import gradio as gr
import boto3
import os

hf_token = os.environ.get("HF_TOKEN")
m=gr.load("imcapsule/tasomi-capsule", src="models",hf_token=hf_token)

def detect_language(text):
    # Initialize the Comprehend client
    comprehend = boto3.client('comprehend', region_name='ap-northeast-2')
    # Call DetectDominantLanguage API
    response = comprehend.detect_dominant_language(Text=text)
    # Extract the detected language
    detected_language = response['Languages'][0]['LanguageCode']
    return detected_language

def translate_and_predict(text):
    """Translates text and generates an image using Stable Diffusion."""
    source_language_code=detect_language(text)
    # Translate input text
    translate = boto3.client('translate', region_name='ap-northeast-2')
    target_language_code="en"
    print("source_language_code:" , source_language_code)
    translation_result = translate.translate_text(Text=text, SourceLanguageCode=source_language_code, TargetLanguageCode=target_language_code)
    translated_text = translation_result.get('TranslatedText')
    print("translated_text:" , translated_text)
    image_path=m(translated_text)
    return image_path

# Define the Gradio interface
iface = gr.Interface(
    fn=translate_and_predict,  # Since we're only displaying an image, there's no function to call
    inputs=["text"],  # Input: text, source language, target language
    outputs="image",  # Output: generated image
    title="Image Viewer",
)

# Launch the interface
iface.launch()