##################################### Imports ######################################
# Generic imports
import gradio as gr

# Module imports
from utilities.setup import get_json_cfg

########################### Global objects and functions ###########################

conf = get_json_cfg()

def dropdown_visibility(radio):
    value = radio
    if value == "Predefined Dataset":
        return gr.Dropdown(visible=bool(1))
    else:
        return gr.Dropdown(visible=bool(0))

def upload_visibility(radio):
    value = radio
    if value == "Upload Your Own":
        return gr.UploadButton(visible=bool(1)) #make it visible
    else:
        return gr.UploadButton(visible=bool(0))

def greet(model_name, prompt_template, name, dataset):
    """The model call"""
    return f"Hello {name}!! Using model: {model_name} with template: {prompt_template}"

##################################### App UI #######################################
with gr.Blocks() as demo:

    ##### Title Block #####
    gr.Markdown("# Instruction Tuning with Unsloth")

    ##### Model Inputs #####

    # Select Model
    model_name = gr.Dropdown(label="Model", choices=conf['model']['choices'], value="gpt2")
    # Prompt template
    prompt_template = gr.Textbox(label="Prompt Template", value="Instruction: {0}\nOutput: {1}")
    # Prompt Input
    name_input = gr.Textbox(label="Your Name")
    # Dataset choice
    dataset_choice = gr.Radio(label="Choose Dataset", choices=["Predefined Dataset", "Upload Your Own"], value="Predefined Dataset")
    dataset_predefined = gr.Dropdown(label="Predefined Dataset", choices=['1', '2', '3'], value='1', visible=True)
    dataset_upload = gr.UploadButton(label="Upload Dataset", file_types=[".pdf",".csv",".jsonl"], visible=False) # gr.File(label="Upload Dataset", visible=False)
    dataset_choice.change(dropdown_visibility, dataset_choice, dataset_predefined)
    dataset_choice.change(upload_visibility, dataset_choice, dataset_upload)

    ##### Model Outputs #####

    # Text output
    output = gr.Textbox(label="Output")
    
    ##### Execution #####

    # Setup button
    tune_btn = gr.Button("Start Fine Tuning")
    # Execute button
    tune_btn.click(fn=greet, 
                   inputs=[model_name, prompt_template, name_input, dataset_predefined],
                   outputs=output)

##################################### Launch #######################################

if __name__ == "__main__":
    demo.launch()