chatomon.orbitals.judge ¶

def to_verdict(self) -> Verdict:
    """Convert the decision into a verdict.

    The model's `reason` and `explanation` are model-written text that may quote
    the user, so they go into the annotations (treated as content). The
    verdict's audit reason is the fixed label `judge_<action>`.

    Returns:
        The verdict.

    Raises:
        ValueError: If the fields do not form a valid verdict (for example
            `respond` without a reply, or `block` with both reply and guidance).
    """
    reason = f"judge_{self.action}"
    annotations = {"label": self.reason, "explanation": self.explanation}
    if self.action == "allow":
        return Verdict.allow(self.guidance, reason=reason, annotations=annotations)
    if self.action == "block":
        return Verdict.block(
            self.reply, guidance=self.guidance, reason=reason, annotations=annotations
        )
    if not self.reply:
        raise ValueError("the judge chose 'respond' without a reply")
    return Verdict.respond(self.reply, reason=reason, annotations=annotations)

def bind(self, connector: Connector[Any]) -> None:
    """Remember the atom's connector, used when no connector was given.

    A judge can be shared by several atoms only if they use the same connector
    (or if the judge has its own `connector`).

    Args:
        connector: The atom's connector.

    Raises:
        ChatomonConfigError: If the judge is already bound to a different connector.
    """
    if self._connector is None and self._bound is not None and self._bound is not connector:
        raise ChatomonConfigError(
            f"judge {self.name!r} is already bound to another atom's connector; "
            "create one judge per atom or pass connector= explicitly"
        )
    self._bound = connector

def system_prompt(self, side: Side) -> str:
    """Build the judge's system prompt for one side.

    Args:
        side: The side being judged.

    Returns:
        The fixed frame, the instructions and the context.
    """
    prompt = _FRAME.format(
        side_description=_SIDE_DESCRIPTIONS[side],
        allow_guidance=_ALLOW_GUIDANCE[side],
        instructions=self.instructions.strip(),
    )
    if self.context is not None:
        prompt += "\n\nReference material:\n" + self.context.render()
    return prompt

def user_prompt(self, ctx: OrbitalContext) -> str:
    """Build the judge's user prompt.

    Args:
        ctx: The orbital context.

    Returns:
        The history window, the annotations in `reads` and the text under review,
        each in its own tag. Inserted text is XML-escaped, so it cannot close a tag.
    """
    parts: list[str] = []
    history = ctx.history[-self.history_window :] if self.history_window else ()
    if history:
        lines = "\n".join(f"{message.role}: {_escape(message.content)}" for message in history)
        parts.append(f"<history>\n{lines}\n</history>")
    for name in self.reads:
        data = _escape(stable_json(ctx.annotations.get(name)))
        parts.append(f'<annotations from="{name}">\n{data}\n</annotations>')
    parts.append(f"<text_under_review>\n{_escape(ctx.message)}\n</text_under_review>")
    return "\n\n".join(parts)

async def check(self, ctx: OrbitalContext) -> Verdict:
    """Ask the model for a decision.

    Args:
        ctx: The orbital context.

    Returns:
        The verdict built from the model's decision.

    Raises:
        ChatomonConfigError: If the judge has no connector.
        ValueError: If the model's decision is not a valid verdict. The engine
            treats both as an orbital failure and applies `on_error`.
    """  # noqa: DOC502 - raised by the connector property and to_verdict()
    decision = await self.connector.generate_structured(
        self.model,
        system=self.system_prompt(ctx.side),
        prompt=self.user_prompt(ctx),
        schema=JudgeDecision,
    )
    trace.get_current_span().add_event(
        "gen_ai.evaluation.result",
        attributes={
            "gen_ai.evaluation.name": self.name,
            "gen_ai.evaluation.score.label": decision.action,
            "gen_ai.request.model": self.model,
        },
    )
    return decision.to_verdict()

def config(self) -> dict[str, Any]:
    """Return the configuration, including model, instructions and context.

    Returns:
        A JSON-serializable dictionary.
    """
    return {
        **super().config(),
        "model": self.model,
        "instructions": self.instructions,
        "context": self.context.render() if self.context is not None else None,
        "history_window": self.history_window,
    }