auto push

app.py

@@ -217,265 +217,387 @@
 
 # demo.launch()
 
-import gradio as gr
-import polars as pl
-from huggingface_hub import HfApi
-import re
-# --- Hugging Face Org ---
-org_name = "hugging-science"
-api = HfApi()
+# import gradio as gr
+# import polars as pl
+# from huggingface_hub import HfApi
+# import re
+# # --- Hugging Face Org ---
+# org_name = "hugging-science"
+# api = HfApi()
 
-def fetch_members():
-    members = api.list_organization_members(org_name)
-    return [member.username for member in members]
+# def fetch_members():
+#     members = api.list_organization_members(org_name)
+#     return [member.username for member in members]
 
-member_list = fetch_members()
+# member_list = fetch_members()
 
-# --- Dataset ---
-COMBINED_PARQUET_PATH = "datasetcards_new.parquet"
-UPDATED_PARQUET_PATH = "datasetcards_new.parquet"
-ROWS_PER_PAGE = 50
+# # --- Dataset ---
+# COMBINED_PARQUET_PATH = "datasetcards_new.parquet"
+# UPDATED_PARQUET_PATH = "datasetcards_new.parquet"
+# ROWS_PER_PAGE = 50
 
+# # df = pl.read_parquet(COMBINED_PARQUET_PATH)
 # df = pl.read_parquet(COMBINED_PARQUET_PATH)
-df = pl.read_parquet(COMBINED_PARQUET_PATH)
-df = df.with_columns([
-    pl.lit("todo").alias("status"),
-    pl.lit("").alias("assigned_to")
-]).sort(by=["downloads", "last_modified", "usedStorage"], descending=[True, True, True])
-
-if "reason" in df.columns:
-    df = df.with_columns([
-        pl.Series(
-            "reason",
-            ["short description" if x and "short description" in x.lower() else (x if x is not None else "") for x in df["reason"]]
-        )
-    ])
-
-
-
-
-# Add editable columns if missing
-for col in ["assigned_to", "status"]:
-    if col not in df.columns:
-        default_val = "" if col == "assigned_to" else "todo"
-        df = df.with_columns(pl.lit(default_val).alias(col))
-    else:
-        # Fill nulls with default
-        default_val = "" if col == "assigned_to" else "todo"
-        df = df.with_columns(pl.col(col).fill_null(default_val))
-
-# --- Columns ---
-DROPDOWN_COLUMNS = ["reason", "category", "field", "keyword", "assigned_to", "status"]
-STATUS_OPTIONS = ["todo", "inprogress", "PR submitted", "PR merged"]
-
-# Prepare unique values for dropdown search
-unique_values = {col: sorted(df[col].drop_nulls().unique().to_list()) for col in DROPDOWN_COLUMNS}
-unique_values['assigned_to'] = sorted(member_list)
-unique_values['status'] = STATUS_OPTIONS
-
-# --- Helper to get page ---
-def get_page(df, page, column=None, query=None):
-    filtered_df = df
-    if column and query:
-        if column in DROPDOWN_COLUMNS:
-            filtered_df = filtered_df.filter(pl.col(column) == query)
+# df = df.with_columns([
+#     pl.lit("todo").alias("status"),
+#     pl.lit("").alias("assigned_to")
+# ]).sort(by=["downloads", "last_modified", "usedStorage"], descending=[True, True, True])
+
+# if "reason" in df.columns:
+#     df = df.with_columns([
+#         pl.Series(
+#             "reason",
+#             ["short description" if x and "short description" in x.lower() else (x if x is not None else "") for x in df["reason"]]
+#         )
+#     ])
+
+
+
+
+# # Add editable columns if missing
+# for col in ["assigned_to", "status"]:
+#     if col not in df.columns:
+#         default_val = "" if col == "assigned_to" else "todo"
+#         df = df.with_columns(pl.lit(default_val).alias(col))
+#     else:
+#         # Fill nulls with default
+#         default_val = "" if col == "assigned_to" else "todo"
+#         df = df.with_columns(pl.col(col).fill_null(default_val))
+
+# # --- Columns ---
+# DROPDOWN_COLUMNS = ["reason", "category", "field", "keyword", "assigned_to", "status"]
+# STATUS_OPTIONS = ["todo", "inprogress", "PR submitted", "PR merged"]
+
+# # Prepare unique values for dropdown search
+# unique_values = {col: sorted(df[col].drop_nulls().unique().to_list()) for col in DROPDOWN_COLUMNS}
+# unique_values['assigned_to'] = sorted(member_list)
+# unique_values['status'] = STATUS_OPTIONS
+
+# # --- Helper to get page ---
+# def get_page(df, page, column=None, query=None):
+#     filtered_df = df
+#     if column and query:
+#         if column in DROPDOWN_COLUMNS:
+#             filtered_df = filtered_df.filter(pl.col(column) == query)
+#         else:
+#             q = query.lower().strip()
+#             filtered_df = (
+#                 filtered_df.with_columns([pl.col(column).str.to_lowercase().alias(column)])
+#                 .filter(pl.col(column).str.contains(q, literal=False))
+#             )
+#     start = page * ROWS_PER_PAGE
+#     page_df = filtered_df[start:start + ROWS_PER_PAGE].to_pandas().fillna("")
+#     total_rows = filtered_df.height
+#     total_pages = (total_rows - 1) // ROWS_PER_PAGE + 1 if total_rows > 0 else 1
+#     return page_df, total_pages
+
+# initial_df, total_pages = get_page(df, 0)
+# columns = list(initial_df.columns)
+
+# with gr.Blocks() as demo:
+#     gr.Markdown("""
+#     # Dataset Insight Portal
+
+#     Welcome! This portal helps you explore and manage datasets from our Hugging Face organization.
+
+#     ## What is this space for?
+#     This space provides a table of datasets along with metadata. You can:
+#     - Browse datasets with pagination.
+#     - Search datasets by various fields.
+#     - Assign responsibility for reviewing datasets (`assigned_to`).
+#     - Track progress using `status`.
+
+#     ## Why the table?
+#     The table gives a structured view of all datasets, making it easy to sort, filter, and update information for each dataset. It consists of all datasets until 20-09-2025. 
+
+#     ## What does the table contain?
+#     Each row represents a dataset. Columns include:
+#     - **dataset_id**: Unique identifier of the dataset.
+#     - **dataset_url**: Link to the dataset page on Hugging Face.
+#     - **downloads**: Number of downloads.
+#     - **author**: Dataset author.
+#     - **license**: License type.
+#     - **tags**: Tags describing the dataset. Obtained from the dataset card.
+#     - **task_categories**: Categories of tasks the dataset is useful for. Obtained from the dataset card.
+#     - **last_modified**: Date of last update.
+#     - **field, keyword**: Metadata columns describing dataset purpose based on heuristics. Use the `field` and `keyword` to filter for science based datasets.
+#     - **category**: Category of the dataset (`rich` means it is good dataset card. `minimal` means it needs improvement for the reasons below).
+#     - **reason**: Reason why the dataset is classified as `minimal`. Options: `Failed to load card`, `No metadata and no description`, `No metadata and has description`, `Short description`.
+#     - **usedStorage**: Storage used by the dataset (bytes).
+#     - **assigned_to**: Person responsible for the dataset (editable).
+#     - **status**: Progress status (editable). Options: `todo`, `inprogress`, `PR submitted`, `PR merged`.
+
+#     ## How to use search
+#     - Select a **column** from the dropdown.
+#     - If the column is textual, type your query in the text box.
+#     - If the column is a dropdown (like `assigned_to` or `status`), select the value from the dropdown.
+#     - Click **Search** to filter the table.
+
+#     ## How to add or update `assigned_to` and `status`
+#     1. Search for the **dataset_id** initially.
+#     2. Then, select the **dataset_id** from the dropdown below the table.
+#     3. Choose the person responsible in **Assigned To**. If you are a member of the organization, your username should appear in the list. Else refresh and try again.
+#     4. Select the current status in **Status**.
+#     5. Click **Save Changes** to update the table and persist the changes.
+#     6. Use **Refresh All** to reload the table and the latest members list.
+
+#     This portal makes it easy to keep track of dataset reviews, assignments, and progress all in one place.
+#     """)
+
+#     # --- Pagination controls ---
+#     with gr.Row():
+#         prev_btn = gr.Button("Previous")
+#         next_btn = gr.Button("Next")
+#         page_number = gr.Number(value=0, label="Page", precision=0)
+#         total_pages_display = gr.Label(value=f"Total Pages: {total_pages}")
+
+#     # --- Data table ---
+#     data_table = gr.Dataframe(
+#         value=initial_df,
+#         headers=columns,
+#         datatype="str",
+#         interactive=False,
+#         row_count=ROWS_PER_PAGE
+#     )
+
+#     # --- Search controls ---
+#     with gr.Row():
+#         col_dropdown = gr.Dropdown(choices=columns, label="Column to Search")
+#         search_text = gr.Textbox(label="Search Text")
+#         search_dropdown = gr.Dropdown(choices=[], label="Select Value", visible=False)
+#         search_btn = gr.Button("Search")
+#         reset_btn = gr.Button("Reset")
+
+#     # --- Dataset selection & editable fields ---
+#     selected_dataset_id = gr.Dropdown(label="Select dataset_id", choices=initial_df['dataset_id'].tolist())
+#     assigned_to_input = gr.Dropdown(choices=member_list, label="Assigned To")
+#     # status_input = gr.Dropdown(choices=STATUS_OPTIONS, label="Status")
+#     status_input = gr.Dropdown(choices=STATUS_OPTIONS, label="Status", value="todo")
+
+
+#     save_btn = gr.Button("Save Changes")
+#     refresh_btn = gr.Button("Refresh All")
+#     save_message = gr.Textbox(label="Save Status", interactive=False)
+
+#     # --- Update search input depending on column ---
+#     def update_search_input(column):
+#         if column in DROPDOWN_COLUMNS:
+#             return gr.update(choices=unique_values[column], visible=True), gr.update(visible=False)
+#         else:
+#             return gr.update(visible=False), gr.update(visible=True)
+
+#     col_dropdown.change(update_search_input, col_dropdown, [search_dropdown, search_text])
+
+#     # --- Prefill editable fields ---
+#     def prefill_fields(dataset_id):
+#         if not dataset_id:
+#             return "", "todo"
+#         dataset_id = str(dataset_id)
+#         filtered = [row for row in df.to_dicts() if str(row.get("dataset_id")) == dataset_id]
+#         if not filtered:
+#             return "", "todo"
+#         row = filtered[0]
+#         return row.get("assigned_to", ""), row.get("status", "todo")
+
+#     selected_dataset_id.change(prefill_fields, selected_dataset_id, [assigned_to_input, status_input])
+
+#     # --- Search function ---
+#     def search_func(page, column, txt, ddl):
+#         query = ddl if column in DROPDOWN_COLUMNS else txt
+#         page_df, total_pages = get_page(df, page, column, query)
+#         return page_df, f"Total Pages: {total_pages}", 0, gr.update(choices=page_df['dataset_id'].tolist())
+
+#     # --- Pagination functions ---
+#     def next_page(page, column, txt, ddl):
+#         page += 1
+#         query = ddl if column in DROPDOWN_COLUMNS else txt
+#         page_df, total_pages = get_page(df, page, column, query)
+#         if page >= total_pages:
+#             page = total_pages - 1
+#             page_df, total_pages = get_page(df, page, column, query)
+#         return page_df, f"Total Pages: {total_pages}", page, gr.update(choices=page_df['dataset_id'].tolist())
+
+#     def prev_page(page, column, txt, ddl):
+#         page = max(0, page - 1)
+#         query = ddl if column in DROPDOWN_COLUMNS else txt
+#         page_df, total_pages = get_page(df, page, column, query)
+#         return page_df, f"Total Pages: {total_pages}", page, gr.update(choices=page_df['dataset_id'].tolist())
+
+#     def reset_func():
+#         page_df, total_pages = get_page(df, 0)
+#         return page_df, f"Total Pages: {total_pages}", 0, gr.update(choices=page_df['dataset_id'].tolist())
+
+#     # --- Save changes & refresh ---
+#     def save_changes(dataset_id, assigned_to_val, status_val, page_val, col, txt, ddl):
+#         global df
+#         if not dataset_id:
+#             return gr.update(value="Please select a row first."), None, None, None
+#         df = df.with_columns([
+#             pl.when(pl.col("dataset_id") == dataset_id).then(pl.lit(assigned_to_val)).otherwise(pl.col("assigned_to")).alias("assigned_to"),
+#             pl.when(pl.col("dataset_id") == dataset_id).then(pl.lit(status_val)).otherwise(pl.col("status")).alias("status")
+#         ])
+#         df.write_parquet(UPDATED_PARQUET_PATH)
+#         page_df, total_pages = get_page(df, page_val, col, txt if col not in DROPDOWN_COLUMNS else ddl)
+#         return (
+#             gr.update(value=f"Saved changes for dataset_id: {dataset_id}"),
+#             page_df,
+#             gr.update(choices=page_df['dataset_id'].tolist()),
+#             f"Total Pages: {total_pages}"
+#         )
+
+#     # --- Refresh All: table + members ---
+#     def refresh_all(page, column, txt, ddl):
+#         global df, member_list, unique_values
+#         # Refresh members
+#         member_list = fetch_members()
+#         unique_values['assigned_to'] = sorted(member_list)
+#         # Refresh table
+#         try:
+#             df = pl.read_parquet(UPDATED_PARQUET_PATH)
+#         except FileNotFoundError:
+#             pass
+#         page_df, total_pages = get_page(df, page, column, txt if column not in DROPDOWN_COLUMNS else ddl)
+#         return page_df, f"Total Pages: {total_pages}", page, gr.update(choices=page_df['dataset_id'].tolist()), gr.update(choices=member_list)
+
+#     # --- Wire buttons ---
+#     inputs_search = [page_number, col_dropdown, search_text, search_dropdown]
+#     outputs_search = [data_table, total_pages_display, page_number, selected_dataset_id]
+
+#     search_btn.click(search_func, inputs_search, outputs_search)
+#     next_btn.click(next_page, inputs_search, outputs_search)
+#     prev_btn.click(prev_page, inputs_search, outputs_search)
+#     reset_btn.click(reset_func, [], outputs_search)
+#     save_btn.click(
+#         save_changes,
+#         [selected_dataset_id, assigned_to_input, status_input, page_number, col_dropdown, search_text, search_dropdown],
+#         [save_message, data_table, selected_dataset_id, total_pages_display]
+#     )
+#     refresh_btn.click(
+#         refresh_all,
+#         inputs=[page_number, col_dropdown, search_text, search_dropdown],
+#         outputs=[data_table, total_pages_display, page_number, selected_dataset_id, assigned_to_input]
+#     )
+
+# demo.launch()
+
+
+
+
+import gradio as gr
+import polars as pl
+import os
+import subprocess
+import threading
+import time
+
+# --- Config ---
+COMBINED_PARQUET_PATH = "datasetcards_new.parquet"
+UPDATED_PARQUET_PATH = "datasetcards_new.parquet"  # overwrite same file
+ROWS_PER_PAGE = 50
+ORG_NAME = "hugging-science"   # replace with your org
+SPACE_NAME = "dataset-insight-portal" # replace with your space
+
+# --- Load dataset ---
+df = pl.read_parquet(COMBINED_PARQUET_PATH).with_columns([
+    pl.lit("").alias("assigned_to"),
+    pl.lit("todo").alias("status")
+])
+columns = df.columns
+total_pages = (len(df) + ROWS_PER_PAGE - 1) // ROWS_PER_PAGE
+
+# --- Git push helpers ---
+def save_and_push():
+    """Commit and push parquet file changes to the repo."""
+    try:
+        subprocess.run(["git", "config", "--global", "user.email", "[email protected]"])
+        subprocess.run(["git", "config", "--global", "user.name", "Santosh Sanjeev"])
+
+        hf_token = os.environ["HF_TOKEN"]
+        repo_url = f"https://user:{hf_token}@huggingface.co/spaces/{ORG_NAME}/{SPACE_NAME}"
+        subprocess.run(["git", "remote", "set-url", "origin", repo_url])
+
+        # Commit only if parquet changed
+        subprocess.run(["git", "add", UPDATED_PARQUET_PATH])
+        result = subprocess.run(["git", "diff", "--cached", "--quiet"])
+        if result.returncode != 0:
+            subprocess.run(["git", "commit", "-m", "Auto-update parquet file"])
+            subprocess.run(["git", "push", "origin", "main"])
+            print("✅ Pushed parquet to repo")
         else:
-            q = query.lower().strip()
-            filtered_df = (
-                filtered_df.with_columns([pl.col(column).str.to_lowercase().alias(column)])
-                .filter(pl.col(column).str.contains(q, literal=False))
-            )
-    start = page * ROWS_PER_PAGE
-    page_df = filtered_df[start:start + ROWS_PER_PAGE].to_pandas().fillna("")
-    total_rows = filtered_df.height
-    total_pages = (total_rows - 1) // ROWS_PER_PAGE + 1 if total_rows > 0 else 1
-    return page_df, total_pages
-
-initial_df, total_pages = get_page(df, 0)
-columns = list(initial_df.columns)
+            print("ℹ️ No parquet changes to push")
+    except Exception as e:
+        print("⚠️ Push failed:", e)
+
+def auto_push_loop(interval=300):
+    """Run save_and_push every `interval` seconds (default 5 min)."""
+    while True:
+        save_and_push()
+        time.sleep(interval)
+
+# --- Gradio app functions ---
+def get_page(page_num, col, search_text, search_dropdown):
+    global df
+    filtered = df
+
+    if col and col in df.columns:
+        if col in DROPDOWN_COLUMNS and search_dropdown:
+            filtered = filtered.filter(pl.col(col) == search_dropdown)
+        elif search_text:
+            filtered = filtered.filter(pl.col(col).cast(str).str.contains(search_text, literal=False))
+
+    total_pages = (len(filtered) + ROWS_PER_PAGE - 1) // ROWS_PER_PAGE
+    start, end = (page_num - 1) * ROWS_PER_PAGE, page_num * ROWS_PER_PAGE
+    page_df = filtered[start:end]
+    return page_df.to_pandas(), f"of {total_pages}", page_num, "", "", ""
+
+def save_changes(dataset_id, assigned_to, status):
+    global df
+    mask = df["dataset_id"] == dataset_id
+    if mask.any():
+        df = df.with_columns([
+            pl.when(mask).then(assigned_to).otherwise(df["assigned_to"]).alias("assigned_to"),
+            pl.when(mask).then(status).otherwise(df["status"]).alias("status")
+        ])
+        df.write_parquet(UPDATED_PARQUET_PATH)
+        save_and_push()  # push immediately after change
+    return f"Saved for {dataset_id} ✅"
+
+def refresh_all(page_num, col, search_text, search_dropdown):
+    return get_page(page_num, col, search_text, search_dropdown)
+
+# --- UI ---
+DROPDOWN_COLUMNS = ["status", "assigned_to"]
 
 with gr.Blocks() as demo:
-    gr.Markdown("""
-    # Dataset Insight Portal
-
-    Welcome! This portal helps you explore and manage datasets from our Hugging Face organization.
-
-    ## What is this space for?
-    This space provides a table of datasets along with metadata. You can:
-    - Browse datasets with pagination.
-    - Search datasets by various fields.
-    - Assign responsibility for reviewing datasets (`assigned_to`).
-    - Track progress using `status`.
-
-    ## Why the table?
-    The table gives a structured view of all datasets, making it easy to sort, filter, and update information for each dataset. It consists of all datasets until 20-09-2025. 
-
-    ## What does the table contain?
-    Each row represents a dataset. Columns include:
-    - **dataset_id**: Unique identifier of the dataset.
-    - **dataset_url**: Link to the dataset page on Hugging Face.
-    - **downloads**: Number of downloads.
-    - **author**: Dataset author.
-    - **license**: License type.
-    - **tags**: Tags describing the dataset. Obtained from the dataset card.
-    - **task_categories**: Categories of tasks the dataset is useful for. Obtained from the dataset card.
-    - **last_modified**: Date of last update.
-    - **field, keyword**: Metadata columns describing dataset purpose based on heuristics. Use the `field` and `keyword` to filter for science based datasets.
-    - **category**: Category of the dataset (`rich` means it is good dataset card. `minimal` means it needs improvement for the reasons below).
-    - **reason**: Reason why the dataset is classified as `minimal`. Options: `Failed to load card`, `No metadata and no description`, `No metadata and has description`, `Short description`.
-    - **usedStorage**: Storage used by the dataset (bytes).
-    - **assigned_to**: Person responsible for the dataset (editable).
-    - **status**: Progress status (editable). Options: `todo`, `inprogress`, `PR submitted`, `PR merged`.
-
-    ## How to use search
-    - Select a **column** from the dropdown.
-    - If the column is textual, type your query in the text box.
-    - If the column is a dropdown (like `assigned_to` or `status`), select the value from the dropdown.
-    - Click **Search** to filter the table.
-
-    ## How to add or update `assigned_to` and `status`
-    1. Search for the **dataset_id** initially.
-    2. Then, select the **dataset_id** from the dropdown below the table.
-    3. Choose the person responsible in **Assigned To**. If you are a member of the organization, your username should appear in the list. Else refresh and try again.
-    4. Select the current status in **Status**.
-    5. Click **Save Changes** to update the table and persist the changes.
-    6. Use **Refresh All** to reload the table and the latest members list.
-
-    This portal makes it easy to keep track of dataset reviews, assignments, and progress all in one place.
-    """)
-
-    # --- Pagination controls ---
     with gr.Row():
-        prev_btn = gr.Button("Previous")
-        next_btn = gr.Button("Next")
-        page_number = gr.Number(value=0, label="Page", precision=0)
-        total_pages_display = gr.Label(value=f"Total Pages: {total_pages}")
-
-    # --- Data table ---
-    data_table = gr.Dataframe(
-        value=initial_df,
-        headers=columns,
-        datatype="str",
-        interactive=False,
-        row_count=ROWS_PER_PAGE
-    )
-
-    # --- Search controls ---
-    with gr.Row():
-        col_dropdown = gr.Dropdown(choices=columns, label="Column to Search")
+        col_dropdown = gr.Dropdown(choices=columns, label="Search Column")
         search_text = gr.Textbox(label="Search Text")
-        search_dropdown = gr.Dropdown(choices=[], label="Select Value", visible=False)
-        search_btn = gr.Button("Search")
-        reset_btn = gr.Button("Reset")
+        search_dropdown = gr.Dropdown(choices=["todo", "inprogress", "PR submitted", "PR merged"], label="Status")
+
+    with gr.Row():
+        page_number = gr.Number(value=1, precision=0, label="Page #")
+        total_pages_display = gr.Textbox(value=f"of {total_pages}", interactive=False)
 
-    # --- Dataset selection & editable fields ---
-    selected_dataset_id = gr.Dropdown(label="Select dataset_id", choices=initial_df['dataset_id'].tolist())
-    assigned_to_input = gr.Dropdown(choices=member_list, label="Assigned To")
-    # status_input = gr.Dropdown(choices=STATUS_OPTIONS, label="Status")
-    status_input = gr.Dropdown(choices=STATUS_OPTIONS, label="Status", value="todo")
+    data_table = gr.Dataframe(headers=columns, datatype=["str"] * len(columns), row_count=ROWS_PER_PAGE)
 
+    selected_dataset_id = gr.Textbox(label="Selected Dataset ID", interactive=False)
+    assigned_to_input = gr.Textbox(label="Assigned To")
+    status_input = gr.Dropdown(choices=["todo", "inprogress", "PR submitted", "PR merged"], label="Status")
 
     save_btn = gr.Button("Save Changes")
-    refresh_btn = gr.Button("Refresh All")
-    save_message = gr.Textbox(label="Save Status", interactive=False)
+    refresh_btn = gr.Button("Refresh")
 
-    # --- Update search input depending on column ---
-    def update_search_input(column):
-        if column in DROPDOWN_COLUMNS:
-            return gr.update(choices=unique_values[column], visible=True), gr.update(visible=False)
-        else:
-            return gr.update(visible=False), gr.update(visible=True)
-
-    col_dropdown.change(update_search_input, col_dropdown, [search_dropdown, search_text])
-
-    # --- Prefill editable fields ---
-    def prefill_fields(dataset_id):
-        if not dataset_id:
-            return "", "todo"
-        dataset_id = str(dataset_id)
-        filtered = [row for row in df.to_dicts() if str(row.get("dataset_id")) == dataset_id]
-        if not filtered:
-            return "", "todo"
-        row = filtered[0]
-        return row.get("assigned_to", ""), row.get("status", "todo")
-
-    selected_dataset_id.change(prefill_fields, selected_dataset_id, [assigned_to_input, status_input])
-
-    # --- Search function ---
-    def search_func(page, column, txt, ddl):
-        query = ddl if column in DROPDOWN_COLUMNS else txt
-        page_df, total_pages = get_page(df, page, column, query)
-        return page_df, f"Total Pages: {total_pages}", 0, gr.update(choices=page_df['dataset_id'].tolist())
-
-    # --- Pagination functions ---
-    def next_page(page, column, txt, ddl):
-        page += 1
-        query = ddl if column in DROPDOWN_COLUMNS else txt
-        page_df, total_pages = get_page(df, page, column, query)
-        if page >= total_pages:
-            page = total_pages - 1
-            page_df, total_pages = get_page(df, page, column, query)
-        return page_df, f"Total Pages: {total_pages}", page, gr.update(choices=page_df['dataset_id'].tolist())
-
-    def prev_page(page, column, txt, ddl):
-        page = max(0, page - 1)
-        query = ddl if column in DROPDOWN_COLUMNS else txt
-        page_df, total_pages = get_page(df, page, column, query)
-        return page_df, f"Total Pages: {total_pages}", page, gr.update(choices=page_df['dataset_id'].tolist())
-
-    def reset_func():
-        page_df, total_pages = get_page(df, 0)
-        return page_df, f"Total Pages: {total_pages}", 0, gr.update(choices=page_df['dataset_id'].tolist())
-
-    # --- Save changes & refresh ---
-    def save_changes(dataset_id, assigned_to_val, status_val, page_val, col, txt, ddl):
-        global df
-        if not dataset_id:
-            return gr.update(value="Please select a row first."), None, None, None
-        df = df.with_columns([
-            pl.when(pl.col("dataset_id") == dataset_id).then(pl.lit(assigned_to_val)).otherwise(pl.col("assigned_to")).alias("assigned_to"),
-            pl.when(pl.col("dataset_id") == dataset_id).then(pl.lit(status_val)).otherwise(pl.col("status")).alias("status")
-        ])
-        df.write_parquet(UPDATED_PARQUET_PATH)
-        page_df, total_pages = get_page(df, page_val, col, txt if col not in DROPDOWN_COLUMNS else ddl)
-        return (
-            gr.update(value=f"Saved changes for dataset_id: {dataset_id}"),
-            page_df,
-            gr.update(choices=page_df['dataset_id'].tolist()),
-            f"Total Pages: {total_pages}"
-        )
-
-    # --- Refresh All: table + members ---
-    def refresh_all(page, column, txt, ddl):
-        global df, member_list, unique_values
-        # Refresh members
-        member_list = fetch_members()
-        unique_values['assigned_to'] = sorted(member_list)
-        # Refresh table
-        try:
-            df = pl.read_parquet(UPDATED_PARQUET_PATH)
-        except FileNotFoundError:
-            pass
-        page_df, total_pages = get_page(df, page, column, txt if column not in DROPDOWN_COLUMNS else ddl)
-        return page_df, f"Total Pages: {total_pages}", page, gr.update(choices=page_df['dataset_id'].tolist()), gr.update(choices=member_list)
-
-    # --- Wire buttons ---
-    inputs_search = [page_number, col_dropdown, search_text, search_dropdown]
-    outputs_search = [data_table, total_pages_display, page_number, selected_dataset_id]
-
-    search_btn.click(search_func, inputs_search, outputs_search)
-    next_btn.click(next_page, inputs_search, outputs_search)
-    prev_btn.click(prev_page, inputs_search, outputs_search)
-    reset_btn.click(reset_func, [], outputs_search)
-    save_btn.click(
-        save_changes,
-        [selected_dataset_id, assigned_to_input, status_input, page_number, col_dropdown, search_text, search_dropdown],
-        [save_message, data_table, selected_dataset_id, total_pages_display]
-    )
-    refresh_btn.click(
-        refresh_all,
-        inputs=[page_number, col_dropdown, search_text, search_dropdown],
-        outputs=[data_table, total_pages_display, page_number, selected_dataset_id, assigned_to_input]
-    )
+    output_msg = gr.Textbox(label="Message", interactive=False)
+
+    page_number.change(get_page, inputs=[page_number, col_dropdown, search_text, search_dropdown],
+                       outputs=[data_table, total_pages_display, page_number,
+                                selected_dataset_id, assigned_to_input, status_input])
+    save_btn.click(save_changes, inputs=[selected_dataset_id, assigned_to_input, status_input], outputs=[output_msg])
+    refresh_btn.click(refresh_all, inputs=[page_number, col_dropdown, search_text, search_dropdown],
+                      outputs=[data_table, total_pages_display, page_number,
+                               selected_dataset_id, assigned_to_input, status_input])
+
+# 🔄 Start auto-push loop
+threading.Thread(target=auto_push_loop, args=(300,), daemon=True).start()
 
 demo.launch()

datasetcards.parquet

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+size 38347730

datasetcards_new.parquet

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+size 38347730