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majordomo/docs/adr/0015-llama-swap-provider.md
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feat(llamaswap): add llama-swap provider + canonical imagegen interface
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>
2026-06-27 15:01:54 -04:00

3.0 KiB

ADR-0015: llama-swap provider

Status: Accepted — 2026-06-27

Context

llama-swap (https://github.com/mostlygeek/llama-swap) is an on-demand model-swapping proxy in front of llama.cpp (and stable-diffusion.cpp) servers: it extracts the model from each request, loads/hot-swaps the matching upstream, and serves it. It is what foreman reached for, but more robust (groups, TTL unload, health checks, a management API). We want it as a first-class majordomo target — llama-swap://token@host:port in the DSN — and the user explicitly asked for a tailored provider, not a bare alias of the OpenAI client.

The tension: llama-swap's chat API is byte-for-byte OpenAI Chat Completions. A new hand-rolled chat wire client would duplicate provider/openai for zero behavioral gain, which ADR-0007 forbids. But the "more robust" surface (model discovery, running list, unload) does not fit the canonical llm.Provider/llm.Model interface (anti-creep: no provider-specific features leak into the canonical API).

Decision

  • A dedicated provider/llamaswap package, but its chat path delegates to provider/openai pointed at {baseURL}/v1 — no duplicated wire client. Provider.Model returns openai.New(...).Model(id).
  • Chat construction specifics: WithLegacyMaxTokens() (llama.cpp's OpenAI shim honors max_tokens, not max_completion_tokens); a placeholder Bearer no-key when no token is set (the openai client treats a blank key as a synthetic 401, but a local keyless llama-swap ignores a bearer it didn't ask for); the injected HTTP client carries no timeout — a cold model swap blocks up to llama-swap's healthCheckTimeout (≥15s), so callers bound work with a context deadline, never a client timeout.
  • The "tailored" surface lives as concrete methods on *llamaswap.Provider, outside the canonical interface: ListModels (GET /v1/models), Running (GET /running, returned as raw JSON — its shape is not a stable contract), Unload (POST /api/models/unload[/:model]). A small doJSON helper shares bearer auth + error mapping; non-2xx → *llm.APIError (so llm.Classify applies), transport errors wrapped raw.
  • DSN: the llama-swap scheme builds an http:// base URL from the host (llama-swap is local-first), deliberately not the DSN's https-always BaseURL(). A TLS-fronted instance can use the openai:// scheme for chat. A no-DSN built-in llama-swap provider registers but errors on use (mirrors foreman).
  • Image generation is implemented here too, against the new imagegen interface (see ADR-0016).

Consequences

  • No new dependency, no duplicated chat client; the chat path inherits every openai feature/fix automatically.
  • Management methods are reachable only by holding the concrete *llamaswap.Provider (e.g. mort), not through Parse/llm.Provider — the correct boundary for non-canonical features.
  • Running's raw-JSON return is honest about llama-swap not publishing a stable schema; a typed shape can be added later without breaking callers that ignore it.