d02e9f1bd6
Move the 18 flat packages/<name> packages into role-grouped dirs: core/, llm/, bash/, session-persistence/, ui/, support/. Group dirs are pure containers; each package keeps its @deepseek-ai/dsh-* name. Collapse the per-package tsconfig paths maps (base + typecheck) into one @deepseek-ai/dsh-* wildcard with a candidate per group, and derive the publint list from the hierarchy. Update all depth-coupled globs/configs (workspace, tsdown, vitest, eslint, knip, tsconfig includes/refs, per-package tsconfigs, generators, doc-script scopes, type-equiv manifest) and the cross-package/script relative imports in tests. Fix doc-typecheck's workspacePaths() to parse tsconfig JSONC via the TypeScript API instead of a regex comment-strip, which corrupted the new wildcard `/*/` path candidates. WIP: doc cross-links and package/RFC docs still to update.
39 lines
2.6 KiB
Markdown
39 lines
2.6 KiB
Markdown
# @deepseek-ai/dsh-llm-pi-ai
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DeepSeek adapter for the harness LLM seam backed by [`@earendil-works/pi-ai`](https://www.npmjs.com/package/@earendil-works/pi-ai) (the LLM library behind the pi agent).
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## Why a second adapter exists
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`@deepseek-ai/dsh-llm-deepseek` already talks to the same endpoint. This package is its **design-verification twin**: same models, same wire protocol, completely different internals — a unified LLM library with its own event vocabulary versus hand-rolled fetch/SSE. Anything the harness `StreamChunk` protocol cannot express for BOTH implementations is a core-vocabulary bug. The differences it exercised on purpose:
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- pi-ai hands tool-call `arguments` around as **parsed objects**; the harness keeps raw JSON strings. The adapter patches replay payloads back to the original raw strings before sending them, and re-stringifies parsed output tool calls at `block-end`.
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- pi-ai reports failures as **in-stream error events** (it never throws mid-stream); these map to `finish {kind:'error'|'aborted'}` chunks — the protocol's other sanctioned error path besides throwing (which llm-deepseek uses).
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- pi-ai folds reasoning tokens into `usage.output`; there is no separate reasoning count to map.
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- pi-ai's options omit some DeepSeek/OpenAI-compatible details; the adapter uses its `onPayload` hook to preserve the harness contract (`stop`, per-tool `strict`, omitted reasoning effort, raw replayed tool arguments).
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## Config
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Same shape as llm-deepseek (one-line swap in cordis.yml), with pi-ai's thinking-level vocabulary:
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```yaml
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- id: llm
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name: '@deepseek-ai/dsh-llm-pi-ai'
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config:
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apiKey: !!js process.env.DEEPSEEK_API_KEY
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baseURL: !!js process.env.DEEPSEEK_BASE_URL
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models: [deepseek-v4-flash, deepseek-v4-pro]
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reasoning: high # off | high | xhigh (xhigh → wire 'max')
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```
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## Dependency weight
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pi-ai declares the openai/anthropic/google/mistral/AWS SDKs as install-time dependencies. They are lazy-loaded — only the openai SDK actually loads for this adapter — but they do land in `node_modules`. Accepted for a package whose purpose is design verification.
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## Limitations
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Same MVP contract as llm-deepseek: `prefill` throws `UNSUPPORTED`, images are not representable, `tool_choice` is not mapped.
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## Testing
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Unit suites run against a local `node:http` mock SSE server (pi-ai's openai SDK happily talks to any base URL). Real-API coverage in `tests/adapter.e2e.ts` (`pnpm run test:e2e`, key-gated): V4 Flash + V4 Pro across all exposed reasoning levels (off/high/xhigh), the thinking+tools round trip, and a cross-adapter structural-equivalence check against llm-deepseek.
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