AbstractGateway v0.2.4

Added

• Explicit install profiles for the Gateway package: minimal base,
  http, multimodal, server, memory, apple, gpu, all-apple,
  all-gpu, and server-nvidia.
• abstractgateway-config plus abstractgateway config for operator status and
  private .env bootstrap without taking ownership of AbstractCore provider
  configuration.
• Gateway memory store resolver for AbstractMemory-backed LanceDB, SQLite, and
  in-memory stores, including /kg/query store metadata.
• Core catalog proxy endpoints for thin clients:
  GET /api/gateway/voice/voices,
  GET /api/gateway/audio/speech/models, and
  GET /api/gateway/vision/provider_models.
• Added a server-nvidia extra plus an experimental CUDA/PyTorch-based
  abstractgateway-server-nvidia Docker image recipe for full NVIDIA machines.
• Release and manual GHCR image workflows now publish the light default server
  image and attempt an experimental best-effort NVIDIA full image.

Changed

• Base installs are now intentionally minimal again:
  AbstractRuntime>=0.4.8 only.
• Server and multimodal profiles now use the aligned Runtime/Core/Voice/Vision
  floors: AbstractRuntime>=0.4.8, abstractcore>=2.13.12,
  abstractvision>=0.3.3, and abstractvoice>=0.9.2.
• Server, native Apple, native GPU, and NVIDIA profiles now require
  abstractagent>=0.3.5, so Gateway-hosted agent nodes resolve against the
  same Core/Runtime baseline as Gateway itself.
• Release tests now reset Gateway's process-global service between cases and
  pass explicit provider/model overrides for ledger summary/chat generation
  tests.
• Native Python hardware profiles are full deployment aggregates:
  abstractgateway[apple] and abstractgateway[all-apple] install the
  Apple-local stack and all relevant non-NVIDIA framework capabilities, while
  abstractgateway[gpu] and abstractgateway[all-gpu] install the matching
  local GPU stack.
• Gateway-owned runtime handoff now seeds _runtime.prompt_cache,
  _runtime.max_attachment_bytes, and _runtime.workflow_bundles_dir from
  Gateway configuration.
• Gateway LLM helper defaults now resolve through the same deployment cascade as
  runtime execution instead of hardcoded local model fallbacks.
• Docker Compose local builds can override ABSTRACTGATEWAY_EXTRAS; the
  default examples use port 8080, and an NVIDIA compose overlay is available
  for GPU hosts.
• The default Docker server image now composes abstractgateway[server,memory]
  so KG workflows and /kg/query have the AbstractMemory/LanceDB store package
  available without making memory a base-package dependency.
• The memory profile now depends on AbstractMemory[lancedb]>=0.2.6.

Fixed

• memory_kg_* effects and /kg/query no longer assume LanceDB directly;
  in-memory stores work, SQLite structured queries work when the installed
  AbstractMemory build exposes SQLiteTripleStore, and semantic queries fail
  clearly when the selected store has no vector/search capability.
• Dynamic voice/audio/vision catalog discovery now delegates to the AbstractCore
  server catalog boundary when configured, with bounded static fallback when it
  is not.
• Observer/chat/backlog/discovery helpers now return a clear provider/model
  configuration error when no request, Gateway env, or AbstractCore default is
  available.

Notes

• The default Docker image remains the release-grade light, portable image for
  linux/amd64 and linux/arm64. The NVIDIA image is linux/amd64 only and
  is experimental/best-effort because vLLM/Torch/Diffusers dependency
  resolution is much heavier than the default server profile and still needs a
  CUDA host smoke gate before production positioning.
• There is no practical MLX Docker image target for Apple Silicon today: MLX
  depends on Apple's Metal stack and Docker Desktop runs Linux containers
  without Metal/MPS device access. Apple local inference should stay native on
  macOS, not containerized; the Gateway container can point at Docker Model
  Runner, native LM Studio, mlx_lm.server, or Ollama OpenAI-compatible
  endpoints via model-runner.docker.internal or host.docker.internal.