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ReasonedIntent — structured output contract between Codette's reasoning
pipeline and the LLM verbalization step.
The reasoning engine (agents, debate, AEGIS, consciousness stack) produces a
ReasonedIntent. The LLM only receives that intent + a verbalization prompt.
It must not add facts, dates, or claims not present in the intent.
This separates cognition from rendering without requiring architectural changes
to the existing ForgeEngine — it's a drop-in wrapper at L7.
"""
from __future__ import annotations
import json
from dataclasses import dataclass, field, asdict
from typing import Optional
@dataclass
class ReasonedIntent:
core_claim: str
supporting_points: list[str] = field(default_factory=list)
caveats: list[str] = field(default_factory=list)
ethical_alignment: float = 1.0 # 0-1, from AEGIS η
confidence: float = 1.0 # 0-1, from gamma
tone: str = "balanced" # analytical | empathetic | creative | balanced
perspective_weights: dict = field(default_factory=dict) # agent name -> contribution weight
intent_risk: str = "low" # from Nexis Signal Engine
def to_verbalization_prompt(self) -> str:
points_block = "\n".join(f"- {p}" for p in self.supporting_points) if self.supporting_points else " (none)"
caveats_block = "\n".join(f"- {c}" for c in self.caveats) if self.caveats else " (none)"
return (
"You are the voice of Codette. Verbalize the following structured reasoning "
"conclusion in natural, conversational language.\n\n"
"STRICT RULES:\n"
"- Do not add facts, dates, names, versions, or statistics not present below.\n"
"- Do not flatter or soften the conclusion — express it directly.\n"
"- Match the tone specified.\n"
"- Keep it concise: one paragraph unless the supporting points require more.\n\n"
f"TONE: {self.tone}\n"
f"CONFIDENCE: {self.confidence:.2f}\n"
f"CORE CLAIM:\n{self.core_claim}\n\n"
f"SUPPORTING POINTS:\n{points_block}\n\n"
f"CAVEATS:\n{caveats_block}\n"
)
def to_dict(self) -> dict:
return asdict(self)
def to_json(self) -> str:
return json.dumps(self.to_dict(), indent=2)
def intent_from_synthesis(
synthesis: str,
*,
aegis_score: float = 1.0,
gamma: float = 1.0,
intent_risk: str = "low",
perspective_weights: Optional[dict] = None,
) -> ReasonedIntent:
"""
Build a ReasonedIntent from an existing synthesis string.
Splits synthesis into claim + supporting sentences heuristically.
Used as a zero-disruption drop-in at L7 of the consciousness stack.
"""
sentences = [s.strip() for s in synthesis.replace("\n", " ").split(".") if s.strip()]
core = sentences[0] if sentences else synthesis[:200]
supporting = [s for s in sentences[1:5] if len(s) > 20]
caveats = [s for s in sentences[5:] if any(
w in s.lower() for w in ("however", "caveat", "note", "uncertain", "may", "might", "could")
)]
tone = "analytical"
lower = synthesis.lower()
if any(w in lower for w in ("feel", "empath", "compassion", "human", "emotional")):
tone = "empathetic"
elif any(w in lower for w in ("imagine", "creative", "novel", "invent", "design")):
tone = "creative"
return ReasonedIntent(
core_claim=core,
supporting_points=supporting,
caveats=caveats,
ethical_alignment=aegis_score,
confidence=gamma,
tone=tone,
perspective_weights=perspective_weights or {},
intent_risk=intent_risk,
)
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