Upload app_grad.py

app_grad.py

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+import gradio as gr
+from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
+from langchain_groq import ChatGroq
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+# Initialize Groq Chat model
+chat = ChatGroq(model="gemma2-9b-it", temperature=0.5)
+
+# Initialize session context
+conversation_history = [SystemMessage(content="You are a comedian AI assistant")]
+
+def chatbot_response(user_input):
+    # Append user message
+    conversation_history.append(HumanMessage(content=user_input))
+    
+    # Get model response
+    response = chat.invoke(conversation_history)
+    
+    # Append bot message
+    conversation_history.append(AIMessage(content=response.content))
+    
+    # Format chat history for display
+    chat_log = ""
+    for msg in conversation_history:
+        if isinstance(msg, SystemMessage):
+            chat_log += f"⚙️ *System Role*: {msg.content}\n\n"
+        elif isinstance(msg, HumanMessage):
+            chat_log += f"👤 **User**: {msg.content}\n\n"
+        elif isinstance(msg, AIMessage):
+            chat_log += f"🤖 **Bot**: {msg.content}\n\n"
+    
+    return response.content, chat_log
+
+# Gradio interface layout
+with gr.Blocks() as demo:
+    gr.Markdown("# 🤖 Conversational Q&A Chatbot")
+    gr.Markdown("Chat with a friendly AI powered by Groq’s `gemma2-9b-it` model.")
+
+    with gr.Row():
+        user_input = gr.Textbox(label="Enter your question")
+        submit_btn = gr.Button("Ask")
+
+    response_output = gr.Textbox(label="Response", interactive=False)
+    chat_history = gr.Markdown()
+
+    def handle_submit(input_text):
+        response, history = chatbot_response(input_text)
+        return response, history
+
+    submit_btn.click(fn=handle_submit, inputs=user_input, outputs=[response_output, chat_history])
+
+# Launch app
+demo.launch()