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from pydantic import BaseModel | |
from .ConfigEnv import config | |
from fastapi.middleware.cors import CORSMiddleware | |
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: | |
prompt = PromptTemplate(template=prompt, input_variables=['Prompt']) | |
llm = Clarifai( | |
pat = config.CLARIFAI_PAT, | |
user_id = config.USER_ID, | |
app_id = config.APP_ID, | |
model_id = config.MODEL_ID, | |
model_version_id=config.MODEL_VERSION_ID, | |
) | |
llmchain = LLMChain( | |
prompt=prompt, | |
llm=llm | |
) | |
llm_response = llmchain.run({"Prompt": prompt}) | |
return Generate(text=llm_response) | |
app.add_middleware( | |
CORSMiddleware, | |
allow_origins=["*"], | |
allow_credentials=True, | |
allow_methods=["*"], | |
allow_headers=["*"], | |
) | |
def api_home(): | |
return {'detail': 'Welcome to FastAPI TextGen Tutorial!'} | |
def inference(input_prompt: str): | |
return generate_text(prompt=input_prompt) |