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Create app.py
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app.py
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import chatglm_cpp
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import gradio as gr
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from pathlib import Path
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model_file_path = "chatglm3-ggml_q4_0.bin"
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chatglm_llm = chatglm_cpp.Pipeline(Path(model_file_path))
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def predict(message, history):
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'''
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messages = []
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for human_content, system_content in history:
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message_human = {
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"role": "user",
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"content": human_content + "\n",
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}
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message_system = {
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"role": "system",
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"content": system_content + "\n",
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}
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messages.append(message_human)
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messages.append(message_system)
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message_human = {
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"role": "user",
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"content": message + "\n",
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}
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messages.append(message_human)
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# Llamaでの回答を取得(ストリーミングオン)
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streamer = llama.create_chat_completion(messages, stream=True)
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'''
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flatten_history = []
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for a, b in history:
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flatten_history.append(a)
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flatten_history.append(b)
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streamer = chatglm_llm.chat(
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history= flatten_history + [message], do_sample=False,
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stream = True
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)
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'''
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partial_message = ""
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for msg in streamer:
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message = msg['choices'][0]['delta']
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if 'content' in message:
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partial_message += message['content']
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yield partial_message
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'''
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response = ""
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for new_text in streamer:
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response += new_text
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yield response
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gr.ChatInterface(predict,
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chatbot=gr.Chatbot(height=300),
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textbox=gr.Textbox(placeholder="你好 人工智能助手 ChatGLM3,我可以问你一些问题吗?", container=False, scale=7),
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title="ChatGLM3 Chatbot 🐼",
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description="与人工智能助手 ChatGLM3 进行对话",
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theme="soft",
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examples=["你听说过马克思吗?", "如何进行经济建设?", "明朝内阁制度的特点是什么?",
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"请解释下面的emoji符号描述的情景👨👩🔥❄️",
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],
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cache_examples=False,
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retry_btn=None,
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undo_btn="Delete Previous",
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clear_btn="Clear",
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).launch(enable_queue=True)
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