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| import gradio as gr | |
| import os | |
| import litellm | |
| DESCRIPTION = ''' | |
| <div> | |
| <h1 style="text-align: center;">TAIDE/TAIDE-LX-7B-Chat</h1> | |
| <p>This Space demonstrates the instruction-tuned model <a href="https://huggingface.co/taide/TAIDE-LX-7B-Chat"><b>TAIDE-LX-7B-Chat</b></a>. TAIDE-LX-7B-Chat is the new open LLM and comes in one sizes: 8b. Feel free to play with it, or duplicate to run privately!</p> | |
| </div> | |
| ''' | |
| LICENSE = """ | |
| <p/> | |
| --- | |
| Built with TAIDE-LX-7B-Chat | |
| """ | |
| css = """ | |
| h1 { | |
| text-align: center; | |
| display: block; | |
| } | |
| #duplicate-button { | |
| margin: auto; | |
| color: white; | |
| background: #1565c0; | |
| border-radius: 100vh; | |
| } | |
| """ | |
| def chat(message: str, | |
| history: list, | |
| temperature: float, | |
| max_new_tokens: int | |
| ) -> str: | |
| """ | |
| Generate a streaming response using the llama3-8b model. | |
| """ | |
| try: | |
| messages = [] | |
| for user, assistant in history: | |
| messages.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}]) | |
| messages.append({"role": "user", "content": message}) | |
| response = litellm.completion( | |
| model="openai/TAIDE-LX-7B-Chat", # tells litellm to call the model via the Responses API | |
| messages=messages, | |
| max_completion_tokens=max_new_tokens, | |
| temperature=temperature, | |
| stream=True, | |
| ) | |
| output = [] | |
| for part in response: | |
| content = part.choices[0].delta.content or "" | |
| output.append(content) | |
| yield "".join(output) | |
| except Exception as e: | |
| yield f"生成過程中發生錯誤: {str(e)}" | |
| # Gradio block | |
| chatbot = gr.Chatbot(height=450, label='Gradio ChatInterface') | |
| with gr.Blocks(fill_height=True, css=css) as demo: | |
| gr.Markdown(DESCRIPTION) | |
| gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button") | |
| gr.ChatInterface( | |
| fn=chat, | |
| chatbot=chatbot, | |
| fill_height=True, | |
| additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False), | |
| additional_inputs=[ | |
| gr.Slider(minimum=0, | |
| maximum=1, | |
| step=0.1, | |
| value=0.95, | |
| label="Temperature", | |
| render=False), | |
| gr.Slider(minimum=128, | |
| maximum=131584, | |
| step=1, | |
| value=512, | |
| label="Max new tokens", | |
| render=False), | |
| ], | |
| examples=[ | |
| ['請以以下內容為基礎，寫一篇文章：撰寫一篇作文，題目為《一張舊照片》，內容要求為：選擇一張令你印象深刻的照片，說明令你印象深刻的原因，並描述照片中的影像及背後的故事。記錄成長的過程、與他人的情景、環境變遷和美麗的景色。'], | |
| ['請以品牌經理的身份，給廣告公司的創意總監寫一封信，提出對於新產品廣告宣傳活動的創意建議。'], | |
| ['以下提供英文內容，請幫我翻譯成中文。Dongshan coffee is famous for its unique position, and the constant refinement of production methods. The flavor is admired by many caffeine afficionados.'], | |
| ], | |
| cache_examples=False, | |
| ) | |
| gr.Markdown(LICENSE) | |
| if __name__ == "__main__": | |
| demo.launch(server_name='0.0.0.0') |