51 lines
2.0 KiB
Python
51 lines
2.0 KiB
Python
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"""Multi-path inference: parallel hypothesis generation and scoring."""
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from __future__ import annotations
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from typing import Any, Callable
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from fusionagi.schemas.atomic import AtomicSemanticUnit
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from fusionagi.reasoning.tot import ThoughtNode
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from fusionagi._logger import logger
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def _score_coherence(node: ThoughtNode, _units: list[AtomicSemanticUnit]) -> float:
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return node.score * (0.9 + 0.1 * min(1, len(node.trace) / 5))
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def _score_consistency(node: ThoughtNode, units: list[AtomicSemanticUnit]) -> float:
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if not units:
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return 0.5
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unit_content = " ".join(u.content.lower() for u in units)
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thought_words = set(node.thought.lower().split())
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unit_words = set(unit_content.split())
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overlap = len(thought_words & unit_words) / max(len(thought_words), 1)
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return min(1.0, overlap * 2)
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def generate_and_score_parallel(
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hypotheses: list[str],
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units: list[AtomicSemanticUnit],
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score_fn: Callable[[ThoughtNode, list[AtomicSemanticUnit]], float] | None = None,
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) -> list[tuple[ThoughtNode, float]]:
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"""Score multiple hypotheses in parallel."""
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score_fn = score_fn or (lambda n, u: _score_coherence(n, u) * 0.5 + _score_consistency(n, u) * 0.5)
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def score_one(h: str, i: int) -> tuple[ThoughtNode, float]:
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node = ThoughtNode(thought=h, trace=[h], unit_refs=[u.unit_id for u in units[:10]])
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s = score_fn(node, units)
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node.score = s
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return node, s
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results: list[tuple[ThoughtNode, float]] = []
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with ThreadPoolExecutor(max_workers=min(len(hypotheses), 8)) as ex:
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futures = {ex.submit(score_one, h, i): i for i, h in enumerate(hypotheses)}
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for future in as_completed(futures):
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try:
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node, score = future.result()
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results.append((node, score))
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except Exception as e:
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logger.warning("Multi-path score failed", extra={"error": str(e)})
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return results
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