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app.py

@@ -1,4 +1,45 @@
+import json
+from json import JSONDecodeError
+
 import streamlit as st
+from datasets import Dataset
+
+from spacy_to_hf import spacy_to_hf
+
+demo_option = [
+    {
+        "text": "Planned to go to the Apple Storefront on Tuesday",
+        "spans": [
+            {"start": 0, "end": 7, "label": "Action"},
+            {"start": 21, "end": 37, "label": "Loc"},
+            {"start": 41, "end": 48, "label": "Date"},
+        ],
+    }
+]
+
+tokenizers = [
+    "bert-base-uncased",
+    "bert-base-cased",
+    "distilbert-base-uncased",
+    "distilbert-base-cased",
+    "roberta-base",
+]
+tok = st.selectbox("Pick a tokenizer", tokenizers)
+spacy_data = st.text_area("Input your NER Span data here")
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+if spacy_data or st.button("Or try an example"):
+    run_data = None
+    if spacy_data:
+        try:
+            run_data = json.loads(spacy_data)
+        except JSONDecodeError as e:
+            st.warning(f"Invalid JSON data, try again\n{str(e)}")
+    else:
+        run_data = demo_option
+    if run_data:
+        st.write("Spacy input data:")
+        st.json(run_data)
+        hf_data = spacy_to_hf(run_data, tok)
+        df = Dataset.from_dict(hf_data).to_pandas()
+        st.write("Output huggingface format:")
+        st.dataframe(df)

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+spacy-to-hf
+datasets
+https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.3.1/en_core_web_sm-2.3.1.tar.gz#egg=en_core_web_sm