Create app.py

app.py

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+import json
+
+import gradio as gr
+import torch
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline(
+    "translation", 
+    model="facebook/nllb-200-distilled-600M",
+    torch_dtype=torch.bfloat16)
+
+# Load the JSON data from the file
+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)
+    if dest_code is None:
+        return "Invalid 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 for translation",lines=6), gr.Dropdown(
+                        ["Arabic", "Afrikaans", "Bengali", "Greek", "Estonian", "Portuguese", "Spanish"], 
+                        label="Select Destination Language")
+                        ],
+                    outputs=[gr.Textbox(label="Translated Text",lines=4)],
+                    title="@caesar-2series: Multilingual Language Interpreter",
+                    description="Translations from English into a few foreign languages")
+demo.launch()