""" Star Coder2 chat demo """ from typing import List, Tuple, Union import gradio as gr from huggingface_hub import InferenceClient # HF InferenceClient client = InferenceClient("microsoft/Phi-3.5-mini-instruct") def chat( message: str, history: List[Tuple[str, str]], system_message: str, max_tokens: Union[int, None], temperature: Union[float, None], top_p: Union[float, None], ): """Code assistant""" # Chat history messages = [{"role": "system", "content": system_message}] for val in history: if val[0]: messages.append({"role": "user", "content": val[0]}) if val[1]: messages.append({"role": "assistant", "content": val[1]}) # Add user message messages.append({"role": "user", "content": message}) llm_message = client.chat_completion( messages, max_tokens=max_tokens, temperature=temperature, top_p=top_p, ) # Add chatbot message messages.append( { "role": "assistant", "content": llm_message.choices[0].message.content, } ) yield llm_message.choices[0].message.content # UI demo = gr.ChatInterface( chat, title="Phi-3.5-mini-instruct", theme="soft", description="Phi-3.5-mini is a lightweight, state-of-the-art open model built upon " "datasets used for Phi-3 - synthetic data and filtered publicly available websites - " "with a focus on very high-quality, reasoning dense data.", 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", ), ], ) if __name__ == "__main__": demo.launch()