import os
import gradio as gr
from openai import OpenAI

client=OpenAI(base_url=os.getenv('OPENAI_BASE_URL'),api_key=os.getenv('OPENAI_API_KEY'))

def explain(input: str, lang: str):
    prompt=f'as a language expert, explain how to express "{input}" in {lang}, answer in plain text concisely, if has some other expressions or examples can be improved understand, append it after a separator "-----".'
    res=client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role":"user","content":prompt}],
    )
    print(res)
    return res.choices[0].message.content

_allow_langs=["English", "Chinese", "Japanese"]

demo = gr.Interface(
    fn=explain,
    inputs=[
        gr.Textbox(label="Concept"),
        gr.Dropdown(label="Language", choices=_allow_langs, value="English"),
    ],
    outputs=[
        'text',
    ],
    title="Explainer",
    description="an easy way to explain a concept in other language, get a better expression.",
    head='<meta name="description" content="explain a concept in other language, get a better expression.">',
)

# with gr.Blocks() as demo:
#     gr.Markdown('# concept explain')

#     with gr.Row():
#         with gr.Column():
#             explain_input=gr.Textbox(label="Concept")
#             explain_lang=gr.Dropdown(label="Language", choices=_allow_langs, value=_allow_langs[0])
#             explain_btn=gr.Button("Run", variant="primary")
#         with gr.Column():
#             explain_result=gr.Textbox(label="Result")

#     explain_btn.click(fn=explain, inputs=[explain_input, explain_lang], outputs=[explain_result])

if __name__=="__main__":
    demo.launch()