import gradio as gr import requests import os # 환경 변수에서 API 토큰 가져오기 TOKEN = os.getenv("HUGGINGFACE_API_TOKEN") # API 토큰이 설정되어 있는지 확인 if not TOKEN: raise ValueError("API token is not set. Please set the HUGGINGFACE_API_TOKEN environment variable.") def respond( message, history: list[tuple[str, str]], system_message="너의 이름은 홍길동이다", max_tokens=512, temperature=0.7, top_p=0.95, ): 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]}) messages.append({"role": "user", "content": message}) headers = { "Authorization": f"Bearer {TOKEN}", "Content-Type": "application/json" } payload = { "model": "meta-llama/Meta-Llama-3.1-405B-Instruct", "max_tokens": max_tokens, "temperature": temperature, "top_p": top_p, "messages": messages } response = requests.post("https://api-inference.huggingface.co/v1/chat/completions", headers=headers, json=payload, stream=True) response_text = "" for chunk in response.iter_content(chunk_size=None): if chunk: chunk_data = chunk.decode('utf-8') response_json = json.loads(chunk_data) # content 영역만 출력 if "choices" in response_json: content = response_json["choices"][0]["message"]["content"] yield content theme="Nymbo/Nymbo_Theme" demo = gr.ChatInterface( respond, theme=theme, additional_inputs=[ gr.Textbox(value="너의 이름은 홍길동이다", 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)", ), ], ) if __name__ == "__main__": demo.launch()