Add files

app.py

@@ -1,8 +1,8 @@
+import torch
 from transformers import pipeline
 from transformers import AutoModelForSeq2SeqLM
 from transformers import AutoTokenizer
 
-
 # Load trained model
 model = AutoModelForSeq2SeqLM.from_pretrained("/output/reframer")
 tokenizer = AutoTokenizer.from_pretrained("/output/reframer")
@@ -11,6 +11,18 @@ reframer = pipeline('summarization', model=model, tokenizer=tokenizer)
 
 def reframe(text, strategy):
     text_with_strategy = text +  "Strategy: ['" + strategy + "']"
+    #Input Control
+    #The input text cannot be too short to ensure it has substantial content to be reframed. It also cannot be too long to ensure the text has a focused idea.
+    if len(text) < 15 or len(text) > 150:
+      return "Please try again by inputing text with moderate length."
+    if TextBlob(text).sentiment.polarity > 0.2:
+      return "Please try again by inputing text that is negative."
+    from hatesonar import Sonar
+    sonar = Sonar()
+    if sonar.ping(text)['classes'][1]['confidence'] > 0.8:
+      return "Please try again by not inputing offensive language."
+    #if TextBlob(text).sentiment.polarity > 0:
+    #  return "Please try again by inputing text that is negative."
     return reframer(text_with_strategy)[0]['summary_text']
 
 

requirements.txt

@@ -1,2 +1,4 @@
 gradio==3.3.1
+hatesonar==0.0.7
+torch==1.8.0
 transformers==4.10.0