import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed
from transformers import pipeline
import os

description = """# SantaCoder Endpoint"""
token = os.environ["HUB_TOKEN"]
device="cuda:0"

tokenizer = AutoTokenizer.from_pretrained("bigcode/christmas-models", use_auth_token=token)
model = AutoModelForCausalLM.from_pretrained("bigcode/christmas-models", trust_remote_code=True, use_auth_token=token)


def code_generation(gen_prompt, max_tokens, temperature=0.6, seed=42):
    set_seed(seed)
    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
    generated_text = pipe(gen_prompt, do_sample=True, top_p=0.95, temperature=temperature, max_new_tokens=max_tokens)[0]['generated_text']
    return generated_text


import gradio as gr
from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed
from transformers import pipeline
import os

title = "Santa Model Generator"
description = "Demo"
example = [
    ["def print_hello_world():", 8, 0.6, 42],
    ["def get_file_size(filepath):", 24, 0.6, 42],
    ["def count_lines(filename):", 40, 0.6, 42],
    ["def count_words(filename):", 40, 0.6, 42]]

token = os.environ["HUB_TOKEN"]
device="cuda:0"
revision = "dedup-alt-comments"

tokenizer = AutoTokenizer.from_pretrained("bigcode/christmas-models", use_auth_token=token)
model = AutoModelForCausalLM.from_pretrained("bigcode/christmas-models", revision=revision, trust_remote_code=True, use_auth_token=token)


def code_generation(gen_prompt, max_tokens, temperature=0.6, seed=42):
    set_seed(seed)
    pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
    generated_text = pipe(gen_prompt, do_sample=True, top_p=0.95, temperature=temperature, max_new_tokens=max_tokens)[0]['generated_text']
    return generated_text


iface = gr.Interface(
    fn=code_generation, 
    inputs=[
        gr.Textbox(lines=10, label="Input code"),
        gr.inputs.Slider(
            minimum=8,
            maximum=1000,
            step=1,
            default=8,
            label="Number of tokens to generate",
        ),
        gr.inputs.Slider(
            minimum=0,
            maximum=2.5,
            step=0.1,
            default=0.6,
            label="Temperature",
        ),
        gr.inputs.Slider(
            minimum=0,
            maximum=1000,
            step=1,
            default=42,
            label="Random seed to use for the generation"
        )
    ],
    outputs=gr.Textbox(label="Predicted code", lines=10),
    examples=example,
    layout="horizontal",
    theme="peach",
    description=description,
    title=title
)
iface.launch()