Add trainable Model primitive examples (IMDB NB + HF)#1
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- Add support inbox triage example with retry-focused BDD spec\n- Add composite fuzzy-then-LLM example with deterministic mock-mode specs\n- Include snippet markers for docs ingestion
- Add chapter 03-human-in-the-loop/ for HITL patterns - 01-basic-hitl.tac: traditional HITL with direct primitive calls - 02-agent-driven-approval.tac: agent-driven HITL with tool wrappers - Demonstrates progression from hardcoded to intelligent HITL workflows
- Add support inbox triage example with retry-focused BDD spec\n- Add composite fuzzy-then-LLM example with deterministic mock-mode specs\n- Include snippet markers for docs ingestion
- Add chapter 03-human-in-the-loop/ for HITL patterns - 01-basic-hitl.tac: traditional HITL with direct primitive calls - 02-agent-driven-approval.tac: agent-driven HITL with tool wrappers - Demonstrates progression from hardcoded to intelligent HITL workflows
… into feature/classification-examples
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Adds two registry-backed, trainable Model primitive examples with deterministic mocks/specs (Naive Bayes + HF sequence classifier), updates existing LLM classification and HITL examples to use the current mocking story, and fixes the CI test runner Python selection/counter logic.
Related: Tactus-84l.3