Update app.py

app.py

@@ -1,73 +1,77 @@
-# app.py ─ Streamlit Space
+# app.py  ─  Streamlit + LangChain + Groq
 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.schema import SystemMessage, HumanMessage, AIMessage
+from langchain_groq import ChatGroq
 
-# ─────────────────────────  ensure event‑loop  ────────────────────────
+# ─────────────────────────  bootstrap event‑loop  ─────────────────────
 try:
     asyncio.get_running_loop()
 except RuntimeError:
     asyncio.set_event_loop(asyncio.new_event_loop())
-if os.name == "nt":  # Windows only
-    asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())
+if os.name == "nt":
+    import asyncio as _asyncio
+    asyncio.set_event_loop_policy(_asyncio.WindowsSelectorEventLoopPolicy())
 
-# ───────────────────────────  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**.")
+# ───────────────────────────  UI  /  SETTINGS  ────────────────────────
+st.set_page_config("Groq Chatbot", "🤖")
+st.title("🤖  Groq‑powered Advanced Chatbot")
+st.caption("DeepSeek‑R1‑Distill‑Llama‑70B • LangChain • Streamlit")
 
-# 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.*")
+    st.header("🔑  Groq API Key")
+    groq_key = st.text_input("Paste your key here", type="password")
+    st.divider()
+    temperature = st.slider("Temperature", 0.0, 1.2, 0.7, 0.1)
+    top_p       = st.slider("Top‑p",       0.0, 1.0, 1.0, 0.05)
+    st.markdown("*All values remain local to your browser.*")
 
-# Question input
-user_q = st.text_input("Enter your question:")
+user_q = st.chat_input("Type your message…")
+
+# ──────────────────────────  LLM (lazy init)  ─────────────────────────
+MODEL_NAME = "deepseek-r1-distill-llama-70b"
 
-# ────────────────────  lazy LLM constructor  ──────────────────────────
 def get_llm():
     if "llm" not in st.session_state:
-        key = google_key or os.getenv("GOOGLE_API_KEY")
+        key = groq_key or os.getenv("GROQ_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,
+            raise ValueError("Add your Groq key in the sidebar.")
+        os.environ["GROQ_API_KEY"] = key                  # for the client
+        st.session_state.llm = ChatGroq(
+            model        = MODEL_NAME,
+            groq_api_key = key,
+            temperature  = temperature,
+            top_p        = top_p,
         )
-    return st.session_state.llm
+    # refresh sampling params if the sliders changed
+    llm = st.session_state.llm
+    llm.temperature = temperature
+    llm.top_p       = top_p
+    return llm
 
-# Prompt template (built once – static)
-PROMPT = ChatPromptTemplate.from_messages(
-    [
-        ("system", "You are a helpful assistant. Please answer the user."),
-        ("user",   "Question: {question}"),
+# ─────────────────────────  conversation memory  ──────────────────────
+if "history" not in st.session_state:
+    st.session_state.history = [
+        SystemMessage(content="You are an advanced, helpful assistant.")
     ]
-)
-PARSER = StrOutputParser()
 
-# ───────────────────────────  main action  ────────────────────────────
+# ────────────────────────────  main loop  ─────────────────────────────
 if user_q:
-    try:
-        with st.spinner("Thinking…"):
-            llm   = get_llm()
-            chain = PROMPT | llm | PARSER
-            answer = chain.invoke({"question": user_q})
+    st.session_state.history.append(HumanMessage(content=user_q))
 
-        st.success(answer)
+    try:
+        with st.chat_message("assistant", avatar="🤖"):
+            with st.spinner("Thinking…"):
+                answer = get_llm().invoke(st.session_state.history).content
+            st.markdown(answer)
 
-        st.session_state.setdefault("history", []).extend(
-            [{"role": "user", "text": user_q},
-             {"role": "bot",  "text": answer}]
-        )
+        st.session_state.history.append(AIMessage(content=answer))
 
     except Exception as err:
-        st.error(f"❌ {err}")
+        st.error(f"**Error:** {err}")
 
-# Conversation history
-st.sidebar.header("Conversation History")
-for msg in st.session_state.get("history", []):
-    role = "You" if msg["role"] == "user" else "Bot"
-    st.sidebar.write(f"**{role}:** {msg['text']}")
+# ────────────────────────  display chat history  ──────────────────────
+for msg in st.session_state.history[1:]:              # skip system message
+    role = "user" if isinstance(msg, HumanMessage) else "assistant"
+    with st.chat_message(role):
+        st.markdown(msg.content)