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Update app.py
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app.py
CHANGED
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import gradio as gr
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from huggingface_hub import InferenceClient
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import json
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import os
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client = InferenceClient("Qwen/Qwen2.5-72B-Instruct")
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def respond(
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message,
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response += token
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yield response
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def load_rooms():
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if os.path.exists("rooms.json"):
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with open("rooms.json", "r", encoding="utf-8") as f:
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return json.load(f)
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return {}
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def create_room(rooms, room_name):
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if room_name not in rooms:
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rooms[room_name] = []
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save_rooms(rooms)
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return rooms
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def switch_room(room_name, rooms):
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return rooms.get(room_name, [])
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def add_message_to_room(room_name, rooms, message, response):
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if room_name in rooms:
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rooms[room_name].append((message, response))
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save_rooms(rooms)
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def chat_interface(room_name, rooms, message, history, system_message, max_tokens, temperature, top_p):
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response = list(respond(message, history, system_message, max_tokens, temperature, top_p))[-1]
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add_message_to_room(room_name, rooms, message, response)
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return response, history + [(message, response)]
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def main():
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rooms = load_rooms()
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room_names = list(rooms.keys())
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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room_name_dropdown = gr.Dropdown(room_names, label="会話部屋", value=room_names[0] if room_names else None)
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new_room_name = gr.Textbox(label="新しい会話部屋の名前")
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create_room_button = gr.Button("新しい会話部屋を作成")
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create_room_button.click(
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fn=lambda name, r: (create_room(r, name), name, switch_room(name, r)),
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inputs=[new_room_name, gr.State(rooms)],
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outputs=[room_name_dropdown, room_name_dropdown, gr.Chatbot]
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)
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room_name_dropdown.change(
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fn=lambda name, r: (switch_room(name, r),),
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inputs=[room_name_dropdown, gr.State(rooms)],
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outputs=[gr.Chatbot]
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)
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with gr.Column(scale=3):
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chatbot = gr.Chatbot(label="会話")
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message = gr.Textbox(label="メッセージ")
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system_message = gr.Textbox(value="あなたは親切なチャットボットでありQwenというLLMです。", label="システムメッセージ")
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max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="新規トークン最大")
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temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="温度")
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top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (核 sampling)")
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submit_button = gr.Button("送信")
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submit_button.click(
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fn=chat_interface,
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inputs=[room_name_dropdown, gr.State(rooms), message, chatbot, system_message, max_tokens, temperature, top_p],
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outputs=[chatbot, chatbot]
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)
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demo.launch()
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if __name__ == "__main__":
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import gradio as gr
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from huggingface_hub import InferenceClient
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"""
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For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
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"""
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client = InferenceClient("Qwen/Qwen2.5-72B-Instruct")
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#応答部分
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def respond(
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message,
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response += token
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yield response
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"""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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#インターフェース
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(value="ユーザーの応答と依頼に答えてください。ポジティブに", label="システムメッセージ"),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="新規トークン最大"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="温度"),
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gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.95,
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step=0.05,
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label="Top-p (核 sampling)",
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),
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],
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concurrency_limit=30 # 例: 同時に4つのリクエストを処理
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)
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if __name__ == "__main__":
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demo.launch()
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