steve
96c612e707
Add provider/llamaswap, a tailored provider for llama-swap (the model-swapping
proxy over llama.cpp / stable-diffusion.cpp). Its chat path delegates to
provider/openai at {base}/v1 — no duplicated wire client (ADR-0007) — with
legacy max_tokens, a Bearer no-key placeholder for keyless local instances, and
a timeout-free client so cold model swaps rely on context deadlines. The
"tailored" surface is concrete management methods (ListModels / Running /
Unload) that don't belong on the canonical llm.Provider interface. The
llama-swap:// DSN scheme builds an http base URL (local-first); a no-URL
built-in errors clearly on use, mirroring foreman.
Add imagegen, a new canonical text-to-image interface separate from llm
(Request/Result/Model/Provider; Image = llm.ImagePart so generated images feed
straight back into chat). First backend is llama-swap via OpenAI
/v1/images/generations (b64_json, bytes-only). Re-exported from the root. v1 is
txt2img only.
Hermetic httptest coverage for chat delegation, management endpoints, image
decode, and scheme wiring. ADR-0015 + ADR-0016, README support matrix +
image-gen section, CLAUDE.md package map, and progress.md updated in the same
commit.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2.3 KiB
2.3 KiB
ADR-0016: imagegen — a canonical text-to-image interface
Status: Accepted — 2026-06-27
Context
mort needs to generate images (via llama-swap's stable-diffusion.cpp backend),
and majordomo had no image-generation surface. Image generation does not fit
the chat contract: there are no conversation messages, tools, streaming, or
failover-chain semantics — forcing it through llm.Request/llm.Response/
llm.Model would overload that contract with mostly-unused fields. The user
asked for "a new ai image interface as opposed to llm".
Decision
- A new canonical leaf package
imagegen, parallel tollm, re-exported from the root (ImageModel,ImageProvider,ImageRequest,ImageResult,ImageOption, plusWithImageCount/WithImageSize). Providers importimagegen; mort codes to the interface, not to llama-swap. - Minimal v1 surface (text-to-image only):
Request{ Prompt string; N int; Size string }— zero values mean provider default (N=0 → backend default count; "" Size → backend default).Result{ Images []Image; Raw any }.Model.Generate(ctx, Request, ...Option) (*Result, error)andProvider.ImageModel(id, ...ModelOption) (Model, error).- Functional options +
Request.Apply, mirroringllm.
type Image = llm.ImagePart(bytes + MIME). Reusing the chat content type means a generated image drops straight back into a chat turn (llm.UserParts(res.Images[0])) with no conversion — the key interop win.- Out of scope for v1 (designed-for, deferred): image edits / img2img, the raw A1111 SDAPI, masks/seeds/steps, streaming, and registry-level image-model DSN resolution (construct the provider directly for now).
- First implementation:
provider/llamaswap, targeting OpenAI/v1/images/generationswithresponse_format: "b64_json"(bytes inline; we never fetch remote URLs — mirrorsImagePart's bytes-only contract).
Consequences
- Image generation is provider-agnostic from day one; a future OpenAI DALL·E or Gemini image backend implements the same interface.
- The narrow interface keeps the door open for richer requests without breaking callers (additive fields/options).
- No health/failover for image models yet; if needed it can be added as a separate chain type rather than retrofitting the chat chain.