Files
deepseek-harness/packages/llm/llm
Tianyi Cui 07f4047ff0 Use explicit ts specifiers for declarations
Restore explicit .ts relative specifiers in source and enable rewriteRelativeImportExtensions so emitted JS uses .js while declarations keep explicit .ts specifiers. Add a NodeNext declaration-consumer gate to prevent extensionless declaration regressions.
2026-06-22 06:11:00 +08:00
..

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 a single streaming call surface, interceptable via a waterfall event.

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). Consumers assemble the chunks into blocks/messages with BlockAssembler.

Events

Event Mode Purpose
llm/stream waterfall Intercept/wrap every streaming model call (retry, caching, routing)

Extension points

  • Subclass LlmAdapter and call ctx.llm.registerAdapter(models, adapter) to add a new model provider.
  • Wrap llm/stream 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. The agent loop feeds it raw chunks (logging them for replay) while reading the assembled blocks/message for history.
  • HarnessError — base class for the harness error taxonomy: a stable code string (distinct from the human message) plus cause chaining. Lives here, in the leaf package every other imports, so a single base is shared without a new dependency edge. Per-package errors (LlmError, ToolArgsError, InvariantError, …) extend it. isHarnessError(value) narrows at seams.
  • LlmError — extends HarnessError; code string (NO_ADAPTER, DUPLICATE_ADAPTER, and adapter codes like AUTH/RATE_LIMIT) plus 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 the twin LLM adapters): @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).