first commit

app.py

@@ -0,0 +1,59 @@
+import gradio as gr
+import pandas as pd
+import spacy
+import concepcy
+
+LIST_RELATIONS = ["RelatedTo", "FormOf", "IsA", "PartOf", "HasA", "UserFor", "CapableOf", "AtLocation", "Causes",
+                  "HasSubevent", "HasFirstSubevent", "HasLastSubevent", "HasPrerequisite", "HasProperty",
+                  "MotivatedByGoal", "ObstructedBy", "Desires", "CreatedBy", "Synonym", "Antonym", "DistinctFrom",
+                  "DerivedFrom", "SymbolOf", "DefinedAs", "MannerOf", "LocatedNear", "HasContext", "SimilarTo",
+                  "EtymologicallyRelatedTo", "EtymologicallyDerivedFrom", "CausesDesire", "MadeOf", "ReceivesAction",
+                  "ExternalURL"]
+
+nlp = spacy.load("en_core_web_sm")
+nlp.add_pipe(
+    "concepcy",
+    config={
+        "relations_of_interest": LIST_RELATIONS,
+        "filter_missing_text": True,
+        "filter_edge_weight": 2,
+    }
+)
+
+
+def greet(text, relations, to_enrich):
+    doc = nlp(text)
+
+    outs0, outs1 = [], []
+    if "document" in to_enrich:
+        outs0 = []
+        for relation in relations:
+            for r in doc._.get(relation.lower()).values():
+                outs0.extend([[relation, elt["text"]] for elt in r])
+
+    if "token" in to_enrich:
+
+        for token in doc:
+            for relation in relations:
+                rels = token._.get(relation.lower())
+                if len(rels) > 0:
+                    print(rels)
+                    print([[token.text, relation, r["text"]] for r in rels])
+                    outs1.extend([[token.text, relation, r["text"]] for r in rels])
+
+    return pd.DataFrame(outs0, columns=["relation", "text"]), pd.DataFrame(outs1, columns=["word", "relation", "text"])
+
+
+iface = gr.Interface(
+    fn=greet,
+    inputs=[
+        gr.Textbox(placeholder="Enter sentence here...", lines=5, value="I love eating pizzas"),
+        gr.CheckboxGroup(choices=LIST_RELATIONS, value=["IsA"]),
+        gr.CheckboxGroup(choices=["document", "token"], value=["document"])
+    ],
+    outputs=[
+        gr.Dataframe(headers=["relation", "text"], label="Document-level relations"),
+        gr.Dataframe(headers=["word", "relation", "text"], label="Token-level relations")
+    ]
+)
+iface.launch()

requirements.txt

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+concepcy==0.1.0
+spacy==3.3.0
+https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.3.0/en_core_web_sm-3.3.0.tar.gz#egg=en_core_web_sm
+pandas
+