Create app.py

app.py

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+import torch
+import json
+import gradio as gr
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+# model_path = "../Models/models--facebook--nllb-200-distilled-600M/snapshots/f8d333a098d19b4fd9a8b18f94170487ad3f821d"
+
+# text_translator = pipeline("translation", model=model_path, torch_dtype=torch.bfloat16)
+
+pipe = pipeline("translation", model="facebook/nllb-200-distilled-600M")
+
+# text = "Hello friends, How are you?"
+
+# translation = text_translator(text, src_lang="eng_Latn", tgt_lang="deu_Latn")
+
+with open('language.json', 'r') as file:
+    language_data = json.load(file)
+
+def get_FLORES_code_from_language(language):
+    for entry in language_data:
+        if entry['Language'].lower() == language.lower():
+            return entry['FLORES-200 code']
+    return None
+
+def translate_text(text, destination_language):
+    dest_code = get_FLORES_code_from_language(destination_language)
+    translation = text_translator(text, src_lang="eng_Latn", tgt_lang=dest_code)
+    return translation[0]["translation_text"]
+
+gr.close_all()
+
+# print(translate_text(text, "Hindi"))
+demo = gr.Interface(fn=translate_text,
+                    inputs=[gr.Textbox(label="Input text to translate",lines=6), gr.Dropdown(["German", "French", "Hindi", "Romanian", "Marathi"], label="Select Destination Language")],
+                    outputs=[gr.Textbox(label="Translated text",lines=4)],
+                    title="@GenAILearniverse Project 4: Multi language translator",
+                    description="THIS APPLICATION WILL BE USED TO TRNSLATE ANY ENGLIST TEXT TO MULTIPLE LANGUAGES.")
+
+demo.launch()
+