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| import gradio as gr | |
| from chatllm import ( | |
| chat_response, get_llm_model, set_llm_model, get_llm_model_info, | |
| get_llm_language, set_llm_language, get_llm_sysprompt, get_llm_sysprompt_mode, | |
| set_llm_sysprompt_mode, | |
| ) | |
| # Custom CSS for Gradio app | |
| css = ''' | |
| .gradio-container{max-width: 1000px !important} | |
| h1{text-align:center} | |
| footer { visibility: hidden } | |
| ''' | |
| # Create Gradio interface | |
| with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", css=css) as app: | |
| with gr.Column(): | |
| with gr.Group(): | |
| chatbot = gr.Chatbot(likeable=False, show_copy_button=True, show_share_button=False, layout="bubble", container=True) | |
| with gr.Row(): | |
| chat_query = gr.Textbox(label="Search Query", placeholder="hatsune miku", value="", scale=3) | |
| chat_clear = gr.Button("🗑️ Clear", scale=1) | |
| with gr.Row(): | |
| chat_msg = gr.Textbox(label="Message", placeholder="Input message with or without query and press Enter or click Sumbit.", value="", scale=3) | |
| chat_submit = gr.Button("Submit", scale=1) | |
| with gr.Accordion("Additional inputs", open=False): | |
| chat_model = gr.Dropdown(choices=get_llm_model(), value=get_llm_model()[0], allow_custom_value=True, label="Model") | |
| chat_model_info = gr.Markdown(value=get_llm_model_info(get_llm_model()[0]), label="Model info") | |
| with gr.Row(): | |
| chat_mode = gr.Dropdown(choices=get_llm_sysprompt_mode(), value=get_llm_sysprompt_mode()[0], allow_custom_value=False, label="Mode") | |
| chat_lang = gr.Dropdown(choices=get_llm_language(), value="language same as user input", allow_custom_value=True, label="Output language") | |
| chat_tokens = gr.Slider(minimum=1, maximum=4096, value=2000, step=1, label="Max tokens") | |
| chat_temp = gr.Slider(minimum=0.1, maximum=4.0, value=0.9, step=0.1, label="Temperature") | |
| chat_topp = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p") | |
| chat_fp = gr.Slider(minimum=0.0, maximum=2.0, value=0.0, step=0.1, label="Frequency penalty") | |
| chat_sysmsg = gr.Textbox(value=get_llm_sysprompt(), interactive=True, label="System message") | |
| examples = gr.Examples( | |
| examples = [ | |
| ["Describe this person.", "Kafuu Chino from Gochiusa"], | |
| ["Hello", ""], | |
| ], | |
| inputs=[chat_msg, chat_query], | |
| ) | |
| gr.Markdown( | |
| f"""This demo was created in reference to the following demos.<br> | |
| [prithivMLmods/WEB-DAC](https://huggingface.co/spaces/prithivMLmods/WEB-DAC), | |
| [featherless-ai/try-this-model](https://huggingface.co/spaces/featherless-ai/try-this-model), | |
| """ | |
| ) | |
| gr.DuplicateButton(value="Duplicate Space") | |
| gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.") | |
| gr.on( | |
| triggers=[chat_msg.submit, chat_query.submit, chat_submit.click], | |
| fn=chat_response, | |
| inputs=[chat_msg, chatbot, chat_query, chat_tokens, chat_temp, chat_topp, chat_fp], | |
| outputs=[chatbot], | |
| queue=True, | |
| show_progress="full", | |
| trigger_mode="once", | |
| ) | |
| chat_clear.click(lambda: (None, None, None), None, [chatbot, chat_msg, chat_query], queue=False) | |
| chat_model.change(set_llm_model, [chat_model], [chat_model, chat_model_info], queue=True, show_progress="full")\ | |
| .success(lambda: None, None, chatbot, queue=False) | |
| chat_mode.change(set_llm_sysprompt_mode, [chat_mode], [chat_sysmsg], queue=False) | |
| chat_lang.change(set_llm_language, [chat_lang], [chat_sysmsg], queue=False) | |
| if __name__ == "__main__": | |
| app.queue() | |
| app.launch() | |