app.py

import spaces
import json
import subprocess
from llama_cpp import Llama
from llama_cpp_agent import LlamaCppAgent, MessagesFormatterType
from llama_cpp_agent.providers import LlamaCppPythonProvider
from llama_cpp_agent.chat_history import BasicChatHistory
from llama_cpp_agent.chat_history.messages import Roles
import gradio as gr
from huggingface_hub import hf_hub_download

# モデルのダウンロード
hf_hub_download(
   repo_id="bartowski/gemma-2-9b-it-GGUF",
   filename="gemma-2-9b-it-Q5_K_M.gguf",
   local_dir="./models"
)

hf_hub_download(
   repo_id="bartowski/Gemma-2-9B-It-SPPO-Iter3-GGUF",
   filename="Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf",
   local_dir="./models"
)


# 推論関数
@spaces.GPU(duration=120)
def respond(
    message,
    history: list[tuple[str, str]],
    model,
    system_message,
    max_tokens,
    temperature,
    top_p,
    top_k,
    repeat_penalty,
):
    chat_template = MessagesFormatterType.GEMMA_2

    llm = Llama(
        model_path=f"models/{model}",
        flash_attn=True,
        n_gpu_layers=81,
        n_batch=1024,
        n_ctx=8192,
    )
    provider = LlamaCppPythonProvider(llm)

    agent = LlamaCppAgent(
        provider,
        system_prompt=f"{system_message}",
        predefined_messages_formatter_type=chat_template,
        debug_output=True
    )

    settings = provider.get_provider_default_settings()
    settings.temperature = temperature
    settings.top_k = top_k
    settings.top_p = top_p
    settings.max_tokens = max_tokens
    settings.repeat_penalty = repeat_penalty
    settings.stream = True

    messages = BasicChatHistory()

    for msn in history:
        user = {
            'role': Roles.user,
            'content': msn[0]
        }
        assistant = {
            'role': Roles.assistant,
            'content': msn[1]
        }
        messages.add_message(user)
        messages.add_message(assistant)

    stream = agent.get_chat_response(
        message,
        llm_sampling_settings=settings,
        chat_history=messages,
        returns_streaming_generator=True,
        print_output=False
    )

    outputs = ""
    for output in stream:
        outputs += output
        yield [(message, outputs)]

# Gradioのインターフェースを作成
def create_interface(model_name, description):
    return gr.ChatInterface(
        respond,
        additional_inputs=[
            gr.Textbox(value=model_name, label="Model", interactive=False),
            gr.Textbox(value="You are a helpful assistant.", label="System message"),
            gr.Slider(minimum=1, maximum=4096, value=2048, step=1, label="Max tokens"),
            gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
            gr.Slider(
                minimum=0.1,
                maximum=1.0,
                value=0.95,
                step=0.05,
                label="Top-p",
            ),
            gr.Slider(
                minimum=0,
                maximum=100,
                value=40,
                step=1,
                label="Top-k",
            ),
            gr.Slider(
                minimum=0.0,
                maximum=2.0,
                value=1.1,
                step=0.1,
                label="Repetition penalty",
            ),
        ],
        retry_btn="Retry",
        undo_btn="Undo",
        clear_btn="Clear",
        submit_btn=None,  # Remove the individual submit button
        title=f"Chat with Gemma 2 using llama.cpp - {model_name}",
        description=description,
        chatbot=gr.Chatbot(
            scale=1,
            likeable=False,
            show_copy_button=True
        )
    )

# 各モデルのインターフェース
description_9b = """<p align="center">Gemma-2 9B it Model</p>"""
description_27b = """<p align="center">Gemma-2-9B-It-SPPO-Iter3 Model</p>"""

interface_9b = create_interface('gemma-2-9b-it-Q5_K_M.gguf', description_9b)
interface_27b = create_interface('Gemma-2-9B-It-SPPO-Iter3-Q5_K_M.gguf', description_27b)

# Gradio Blocksで2つのインターフェースを並べて表示
with gr.Blocks() as demo:
    #gr.Markdown("# Compare Gemma-2 9B and 27B Models")
    with gr.Row():
        with gr.Column():
            input_field = gr.Textbox(label="Input", interactive=True)
        with gr.Column():
            interface_9b.render()
        with gr.Column():
            interface_27b.render()

    submit_btn = gr.Button("Send")

    def send_to_both(input_text):
        return input_text, input_text

    submit_btn.click(
        fn=send_to_both,
        inputs=input_field,
        outputs=[interface_9b.chatbot, interface_27b.chatbot]
    )

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