from huggingface_hub import HfApi, Repository
import gradio as gr
import json


def change_tab(query_param):
    query_param = query_param.replace("'", '"')
    query_param = json.loads(query_param)

    if (
        isinstance(query_param, dict)
        and "tab" in query_param
        and query_param["tab"] == "plot"
    ):
        return gr.Tabs.update(selected=1)
    else:
        return gr.Tabs.update(selected=0)


LLM_MODEL_ARCHS = {
    # branded ?
    "gpt_bigcode": "GPT-BigCode 🌸",
    "RefinedWebModel": "Falcon 🦅",
    "RefinedWeb": "Falcon 🦅",
    "baichuan": "Baichuan 🌊",
    "bloom": "Bloom 🌸",
    "llama": "LLaMA 🦙",
    # unbranded ? suggest something
    "stablelm_alpha": "StableLM-Alpha",
    "gpt_neox": "GPT-NeoX",
    "gpt_neo": "GPT-Neo",
    "codegen": "CodeGen",
    "chatglm": "ChatGLM",
    "gpt2": "GPT-2",
    "gptj": "GPT-J",
    "xglm": "XGLM",
    "rwkv": "RWKV",
    "bart": "BART",
    "opt": "OPT",
    "mpt": "MPT",
}


def model_hyperlink(link, model_name):
    return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'


def process_model_name(model_name):
    link = f"https://huggingface.co/{model_name}"
    return model_hyperlink(link, model_name)


def process_model_arch(model_arch):
    if model_arch in LLM_MODEL_ARCHS:
        return LLM_MODEL_ARCHS[model_arch]
    else:
        return model_arch