implement basic structure by resource type

.gitignore

@@ -1 +1,2 @@
-venv
+venv/
+__pycache__/

app.py

@@ -1,68 +1,64 @@
 import gradio as gr
-import pandas as pd
 
-df = pd.read_csv("eventos_pln_es.csv")
+# Import the resource type modules
+import datasets_resource
+import events_resource
+import initiatives_resource
+import models_resource
+import shared_tasks_resource
 
+# Create the main Gradio interface
+with gr.Blocks(title="Recursos de PLN en español", theme=gr.themes.Soft()) as app:
 
-def update_table(search_query):
-    if search_query == "":
-        return df
-    else:
-        # Filter the dataframe based on the search query
-        filtered_df = df[
-            df.apply(
-                lambda row: row.astype(str)
-                .str.contains(search_query, case=False)
-                .any(),
-                axis=1,
-            )
-        ]
-        return filtered_df
-
-
-with gr.Blocks() as app:
-
+    # Header
     gr.Markdown(
         """
-        # 🚀 Recursos de PLN en español
-                
-        Descubre recursos gratuitos online de PLN en español.
-                
-        Ayúdanos a expandir esta lista, [comenta](https://huggingface.co/spaces/somosnlp/spanish-nlp-initiatives/discussions) y contribuye para hacerla lo más completa posible ¡Gracias!
-        """
+    # 🚀 Recursos de PLN en español
+    
+    Descubre y contribuye con recursos gratuitos online de PLN en español.
+    
+    Explora datasets, modelos, tareas compartidas, eventos e iniciativas. ¡Ayúdanos a expandir esta colección para hacerla lo más completa posible!
+    """
     )
-    with gr.Accordion(label="Leer más", open=False, visible=False):
-        gr.Markdown(
-            """
-            En los últimos años han surgido iniciativas para impulsar el PLN en español. El objetivo de esta lista es dar a conocer los recursos creados por estas iniciativas y facilitar la formación de personas apasionadas por el PLN en todo el mundo.
 
-            La lista no es exhaustiva y son más que bienvenidas las contribuciones vía [comentarios o PRs](https://huggingface.co/spaces/somosnlp/spanish-nlp-initiatives/discussions).
-            
-            Estructura:
-            - Recurso: Nombre del recurso
-            - Categoría: Charla, taller aplicado, notebook, artículo de blog
-            - Etiqueta: LLM, traducción, ética, ...
-            - Creado por: Organización o persona que lo ha creado/organizado
-            - Web: Página web del recurso
-            """
-        )
+    # Main tabs for resource types
+    with gr.Tabs() as main_tabs:
 
-    with gr.Row():
-        search_box = gr.Textbox(
-            placeholder="Buscar...",
-            label="Filtra la tabla",
-            show_label=False,
-        )
-    with gr.Row():
-        table = gr.Dataframe(
-            value=df,
-            label="Recursos de PLN en español",
-            show_label=False,
-            interactive=False,
-            wrap=False,
-            # column_widths=["30%", "15%", "20%", "15%", "15%"],
-        )
-    search_box.change(fn=update_table, inputs=search_box, outputs=table)
+        # Create tabs for each resource type
+        datasets_tab = datasets_resource.create_tab()
+        models_tab = models_resource.create_tab()
+        shared_tasks_tab = shared_tasks_resource.create_tab()
+        events_tab = events_resource.create_tab()
+        initiatives_tab = initiatives_resource.create_tab()
 
+    # Footer
+    gr.Markdown(
+        """
+    ---
+    
+    ### 📖 About
+    
+    Esta plataforma forma parte de la iniciativa [SomosNLP](https://somosnlp.org) para democratizar el acceso 
+    a recursos de procesamiento de lenguaje natural en español.
+    
+    **¿Cómo contribuir?**
+    1. Ve a la pestaña del tipo de recurso que quieras añadir
+    2. Haz clic en la sub-pestaña "Contribute"
+    3. Haz login con tu cuenta de Hugging Face
+    4. Rellena el formulario con la información del recurso
+    5. ¡Envía tu contribución!
+    
+    Los recursos enviados se almacenan en datasets públicos de Hugging Face y están disponibles para toda la comunidad.
+    
+    **Tipos de recursos:**
+    - **Datasets**: Conjuntos de datos para entrenar y evaluar modelos de PLN
+    - **Models**: Modelos pre-entrenados y fine-tuned para tareas de PLN
+    - **Shared Tasks**: Competiciones y evaluaciones compartidas
+    - **Events**: Conferencias, workshops, charlas y eventos relacionados con PLN
+    - **Initiatives**: Proyectos, organizaciones e iniciativas que impulsan el PLN en español
+    """
+    )
 
-app.launch()
+# Launch the app
+if __name__ == "__main__":
+    app.launch(share=False, server_name="0.0.0.0", server_port=7860)

datasets_resource.py

@@ -0,0 +1,178 @@
+from datetime import datetime, timezone
+
+import gradio as gr
+import pandas as pd
+from datasets import Dataset, load_dataset
+
+# Dataset configuration
+DATASET_NAME = "somosnlp/recursos-pln-es-datasets"
+RESOURCE_TYPE = "datasets"
+RESOURCE_TITLE = "Datasets"
+
+
+def load_data() -> pd.DataFrame:
+    """Load data from HuggingFace dataset or return empty DataFrame."""
+    try:
+        dataset = load_dataset(DATASET_NAME, split="train")
+        return dataset.to_pandas()
+    except Exception as e:
+        print(f"Could not load {RESOURCE_TYPE} dataset: {e}")
+        # Return empty DataFrame with required columns
+        return pd.DataFrame(
+            columns=["name", "url", "country", "submitted_by", "date_submitted"]
+        )
+
+
+def search_and_filter_data(df: pd.DataFrame, search_query: str) -> pd.DataFrame:
+    """Filter dataframe based on search query."""
+    if search_query == "":
+        return df
+    else:
+        filtered_df = df[
+            df.apply(
+                lambda row: row.astype(str)
+                .str.contains(search_query, case=False)
+                .any(),
+                axis=1,
+            )
+        ]
+        return filtered_df
+
+
+def check_login(profile: gr.OAuthProfile | None) -> bool:
+    """Check if a user is logged in."""
+    return profile is not None
+
+
+def submit_resource(name: str, url: str, country: str, profile: gr.OAuthProfile | None):
+    """Submit a new resource to the corresponding dataset."""
+
+    # Check if user is logged in
+    if not check_login(profile):
+        return "❌ Error: You need to be logged in to submit a resource."
+
+    # Validate inputs
+    if not name or not url or not country:
+        return "❌ Error: All fields (name, url, country) are required."
+
+    try:
+        username = profile.username
+        current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+
+        # Create new row data
+        new_data = {
+            "name": name,
+            "url": url,
+            "country": country,
+            "submitted_by": username,
+            "date_submitted": current_time,
+        }
+
+        # Try to load existing dataset, or create new one
+        try:
+            existing_dataset = load_dataset(DATASET_NAME, split="train")
+            existing_df = existing_dataset.to_pandas()
+            # Add new row
+            updated_df = pd.concat(
+                [existing_df, pd.DataFrame([new_data])], ignore_index=True
+            )
+        except:
+            # Create new dataset if it doesn't exist
+            updated_df = pd.DataFrame([new_data])
+
+        # Convert back to Dataset and push to hub
+        updated_dataset = Dataset.from_pandas(updated_df)
+        updated_dataset.push_to_hub(
+            DATASET_NAME,
+            commit_message=f"Add {name} by {username}",
+            token=True,  # Use the user's token
+        )
+
+        return f"✅ Success: {name} has been submitted successfully!"
+
+    except Exception as e:
+        return f"❌ Error: Failed to submit resource. {str(e)}"
+
+
+def create_all_tab():
+    """Create the 'All' tab for this resource type."""
+    with gr.TabItem("📋 All", id=f"{RESOURCE_TYPE}_all"):
+        gr.Markdown(f"### All {RESOURCE_TITLE}")
+
+        search_box = gr.Textbox(
+            placeholder=f"Search {RESOURCE_TYPE}...",
+            label="Filter the table",
+            show_label=False,
+        )
+
+        # Load initial data
+        initial_df = load_data()
+
+        table = gr.Dataframe(
+            value=initial_df,
+            label=RESOURCE_TITLE,
+            show_label=False,
+            interactive=False,
+            wrap=True,
+        )
+
+        # Connect search functionality
+        search_box.change(
+            fn=lambda query: search_and_filter_data(initial_df, query),
+            inputs=search_box,
+            outputs=table,
+        )
+
+        # Refresh button to reload data
+        refresh_btn = gr.Button("🔄 Refresh Data", variant="secondary")
+        refresh_btn.click(fn=lambda: load_data(), outputs=table)
+
+        return table
+
+
+def create_contribute_tab():
+    """Create the 'Contribute' tab for this resource type."""
+    with gr.TabItem("➕ Contribute", id=f"{RESOURCE_TYPE}_contribute"):
+        gr.Markdown(f"### Contribute a New {RESOURCE_TITLE[:-1]}")
+
+        # Login section
+        gr.Markdown("Please log in to contribute resources:")
+        login_button = gr.LoginButton(elem_id=f"{RESOURCE_TYPE}-oauth-button")
+
+        gr.Markdown("Please fill in the information below to add a new dataset:")
+
+        with gr.Column():
+            name_input = gr.Textbox(
+                label="Name",
+                placeholder="Enter the name of the dataset",
+                info="The name or title of the resource",
+            )
+            url_input = gr.Textbox(
+                label="URL", placeholder="https://...", info="Link to the resource"
+            )
+            country_input = gr.Textbox(
+                label="Country",
+                placeholder="e.g., Spain, Mexico, Argentina",
+                info="Country of origin or primary focus",
+            )
+
+        submit_btn = gr.Button(f"Submit {RESOURCE_TITLE[:-1]}", variant="primary")
+        result_msg = gr.Markdown()
+
+        # Submit function
+        submit_btn.click(
+            fn=submit_resource,
+            inputs=[name_input, url_input, country_input],
+            outputs=[result_msg],
+        )
+
+        return name_input, url_input, country_input, submit_btn, result_msg
+
+
+def create_tab():
+    """Create the complete tab for this resource type."""
+    with gr.TabItem(f"📊 {RESOURCE_TITLE}", id=RESOURCE_TYPE):
+        with gr.Tabs():
+            table = create_all_tab()
+            inputs = create_contribute_tab()
+            return table, inputs

events_resource.py

@@ -0,0 +1,178 @@
+from datetime import datetime, timezone
+
+import gradio as gr
+import pandas as pd
+from datasets import Dataset, load_dataset
+
+# Dataset configuration
+DATASET_NAME = "somosnlp/recursos-pln-es-events"
+RESOURCE_TYPE = "events"
+RESOURCE_TITLE = "Events"
+
+
+def load_data() -> pd.DataFrame:
+    """Load data from HuggingFace dataset or return empty DataFrame."""
+    try:
+        dataset = load_dataset(DATASET_NAME, split="train")
+        return dataset.to_pandas()
+    except Exception as e:
+        print(f"Could not load {RESOURCE_TYPE} dataset: {e}")
+        # Return empty DataFrame with required columns
+        return pd.DataFrame(
+            columns=["name", "url", "country", "submitted_by", "date_submitted"]
+        )
+
+
+def search_and_filter_data(df: pd.DataFrame, search_query: str) -> pd.DataFrame:
+    """Filter dataframe based on search query."""
+    if search_query == "":
+        return df
+    else:
+        filtered_df = df[
+            df.apply(
+                lambda row: row.astype(str)
+                .str.contains(search_query, case=False)
+                .any(),
+                axis=1,
+            )
+        ]
+        return filtered_df
+
+
+def check_login(profile: gr.OAuthProfile | None) -> bool:
+    """Check if a user is logged in."""
+    return profile is not None
+
+
+def submit_resource(name: str, url: str, country: str, profile: gr.OAuthProfile | None):
+    """Submit a new resource to the corresponding dataset."""
+
+    # Check if user is logged in
+    if not check_login(profile):
+        return "❌ Error: You need to be logged in to submit a resource."
+
+    # Validate inputs
+    if not name or not url or not country:
+        return "❌ Error: All fields (name, url, country) are required."
+
+    try:
+        username = profile.username
+        current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+
+        # Create new row data
+        new_data = {
+            "name": name,
+            "url": url,
+            "country": country,
+            "submitted_by": username,
+            "date_submitted": current_time,
+        }
+
+        # Try to load existing dataset, or create new one
+        try:
+            existing_dataset = load_dataset(DATASET_NAME, split="train")
+            existing_df = existing_dataset.to_pandas()
+            # Add new row
+            updated_df = pd.concat(
+                [existing_df, pd.DataFrame([new_data])], ignore_index=True
+            )
+        except:
+            # Create new dataset if it doesn't exist
+            updated_df = pd.DataFrame([new_data])
+
+        # Convert back to Dataset and push to hub
+        updated_dataset = Dataset.from_pandas(updated_df)
+        updated_dataset.push_to_hub(
+            DATASET_NAME,
+            commit_message=f"Add {name} by {username}",
+            token=True,  # Use the user's token
+        )
+
+        return f"✅ Success: {name} has been submitted successfully!"
+
+    except Exception as e:
+        return f"❌ Error: Failed to submit resource. {str(e)}"
+
+
+def create_all_tab():
+    """Create the 'All' tab for this resource type."""
+    with gr.TabItem("📋 All", id=f"{RESOURCE_TYPE}_all"):
+        gr.Markdown(f"### All {RESOURCE_TITLE}")
+
+        search_box = gr.Textbox(
+            placeholder=f"Search {RESOURCE_TYPE}...",
+            label="Filter the table",
+            show_label=False,
+        )
+
+        # Load initial data
+        initial_df = load_data()
+
+        table = gr.Dataframe(
+            value=initial_df,
+            label=RESOURCE_TITLE,
+            show_label=False,
+            interactive=False,
+            wrap=True,
+        )
+
+        # Connect search functionality
+        search_box.change(
+            fn=lambda query: search_and_filter_data(initial_df, query),
+            inputs=search_box,
+            outputs=table,
+        )
+
+        # Refresh button to reload data
+        refresh_btn = gr.Button("🔄 Refresh Data", variant="secondary")
+        refresh_btn.click(fn=lambda: load_data(), outputs=table)
+
+        return table
+
+
+def create_contribute_tab():
+    """Create the 'Contribute' tab for this resource type."""
+    with gr.TabItem("➕ Contribute", id=f"{RESOURCE_TYPE}_contribute"):
+        gr.Markdown(f"### Contribute a New {RESOURCE_TITLE[:-1]}")
+
+        # Login section
+        gr.Markdown("Please log in to contribute resources:")
+        login_button = gr.LoginButton(elem_id=f"{RESOURCE_TYPE}-oauth-button")
+
+        gr.Markdown("Please fill in the information below to add a new event:")
+
+        with gr.Column():
+            name_input = gr.Textbox(
+                label="Name",
+                placeholder="Enter the name of the event",
+                info="The name or title of the resource",
+            )
+            url_input = gr.Textbox(
+                label="URL", placeholder="https://...", info="Link to the resource"
+            )
+            country_input = gr.Textbox(
+                label="Country",
+                placeholder="e.g., Spain, Mexico, Argentina",
+                info="Country of origin or primary focus",
+            )
+
+        submit_btn = gr.Button(f"Submit {RESOURCE_TITLE[:-1]}", variant="primary")
+        result_msg = gr.Markdown()
+
+        # Submit function
+        submit_btn.click(
+            fn=submit_resource,
+            inputs=[name_input, url_input, country_input],
+            outputs=[result_msg],
+        )
+
+        return name_input, url_input, country_input, submit_btn, result_msg
+
+
+def create_tab():
+    """Create the complete tab for this resource type."""
+    with gr.TabItem(f"📅 {RESOURCE_TITLE}", id=RESOURCE_TYPE):
+        with gr.Tabs():
+            table = create_all_tab()
+            inputs = create_contribute_tab()
+            return table, inputs

initiatives_resource.py

@@ -0,0 +1,178 @@
+from datetime import datetime, timezone
+
+import gradio as gr
+import pandas as pd
+from datasets import Dataset, load_dataset
+
+# Dataset configuration
+DATASET_NAME = "somosnlp/recursos-pln-es-initiatives"
+RESOURCE_TYPE = "initiatives"
+RESOURCE_TITLE = "Initiatives"
+
+
+def load_data() -> pd.DataFrame:
+    """Load data from HuggingFace dataset or return empty DataFrame."""
+    try:
+        dataset = load_dataset(DATASET_NAME, split="train")
+        return dataset.to_pandas()
+    except Exception as e:
+        print(f"Could not load {RESOURCE_TYPE} dataset: {e}")
+        # Return empty DataFrame with required columns
+        return pd.DataFrame(
+            columns=["name", "url", "country", "submitted_by", "date_submitted"]
+        )
+
+
+def search_and_filter_data(df: pd.DataFrame, search_query: str) -> pd.DataFrame:
+    """Filter dataframe based on search query."""
+    if search_query == "":
+        return df
+    else:
+        filtered_df = df[
+            df.apply(
+                lambda row: row.astype(str)
+                .str.contains(search_query, case=False)
+                .any(),
+                axis=1,
+            )
+        ]
+        return filtered_df
+
+
+def check_login(profile: gr.OAuthProfile | None) -> bool:
+    """Check if a user is logged in."""
+    return profile is not None
+
+
+def submit_resource(name: str, url: str, country: str, profile: gr.OAuthProfile | None):
+    """Submit a new resource to the corresponding dataset."""
+
+    # Check if user is logged in
+    if not check_login(profile):
+        return "❌ Error: You need to be logged in to submit a resource."
+
+    # Validate inputs
+    if not name or not url or not country:
+        return "❌ Error: All fields (name, url, country) are required."
+
+    try:
+        username = profile.username
+        current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+
+        # Create new row data
+        new_data = {
+            "name": name,
+            "url": url,
+            "country": country,
+            "submitted_by": username,
+            "date_submitted": current_time,
+        }
+
+        # Try to load existing dataset, or create new one
+        try:
+            existing_dataset = load_dataset(DATASET_NAME, split="train")
+            existing_df = existing_dataset.to_pandas()
+            # Add new row
+            updated_df = pd.concat(
+                [existing_df, pd.DataFrame([new_data])], ignore_index=True
+            )
+        except:
+            # Create new dataset if it doesn't exist
+            updated_df = pd.DataFrame([new_data])
+
+        # Convert back to Dataset and push to hub
+        updated_dataset = Dataset.from_pandas(updated_df)
+        updated_dataset.push_to_hub(
+            DATASET_NAME,
+            commit_message=f"Add {name} by {username}",
+            token=True,  # Use the user's token
+        )
+
+        return f"✅ Success: {name} has been submitted successfully!"
+
+    except Exception as e:
+        return f"❌ Error: Failed to submit resource. {str(e)}"
+
+
+def create_all_tab():
+    """Create the 'All' tab for this resource type."""
+    with gr.TabItem("📋 All", id=f"{RESOURCE_TYPE}_all"):
+        gr.Markdown(f"### All {RESOURCE_TITLE}")
+
+        search_box = gr.Textbox(
+            placeholder=f"Search {RESOURCE_TYPE}...",
+            label="Filter the table",
+            show_label=False,
+        )
+
+        # Load initial data
+        initial_df = load_data()
+
+        table = gr.Dataframe(
+            value=initial_df,
+            label=RESOURCE_TITLE,
+            show_label=False,
+            interactive=False,
+            wrap=True,
+        )
+
+        # Connect search functionality
+        search_box.change(
+            fn=lambda query: search_and_filter_data(initial_df, query),
+            inputs=search_box,
+            outputs=table,
+        )
+
+        # Refresh button to reload data
+        refresh_btn = gr.Button("🔄 Refresh Data", variant="secondary")
+        refresh_btn.click(fn=lambda: load_data(), outputs=table)
+
+        return table
+
+
+def create_contribute_tab():
+    """Create the 'Contribute' tab for this resource type."""
+    with gr.TabItem("➕ Contribute", id=f"{RESOURCE_TYPE}_contribute"):
+        gr.Markdown(f"### Contribute a New {RESOURCE_TITLE[:-1]}")
+
+        # Login section
+        gr.Markdown("Please log in to contribute resources:")
+        login_button = gr.LoginButton(elem_id=f"{RESOURCE_TYPE}-oauth-button")
+
+        gr.Markdown("Please fill in the information below to add a new initiative:")
+
+        with gr.Column():
+            name_input = gr.Textbox(
+                label="Name",
+                placeholder="Enter the name of the initiative",
+                info="The name or title of the resource",
+            )
+            url_input = gr.Textbox(
+                label="URL", placeholder="https://...", info="Link to the resource"
+            )
+            country_input = gr.Textbox(
+                label="Country",
+                placeholder="e.g., Spain, Mexico, Argentina",
+                info="Country of origin or primary focus",
+            )
+
+        submit_btn = gr.Button(f"Submit {RESOURCE_TITLE[:-1]}", variant="primary")
+        result_msg = gr.Markdown()
+
+        # Submit function
+        submit_btn.click(
+            fn=submit_resource,
+            inputs=[name_input, url_input, country_input],
+            outputs=[result_msg],
+        )
+
+        return name_input, url_input, country_input, submit_btn, result_msg
+
+
+def create_tab():
+    """Create the complete tab for this resource type."""
+    with gr.TabItem(f"🌟 {RESOURCE_TITLE}", id=RESOURCE_TYPE):
+        with gr.Tabs():
+            table = create_all_tab()
+            inputs = create_contribute_tab()
+            return table, inputs

models_resource.py

@@ -0,0 +1,178 @@
+from datetime import datetime, timezone
+
+import gradio as gr
+import pandas as pd
+from datasets import Dataset, load_dataset
+
+# Dataset configuration
+DATASET_NAME = "somosnlp/recursos-pln-es-models"
+RESOURCE_TYPE = "models"
+RESOURCE_TITLE = "Models"
+
+
+def load_data() -> pd.DataFrame:
+    """Load data from HuggingFace dataset or return empty DataFrame."""
+    try:
+        dataset = load_dataset(DATASET_NAME, split="train")
+        return dataset.to_pandas()
+    except Exception as e:
+        print(f"Could not load {RESOURCE_TYPE} dataset: {e}")
+        # Return empty DataFrame with required columns
+        return pd.DataFrame(
+            columns=["name", "url", "country", "submitted_by", "date_submitted"]
+        )
+
+
+def search_and_filter_data(df: pd.DataFrame, search_query: str) -> pd.DataFrame:
+    """Filter dataframe based on search query."""
+    if search_query == "":
+        return df
+    else:
+        filtered_df = df[
+            df.apply(
+                lambda row: row.astype(str)
+                .str.contains(search_query, case=False)
+                .any(),
+                axis=1,
+            )
+        ]
+        return filtered_df
+
+
+def check_login(profile: gr.OAuthProfile | None) -> bool:
+    """Check if a user is logged in."""
+    return profile is not None
+
+
+def submit_resource(name: str, url: str, country: str, profile: gr.OAuthProfile | None):
+    """Submit a new resource to the corresponding dataset."""
+
+    # Check if user is logged in
+    if not check_login(profile):
+        return "❌ Error: You need to be logged in to submit a resource."
+
+    # Validate inputs
+    if not name or not url or not country:
+        return "❌ Error: All fields (name, url, country) are required."
+
+    try:
+        username = profile.username
+        current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+
+        # Create new row data
+        new_data = {
+            "name": name,
+            "url": url,
+            "country": country,
+            "submitted_by": username,
+            "date_submitted": current_time,
+        }
+
+        # Try to load existing dataset, or create new one
+        try:
+            existing_dataset = load_dataset(DATASET_NAME, split="train")
+            existing_df = existing_dataset.to_pandas()
+            # Add new row
+            updated_df = pd.concat(
+                [existing_df, pd.DataFrame([new_data])], ignore_index=True
+            )
+        except:
+            # Create new dataset if it doesn't exist
+            updated_df = pd.DataFrame([new_data])
+
+        # Convert back to Dataset and push to hub
+        updated_dataset = Dataset.from_pandas(updated_df)
+        updated_dataset.push_to_hub(
+            DATASET_NAME,
+            commit_message=f"Add {name} by {username}",
+            token=True,  # Use the user's token
+        )
+
+        return f"✅ Success: {name} has been submitted successfully!"
+
+    except Exception as e:
+        return f"❌ Error: Failed to submit resource. {str(e)}"
+
+
+def create_all_tab():
+    """Create the 'All' tab for this resource type."""
+    with gr.TabItem("📋 All", id=f"{RESOURCE_TYPE}_all"):
+        gr.Markdown(f"### All {RESOURCE_TITLE}")
+
+        search_box = gr.Textbox(
+            placeholder=f"Search {RESOURCE_TYPE}...",
+            label="Filter the table",
+            show_label=False,
+        )
+
+        # Load initial data
+        initial_df = load_data()
+
+        table = gr.Dataframe(
+            value=initial_df,
+            label=RESOURCE_TITLE,
+            show_label=False,
+            interactive=False,
+            wrap=True,
+        )
+
+        # Connect search functionality
+        search_box.change(
+            fn=lambda query: search_and_filter_data(initial_df, query),
+            inputs=search_box,
+            outputs=table,
+        )
+
+        # Refresh button to reload data
+        refresh_btn = gr.Button("🔄 Refresh Data", variant="secondary")
+        refresh_btn.click(fn=lambda: load_data(), outputs=table)
+
+        return table
+
+
+def create_contribute_tab():
+    """Create the 'Contribute' tab for this resource type."""
+    with gr.TabItem("➕ Contribute", id=f"{RESOURCE_TYPE}_contribute"):
+        gr.Markdown(f"### Contribute a New {RESOURCE_TITLE[:-1]}")
+
+        # Login section
+        gr.Markdown("Please log in to contribute resources:")
+        login_button = gr.LoginButton(elem_id=f"{RESOURCE_TYPE}-oauth-button")
+
+        gr.Markdown("Please fill in the information below to add a new model:")
+
+        with gr.Column():
+            name_input = gr.Textbox(
+                label="Name",
+                placeholder="Enter the name of the model",
+                info="The name or title of the resource",
+            )
+            url_input = gr.Textbox(
+                label="URL", placeholder="https://...", info="Link to the resource"
+            )
+            country_input = gr.Textbox(
+                label="Country",
+                placeholder="e.g., Spain, Mexico, Argentina",
+                info="Country of origin or primary focus",
+            )
+
+        submit_btn = gr.Button(f"Submit {RESOURCE_TITLE[:-1]}", variant="primary")
+        result_msg = gr.Markdown()
+
+        # Submit function
+        submit_btn.click(
+            fn=submit_resource,
+            inputs=[name_input, url_input, country_input],
+            outputs=[result_msg],
+        )
+
+        return name_input, url_input, country_input, submit_btn, result_msg
+
+
+def create_tab():
+    """Create the complete tab for this resource type."""
+    with gr.TabItem(f"🤖 {RESOURCE_TITLE}", id=RESOURCE_TYPE):
+        with gr.Tabs():
+            table = create_all_tab()
+            inputs = create_contribute_tab()
+            return table, inputs

requirements.txt

@@ -1,2 +1,5 @@
 gradio==4.26.0
 pandas==2.2.1
+huggingface_hub>=0.20.0
+datasets>=2.17.0
+gradio[oauth]

shared_tasks_resource.py

@@ -0,0 +1,178 @@
+from datetime import datetime, timezone
+
+import gradio as gr
+import pandas as pd
+from datasets import Dataset, load_dataset
+
+# Dataset configuration
+DATASET_NAME = "somosnlp/recursos-pln-es-shared-tasks"
+RESOURCE_TYPE = "shared_tasks"
+RESOURCE_TITLE = "Shared Tasks"
+
+
+def load_data() -> pd.DataFrame:
+    """Load data from HuggingFace dataset or return empty DataFrame."""
+    try:
+        dataset = load_dataset(DATASET_NAME, split="train")
+        return dataset.to_pandas()
+    except Exception as e:
+        print(f"Could not load {RESOURCE_TYPE} dataset: {e}")
+        # Return empty DataFrame with required columns
+        return pd.DataFrame(
+            columns=["name", "url", "country", "submitted_by", "date_submitted"]
+        )
+
+
+def search_and_filter_data(df: pd.DataFrame, search_query: str) -> pd.DataFrame:
+    """Filter dataframe based on search query."""
+    if search_query == "":
+        return df
+    else:
+        filtered_df = df[
+            df.apply(
+                lambda row: row.astype(str)
+                .str.contains(search_query, case=False)
+                .any(),
+                axis=1,
+            )
+        ]
+        return filtered_df
+
+
+def check_login(profile: gr.OAuthProfile | None) -> bool:
+    """Check if a user is logged in."""
+    return profile is not None
+
+
+def submit_resource(name: str, url: str, country: str, profile: gr.OAuthProfile | None):
+    """Submit a new resource to the corresponding dataset."""
+
+    # Check if user is logged in
+    if not check_login(profile):
+        return "❌ Error: You need to be logged in to submit a resource."
+
+    # Validate inputs
+    if not name or not url or not country:
+        return "❌ Error: All fields (name, url, country) are required."
+
+    try:
+        username = profile.username
+        current_time = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
+
+        # Create new row data
+        new_data = {
+            "name": name,
+            "url": url,
+            "country": country,
+            "submitted_by": username,
+            "date_submitted": current_time,
+        }
+
+        # Try to load existing dataset, or create new one
+        try:
+            existing_dataset = load_dataset(DATASET_NAME, split="train")
+            existing_df = existing_dataset.to_pandas()
+            # Add new row
+            updated_df = pd.concat(
+                [existing_df, pd.DataFrame([new_data])], ignore_index=True
+            )
+        except:
+            # Create new dataset if it doesn't exist
+            updated_df = pd.DataFrame([new_data])
+
+        # Convert back to Dataset and push to hub
+        updated_dataset = Dataset.from_pandas(updated_df)
+        updated_dataset.push_to_hub(
+            DATASET_NAME,
+            commit_message=f"Add {name} by {username}",
+            token=True,  # Use the user's token
+        )
+
+        return f"✅ Success: {name} has been submitted successfully!"
+
+    except Exception as e:
+        return f"❌ Error: Failed to submit resource. {str(e)}"
+
+
+def create_all_tab():
+    """Create the 'All' tab for this resource type."""
+    with gr.TabItem("📋 All", id=f"{RESOURCE_TYPE}_all"):
+        gr.Markdown(f"### All {RESOURCE_TITLE}")
+
+        search_box = gr.Textbox(
+            placeholder=f"Search {RESOURCE_TYPE}...",
+            label="Filter the table",
+            show_label=False,
+        )
+
+        # Load initial data
+        initial_df = load_data()
+
+        table = gr.Dataframe(
+            value=initial_df,
+            label=RESOURCE_TITLE,
+            show_label=False,
+            interactive=False,
+            wrap=True,
+        )
+
+        # Connect search functionality
+        search_box.change(
+            fn=lambda query: search_and_filter_data(initial_df, query),
+            inputs=search_box,
+            outputs=table,
+        )
+
+        # Refresh button to reload data
+        refresh_btn = gr.Button("🔄 Refresh Data", variant="secondary")
+        refresh_btn.click(fn=lambda: load_data(), outputs=table)
+
+        return table
+
+
+def create_contribute_tab():
+    """Create the 'Contribute' tab for this resource type."""
+    with gr.TabItem("➕ Contribute", id=f"{RESOURCE_TYPE}_contribute"):
+        gr.Markdown(f"### Contribute a New {RESOURCE_TITLE[:-1]}")
+
+        # Login section
+        gr.Markdown("Please log in to contribute resources:")
+        login_button = gr.LoginButton(elem_id=f"{RESOURCE_TYPE}-oauth-button")
+
+        gr.Markdown("Please fill in the information below to add a new shared task:")
+
+        with gr.Column():
+            name_input = gr.Textbox(
+                label="Name",
+                placeholder="Enter the name of the shared task",
+                info="The name or title of the resource",
+            )
+            url_input = gr.Textbox(
+                label="URL", placeholder="https://...", info="Link to the resource"
+            )
+            country_input = gr.Textbox(
+                label="Country",
+                placeholder="e.g., Spain, Mexico, Argentina",
+                info="Country of origin or primary focus",
+            )
+
+        submit_btn = gr.Button(f"Submit {RESOURCE_TITLE[:-1]}", variant="primary")
+        result_msg = gr.Markdown()
+
+        # Submit function
+        submit_btn.click(
+            fn=submit_resource,
+            inputs=[name_input, url_input, country_input],
+            outputs=[result_msg],
+        )
+
+        return name_input, url_input, country_input, submit_btn, result_msg
+
+
+def create_tab():
+    """Create the complete tab for this resource type."""
+    with gr.TabItem(f"🏆 {RESOURCE_TITLE}", id=RESOURCE_TYPE):
+        with gr.Tabs():
+            table = create_all_tab()
+            inputs = create_contribute_tab()
+            return table, inputs