# `Dsxir.Retrieval.InMemory`

Cosine-similarity brute-force retriever backed by a struct value.

    embedder = %Dsxir.Retrieval.Embedder{}
    index    = %Dsxir.Retrieval.InMemory{embedder: embedder}

    {:ok, index} = Dsxir.Retrieval.InMemory.add(index, ["alpha doc", "beta doc"])
    {:ok, hits}  = Dsxir.Retrieval.InMemory.search(index, "alpha-ish query", k: 1)

No process, no ETS table. Mutation returns a new struct.

## Persistence

    :ok          = Dsxir.Retrieval.InMemory.save(index, "/tmp/idx.bin")
    {:ok, index} = Dsxir.Retrieval.InMemory.load("/tmp/idx.bin")

Format is `:erlang.term_to_binary/1`; loads run with `[:safe]`.

# `t`

```elixir
@type t() :: %Dsxir.Retrieval.InMemory{
  docs: [String.t()],
  embedder: Dsxir.Retrieval.Embedder.t(),
  vectors: [[float()]]
}
```

# `add`

```elixir
@spec add(t(), [String.t()], keyword()) :: {:ok, t()} | {:error, term()}
```

Embed and append `new_docs` to the index, returning the updated struct.

# `load`

```elixir
@spec load(Path.t()) :: {:ok, t()} | {:error, term()}
```

Load an index from `path` previously written by `save/2`.

# `save`

```elixir
@spec save(t(), Path.t()) :: :ok | {:error, File.posix()}
```

Persist the index to `path` using `:erlang.term_to_binary/1`.

# `search`

```elixir
@spec search(t(), String.t(), keyword()) ::
  {:ok, [%{doc: String.t(), score: float()}]} | {:error, term()}
```

Return the top `:k` (default 3) documents ranked by cosine similarity against
the embedded `query`.

---

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