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João MouraandClaude Opus 5.5
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* fix(flow): learn from human feedback that resumes a paused flow With learn=True, lessons were distilled only when the reply arrived during the same run. A reply that resumes a paused flow (resume / resume_async after from_pending, which is how async providers such as AMP's email review work) went through outcome collapse and routing but never reached _distill_and_store_lessons, so it taught nothing. Resume now stores lessons under the same conditions as an in-run reply: memory available, non-empty feedback, the method's learn_source and learn_strict, and the persisted LLM config. Both paths share one helper. A strict distillation failure fails the resume before the pending review is cleared, so it can be retried. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(flow): undo the recorded reply when strict learning fails on resume _finalize_human_feedback appends the reply to human_feedback_history and sets last_human_feedback before lessons are stored. With learn_strict, a distillation failure re-raises and the review stays pending, so a retry on the same instance recorded the reply twice. Restore both on failure. Lesson storage stays after outcome collapse, so a collapse failure never leaves lessons behind to be stored again on retry. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(flow): keep the reviewed output's type when learn=True pre-reviews it Pre-review always returned PreReviewResult.improved_output, a str, so a method returning a Pydantic model or a dict reached the reviewer, and last_human_feedback.output, as a repr string. Text output is still rewritten as text; a Pydantic model is now rewritten as the same model (response_model=type(output)); other outputs are shown unchanged. LiteLLM-routed models return structured output as a JSON string, which PreReviewResult/DistilledLessons.model_validate rejected, so pre-review and lesson storage silently did nothing for them. One parser now accepts an instance, a JSON string, or a dict. Docs (en, ar, ko, pt-BR): drop the nonexistent learn_limit, document learn_source and learn_strict, say lessons are also learned from replies that resume a paused flow, how each output type is pre-reviewed, and that downstream steps should read last_human_feedback.output. Correct the HumanFeedbackResult.output docstring and the learn/learn_strict field descriptions. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(flow): keep pre-review failures and unseen fields from leaking into the output model_dump_json() ran before the pre-review try, so a Pydantic output that cannot be serialized failed the feedback step even with learn_strict off. It now runs inside the try and falls back to the original output. A reviewed Pydantic model is rebuilt from what the LLM saw, so a SecretStr (sent masked) or an excluded field (not sent) came back as the mask or the default. Fields the review left unchanged now keep their original values. Also pin that a retry after a persistence failure that follows lesson storage offers the lessons to memory again. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(flow): keep nested hidden values when pre-review edits sibling fields The unchanged-field restore only looked at top-level fields, so editing a sibling inside a nested model, or one item of a list of models, kept the LLM's masked secret and default excluded values for that whole object. The restore now recurses into nested models and same-length lists of models. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * fix(flow): skip pre-review for models holding secrets or excluded fields Restoring hidden values after the review kept growing edge cases: aliased fields compared by name discarded the review's edit, dicts of models were not recursed, and reordered lists paired the wrong items, which could copy one account's secret onto another. Drop the merge. A Pydantic output is pre-reviewed only when the LLM sees all of it; one holding a Secret, SecretStr, SecretBytes or Field(exclude=True) value at any depth reaches the reviewer unchanged. Docs updated in en, ar, ko and pt-BR. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> * docs(flow): say a resumed review's Pydantic output arrives as a dict PendingFeedbackContext persists method_output as JSON, so after from_pending and resume, last_human_feedback.output is a dict even when the method returned a model. The docstring and docs said "same type" without that qualification. Also say learn_strict covers distillation and submitting lessons, not the background memory write. Pin the dict behavior with a pause/resume test. Docs in en, ar, ko and pt-BR. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>