Added prediction system

app.py

@@ -1,15 +1,31 @@
 import streamlit as st
 from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
 
-pulled_model = AutoModelForSequenceClassification.from_pretrained(
-    "NazmusAshrafi/stock_twitter_sentiment_Bert")
+@st.cache(allow_output_mutation=True)
+def get_model():
+    tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
+    pulled_model = AutoModelForSequenceClassification.from_pretrained(
+        "NazmusAshrafi/stock_twitter_sentiment_Bert")
+    return tokenizer, pulled_model
+
+
+tokenizer, model = get_model()
+
 
 classifier = pipeline("sentiment-analysis",
-                      model=pulled_model, tokenizer=tokenizer)
+                      model=model, tokenizer=tokenizer)
 
 
-print(classifier("AAP Up Theory = Will go up in future, buy now"))
+# print(classifier("AAP Up Theory = Will go up in future, buy now"))
 
 st.title("Topic Modeling and Sentiment Analysis of Stock Tweets")
+
+user_input = st.text_area("Enter a tweet about a stock")
+button = st.button("Analyze")
+
+
+if user_input and button:
+    # output
+    classifier("AAP Up Theory = Will go up in future, buy now")
+    st.write("Raw Pred: ", classifier(user_input))

requirements.txt

@@ -1,2 +1,3 @@
+streamlit
 transformers
 torch