Update app.py

app.py

@@ -1,89 +1,55 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-from translator import translate
+import requests
 
-def respond(
-    message,
-    history: list[dict[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-    hf_token: gr.OAuthToken,
-):
-    """
-    For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-    """
-    client = InferenceClient(token=hf_token.token, model="openai/gpt-oss-20b")
+HF_TOKEN = hf_token.token  # ganti tokenmu
 
-    messages = [{"role": "system", "content": system_message}]
-
-    messages.extend(history)
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-chatbot = gr.ChatInterface(
-    respond,
-    type="messages",
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    chatbot.render()
-
-# ===== Translator =====
 def translate_ui(text, direction):
-    return translate(text, direction)
-
-# ===== Layout Gradio =====
-with gr.Blocks() as demo:
-    with gr.Sidebar():
-        gr.LoginButton()
-    
-    with gr.Tabs():
-        with gr.Tab("Chatbot"):
-            chatbot.render()
-        
-        with gr.Tab("Translator"):
-            input_text = gr.Textbox(lines=4, label="Input")
-            direction = gr.Dropdown(["ID → EN", "EN → ID"], label="Direction")
-            output_text = gr.Textbox(label="Output")
-            translate_btn = gr.Button("Translate")
-            translate_btn.click(fn=translate_ui, inputs=[input_text, direction], outputs=output_text)
+    try:
+        if not text.strip():
+            return "Masukkan teks untuk diterjemahkan"
+
+        if direction == "ID → EN":
+            model = "Helsinki-NLP/opus-mt-id-en"
+        else:
+            model = "Helsinki-NLP/opus-mt-en-id"
+
+        url = f"https://api-inference.huggingface.co/models/{model}"
+        headers = {"Authorization": f"Bearer {HF_TOKEN}"}
+        payload = {"inputs": text}
+
+        response = requests.post(url, headers=headers, json=payload, timeout=20)
+
+        if response.status_code == 200:
+            data = response.json()
+            # HF API translation biasanya outputnya list of dict
+            if isinstance(data, list) and "translation_text" in data[0]:
+                return data[0]["translation_text"]
+            else:
+                return "Error: Model tidak mengembalikan hasil"
+        else:
+            return f"API Error: {response.status_code} - {response.text}"
+
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🌐 Translator ID-EN (Hugging Face API)")
+
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(label="Input Text", lines=3, placeholder="Masukkan teks...")
+            direction = gr.Radio(["ID → EN", "EN → ID"], value="ID → EN", label="Direction")
+            translate_btn = gr.Button("🔍 Translate", variant="primary")
+
+        with gr.Column():
+            output_text = gr.Textbox(label="Hasil Terjemahan", lines=3, interactive=False)
+
+    translate_btn.click(
+        fn=translate_ui,
+        inputs=[input_text, direction],
+        outputs=output_text
+    )
 
 if __name__ == "__main__":
     demo.launch()