3 Commits

Author SHA1 Message Date
Eilen Shin
aaca3eeaeb
refactor(agent): ground runtime decisions in structured evidence (#7986)
* refactor(agent): ground runtime decisions in structured evidence

Use producer status and structured errors for tool recovery, preserve memory context without lexical confirmation, and remove predetermined receipt and skill conclusions.

Require explicit MCP discovery and authenticated schedule trial actions. Preserve authorization, ownership, isolation, and bounded execution; update documentation and regression coverage.

* test(sandbox): expect read_file initialization error callback

* fix(agent): address evidence review follow-ups

* fix(agent): preserve retry budgets for OpenAI transport errors

* fix(agent): expose tool execution status in model requests

Project validated execution metadata and exact tool text into request-only JSON so status survives provider serialization. Preserve stored results and receipt hashes, cover SDK and graph boundaries, and migrate replay input hashes without changing recorded responses.

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Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-11-08 22:00:23 +08:00
一片一片
38e6be638b
fix(memory): tolerate unbounded stored fact confidence (#7764)
* fix(memory): tolerate unbounded stored fact confidence

A stored memory fact can carry a JSON integer such as 10**400. float() on it
raises OverflowError in _coerce_source_confidence and in the dedup merge
comparison, aborting the whole update cycle even though both sites already
handle every other unusable confidence. Treat the overflow like a missing or
non-finite value: 0.5 for ranking, 0.0 for the merge comparison.

* fix(memory): harden the remaining fact-confidence coercions

The import normalizer, prompt builder and relevance scorer each coerce a
stored fact confidence with float() and caught only TypeError/ValueError, so
an unbounded JSON integer such as 10**400 raised OverflowError: import failed
before the updater fallbacks ran, and prompt/relevance ranking could abort.
Catch OverflowError and take the existing defaults; document the full set of
coercions.
2026-11-01 15:04:16 +08:00
wd_pan
5d86ce345c
feat(memory): add deterministic near-duplicate fact gate (#5254)
* feat(memory): add deterministic near-duplicate fact gate

Add an opt-in write-side gate for DeerMem (issue #5252): a proposed NEW
fact whose bounded token-Jaccard similarity to an existing fact in the
same user/agent scope AND category reaches
fact_dedup_similarity_threshold merges into that fact instead of being
appended — the existing id/content/createdAt are kept, confidence is
raised to the maximum, and the source is refreshed, with one
facts_merged_dedup metric increment recording the merge.

Defaults preserve the legacy behavior exactly; targeted updates by fact
id and the exact-content key check are untouched. Companion write-side
step to the read-side relevance/diversity work in #5251.

Refs #5252
Signed-off-by: pwd11 <fvdsrc@163.com>

* fix(memory): preserve corrections during fact deduplication

Signed-off-by: pwd11 <fvdsrc@163.com>

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Signed-off-by: pwd11 <fvdsrc@163.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-09-14 07:22:38 +08:00