added code for logs save

app.py

@@ -3,13 +3,37 @@ import requests
 import os
 import numpy as np
 import pandas as pd
-import io
-import os
+=import json
 # from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, AutoModelForSequenceClassification
 from questiongenerator import QuestionGenerator
 
 qg = QuestionGenerator()
-# num_que = 5
+
+HF_TOKEN = os.environ.get("HF_TOKEN")
+DATASET_NAME = "Question_Generation_T5"
+DATASET_REPO_URL = f"https://huggingface.co/datasets/pragnakalp/{DATASET_NAME}"
+DATA_FILENAME = "que_gen_logs.json"
+DATA_FILE = os.path.join("que_gen_logs", DATA_FILENAME)
+DATASET_REPO_ID = "pragnakalp/Question_Generation_T5"
+print("is none?", HF_TOKEN is None)
+# REPOSITORY_DIR = "data"
+# LOCAL_DIR = 'data_local'
+# os.makedirs(LOCAL_DIR,exist_ok=True)
+
+try:
+    hf_hub_download(
+        repo_id=DATASET_REPO_ID,
+        filename=DATA_FILENAME,
+        cache_dir=DATA_DIRNAME,
+        force_filename=DATA_FILENAME
+    )
+    
+except:
+    print("file not found")
+
+repo = Repository(
+    local_dir="que_gen_logs", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
+)
 
 def generate_questions(article,num_que):
     result = ''
@@ -23,9 +47,17 @@ def generate_questions(article,num_que):
         "generated_questions" : generated_questions_list
     }
     generated_questions = summarized_data.get("generated_questions",'')
+    entry = {"article": article, "generated_questions": generated_questions, "num_of_question": num_que}
+    with open(DATA_FILE, "r") as file:
+        data = json.load(file)
+    data.append(entry)
+    with open(DATA_FILE, "w") as file:
+        json.dump(data, file)
+        commit_url = repo.push_to_hub()
     for q in generated_questions:
         print(q)
         result = result + q + '\n'
+        
     return result
 
 ## design 1