email upload

app.py

@@ -53,13 +53,8 @@ def parse_query(sentences: List[str], labels: List[str], threshold: float = 0.3,
 
     for sentence in sentences:
         _entities = model.predict_entities(sentence, labels, threshold=threshold)
-
-        entities = []
-
-        for entity in _entities:
-            entities.append(entity)
-
-        results.append({"sentence": sentence, "entities": entities})
+        entities = [{"text": entity["text"], "label": entity["label"]} for entity in _entities]
+        results.extend(entities)
 
     return results
 
@@ -69,17 +64,16 @@ def present(email_file, labels, multilingual=False):
     further_cleaned_text = remove_special_characters(cleaned_text)
     sentence_list = get_sentences(further_cleaned_text)
     
-    result = parse_query(sentence_list, labels, threshold=0.3, nested_ner=False, model_name="urchade/gliner_base", multilingual=multilingual)
+    entities = parse_query(sentence_list, labels, threshold=0.3, nested_ner=False, model_name="urchade/gliner_base", multilingual=multilingual)
 
     email_info = {
         "Subject": email.subject,
         "From": email.from_,
         "To": email.to,
         "Date": email.date,
-        "Cleaned Body": further_cleaned_text,
-        "Extracted Entities": result
+        "Extracted Entities": entities
     }
-    return [email_info[key] for key in email_info]
+    return [email_info[key] for key in ["Subject", "From", "To", "Date"]] + [entities]
 
 labels = ["PERSON", "PRODUCT", "DEAL", "ORDER", "ORDER PAYMENT METHOD", "STORE", "LEGAL ENTITY", "MERCHANT", "FINANCIAL TRANSACTION", "UNCATEGORIZED", "DATE"]
 
@@ -99,8 +93,7 @@ demo = gr.Interface(
         gr.components.Textbox(label="From"),
         gr.components.Textbox(label="To"),
         gr.components.Textbox(label="Date"),
-        gr.components.Textbox(label="Cleaned Body"),
-        gr.components.JSON(label="Extracted Entities")
+        gr.components.Dataframe(label="Extracted Entities")
     ],
     title="Email Info Extractor",
     description="Upload an email file (.eml) to extract its details and detected entities."