import openai import gradio import os import re openai.api_key = os.environ.get("API_TOKEN") messages = [{"role": "system", "content": "You are an education expert who can correct essays. You are bilingual in English and Japanese"}] MAX_TOKENS = 4096 MAX_HISTORY = 1 def CustomChatGPT(user_input): global messages essay_keywords = ["essay", "エッセイ", "論文"] action_keywords = ["write", "make", "create", "生成", "作成", "書く"] if any(re.search(f"{action_kw}.*{essay_kw}", user_input.lower()) for action_kw in action_keywords for essay_kw in essay_keywords): return "I'm sorry, I cannot write an essay for you." # Clear the messages list before adding new messages messages = [{"role": "system", "content": "You are an education expert who can correct English writing. You are bilingual in English and Japanese"}] user_message = {"role": "user", "content": f"Step 1, find errors on the composition's logic. Focus mainly on how well the sentences are connected to each other and proper use of discourse markers. You do not need to worry about grammatical mistakes. You do not have to correct the composition either. Step 3, Explain in detail all the errors from what I originally wrote. Put each explanation in a bullet point. You do not need to edit the essay, just explain everything wrong with it: [{user_input}]"} messages.append(user_message) while True: response = openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=messages ) total_tokens = response['usage']['total_tokens'] if total_tokens < MAX_TOKENS: break ChatGPT_reply = response["choices"][0]["message"]["content"] messages.append({"role": "assistant", "content": ChatGPT_reply}) return ChatGPT_reply # Add text instructions on top of the input and output boxes input_text = "ここに訂正してほしい英語の作文を置いてください。そして「Submit」を押してください:" output_text = "訂正と説明はここに表示されます:" instructions = "このアプリケーションは、文法と綴りをチェックするために使用できます。アプリは、修正した作文を提供し、それに続いて修正の説明を示します。アプリは、1つのパラグラフずつ入力する場合に最適に機能します。例えば、3つのパラグラフから成る作文をチェックしたい場合は、それぞれのパラグラフを「Submit」してください。つまり、プログラムを3回実行し、各パラグラフごとに1回ずつ実行してください。" # Modify the Gradio interface to include the text instructions and image demo = gradio.Interface(fn=CustomChatGPT, inputs=gradio.inputs.Textbox(lines=5, label=input_text), outputs=gradio.outputs.Textbox(label=output_text), title="Teacher Jihan's Checking Assistant", description=instructions) demo.launch(share=False, debug=True)