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AppDirectory/Dockerfile

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+FROM python:3.9
+
+RUN pip install -U pip
+
+WORKDIR /app
+
+
+RUN pip freeze > requirements.txt
+
+COPY requirements.txt /requirements.txt
+
+RUN pip install -r /requirements.txt
+
+
+EXPOSE 8501
+
+COPY . /app
+
+ENTRYPOINT ["python","-m","streamlit", "run", "app.py"]

AppDirectory/app.py

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+import streamlit as st
+from transformers import pipeline
+import torch
+import torch.nn.functional as F
+
+def main():
+
+    models = ["distilbert-base-uncased-finetuned-sst-2-english","cardiffnlp/twitter-roberta-base-sentiment","finiteautomata/bertweet-base-sentiment-analysis","papluca/xlm-roberta-base-language-detection","cardiffnlp/twitter-roberta-base-sentiment-latest","yiyanghkust/finbert-tone","ProsusAI/finbert","j-hartmann/emotion-english-distilroberta-base"]
+
+    st.title("Streamlit Sentiment Analysis App ")
+    st.header("Sentiments analysis using Trnasformers by 🤗")
+    st.header("Jozef Janosko - CS 482, Milestone 2")
+
+    st.text("Input a test string for sentiment analysis.")
+    input=st.text_input("input string","Here is a default string. I love machine learning!")
+    model = st.selectbox("Select Model...", models)
+    st.text("Result using "+model+": ")
+    st.text(str(sentiment_Analysis(input,model)))
+
+def sentiment_Analysis(input, model):
+
+    classifier = pipeline("sentiment-analysis",model)
+    ret=classifier(input)
+    return ret
+
+if __name__ == '__main__' :
+    main()