LLM_MODEL_ARCHS = {
    "stablelm_epoch": "🔴 StableLM-Epoch",
    "stablelm_alpha": "🔴 StableLM-Alpha",
    "mixformer-sequential": "🧑‍💻 Phi φ",
    "RefinedWebModel": "🦅 Falcon",
    "gpt_bigcode": "⭐ StarCoder",
    "RefinedWeb": "🦅 Falcon",
    "baichuan": "🌊 Baichuan 百川",  # river
    "internlm": "🧑‍🎓 InternLM 书生",  # scholar
    "mistral": "Ⓜ️ Mistral",
    "codegen": "♾️ CodeGen",
    "chatglm": "💬 ChatGLM",
    "falcon": "🦅 Falcon",
    "bloom": "🌸 Bloom",
    "llama": "🦙 LLaMA",
    "rwkv": "🐦‍⬛ RWKV",
    "mpt": "🧱 MPT",
    "Yi": "🫂 Yi 人" , # people
    # suggest something
    "gpt_neox": "GPT-NeoX",
    "gpt_neo": "GPT-Neo",
    "gpt2": "GPT-2",
    "gptj": "GPT-J",
    "xglm": "XGLM",
    "bart": "BART",
    "opt": "OPT",
}


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_arch(model_arch):
    if model_arch in LLM_MODEL_ARCHS:
        return LLM_MODEL_ARCHS[model_arch]
    else:
        return model_arch


def process_score(score, quantization):
    if quantization != "None":
        return f"{score:.2f}*"
    else:
        return f"{score:.2f} "


# 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)