mirror of
https://github.com/bytedance/deer-flow.git
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69 lines
2.0 KiB
Python
69 lines
2.0 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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# Authorization identity fields (populated by GuardrailMiddleware from
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# runtime context). Default values ensure backward compatibility for
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# providers that don't read them.
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channel_user_id: str | None = None
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is_internal: bool = False
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authz_attributes: dict[str, Any] = field(default_factory=dict)
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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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