dataframe prettied it up

Dockerfile

@@ -22,4 +22,4 @@ HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
 
 ADD . /app
 RUN pip3 install streamlit
-ENTRYPOINT ["streamlit", "run", "streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+CMD ["streamlit", "run", "language_models_project/app.py", "--server.port=8501", "--server.address=0.0.0.0"]

docker-run.esh

@@ -1 +1 @@
-(run-python "dtach -A /tmp/streamlit docker run -ti --rm -v .:/app -v /tmp:/tmp -p 10.147.17.74:6969:8501 streamlit /usr/local/bin/ipython")
+(run-python "dtach -A /tmp/streamlit docker run -ti --rm -v .:/app -v /tmp:/tmp streamlit /usr/local/bin/ipython")

language_models_project/app.py

@@ -70,7 +70,9 @@ def infer(text: str) -> List[Dict[str, float]]:
     predictions = np.zeros(probs.shape)
     predictions[np.where(probs >= 0.5)] = 1
     predictions = pd.Series(predictions == 1)
-    predictions.index = [
+
+    l = pd.Series(zip(predictions.tolist(), probs.tolist()))
+    l.index = [
         "toxic",
         "severe_toxic",
         "obscene",
@@ -78,7 +80,8 @@ def infer(text: str) -> List[Dict[str, float]]:
         "insult",
         "identity_hate",
     ]
-    return [{"label": predictions, "score": probs}]
+    #probs.index = predictions.index
+    return l.to_dict()
 
 
 def wrapper(*args, **kwargs):
@@ -109,7 +112,8 @@ if st.button("Classify"):
             "processed before displaying. Please allow a few minutes for longer"
             "inputs."
         )
-        j = pd.DataFrame([infer(text=i) for i in data])
+        internal_list = [infer(text=i) for i in data]
+        j = pd.DataFrame(internal_list)
         st.dataframe(data=j)