generate_paragraph_evaluate_button = gr.Button("Save and Evaluate")

{ "original": "# original_sentence1", "Correction": "#correction_1", "Explanation": "#explanation_1(in_traditional_chinese)" },

- When explaining, use Traditional Chinese (Taiwan, 繁體中文) for clarity. But others in English.

, show_copy_button=True

, copyable=True

outputs=[

save

transformers

response = OPEN_AI_CLIENT.audio.speech.create(

audio_output

paragraph_save_output = gr.Textbox(label="Save and Share")

- When explaining, use Traditional Chinese (Taiwan, 繁體中文) for clarity.

paragraph_refine_output = gr.Textbox(label="Refine Paragraph 段落改善建議")

Evaluate

del xx

outputs=correct_grammatical_spelling_errors_output

def generate_paragraph_evaluate(paragraph, user_generate_paragraph_evaluate_prompt):

paragraph_evaluate_output

paragraph_evaluate_output

refactor

outputs=conclusion_sentence_output

def generate_paragraph(topic_sentence, supporting_sentences, conclusion_sentence):

gr.Markdown("## 6. Conclusion sentence 結論句")

no more explanation either no more extra non-relation sentences.

supporting_sentences_output = gr.Textbox(label="Generated Supporting Sentences 支持句")

def generate_supporting_sentences(model, max_tokens, sys_content, scenario, eng_level, topic, points, topic_sentence, user_generate_supporting_sentences_prompt):

import json

content = parse_and_display_topic_sentences(json_content)

"response_format": response_format

topic_sentence_output

def generate_topic_sentences(model, max_tokens, sys_content, scenario, eng_level, topic, points, user_generate_topic_sentences_prompt):

generate_topics

default_generate_points_prompt = """

def generate_points(model, max_tokens, sys_content, scenario, eng_level, topic, user_generate_points_prompt):

max_tokens = gr.Slider(minimum=50, maximum=4000, value=1000, label="Max Tokens")

Markdown

def generate_topic_sentences(model, max_tokens, sys_content, scenario, eng_level, user_generate_topics_prompt):

user_generate_topics_prompt = gr.Textbox(label="User Prompt", value="Give me 10 topics relevant to Scenario, for a paragraph. Just the topics, no explanation, use simple English language. Make sure the vocabulary you use is at english level.")

topic_output

openai>=1.0.0

rename

openai

import os

from openai import OpenAI

OPEN_AI_CLIENT

OPENAI_CLIENT

OPEN_AI_KEY = os.getenv("OPEN_AI_KEY")

init

initial commit