import gradio as gr
from flores import code_mapping
from functools import lru_cache
import openai  # 用于调用外部API

code_mapping = dict(sorted(code_mapping.items(), key=lambda item: item[0]))
flores_codes = list(code_mapping.keys())
target_languages = flores_codes  # 简化列表

# 假设openai_client已定义，例如：


@lru_cache(maxsize=100)
def translate(text: str, src_lang: str, tgt_lang: str):
    if not src_lang:
        raise gr.Error("The source language is empty! Please choose it in the dropdown list.")
    if not tgt_lang:
        raise gr.Error("The target language is empty! Please choose it in the dropdown list.")
    return _translate(text, src_lang, tgt_lang)

def _translate(text: str, src_lang: str, tgt_lang: str):
    prompt = f"Translate the following text from {src_lang} to {tgt_lang}: {text}"
    openai_client = openai.OpenAI(base_url="https://ssapi.cppbear.site/v1", api_key="sk-5VFSx79t3fLQk4BtN68WTeeRckZ12CONElR7RsK39zrQysji")
    response = openai_client.chat.completions.create(
        model="gemini-2.5-flash",  # 如gpt-3.5-turbo或其他兼容模型
        messages=[{"role": "user", "content": prompt}],
        max_tokens=30240,
        temperature=0.0
    )
    print(response)
    return response.choices[0].message.content.strip()

description = """
<div style="text-align: center;">
    <img src="https://github.com/user-attachments/assets/c42e675e-497c-4508-8bb9-093ad4d1f216" alt="UNESCO Meta Hugging Face Banner" style="max-width: 800px; width: 100%; margin: 0 auto;">
    <h1 style="color: #0077be;">Seed-X, powered by Bytedance</h1>
</div>
We are excited to introduce Seed-X, a powerful series of open-source multilingual translation language models, including an instruction model, a reinforcement learning model, and a reward model. It pushes the boundaries of translation capabilities within 7 billion parameters. We develop Seed-X as an accessible, off-the-shelf tool to support the community in advancing translation research and applications:
"""
disclaimer = """
We are excited to introduce Seed-X, a powerful series of open-source multilingual translation language models, including an instruction model, a reinforcement learning model, and a reward model. It pushes the boundaries of translation capabilities within 7 billion parameters. We develop Seed-X as an accessible, off-the-shelf tool to support the community in advancing translation research and applications
"""

examples_inputs = [["Seed-X is indeed a good translation model ","English","Chinese"],]

with gr.Blocks() as demo:
    gr.Markdown(description)
    with gr.Row():
        src_lang = gr.Dropdown(label="Source Language", choices=flores_codes)
        target_lang = gr.Dropdown(label="Target Language", choices=target_languages)
    with gr.Row():
        input_text = gr.Textbox(label="Input Text", lines=6)
    with gr.Row():
        btn = gr.Button("Translate text")
    with gr.Row():
        output = gr.Textbox(label="Output Text", lines=6)
    btn.click(
        translate,
        inputs=[input_text, src_lang, target_lang],
        outputs=output,
    )
    examples = gr.Examples(examples=examples_inputs,inputs=[input_text, src_lang,target_lang], fn=translate, outputs=output, cache_examples=True)
    with gr.Row():
        gr.Markdown(disclaimer)
demo.launch()