import gradio as gr from huggingface_hub import InferenceClient """ 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 """ client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") SYSTEM_MAGIC = """ Your container is written in HTML. All outputs must be in HTML format. User cannot see what you say unles it is in HTML. """ def respond(message): messages = [{"role": "system", "content": SYSTEM_MAGIC}] messages.append({"role": "user", "content": message}) response = "" for message in client.chat_completion( messages, max_tokens=4096, stream=True, temperature=0.248, top_p=0.842, ): token = message.choices[0].delta.content response += token yield response print(response) return response """ For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface """ #demo = gr.ChatInterface( # respond, ## additional_inputs=[ # gr.Textbox(value="You are a friendly Chatbot.", label="System message"), # gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new 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 (nucleus sampling)", # ), # ], #) with gr.Blocks() as demo: with gr.Row(): hml = gr.HTML("") with gr.Row(): tb = gr.Textbox(placeholder="Your input here...") with gr.Row(): bn = gr.Button("Submit") bn.click(respond, inputs=[tb], outputs=[hml]) if __name__ == "__main__": demo.launch()