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#import gradio as gr
#gr.Interface.load("models/pyannote/speaker-diarization").launch()
from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
#from pyannote.audio import Pipeline
from transformers import pipeline
app = FastAPI()
pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")
@app.get("/")
def t5(input):
output = pipe_flan(input)
#pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization")
#pipeline("file.wav")
return {"output":"OK"+output}
#app.mount("/", StaticFiles(directory="static", html=True), name="static")
# @app.get("/")
#def index() -> FileResponse:
# return FileResponse(path="/app/static/index.html", media_type="text/html")
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