model-gallery/deploy/llm/BladeLLM/webui_client.py [20:77]:
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    parser.add_argument(
        "--share",
        action="store_true",
        default=False,
        help="Create a publicly shareable link for the interface.",
    )
    parser.add_argument(
        "--inbrowser",
        action="store_true",
        default=False,
        help="Automatically launch the interface in a new tab on the default browser.",
    )
    parser.add_argument(
        "--server-port", type=int, default=7860, help="Demo server port."
    )
    parser.add_argument(
        "--server-name", type=str, default="127.0.0.1", help="Demo server name."
    )

    args = parser.parse_args()
    return args


css = """
.checkbox {
    max-width: 2.5em;
    min-width: 2.5em !important;
    display:flex;
    align-items:center;
}
"""


def _launch_ui(model_name, client, args):
    def _post_process(text):
        return text.replace("<think>", "&lt;think&gt;").replace(
            "</think>", "&lt;/think&gt;"
        )

    def _transform_messages(history, max_rounds, apply_max_rounds, system_prompt):
        messages = []
        if system_prompt:
            messages.append({"role": "system", "content": system_prompt})

        if not apply_max_rounds:
            begin_index = 0
        else:
            begin_index = max(0, len(history) - max_rounds)

        for i in range(begin_index, len(history)):
            query, response = history[i]
            messages.append({"role": "user", "content": query})
            messages.append({"role": "assistant", "content": response})
        messages.pop()  # pop the None assistant response
        return messages

    def predict(
        _chatbot,
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model-gallery/deploy/llm/vLLM/webui_client.py [13:70]:
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    parser.add_argument(
        "--share",
        action="store_true",
        default=False,
        help="Create a publicly shareable link for the interface.",
    )
    parser.add_argument(
        "--inbrowser",
        action="store_true",
        default=False,
        help="Automatically launch the interface in a new tab on the default browser.",
    )
    parser.add_argument(
        "--server-port", type=int, default=7860, help="Demo server port."
    )
    parser.add_argument(
        "--server-name", type=str, default="127.0.0.1", help="Demo server name."
    )

    args = parser.parse_args()
    return args


css = """
.checkbox {
    max-width: 2.5em;
    min-width: 2.5em !important;
    display:flex;
    align-items:center;
}
"""


def _launch_ui(model_name, client, args):
    def _post_process(text):
        return text.replace("<think>", "&lt;think&gt;").replace(
            "</think>", "&lt;/think&gt;"
        )

    def _transform_messages(history, max_rounds, apply_max_rounds, system_prompt):
        messages = []
        if system_prompt:
            messages.append({"role": "system", "content": system_prompt})

        if not apply_max_rounds:
            begin_index = 0
        else:
            begin_index = max(0, len(history) - max_rounds)

        for i in range(begin_index, len(history)):
            query, response = history[i]
            messages.append({"role": "user", "content": query})
            messages.append({"role": "assistant", "content": response})
        messages.pop()  # pop the None assistant response
        return messages

    def predict(
        _chatbot,
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