import gradio as gr import openai import requests import os import fileinput from dotenv import load_dotenv title="Abstract Language Object Generator" inputs_label="Input Object" outputs_label="ALOs" description=""" - ※up to 1000 character it takes 120 sec for generation. Because of API. """ article = """ """ load_dotenv() openai.api_key = os.getenv('OPENAI_API_KEY') MODEL = "gpt-4" def get_filetext(filename, cache={}): if filename in cache: # キャッシュに保存されている場合は、キャッシュからファイル内容を取得する return cache[filename] else: if not os.path.exists(filename): raise ValueError(f"ファイル '{filename}' が見つかりませんでした") with open(filename, "r") as f: text = f.read() # ファイル内容をキャッシュする cache[filename] = text return text class OpenAI: @classmethod def chat_completion(cls, prompt, start_with=""): constraints = get_filetext(filename = "constraints.md") template = get_filetext(filename = "template.md") # ChatCompletion APIに渡すデータを定義する data = { "model": "gpt-4", "messages": [ {"role": "system", "content": constraints} ,{"role": "system", "content": template} ,{"role": "assistant", "content": "Sure!"} ,{"role": "user", "content": prompt} ,{"role": "assistant", "content": start_with} ], } # ChatCompletion APIを呼び出す response = requests.post( "https://api.openai.com/v1/chat/completions", headers={ "Content-Type": "application/json", "Authorization": f"Bearer {openai.api_key}" }, json=data ) # ChatCompletion APIから返された結果を取得する result = response.json() print(result) content = result["choices"][0]["message"]["content"].strip() return content class NajiminoAI: @classmethod def generate_emo_prompt(cls, user_message): template = get_filetext(filename="template.md") prompt = f""" --- INPUT = --- {user_message} --- ALOs(INPUT) --- {template} """ return prompt @classmethod def generate_emo(cls, user_message): prompt = NajiminoAI.generate_emo_prompt(user_message); start_with = "" result = OpenAI.chat_completion(prompt=prompt, start_with=start_with) return result def main(): iface = gr.Interface(fn=NajiminoAI.generate_emo, inputs=gr.Textbox(label=inputs_label), outputs=gr.Textbox(label=outputs_label), title=title, description=description, article=article, allow_flagging='never' ) iface.launch() if __name__ == '__main__': main()