Create app.py

app.py

@@ -1,26 +1,20 @@
 import gradio as gr
 from langchain.chat_models import ChatOpenAI
-!pip install groq
-!pip install langchain-groq
-!pip install langchain
-!pip install gradio
-!pip install huggingface_hub
-!pip install langchain-community
-from langchain.chat_models import ChatOpenAI
-
-
-
 
+# Ensure you have the necessary imports and installations
+# If you're using Groq AI, make sure to import it correctly
+# from groq import Groq  # Uncomment if using Groq
 
+# Initialize your model here (ensure you have the correct model setup)
+# For example, if using Groq:
+# client = Groq(api_key="YOUR_API_KEY")
 
 with gr.Blocks() as iface:
-  
     gr.Markdown("# Mr AI")
     gr.Markdown("Hi there! I'm your friendly assistant. Ask me anything, and I'll do my best to help! (By Thirumoorthi.A)")
 
     chat_history_output = gr.Chatbot(label="Chat History", height=400)
 
-    
     with gr.Row():
         message_input = gr.Textbox(label="Your Question", placeholder="Type your question here...", lines=2)
         submit_btn = gr.Button("Submit")
@@ -28,19 +22,17 @@ with gr.Blocks() as iface:
 
     def respond(message, chat_history):
         chat_history.append(("USER", message))  
-        response = llm_chain.run(input=message)
+        # Replace this line with your model's response logic
+        response = "This is a placeholder response."  # Replace with actual model call
+        # If using Groq, it might look like:
+        # response = client.chat.completions.create(messages=[{"role": "user", "content": message}])
         chat_history.append(("Assistant", response)) 
         return "", chat_history  
 
-    
     def clear_chat():
         return []  
 
-    
-
     submit_btn.click(respond, inputs=[message_input, chat_history_output], outputs=[message_input, chat_history_output])
     clear_btn.click(clear_chat, outputs=chat_history_output)
-    
 
 iface.launch()
-