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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=["*"],
)
@app.get("/", tags=["Home"])
def api_home():
return {"detail": "Welcome to FastAPI TextGen Tutorial!"}
@app.post(
"/api/generate",
summary="Generate text from prompt",
tags=["Generate"],
response_model=Generate,
)
def inference(input_prompt: str):
return generate_text(prompt=input_prompt)
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