Initial commit of demo

app.py

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+import spacy.displacy
+import streamlit as st
+from flair.models import SequenceTagger
+from flair.splitter import SegtokSentenceSplitter
+from colorhash import ColorHash
+
+# st.title("Flair NER Demo")
+st.set_page_config(layout="centered")
+
+# models to choose from
+model_map = {
+    "find Entities (default)": "ner",
+    "find Entities (18-class)": "ner-ontonotes",
+    "find Parts-of-Speech": "upos",
+}
+
+# Block 1: Users can select a model
+st.subheader("Select Model")
+selected_model_id = st.selectbox("This is a check box",
+                                 model_map.keys(),
+                                 label_visibility="collapsed",
+                                 )
+
+# Block 2: Users can input text
+st.subheader("Input your text here")
+input_text = st.text_area('Write or Paste Text Below',
+                          value="George was born in Washington.",
+                          height=128,
+                          max_chars=None,
+                          label_visibility="collapsed")
+
+
+@st.cache_resource()
+def get_model(model_name):
+    return SequenceTagger.load(model_map[model_name])
+
+
+def get_html(html: str):
+    WRAPPER = """<div style="overflow-x: auto; border: 1px solid #e6e9ef; border-radius: 0.25rem; padding: 1rem; margin-bottom: 2.5rem">{}</div>"""
+    html = html.replace("\n", " ")
+    return WRAPPER.format(html)
+
+
+def color_variant(hex_color, brightness_offset=1):
+    """ takes a color like #87c95f and produces a lighter or darker variant
+    taken from: https://chase-seibert.github.io/blog/2011/07/29/python-calculate-lighterdarker-rgb-colors.html
+    """
+    if len(hex_color) != 7:
+        raise Exception("Passed %s into color_variant(), needs to be in #87c95f format." % hex_color)
+    rgb_hex = [hex_color[x:x + 2] for x in [1, 3, 5]]
+    new_rgb_int = [int(hex_value, 16) + brightness_offset for hex_value in rgb_hex]
+    new_rgb_int = [min([255, max([0, i])]) for i in new_rgb_int]  # make sure new values are between 0 and 255
+    # hex() produces "0x88", we want just "88"
+    return "#" + "".join([hex(i)[2:] for i in new_rgb_int])
+
+
+# Block 3: Output is displayed
+button_clicked = st.button("**Click to tag the input text**", key=None)
+
+if button_clicked:
+
+    # get a sentence splitter and split text into sentences
+    splitter = SegtokSentenceSplitter()
+    sentences = splitter.split(input_text)
+
+    # get the model and predict
+    model = get_model(selected_model_id)
+    model.predict(sentences)
+
+    spacy_display = {"ents": [], "text": input_text, "title": None}
+
+    predicted_labels = set()
+    for sentence in sentences:
+        for prediction in sentence.get_labels():
+            spacy_display["ents"].append(
+                {"start": prediction.data_point.start_position + sentence.start_position,
+                 "end": prediction.data_point.end_position + sentence.start_position,
+                 "label": prediction.value})
+            predicted_labels.add(prediction.value)
+
+    # create colors for each label
+    colors = {}
+    for label in predicted_labels:
+        colors[label] = color_variant(ColorHash(label).hex, brightness_offset=85)
+
+    # use displacy to render
+    html = spacy.displacy.render(spacy_display,
+                                 style="ent",
+                                 minify=True,
+                                 manual=True,
+                                 options={
+                                     "colors": colors,
+                                 },
+                                 )
+    style = "<style>mark.entity { display: inline-block }</style>"
+    st.subheader("Found entities")
+    st.write(f"{style}{get_html(html)}", unsafe_allow_html=True)

requirements.txt

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+flair
+spacy
+colorhash