c923e7769b
Signed-off-by: Francisco Javier Arceo <4163062+franciscojavierarceo@users.noreply.github.com> Co-authored-by: Codex <noreply@openai.com> Co-authored-by: Misha Goin <mgoin64@gmail.com>
84 lines
2.9 KiB
Python
84 lines
2.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""Request and response models of the structured decisions API (/v1/systemone)."""
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import time
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from typing import Any, Literal
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from pydantic import Field, model_validator
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from vllm.entrypoints.generate.base.protocol import validate_cache_salt
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from vllm.entrypoints.serve.engine.protocol import OpenAIBaseModel
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from vllm.utils import random_uuid
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class QuestionSpec(OpenAIBaseModel):
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type: str
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instructions: Any = ""
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criteria: Any = None
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class StructuredDecisionRequest(OpenAIBaseModel):
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model: str | None = None
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state: Any = Field(..., description="What the questions are about: text or JSON.")
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questions: dict[str, QuestionSpec] = Field(
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..., description="Question id to question, asked in this order."
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)
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instructions: str | None = Field(
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default=None, description="Context placed ahead of the questions."
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)
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images: list[str] | None = Field(
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default=None, description="Image URLs or data URLs, for models that see."
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)
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audio: list[str] | None = Field(
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default=None, description="Audio URLs or data URLs, for models that hear."
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)
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videos: list[str] | None = Field(
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default=None, description="Video URLs or data URLs, for models that see."
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)
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chat_template_kwargs: dict[str, Any] | None = None
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cache_salt: str | None = Field(
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default=None,
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description=(
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"If specified, the prefix cache will be salted with the provided "
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"string to prevent an attacker to guess prompts in multi-user "
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"environments. The salt should be random, protected from "
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"access by 3rd parties, and long enough to be "
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"unpredictable (e.g., 43 characters base64-encoded, corresponding "
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"to 256 bit)."
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),
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)
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priority: int = Field(default=0, ge=-(2**63), le=2**63 - 1)
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request_id: str = Field(default_factory=random_uuid)
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@model_validator(mode="before")
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@classmethod
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def check_cache_salt_support(cls, data: Any) -> Any:
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if isinstance(data, dict):
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validate_cache_salt(data.get("cache_salt"))
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return data
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class DecisionUsage(OpenAIBaseModel):
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input_tokens: int
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output_tokens: int
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class QuestionDiagnostics(OpenAIBaseModel):
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label_mass: float = Field(
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description="Probability the model put on the labels, over the full "
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"vocabulary. A low value means most of the probability went to tokens "
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"that are not labels."
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)
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argmax_is_label: bool
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class StructuredDecisionResponse(OpenAIBaseModel):
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id: str
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object: Literal["structured_decision"] = "structured_decision"
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created: int = Field(default_factory=lambda: int(time.time()))
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model: str
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answers: dict[str, dict[str, Any]]
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usage: DecisionUsage
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diagnostics: dict[str, QuestionDiagnostics]
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