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# 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("""<html>
<head>
<style>
h1 {
text-align: center;
}
</style>
</head>
<body>
<h1>Open Translate</h1>
</body>
</html>""")
with gr.Row():
with gr.Column():
source_language_dropdown = gr.Dropdown(choices=source_languages,
value="Auto Detect",
label="Source Language")
input_textbox = gr.Textbox(lines=5, placeholder="Enter text to translate", label="Input Text")
with gr.Column():
target_language_dropdown = gr.Dropdown(choices=["English", "French", "Spanish"],
value="English",
label="Target Language")
translated_textbox = gr.Textbox(lines=5, placeholder="", label="Translated Text")
info_label = gr.HTML("")
btn = gr.Button("Translate")
source_language_dropdown.change(input_changed, inputs=[source_language_dropdown, input_textbox], outputs=[source_language_dropdown, target_language_dropdown])
input_textbox.change(input_changed, inputs=[source_language_dropdown, input_textbox], outputs=[source_language_dropdown, target_language_dropdown])
btn.click(translate, inputs=[input_textbox,
source_language_dropdown,
target_language_dropdown],
outputs=[translated_textbox, info_label])
gr.Examples(example_sentences, inputs=[input_textbox])
if __name__ == "__main__":
demo.launch() |