Update app.py

app.py

@@ -212,21 +212,12 @@ def get_ranking_trend(json_data, org_name):
         return {"id": "Not Found", "rank": "Not Found"}
 
 
-def fetch_data_from_url(url):
-    response = requests.get(url)
-    if response.status_code == 200:
-        data = response.text.splitlines()
-        return [line.strip() for line in data]
-    else:
-        print(f"Failed to fetch data from URL: {url}")
-        return []
-
 
-user_names_url = "https://huggingface.co/datasets/PulsarAI/user-orgs-huggingface-leaderboard/raw/main/user_names.txt"
-org_names_url = "https://huggingface.co/datasets/PulsarAI/user-orgs-huggingface-leaderboard/raw/main/org_names.txt"
+with open("org_names.txt", "r") as f:
+    org_names_in_list = [i.rstrip("\n") for i in f.readlines()]
 
-org_names_in_list = fetch_data_from_url(user_names_url)
-user_names_in_list = fetch_data_from_url(org_names_url)
+with open("user_names.txt", "r") as f:
+    user_names_in_list = [i.rstrip("\n") for i in f.readlines()]
 
 datetime_now = str(datetime.datetime.now().strftime("%Y-%m-%d %H:%M"))
 INTRODUCTION_TEXT = f"""
@@ -244,9 +235,9 @@ INTRODUCTION_TEXT = f"""
 
 🛠️ The leaderboard's backend mainly runs on the [Hugging Face Hub API](https://huggingface.co/docs/huggingface_hub/v0.5.1/en/package_reference/hf_api).
 
-**📝 Note:** In the model's dataframe, there are some columns related to the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). This data is also retrieved through web scraping.
+**🌐 Note:** In the model's dataframe, there are some columns related to the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard). This data is also retrieved through web scraping.
 
-**📝 Note:** In trending models/datasets/spaces, first 300 models/datasets/spaces is being retrieved from huggingface.
+**🌐 Note:** In trending models/datasets/spaces, first 300 models/datasets/spaces is being retrieved from huggingface.
 
 ## 🔍 Searching Organizations and Users
 
@@ -547,4 +538,4 @@ filtered_datasets_orgs = update_table_datasets(orgs=True, users=False, return_al
 filtered_spaces_users = update_table_spaces(orgs=False, users=True, return_all=True)['Author Name'].tolist()
 filtered_spaces_orgs = update_table_spaces(orgs=True, users=False, return_all=True)['Author Name'].tolist()
 
-demo.launch(debug=True)
+demo.launch(debug=True)