Update app.py

app.py

@@ -1,47 +1,18 @@
-import streamlit as st 
-import os
-from bardapi import Bard 
-from pymongo import MongoClient
-
-#Mongo connection
-url = os.environ["MONGO_CONNECTION_STRING"]
-client = MongoClient(url,tlsCertificateKeyFile ="cert.pem")
-
-#Fetch database 
-db = client["myapp"]
-
-#Fetch collections
-remcol = db["Reminders"]
-usrcol = db["Users"]
-notecol = db["Notes"]
-
-#Connect with Bard
-uri = os.environ["BARD_API_KEY"]
-bard = Bard(token = uri )
-
-#Store user bot chat messages
-def chat_message(ques, ans):
-    chat = {
-            "user": ques,
-            "bot": ans
-        }
-    usrcol.insert_one(chat)
-
-#Creating reminders from the described goal
-def create_rem(ans):
-    remlist = bard.get_answer(f"Create a daily routine to achieve this goal below and make a list of reminders with values for reminder_message, time, repetition, days\n\nGoal = {ans}")
-
-def Chatbot():
-    st.title("chatbot")
-    if query:= st.chat_input("Describe your goal"):
-        answer = bard.get_answer(query)
-        chat_message(query, answer)
-        create_rem(answer["content"])
-
-        with st.chat_message("assistant"):
-            st.write(answer["content"])
-
-
-Chatbot()
-    
-    
+rom transformers import GPT2LMHeadModel, GPT2Tokenizer
+model_id = "gpt2"
+
+model = GPT2LMHeadModel.from_pretrained(model_id)
+
+tokenizer = GPT2Tokenizer.from_pretrained(model_id)
+
+
+
+
+text = "Hello"
+
+encoded_text = tokenizer(text, return_tensors="pt") 
+
+
+
+
+outputs = model(**encoded_text)