Update app.py

app.py

@@ -1,55 +1,89 @@
 import gradio as gr
-import requests
+from huggingface_hub import InferenceClient
+from translator import translate
 
-HF_TOKEN = hf_token.token  # ganti tokenmu
+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")
 
+    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):
-    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
-    )
+    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)
 
 if __name__ == "__main__":
     demo.launch()