Update app.py

app.py

@@ -1,15 +1,13 @@
 import gradio as gr
 import requests
-import io
-import contextlib
 import os
 
 # API key from Hugging Face Space secret
 API_KEY = os.environ.get("API_KEY")
 API_URL = "https://api.deepseek.com/v1/chat/completions"  # Replace if different
 
-# DeepSeek V3 AI explanation function
-def deepseek_reply(code_input):
+# DeepSeek V3 Chatbot function
+def deepseek_chat(user_message, chat_history):
     if not API_KEY:
         return "❌ API Key not found. Please set API_KEY in HF Space secrets."
 
@@ -17,56 +15,52 @@ def deepseek_reply(code_input):
         "Authorization": f"Bearer {API_KEY}",
         "Content-Type": "application/json"
     }
+
+    # Append the user message to the conversation history
+    chat_history.append({"role": "user", "content": user_message})
+
     payload = {
         "model": "deepseek-coder:33b",
-        "messages": [
-            {"role": "system", "content": "You are a helpful coding assistant."},
-            {"role": "user", "content": code_input}
-        ],
-        "temperature": 0.2,
+        "messages": chat_history,
+        "temperature": 0.7,
         "stream": False
     }
 
     try:
+        # Make request to the DeepSeek V3 API for the chatbot response
         response = requests.post(API_URL, headers=headers, json=payload)
         result = response.json()
-        return result["choices"][0]["message"]["content"]
-    except Exception as e:
-        return f"❌ DeepSeek Error: {e}"
+        
+        # Extract the AI response
+        ai_message = result["choices"][0]["message"]["content"]
+        
+        # Add the AI's response to the chat history
+        chat_history.append({"role": "assistant", "content": ai_message})
 
-# Code execution preview function
-def execute_code(code_input):
-    buffer = io.StringIO()
-    try:
-        with contextlib.redirect_stdout(buffer):
-            exec(code_input, {})
-        return buffer.getvalue()
+        return ai_message, chat_history
     except Exception as e:
-        return f"❌ Execution Error: {e}"
+        return f"❌ DeepSeek Error: {e}", chat_history
 
-# Gradio UI setup
+# Gradio UI setup for the chatbot
 with gr.Blocks(css="footer {display: none !important}") as demo:
     gr.Markdown("""
-    # ⚡ Sparkle Code Lab — Powered by DeepSeek V3
-    ### Live Code Explanation & Execution
+    # 🤖 DeepSeek V3 Chatbot
+    ### Chat with the AI powered by DeepSeek V3!
     
-    This is your space to explore code and get real-time explanations and outputs.
+    Type a message and start chatting with the AI.
     """, elem_id="header")
     
     with gr.Row():
         with gr.Column(scale=5):
-            # Code input box
-            code = gr.Code(label="✍️ Paste your code or question", language="python", lines=20)
+            # Text input for user message
+            user_message = gr.Textbox(label="Your Message", placeholder="Type something...", interactive=True)
         with gr.Column(scale=2):
-            # DeepSeek AI output
-            deepseek_out = gr.Markdown(label="🧠 AI Explanation (DeepSeek)", elem_id="ai-output")
-            # Execution output
-            exec_out = gr.Textbox(label="📤 Code Output", lines=10, interactive=False, elem_id="code-output")
-            # Run button
-            run_btn = gr.Button("🚀 Run & Explain", elem_id="run-button")
-
-    # Action when button is clicked
-    run_btn.click(fn=deepseek_reply, inputs=code, outputs=deepseek_out)
-    run_btn.click(fn=execute_code, inputs=code, outputs=exec_out)
+            # Chat history and bot response
+            chatbot_output = gr.Chatbot(label="Chat History", elem_id="chatbot-output")
+            # Submit button
+            submit_button = gr.Button("Send", elem_id="send-button")
+    
+    # Define the action when the button is clicked
+    submit_button.click(fn=deepseek_chat, inputs=[user_message, chatbot_output], outputs=[chatbot_output, chatbot_output])
 
 demo.launch()