Create app.py

app.py

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+import torch
+import gradio as gr
+from transformers import pipeline
+import json
+
+# model_path = "C:\\Users\\abdul\\Documents\\genaiproj\\genai\\Models\models--facebook--nllb-200-distilled-600M\\snapshots\\f8d333a098d19b4fd9a8b18f94170487ad3f821d"
+text_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", torch_dtype=torch.bfloat16)
+# text_translator = pipeline("translation", model=model_path, torch_dtype=torch.bfloat16)
+
+# with open('C:\\Users\\abdul\\Documents\\genaiproj\\genai\\Files\\language.json', 'r') as file:
+with open('language.json', 'r') as file:
+
+    language_data = json.load(file)
+
+def get_flores_code_from_language(language_name):
+    for entry in language_data:
+        if entry["Language"].lower() == language_name.lower():
+            return entry["FLORES-200 code"]
+    return "Language not found."
+
+def translate_text(text, destination_language):
+    # text = input("Enter the text to translate: ")
+    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()
+
+# demo = gr.Interface(fn=summary, inputs="text", outputs="text")
+
+demo = gr.Interface(
+    fn=translate_text, 
+    inputs=[gr.Textbox(label="Input text to translate", lines=6), gr.Dropdown(["German", "French", "Tamil", "Romanian", "Arabic"], label="Select Destination Language")], 
+    outputs=[gr.Textbox(label="Translated text", lines=4)], 
+    title="Multilanguage Translator", 
+    theme="soft",
+    description="Translate text to any language in seconds!")
+    
+demo.launch(share=True)