Create app-py

app-py

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+import gradio as gr
+from transformers import pipeline
+
+# Chargement des pipelines
+fr_en_nllb_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", src_lang="fra_Latn", tgt_lang="eng_Latn")
+en_fr_nllb_translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", src_lang="eng_Latn", tgt_lang="fra_Latn")
+en_fr_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-en-fr")
+fr_en_translator = pipeline("translation", model="Helsinki-NLP/opus-mt-fr-en")
+# Fonction de traduction
+def translate_text(text, model_choice):
+    if model_choice == "NLLB-200-FR-EN (facebook)":
+        result = fr_en_nllb_translator(text.strip())[0]["translation_text"]
+    elif model_choice == "NLLB-200-EN-FR (facebook)":
+        result = en_fr_nllb_translator(text.strip())[0]["translation_text"]
+    elif model_choice == "Opus-MT-EN-FR (Helsinki-NLP)":
+        result = en_fr_translator(text.strip())[0]["translation_text"]
+    else:
+        result = fr_en_translator(text.strip())[0]["translation_text"]
+    return result
+
+# Interface Gradio
+demo = gr.Interface(
+    fn=translate_text,
+    inputs=[
+        gr.Textbox(label="Texte à traduire", placeholder="Entrez du texte en français ici..."),
+        gr.Radio(["NLLB-200-FR-EN (facebook)", "NLLB-200-EN-FR (facebook)", 
+                  "Opus-MT-FR-EN (Helsinki-NLP)","Opus-MT-EN-FR (Helsinki-NLP)"], label="Choisissez le modèle")
+    ],
+    outputs=gr.Textbox(label="Texte traduit"),
+    title="Traduction FR-EN & EN-FR"
+)
+
+demo.launch()