Update app.py

app.py

@@ -1,45 +1,28 @@
 import math
 import gradio as gr
 import pandas as pd
-from huggingface_hub import HfApi, hf_hub_download
+from datasets import load_dataset
 
 # ======================================================
 # CONFIG
 # ======================================================
-DATASET_REPO = "rahul7star/Wan-video"
-CSV_FILE = "train.csv"
+DATASET_NAME = "rahul7star/Wan-video"
 
 VIDEO_COL = "video"
 TEXT_COL = "text"
 DATE_COL = "date"
 
 # ======================================================
-# AUTH + DATA LOAD (LEARNED FROM YOUR SAMPLE)
+# LOAD DATASET (PRIVATE-SAFE)
 # ======================================================
-api = HfApi()  # auto-reads HUGGINGFACE_HUB_TOKEN
+# Auth is handled automatically via:
+# - `huggingface-cli login`
+# - or HUGGINGFACE_HUB_TOKEN env var
+dataset = load_dataset(DATASET_NAME, split="train")
 
-
-def load_dataset_csv():
-    """
-    Validate repo access and load CSV from private dataset.
-    """
-    # 1️⃣ Permission + existence check
-    api.repo_info(repo_id=DATASET_REPO, repo_type="dataset")
-
-    # 2️⃣ Download CSV (auth handled implicitly)
-    csv_path = hf_hub_download(
-        repo_id=DATASET_REPO,
-        filename=CSV_FILE,
-        repo_type="dataset"
-    )
-
-    # 3️⃣ Load dataframe
-    df = pd.read_csv(csv_path)
-    df = df[[VIDEO_COL, TEXT_COL, DATE_COL]].dropna().reset_index(drop=True)
-    return df
-
-
-df = load_dataset_csv()
+# Convert to pandas for easy slicing
+df = dataset.to_pandas()
+df = df[[VIDEO_COL, TEXT_COL, DATE_COL]].dropna().reset_index(drop=True)
 
 # ======================================================
 # PAGINATION LOGIC
@@ -149,7 +132,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as demo:
     gr.Markdown(
         """
         # 🎬 Wan Video Dataset Showcase  
-        Securely browsing a **private Hugging Face dataset**.
+        Powered by **Hugging Face Datasets** (private-safe).
         """
     )