dspex

# Generated by SnakeBridge v0.13.0 - DO NOT EDIT MANUALLY
# Regenerate with: mix compile
# Library: dspy 3.1.2
# Python module: dspy.propose.grounded_proposer

defmodule Dspy.Propose.GroundedProposer do
  @moduledoc """
  Submodule bindings for `dspy.propose.grounded_proposer`.

  ## Version

  - Requested: 3.1.2
  - Observed at generation: 3.1.2

  ## Runtime Options

  All functions accept a `__runtime__` option for controlling execution behavior:

      Dspy.Propose.GroundedProposer.some_function(args, __runtime__: [timeout: 120_000])

  ### Supported runtime options

  - `:timeout` - Call timeout in milliseconds (default: 120,000ms / 2 minutes)
  - `:timeout_profile` - Use a named profile (`:default`, `:ml_inference`, `:batch_job`, `:streaming`)
  - `:stream_timeout` - Timeout for streaming operations (default: 1,800,000ms / 30 minutes)
  - `:session_id` - Override the session ID for this call
  - `:pool_name` - Target a specific Snakepit pool (multi-pool setups)
  - `:affinity` - Override session affinity (`:hint`, `:strict_queue`, `:strict_fail_fast`)

  ### Timeout Profiles

  - `:default` - 2 minute timeout for regular calls
  - `:ml_inference` - 10 minute timeout for ML/LLM workloads
  - `:batch_job` - Unlimited timeout for long-running jobs
  - `:streaming` - 2 minute timeout, 30 minute stream_timeout

  ### Example with timeout override

      # For a long-running ML inference call
      Dspy.Propose.GroundedProposer.predict(data, __runtime__: [timeout_profile: :ml_inference])

      # Or explicit timeout
      Dspy.Propose.GroundedProposer.predict(data, __runtime__: [timeout: 600_000])

      # Route to a pool and enforce strict affinity
      Dspy.Propose.GroundedProposer.predict(data, __runtime__: [pool_name: :strict_pool, affinity: :strict_queue])

  See `SnakeBridge.Defaults` for global timeout configuration.

  """

  @doc false
  def __snakebridge_python_name__, do: "dspy.propose.grounded_proposer"
  @doc false
  def __snakebridge_library__, do: "dspy"

  @doc """
  Python binding for `dspy.propose.grounded_proposer.generate_instruction_class`.

  ## Parameters

  - `use_dataset_summary` (term() default: True)
  - `program_aware` (term() default: True)
  - `use_task_demos` (term() default: True)
  - `use_instruct_history` (term() default: True)
  - `use_tip` (term() default: True)

  ## Returns

  - `term()`
  """
  @spec generate_instruction_class() :: {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(keyword()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), keyword()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term(), keyword()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term(), term()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term(), term(), keyword()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term(), term(), term()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term(), term(), term(), keyword()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term(), term(), term(), term()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  @spec generate_instruction_class(term(), term(), term(), term(), term(), keyword()) ::
          {:ok, term()} | {:error, Snakepit.Error.t()}
  def generate_instruction_class() do
    SnakeBridge.Runtime.call(__MODULE__, :generate_instruction_class, [], [])
  end

  def generate_instruction_class(opts)
      when is_list(opts) and
             (opts == [] or
                (is_tuple(hd(opts)) and tuple_size(hd(opts)) == 2 and is_atom(elem(hd(opts), 0)))) do
    SnakeBridge.Runtime.call(__MODULE__, :generate_instruction_class, [], opts)
  end

  def generate_instruction_class(use_dataset_summary) do
    SnakeBridge.Runtime.call(__MODULE__, :generate_instruction_class, [use_dataset_summary], [])
  end

  def generate_instruction_class(use_dataset_summary, opts)
      when is_list(opts) and
             (opts == [] or
                (is_tuple(hd(opts)) and tuple_size(hd(opts)) == 2 and is_atom(elem(hd(opts), 0)))) do
    SnakeBridge.Runtime.call(__MODULE__, :generate_instruction_class, [use_dataset_summary], opts)
  end

  def generate_instruction_class(use_dataset_summary, program_aware) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware],
      []
    )
  end

  def generate_instruction_class(use_dataset_summary, program_aware, opts)
      when is_list(opts) and
             (opts == [] or
                (is_tuple(hd(opts)) and tuple_size(hd(opts)) == 2 and is_atom(elem(hd(opts), 0)))) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware],
      opts
    )
  end

  def generate_instruction_class(use_dataset_summary, program_aware, use_task_demos) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware, use_task_demos],
      []
    )
  end

  def generate_instruction_class(use_dataset_summary, program_aware, use_task_demos, opts)
      when is_list(opts) and
             (opts == [] or
                (is_tuple(hd(opts)) and tuple_size(hd(opts)) == 2 and is_atom(elem(hd(opts), 0)))) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware, use_task_demos],
      opts
    )
  end

  def generate_instruction_class(
        use_dataset_summary,
        program_aware,
        use_task_demos,
        use_instruct_history
      ) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware, use_task_demos, use_instruct_history],
      []
    )
  end

  def generate_instruction_class(
        use_dataset_summary,
        program_aware,
        use_task_demos,
        use_instruct_history,
        opts
      )
      when is_list(opts) and
             (opts == [] or
                (is_tuple(hd(opts)) and tuple_size(hd(opts)) == 2 and is_atom(elem(hd(opts), 0)))) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware, use_task_demos, use_instruct_history],
      opts
    )
  end

  def generate_instruction_class(
        use_dataset_summary,
        program_aware,
        use_task_demos,
        use_instruct_history,
        use_tip
      ) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware, use_task_demos, use_instruct_history, use_tip],
      []
    )
  end

  def generate_instruction_class(
        use_dataset_summary,
        program_aware,
        use_task_demos,
        use_instruct_history,
        use_tip,
        opts
      )
      when is_list(opts) and
             (opts == [] or
                (is_tuple(hd(opts)) and tuple_size(hd(opts)) == 2 and is_atom(elem(hd(opts), 0)))) do
    SnakeBridge.Runtime.call(
      __MODULE__,
      :generate_instruction_class,
      [use_dataset_summary, program_aware, use_task_demos, use_instruct_history, use_tip],
      opts
    )
  end
end