61 lines
2.0 KiB
Python
61 lines
2.0 KiB
Python
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"""AI transparency helpers.
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Provides utilities to mark content as AI-generated and to detect whether a
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communication participant is an AI agent. This is the transparency layer
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required by the AI governance framework: any content produced by an AI agent
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must be identifiable as such.
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Used by:
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- ``app/plugins/builtins/kommunikation`` — marking AI agent messages
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- ``app/ai/agent_loop.py`` — tagging final outputs as AI-generated
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"""
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from __future__ import annotations
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from datetime import UTC, datetime
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from typing import Any
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# Participant types that represent an AI agent (not a human user).
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AI_PARTICIPANT_TYPES = ("agent", "ai", "system_ai")
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def mark_as_ai_generated(content: str, metadata: dict[str, Any] | None = None) -> dict[str, Any]:
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"""Add AI transparency metadata to content.
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Args:
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content: The AI-generated content.
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metadata: Optional dict with ``model`` and ``provider`` keys plus any
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additional context to record.
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Returns:
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A dict with the original content plus an ``ai_generated`` flag and an
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``ai_metadata`` block containing model, provider, timestamp, and any
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extra metadata passed in.
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"""
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metadata = metadata or {}
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return {
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"content": content,
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"ai_generated": True,
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"ai_metadata": {
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"model": metadata.get("model", "unknown"),
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"provider": metadata.get("provider", "unknown"),
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"timestamp": datetime.now(UTC).isoformat(),
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**metadata,
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},
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}
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def is_ai_participant(participant_id: str, participant_type: str) -> bool:
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"""Check if a participant is an AI agent.
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Args:
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participant_id: The participant's ID (unused for the check, kept for
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API symmetry and future heuristics).
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participant_type: The participant type string (e.g. ``user``,
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``agent``, ``ai``, ``system_ai``).
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Returns:
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``True`` if the participant type is an AI agent type.
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"""
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return participant_type in AI_PARTICIPANT_TYPES
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