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from langchain.chains import LLMChain | |
from langchain.llms import OpenAI | |
import gradio as gr | |
from dotenv import load_dotenv | |
load_dotenv() | |
def generate_questions(resume,role='',experience=''): | |
_PROMPT_TEMPLATE = """ | |
this is the resume of user: | |
{resume_details} | |
here is the role he want to join in : | |
{role} | |
Based on the following experience: | |
{experience} | |
What are your interview questions for the given user resume and role he want to join in with that experience? | |
generate no of questions = {questions}! | |
""" | |
PROMPT = PromptTemplate(input_variables=["resume_details", "role", "experience",'questions'], template=_PROMPT_TEMPLATE) | |
llm1 = OpenAI(model_name="text-davinci-003", temperature=0) | |
chain = LLMChain(llm=llm1, prompt=PROMPT) | |
prompt = chain.predict_and_parse(resume_details= gen_text(resume), | |
role= role, | |
experience= experience, | |
questions=10) | |
return prompt.split('\n') | |
k=gr.Interface( | |
fn=generate_questions, | |
inputs=['textbox','text','text'], | |
outputs=['text'] | |
) | |
k.launch() |