Update app.py

app.py

@@ -7,12 +7,13 @@ nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
 
 # dataset save ------------------------------------
 import huggingface_hub
+import os
 from huggingface_hub import Repository, hf_hub_download, upload_file
 from datetime import datetime
 # created new dataset as awacke1/MindfulStory.csv
-DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/MindfulStory.csv"
-DATASET_REPO_ID = "awacke1/MindfulStory.csv"
-DATA_FILENAME = "MindfulStory.csv"
+DATASET_REPO_URL = "https://huggingface.co/datasets/awacke1/WikipediaSearch"
+DATASET_REPO_ID = "awacke1/WikipediaSearch.csv"
+DATA_FILENAME = "WikipediaSearch.csv"
 DATA_FILE = os.path.join("data", DATA_FILENAME)
 HF_TOKEN = os.environ.get("HF_TOKEN")
 # Download dataset repo using hub download
@@ -90,4 +91,6 @@ examples = [
     ['Pharmacy', 'What does a pharmacist do?']     
 ]
 
-gr.Interface(get_answer, inputs, outputs, title=title, description=description, article=article, examples=examples, flagging_options=["strongly related","related", "neutral", "unrelated", "strongly unrelated"]).launch(share=False,enable_queue=False)
+gr.Interface(get_answer, inputs, outputs, title=title, description=description, article=article, examples=examples, 
+article="Saved dataset: https://huggingface.co/datasets/awacke1/WikipediaSearch",
+flagging_options=["strongly related","related", "neutral", "unrelated", "strongly unrelated"]).launch(share=False,enable_queue=False)