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app.py

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+import streamlit as st
+from langchain_groq import ChatGroq
+from langchain_community.utilities import ArxivAPIWrapper, WikipediaAPIWrapper
+from langchain_community.tools import ArxivQueryRun, WikipediaQueryRun, DuckDuckGoSearchRun
+from langchain.agents import initialize_agent, AgentType
+from langchain.callbacks import StreamlitCallbackHandler
+import os
+from dotenv import load_dotenv
+
+# Load API keys from environment variables
+load_dotenv()
+api_key = os.getenv("GROQ_API_KEY")
+
+# Initialize Search Tools
+arxiv_wrapper = ArxivAPIWrapper(top_k_results=1, doc_content_chars_max=200)
+arxiv = ArxivQueryRun(api_wrapper=arxiv_wrapper)
+
+wiki_wrapper = WikipediaAPIWrapper(top_k_results=1, doc_content_chars_max=200)
+wiki = WikipediaQueryRun(api_wrapper=wiki_wrapper)
+
+search = DuckDuckGoSearchRun(name="Search")
+
+# --------------------------- Streamlit UI Setup ---------------------------
+
+# Page Configuration
+st.set_page_config(page_title="🔎 LangChain Search Assistant", page_icon="🔍", layout="wide")
+
+# Custom Styling
+st.markdown(
+    """
+    <style>
+        body { background-color: #f0f2f6; }
+        .stChatMessage { border-radius: 12px; padding: 10px; margin-bottom: 10px; }
+        .stChatMessage-user { background-color: #4a90e2; color: white; }
+        .stChatMessage-assistant { background-color: #f8f9fa; color: black; }
+        .stSpinner { font-size: 18px; font-weight: bold; }
+    </style>
+    """,
+    unsafe_allow_html=True
+)
+
+# Title & Description
+st.title("🔎 LangChain - Chat with Search")
+st.markdown(
+    "This chatbot can **search the web, retrieve articles from Arxiv, Wikipedia**, and more.\n\n"
+    "💡 Try **asking about recent discoveries, technical concepts, or general knowledge!**"
+)
+
+# --------------------------- Chat Memory ---------------------------
+
+# Initialize session state
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [
+        {"role": "assistant", "content": "Hi! I'm a chatbot that can search the web. How can I help you?"}
+    ]
+
+# Display previous messages
+for msg in st.session_state.messages:
+    role = "🧑‍💻 User" if msg["role"] == "user" else "🤖 Assistant"
+    st.chat_message(msg["role"]).markdown(f"**{role}**: {msg['content']}")
+
+# --------------------------- Chat Input & Processing ---------------------------
+
+# User Input
+if prompt := st.chat_input("Ask me anything..."):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    st.chat_message("user").markdown(f"**🧑‍💻 User**: {prompt}")
+
+    # Initialize LLM
+    llm = ChatGroq(groq_api_key=api_key, model_name="llama-3.3-70b-versatile", streaming=True)
+    tools = [search, arxiv, wiki]
+
+    search_agent = initialize_agent(
+        tools=tools,
+        llm=llm,
+        agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
+        handle_parsing_errors=True
+    )
+
+    with st.chat_message("assistant"):
+        st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False)
+        with st.spinner("🔍 Searching..."):
+            response = search_agent.run(st.session_state.messages, callbacks=[st_cb])
+
+        st.session_state.messages.append({"role": "assistant", "content": response})
+        st.markdown(f"**🤖 Assistant**: {response}")