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docs: document package model experience

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Tianyi Cui
2026-07-12 02:12:36 +08:00
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packages/llm/llm-deepseek/README.md
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@@ -4,6 +4,13 @@ DeepSeek chat-completions adapter for the harness LLM seam: hand-rolled `fetch`
A second, independent implementation of the same seam exists in `@deepseek-ai/dsh-llm-pi-ai` (library-backed). Same Config shape — pick one per context (registering both for the same model names throws by design).
## Model Experience
| Context surface | What the model sees | Token effect |
|---|---|---|
| DeepSeek request | The selected DeepSeek model receives the harness system prompt, message history, tool schemas, stop sequences, and call config without adapter-authored prompt prose. On a prior assistant turn with tool calls, its reasoning content is passed back as required; reasoning from tool-call-free turns is omitted. | Provider tokenization governs exact input. Conditional reasoning passback increases tool-round-trip context, while dropping other reasoning avoids paying those tokens again; cache-read usage is reported when available. |
| DeepSeek response | Reasoning, text, and raw-string tool arguments are translated into harness chunks for the loop to log and assemble. | Generated tokens follow provider thinking and effort settings plus the request's `maxTokens`; only loop-retained blocks affect later input. |
## Config
```yaml

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packages/llm/llm-pi-ai/README.md
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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).
## Model Experience
| Context surface | What the model sees | Token effect |
|---|---|---|
| DeepSeek request through pi-ai | The selected model receives the same logical system prompt, history, tools, stop sequences, and raw replayed tool arguments as the hand-written adapter. This package adds no prompt prose and removes pi-ai's own per-tool `strict` default to preserve that contract. | Provider tokenization governs exact input. Reasoning level changes generated and passback content; pi-ai reports reasoning inside output usage rather than as a separate count. |
| DeepSeek response | pi-ai events become harness reasoning, text, tool-call, usage, and finish chunks; parsed tool arguments are restored to raw JSON strings at the harness boundary. | Generated content affects later inputs only after the loop records it; adapter conversion adds no model-visible text. |
## Why a second adapter exists
`@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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Provider-neutral LLM vocabulary and abstract service. This package defines the canonical language spoken by the agent loop, session logs, and every plugin.
## Model Experience
| Context surface | What the model sees | Token effect |
|---|---|---|
| Provider request transport | This service adds no system text, schema, or message. It routes the already-assembled frozen `GenerateOptions` to one adapter, while `llm/stream` listeners may cache, retry, or replace the stream without mutating that request. | Zero direct context tokens. The selected adapter and provider tokenizer determine billing, cache accounting, and serialization overhead for the existing content. |
| Streamed model output | Text, reasoning, and tool-call chunks are exposed to the loop, which decides what becomes retained assistant history. | Output usage is provider-reported; later input cost arises only after the loop records assembled content. |
## Service: `LlmService` (ctx key: `llm`)
An adapter registry plus a single streaming call surface, interceptable via a waterfall event.