Create app.py

app.py

@@ -0,0 +1,63 @@
+import os 
+import langchain
+import openai
+from dotenv import load_dotenv
+from langchain.chat_models import ChatOpenAI
+from langchain.tools import Tool
+from langchain.utilities import SerpAPIWrapper
+from langchain.agents import initialize_agent, AgentType
+from langchain_core.exceptions import OutputParserException
+
+import gradio as gr
+
+
+
+load_dotenv(override=True)
+os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')
+os.environ['SERPAPI_API_KEY'] = os.getenv('SERP_KEY', 'your-key-if-not-using-env')
+MODEL = "gpt-4o-mini"
+
+# serpapi wrapper 
+search = SerpAPIWrapper()
+
+# here is the defination of the tool 
+tools = [
+    Tool(
+        name="Google Search",
+        func=search.run,
+        description="Useful for answering real-time or current event questions."
+    )
+]
+
+#define llm with temperature 0
+llm = ChatOpenAI(temperature=0.7, model=MODEL) 
+# define an agent using athe   tool that we have defined above
+agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, handle_parsing_errors=True, verbose=True)
+
+# chat bot definition with history 
+def chatbot(user_input):
+    if user_input.lower().strip() in ["hi", "hello", "hey"]:
+        return "Hello! How can I help you today?"
+    try:
+        # Example agent usage (replace with your real agent.run)
+        output = agent.run(user_input)
+    except OutputParserException:
+        output = "Agent encountered a parsing issue. Please rephrase your query."
+    except Exception as e:
+        output = f"Unexpected Error: {e}"
+    return output
+# UI USING GRADIO 
+with gr.Blocks() as demo:
+    chatbot_ui = gr.Chatbot(type="messages")
+    user_input = gr.Textbox(placeholder="Ask Anything...")
+    submit = gr.Button("Ask")
+    def respond(user_message, chat_history):
+        chat_history = chat_history or []
+        chat_history.append({"role": "user", "content": user_message})
+        response = chatbot(user_message)
+        chat_history.append({"role": "assistant", "content": response})
+        return chat_history, ""
+    user_input.submit(respond, inputs=[user_input, chatbot_ui], outputs=[chatbot_ui, user_input])
+    submit.click(respond, inputs=[user_input, chatbot_ui], outputs=[chatbot_ui, user_input])
+
+demo.launch(inline=False)