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deepseek-harness/packages/llm
Tianyi Cui 39b3db4b9c docs: accuracy sweep, architecture restructure, two ADRs, review skill
- AGENTS.md Commands: fix typecheck/build descriptions; add lint, lint:fix,
  test:coverage, knip, publint, hygiene (were undocumented).
- Drop the bare `yarn demo` for explicit `demo:echo` + `demo:coding`; update
  README, examples READMEs (and document coding-agent in examples/README).
- New cookbook guide: adding-a-vendored-package.md (the missing "add" half of
  vendor/README's update-only procedure).
- architecture.md: add a table-of-contents and extract the Extension cookbook
  to docs/cookbook/extension-cookbook.md (link-preserving); drop the completed
  "restructure this document" TODO.
- ADR 0009 (capability seams) + 0010 (twin LLM adapters), and a "when to write
  an ADR" standard in adr/README.
- Add a committed dsh-code-review skill under .agents/skills, exposed to Claude
  Code via a tracked .claude/skills symlink (gitignore carve-out).
2026-06-13 22:05:34 +08:00
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dsh-llm

Provider-neutral LLM vocabulary and abstract service. This package defines the canonical language spoken by the agent loop, session logs, and every plugin.

Service: LlmService (ctx key: llm)

An adapter registry plus streaming / non-streaming call surfaces. Both call surfaces are interceptable via waterfall events.

Public API

  • ctx.llm.registerAdapter(models: string[], adapter: LlmAdapter): () => void Register an adapter for the given model names. Disposed with the calling fiber.
  • ctx.llm.models(): string[] — model names with a registered adapter.
  • ctx.llm.stream(options: GenerateOptions): AsyncIterable<StreamChunk> Stream one model call as raw chunks (token-level deltas).
  • ctx.llm.streamBlocks(options: GenerateOptions): AsyncIterable<ContentBlock> Stream as completed content blocks (convenience view).
  • ctx.llm.generate(options: GenerateOptions): Promise<GenerateResult> One model call, fully assembled.

Events

Event Mode Purpose
llm/stream waterfall Intercept/wrap every streaming model call (retry, caching, routing)
llm/generate waterfall Intercept/wrap every non-streaming model call
llm/adapter-change emit An adapter was registered or unregistered

Extension points

  • Subclass LlmAdapter and call ctx.llm.registerAdapter(models, adapter) to add a new model provider.
  • Wrap llm/stream or llm/generate via ctx.on() waterfall listeners for caching, retry, logging, rate-limiting, etc.

Content-block vocabulary (types.ts)

Messages are arrays of typed content blocks: text, reasoning, tool-call, tool-result, image. The union is derived from the merge-extensible ContentBlockMap, so plugins can add block types via declaration merging.

Streaming is a raw chunk protocol (block-start, text-delta, reasoning-delta, tool-call-delta, block-end, usage, finish). BlockAssembler is the single shared implementation that assembles chunks into blocks/messages.

Classes

  • LlmAdapter — abstract base class for provider adapters. The only required method is stream().
  • BlockAssembler — incrementally assembles raw chunks into complete content blocks and an assistant message. Used by the agent loop (raw chunks for replay
    • assembled for history) and by streamBlocks()/generate().
  • LlmError — typed error with a code string (NO_ADAPTER, DUPLICATE_ADAPTER, and adapter codes like AUTH/RATE_LIMIT) and an optional numeric status when the failure came from a non-2xx provider response.

Real adapters

Two adapters implement LlmAdapter against this vocabulary, deliberately built on different internals to keep the contract honest (see ADR 0010): @deepseek-ai/dsh-llm-deepseek (hand-rolled fetch/SSE) and @deepseek-ai/dsh-llm-pi-ai (via @earendil-works/pi-ai). The pair pinned down the StreamChunk conventions now documented in types.ts (usage before finish, raw-string tool arguments, the two sanctioned error paths).