Sync RAG and semantic-search updates from che-computing

- 03-rag, 04-semantic-search: env-var-before-imports fix in build/query scripts
- 03-rag: new libraries section, fetch_arxiv.py, exercises for larger corpus
  and finding current SOTA models, formal references (Lewis, Booth)
- 04-semantic-search: libraries pointer back to Part III, larger corpus
  subsection, model-update exercise, formal references
- 06-neural-networks: add Nielsen reference (recommended by student)
- README: vocab.md link, agentic systems in description, Ollama prereq for 02-05
- New: vocab.md (glossary organized by section)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

03-rag/query.py

@@ -5,6 +5,14 @@
 # August 2025
 # E. M. Furst
 
+# Environment vars must be set before importing huggingface/transformers
+# libraries, because huggingface_hub.constants evaluates HF_HUB_OFFLINE
+# at import time.
+import os
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+os.environ["SENTENCE_TRANSFORMERS_HOME"] = "./models"
+os.environ["HF_HUB_OFFLINE"] = "1"
+
 from llama_index.core import (
     load_index_from_storage,
     StorageContext,
@@ -13,12 +21,7 @@ from llama_index.core import (
 from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 from llama_index.llms.ollama import Ollama
 from llama_index.core.prompts import PromptTemplate
-import os, time
-
-#
-# Globals
-#
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
+import time
 
 # Embedding model used in vector store (this should match the one in build.py)
 embed_model = HuggingFaceEmbedding(cache_folder="./models",