indifferentketchup/boocode
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat: deferred items — arena token API + UI, ToolShim docs

Browse Source 
- Arena API: token_breakdown selected in contestant query
- ArenaPane: token category breakdown bar (s/u/a/t/r) in expanded contestant view
- apps/server/CLAUDE.md: document tool-shim and loop-detectors
This commit is contained in:
indifferentketchup
2026-06-07 18:41:26 +00:00
parent bef6bef504
commit f436021bf9
3 changed files with 13 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
apps/server/CLAUDE.md
View File

@@ -17,6 +17,8 @@
- **Tools have NO `execute` field.** BooCode dispatches tools in tool-phase.ts, not the AI SDK loop — only `description` + `inputSchema: jsonSchema(parameters)`.
- **`includeUsage: true` MUST be set on `createOpenAICompatible`** in `provider.ts`. The adapter defaults it false → no `stream_options.include_usage` → llama-swap emits no usage block → `result.usage` resolves `undefined` (NULL token counts). Don't remove during refactor.
- **Tool-call-only turns may emit a leading `\n` text-delta.** `MessageList.flatten`'s `hasText` and `MessageBubble`'s `hasContent` both `.trim()` before the length check, else whitespace-only content renders an empty bubble + ActionRow between tool calls. `buildMessagesPayload` also skips `status='failed'` and complete-but-empty assistant rows (avoids "Cannot have 2 or more assistant messages at the end of the list" upstream rejection after cap-hit + Continue).
- **`services/inference/tool-shim.ts`** — Recovers structured tool calls from plain-text model output. Some models (notably Qwen) emit `<tool_call><name>...</name><arguments>...</arguments></tool_call>` inline text instead of structured JSON. `extractToolCalls(text)` parses both XML and JSON inline formats. `hasToolCallMarkup(text)` is a fast pre-check. Used as a fallback in the stream phase when structured `tool_calls` parse fails. Does NOT require `FAST_MODEL` — operates on the existing turn's output text.
- **`services/inference/loop-detectors.ts`** — Six detectors that catch repetitive model behavior: `detectContentRepeat` (same content N times), `detectToolLoop` (same tool called consecutively). `detectDoomLoop` combines both. These are additive to the existing `sentinels.ts` doom-loop detection.
- **AI SDK ModelMessage conversion** (`toModelMessages` in stream-phase.ts). Tool messages need a `toolName` for `ToolResultPart`; BooCode's OpenAI-shape history lacks it, so a forward-scan builds a `tool_call_id → toolName` map from prior assistant `tool_calls`. Tool outputs wrapped as `{ type: 'json' | 'text', value }` (v6 `ToolResultOutput`). Reasoning emits a `ReasoningPart` first in the content array.
- **`experimental_repairToolCall`** wired into `streamText` to keep the stream alive when qwen3.6 emits malformed tool args. Pass-through: logs the bad call, returns it unmodified; `executeToolPhase`'s zod-reject path routes it back to the model next turn.
- **`chat_status` frame** (via `broker.publishUser`) — `status: 'streaming' | 'tool_running' | 'waiting_for_input' | 'idle' | 'error'`. Frontend `useChatStatus` derives `idle_warm` (<30s since idle) vs `idle_cold`. `ChatThroughput` renders beside `StatusDot` only when streaming/tool_running, fed by 500ms-throttled `'usage'` frames (`completion_tokens` + `ctx_used` + `ctx_max`). `POST /api/chats/:id/discard_stale` marks a stuck-streaming row `failed` when the frontend's 60s no-token timer gives up.