Create app.py

app.py

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+# app.py
+ 
+import os
+import streamlit as st
+from dotenv import load_dotenv
+ 
+from langchain_community.tools import ArxivQueryRun, WikipediaQueryRun
+from langchain_community.utilities import WikipediaAPIWrapper, ArxivAPIWrapper
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_groq import ChatGroq
+ 
+from langgraph.graph import StateGraph, START, END
+from langgraph.prebuilt import ToolNode, tools_condition
+from langgraph.checkpoint.memory import MemorySaver
+from langchain_core.messages import AIMessage, HumanMessage
+from langgraph.graph.message import add_messages
+from typing import Annotated
+from typing_extensions import TypedDict
+ 
+# Load environment
+load_dotenv()
+os.environ["TAVILY_API_KEY"] = os.getenv("TAVILY_API_KEY")
+os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")
+ 
+# Define tools
+arxiv = ArxivQueryRun(api_wrapper=ArxivAPIWrapper(top_k_results=2, doc_content_chars_max=1000))
+wiki = WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper(top_k_results=1, doc_content_chars_max=1000))
+tavily = TavilySearchResults()
+tools = [arxiv, wiki, tavily]
+ 
+# LangGraph State
+class State(TypedDict):
+    messages: Annotated[list, add_messages]
+    name: str
+    birthday: str
+ 
+# LLM
+llm = ChatGroq(model="deepseek-r1-distill-llama-70b")
+llm_with_tools = llm.bind_tools(tools=tools)
+ 
+# Memory
+memory = MemorySaver()
+ 
+# Define node
+def ai_assistance(state: State):
+    result = llm_with_tools.invoke(state["messages"])
+    return {"messages": [result]}
+ 
+# Build LangGraph
+builder = StateGraph(State)
+builder.add_node("AI_Assistance", ai_assistance)
+builder.add_node("tools", ToolNode(tools))
+ 
+builder.add_edge(START, "AI_Assistance")
+builder.add_conditional_edges("AI_Assistance", tools_condition)
+builder.add_edge("tools", "AI_Assistance")
+graph = builder.compile(checkpointer=memory)
+ 
+# Streamlit UI setup
+st.set_page_config(page_title="LangGraph Chatbot", layout="wide")
+ 
+st.markdown("""
+<style>
+.stChatMessage {
+    padding: 12px;
+    margin-bottom: 12px;
+    border-radius: 12px;
+    max-width: 90%;
+}
+.user {
+    background-color: #dcf8c6;
+    align-self: flex-end;
+}
+.bot {
+    background-color: #f1f0f0;
+    align-self: flex-start;
+}
+.input-box {
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+}
+#floating-container {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    padding: 0.25rem 0.75rem;
+    background-color: #f9f9f9;
+    border-radius: 0.75rem;
+    margin-top: 1rem;
+    border: 1px solid #ccc;
+}
+.floating-popup {
+    margin-top: 0.5rem;
+    padding: 0.5rem;
+    border-radius: 0.5rem;
+    border: 1px solid #ccc;
+    background-color: white;
+}
+</style>
+""", unsafe_allow_html=True)
+ 
+st.title("🧠 LangGraph Chatbot (Groq + Tools)")
+ 
+# Initialize session
+if "thread_id" not in st.session_state:
+    st.session_state.thread_id = "1"
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+if "show_upload" not in st.session_state:
+    st.session_state.show_upload = False
+if "selected_tools" not in st.session_state:
+    st.session_state.selected_tools = ["Arxiv", "Wikipedia", "Tavily"]
+ 
+# Show chat
+for msg in st.session_state.chat_history:
+    role = "user" if isinstance(msg, HumanMessage) else "bot"
+    st.markdown(f"<div class='stChatMessage {role}'>{msg.content}</div>", unsafe_allow_html=True)
+ 
+# Custom Chat Input Box UI
+with st.container():
+    with st.form("chat_form", clear_on_submit=True):
+        st.markdown('<div id="floating-container">', unsafe_allow_html=True)
+ 
+        col1, col2 = st.columns([1, 17])
+        with col1:
+            toggle = st.form_submit_button("➕", use_container_width=True)
+        with col2:
+            user_input = st.text_input("Ask me", label_visibility="collapsed",placeholder="Ask me Anything")
+ 
+        st.markdown('</div>', unsafe_allow_html=True)
+ 
+        # Floating Popup for Uploads and Tools
+        if toggle:
+            st.session_state.show_upload = not st.session_state.show_upload
+ 
+        if st.session_state.show_upload:
+            with st.expander("📎 Upload Files or Images", expanded=False,width=300):
+                st.file_uploader("Upload:", type=["txt", "pdf", "docx"], key="text_file")
+                st.file_uploader("Upload image:", type=["jpg", "jpeg", "png"], key="img_file")
+ 
+            st.session_state.selected_tools = st.multiselect(
+                "🛠 Select Tools:",
+                ["Arxiv", "Wikipedia", "Tavily"],
+                default=st.session_state.selected_tools,
+                width= 300
+            )
+ 
+        submitted = st.form_submit_button(label = "Send")
+        if submitted and user_input:
+            st.session_state.chat_history.append(HumanMessage(content=user_input))
+            config = {"configurable": {"thread_id": st.session_state.thread_id}}
+            result = graph.invoke({"messages": st.session_state.chat_history}, config=config)
+            st.session_state.chat_history.append(result["messages"][-1])
+            st.rerun()
+ 
+