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name: notebook description: Work with Jupyter notebooks in the wc_simd project. Use this skill to run, convert, or explore notebooks. Invoke with /notebook.

Jupyter Notebooks

This skill helps work with Jupyter notebooks in the wc_simd project.

Notebook Categories

Data Ingestion & Processing

• wellcome_dataset.ipynb - Load works/images into Hive (738K works, 128K images)
• download_iiif_manifests.ipynb - Batch download IIIF manifests (340K files)
• iiif_manifests.ipynb - Process manifests for text renderings (226K works)
• iiif_manifest_pages.ipynb - Estimate collection size (~42M pages)

Text Analysis & NLP

• alto_text.ipynb - OCR text analysis (9.8B words, 78.9% English)
• alto_text_chunking.ipynb - Text chunking (74M chunks) + Elasticsearch indexing
• alto_text_analysis.ipynb - Comprehensive NLP: NER, sentiment, topic modeling

Labels & Metadata

• dn_labels.ipynb - Combined labels DataFrame (646K labels)
• works_labels.ipynb - Genre/subject/concept exploration

VLM Embeddings

• vlm_embed.ipynb - VLM embedding analysis (537K attempted, 150K failed)
• vlm_embed_train_data.ipynb - AE3D latent visualization, UMAP plots

Name Reconciliation

• name_rec_poc.ipynb - Name reconciliation POC with Qwen3-Embedding
• narese_evaluation.ipynb - NARESE evaluation (81.7% accuracy)

LLM & Agents

• llm.ipynb - Test VLLM/VLM models (Qwen3-30B, Qwen2.5-VL)
• chat_simple.ipynb - LangGraph chat with memory
• agent_spark_sql_toolkit.ipynb - Spark SQL agent
• describe_works.ipynb - LLM-driven SQL generation

Run Notebook

Interactive (Jupyter)

jupyter notebook notebooks/

Non-Interactive (papermill)

papermill notebooks/alto_text.ipynb output.ipynb

Convert to Script

jupyter nbconvert --to script notebooks/alto_text.ipynb

Convert to HTML

jupyter nbconvert --to html notebooks/alto_text.ipynb

Start Jupyter Server

# Standard
jupyter notebook

# With specific port
jupyter notebook --port 8889

# Lab interface
jupyter lab

Clear Outputs

jupyter nbconvert --clear-output --inplace notebooks/*.ipynb

Prerequisites

Ensure Spark is running for notebooks that use Hive tables:

cd spark_docker_s3 && docker compose up -d --build

Load environment variables:

from dotenv import load_dotenv
load_dotenv()