Update app.py

app.py

@@ -81,35 +81,11 @@ def theme_classification(text, text_classifier):
 
 sid_obj = SentimentIntensityAnalyzer()
 classifier = pipeline("zero-shot-classification", model="joeddav/xlm-roberta-large-xnli")
-dataset = load_dataset('csv', data_files=["Hugging Face DF.csv"], delimiter=',', column_names=["date", "url", "texts", "is_title", "theme", "translated"])
-df = pd.DataFrame(dataset)
-new_df = pd.DataFrame()
-
-dates = []
-is_title = []
-texts = []
-themes = []
-trans_text = []
-url = []
-
-st.dataframe(df)
-
-for i in range(len(dataset)):
-    dates.append(dataset["train"][i]["date"])
-    is_title.append(dataset["train"][i]["is_title"])
-    texts.append(dataset["train"][i]["texts"])
-    themes.append(dataset["train"][i]["theme"])
-    trans_text.append(dataset["train"][i]["translated"])
-    url.append(dataset["train"][i]["url"])   
-
-new_df["date"] = dates
-new_df["text"] = texts
-new_df["theme"] = themes
-new_df["translated"] = trans_text
-new_df["is_title"] = is_title
-new_df["url"] = url
-
-df = new_df[:]
+
+sheet_id = "1IGFSKnnmQndKVmGOWMCbsvJJMU_2jvnm"
+sheet_name = "Sheet1"
+url = f"https://docs.google.com/spreadsheets/d/{sheet_id}/gviz/tq?tqx=out:csv&sheet={sheet_name}"
+df = pd.read_csv(url)
 
 header = st.container()
 model = st.container()