helper functions

utility.py

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+import os
+import urllib.request
+import gradio as gr
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+import huggingface_hub
+import re
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import time
+import transformers
+import requests
+import globals
+
+def fetch_model(url, filename):
+    if not os.path.isfile(filename):
+        urllib.request.urlretrieve(url, filename)
+        print("File downloaded successfully.")
+    else:
+        print("File already exists.")
+
+def api_query(API_URL, headers, payload):
+  response = requests.post(API_URL, headers=headers, json=payload)
+  return response.json()
+
+def post_process(model_output,input):
+  start_pos = model_output.find(input)
+  if start_pos != -1:
+    answer = model_output[start_pos + len(input):].strip()
+  else:
+    answer = model_output
+    print("'Literal meaning:' not found in the text.")
+  answer.replace("\n", "")
+  return answer