Add OpenAI API

app.py

@@ -11,6 +11,13 @@ from autocorrect import Speller
 from transformers import BertTokenizer, BertForSequenceClassification
 import torch
 from torch.nn.utils.rnn import pad_sequence
+from openai import OpenAI
+from tenacity import (
+    retry,
+    stop_after_attempt,
+    wait_random_exponential,
+)  # for exponential backoff
+import os
 
 # ***************************** Load needed models *****************************
 nlp = stanza.Pipeline(lang='en', processors='tokenize,pos,constituency')
@@ -21,6 +28,35 @@ sentences_similarity_model = CrossEncoder('WillHeld/roberta-base-stsb')
 nli_model = BertForSequenceClassification.from_pretrained("nouf-sst/bert-base-MultiNLI", use_auth_token="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")
 nli_tokenizer = BertTokenizer.from_pretrained("nouf-sst/bert-base-MultiNLI", use_auth_token="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", do_lower_case=True)
 
+
+# ***************************** GPT API *****************************
+client = OpenAI(
+    api_key=os.getenv("OpenAI"),
+)
+
+
+@retry(wait=wait_random_exponential(min=1, max=60), stop=stop_after_attempt(6))
+def completion_with_backoff(**kwargs):
+    return client.chat.completions.create(**kwargs)
+
+def prompt(prompt_message, bad_smell):
+  message = [
+        {
+          "role": "system",
+          "content": prompt_message
+          },
+        {
+          "role": "user",
+          "content": bad_smell
+        }
+  ]
+  completion = completion_with_backoff(
+        model="gpt-3.5-turbo",
+        messages=message,
+        temperature= 0.2,
+      )
+  return completion.choices[0].message.content
+    
 # ***************************** TGRL Parsing *****************************
 
 def parse_tgrl(file_obj):