", "sk-env")
+        await sps.update_sentiment_config(session, provider="openai")
+        provider = await sps.build_sentiment_provider(session)
+        assert type(provider).__name__ == "OpenAISentimentProvider"