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| 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)}") |