app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Load your model and tokenizer
model_name = "Sakshi1307/SakshiAI" 
tokenizer = AutoTokenizer.from_pretrained(model_name,use_fast=False)
model = AutoModelForCausalLM.from_pretrained(model_name)

def generate_answer(question):
    inputs = tokenizer.encode(question, return_tensors='pt')
    outputs = model.generate(inputs, max_length=500, num_return_sequences=1)
    answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return answer

# Create a Gradio interface
iface = gr.Interface(
    fn=generate_answer,
    inputs=gr.Textbox(lines=2, placeholder="Enter your interview question here..."),
    outputs="text",
    title="Interview Simulation AI",
    description="This AI model simulates me in an interview questions. Type in a question and see how it responds!"
)

# Launch the application
if __name__ == "__main__":
    iface.launch()