Ui^&dZddlmZddlZddlmZddlmZmZm Z m Z m Z ddl m Z mZmZddlmZej$d ZGd d Zy) aRLM Neo-Cortex -- Surprise Integration. Wraps core.surprise_memory.MemorySystem (v2.0.0, 585 lines) into the Gateway's tier-routing pipeline. Does NOT rebuild surprise scoring -- bridges it with tier-awareness, write gating, batch scoring, and statistics reporting. Public API: score_content(content, source, domain) -> (float, MemoryTier) score_content_for_tier(content, source, domain, tier) -> (float, MemoryTier) register_prediction(domain, expected, confidence) -> str resolve_prediction(prediction_id, actual_outcome) -> (float, MemoryTier) score_batch(items) -> list[(float, MemoryTier)] get_stats() -> dict get_score_distribution() -> dict ) annotationsN) defaultdict)AnyDictListOptionalTuple) CustomerTier MemoryTierSurpriseIntegrationProtocol)get_thresholdszcore.rlm.surpriseceZdZUdZddddZded<ddd Z dd Z dd Z d dd Z dd Z ddZ ddZ ddZ e ddZy)SurpriseIntegrationawBridges existing surprise engine to Gateway tier routing. Wraps :class:`core.surprise_memory.MemorySystem` and adds: - Tier-aware threshold routing (different tiers have different sensitivity) - Write gating (below discard threshold = memory not stored) - Batch scoring for nightly consolidation - Statistics and score distribution reporting g333333?g?g?)discardworkingepisodicDict[str, float]TIER_THRESHOLDSNcbddlm}|||_g|_tj dy)zInitialize wrapper around existing MemorySystem. Args: persistence_path: Optional path for surprise history persistence. Forwarded to the underlying MemorySystem constructor. r) MemorySystemz*>? ""E6?3d{r!c|jj|||}|dd}t|j}|j ||}|j j ||f||fS)aEScore content with tier-adjusted thresholds. The raw surprise score is identical regardless of tier -- only the classification thresholds change. Enterprise/Queen tiers have lower discard thresholds (capture more), while Starter has a higher discard threshold (more selective). Args: content: The text content to evaluate. source: Origin of the content. domain: Domain category. tier: Customer subscription tier. Returns: Tuple of (composite_score, MemoryTier). r#r$)rr%rvaluer&rr') rr(r)r*r,r+r# thresholds memory_tiers rscore_content_for_tierz*SurpriseIntegration.score_content_for_tier[sn.&&w?w 12#DJJ/ ))%<  ""E6?3k!!r!c<|jj|||S)aRegister a prediction for later surprise resolution. Forwards to the underlying engine's make_prediction(). Args: domain: Domain context for the prediction. expected: The expected outcome string. confidence: Confidence level (0-1) in the prediction. Returns: prediction_id string for later resolution. )rmake_prediction)rr*expected confidences rregister_predictionz'SurpriseIntegration.register_prediction}s||++FHjIIr!c|jj||\}}|j}|j||j}|j j |df||fS)a Resolve a prediction and return surprise-based tier routing. Args: prediction_id: ID returned by register_prediction(). actual_outcome: What actually happened. Returns: Tuple of (error_score, MemoryTier). prediction)rresolve_predictiontotalr&rrr')r prediction_idactual_outcome error_scoresurprise_scorer#r,s rr:z&SurpriseIntegration.resolve_predictionsj'+ll&E&E >' # ^$$""5$*>*>? ""E<#89d{r!c 2|sgShd}g}t|D]~\}}|t|jz }|r)td|ddj t ||j |d|d|d\}}|j||f|S)aqScore multiple items efficiently. Each item dict must contain keys: content, source, domain. Args: items: List of dicts, each with 'content', 'source', 'domain'. Returns: List of (score, MemoryTier) tuples in same order as input. Raises: ValueError: If any item is missing a required key. >r*r)r(zItem at index z missing required key(s): z, r(r)r*) enumeratesetkeys ValueErrorjoinsortedr-r') ritems required_keysresultsidxitemmissingr#r,s r score_batchzSurpriseIntegration.score_batchs I7 24"5) *IC#c$))+&66G $SE)Cyy124,,YhhKE4 NNE4= ) *r!c6|jjS)zReturn surprise engine statistics including domain baselines. Returns: Dict with keys: total_events, avg_surprise, domains, level_distribution, active_predictions. )r get_stats)rs rrOzSurpriseIntegration.get_statss||%%''r!ctt}tD]}d||j<|jD]8\}}|j ||j }||jxxdz cc<:t|S)aReturn distribution of scores across MemoryTier values. Uses the internal score history to compute how many scores fell into each tier bucket using default thresholds. Returns: Dict mapping MemoryTier value strings to counts. rr )rintr r/rr&rdict)r distributiontier_valr#_r,s rget_score_distributionz*SurpriseIntegration.get_score_distributions(33'7 " -H+,L ( -++ *HE1&&ud.B.BCD  $ ) $ *L!!r!c||dkrtjS||dkrtjS||dkrtjStjS)aClassify a surprise score into a MemoryTier. Boundary rules: score < discard threshold -> DISCARD discard <= score < working -> WORKING working <= score < episodic -> EPISODIC score >= episodic -> SEMANTIC Args: score: The composite surprise score (0-1). thresholds: Dict with keys 'discard', 'working', 'episodic'. Returns: The appropriate MemoryTier. rrr)r DISCARDWORKINGEPISODICSEMANTIC)r#r0s rr&z"SurpriseIntegration._classify_tiers[& :i( (%% % Z * *%% % Z + +&& &&& &r!)N)rz Optional[str]returnNone)r(strr)r^r*r^r\Tuple[float, MemoryTier]) r(r^r)r^r*r^r,r r\r_)gffffff?)r*r^r5r^r6floatr\r^)r<r^r=r^r\r_)rGzList[Dict[str, Any]]r\zList[Tuple[float, MemoryTier]])r\zDict[str, Any])r\zDict[str, int])r#r`r0rr\r )__name__ __module__ __qualname____doc__r__annotations__r r-r2r7r:rMrOrV staticmethodr&r!rrrs)O% T"$'14 !4""" "  " " "F?BJJ%(J6;J J" 25 !0")" '"P(".''"2' ''r!r)rd __future__rlogging collectionsrtypingrrrrr contractsr r r surprise_configr getLoggerrrrgr!rrosC ##33LL+   . /k'k'r!