Delete app.py

app.py

@@ -1,113 +0,0 @@
-import os
-import streamlit as st
-import requests
-from dotenv import load_dotenv
-load_dotenv()
-
-# Set environment variables
-os.environ["GROQ_API_KEY"] = st.secrets["GROQ_API_KEY"]
-os.environ["TAVILY_API_KEY"] = st.secrets["TAVILY_API_KEY"]
-
-from langchain_groq import ChatGroq
-from langchain_community.tools.tavily_search import TavilySearchResults
-from langgraph.prebuilt import create_react_agent
-from langchain_core.messages import HumanMessage, SystemMessage, AIMessage
-
-def get_response_from_ai_agent(llm_id, query, allow_search, system_prompt):
-    """
-    Create and invoke an AI agent with optional search capabilities
-    """
-    try:
-        # Initialize LLM with proper configuration
-        llm = ChatGroq(
-            api_key=os.environ.get("GROQ_API_KEY"),
-            model_name=llm_id
-        )
-        
-        # Setup tools based on allow_search flag
-        tools = []
-        if allow_search:
-            tools.append(TavilySearchResults(
-                api_key=os.environ.get("TAVILY_API_KEY"),
-                max_results=2
-            ))
-        
-        # Create the agent
-        agent = create_react_agent(
-            model=llm,
-            tools=tools
-        )
-        
-        # Prepare the initial messages
-        initial_messages = [
-            SystemMessage(content=system_prompt),
-            HumanMessage(content=query)
-        ]
-        
-        # Create proper state with messages
-        state = {
-            "messages": initial_messages,
-            "next_steps": [],
-            "structured_response": None
-        }
-        
-        # Invoke agent with proper state
-        response = agent.invoke(state)
-        
-        # Handle response
-        if isinstance(response, dict):
-            if "messages" in response:
-                messages = response["messages"]
-                ai_messages = [msg for msg in messages if isinstance(msg, AIMessage)]
-                if ai_messages:
-                    return ai_messages[-1].content
-            elif "structured_response" in response:
-                return response["structured_response"]
-        
-        return "I apologize, but I couldn't generate a proper response. Please try again."
-        
-    except Exception as e:
-        print(f"Debug - Error in get_response_from_ai_agent: {str(e)}")
-        raise Exception(f"Agent error: {str(e)}")
-
-# Streamlit UI
-st.set_page_config(page_title="AI Chatbot Agents", layout="centered")
-st.title("AI Chatbot Agents")
-st.write("Create and Interact with the AI Agents!")
-
-system_prompt = st.text_area(
-    "Define your AI Agent: ",
-    height=70,
-    placeholder="Type your system prompt here...",
-    value="You are a helpful AI assistant."
-)
-
-MODEL_NAMES_GROQ = ["llama-3.3-70b-versatile", "mixtral-8x7b-32768"]
-selected_model = st.selectbox("Select Groq Model:", MODEL_NAMES_GROQ)
-
-allow_web_search = st.checkbox("Allow Web Search")
-
-user_query = st.text_area(
-    "Enter your query: ",
-    height=150,
-    placeholder="Ask Anything!"
-)
-
-if st.button("Ask Agent!"):
-    if not user_query.strip():
-        st.error("Please enter a query!")
-    else:
-        try:
-            with st.spinner("Getting response..."):
-                response = get_response_from_ai_agent(
-                    llm_id=selected_model,
-                    query=user_query,
-                    allow_search=allow_web_search,
-                    system_prompt=system_prompt
-                )
-                
-                st.subheader("Agent Response")
-                st.markdown(response)
-                
-        except Exception as e:
-            st.error(f"An error occurred: {str(e)}")