77 lines
1.8 KiB
Python
77 lines
1.8 KiB
Python
from pydantic import BaseModel as PydanticBaseModel
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from typing import List, Any, Dict, Optional,Union
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from .structures import Embedding,Word, Symbol,Phrase,NoEmbeddingPhrase
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from pydantic import field_validator, ConfigDict
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from pydantic_tensor import Tensor
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import torch
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from typing import Any, Literal
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class ModifiedBaseModel(PydanticBaseModel):
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pass
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#model_config = ConfigDict(arbitrary_types_allowed=True)
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class EmbeddingRequest(ModifiedBaseModel):
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stemmed_words: List[str]
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tokens: dict
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word_ids: List[int]
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class EmbeddingResponse(ModifiedBaseModel):
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embeddings: List[Embedding]
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class ResponseRequest(ModifiedBaseModel):
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text: str
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context: Dict[str, Any]
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class PreprocessRequest(ModifiedBaseModel):
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text: str
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class PreprocessResponse(ModifiedBaseModel):
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raw_words: List[str]
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tokens: Dict[str, Any]
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word_ids: List[int]
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class GetSymbolRequest(ModifiedBaseModel):
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lexeme_id: int
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class GetSymbolResponse(ModifiedBaseModel):
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symbol: Optional[Symbol]
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class GetWordRequest(ModifiedBaseModel):
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word_text: str
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stemmed: bool = False
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class GetWordResponse(ModifiedBaseModel):
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word: Optional[Word]
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class GetSimilarWordRequest(ModifiedBaseModel):
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embedding: Embedding
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class GetAllPhrasesResponse(ModifiedBaseModel):
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phrases: List[NoEmbeddingPhrase]
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class GetFullPhrasesRequest(ModifiedBaseModel):
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phrases: List[NoEmbeddingPhrase]
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class GetFullPhrasesResponse(ModifiedBaseModel):
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phrases: List[Phrase]
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class GetTranscriptionRequest(ModifiedBaseModel):
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audio_data: bytes
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class GetTranscriptionResponse(ModifiedBaseModel):
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transcription: str
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class AudioToSymbolRequest(ModifiedBaseModel):
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audio_data: bytes
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class AudioToSymbolResponse(ModifiedBaseModel):
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symbols: List[Symbol]
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