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import gradio as gr | |
import subprocess | |
import openai | |
import time | |
import re | |
def translate(text_input, openapi_key): | |
openai.api_key = openapi_key | |
text_list = text_input.split('\n')[8:] | |
print(text_list) | |
reply = [] | |
for i in range(0,len(text_list)+9,10): | |
content = """What do these sentences about Hugging Face Transformers (a machine learning library) mean in Korean? Please do not translate the word after a π€ emoji as it is a product name. Please ignore the video and image and translate only the sentences I provided. Ignore the contents of the iframe tag. | |
```md | |
%s"""%'\n'.join(text_list[i:i+10]) | |
chat = openai.ChatCompletion.create( | |
model = "gpt-3.5-turbo-0301", messages=[ | |
{"role": "system", | |
"content": content},]) | |
print("μ§λ¬Έ") | |
print(content) | |
print("μλ΅") | |
print(chat.choices[0].message.content) | |
reply.append(chat.choices[0].message.content) | |
time.sleep(20) | |
return reply | |
inputs = [ | |
gr.inputs.Textbox(lines=2, label="Input Open API Key"), | |
gr.inputs.File(label="Upload MDX File") | |
] | |
outputs = gr.outputs.Textbox(label="Translation") | |
def translate_with_upload(text, file): | |
openapi_key = text | |
if file is not None: | |
text_input = file.read().decode('utf-8') | |
# ν μ€νΈμμ μ½λ λΈλ‘μ μ κ±°ν©λλ€. | |
text_input = re.sub(r'```.*?```', '', text_input, flags=re.DOTALL) | |
text_input = re.sub(r'^\|.*\|$\n?', '', text_input, flags=re.MULTILINE) | |
# ν μ€νΈμμ λΉ μ€μ μ κ±°ν©λλ€. | |
text_input = re.sub(r'^\n', '', text_input, flags=re.MULTILINE) | |
text_input = re.sub(r'\n\n+', '\n\n', text_input) | |
return translate(text_input, openapi_key) | |
prompt_translate = gr.Interface( | |
fn=translate_with_upload, | |
inputs=inputs, | |
outputs=outputs, | |
title="ChatGPT Korean Prompt Translation", | |
description="Translate your text into Korean using the GPT-3 model.", | |
theme="compact" | |
) | |
prompt_translate.launch() | |