Status: implemented
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dsh-llm owns a provider-neutral streaming vocabulary — the StreamChunk protocol (block-start, text-delta, reasoning-delta, tool-call-delta, block-end, usage, finish) and the content-block types (the content-block vocabulary). A vocabulary defined against a single adapter risks baking that adapter's quirks into the "neutral" contract: anything the one implementation happens to do becomes the de-facto spec, and the abstraction is unverified until a second provider arrives — by which point the leak is expensive to fix.
Ship two adapters against the one contract from the start, deliberately built on different internals:
dsh-llm-deepseek— directfetch+ in-repo translation against the DeepSeek API; SSE framing is delegated toeventsource-parser(the archived SSE-parser swap). The twin identity is owning the fetch/translate internals rather than delegating to a full provider SDK, not hand-rolling transport plumbing.dsh-llm-pi-ai— the same endpoint through the@earendil-works/pi-ailibrary (its own event vocabulary).
The rule they enforce: anything the StreamChunk vocabulary cannot express for BOTH implementations is a core-vocabulary bug, caught immediately rather than at the next provider. The pair pinned down conventions now documented on StreamChunk in dsh-llm/src/types.ts: usage emitted before finish, nothing after finish, tool-call arguments as raw JSON strings end-to-end, and the two sanctioned error paths (throw from stream() or end with finish {kind:'error'|'aborted'}) that a consumer must handle on both sides — a divergence the library-backed adapter surfaced that a single direct-fetch adapter would have hidden.
- A single adapter — less code and half the e2e cost, but leaves the "provider-neutral" claim unverified; the vocabulary would encode DeepSeek-via-fetch assumptions silently.
- A mock second adapter — cheaper but doesn't exercise a real provider's wire quirks, so it proves little. The twin is real-on-real.
The twin doubles adapter and key-gated e2e maintenance—both cover V4 Flash and Pro across representative reasoning modes—in exchange for continuous seam-neutrality validation and a second implementation example. Both use apiKey, baseURL, and models; the direct-fetch adapter exposes thinking/reasoningEffort, while pi-ai exposes one reasoning level. A future conformance suite could justify retiring one adapter through a superseding Agent Note.