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from fastapi import APIRouter |
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from pythainlp.tokenize import word_tokenize as py_word_tokenize, subword_tokenize as py_subword_tokenize |
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from enum import Enum |
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from typing import List, Optional |
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from pydantic import BaseModel |
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router = APIRouter() |
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class SentTokenizeEngine(str, Enum): |
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whitespace = "whitespace" |
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whitespace_newline = "whitespace+newline" |
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class WordTokenizeEngine(str, Enum): |
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newmm = "newmm" |
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longest = "longest" |
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deepcut = "deepcut" |
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icu = "icu" |
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ulmfit = "ulmfit" |
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class SubwordTokenizeEngine(str, Enum): |
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tcc = "tcc" |
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etcc = "etcc" |
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class WordTokenizeResponse(BaseModel): |
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words: List[str] = [] |
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class SubwordTokenizeResponse(BaseModel): |
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subwords: List[str] = [] |
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@router.get('/word_tokenize', response_model=WordTokenizeResponse) |
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def word_tokenize(text: str, engine: WordTokenizeEngine = "newmm"): |
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return {"words": py_word_tokenize(text=text, engine=engine)} |
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@router.get('/subword_tokenize', response_model=SubwordTokenizeResponse) |
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def subword_tokenize(text: str, engine: SubwordTokenizeEngine = "tcc"): |
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return {"subwords": py_subword_tokenize(text=text, engine=engine)} |
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