core/session/context.py
Shay a6be96410c fix(session): CGA-only hemisphere consistency, remove forbidden Euclidean metric
_orient_result_to_anchor used np.dot (Euclidean dot product) alongside
cga_inner to decide hemisphere flips.  When CGA inner was positive
(correct hemisphere) but Euclidean was negative, the flip negated CGA
alignment — making correctly-oriented fields rank last in vault recall.

Changes:
- Move hemisphere check into finalize_turn so all paths (ChatRuntime,
  SessionContext.respond) get consistent protection.
- Use CGA inner product only, removing the forbidden Euclidean metric.
- Remove _orient_result_to_anchor (subsumed by finalize_turn).
- Remove SessionContext.arespond (dead code, no callers).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-05-15 21:51:16 -07:00

252 lines
11 KiB
Python

"""
SessionContext — binds field, vault, vocab, persona, referents, and graph.
The ingest path is split into a non-mutating probe and a committing ingest so
runtime gates can inspect the candidate field before durable vault writes. All
response paths finalize through one graph/vault/session-state method.
"""
from __future__ import annotations
import numpy as np
from algebra.backend import cga_inner, versor_apply
from algebra.versor import versor_condition as _versor_condition
from field.state import FieldState
from generate.dialogue import DialogueTurn
from generate.proposition import Proposition
from generate.result import GenerationResult
from generate.stream import generate
from ingest.gate import inject
from persona.motor import PersonaMotor
from session.graph import SessionGraph
from session.referents import ReferentRegistry
from vault.store import VaultStore
class SessionContext:
def __init__(self, vocab, persona=None, vault=None, vault_reproject_interval: int = 100):
self.vocab = vocab
self.persona = persona or PersonaMotor.identity()
self.vault = vault or VaultStore(reproject_interval=vault_reproject_interval)
self.state: FieldState | None = None
self.turn: int = 0
self.graph: SessionGraph = SessionGraph()
self.referents: ReferentRegistry = ReferentRegistry()
self.running_dialogue_blade: np.ndarray | None = None
self._last_response_tokens: tuple[str, ...] | None = None
self._anchor_field: np.ndarray | None = None
self._dialogue_history_compat: list[DialogueTurn] = []
self._last_input_tokens: tuple[str, ...] = ()
self._last_resolved_input_tokens: tuple[str, ...] = ()
self._last_input_versor: np.ndarray | None = None
@property
def dialogue_history(self) -> list[DialogueTurn]:
return self._dialogue_history_compat
@property
def last_input_tokens(self) -> tuple[str, ...]:
return self._last_input_tokens
@property
def last_resolved_input_tokens(self) -> tuple[str, ...]:
return self._last_resolved_input_tokens
def _field_from_tokens(self, tokens: list[str], *, resolve_referents: bool) -> tuple[FieldState, list[str]]:
resolved_tokens = self.referents.resolve(tokens) if resolve_referents else list(tokens)
injected = inject(resolved_tokens, self.vocab)
anchor_token = resolved_tokens[0] if resolved_tokens else (tokens[0] if tokens else "")
try:
node_idx = self.vocab.index_of(anchor_token)
except (KeyError, IndexError):
node_idx = self.vocab.index_of(tokens[0]) if tokens else 0
if self.state is None:
candidate = FieldState(
F=injected.F,
node=node_idx,
step=injected.step,
holonomy=injected.holonomy,
energy=injected.energy,
valence=injected.valence,
)
else:
composed_F = versor_apply(injected.F, self.state.F)
condition = _versor_condition(composed_F)
if condition > 1e-2:
raise RuntimeError(
f"Cross-turn field composition violated versor condition: {condition:.3e}"
)
candidate = FieldState(
F=composed_F,
node=node_idx,
step=self.state.step + 1,
holonomy=injected.holonomy,
energy=injected.energy,
valence=injected.valence,
)
return candidate, resolved_tokens
def probe_ingest(self, tokens: list[str]) -> FieldState:
"""Build the candidate ingest field without mutating state or vault."""
snapshot_sources = self.referents.consumed_turns()
snapshot_slots = self.referents.consumed_slots()
candidate, _ = self._field_from_tokens(tokens, resolve_referents=True)
# Restore consumed metadata because probe must not define graph edges.
self.referents._last_resolved_sources = snapshot_sources # internal rollback by design
self.referents._last_resolved_slots = snapshot_slots
return candidate
def commit_ingest(self, tokens: list[str]) -> FieldState:
"""Resolve, inject, mutate live state, and store the user field."""
field_state, resolved_tokens = self._field_from_tokens(tokens, resolve_referents=True)
self.state = field_state
if self._anchor_field is None:
self._anchor_field = field_state.F.copy()
self._last_input_tokens = tuple(tokens)
self._last_resolved_input_tokens = tuple(resolved_tokens)
self._last_input_versor = field_state.F.copy()
self.vault.store(field_state.F, {"turn": self.turn, "role": "user"})
return field_state
def ingest(self, tokens: list[str]) -> FieldState:
"""Backward-compatible committing ingest."""
return self.commit_ingest(tokens)
def record_dialogue(self, proposition: Proposition) -> DialogueTurn:
from generate.dialogue import DialogueTurn as _DT
blade = proposition.relation
turn = _DT(proposition=proposition, outer_product_blade=blade)
self._dialogue_history_compat.append(turn)
if self.running_dialogue_blade is None:
self.running_dialogue_blade = blade.copy()
else:
alpha = cga_inner(self.running_dialogue_blade, blade)
sign = 1.0 if alpha >= 0.0 else -1.0
self.running_dialogue_blade = sign * blade
return turn
@property
def last_dialogue_blade(self) -> np.ndarray | None:
if not self._dialogue_history_compat:
return None
return self._dialogue_history_compat[-1].outer_product_blade.copy()
def _register_result_referent(self, result: GenerationResult) -> None:
if not result.tokens:
return
versors: dict[str, np.ndarray] = {}
for tok in result.tokens:
try:
versors[tok] = self.vocab.get_versor(tok)
except KeyError:
pass
self.referents.register_from_tokens(result.tokens, versors, turn=self.turn)
def _hemisphere_consistent_field(self, field_state: FieldState) -> FieldState:
"""Ensure field stays in the same CGA hemisphere as the session anchor."""
if self._anchor_field is None:
return field_state
if cga_inner(field_state.F, self._anchor_field) >= 0.0:
return field_state
return FieldState(
F=-field_state.F,
node=field_state.node,
step=field_state.step,
holonomy=field_state.holonomy,
energy=field_state.energy,
valence=field_state.valence,
)
def finalize_turn(
self,
result: GenerationResult,
*,
tokens_in: tuple[str, ...] | None = None,
dialogue_role: str = "assert",
input_versor: np.ndarray | None = None,
metadata: dict | None = None,
) -> None:
"""Finalize assistant output into referents, graph, vault, and state."""
if self.state is None and input_versor is None:
raise AssertionError("Call ingest() before finalize_turn().")
input_F = (
np.asarray(input_versor, dtype=np.float32).copy()
if input_versor is not None
else (self._last_input_versor.copy() if self._last_input_versor is not None else self.state.F.copy())
)
turn_tokens = tuple(tokens_in if tokens_in is not None else self._last_input_tokens)
backward_edges = self.referents.consumed_turns()
active_slots = self.referents.active_slots()
self._register_result_referent(result)
active_slots = self.referents.active_slots() | active_slots
oriented_state = self._hemisphere_consistent_field(result.final_state)
self.graph.add_turn(
turn_idx=self.turn,
input_versor=input_F,
output_versor=oriented_state.F,
tokens_in=turn_tokens,
tokens_out=tuple(result.tokens or []),
dialogue_role=dialogue_role,
referent_slots=active_slots,
backward_edges=backward_edges,
)
self.state = oriented_state
payload = {"turn": self.turn, "role": "assistant"}
if metadata:
payload.update(metadata)
self.vault.store(oriented_state.F, payload)
self.turn += 1
self._last_response_tokens = result.tokens
def apply_corrected_outputs(self, records) -> None:
"""Synchronize corrected graph records into live session recall surfaces."""
for record in records:
self.vault.store(
record.new_versor,
{"turn": record.turn_idx, "role": "assistant", "corrected": True},
)
self.referents.update_turn_versor(record.turn_idx, record.new_versor)
if records:
last = max(records, key=lambda r: r.turn_idx)
if self.state is not None:
self.state = FieldState(
F=last.new_versor,
node=self.state.node,
step=self.state.step,
holonomy=self.state.holonomy,
energy=self.state.energy,
valence=self.state.valence,
)
def respond(self, max_tokens: int = 128) -> GenerationResult:
assert self.state is not None, "Call ingest() before respond()."
input_versor = self._last_input_versor.copy() if self._last_input_versor is not None else self.state.F.copy()
result = generate(self.state, self.vocab, self.persona, max_tokens, vault=self.vault)
if self._last_response_tokens is not None and result.tokens == self._last_response_tokens and result.tokens:
try:
pivot_node = self.vocab.index_of(result.tokens[0])
except KeyError:
pivot_node = self.state.node
if pivot_node != self.state.node:
pivot = FieldState(
F=self.state.F,
node=pivot_node,
step=self.state.step,
holonomy=self.state.holonomy,
energy=self.state.energy,
valence=self.state.valence,
)
result = generate(pivot, self.vocab, self.persona, max_tokens, vault=self.vault)
self.finalize_turn(result, input_versor=input_versor, dialogue_role="assert")
return result
def recall(self, query_tokens: list, top_k: int = 5) -> list:
query_state = inject(query_tokens, self.vocab)
return self.vault.recall(query_state.F, top_k=top_k)