445865e429
Some checks failed
- Integrate GPU scoring inline into reasoning/multi_path.py (auto-uses GPU when available) - Integrate GPU deduplication into multi_agent/consensus_engine.py - Add semantic_search() method to memory/semantic_graph.py with GPU acceleration - Integrate GPU training into self_improvement/training.py AutoTrainer - Fix all 758 ruff lint issues (whitespace, import sorting, unused imports, ambiguous vars, undefined names) - Fix all 40 mypy type errors across the codebase (no-any-return, union-attr, arg-type, etc.) - Fix deprecated ruff config keys (select/ignore -> [tool.ruff.lint]) - Add .dockerignore to exclude .venv/, tests/, docs/ from Docker builds - Add type hints and docstrings to verification/outcome.py - Fix E402 import ordering in witness_agent.py - Fix F821 undefined names in vector_pgvector.py and native.py - Fix E741 ambiguous variable names in reflective.py and recommender.py All 276 tests pass. 0 ruff errors. 0 mypy errors. Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
84 lines
2.6 KiB
Python
84 lines
2.6 KiB
Python
"""Meta-reasoning: challenge assumptions, detect contradictions, revisit nodes."""
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from __future__ import annotations
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from fusionagi._logger import logger
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from fusionagi.reasoning.tot import ThoughtNode, expand_node
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from fusionagi.schemas.atomic import AtomicSemanticUnit, AtomicUnitType
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def challenge_assumptions(
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units: list[AtomicSemanticUnit],
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current_conclusion: str,
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) -> list[str]:
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"""
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Identify and flag assumptions in units that support the conclusion.
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"""
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flagged: list[str] = []
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conclusion_lower = current_conclusion.lower()
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for u in units:
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if u.type == AtomicUnitType.ASSUMPTION:
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flagged.append(u.content)
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elif "assume" in u.content.lower() or "assumption" in u.content.lower():
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flagged.append(u.content)
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elif u.type == AtomicUnitType.CONSTRAINT:
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if any(w in conclusion_lower for w in ["must", "should", "require"]):
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flagged.append(f"Constraint may be assumed: {u.content[:100]}")
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logger.debug("Assumptions flagged", extra={"count": len(flagged)})
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return flagged
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def detect_contradictions(
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units: list[AtomicSemanticUnit],
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) -> list[tuple[str, str]]:
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"""
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Find conflicting units (heuristic: negation mismatch, same subject).
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"""
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neg_words = {"not", "no", "never", "none", "cannot", "shouldn't", "won't", "don't", "doesn't"}
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pairs: list[tuple[str, str]] = []
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for i, a in enumerate(units):
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wa = set(a.content.lower().split())
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for b in units[i + 1:]:
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wb = set(b.content.lower().split())
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a_neg = bool(wa & neg_words)
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b_neg = bool(wb & neg_words)
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if a_neg != b_neg:
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overlap = len(wa & wb) / max(len(wa), 1)
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if overlap > 0.2:
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pairs.append((a.unit_id, b.unit_id))
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logger.debug("Contradictions detected", extra={"count": len(pairs)})
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return pairs
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def revisit_node(
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tree: ThoughtNode | None,
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node_id: str,
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new_evidence: str,
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) -> ThoughtNode | None:
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"""
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Re-expand a node when new evidence arrives.
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Creates a new child with the new evidence.
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"""
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if tree is None:
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return None
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def find_node(n: ThoughtNode) -> ThoughtNode | None:
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if n.node_id == node_id:
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return n
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for c in n.children:
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found = find_node(c)
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if found:
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return found
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return None
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node = find_node(tree)
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if not node:
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return tree
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child = expand_node(node, new_evidence)
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child.metadata["revisit_evidence"] = new_evidence[:200]
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return tree
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