app.py

import gradio as gr
from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
from transformers import pipeline, AutoTokenizer

model = pipeline("token-classification", model="ckiplab/bert-base-chinese-pos", tokenizer=AutoTokenizer.from_pretrained("ckiplab/bert-base-chinese-pos"), aggregation_strategy="simple")

def analyze(sentence: str):
    result = model(sentence)
    return  

demo = gr.Interface(fn=analyze, inputs="text", outputs="text", title="詞性標註")

app = FastAPI()
app = gr.mount_gradio_app(app, demo, path="/")

@app.post("/analyze")
async def api_analyze(request: Request):
    payload = await request.json()
    return JSONResponse(content={"result": analyze(payload.get("sentence", ""))})