First commit

.gitignore

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+*.pyc

app.py

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+from functions import *
+
+# set the title
+st.sidebar.title(DASHBOARD_TITLE)
+
+# load the model
+with st.spinner("Loading the model..."):
+    model = load_pipeline()
+
+# input
+text = st.text_area(value="Woman, 43, feeling pain in the stomach. No vomiting", label="Enter the text here")
+submit = st.button("Submit")
+
+if text and submit:
+
+    # get the entities
+    entities =  model(text)
+
+    if len(entities) == 0:
+        st.error("No entities found")
+
+    # annotate the entities
+    annotated_entities = [annotate(entity) for entity in entities]
+
+    # display the entities
+    annotated_text(annotated_entities)
+
+

config.py

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+import streamlit as st
+from transformers import pipeline
+from annotated_text import annotated_text
+
+
+DASHBOARD_TITLE = "Medical NER Dashboard"
+MODEL_PATH = "Clinical-AI-Apollo/Medical-NER"

functions.py

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+from config import *
+
+@st.cache_resource
+def load_pipeline():
+    """
+    Load the pipeline
+    """
+    return  pipeline("token-classification", model=MODEL_PATH)
+
+@st.cache_data
+def annotate(entity):
+
+    """
+    Annotate the text
+    """
+    return (entity["word"].replace('▁',''), entity["entity"])
+
+

requirements.txt

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+streamlit
+st-annotated-text
+transformers