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5a699e24a1
* docs: guardrail runtime attribution spec * docs: guardrail request attribution implementation plan * feat(guardrails): add runtime user context and attribution fields to GuardrailRequest Extend GuardrailRequest with optional runtime attribution fields so that pluggable GuardrailProviders can access authenticated user context and tool-call-level attribution: - Gateway injects user_role, oauth_provider, oauth_id into runtime context alongside the existing user_id (server-authenticated only, client spoofing prevented) - GuardrailRequest gains: user_id, user_role, oauth_provider, oauth_id, run_id, tool_call_id (all optional, backward compatible) - GuardrailMiddleware reads these from ToolCallRequest.runtime.context - thread_id now actually populated from context (was always None before) - Tests: 15 new/expanded tests covering Gateway injection, runtime context reading, partial/missing fields, and client spoofing prevention - Docs: new Runtime Attribution section in GUARDRAILS.md with provider example and YAML policy illustration * fix(guardrails): propagate attribution to subagents * fix(guardrails): complete subagent attribution propagation --------- Co-authored-by: Miracle778 <miracle778@no-reply.com>
63 lines
1.7 KiB
Python
63 lines
1.7 KiB
Python
"""GuardrailProvider protocol and data structures for pre-tool-call authorization."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Protocol, runtime_checkable
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@dataclass
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class GuardrailRequest:
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"""Context passed to the provider for each tool call."""
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tool_name: str
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tool_input: dict[str, Any]
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agent_id: str | None = None
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thread_id: str | None = None
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is_subagent: bool = False
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timestamp: str = ""
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user_id: str | None = None
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user_role: str | None = None
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oauth_provider: str | None = None
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oauth_id: str | None = None
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run_id: str | None = None
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tool_call_id: str | None = None
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@dataclass
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class GuardrailReason:
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"""Structured reason for an allow/deny decision (OAP reason object)."""
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code: str
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message: str = ""
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@dataclass
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class GuardrailDecision:
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"""Provider's allow/deny verdict (aligned with OAP Decision object)."""
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allow: bool
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reasons: list[GuardrailReason] = field(default_factory=list)
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policy_id: str | None = None
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metadata: dict[str, Any] = field(default_factory=dict)
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@runtime_checkable
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class GuardrailProvider(Protocol):
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"""Contract for pluggable tool-call authorization.
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Any class with these methods works - no base class required.
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Providers are loaded by class path via resolve_variable(),
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the same mechanism DeerFlow uses for models, tools, and sandbox.
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"""
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name: str
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def evaluate(self, request: GuardrailRequest) -> GuardrailDecision:
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"""Evaluate whether a tool call should proceed."""
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...
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async def aevaluate(self, request: GuardrailRequest) -> GuardrailDecision:
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"""Async variant."""
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...
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