from transformers import AutoTokenizer, AutoModelForCausalLM
import gradio as grad
codegen_tkn = AutoTokenizer.from_pretrained("Salesforce/codegen-350M-mono")
mdl = AutoModelForCausalLM.from_pretrained("Salesforce/codegen-350M-mono")

def codegen(intent):
    input_ids = codegen_tkn(intent, return_tensors="pt").input_ids

    gen_ids = mdl.generate(input_ids, max_length=256)
    response = codegen_tkn.decode(gen_ids[0], skip_special_tokens=True)
    return response

output = grad.Textbox(lines=1, label="Generated Python Code", placeholder="")
inp = grad.Textbox(lines=1, label="place your intent here")
grad.Interface(codegen, inputs=inp, outputs=output).launch()

text = """def merge_sort(unsorted:list):
"""
input_ids = codegen_tkn(text, return_tensors="pt").input_ids

gen_ids = mdl.generate(input_ids, max_length=256)
print(codegen_tkn.decode(gen_ids[0],skip_special_tokens=True))