# from responses import start import gradio as gr from language_directions import * from transformers import pipeline from examples import example_sentences source_lang_dict = get_all_source_languages() target_lang_dict = {} source_languages = source_lang_dict.keys() def get_auto_detect_source_dropdown(input_text): source, _ = auto_detect_language_code(input_text) language_name = get_name_from_iso_code(source) source_dropdown_text = "Detected - " + language_name update_source_languages_dict(source_lang_dict, source_dropdown_text) source_language_dropdown = gr.Dropdown(choices=source_languages, value=source_dropdown_text, label="Source Language") return source_language_dropdown, language_name def get_target_dropdown(source_language_name, input_text): global target_lang_dict target_lang_dict, source_language = get_target_languages(source_lang_dict[source_language_name], input_text) target_languages = list(target_lang_dict.keys()) default_target_value = None if "English" in target_languages or "english" in target_languages: default_target_value = "English" else: default_target_value = target_languages[0] target_dropdown = gr.Dropdown(choices=target_languages, value=default_target_value, label="Target Language") return target_dropdown def get_dropdown_value(dropdown): if isinstance(dropdown, gr.Dropdown): dropdown_value = dropdown.constructor_args.get('value') elif isinstance(dropdown, str): dropdown_value = dropdown return dropdown_value def get_dropdowns(source_dropdown, input_text): source_language_name = get_dropdown_value(source_dropdown) if input_text and source_language_name == "Auto Detect" or source_language_name.startswith("Detected"): source_dropdown, source_language_name = get_auto_detect_source_dropdown(input_text) target_dropdown = get_target_dropdown(source_language_name=source_language_name, input_text=input_text) return source_dropdown, target_dropdown def input_changed(source_language_dropdown, input_text=""): return get_dropdowns(source_dropdown=source_language_dropdown, input_text=input_text) def translate(input_text, source, target): source_readable = source if source == "Auto Detect" or source.startswith("Detected"): source, _ = auto_detect_language_code(input_text) if source in source_lang_dict.keys(): source = source_lang_dict[source] target_lang_dict, _ = get_target_languages(source) try: target = target_lang_dict[target] model = f"Helsinki-NLP/opus-mt-{source}-{target}" pipe = pipeline("translation", model=model) translation = pipe(input_text) return translation[0]['translation_text'], "" except KeyError: return "", f"Error: Translation direction {source_readable} to {target} is not supported by Helsinki Translation Models" with gr.Blocks() as demo: gr.HTML("""