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from pydantic import BaseModel
from .ConfigEnv import config
from fastapi.middleware.cors import CORSMiddleware
from happytransformer import HappyTextToText, TTSettings
from langchain.llms import Clarifai
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from TextGen import app
class Generate(BaseModel):
text:str
def generate_text(prompt: str):
if prompt == "":
return {"detail": "Please provide a prompt."}
else:
happy_tt = HappyTextToText("T5", "vennify/t5-base-grammar-correction")
args = TTSettings(num_beams=5, min_length=1, max_length=100000)
result = happy_tt.generate_text(f"grammar: {prompt}", args=args)
return result.text
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/", tags=["Home"])
def api_home():
return {'detail': 'Welcome to FastAPI TextGen Tutorial!'}
@app.post("/api/generate", tags=["Generate"], response_model=Generate)
def inference(input_prompt: str):
return generate_text(prompt=input_prompt)
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