Update app.py

app.py

@@ -1,10 +1,12 @@
 import gradio as gr
 from spacy import displacy
 
-from transformers import AutoTokenizer, AutoModelForTokenClassification,pipeline
+from transformers import AutoTokenizer, AutoModelForTokenClassification, pipeline
+
+# Carregar o modelo de tokenização e classificação de entidades
 tokenizer = AutoTokenizer.from_pretrained("abhibisht89/spanbert-large-cased-finetuned-ade_corpus_v2")
 model = AutoModelForTokenClassification.from_pretrained("abhibisht89/spanbert-large-cased-finetuned-ade_corpus_v2").to('cpu')
-adr_ner_model = pipeline(task="ner", model=model, tokenizer=tokenizer,grouped_entities=True)      
+adr_ner_model = pipeline(task="ner", model=model, tokenizer=tokenizer, grouped_entities=True) 
 
 def get_adr_from_text(sentence):
     tokens = adr_ner_model(sentence)
@@ -16,31 +18,45 @@ def get_adr_from_text(sentence):
             token["label"] = label
             entities.append(token)
     
-    params = [{"text": sentence,
-               "ents": entities,
-               "title": None}]
+    params = [{
+        "text": sentence,
+        "ents": entities,
+        "title": None
+    }]
     
     html = displacy.render(params, style="ent", manual=True, options={
         "colors": {
-                   "DRUG": "#f08080",
-                   "ADR": "#9bddff",
-               },
+            "DRUG": "#f08080",
+            "ADR": "#9bddff",
+        },
     })
     return html
 
-exp=["Abortion, miscarriage or uterine hemorrhage associated with misoprostol (Cytotec), a labor-inducing drug.",
+exp = [
+    "Abortion, miscarriage or uterine hemorrhage associated with misoprostol (Cytotec), a labor-inducing drug.",
     "Addiction to many sedatives and analgesics, such as diazepam, morphine, etc.",
     "Birth defects associated with thalidomide",
     "Bleeding of the intestine associated with aspirin therapy",
     "Cardiovascular disease associated with COX-2 inhibitors (i.e. Vioxx)",
     "Deafness and kidney failure associated with gentamicin (an antibiotic)",
-    "Having fever after taking paracetamol"]
+    "Having fever after taking paracetamol"
+]
+
+desc = "An adverse drug reaction (ADR) can be defined as an appreciably harmful or unpleasant reaction resulting from an intervention related to the use of a medicinal product. \
+The goal of this project is to extract the adverse drug reaction from unstructured text with the Drug."
 
-desc="An adverse drug reaction (ADR) can be defined as an appreciably harmful or unpleasant reaction resulting from an intervention related to the use of a medicinal product.\
- The goal of this project is to extracts the adverse drug reaction from unstructured text with the Drug."
+inp = gr.inputs.Textbox(lines=5, placeholder=None, default="", label="Texto para extrair reação adversa a medicamentos e menção ao medicamento")
+out = gr.outputs.HTML(label=None)
 
-inp=gr.inputs.Textbox(lines=5, placeholder=None, default="", label="text to extract adverse drug reaction and drug mention")
-out=gr.outputs.HTML(label=None)
+iface = gr.Interface(
+    fn=get_adr_from_text,
+    inputs=inp,
+    outputs=out,
+    examples=exp,
+    article=desc,
+    title="Extrator de Reações Adversas a Medicamentos",
+    theme="huggingface",
+    layout="horizontal"
+)
 
-iface = gr.Interface(fn=get_adr_from_text, inputs=inp, outputs=out,examples=exp,article=desc,title="Adverse Drug Reaction Xtractor",theme="huggingface",layout='horizontal')
-iface.launch()
+iface.launch()