pushing app to the spaces

app.py

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+import gradio as gr
+from spacy import displacy
+
+from transformers import AutoTokenizer, AutoModelForTokenClassification,pipeline
+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)      
+
+def get_adr_from_text(sentence):
+    tokens = adr_ner_model(sentence)
+    entities = []
+    
+    for token in tokens:
+        label = token["entity_group"]
+        if label != "O":
+            token["label"] = label
+            entities.append(token)
+    
+    params = [{"text": sentence,
+               "ents": entities,
+               "title": None}]
+    
+    html = displacy.render(params, style="ent", manual=True, options={
+        "colors": {
+                   "DRUG": "#f08080",
+                   "ADR": "#9bddff",
+               },
+    })
+    return html
+
+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"]
+
+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="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="Adverse Drug Reaction Xtractor",theme="huggingface",layout='horizontal')
+iface.launch()

requirements.txt

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+spacy==3.0.2
+torch==1.5.0
+transformers==4.12.5