src/pqc_reasoning_ledger/step.py
| 1 | """ReasoningStep - one hash-chained unit of thought.""" |
| 2 | |
| 3 | from __future__ import annotations |
| 4 | |
| 5 | import hashlib |
| 6 | import json |
| 7 | import uuid |
| 8 | from dataclasses import asdict, dataclass, field |
| 9 | from datetime import datetime, timezone |
| 10 | from enum import Enum |
| 11 | from typing import Any |
| 12 | |
| 13 | |
| 14 | class StepKind(str, Enum): |
| 15 | """Types of reasoning steps - the symbolic vocabulary.""" |
| 16 | |
| 17 | THOUGHT = "thought" # free-form reasoning statement |
| 18 | OBSERVATION = "observation" # observation about input or retrieved data |
| 19 | HYPOTHESIS = "hypothesis" # a tentative conclusion |
| 20 | DEDUCTION = "deduction" # logical deduction from prior steps |
| 21 | RETRIEVAL = "retrieval" # fetching external knowledge |
| 22 | TOOL_CALL = "tool-call" # calling an external tool / function |
| 23 | TOOL_RESULT = "tool-result" |
| 24 | SELF_CRITIQUE = "self-critique" # model critiquing its own prior step |
| 25 | REFINEMENT = "refinement" # updated answer after critique |
| 26 | DECISION = "decision" # final decision / answer |
| 27 | META = "meta" # metadata about the run |
| 28 | |
| 29 | |
| 30 | @dataclass(frozen=True) |
| 31 | class StepReference: |
| 32 | """A reference from one step to an earlier step |
| 33 | (e.g. 'deduction references observation X').""" |
| 34 | |
| 35 | step_id: str |
| 36 | relationship: str # "depends-on" | "refutes" | "refines" | "cites" |
| 37 | |
| 38 | def to_dict(self) -> dict[str, Any]: |
| 39 | return asdict(self) |
| 40 | |
| 41 | |
| 42 | @dataclass |
| 43 | class ReasoningStep: |
| 44 | """One step in a chain-of-thought reasoning trace. |
| 45 | |
| 46 | Every step is hashed with: |
| 47 | SHA3-256( previous_hash || canonical_bytes(step_payload) ) |
| 48 | Steps chain via previous_step_hash, so any tampering of an intermediate |
| 49 | step invalidates every step after it. |
| 50 | """ |
| 51 | |
| 52 | step_id: str |
| 53 | step_number: int # 1-based position within the trace |
| 54 | kind: StepKind |
| 55 | content: str # the actual reasoning text |
| 56 | timestamp: str |
| 57 | content_hash: str = "" # SHA3-256 of content |
| 58 | step_hash: str = "" # chain hash: SHA3-256(prev_hash || canonical_bytes) |
| 59 | previous_step_hash: str = "0" * 64 |
| 60 | references: list[StepReference] = field(default_factory=list) |
| 61 | confidence: float = 1.0 # 0..1 model's reported confidence in this step |
| 62 | metadata: dict[str, Any] = field(default_factory=dict) |
| 63 | |
| 64 | @staticmethod |
| 65 | def hash_content(content: str) -> str: |
| 66 | return hashlib.sha3_256(content.encode("utf-8")).hexdigest() |
| 67 | |
| 68 | def canonical_bytes(self) -> bytes: |
| 69 | """Deterministic payload for hashing - excludes chain hash.""" |
| 70 | payload = { |
| 71 | "step_id": self.step_id, |
| 72 | "step_number": self.step_number, |
| 73 | "kind": self.kind.value, |
| 74 | "content_hash": self.content_hash, |
| 75 | "timestamp": self.timestamp, |
| 76 | "previous_step_hash": self.previous_step_hash, |
| 77 | "references": [r.to_dict() for r in self.references], |
| 78 | "confidence": self.confidence, |
| 79 | "metadata": self.metadata, |
| 80 | } |
| 81 | return json.dumps( |
| 82 | payload, sort_keys=True, separators=(",", ":"), ensure_ascii=False |
| 83 | ).encode("utf-8") |
| 84 | |
| 85 | def compute_step_hash(self) -> str: |
| 86 | """SHA3-256 over (previous_step_hash || canonical_bytes).""" |
| 87 | prev = ( |
| 88 | bytes.fromhex(self.previous_step_hash) |
| 89 | if self.previous_step_hash |
| 90 | else b"\x00" * 32 |
| 91 | ) |
| 92 | return hashlib.sha3_256(prev + self.canonical_bytes()).hexdigest() |
| 93 | |
| 94 | @classmethod |
| 95 | def create( |
| 96 | cls, |
| 97 | kind: StepKind, |
| 98 | content: str, |
| 99 | step_number: int, |
| 100 | previous_step_hash: str = "0" * 64, |
| 101 | references: list[StepReference] | None = None, |
| 102 | confidence: float = 1.0, |
| 103 | metadata: dict[str, Any] | None = None, |
| 104 | ) -> ReasoningStep: |
| 105 | step_id = f"urn:pqc-step:{uuid.uuid4().hex}" |
| 106 | now = datetime.now(timezone.utc).isoformat() |
| 107 | content_hash = cls.hash_content(content) |
| 108 | step = cls( |
| 109 | step_id=step_id, |
| 110 | step_number=step_number, |
| 111 | kind=kind, |
| 112 | content=content, |
| 113 | timestamp=now, |
| 114 | content_hash=content_hash, |
| 115 | step_hash="", |
| 116 | previous_step_hash=previous_step_hash, |
| 117 | references=list(references or []), |
| 118 | confidence=confidence, |
| 119 | metadata=dict(metadata or {}), |
| 120 | ) |
| 121 | step.step_hash = step.compute_step_hash() |
| 122 | return step |
| 123 | |
| 124 | def to_dict(self) -> dict[str, Any]: |
| 125 | d = asdict(self) |
| 126 | d["kind"] = self.kind.value |
| 127 | return d |
| 128 | |
| 129 | @classmethod |
| 130 | def from_dict(cls, data: dict[str, Any]) -> ReasoningStep: |
| 131 | return cls( |
| 132 | step_id=data["step_id"], |
| 133 | step_number=int(data["step_number"]), |
| 134 | kind=StepKind(data["kind"]), |
| 135 | content=data["content"], |
| 136 | timestamp=data["timestamp"], |
| 137 | content_hash=data.get("content_hash", ""), |
| 138 | step_hash=data.get("step_hash", ""), |
| 139 | previous_step_hash=data.get("previous_step_hash", "0" * 64), |
| 140 | references=[StepReference(**r) for r in data.get("references", [])], |
| 141 | confidence=float(data.get("confidence", 1.0)), |
| 142 | metadata=dict(data.get("metadata", {})), |
| 143 | ) |
| 144 | |