Coder/deepseek-harness
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

docs: replace model experience tables with sections

Browse Source
This commit is contained in:
Tianyi Cui
2026-07-13 22:26:33 +08:00
parent 646f3d2d0c
commit d77f797d89
57 changed files with 712 additions and 325 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
packages/llm/llm-deepseek/README.md
View File

@@ -44,10 +44,17 @@ Unit suites run against a local `node:http` mock SSE server (no network). Real-A
## 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. |
### DeepSeek request
**What the model sees**: 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.
**Token effect**: 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
**What the model sees**: Reasoning, text, and raw-string tool arguments are translated into harness chunks for the loop to log and assemble.
**Token effect**: Generated tokens follow provider thinking and effort settings plus the request's `maxTokens`; only loop-retained blocks affect later input.
## Known Limitations and Deferred Work