Create app.py

app.py

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+import streamlit as st
+from huggingface_hub import HfApi, HfFolder
+from datasets import load_dataset
+
+# Function to fetch dataset names for typeahead (autocomplete)
+def fetch_dataset_names(query):
+    api = HfApi()
+    datasets = api.list_datasets()
+    filtered_datasets = [d.id for d in datasets if query.lower() in d.id.lower()]
+    return filtered_datasets
+
+# Function to create a new dataset
+def create_sampled_dataset(dataset_name, num_rows, user_token):
+    # Load the dataset
+    dataset = load_dataset(dataset_name)
+
+    # Sample the dataset
+    sampled_dataset = dataset['train'].shuffle().select(range(num_rows))
+
+    # Save the sampled dataset to a file (modify this as needed)
+    sampled_dataset.to_csv('sampled_dataset.csv')
+
+    # Here you'd need to implement the logic to upload this dataset to the user's Hf account
+    # This part is not straightforward and requires using the Hf API to create a new dataset repo
+    # You'll need to refer to the Hf API documentation for details on how to implement this
+
+    return "URL_to_new_dataset"  # This should be the URL to the newly created dataset
+
+# Main app
+def main():
+    st.title("HuggingFace Dataset Sampler")
+
+    # User authentication
+    user_token = st.text_input("Enter your HuggingFace token for authentication")
+
+    # Dataset input with typeahead
+    dataset_query = st.text_input("Enter Dataset Name")
+    if dataset_query:
+        dataset_names = fetch_dataset_names(dataset_query)
+        selected_dataset = st.selectbox("Select Dataset", options=dataset_names)
+    else:
+        selected_dataset = None
+
+    # Number of rows input
+    num_rows = st.number_input("Enter number of rows to sample", min_value=1, step=1)
+
+    # Button to create new dataset
+    if st.button("Create Sampled Dataset"):
+        if user_token and selected_dataset and num_rows:
+            try:
+                # Create the sampled dataset and get its URL
+                dataset_url = create_sampled_dataset(selected_dataset, num_rows, user_token)
+                st.success(f"Dataset created successfully! Find it here: {dataset_url}")
+            except Exception as e:
+                st.error(f"Error: {e}")
+        else:
+            st.error("Please fill in all required fields.")
+
+if __name__ == "__main__":
+    main()