# `Giza.ManticoreQL`

Query building helper functions for ManticoreQL. Manticore Search is a fork of Sphinx Search
with active development and new features. This module delegates the standard query-composing
interface to `ManticoreQL` and is the place to add Manticore-specific extensions.

# `autocomplete`

Word-level autocomplete via `CALL SUGGEST`. Returns candidate completions for the given
partial word against the specified index dictionary.

Options:
  - `:limit` - max suggestions (default: 5)
  - `:max_edits` - Levenshtein distance tolerance (default: 4)

## Examples

    iex> ManticoreQL.autocomplete("elxi", "posts_index")
    {:ok, %SphinxqlResponse{}}

    iex> ManticoreQL.autocomplete("elxi", "posts_index", limit: 3, max_edits: 2)
    {:ok, %SphinxqlResponse{}}

# `autocomplete`

# `call`

# `facet`

Appends a FACET clause to the query. Multiple calls chain additional facets. Manticore
reuses the base result set for each facet, so the total cost is only marginally more than
the plain query.

Options:
  - `:order` - ORDER BY expression string, e.g. `"COUNT(*) DESC"`
  - `:limit` - integer cap on facet rows returned

## Examples

    iex> ManticoreQL.new()
    |> ManticoreQL.from("products")
    |> ManticoreQL.match("phone")
    |> ManticoreQL.facet("brand_id")
    |> ManticoreQL.facet("price", order: "COUNT(*) DESC", limit: 10)
    |> ManticoreQL.send()

# `facet`

# `from`

# `highlight`

Adds `HIGHLIGHT()` to the SELECT list so Manticore annotates matching keywords in stored
fields. Requires the table to have `stored_fields` configured.

Options are passed as keyword pairs and become `key='value'` inside `HIGHLIGHT({...})`.
Common options: `before_match`, `after_match`, `around`, `limit`, `limit_passages`.

## Examples

    iex> ManticoreQL.new()
    |> ManticoreQL.from("articles")
    |> ManticoreQL.match("elixir")
    |> ManticoreQL.highlight()
    |> ManticoreQL.send()

    iex> ManticoreQL.new()
    |> ManticoreQL.from("articles")
    |> ManticoreQL.match("elixir")
    |> ManticoreQL.highlight(before_match: "<em>", after_match: "</em>", limit: 200)
    |> ManticoreQL.send()

# `highlight`

# `knn`

Sets a KNN (k-nearest-neighbour) vector search clause in WHERE. Requires the table to
have a `float_vector` attribute with an HNSW index.

Typically combine with `select/2` to also retrieve `knn_dist()` in results.

## Examples

    iex> ManticoreQL.new()
    |> ManticoreQL.select(["id", "title", "knn_dist()"])
    |> ManticoreQL.from("articles")
    |> ManticoreQL.knn("embedding", 5, [0.1, 0.2, 0.3, 0.4])
    |> Giza.send()

# `limit`

# `match`

# `meta`

# `new`

# `offset`

# `option`

# `order_by`

# `percolate`

Executes a percolate (reverse search) query — matches stored queries in a percolate table
against one or more incoming documents.

`doc` is a JSON string. `docs` is a list of JSON strings that will be wrapped in a JSON
array.

## Examples

    iex> ManticoreQL.percolate("pq_alerts", ~s({"title": "breaking news"}))
    {:ok, %SphinxqlResponse{}}

    iex> ManticoreQL.percolate("pq_alerts", [~s({"title": "foo"}), ~s({"title": "bar"})])
    {:ok, %SphinxqlResponse{}}

# `raw`

# `select`

# `suggest`

# `suggest`

# `where`

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*Consult [api-reference.md](api-reference.md) for complete listing*