feat: competitive intelligence & historical pattern matching layer

services/shared/config.py

@@ -110,6 +110,19 @@ BUCKET_RETENTION_FIELDS: dict[str, str] = {
 }
 
 
+@dataclass
+class MacroConfig:
+    """Configuration for the macro news interpolation layer.
+
+    Requirements: 5.6, 10.1, 10.2, 12.9
+    """
+    macro_signal_weight: float = 0.3  # relative weight of macro vs company signals
+    macro_enabled: bool = True  # runtime toggle state (default on)
+    macro_confidence_threshold: float = 0.4  # minimum confidence for event inclusion
+    macro_short_term_staleness_hours: int = 48  # hours after which short-term events get accelerated decay
+    projection_confidence_threshold: float = 0.3  # minimum confidence for projections to influence recommendations
+
+
 @dataclass
 class AlertingConfig:
     """Thresholds for operational alerting rules.
@@ -135,6 +148,26 @@ class AlertingConfig:
     check_interval_seconds: int = 120
 
 
+@dataclass
+class CompetitiveConfig:
+    """Configuration for the competitive intelligence & historical pattern matching layer.
+
+    Requirements: 5.6, 6.1, 9.1, 9.2, 11.2, 11.3
+    """
+    competitive_signal_weight: float = 0.2
+    competitive_enabled: bool = True
+    pattern_confidence_threshold: float = 0.3
+    propagation_strength_threshold: float = 0.2
+    routine_lookback_days: int = 180
+    major_decision_lookback_days: int = 365
+    major_decision_weight_multiplier: float = 1.3
+    staleness_window_days: int = 180
+    staleness_recent_days: int = 90
+    staleness_decay_penalty: float = 0.5
+    min_pattern_samples: int = 3
+    propagation_failure_threshold: int = 5  # consecutive failures before operator alert
+
+
 @dataclass
 class AppConfig:
     postgres: PostgresConfig = field(default_factory=PostgresConfig)
@@ -146,6 +179,8 @@ class AppConfig:
     broker: BrokerConfig = field(default_factory=BrokerConfig)
     retention: RetentionConfig = field(default_factory=RetentionConfig)
     alerting: AlertingConfig = field(default_factory=AlertingConfig)
+    macro: MacroConfig = field(default_factory=MacroConfig)
+    competitive: CompetitiveConfig = field(default_factory=CompetitiveConfig)
     log_level: str = "INFO"
     json_logs: bool = True
 
@@ -222,6 +257,27 @@ def load_config() -> AppConfig:
             broker_error_window_hours=int(os.getenv("ALERT_BROKER_ERROR_WINDOW_HOURS", "1")),
             check_interval_seconds=int(os.getenv("ALERT_CHECK_INTERVAL_SECONDS", "120")),
         ),
+        macro=MacroConfig(
+            macro_signal_weight=float(os.getenv("MACRO_SIGNAL_WEIGHT", "0.3")),
+            macro_enabled=os.getenv("MACRO_ENABLED", "true").lower() == "true",
+            macro_confidence_threshold=float(os.getenv("MACRO_CONFIDENCE_THRESHOLD", "0.4")),
+            macro_short_term_staleness_hours=int(os.getenv("MACRO_SHORT_TERM_STALENESS_HOURS", "48")),
+            projection_confidence_threshold=float(os.getenv("PROJECTION_CONFIDENCE_THRESHOLD", "0.3")),
+        ),
+        competitive=CompetitiveConfig(
+            competitive_signal_weight=float(os.getenv("COMPETITIVE_SIGNAL_WEIGHT", "0.2")),
+            competitive_enabled=os.getenv("COMPETITIVE_ENABLED", "true").lower() == "true",
+            pattern_confidence_threshold=float(os.getenv("COMPETITIVE_PATTERN_CONFIDENCE_THRESHOLD", "0.3")),
+            propagation_strength_threshold=float(os.getenv("COMPETITIVE_PROPAGATION_STRENGTH_THRESHOLD", "0.2")),
+            routine_lookback_days=int(os.getenv("COMPETITIVE_ROUTINE_LOOKBACK_DAYS", "180")),
+            major_decision_lookback_days=int(os.getenv("COMPETITIVE_MAJOR_DECISION_LOOKBACK_DAYS", "365")),
+            major_decision_weight_multiplier=float(os.getenv("COMPETITIVE_MAJOR_DECISION_WEIGHT_MULTIPLIER", "1.3")),
+            staleness_window_days=int(os.getenv("COMPETITIVE_STALENESS_WINDOW_DAYS", "180")),
+            staleness_recent_days=int(os.getenv("COMPETITIVE_STALENESS_RECENT_DAYS", "90")),
+            staleness_decay_penalty=float(os.getenv("COMPETITIVE_STALENESS_DECAY_PENALTY", "0.5")),
+            min_pattern_samples=int(os.getenv("COMPETITIVE_MIN_PATTERN_SAMPLES", "3")),
+            propagation_failure_threshold=int(os.getenv("COMPETITIVE_PROPAGATION_FAILURE_THRESHOLD", "5")),
+        ),
         log_level=os.getenv("LOG_LEVEL", "INFO"),
         json_logs=os.getenv("JSON_LOGS", "true").lower() == "true",
     )