Update app.py

app.py

@@ -1,56 +1,73 @@
+# app.py ─ Streamlit Space
 import os, asyncio, streamlit as st
 from dotenv import load_dotenv
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_google_genai import ChatGoogleGenerativeAI
 
-# ------------------------------------------------------------------ #
-# 1️⃣  Ensure the current thread owns an asyncio event‑loop
+# ─────────────────────────  ensure event‑loop  ────────────────────────
 try:
     asyncio.get_running_loop()
 except RuntimeError:
     asyncio.set_event_loop(asyncio.new_event_loop())
-if os.name == "nt":                          # optional Windows tweak
+if os.name == "nt":  # Windows only
     asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
-# ------------------------------------------------------------------ #
-
-load_dotenv()                                # reads .env into os.environ
-os.environ["GOOGLE_API_KEY"] = os.getenv("api")  # keep your .env key name
-
-system_template = "You are a helpful assistant. Please respond to the user queries."
-prompt_template = ChatPromptTemplate.from_messages([
-    ('system', system_template),
-    ('user', 'Question: {question}')
-])
-
-model   = ChatGoogleGenerativeAI(model="gemini-pro",
-                                 convert_system_message_to_human=True)
-parser  = StrOutputParser()
-chain   = prompt_template | model | parser
-
-st.title("LangChain Chatbot Demo")
-st.markdown("""
-Welcome to the LangChain Chatbot Demo!  
-Type your query below and get responses powered by Google's Generative AI.
-""")
-
-input_text = st.text_input("Enter your question:")
-
-if input_text:
-    with st.spinner("Generating response…"):
-        try:
-            response = chain.invoke({"question": input_text})
-            st.write("**Chatbot Response:**")
-            st.write(response)
-
-            st.session_state.setdefault("history", []).extend([
-                {"role": "user",    "text": input_text},
-                {"role": "chatbot", "text": response},
-            ])
-        except Exception as e:
-            st.error(f"An error occurred: {e}")
 
+# ───────────────────────────  Streamlit UI  ───────────────────────────
+st.set_page_config(page_title="LangChain Chatbot", page_icon="🤖")
+st.title("🤖  LangChain Chatbot Demo")
+st.markdown("Type a question and get answers from **Gemini‑Pro**.")
+
+# Sidebar – API key input
+with st.sidebar:
+    google_key = st.text_input("Google API Key", type="password")
+    st.markdown("*Your key is kept only in this browser session.*")
+
+# Question input
+user_q = st.text_input("Enter your question:")
+
+# ────────────────────  lazy LLM constructor  ──────────────────────────
+def get_llm():
+    if "llm" not in st.session_state:
+        key = google_key or os.getenv("GOOGLE_API_KEY")
+        if not key:
+            raise ValueError("Please enter your Google API key in the sidebar.")
+        os.environ["GOOGLE_API_KEY"] = key           # make client happy
+        st.session_state.llm = ChatGoogleGenerativeAI(
+            model="gemini-pro",
+            convert_system_message_to_human=True,
+        )
+    return st.session_state.llm
+
+# Prompt template (built once – static)
+PROMPT = ChatPromptTemplate.from_messages(
+    [
+        ("system", "You are a helpful assistant. Please answer the user."),
+        ("user",   "Question: {question}"),
+    ]
+)
+PARSER = StrOutputParser()
+
+# ───────────────────────────  main action  ────────────────────────────
+if user_q:
+    try:
+        with st.spinner("Thinking…"):
+            llm   = get_llm()
+            chain = PROMPT | llm | PARSER
+            answer = chain.invoke({"question": user_q})
+
+        st.success(answer)
+
+        st.session_state.setdefault("history", []).extend(
+            [{"role": "user", "text": user_q},
+             {"role": "bot",  "text": answer}]
+        )
+
+    except Exception as err:
+        st.error(f"❌ {err}")
+
+# Conversation history
 st.sidebar.header("Conversation History")
 for msg in st.session_state.get("history", []):
-    role = "You" if msg["role"] == "user" else "Chatbot"
+    role = "You" if msg["role"] == "user" else "Bot"
     st.sidebar.write(f"**{role}:** {msg['text']}")