tzhouam
83e7f6ba12
- Introduced `OmniModelRunnerOutput` and `OmniRequestOutput` classes for handling multimodal outputs. - Implemented `OmniEngineCoreRequest` and `OmniInputPreprocessor` to manage prompt embeddings and additional information. - Created `OmniTokensPrompt`, `OmniTokenInputs`, and `OmniEmbedsPrompt` for enhanced token handling. - Added parsing and preprocessing functions to support new input structures. - Removed the obsolete `diffusion_engine.py` file as part of the refactor.
21 lines
1.1 KiB
Python
21 lines
1.1 KiB
Python
from vllm.inputs.parse import ParsedSingletonPrompt, ParsedStrPrompt, ParsedEmbedsPrompt, ParsedTokensPrompt, ParsedTextPrompt
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from vllm.inputs.data import SingletonPrompt
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def parse_singleton_prompt_omni(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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# 优先 tokens：当 tokens 与 embeds 同在时，保留两者并走 tokens 路径
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if "prompt_token_ids" in prompt:
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return ParsedTokensPrompt(
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type="tokens", content=prompt) # type: ignore[typeddict-item]
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elif "prompt_embeds" in prompt:
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return ParsedEmbedsPrompt(
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type="embeds", 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") |