Update app.py

app.py

@@ -1,34 +1,97 @@
-import os, time, io
-import gradio as gr
+import os
 from huggingface_hub import InferenceClient
-from PIL import Image
+import gradio as gr
 
-HF_MODEL_ID = os.environ.get("HF_MODEL_ID", "stabilityai/stable-diffusion-x4-upscaler")
+# Initialize the client with the correct provider
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
-client = InferenceClient(token=HF_TOKEN)
+client = InferenceClient(
+    provider="hf-inference",
+    api_key=HF_TOKEN
+)
 
-def call_inference_image(fileobj, scale: int = 2):
-    start = time.time()
-    if hasattr(fileobj, "name"):
-        img_bytes = open(fileobj.name, "rb").read()
-    else:
-        img_bytes = fileobj.read()
-    params = {"scale": int(scale)} if scale else {}
-    res = client.invoke(HF_MODEL_ID, inputs=img_bytes, params=params)
-    latency = time.time() - start
-    if isinstance(res, (bytes, bytearray)):
-        return Image.open(io.BytesIO(res)), f"{latency:.3f}s"
-    return str(res), f"{latency:.3f}s"
+def translate_text(text, src_lang, tgt_lang):
+    """
+    Function to handle translation using the MBART model
+    """
+    if not text.strip():
+        return "Please enter text to translate"
+    
+    try:
+        # Use the translation method with model-specific parameters
+        result = client.translation(
+            text,
+            model="facebook/mbart-large-50-many-to-many-mmt",
+            src_lang=src_lang,  # Source language code
+            tgt_lang=tgt_lang   # Target language code
+        )
+        return result
+        
+    except Exception as e:
+        return f"Error in translation: {str(e)}"
 
-with gr.Blocks() as demo:
-    gr.Markdown("# API-based Upscaler (calls HF Inference API)")
+# Create the Gradio interface
+with gr.Blocks(title="Multilingual Translation Chatbot", theme="soft") as demo:
+    gr.Markdown("# 🌍 Multilingual Translation Chatbot")
+    gr.Markdown("Translate between 50 languages using facebook/mbart-large-50-many-to-many-mmt")
+    
     with gr.Row():
-        inp = gr.Image(type="filepath", label="Upload image")
-        scale = gr.Slider(2, 8, value=2, step=1, label="Scale (requested)")
-    out_img = gr.Image(label="Result")
-    latency = gr.Textbox(label="Latency")
-    btn = gr.Button("Upscale via API")
-    btn.click(call_inference_image, inputs=[inp, scale], outputs=[out_img, latency])
+        with gr.Column():
+            src_lang = gr.Dropdown(
+                choices=[
+                    "ar_AR", "en_XX", "fr_XX", "es_XX", "de_DE", 
+                    "zh_CN", "hi_IN", "ru_RU", "ja_XX", "pt_XX", "it_IT"
+                ],
+                value="ru_RU",
+                label="Source Language Code"
+            )
+            input_text = gr.Textbox(
+                lines=4,
+                placeholder="Enter text to translate...",
+                label="Input Text",
+                value="Меня зовут Вольфганг и я живу в Берлине"
+            )
+        
+        with gr.Column():
+            tgt_lang = gr.Dropdown(
+                choices=[
+                    "ar_AR", "en_XX", "fr_XX", "es_XX", "de_DE", 
+                    "zh_CN", "hi_IN", "ru_RU", "ja_XX", "pt_XX", "it_IT"
+                ],
+                value="en_XX",
+                label="Target Language Code"
+            )
+            output_text = gr.Textbox(
+                lines=4,
+                label="Translation",
+                interactive=False
+            )
+    
+    # Translate button
+    translate_btn = gr.Button("Translate 🌐", variant="primary")
+    translate_btn.click(
+        fn=translate_text,
+        inputs=[input_text, src_lang, tgt_lang],
+        outputs=output_text
+    )
+    
+    # Examples for quick testing
+    gr.Examples(
+        examples=[
+            ["Меня зовут Вольфганг и я живу в Берлине", "ru_RU", "en_XX"],
+            ["Hello, how are you today?", "en_XX", "es_XX"],
+            ["Bonjour, comment ça va?", "fr_XX", "en_XX"],
+            ["今天天气很好", "zh_CN", "en_XX"]
+        ],
+        inputs=[input_text, src_lang, tgt_lang]
+    )
+    
+    # Clear button
+    clear_btn = gr.Button("Clear")
+    clear_btn.click(
+        fn=lambda: ["", "ru_RU", "en_XX", ""],
+        outputs=[input_text, src_lang, tgt_lang, output_text]
+    )
 
+# Launch the interface
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch(share=True)