138 lines
4.2 KiB
Python
138 lines
4.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from collections.abc import Sequence
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from typing import TYPE_CHECKING, Literal, NamedTuple, Optional, TypedDict, Union, cast
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from typing_extensions import TypeIs
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from vllm.utils import is_list_of
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from .data import (
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EmbedsPrompt,
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ExplicitEncoderDecoderPrompt,
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ProcessorInputs,
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PromptType,
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SingletonInputs,
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SingletonPrompt,
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TextPrompt,
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TokensPrompt,
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)
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if TYPE_CHECKING:
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import torch
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def parse_raw_prompts(
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prompt: Union[str, list[str], list[int], list[list[int]]],
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) -> Union[Sequence[TextPrompt], Sequence[TokensPrompt]]:
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if isinstance(prompt, str):
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# case 1: a string
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return [TextPrompt(prompt=prompt)]
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if isinstance(prompt, list):
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if len(prompt) == 0:
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raise ValueError("please provide at least one prompt")
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if is_list_of(prompt, str):
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# case 2: array of strings
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prompt = cast(list[str], prompt)
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return [TextPrompt(prompt=elem) for elem in prompt]
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if is_list_of(prompt, int):
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# case 3: array of tokens
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prompt = cast(list[int], prompt)
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return [TokensPrompt(prompt_token_ids=prompt)]
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if is_list_of(prompt, list):
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prompt = cast(list[list[int]], prompt)
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if len(prompt[0]) == 0:
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raise ValueError("please provide at least one prompt")
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if is_list_of(prompt[0], int):
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# case 4: array of token arrays
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return [TokensPrompt(prompt_token_ids=elem) for elem in prompt]
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raise TypeError(
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"prompt must be a string, array of strings, "
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"array of tokens, or array of token arrays"
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)
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class ParsedStrPrompt(TypedDict):
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type: Literal["str"]
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content: str
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class ParsedTextPrompt(TypedDict):
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type: Literal["text"]
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content: TextPrompt
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class ParsedTokensPrompt(TypedDict):
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type: Literal["tokens"]
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content: TokensPrompt
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class ParsedEmbedsPrompt(TypedDict):
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type: Literal["embeds"]
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content: EmbedsPrompt
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ParsedSingletonPrompt = Union[
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ParsedStrPrompt, ParsedTextPrompt, ParsedTokensPrompt, ParsedEmbedsPrompt
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]
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def parse_singleton_prompt(prompt: SingletonPrompt) -> ParsedSingletonPrompt:
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if isinstance(prompt, str):
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return ParsedStrPrompt(type="str", content=prompt)
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elif isinstance(prompt, dict):
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# Type ignores are because mypy does not correctly infer the TypedDicts
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# Pyright does succeed.
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if "prompt_embeds" in prompt:
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return ParsedEmbedsPrompt(type="embeds", content=prompt) # type: ignore[typeddict-item]
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elif "prompt_token_ids" in prompt:
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return ParsedTokensPrompt(type="tokens", content=prompt) # type: ignore[typeddict-item]
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elif "prompt" in prompt:
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return ParsedTextPrompt(type="text", content=prompt)
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raise TypeError(
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"inputs must be a string, TextPrompt, TokensPrompt, or EmbedsPrompt"
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)
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def is_explicit_encoder_decoder_prompt(
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prompt: PromptType,
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) -> TypeIs[ExplicitEncoderDecoderPrompt]:
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return isinstance(prompt, dict) and "encoder_prompt" in prompt
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def split_enc_dec_inputs(
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inputs: ProcessorInputs,
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) -> tuple[Optional[SingletonInputs], SingletonInputs]:
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if "encoder" in inputs and "decoder" in inputs:
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# NOTE: This passes pyright but not mypy
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return (
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inputs["encoder"], # type: ignore[typeddict-item]
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inputs["decoder"], # type: ignore[typeddict-item]
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)
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return None, inputs
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class PromptComponents(NamedTuple):
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text: Optional[str] = None
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token_ids: Optional[list[int]] = None
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embeds: Optional["torch.Tensor"] = None
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def get_prompt_components(prompt: PromptType) -> PromptComponents:
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if isinstance(prompt, str):
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return PromptComponents(text=prompt)
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if encoder_prompt := prompt.get("encoder_prompt"):
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return get_prompt_components(encoder_prompt) # type: ignore[arg-type]
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return PromptComponents(
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text=prompt.get("prompt"), # type: ignore[arg-type]
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token_ids=prompt.get("prompt_token_ids"), # type: ignore[arg-type]
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embeds=prompt.get("prompt_embeds"),
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)
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