Update app.py

groq to original

app.py

@@ -2,7 +2,7 @@ import pandas as pd
 import streamlit as st
 from langchain.agents import AgentType
 from langchain_experimental.agents import create_pandas_dataframe_agent
-from langchain_groq import ChatGroq
+from langchain_ollama import ChatOllama
 
 
 # streamlit web app configuration
@@ -12,8 +12,7 @@ st.set_page_config(
     layout="centered"
 )
 
-with st.sidebar:
-    groq_api_key=st.text_input("Groq API Key",value="",type="password")
+
 def read_data(file):
     if file.name.endswith(".csv"):
         return pd.read_csv(file)
@@ -55,9 +54,9 @@ if user_prompt:
     # add user's message to chat history and display it
     st.chat_message("user").markdown(user_prompt)
     st.session_state.chat_history.append({"role":"user","content": user_prompt})
-    
+
     # loading the LLM
-    llm =ChatGroq(model="Gemma-7b-It", groq_api_key=groq_api_key)
+    llm = ChatOllama(model="gemma:2b", temperature=0)
 
     pandas_df_agent = create_pandas_dataframe_agent(
         llm,
@@ -80,6 +79,4 @@ if user_prompt:
 
     # display LLM response
     with st.chat_message("assistant"):
-        st.markdown(assistant_response)
-
-
+        st.markdown(assistant_response)