Update app.py

app.py

@@ -1,56 +1,56 @@
-import os
-import streamlit as st
+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
-from langchain_core.messages import HumanMessage, SystemMessage
-from dotenv import load_dotenv
-
-load_dotenv()
-
 
-os.environ["GOOGLE_API_KEY"] = os.getenv('api')
+# ------------------------------------------------------------------ #
+# 1️⃣  Ensure the current thread owns an asyncio event‑loop
+try:
+    asyncio.get_running_loop()
+except RuntimeError:
+    asyncio.set_event_loop(asyncio.new_event_loop())
+if os.name == "nt":                          # optional Windows tweak
+    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 response to the user queries"
+system_template = "You are a helpful assistant. Please respond to the user queries."
 prompt_template = ChatPromptTemplate.from_messages([
     ('system', system_template),
-    ('user', 'Question:{question}')
+    ('user', 'Question: {question}')
 ])
 
-
-model = ChatGoogleGenerativeAI(model="gemini-pro", convert_system_message_to_human=True)
-parser = StrOutputParser()
-chain = prompt_template | model | parser
+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.
-    """)
-st.sidebar.header("Chatbot Settings")
-st.sidebar.text("You can enter your query in the main section below.")
-
-input_text = st.text_input("Enter your question:", "")
+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:
-    try:
-        with st.spinner('Generating response...'):
+    with st.spinner("Generating response…"):
+        try:
             response = chain.invoke({"question": input_text})
             st.write("**Chatbot Response:**")
             st.write(response)
-            
-            if "history" not in st.session_state:
-                st.session_state.history = []
-            st.session_state.history.append({"role": "user", "text": input_text})
-            st.session_state.history.append({"role": "chatbot", "text": response})
-    
-    except Exception as e:
-        st.error(f"An error occurred: {e}")
+
+            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}")
 
 st.sidebar.header("Conversation History")
-if "history" in st.session_state and st.session_state.history:
-    for message in st.session_state.history:
-        role = "You" if message["role"] == "user" else "Chatbot"
-        st.sidebar.write(f"**{role}:** {message['text']}")
+for msg in st.session_state.get("history", []):
+    role = "You" if msg["role"] == "user" else "Chatbot"
+    st.sidebar.write(f"**{role}:** {msg['text']}")