import gradio as gr

from llm import end_interview, get_problem, send_request

languages_list = ["python", "javascript", "html", "css", "typescript", "dockerfile", "shell", "r", "sql"]  # limited by gradio for now
topics_list = ["Arrays", "Strings", "Linked Lists"]
models = ["gpt-3.5-turbo"]


with gr.Blocks() as demo:
    gr.Markdown("Your coding interview practice AI assistant!")
    with gr.Tab("Coding"):
        chat_history = gr.State([])
        previous_code = gr.State("")
        client = gr.State(None)
        with gr.Accordion("Settings") as init_acc:
            with gr.Row():
                with gr.Column():
                    gr.Markdown("Difficulty")
                    difficulty_select = gr.Dropdown(
                        label="Select difficulty", choices=["Easy", "Medium", "Hard"], value="Medium", container=False
                    )

                    gr.Markdown("Topic")
                    topic_select = gr.Dropdown(
                        label="Select topic", choices=topics_list, value="Arrays", container=False, allow_custom_value=True
                    )

                    gr.Markdown("Select LLM model to use")
                    model_select = gr.Dropdown(label="Select model", choices=models, value="gpt-3.5-turbo", container=False)
                with gr.Column():
                    requirements = gr.Textbox(
                        label="Requirements", placeholder="Specify requirements: topic, difficulty, language, etc.", lines=5
                    )
                    start_btn = gr.Button("Start")

            # TODO: select LLM model
        with gr.Accordion("Solution", open=True) as solution_acc:
            description = gr.Markdown()
            with gr.Row() as content:
                with gr.Column(scale=2):
                    language_select = gr.Dropdown(
                        label="Select language", choices=languages_list, value="python", container=False, interactive=True
                    )
                    code = gr.Code(label="Solution", language=language_select.value, lines=20)
                    message = gr.Textbox(label="Message", lines=1)
                with gr.Column(scale=1):
                    chat = gr.Chatbot(label="Chat history")
                    end_btn = gr.Button("Finish the interview")
        with gr.Accordion("Feedback", open=True) as feedback_acc:
            feedback = gr.Markdown()

    start_btn.click(
        fn=get_problem,
        inputs=[requirements, difficulty_select, topic_select, model_select],
        outputs=[description, chat_history],
        scroll_to_output=True,
    )
    message.submit(
        fn=send_request,
        inputs=[code, previous_code, message, chat_history, chat, model_select],
        outputs=[chat_history, chat, message, previous_code],
    )
    end_btn.click(fn=end_interview, inputs=[chat_history, model_select], outputs=feedback)

demo.launch()