Upload files to 'Streamlit'

update streamlit

Streamlit/Dockerfile

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+FROM python:3.10-slim-bullseye AS base
+
+WORKDIR /app
+
+# Set utf-8 encoding for Python et al
+ENV LANG=C.UTF-8 \
+	# Turn off writing .pyc files
+	PYTHONDONTWRITEBYTECODE=1 \
+	# Reduce the OS system calls for this tool it makes a difference
+	PYTHONUNBUFFERED=1 \
+	# Disables cache dir in pip
+	PIP_NO_CACHE_DIR=1 \
+	# Virtual environment
+	VENV="/opt/venv" \
+	# Add new user
+	APPUSER=appuser \
+	# Ensure that the python and pip executables used in the image
+	PATH="${VENV}/bin:$PATH"
+
+
+FROM base as builder
+
+COPY requirements.txt .
+
+RUN apt-get update \
+    && python -m venv ${VENV} \
+	&& . ${VENV}/bin/activate \
+    && pip install --upgrade pip \
+    && pip install -r requirements.txt
+
+
+FROM base as runner
+
+COPY aplication.py .
+
+
+COPY --from=builder ${VENV} ${VENV}
+ENV PATH="${VENV}/bin:$PATH"
+
+# Update permissions & change user to not run as root
+RUN chgrp -R 0 /app \
+    && chmod -R g=u /app \
+    && groupadd -r ${APPUSER} \
+    && useradd -r -g ${APPUSER} ${APPUSER} \
+    && chown -R ${APPUSER}:${APPUSER} /app \
+    && usermod -d /app ${APPUSER}
+
+
+
+#$HEALTHCHECK CMD curl --fail http://localhost/_stcore/health
+CMD ["streamlit", "run", "aplication.py", "--server.address=0.0.0.0"]

Streamlit/aplication.py

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+import requests
+import json
+import streamlit as st
+import os
+from dotenv import load_dotenv
+load_dotenv()
+def predict(context,question):
+    url = os.getenv("URL")
+    #url = 'http://localhost:8090/predict'
+    data = {'context': context,'question': question}
+    json_data = json.dumps(data)
+    headers = {'Content-type': 'application/json'}
+    response = requests.post(url, data=json_data, headers=headers)
+    result = response.json()
+    return result
+
+def main():
+    st.title("T5 model inference")
+    
+    # Vytvoríme polia pre zadanie hodnôt
+    context = st.text_input("context:")
+    question = st.text_input("question:")
+    prediction = predict(context,question)
+    # Vytvoríme tlačidlo pre vykonanie akcie
+    if st.button("Execute"):
+        
+        st.json({
+    'context': context,
+    'question': question,
+    'prediciton':prediction
+    })
+        
+
+
+if __name__ == "__main__":
+    main()

Streamlit/requirements.txt

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+requests
+streamlit
+python-dotenv