Add Document Ingestion module for curated docs and web search - #48

Add embedding generation and vector storage functionality with tests and documentation.

Introduces a Prompt module with:
- FUNSQL system prompt and customizable PromptTemplate
- Context formatting from retrieved chunks
- Build prompts for LLM query construction

Includes full test coverage and documentation page.

Introduces an Execution module with:
- FUNSQL query execution against DuckDB via RAGTools
- Result extraction, formatting, and display
- End-to-end query-to-answer pipeline integration

Includes tests and documentation updates.

…to response_generation

The Documentation job failed with six unresolvable `@ref` targets,
from two separate causes:

- `Chunk`, `HeaderChunk` and the rest of the chunking API are defined
  and exported by the `Ingestion` submodule but were never re-exported
  from `HealthLLM`, so `[`Chunk`](@ref)` in querying.md (which runs
  under `CurrentModule = HealthLLM`) had no binding to resolve against.
  Add them to the `import .Ingestion:` and `export` lists alongside the
  other ingestion names.

- Documenter resolves `@ref`s inside a docstring in that docstring's own
  module. The `Prompt` docstrings reference `retrieve`, `search` and
  `Chunk`, none of which `Prompt` imports, so they failed as
  `HealthLLM.Prompt.retrieve` and friends. Qualify them with the
  `[`name`](@ref Module.name)` form, which keeps the rendered link text
  unchanged.

`julia --project=docs docs/make.jl` now completes CrossReferences and
RenderDocument with no errors.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01RYi1NAjjGQ848cUMLEbh1x

feat: add Execution module for FUNSQL query execution and answer generation

feat: add Prompt module for grounded RAG query construction

feat: add retrieve() convenience method for text-query-to-search

Add embedding and storage modules

Add document chunking strategies with provenance tracking

… into ingestion