Sync catalog metadata

Dockerfile

@@ -0,0 +1,9 @@
+FROM python:3.13-slim
+
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
+
+RUN uv pip install --system --no-cache faceberg
+
+EXPOSE 7860
+
+CMD sh -c 'faceberg hf://spaces/${SPACE_ID} serve --host 0.0.0.0 --port 7860'

README.md

@@ -1,10 +1,85 @@
 ---
-title: Catalog
-emoji: 📚
-colorFrom: gray
-colorTo: blue
+title: Faceberg REST Catalog
+emoji: 🗃️
+colorFrom: blue
+colorTo: purple
 sdk: docker
-pinned: false
+app_port: 7860
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Faceberg REST Catalog
+
+An Apache Iceberg REST catalog with interactive web interface for browsing and querying Hugging Face datasets using [Faceberg](https://github.com/kszucs/faceberg).
+
+## Features
+
+- **📚 Interactive Browser**: Explore namespaces, tables, and schemas through an intuitive web interface
+- **🔍 SQL Query Interface**: Run queries directly in your browser using DuckDB-WASM with full Iceberg support
+- **🌐 REST API**: Full Iceberg REST catalog specification at `/v1/*` endpoints
+- **🚀 Zero Setup**: No installation required - just visit the Space URL
+
+## Usage
+
+### Web Interface
+
+Visit the Space URL (e.g., `https://your-username-your-space.hf.space`) to:
+
+1. **Browse Catalog**: View all namespaces and tables with detailed metadata
+   - Expand namespaces to see tables
+   - View table schemas with column names, types, and constraints
+   - See row counts, file counts, and HuggingFace dataset links
+
+2. **Query with DuckDB**: Run interactive SQL queries in your browser
+   - Click "Query with DuckDB" tab
+   - Initialize DuckDB-WASM (loads ~10MB with Iceberg extension)
+   - Write SQL queries using `iceberg_scan('metadata_location')`
+   - View results in a formatted table
+
+**Example Queries:**
+```sql
+-- Scan full table (limited)
+SELECT * FROM iceberg_scan('metadata_location') LIMIT 100;
+
+-- Filter by partition
+SELECT * FROM iceberg_scan('metadata_location')
+WHERE split = 'train' LIMIT 10;
+
+-- Aggregate statistics
+SELECT split, COUNT(*) as count
+FROM iceberg_scan('metadata_location')
+GROUP BY split;
+```
+
+### REST API
+
+Connect with any Iceberg client:
+
+```python
+from pyiceberg.catalog import load_catalog
+
+catalog = load_catalog(
+    "rest",
+    uri="https://your-username-your-space.hf.space",
+)
+
+# List namespaces
+namespaces = catalog.list_namespaces()
+
+# Load table
+table = catalog.load_table("namespace.table_name")
+
+# Query with DuckDB
+import duckdb
+duckdb.sql("SELECT * FROM iceberg_scan('table') LIMIT 10").show()
+```
+
+## About
+
+Faceberg enables storing Apache Iceberg table metadata directly on Hugging Face Hub as datasets, making your data lake tables easily shareable and version-controlled.
+
+**DuckDB-WASM Integration**: Powered by DuckDB-WASM with native Iceberg and httpfs extensions, enabling full metadata-aware querying directly in your browser without server load.
+
+Learn more:
+- [Faceberg on GitHub](https://github.com/kszucs/faceberg)
+- [Apache Iceberg](https://iceberg.apache.org/)
+- [DuckDB](https://duckdb.org/)

faceberg.yml

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+deepmind:
+  narrativeqa:
+    type: dataset
+    repo: deepmind/narrativeqa
+    config: default
+nvidia:
+  personas_brazil:
+    type: dataset
+    repo: nvidia/Nemotron-Personas-Brazil
+    config: default
+  open_math_reasoning:
+    type: dataset
+    repo: nvidia/OpenMathReasoning
+    config: default