Update app.py

app.py

@@ -1,36 +1,4 @@
-import torch
-import gradio
-from transformers import pipeline
-from bs4 import BeautifulSoup
-import requests
-
-def SUMMARIZE(Url):
-    summarizer = pipeline("summarization", model="stevhliu/my_awesome_billsum_model")
-    r = requests.get(Url)
-    soup = BeautifulSoup(r.text, 'html.parser')
-    results = soup.find_all(['hl', 'p'])
-    text = [result.text for result in results]
-    Article = ''.join(text)
-    sentences = Article.split(' ')
-    current_chunk = 0
-    chunks = []
-    for sentence in sentences:
-        if len(chunks) == current_chunk + 1:
-            if len(chunks[current_chunk]) + len(sentence.split(' ')) <= max_chunk:
-                chunks[current_chunk].extend(sentence.split(' '))
-            else:
-                current_chunk += 1
-                chunks.append(sentence.split(' '))
-        else:
-            #print(current_chunk)
-            chunks.append(sentence.split(' '))
-
-    for chunk_id in range(len(chunks)):
-        chunks[chunk_id] = ' '.join(chunks[chunk_id])
-    res = summarizer(chunks, max_length=120, min_length=30, do_sample=False)
-    for i in range(len(res)):
-        return res[i].values()
-        
+from util import SUMMARIZE
 
 interface = gradio.Interface(fn=SUMMARIZE,
                              inputs=gradio.TextArea(lines=2, value="https://medium.com/analytics-vidhya/openai-gpt-3-language-models-are-few-shot-learners-82531b3d3122"),