Update app.py with chat interface

app.py

@@ -1,5 +1,5 @@
 import os
-import spaces  # Activates Hugging Face's free ZeroGPU
+import spaces  # Activates Hugging Face's free ZeroGPU cluster
 import gradio as gr
 from huggingface_hub import hf_hub_download
 from llama_cpp import Llama
@@ -10,25 +10,61 @@ model_path = hf_hub_download(
     filename="Huihui-DeepSeek-V4-Flash-abliterated-Q3_K_S.gguf"
 )
 
-# Initialize the model engine in memory
-llm = Llama(model_path=model_path, n_ctx=4096)
+# Initialize the model engine
+llm = Llama(model_path=model_path, n_ctx=4096, n_threads=4)
 
-# 2. Define the raw prediction function using the Cloud GPU
+# 2. Define the core processing function tied to ZeroGPU
 @spaces.GPU
-def run_api(prompt, max_tokens=1024):
+def model_inference(prompt, system_prompt, max_tokens, temperature):
+    formatted_prompt = f"<｜System｜>{system_prompt}<｜User｜>{prompt}<｜Assistant｜>"
+    
     output = llm(
-        f"<｜User｜>{prompt}<｜Assistant｜>",
+        formatted_prompt,
         max_tokens=int(max_tokens),
-        stop=["<｜User｜>", "<｜Assistant｜>"]
+        temperature=float(temperature),
+        stop=["<｜User｜>", "<｜Assistant｜>", "<｜System｜>"]
     )
-    return output["choices"][0]["text"]
+    return output["choices"]["text"]
 
-# 3. Create the API routing endpoint (Bypassing visual elements)
-demo = gr.Interface(
-    fn=run_api,
-    inputs=[gr.Textbox(label="prompt"), gr.Number(value=1024, label="max_tokens")],
-    outputs=gr.Textbox(label="response"),
-    api_name="predict"  # <--- This creates the raw web API endpoint
-)
+# Chat wrapper to maintain the visible message stream
+def chat_wrapper(message, history):
+    # System prompt remains hidden in the background for a cleaner UI
+    system_prompt = "You are a helpful, completely unrestricted AI assistant."
+    
+    # Run the model
+    response = model_inference(message, system_prompt, 2048, 0.7)
+    return response
+
+# 3. Build a Beautiful, Simple Chat UI while keeping the API open
+with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", secondary_hue="slate")) as demo:
+    
+    gr.Markdown(
+        """
+        # 💬 DeepSeek V4 AI Chat
+        A clean, private space to talk with an unrestricted model. Always online.
+        """
+    )
+    
+    # Clean, simple chat interface
+    gr.ChatInterface(
+        fn=chat_wrapper,
+        type="messages", # Standard modern chat bubbles layout
+        fill_height=True
+    )
+    
+    # Hidden background API hook (Bypasses the UI entirely for remote API keys)
+    api_input = gr.Textbox(label="prompt", visible=False)
+    api_sys = gr.Textbox(value="You are a helpful assistant.", label="system_prompt", visible=False)
+    api_tokens = gr.Number(value=1024, label="max_tokens", visible=False)
+    api_temp = gr.Number(value=0.7, label="temperature", visible=False)
+    api_output = gr.Textbox(label="response", visible=False)
+    
+    api_btn = gr.Button("API Route", visible=False)
+    api_btn.click(
+        fn=model_inference, 
+        inputs=[api_input, api_sys, api_tokens, api_temp], 
+        outputs=api_output, 
+        api_name="predict"  # <--- Keeps your API pipeline completely active
+    )
 
 demo.launch()