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app.py

@@ -1,9 +1,15 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import time
+import threading
 
 # Inference client setup
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Global flag to determine the mode and to handle cancellation
+use_local = False
+stop_inference = False
+
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -11,28 +17,45 @@ def respond(
     max_tokens,
     temperature,
     top_p,
+    use_local_model,
 ):
-    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
+    global use_local, stop_inference
+    use_local = use_local_model
+    stop_inference = False  # Reset cancellation flag
+
+    if use_local:
+        # Simulate local inference
+        time.sleep(2)  # simulate a delay
+        response = "This is a response from the local model."
         yield response
+    else:
+        # API-based inference
+        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,
+        ):
+            if stop_inference:
+                yield "Inference cancelled."
+                break
+            token = message.choices[0].delta.content
+            response += token
+            yield response
+
+def cancel_inference():
+    global stop_inference
+    stop_inference = True
 
 # Custom CSS for a fancy look
 custom_css = """
@@ -94,6 +117,8 @@ demo = gr.ChatInterface(
             step=0.05,
             label="Top-p (nucleus sampling)",
         ),
+        gr.Checkbox(label="Use Local Model", value=False),
+        gr.Button("Cancel Inference", variant="danger", on_click=cancel_inference),
     ],
     css=custom_css,
     title="🌟 Fancy AI Chatbot 🌟",

app_update_title.py

@@ -0,0 +1,104 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# Inference client setup
+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
+
+# Custom CSS for a fancy look
+custom_css = """
+#main-container {
+    background-color: #f0f0f0;
+    font-family: 'Arial', sans-serif;
+}
+
+.gradio-container {
+    max-width: 700px;
+    margin: 0 auto;
+    padding: 20px;
+    background: white;
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    border-radius: 10px;
+}
+
+.gr-button {
+    background-color: #4CAF50;
+    color: white;
+    border: none;
+    border-radius: 5px;
+    padding: 10px 20px;
+    cursor: pointer;
+    transition: background-color 0.3s ease;
+}
+
+.gr-button:hover {
+    background-color: #45a049;
+}
+
+.gr-slider input {
+    color: #4CAF50;
+}
+
+.gr-chat {
+    font-size: 16px;
+}
+
+#title {
+    text-align: center;
+    font-size: 2em;
+    margin-bottom: 20px;
+    color: #333;
+}
+"""
+
+# Define the interface
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message", interactive=True),
+        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)",
+        ),
+    ],
+    css=custom_css,
+    title="🌟 Fancy AI Chatbot 🌟",
+    description="Interact with the AI chatbot using customizable settings below."
+)
+
+if __name__ == "__main__":
+    demo.launch()