Update app.py

app.py

@@ -95,14 +95,95 @@
 # if __name__ == "__main__":
 #     demo.launch()
 
+# import torch
+# import gradio as gr
+# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+
+# # --- Config ---
+# MODEL_REPO = "Toadoum/ngambay-fr-v1"
+# FR_CODE = "sba_Latn"
+# NG_CODE = "fr_Latn"  # Ngambay (Saba) Latin
+
+# # --- Device selection ---
+# device = 0 if torch.cuda.is_available() else -1
+
+# # --- Load model & tokenizer once ---
+# tokenizer = AutoTokenizer.from_pretrained(MODEL_REPO)
+# model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_REPO)
+
+# translator = pipeline(
+#     task="translation",
+#     model=model,
+#     tokenizer=tokenizer,
+#     device=device,
+# )
+
+# def translate_fr_to_ng(text, max_new_tokens=256, temperature=0.0):
+#     if not text or not text.strip():
+#         return ""
+#     out = translator(
+#         text,
+#         src_lang=FR_CODE,
+#         tgt_lang=NG_CODE,
+#         max_new_tokens=max_new_tokens,
+#         do_sample=temperature > 0,
+#         temperature=temperature if temperature > 0 else None,
+#     )
+#     return out[0]["translation_text"]
+
+# with gr.Blocks(title="Français → Ngambay · Toadoum/ngambay-fr-v1") as demo:
+#     gr.Markdown(
+#         """
+#         # Français → Ngambay (v1)
+#         Model: **Toadoum/ngambay-fr-v1**  
+#         Entrez un texte en français et obtenez la traduction en Ngambay.
+#         """
+#     )
+
+#     with gr.Row():
+#         with gr.Column():
+#             src = gr.Textbox(
+#                 label="Texte source (Français)",
+#                 placeholder="Entrez le texte à traduire…",
+#                 lines=8
+#             )
+#             max_new_tokens = gr.Slider(
+#                 minimum=32, maximum=1024, value=256, step=32,
+#                 label="Max new tokens"
+#             )
+#             temperature = gr.Slider(
+#                 minimum=0.0, maximum=1.0, value=0.0, step=0.05,
+#                 label="Creativity (temperature)"
+#             )
+#             btn = gr.Button("Traduire", variant="primary")
+#         with gr.Column():
+#             tgt = gr.Textbox(
+#                 label="Traduction (Ngambay)",
+#                 lines=8
+#             )
+
+#     btn.click(
+#         fn=translate_fr_to_ng,
+#         inputs=[src, max_new_tokens, temperature],
+#         outputs=[tgt]
+#     )
+
+# if __name__ == "__main__":
+#     demo.launch()
+
+
 import torch
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 
 # --- Config ---
 MODEL_REPO = "Toadoum/ngambay-fr-v1"
-FR_CODE = "sba_Latn"
-NG_CODE = "fr_Latn"  # Ngambay (Saba) Latin
+FR_CODE = "fr_Latn"     # Français
+NG_CODE = "sba_Latn"    # Ngambay (Saba) Latin
+
+# --- Inference params (fixés pour l'utilisateur) ---
+MAX_NEW_TOKENS = 256
+TEMPERATURE = 0.0
 
 # --- Device selection ---
 device = 0 if torch.cuda.is_available() else -1
@@ -118,55 +199,102 @@ translator = pipeline(
     device=device,
 )
 
-def translate_fr_to_ng(text, max_new_tokens=256, temperature=0.0):
+def translate_fr_to_ng(text: str) -> str:
     if not text or not text.strip():
         return ""
     out = translator(
         text,
         src_lang=FR_CODE,
         tgt_lang=NG_CODE,
-        max_new_tokens=max_new_tokens,
-        do_sample=temperature > 0,
-        temperature=temperature if temperature > 0 else None,
+        max_new_tokens=MAX_NEW_TOKENS,
+        do_sample=False,           # TEMPERATURE=0.0 -> deterministic
     )
     return out[0]["translation_text"]
 
-with gr.Blocks(title="Français → Ngambay · Toadoum/ngambay-fr-v1") as demo:
-    gr.Markdown(
-        """
-        # Français → Ngambay (v1)
-        Model: **Toadoum/ngambay-fr-v1**  
-        Entrez un texte en français et obtenez la traduction en Ngambay.
-        """
-    )
+theme = gr.themes.Soft(
+    primary_hue="indigo",
+    radius_size="lg",
+    font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui"]
+).set(
+    body_background_fill="#f7f7fb",
+    button_primary_text_color="#ffffff"
+)
 
-    with gr.Row():
-        with gr.Column():
-            src = gr.Textbox(
-                label="Texte source (Français)",
-                placeholder="Entrez le texte à traduire…",
-                lines=8
-            )
-            max_new_tokens = gr.Slider(
-                minimum=32, maximum=1024, value=256, step=32,
-                label="Max new tokens"
-            )
-            temperature = gr.Slider(
-                minimum=0.0, maximum=1.0, value=0.0, step=0.05,
-                label="Creativity (temperature)"
-            )
-            btn = gr.Button("Traduire", variant="primary")
-        with gr.Column():
-            tgt = gr.Textbox(
-                label="Traduction (Ngambay)",
-                lines=8
+CUSTOM_CSS = """
+.gradio-container {max-width: 980px !important;}
+.header-card { 
+    background: linear-gradient(135deg, #4f46e5 0%, #7c3aed 100%); 
+    color: white; padding: 22px; border-radius: 18px; 
+    box-shadow: 0 10px 30px rgba(79,70,229,.25);
+}
+.header-title { font-size: 26px; font-weight: 800; margin: 0 0 6px 0; }
+.header-sub { opacity: .95; font-size: 14px; }
+.brand { display:flex; align-items:center; gap:10px; }
+.badge { 
+    display:inline-block; background: rgba(255,255,255,.18); 
+    padding: 4px 10px; border-radius: 999px; font-size: 12px; 
+    border: 1px solid rgba(255,255,255,.25);
+}
+.footer-note {
+    margin-top: 8px; color: #64748b; font-size: 12px; text-align: center;
+}
+"""
+
+with gr.Blocks(title="Français → Ngambay · Toadoum/ngambay-fr-v1", theme=theme, css=CUSTOM_CSS, fill_height=True, analytics_enabled=False) as demo:
+    with gr.Column():
+        with gr.Group(elem_classes=["header-card"]):
+            gr.HTML(
+                """
+                <div class="brand">
+                    <div>
+                        <div class="header-title">Français → Ngambay (v1)</div>
+                        <div class="header-sub">Traduction rapide et fidèle pour la langue la plus parlée au Tchad.</div>
+                    </div>
+                    <span class="badge">Modèle&nbsp;: Toadoum/ngambay-fr-v1</span>
+                </div>
+                """
             )
 
-    btn.click(
-        fn=translate_fr_to_ng,
-        inputs=[src, max_new_tokens, temperature],
-        outputs=[tgt]
-    )
+        with gr.Row():
+            with gr.Column(scale=5):
+                src = gr.Textbox(
+                    label="Texte source (Français)",
+                    placeholder="Saisissez votre texte en français…",
+                    lines=8,
+                    autofocus=True
+                )
+                with gr.Row():
+                    btn = gr.Button("Traduire", variant="primary", scale=3)
+                    clear_btn = gr.Button("Effacer", scale=1)
+
+                gr.Examples(
+                    examples=[
+                        ["Bonjour, comment allez-vous aujourd’hui ?"],
+                        ["La réunion de sensibilisation aura lieu demain au centre communautaire."],
+                        ["Merci pour votre participation et votre soutien."],
+                        ["Veuillez suivre les recommandations de santé pour protéger votre famille."]
+                    ],
+                    inputs=[src],
+                    label="Exemples (cliquez pour remplir)"
+                )
+
+            with gr.Column(scale=5):
+                tgt = gr.Textbox(
+                    label="Traduction (Ngambay)",
+                    lines=8,
+                    interactive=False,
+                    show_copy_button=True
+                )
+                meta = gr.Markdown(
+                    f"**Paramètres** : `max_new_tokens={MAX_NEW_TOKENS}`, `temperature={TEMPERATURE}` · "
+                    f"`src_lang={FR_CODE}` → `tgt_lang={NG_CODE}`",
+                    elem_id="meta"
+                )
+
+        gr.Markdown('<div class="footer-note">Astuce : collez un paragraphe complet pour un meilleur contexte.</div>')
+
+    btn.click(translate_fr_to_ng, inputs=src, outputs=tgt)
+    clear_btn.click(lambda: ("", ""), outputs=[src, tgt])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.queue(api_open=False, concurrency_count=4).launch(show_api=False)