Create app.py

app.py

@@ -0,0 +1,59 @@
+import gradio as gr
+from transformers import pipeline
+import torch
+
+# Load the model and tokenizer
+model_name = 'bilalfaye/nllb-200-distilled-600M-wo-fr-en'
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+# Define the translation pipeline
+translator = pipeline(
+    "translation",
+    model=model_name,
+    device=device
+)
+
+
+# Define the translation function
+def translate_chat(message, history, source_language, target_language):
+    # Mapping of languages to model codes
+    lang_map = {
+        "Wolof": "wol_Latn",
+        "English": "eng_Latn",
+        "French": "fra_Latn"
+    }
+    
+    if source_language not in lang_map or target_language not in lang_map:
+        return "Invalid language selection."
+    
+    src_lang = lang_map[source_language]
+    tgt_lang = lang_map[target_language]
+    
+    if src_lang == tgt_lang:
+        return "Source and target languages must be different."
+    
+    # Perform the translation
+    translation = translator(message, src_lang=src_lang, tgt_lang=tgt_lang)
+    return translation[0]["translation_text"]
+
+# Gradio chat interface
+interface = gr.ChatInterface(
+    fn=translate_chat,
+    additional_inputs=[
+        gr.Dropdown(
+            choices=["Wolof", "French", "English"],
+            label="Source Language",
+            value="Wolof",  # Default value
+        ),
+        gr.Dropdown(
+            choices=["Wolof", "French", "English"],
+            label="Target Language",
+            value="English",  # Default value
+        ),
+    ],
+    title="Wolof ↔ French ↔ English Translator",
+    description="Select the source and target languages (in the bottom) to translate between Wolof, French, and English.",
+)
+
+# Launch the app
+interface.launch(debug=True, share=True)