feat:: causal lab
This commit is contained in:
@@ -321,6 +321,11 @@ class RecommendRequest(BaseModel):
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market_event_id: int
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class InstantiateRequest(BaseModel):
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market_event_id: int
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template_id: int
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class AnalyzeRequest(BaseModel):
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market_event_id: int
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template_id: int
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@@ -635,6 +640,97 @@ def recommend_template(body: RecommendRequest):
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raise HTTPException(500, str(e))
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@router.post("/api/causal-lab/instantiate")
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def instantiate_template(body: InstantiateRequest):
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"""
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GPT-4o-mini suggère les valeurs des nœuds user_input du template
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en fonction des spécificités de l'événement (surprise +/-, magnitude, catégorie…).
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Retourne { inputs: { node_id: value }, rationale: str }
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"""
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try:
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from services.database import get_conn
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conn = get_conn()
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_init(conn)
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ev_row = conn.execute("SELECT * FROM market_events WHERE id = ?", (body.market_event_id,)).fetchone()
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tmpl_row = conn.execute("SELECT * FROM causal_graph_templates WHERE id = ?", (body.template_id,)).fetchone()
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conn.close()
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if not ev_row or not tmpl_row:
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raise HTTPException(404, "event ou template introuvable")
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event = dict(ev_row)
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template = dict(tmpl_row)
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graph_json = json.loads(template.get("graph_json") or "{}")
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input_mapping = graph_json.get("input_mapping", {})
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# Only user_input nodes need to be suggested (auto-sourced nodes are pulled from DB)
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user_nodes = {
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k: v for k, v in input_mapping.items()
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if not v.get("source") or v["source"] == "user_input"
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}
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if not user_nodes:
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return {"inputs": {}, "rationale": "Aucun nœud manuel — tout est auto-récupéré depuis la BD"}
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prompt = f"""Tu es un analyste financier. Tu dois configurer un graphe causal pour un événement de marché précis.
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Événement : {event.get('name')}
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Catégorie : {event.get('category')} / {event.get('sub_type', '')}
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Date : {event.get('start_date')}
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Description : {(event.get('description') or '')[:400]}
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Score impact : {event.get('impact_score', 0.5)}
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Valeur réelle : {event.get('actual_value')} | Valeur attendue : {event.get('expected_value')} | Surprise % : {event.get('surprise_pct')}
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Template : {template.get('name')} (catégorie : {template.get('category')})
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Nœuds à configurer (entrées manuelles) :
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{json.dumps(user_nodes, indent=2, ensure_ascii=False)}
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Règles :
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- Surprise NÉGATIVE → valeurs négatives pour les nœuds de surprise
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- Surprise POSITIVE → valeurs positives
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- Utilise les plages "range" si fournies (ex: [-3, 3] pour z-score)
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- Magnitude proportionnelle à l'ampleur de la surprise
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- Si surprise_pct disponible, utilise-la pour calibrer (ex: -29.1% → nœud_surprise ≈ -2.5)
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Retourne UNIQUEMENT un JSON : {{ "node_id": valeur_numerique, ... }}
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Inclure uniquement les nœuds listés ci-dessus."""
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client = _openai_client()
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resp = client.chat.completions.create(
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model="gpt-4o-mini",
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messages=[{"role": "user", "content": prompt}],
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response_format={"type": "json_object"},
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temperature=0.2,
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max_tokens=400,
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)
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raw = resp.choices[0].message.content or "{}"
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suggested = json.loads(raw)
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# Validate: only keep known nodes with numeric values
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validated: dict = {}
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for k, v in suggested.items():
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if k in user_nodes:
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try:
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validated[k] = float(v)
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except (TypeError, ValueError):
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pass
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surprise = event.get("surprise_pct")
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rationale = (
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f"Surprise {'+' if (surprise or 0) >= 0 else ''}{surprise:.1f}%" if surprise is not None
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else "Calibration basée sur la description de l'événement"
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)
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return {"inputs": validated, "rationale": rationale}
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"[causal_lab] instantiate: {e}")
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raise HTTPException(500, str(e))
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@router.post("/api/causal-lab/analyze")
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def analyze_event(body: AnalyzeRequest):
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"""
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@@ -51,12 +51,13 @@ router = APIRouter(prefix="/api/actions", tags=["Cycle Actions"])
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class CheckEventsRequest(BaseModel):
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sources: Optional[List[str]] = None # ['news','eco','technical','reports']
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news_impact_min: float = 0.55
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news_lookback_hours: int = 48
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eco_z_threshold: float = 1.5
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eco_days: int = 7
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technical_lookback_days: int = 7
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report_days: int = 7
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report_min_importance: int = 3
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# Unified date window for news + eco (replaces eco_days + news_lookback_hours)
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date_from: Optional[str] = None # ISO date, e.g. "2026-06-21"
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date_to: Optional[str] = None # ISO date, e.g. "2026-06-28"
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class ActionResult(BaseModel):
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@@ -151,12 +152,12 @@ def check_market_events(req: CheckEventsRequest):
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result = check_new_market_events(
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sources=req.sources,
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news_impact_min=req.news_impact_min,
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news_lookback_hours=req.news_lookback_hours,
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eco_z_threshold=req.eco_z_threshold,
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eco_days=req.eco_days,
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technical_lookback_days=req.technical_lookback_days,
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report_days=req.report_days,
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report_min_importance=req.report_min_importance,
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date_from=req.date_from,
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date_to=req.date_to,
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)
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except Exception as e:
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_release("check-market-events")
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@@ -204,12 +205,12 @@ def check_market_events_background(
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check_new_market_events(
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sources=req.sources,
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news_impact_min=req.news_impact_min,
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news_lookback_hours=req.news_lookback_hours,
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eco_z_threshold=req.eco_z_threshold,
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eco_days=req.eco_days,
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technical_lookback_days=req.technical_lookback_days,
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report_days=req.report_days,
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report_min_importance=req.report_min_importance,
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date_from=req.date_from,
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date_to=req.date_to,
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)
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except Exception as e:
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logger.error(f"[action/check-market-events/bg] {e}")
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@@ -528,9 +528,14 @@ def _get_relevant_events(
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"""
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try:
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from services.database import get_conn
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from services.causal_graphs import init_tables
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conn = get_conn()
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init_tables(conn) # ensure causal_event_analyses exists
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rows = conn.execute("""
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SELECT e.*,
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(SELECT GROUP_CONCAT(DISTINCT a.instrument)
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FROM causal_event_analyses a
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WHERE a.market_event_id = e.id) AS analyzed_instruments,
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(SELECT a.template_id FROM causal_event_analyses a WHERE a.market_event_id = e.id ORDER BY a.id DESC LIMIT 1) AS template_id,
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(SELECT a.id FROM causal_event_analyses a WHERE a.market_event_id = e.id ORDER BY a.id DESC LIMIT 1) AS analysis_id
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FROM market_events e
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@@ -581,6 +586,7 @@ def _get_relevant_events(
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filtered.append({
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"id": ev.get("id"),
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"template_id": ev.get("template_id"),
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"analyzed_instruments": ev.get("analyzed_instruments"), # comma-sep, e.g. "EURUSD,SP500"
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"date": ev_start,
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"end_date": ev.get("end_date") or None,
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"title": ev.get("name") or ev.get("event_name") or "",
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@@ -187,12 +187,13 @@ Réponds JSON: {{"is_duplicate": true/false, "reason": "courte phrase"}}"""
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def _check_news(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
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from services.data_fetcher import fetch_geo_news
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min_impact = float(desk_cfg.get("min_impact", 0.55))
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lookback_hours = int(desk_cfg.get("lookback_hours", 48))
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max_evaluate = int(desk_cfg.get("max_evaluate", 15))
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dedup_enabled = bool(desk_cfg.get("dedup_enabled", True))
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dedup_days = int(desk_cfg.get("dedup_lookback_days", 2))
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system_prompt = desk_cfg.get("_system_prompt", "")
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min_impact = float(desk_cfg.get("min_impact", 0.55))
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max_evaluate = int(desk_cfg.get("max_evaluate", 15))
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dedup_enabled = bool(desk_cfg.get("dedup_enabled", True))
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dedup_days = int(desk_cfg.get("dedup_lookback_days", 2))
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system_prompt = desk_cfg.get("_system_prompt", "")
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date_from = desk_cfg.get("date_from")
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date_to = desk_cfg.get("date_to")
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api_key = _get_api_key()
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if not api_key:
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@@ -205,14 +206,22 @@ def _check_news(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
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logger.warning(f"[check_events/news] fetch failed: {e}")
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return []
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cutoff_dt = datetime.utcnow() - timedelta(hours=lookback_hours)
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# Build cutoff from date_from; date_to used as upper bound
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try:
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cutoff_from = datetime.fromisoformat(date_from) if date_from else datetime.utcnow() - timedelta(days=7)
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cutoff_to = datetime.fromisoformat(date_to) if date_to else datetime.utcnow()
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except Exception:
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cutoff_from = datetime.utcnow() - timedelta(days=7)
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cutoff_to = datetime.utcnow()
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candidates = []
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for n in all_news:
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if (n.get("impact_score") or 0) < min_impact:
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continue
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pub_date = _parse_date(n.get("date", ""))
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try:
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if datetime.fromisoformat(pub_date) < cutoff_dt:
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pub_dt = datetime.fromisoformat(pub_date)
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if pub_dt < cutoff_from or pub_dt > cutoff_to:
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continue
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except Exception:
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pass
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@@ -329,7 +338,8 @@ FORMAT JSON STRICT:
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def _check_ff_calendar_surprises(
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currencies: List[str],
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min_impact: str,
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days: int,
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date_from: str,
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date_to: str,
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min_surprise_pct: float,
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lookback_releases: int,
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create_evt: bool,
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@@ -347,7 +357,6 @@ def _check_ff_calendar_surprises(
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"low": ("high", "medium", "low"),
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}
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allowed_impacts = impact_map.get(min_impact, ("high", "medium"))
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cutoff = (datetime.utcnow() - timedelta(days=days)).strftime("%Y-%m-%d")
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try:
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conn = get_conn()
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@@ -360,11 +369,12 @@ def _check_ff_calendar_surprises(
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WHERE currency IN ({ccy_ph})
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AND impact IN ({imp_ph})
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AND event_date >= ?
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AND event_date <= ?
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AND actual_value IS NOT NULL
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AND forecast_value IS NOT NULL
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ORDER BY event_date DESC
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LIMIT 200""",
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(*currencies, *allowed_impacts, cutoff),
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(*currencies, *allowed_impacts, date_from, date_to),
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).fetchall()
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conn.close()
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except Exception as e:
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@@ -457,28 +467,45 @@ def _check_ff_calendar_surprises(
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def _check_eco(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
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from services.database import get_recent_economic_surprises, get_conn
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from services.database import get_conn
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z_threshold = float(desk_cfg.get("z_threshold", 1.5))
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days = int(desk_cfg.get("days", 7))
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date_from = desk_cfg.get("date_from") or (datetime.utcnow() - timedelta(days=7)).strftime("%Y-%m-%d")
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date_to = desk_cfg.get("date_to") or datetime.utcnow().strftime("%Y-%m-%d")
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currencies = list(desk_cfg.get("currencies") or ["USD", "EUR", "GBP", "JPY"])
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min_impact = str(desk_cfg.get("min_impact", "medium")).lower()
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create_evt = bool(desk_cfg.get("create_market_event", True))
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lookback_releases = int(desk_cfg.get("lookback_releases", 3))
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min_rank = _IMPACT_RANKS.get(min_impact, 2)
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# ff_calendar surprise threshold: z_threshold used as rough proxy (×10 → % equivalent)
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ff_surprise_min = max(10.0, z_threshold * 10)
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min_rank = _IMPACT_RANKS.get(min_impact, 2)
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ff_surprise_min = max(10.0, z_threshold * 10)
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existing = _existing_event_keys()
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created: List[Dict] = []
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# ── FRED path (USD only) ──────────────────────────────────────────────────
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# ── Local economic_events table (replaces FRED API call) ─────────────────
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if "USD" in currencies:
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try:
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releases = get_recent_economic_surprises(days=days, min_zscore=z_threshold)
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conn = get_conn()
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rows = conn.execute(
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"""SELECT * FROM economic_events
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WHERE event_date >= ? AND event_date <= ?
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AND ABS(COALESCE(surprise_zscore, 0)) >= ?
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ORDER BY event_date DESC, ABS(COALESCE(surprise_zscore, 0)) DESC
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LIMIT 50""",
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(date_from, date_to, z_threshold),
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).fetchall()
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conn.close()
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releases = []
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for r in rows:
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d = dict(r)
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try:
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d["assets_impacted"] = json.loads(d.get("assets_impacted") or "[]")
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except Exception:
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d["assets_impacted"] = []
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releases.append(d)
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except Exception as e:
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logger.warning(f"[check_events/eco] FRED query failed: {e}")
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logger.warning(f"[check_events/eco] local query failed: {e}")
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releases = []
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for rel in releases:
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@@ -572,7 +599,8 @@ def _check_eco(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
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created += _check_ff_calendar_surprises(
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currencies=non_usd,
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min_impact=min_impact,
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days=days,
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date_from=date_from,
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date_to=date_to,
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min_surprise_pct=ff_surprise_min,
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lookback_releases=lookback_releases,
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create_evt=create_evt,
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@@ -860,13 +888,14 @@ def _check_fundamental(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""Corporate fundamental events: layoffs, M&A, earnings, credit, regulatory."""
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from services.data_fetcher import fetch_geo_news
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min_impact = float(desk_cfg.get("min_impact", 0.45))
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lookback_hours = int(desk_cfg.get("lookback_hours", 72))
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max_evaluate = int(desk_cfg.get("max_evaluate", 20))
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dedup_enabled = bool(desk_cfg.get("dedup_enabled", True))
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dedup_days = int(desk_cfg.get("dedup_lookback_days", 3))
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system_prompt = desk_cfg.get("_system_prompt", "")
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focus_types = desk_cfg.get("focus_types", ["layoffs","earnings","ma","credit","regulatory","guidance"])
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min_impact = float(desk_cfg.get("min_impact", 0.45))
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max_evaluate = int(desk_cfg.get("max_evaluate", 20))
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dedup_enabled = bool(desk_cfg.get("dedup_enabled", True))
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dedup_days = int(desk_cfg.get("dedup_lookback_days", 3))
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system_prompt = desk_cfg.get("_system_prompt", "")
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focus_types = desk_cfg.get("focus_types", ["layoffs","earnings","ma","credit","regulatory","guidance"])
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date_from = desk_cfg.get("date_from") or (datetime.utcnow() - timedelta(days=7)).strftime("%Y-%m-%d")
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date_to = desk_cfg.get("date_to") or datetime.utcnow().strftime("%Y-%m-%d")
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api_key = _get_api_key()
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if not api_key:
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@@ -878,11 +907,10 @@ def _check_fundamental(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
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logger.warning(f"[check_events/fundamental] fetch failed: {e}")
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return []
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cutoff_dt = datetime.utcnow() - timedelta(hours=lookback_hours)
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candidates = [
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n for n in all_news
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if (n.get("impact_score") or 0) >= min_impact
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and _parse_date(n.get("date", "")) >= cutoff_dt.strftime("%Y-%m-%d")
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and date_from <= _parse_date(n.get("date", "")) <= date_to
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][:max_evaluate]
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if not candidates:
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@@ -1617,11 +1645,12 @@ def _check_macro_gauges(desk_cfg: Dict[str, Any]) -> List[Dict[str, Any]]:
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def check_new_market_events(
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sources: Optional[List[str]] = None,
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# Unified date window — overrides eco_days/news_lookback_hours when provided
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date_from: Optional[str] = None,
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date_to: Optional[str] = None,
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# Legacy overrides — used when called without an active desk
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news_impact_min: float = 0.55,
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news_lookback_hours: int = 48,
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eco_z_threshold: float = 1.5,
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eco_days: int = 7,
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technical_lookback_days: int = 7,
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report_days: int = 7,
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report_min_importance: int = 3,
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@@ -1655,17 +1684,27 @@ def check_new_market_events(
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cfg["_system_prompt"] = desk.get("system_prompt") or ""
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return cfg
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# Compute default date_from fallback from desk config or 7-day default
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_now = datetime.utcnow()
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_date_to = date_to or _now.strftime("%Y-%m-%d")
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_date_from = date_from or (_now - timedelta(days=7)).strftime("%Y-%m-%d")
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news_cfg = _desk_cfg(news_desk, {
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"min_impact": news_impact_min, "lookback_hours": news_lookback_hours,
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"min_impact": news_impact_min,
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"max_evaluate": 15, "dedup_enabled": False, "dedup_lookback_days": 2,
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})
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news_cfg["date_from"] = _date_from
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news_cfg["date_to"] = _date_to
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|
||||
fundamental_cfg = _desk_cfg(fundamental_desk, {
|
||||
"min_impact": 0.45, "lookback_hours": 72, "max_evaluate": 20,
|
||||
"min_impact": 0.45, "max_evaluate": 20,
|
||||
"dedup_enabled": True, "dedup_lookback_days": 3,
|
||||
})
|
||||
fundamental_cfg["date_from"] = _date_from
|
||||
fundamental_cfg["date_to"] = _date_to
|
||||
|
||||
eco_cfg = _desk_cfg(eco_desk, {
|
||||
"z_threshold": eco_z_threshold,
|
||||
"days": eco_days,
|
||||
"gauge_signals": {
|
||||
"regime_transition": {"enabled": True},
|
||||
"yield_curve_inversion": {"enabled": True, "threshold": 0.0},
|
||||
@@ -1674,6 +1713,8 @@ def check_new_market_events(
|
||||
"gold_copper_ratio": {"enabled": True, "fear_threshold": 700, "growth_threshold": 500},
|
||||
},
|
||||
})
|
||||
eco_cfg["date_from"] = _date_from
|
||||
eco_cfg["date_to"] = _date_to
|
||||
tech_cfg = _desk_cfg(tech_desk, {
|
||||
"lookback_days": technical_lookback_days,
|
||||
"signals": {
|
||||
|
||||
@@ -122,27 +122,44 @@ function BootstrapAction({ action }: { action: ActionDef }) {
|
||||
interface CheckEventsConfig {
|
||||
sources: string[]
|
||||
news_impact_min: number
|
||||
news_lookback_hours: number
|
||||
eco_z_threshold: number
|
||||
eco_days: number
|
||||
technical_lookback_days: number
|
||||
report_days: number
|
||||
report_min_importance: number
|
||||
date_from: string
|
||||
date_to: string
|
||||
}
|
||||
|
||||
const DEFAULT_CONFIG: CheckEventsConfig = {
|
||||
sources: ['news', 'eco', 'technical', 'reports'],
|
||||
news_impact_min: 0.55,
|
||||
news_lookback_hours: 48,
|
||||
eco_z_threshold: 1.5,
|
||||
eco_days: 7,
|
||||
technical_lookback_days: 7,
|
||||
report_days: 7,
|
||||
report_min_importance: 3,
|
||||
const SCAN_PRESETS = [
|
||||
{ label: '6h', hours: 6 },
|
||||
{ label: '12h', hours: 12 },
|
||||
{ label: '24h', hours: 24 },
|
||||
{ label: '48h', hours: 48 },
|
||||
{ label: '72h', hours: 72 },
|
||||
{ label: '7j', hours: 168 },
|
||||
]
|
||||
|
||||
function presetDates(hours: number): { date_from: string; date_to: string } {
|
||||
const now = new Date()
|
||||
const from = new Date(now.getTime() - hours * 3_600_000)
|
||||
const fmt = (d: Date) => d.toISOString().slice(0, 10)
|
||||
return { date_from: fmt(from), date_to: fmt(now) }
|
||||
}
|
||||
|
||||
function makeDefaultConfig(): CheckEventsConfig {
|
||||
return {
|
||||
sources: ['news', 'eco', 'technical', 'reports'],
|
||||
news_impact_min: 0.55,
|
||||
eco_z_threshold: 1.5,
|
||||
technical_lookback_days: 7,
|
||||
report_days: 7,
|
||||
report_min_importance: 3,
|
||||
...presetDates(48),
|
||||
}
|
||||
}
|
||||
|
||||
function CheckEventsPanel() {
|
||||
const [config, setConfig] = useState<CheckEventsConfig>(DEFAULT_CONFIG)
|
||||
const [config, setConfig] = useState<CheckEventsConfig>(makeDefaultConfig)
|
||||
const [running, setRunning] = useState(false)
|
||||
const [result, setResult] = useState<ActionResult | null>(null)
|
||||
const [error, setError] = useState<string | null>(null)
|
||||
@@ -215,14 +232,46 @@ function CheckEventsPanel() {
|
||||
</div>
|
||||
|
||||
{showConfig && (
|
||||
<div className="px-5 pb-4 border-t border-slate-700/30 pt-4 grid grid-cols-2 gap-4 text-sm">
|
||||
<div className="px-5 pb-5 border-t border-slate-700/30 pt-4 space-y-4 text-sm">
|
||||
|
||||
{/* Fenêtre de scan */}
|
||||
<div>
|
||||
<div className="text-slate-400 mb-2 text-xs uppercase tracking-wide">Fenêtre de scan (news + éco)</div>
|
||||
<div className="flex flex-wrap gap-1.5 mb-2">
|
||||
{SCAN_PRESETS.map(p => {
|
||||
const { date_from, date_to } = presetDates(p.hours)
|
||||
const active = config.date_from === date_from && config.date_to === date_to
|
||||
return (
|
||||
<button key={p.label}
|
||||
onClick={() => setConfig(c => ({ ...c, ...presetDates(p.hours) }))}
|
||||
className={`px-3 py-1 rounded text-xs border transition-colors ${
|
||||
active
|
||||
? 'bg-blue-600/30 border-blue-500/50 text-blue-300'
|
||||
: 'border-slate-700 text-slate-500 hover:border-slate-500 hover:text-slate-300'
|
||||
}`}
|
||||
>
|
||||
{p.label}
|
||||
</button>
|
||||
)
|
||||
})}
|
||||
</div>
|
||||
<div className="flex gap-2 items-center">
|
||||
<input type="date" value={config.date_from}
|
||||
onChange={e => setConfig(c => ({ ...c, date_from: e.target.value }))}
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-xs flex-1" />
|
||||
<span className="text-slate-600 text-xs">→</span>
|
||||
<input type="date" value={config.date_to}
|
||||
onChange={e => setConfig(c => ({ ...c, date_to: e.target.value }))}
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-xs flex-1" />
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Sources */}
|
||||
<div>
|
||||
<div className="text-slate-400 mb-2 text-xs uppercase tracking-wide">Sources actives</div>
|
||||
<div className="flex flex-wrap gap-2">
|
||||
{['news', 'eco', 'technical', 'reports'].map(s => (
|
||||
<button
|
||||
key={s}
|
||||
onClick={() => toggleSource(s)}
|
||||
<button key={s} onClick={() => toggleSource(s)}
|
||||
className={`px-3 py-1 rounded-full text-xs border transition-colors ${
|
||||
config.sources.includes(s)
|
||||
? 'bg-emerald-600/30 border-emerald-500/50 text-emerald-300'
|
||||
@@ -234,38 +283,29 @@ function CheckEventsPanel() {
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
<div className="grid grid-cols-2 gap-3">
|
||||
|
||||
{/* Advanced */}
|
||||
<div className="grid grid-cols-3 gap-3">
|
||||
<label className="flex flex-col gap-1">
|
||||
<span className="text-xs text-slate-400">News impact min</span>
|
||||
<input type="number" step="0.05" min="0" max="1"
|
||||
value={config.news_impact_min}
|
||||
onChange={e => setConfig(c => ({ ...c, news_impact_min: +e.target.value }))}
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-sm w-full"
|
||||
/>
|
||||
</label>
|
||||
<label className="flex flex-col gap-1">
|
||||
<span className="text-xs text-slate-400">News lookback (h)</span>
|
||||
<input type="number" step="12" min="6" max="168"
|
||||
value={config.news_lookback_hours}
|
||||
onChange={e => setConfig(c => ({ ...c, news_lookback_hours: +e.target.value }))}
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-sm w-full"
|
||||
/>
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-sm w-full" />
|
||||
</label>
|
||||
<label className="flex flex-col gap-1">
|
||||
<span className="text-xs text-slate-400">Éco z-score min</span>
|
||||
<input type="number" step="0.25" min="0.5" max="5"
|
||||
value={config.eco_z_threshold}
|
||||
onChange={e => setConfig(c => ({ ...c, eco_z_threshold: +e.target.value }))}
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-sm w-full"
|
||||
/>
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-sm w-full" />
|
||||
</label>
|
||||
<label className="flex flex-col gap-1">
|
||||
<span className="text-xs text-slate-400">Report importance min</span>
|
||||
<input type="number" step="1" min="1" max="5"
|
||||
value={config.report_min_importance}
|
||||
onChange={e => setConfig(c => ({ ...c, report_min_importance: +e.target.value }))}
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-sm w-full"
|
||||
/>
|
||||
className="bg-dark-900 border border-slate-700 rounded px-2 py-1 text-slate-200 text-sm w-full" />
|
||||
</label>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -31,6 +31,7 @@ interface LinePoint { time: string; value: number }
|
||||
|
||||
interface SnapshotEvent {
|
||||
id?: number; template_id?: number | null
|
||||
analyzed_instruments?: string | null // comma-sep: "EURUSD,SP500" — set when causal analysis exists
|
||||
date: string; end_date: string | null; title: string; level: string
|
||||
category: string; sub_type?: string; description: string; impact_score: number
|
||||
expected_value?: string | null; actual_value?: string | null
|
||||
@@ -686,11 +687,12 @@ function EventTimeline({
|
||||
return () => obs.disconnect()
|
||||
}, [])
|
||||
|
||||
// Only events that have a causal graph linked to this instrument
|
||||
// Only events that have an instantiated analysis for this instrument
|
||||
// Uses analyzed_instruments (actual DB analyses) — not template.instruments (theoretical)
|
||||
const linked = events.filter(ev => {
|
||||
if (!ev.template_id) return false
|
||||
const tmpl = templates.find(t => t.id === ev.template_id)
|
||||
return tmpl != null && causalInsts.some(ci => tmpl.instruments.includes(ci))
|
||||
if (!ev.analyzed_instruments) return false
|
||||
const insts = ev.analyzed_instruments.split(',')
|
||||
return causalInsts.some(ci => insts.includes(ci))
|
||||
})
|
||||
|
||||
if (!priceData.length || !linked.length) {
|
||||
@@ -781,11 +783,11 @@ function EventGraphCards({
|
||||
}) {
|
||||
const navigate = useNavigate()
|
||||
|
||||
// Events that have a causal graph template touching this instrument
|
||||
// Events that have an instantiated causal analysis for this instrument
|
||||
const linkedEvents = events.filter(ev => {
|
||||
if (!ev.template_id) return false
|
||||
const tmpl = templates.find(t => t.id === ev.template_id)
|
||||
return tmpl != null && causalInsts.some(ci => tmpl.instruments.includes(ci))
|
||||
if (!ev.analyzed_instruments) return false
|
||||
const insts = ev.analyzed_instruments.split(',')
|
||||
return causalInsts.some(ci => insts.includes(ci))
|
||||
})
|
||||
|
||||
// Unique templates from those linked events
|
||||
|
||||
@@ -335,8 +335,11 @@ function EventDetail({
|
||||
const [selTmpl, setSelTmpl] = useState(0)
|
||||
const [instrument, setInstrument] = useState('EURUSD')
|
||||
const [loadingRec, setLoadingRec] = useState(false)
|
||||
const [loadingInst, setLoadingInst] = useState(false)
|
||||
const [loadingAn, setLoadingAn] = useState(false)
|
||||
const [recMsg, setRecMsg] = useState<string | null>(null)
|
||||
const [instInputs, setInstInputs] = useState<Record<string, number>>({})
|
||||
const [instMsg, setInstMsg] = useState<string | null>(null)
|
||||
const [anResult, setAnResult] = useState<{ score: number | null; preds: Record<string, number> } | null>(null)
|
||||
|
||||
const loadDetail = useCallback(async () => {
|
||||
@@ -409,8 +412,24 @@ function EventDetail({
|
||||
onClose()
|
||||
}
|
||||
|
||||
const instantiate = async (tmplId: number) => {
|
||||
if (!tmplId) return
|
||||
setLoadingInst(true); setInstMsg(null); setInstInputs({})
|
||||
try {
|
||||
const r = await fetch('/api/causal-lab/instantiate', {
|
||||
method: 'POST', headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ market_event_id: detail.id, template_id: tmplId }),
|
||||
})
|
||||
const d = await r.json()
|
||||
if (!r.ok) throw new Error(d.detail || r.statusText)
|
||||
setInstInputs(d.inputs || {})
|
||||
setInstMsg(d.rationale || null)
|
||||
} catch (e: any) { setInstMsg(`✗ ${(e as any).message}`) }
|
||||
finally { setLoadingInst(false) }
|
||||
}
|
||||
|
||||
const recommendTemplate = async () => {
|
||||
setLoadingRec(true); setRecMsg(null); setAnResult(null)
|
||||
setLoadingRec(true); setRecMsg(null); setAnResult(null); setInstInputs({}); setInstMsg(null)
|
||||
try {
|
||||
const r = await fetch('/api/causal-lab/recommend', {
|
||||
method: 'POST', headers: { 'Content-Type': 'application/json' },
|
||||
@@ -422,10 +441,11 @@ function EventDetail({
|
||||
if (rec?.template_id) {
|
||||
setSelTmpl(rec.template_id)
|
||||
setRecMsg(`✓ ${rec.template_name}${rec.confidence ? ` (${Math.round(rec.confidence * 100)}%)` : ''}`)
|
||||
await instantiate(rec.template_id)
|
||||
} else {
|
||||
setRecMsg('Aucun template correspondant — créez-en un dans l\'Editeur')
|
||||
setRecMsg('Aucun template — créez-en un dans l\'Editeur')
|
||||
}
|
||||
} catch (e: any) { setRecMsg(`✗ ${e.message}`) }
|
||||
} catch (e: any) { setRecMsg(`✗ ${(e as any).message}`) }
|
||||
finally { setLoadingRec(false) }
|
||||
}
|
||||
|
||||
@@ -435,13 +455,13 @@ function EventDetail({
|
||||
try {
|
||||
const r = await fetch('/api/causal-lab/analyze', {
|
||||
method: 'POST', headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ market_event_id: detail.id, template_id: selTmpl, instrument, inputs: {}, coef_overrides: {} }),
|
||||
body: JSON.stringify({ market_event_id: detail.id, template_id: selTmpl, instrument, inputs: instInputs, coef_overrides: {} }),
|
||||
})
|
||||
const d = await r.json()
|
||||
if (!r.ok) throw new Error(d.detail || r.statusText)
|
||||
setAnResult({ score: d.activation?.score ?? null, preds: d.node_values ?? {} })
|
||||
await loadAnalyses()
|
||||
} catch (e: any) { setAnResult({ score: null, preds: { error: -1 } }) }
|
||||
} catch (e: any) { setAnResult({ score: null, preds: {} }) }
|
||||
finally { setLoadingAn(false) }
|
||||
}
|
||||
|
||||
@@ -738,6 +758,37 @@ function EventDetail({
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Instantiation status + inputs preview */}
|
||||
{selTmpl > 0 && (
|
||||
<div className="space-y-1">
|
||||
<div className="flex items-center gap-2">
|
||||
<button
|
||||
onClick={() => instantiate(selTmpl)}
|
||||
disabled={loadingInst}
|
||||
className="flex items-center gap-1 text-xs text-slate-500 hover:text-purple-400 disabled:opacity-50 transition-colors"
|
||||
>
|
||||
{loadingInst ? <Loader2 size={9} className="animate-spin" /> : <Sparkles size={9} />}
|
||||
{loadingInst ? 'Calibration IA…' : 'Calibrer (IA)'}
|
||||
</button>
|
||||
{instMsg && !instMsg.startsWith('✗') && (
|
||||
<span className="text-xs text-slate-600 truncate">{instMsg}</span>
|
||||
)}
|
||||
</div>
|
||||
{Object.keys(instInputs).length > 0 && (
|
||||
<div className="flex flex-wrap gap-1.5">
|
||||
{Object.entries(instInputs).map(([k, v]) => (
|
||||
<span key={k} className={clsx(
|
||||
'text-xs font-mono px-1.5 py-0.5 rounded border',
|
||||
v > 0 ? 'text-emerald-400 border-emerald-800/50 bg-emerald-900/20' : v < 0 ? 'text-red-400 border-red-800/50 bg-red-900/20' : 'text-slate-500 border-slate-700/50'
|
||||
)}>
|
||||
{k}: {v > 0 ? '+' : ''}{v.toFixed(2)}
|
||||
</span>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Instrument + analyze */}
|
||||
<div className="flex gap-1.5">
|
||||
<select
|
||||
|
||||
Reference in New Issue
Block a user