Update app.py

app.py

@@ -1,64 +1,48 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-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("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    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,
-    ):
-        token = message.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
-"""
-demo = gr.ChatInterface(
-    respond,
-    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)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+import time
+from datetime import datetime
+
+tasks = []
+
+def add_task(message, history):
+    if not message:
+        return "", history
+    
+    history = history or []
+    current_time = datetime.now().strftime("%Y-%m-%d %H:%M")
+    
+    if message.startswith("/task"):
+        task = message[6:].strip()
+        tasks.append({
+            "task": task,
+            "created": current_time,
+            "status": "pending"
+        })
+        response = f"✅ Task added: {task}\nCreated at: {current_time}"
+    elif message == "/list":
+        if not tasks:
+            response = "No tasks found."
+        else:
+            response = "📋 Tasks:\n" + "\n".join([
+                f"{i+1}. {task['task']} ({task['status']}) - {task['created']}"
+                for i, task in enumerate(tasks)
+            ])
+    else:
+        response = "Commands:\n/task [description] - Add new task\n/list - View all tasks"
+    
+    history.append((message, response))
+    return "", history
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 📝 TaskMate")
+    gr.Markdown("### Task Management Made Simple")
+    
+    chatbot = gr.Chatbot(height=400)
+    msg = gr.Textbox(
+        placeholder="Type /task [description] to add a task, or /list to view tasks",
+        label="Input"
+    )
+    
+    msg.submit(add_task, [msg, chatbot], [msg, chatbot])
+
+demo.launch()