When a partial assistant reply fails and automatic retry succeeds, pi
appends a `context_edit` that hides the failed attempt from model
context. Branch summarization (`/tree` with summarize) built its input
from raw session entries through `getMessageFromEntry`, which ignored
`context_edit` entries. As a result, the summarizer received the hidden
attempt again. Content replacements were ignored the same way.
What the change does:
- `prepareBranchEntries` now collects the latest `context_edit` for each
target in the branch.
- It applies those edits to the entries it converts, using the same
`projectContextEntry` logic as the live context and compaction:
- an omission (`replacement: null`) drops the entry;
- a replacement swaps its content.
- `projectContextEntry` is now exported from `session-manager.ts` so
both paths share it.
- The existing branch-summary behavior is unchanged: tool results are
still skipped, and compaction or branch-summary entries still become
summary messages.
Testing:
- Added `applies context edits to branch entries` to
`test/branch-summarization.test.ts`. It covers one omitted assistant
entry and one replaced assistant entry. The test fails without the
change and passes with it.
- Ran `branch-summarization`, `branch-summary-extensions`,
`agent-session-branching` and the compaction tests: all pass.
- `npm run check`: biome and the coding-agent checks pass. `tsc` reports
6 errors in `packages/ai` model-catalog tests, and the same 6 errors
occur on unmodified `main`.
- End-to-end reproduction with the faux provider and `AgentSession`: a
failed attempt, a successful retry, then `navigateTree(target, {
summarize: true })`. Before the change, the summary request contained
the failed attempt's text. After the change, it contains only the
successful retry.
Fixes#11602
Requested by @davidbrai
Co-authored-by: triagent <triagent@localhost>
The `/tree` "Summarize" option ignored the session's thinking level.
`AgentSession` already passes `thinkingLevel` into the
`generateBranchSummary` options, but `generateBranchSummary` never read
it, so the request was built without `reasoning`.
For reasoning models on OpenAI Responses and Azure Responses, a missing
`reasoning` becomes `effort: thinkingLevelMap.off ?? "none"`. Models
that don't accept `"none"` then reject the branch summary with a 400
error:
```
Unsupported value: 'none' is not supported with the 'gpt-6-astra-…' model.
```
This change adds `thinkingLevel` to `GenerateBranchSummaryOptions`. It
sets `reasoning` on the request when the model supports reasoning and
the level is not `off`, the same rule compaction uses in
`createSummarizationOptions`.
**Testing**
- Added a test to
`packages/coding-agent/test/branch-summarization.test.ts` that records
the stream options for three cases: a reasoning model at `xhigh`, a
reasoning model at `off`, and a non-reasoning model. The expected
`reasoning` values are `["xhigh", undefined, undefined]`. Without the
fix, the test fails and every case gets `undefined`. With the fix, it
passes.
- Ran `branch-summarization`, `agent-session-branching`,
`branch-summary-extensions` and `compaction-summary-reasoning`: all
pass.
- `npm run check` passes.
- Not tested against a real provider endpoint.
Fixes#11444
Requested by @davidbrai
Co-authored-by: triagent <triagent@localhost>
Compaction summaries were limited to 0.8 * compaction.reserveTokens (13107 by default), turn-prefix summaries to 0.5 * reserveTokens, and branch summaries to a hardcoded 4096. On providers where reasoning shares the output limit (OpenAI Responses, adaptive Anthropic), high thinking levels used most of that limit and compaction failed with "generation hit the token cap", even though the model allows far more output.
Tying the limit to reserveTokens assumed the summary request is as large as the full context, so its output had to fit in the reserved space. It is usually much smaller: recent messages kept by keepRecentTokens are not sent, a split turn goes to a separate request, tool results are truncated, and tool definitions and the normal system prompt are not included. Manual compaction can also run long before the context is full. The provider layer already sizes output from the actual request, using the model's output limit reduced to fit the remaining context, as for normal turns.
Summary requests now set no maxTokens and rely on that. compaction.reserveTokens only controls when compaction starts.
generateSummary() and generateSummaryWithUsage() now ignore the reserveTokens parameter.
closes#9512, closes#9075, closes#10908
