fix bugs for hg 1.17

app.py

@@ -15,24 +15,25 @@ repo_id = "friendshipkim/IUR_Reddit"
 # ABSOLUTE_PATH = os.path.dirname(__file__)
 # ASSETS_PATH = os.path.join(ABSOLUTE_PATH, 'model_assets')
 
-@st.cache_data
+@st.cache
 def preprocess_text(s):
 	return list(filter(lambda x: x!= '', (''.join(c if c.isalnum() or c == ' ' else ' ' for c in s)).split(' ')))
 
-@st.cache_data
+@st.cache
 def get_pairwise_distances(model):
     # df = pd.read_csv(f"{ASSETS_PATH}/{model}/pairwise_distances.csv").set_index('index')
     df = pd.read_csv(hf_hub_download(repo_id=repo_id, filename="pairwise_distances.csv")).set_index('index')
     return df
 
-@st.cache_data
+@st.cache
 def get_pairwise_distances_chunked(model, chunk):
 	# for df in pd.read_csv(f"{ASSETS_PATH}/{model}/pairwise_distances.csv", chunksize = 16):
 	# 	print(df.iloc[0]['queries'])
 	# 	if chunk == int(df.iloc[0]['queries']):
 	# 		return df
 	return get_pairwise_distances(model)
-@st.cache_data
+
+@st.cache
 def get_query_strings():
     # df = pd.read_json(f"{ASSETS_PATH}/IUR_Reddit_test_queries_english.jsonl", lines = True)
     df = pd.read_json(hf_hub_download(repo_id=repo_id, filename="IUR_Reddit_test_queries_english.jsonl"), lines = True)
@@ -42,7 +43,8 @@ def get_query_strings():
 	# df.to_parquet(f"{ASSETS_PATH}/IUR_Reddit_test_queries_english.parquet", index = 'index', partition_cols = 'partition')
 	
 	# return pd.read_parquet(f"{ASSETS_PATH}/IUR_Reddit_test_queries_english.parquet", columns=['fullText', 'index', 'authorIDs'])
-@st.cache_data
+
+@st.cache
 def get_candidate_strings():
     # df = pd.read_json(f"{ASSETS_PATH}/IUR_Reddit_test_candidates_english.jsonl", lines = True)
     df = pd.read_json(hf_hub_download(repo_id=repo_id, filename="IUR_Reddit_test_candidates_english.jsonl"), lines = True)
@@ -52,26 +54,28 @@ def get_candidate_strings():
 	# df.to_parquet(f"{ASSETS_PATH}/IUR_Reddit_test_candidates_english.parquet", index = 'index', partition_cols = 'partition')
 	# return pd.read_parquet(f"{ASSETS_PATH}/IUR_Reddit_test_candidates_english.parquet", columns=['fullText', 'index', 'authorIDs'])
 
-@st.cache_data
+@st.cache
 def get_embedding_dataset(model):
     # data = load_from_disk(f"{ASSETS_PATH}/{model}/embedding")
     data = load_dataset("friendshipkim/luar_clone2_top_100_embedding")
     return data
 
-@st.cache_data
+@st.cache
 def get_bad_queries(model):
 	df = get_query_strings().iloc[list(get_pairwise_distances(model)['queries'].unique())][['fullText', 'index', 'authorIDs']]
 	return df
-@st.cache_data
+
+@st.cache
 def get_gt_candidates(model, author):
 	gt_candidates = get_candidate_strings()
 	df = gt_candidates[gt_candidates['authorIDs'].apply(lambda x: x[0]) == author]
 	return df
-@st.cache_data
+
+@st.cache
 def get_candidate_text(l):
 	return get_candidate_strings().at[l,'fullText']
 
-@st.cache_data
+@st.cache
 def get_annotated_text(text, word, pos):
 	# print("here", word, pos)
 	start= text.index(word, pos)

requirements.txt

@@ -68,7 +68,7 @@ urllib3==1.26.13
 wasabi==0.10.1
 xxhash==3.1.0
 yarl==1.8.2
-streamlit==1.20.0
+streamlit==1.17.0
 streamlit-aggrid
 st-annotated-text
 --extra-index-url http://download.pytorch.org/whl/cu116