87b0eda345
Implements the PropositionGraph epistemic carrier (ADR-0144): recognition/carrier.py — EpistemicTransition, EpistemicNode, EpistemicGraph. Frozen, JSON-serializable, byte-deterministic. EpistemicNode wraps a RecognitionOutcome with an append-only provenance chain; epistemic_state property tracks last transition's to_state or outcome.state when empty. recognition/connector.py — epistemic_node_to_graph_node(). Maps an admitted EpistemicNode's FeatureBundle (agent/relation/count/unit) to a GraphNode for the generation-side articulation planner. CognitiveTurnPipeline gains a recognizer: DerivedRecognizer | None param (default None — all existing callers unaffected). When attached, run() calls recognize() at the top of every turn and wraps admitted outcomes in an EpistemicGraph. CognitiveTurnResult.epistemic_graph carries it. RuntimeConfig.recognition_grounded_graph: bool = False — opt-in flag that replaces the intent-derived PropositionGraph with one derived from the admitted EpistemicNode via the connector. RatificationOutcome gains three specific PASSTHROUGH sub-values (PASSTHROUGH_NO_FIELD / NO_VOCAB / NO_VERSOR) for _ratify_intent observability (ADR-0142 debt 1). All normalise to "passthrough" before trace_hash so pre-ADR-0144 hashes are byte-identical. 24/24 acceptance tests pass; 67/67 smoke tests pass; no regressions.
66 lines
2.1 KiB
Python
66 lines
2.1 KiB
Python
"""Connector: EpistemicNode → GraphNode — ADR-0144.
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Maps an admitted EpistemicNode's FeatureBundle to a generation-side
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GraphNode so the recognition path can feed the articulation planner.
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The v1 mapping covers has-relation feature bundles (agent, relation,
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count, unit). New proposition types extend the mapping here; unknown
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feature layouts raise ValueError so gaps surface explicitly rather than
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silently defaulting.
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"""
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from __future__ import annotations
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from generate.graph_planner import GraphNode
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from generate.intent import IntentTag
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from recognition.carrier import EpistemicNode
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from recognition.outcome import EVIDENCED
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def epistemic_node_to_graph_node(
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node: EpistemicNode,
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*,
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source_intent: IntentTag,
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node_id: str | None = None,
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) -> GraphNode:
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"""Derive a generation-side GraphNode from an admitted EpistemicNode.
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Raises ``ValueError`` if ``node.recognition_outcome.state != EVIDENCED``.
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Feature-bundle → GraphNode mapping (v1, has-relation propositions):
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subject ← bundle["agent"].value
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predicate ← bundle["relation"].value
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obj ← "{count.value} {unit.value}"
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"""
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outcome = node.recognition_outcome
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if outcome.state != EVIDENCED:
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raise ValueError(
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f"Cannot derive GraphNode from non-EVIDENCED EpistemicNode: "
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f"state={outcome.state!r}"
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)
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bundle = outcome.proposition
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assert bundle is not None # invariant: EVIDENCED → proposition not None
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agent = bundle.get("agent")
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relation = bundle.get("relation")
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count = bundle.get("count")
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unit = bundle.get("unit")
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subject = str(agent.value) if agent is not None else "<unknown-agent>"
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predicate = str(relation.value) if relation is not None else "has"
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obj = (
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f"{count.value} {unit.value}"
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if count is not None and unit is not None
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else "<pending>"
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)
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return GraphNode(
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node_id=node_id or node.node_id,
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subject=subject,
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predicate=predicate,
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obj=obj,
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source_intent=source_intent,
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)
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__all__ = ["epistemic_node_to_graph_node"]
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