Merged
Conversation
* fix: lint * feat: add addMessage Stage log * feat: add addMessage Stage log * feat: optimized embedding item --------- Co-authored-by: harvey_xiang <harvey_xiang22@163.com>
* fix: polardb metadata bug fix * fix: fix chunking bug in memreader * fix: also fix get_node for nested metadata
* feat: optimize dispatcher task * feat: format redis_queue.py
Co-authored-by: yuan.wang <yuan.wang@yuanwangdebijibendiannao.local>
clean_json_response treats its argument as a str and unconditionally calls .replace(). When an upstream LLM helper returns None (e.g. due to the silent-fail pattern in timed_with_status), the resulting AttributeError points to format_utils.py rather than to the failed LLM call, which is hard to diagnose. Add an explicit None check that raises a descriptive ValueError. This turns the symptom 'NoneType has no attribute replace' into a message that names the actual root cause.
* feat: add .env.example-full and fix .env.example
* feat(memos-local-plugin): v2.0 full rewrite with Reflect2Evolve architecture
Complete end-to-end rewrite of the memos-local-plugin package into a
layered, agent-agnostic memory runtime with support for both OpenClaw
and Hermes adapters.
Highlights:
- New `core/` package (agent-agnostic): capture, embedding, feedback,
hub, LLM client, logger, memory (L1/L2/L3), pipeline, reward, recall,
retrieval, skill, session, storage, config modules — each with its
own README + ALGORITHMS notes.
- New `adapters/` layer with `openclaw/` and `hermes/` integrations
isolated from core. Agent-specific concepts (turns, installers,
bridge clients) live only here.
- New `agent-contract/` — single shared contract (dto, errors, events,
jsonrpc, log-record, memory-core) between core and adapters.
- New `bridge/` — JSON-RPC stdio bridge (methods.ts, stdio.ts).
- New `server/` — HTTP/SSE server for the viewer.
- New `site/` — Vite-built public product site + release notes index.
- New `web/` — Vite-built viewer app with memory/skill/timeline/world
model views.
- New `docs/` — ALGORITHM, DATA-MODEL, LOGGING, MANUAL_E2E_TESTING,
Reflect2Skill design core, multi-agent viewer, etc.
- New `tests/` — vitest unit/integration + python bridge tests.
- Tooling: TypeScript multi-project build (tsconfig.{json,site,web}),
Vite + Vitest, cross-platform install.sh / install.ps1, npm release
checker, package-lock committed.
- Removes legacy `src/` and `www/` structure from main branch; the new
layout replaces it entirely.
This change is fully scoped to apps/memos-local-plugin/ and does not
touch any other package.
* style(memos-local-plugin): apply ruff check + format to Python files
- Remove unused imports (Iterable, Dict, List) in memos_provider/__init__.py
- Move Callable into TYPE_CHECKING block in bridge_client.py
- Replace try/except/pass with contextlib.suppress in bridge_client.py
- Combine nested if in test_bridge_client.py
- Apply ruff format to 4 Python files (hermes adapter + tests)
All files now pass `ruff check` and `ruff format --check`.
* feat(memos-local-plugin): preserve mid-turn reasoning + retrieval improvements
Capture path (thinking-between-tool-calls):
- Adapter extractTurn now flushes thinking + assistant-text that appears
between consecutive tool calls into the next ToolCallDTO's
`thinkingBefore`, preserving the model's natural-language bridge
(e.g. "nproc failed, let me try sysctl") in the trace.
- Adapter flattenMessages: when pi-ai `content[toolCall]` coexists with
legacy top-level `tool_calls`, skip the legacy path so each call is
emitted once (prior double-push clobbered the first stub's
`thinkingBefore` via pendingCalls.set, making the field silently go
missing and doubling tool-call rows in the DB).
- Orchestrator: tool turns now persist `thinkingBefore` in
EpisodeTurn.meta so the capture step-extractor can re-attach it.
- Step extractor: only the first tool sub-step carries `userText`;
subsequent sub-steps leave it empty so the viewer's flattenChat
doesn't render the same user bubble N times.
- Step extractor: `toolCallFromTurn` + `coerceToolCall` now read
`thinkingBefore` back from meta.
- Normalizer: sub-step candidates skip the generic dedup path — their
intentionally-identical empty userText/agentText plus 1-tool shape
used to collapse two distinct tools into one whenever their input
prefixes matched under 200 chars.
- Agent contract DTO: `ToolCallDTO.thinkingBefore?: string` added; no
schema migration needed (stored inside `tool_calls_json`).
- Web flattenChat: renders per-tool `thinkingBefore` bubbles before
each tool call for the user↔agent timeline; retains legacy
`agentThinking` single-bubble fallback for pure-reply traces.
Retrieval path:
- LLM-filter: refactored prompt templates and schema shape.
- Ranker: reworked scoring with new blend knobs.
- Retrieve + pipeline wiring updated to match the new types.
- Config defaults + schema expose the new retrieval knobs.
- Viewer LogsView surfaces new filter fields; i18n updated.
Tests:
- New regression tests for extractTurn interleaved thinking, pi-ai +
OpenAI-legacy double-push avoidance, and flattenChat sub-step
rendering.
- Retrieval / llm-filter / ranker tests updated for the new shape.
* feat(memos-local-plugin): one-round-one-card UI + language-aware knowledge + L2/L3 boundary prompts
UI: one user turn = one memory card
- New `traces.turn_id INTEGER` column (migration 013) stamped by
`step-extractor` with the user turn's ts; every sub-step of the same
user message shares the same turnId.
- `MemoryGroup` aggregation in `web/src/views/MemoriesView.tsx` collapses
rows by (episodeId, turnId): one card per turn, role pill chosen by
group-level rule (any tool → "tool"), aggregate V/α displayed as the
member-row mean.
- Drawer rewritten as `<StepList>`: every member step renders as a
collapsible <details> block with its own ts / V / α / agentThinking /
toolCalls / reflection. First step expanded, rest collapsed so a
10-tool turn doesn't drown the user.
- Bulk actions (select / delete / share / export) operate on whole
cards: card checkbox toggles the full set of member ids; delete /
share / export bulk over `g.ids` so a card never half-disappears.
- Algorithm layer untouched — every L1 trace stays step-level so V/α
reflection-weighted backprop, L2 incremental association, Tier-2
error-signature retrieval, and Decision Repair keep their per-step
granularity (V7 §0.1).
Per-tool reasoning capture (carryover, see PR #1515)
- ToolCallDTO carries `value` / `reflection` / `thinkingBefore` so the
drawer's per-step section can show the per-tool intermediate
thinking and any LLM-assigned per-tool score without a schema change.
- StepCandidate.meta.turnId / subStep / subStepIdx / subStepTotal
threaded through capture.ts → traces.turn_id; `pickTurnId` falls
back to the trace's own ts so old fixtures still produce singleton
groups instead of crashing.
Knowledge generation in user's language
- `core/llm/prompts/index.ts` adds `detectDominantLanguage(samples,
{minSignal})` — counts CJK ideographs + ASCII letters and returns
"zh" / "en" / "auto" (allocation-free, runs on every gen call).
- All five knowledge-generation sites now emit a `languageSteeringLine`
system message keyed off their evidence:
* core/capture/alpha-scorer.ts ← reflection-quality reason
* core/capture/batch-scorer.ts ← per-step batch reflections
* core/memory/l2/induce.ts ← L2 policy fields
* core/memory/l3/abstract.ts ← L3 (ℰ, ℐ, C) bullets
* core/skill/crystallize.ts ← skill body + scope
- Effect: a Chinese-speaking user no longer gets a half-English skill
card. An English user no longer gets a 中文-mixed reflection.
L2 / L3 prompts: hard boundary against drift
- `L2_INDUCTION_PROMPT` v1 → v2: explicit "what NOT to write" guard
rejects environment topology, declarative behavioural rules, and
generic taboos. New same-fact-two-framings example shows how to
re-fold an env fact into a state-level trigger or step-level caveat.
- `L3_ABSTRACTION_PROMPT` v1 → v2: bans imperative verbs (do/should/use/
install/run) under any of ℰ/ℐ/C; reworked all three example sets to
pure declarative ("loading a glibc-linked binary wheel inside Alpine
raises a dynamic-link error" instead of "if pip fails, install dev
libs and retry"). Same-fact contrast example included.
- Test mock keys updated v1 → v2 in induce.test.ts /
l2.integration.test.ts / openclaw-full-chain.test.ts /
v7-full-chain.e2e.test.ts. Historical `inducedBy` audit strings
intentionally left at v1 — they're metadata recording the prompt
version a row was generated under, not call-time keys.
Retrieval injector: heading hierarchy
- `# User's conversation history (from memory system)` is now H1, with
`## Memories` / `## Skills` / `## Environment Knowledge` as H2 so the
injected block has a clean outline in the LLM's context (previously
the inner sections used H1 too, breaking the visual hierarchy).
Migration runner: SQLite defensive mode
- better-sqlite3 ≥ v11 enables `SQLITE_DBCONFIG_DEFENSIVE` which blocks
writes to `sqlite_master` even with `PRAGMA writable_schema=ON`.
Migration 012 (status unification) needs that pragma to swap CHECK
constraints in-place. `runMigrations` now flips `db.raw.unsafeMode`
on at the outer boundary if any pending migration uses
`writable_schema`, then off again in `finally`. Migrations are
shipped with the plugin (never user input) so this is safe.
- Migration 012 SQL itself rewritten to use single-quote string
literals with doubled inner quotes (instead of double quotes that
better-sqlite3 strict mode treats as identifiers).
Documentation
- New `docs/GRANULARITY-AND-MEMORY-LAYERS.md` — mental-model alignment
doc explaining: 小步/轮/任务 三个粒度的关系、打分粒度（每步 α/V，
每任务 R_human，"轮"无独立分）、检索粒度（技能/单步/子任务序列/
环境认知，没有"按轮"召回）、生成链路（小步→经验→环境认知→技能）、
以及 §6 "经验 vs 环境认知 边界裁剪" 章节回答"该不该合并"问题：7 条
反对合并的理由 + 三种折中方案对比 + 同事实多框架对照判别表。
- `docs/Reflect2Skill_算法设计核心.md` 头部加阅读顺序提示，引导新人
先看上面那篇粒度对齐文档。
- `docs/README.md` 索引同步更新，标粗 GRANULARITY-AND-MEMORY-LAYERS。
Tests
- `tests/unit/capture/step-extractor.test.ts`: turnId stability
assertions across sub-steps; multi-tool turn shares one turnId.
- All other test fixtures' LLM mock keys synchronized with new prompt
versions; non-mock `inducedBy` audit fields kept at v1 by design.
---------
Co-authored-by: tyh <3211345556@qq.com>
Co-authored-by: jiang <fdjzy@qq.com>
Co-authored-by: Jiang <33757498+hijzy@users.noreply.github.com>
…sing (#1533) * feat: add .env.example-full and fix .env.example * feat(memos-local-plugin): v2.0 full rewrite with Reflect2Evolve architecture Complete end-to-end rewrite of the memos-local-plugin package into a layered, agent-agnostic memory runtime with support for both OpenClaw and Hermes adapters. Highlights: - New `core/` package (agent-agnostic): capture, embedding, feedback, hub, LLM client, logger, memory (L1/L2/L3), pipeline, reward, recall, retrieval, skill, session, storage, config modules — each with its own README + ALGORITHMS notes. - New `adapters/` layer with `openclaw/` and `hermes/` integrations isolated from core. Agent-specific concepts (turns, installers, bridge clients) live only here. - New `agent-contract/` — single shared contract (dto, errors, events, jsonrpc, log-record, memory-core) between core and adapters. - New `bridge/` — JSON-RPC stdio bridge (methods.ts, stdio.ts). - New `server/` — HTTP/SSE server for the viewer. - New `site/` — Vite-built public product site + release notes index. - New `web/` — Vite-built viewer app with memory/skill/timeline/world model views. - New `docs/` — ALGORITHM, DATA-MODEL, LOGGING, MANUAL_E2E_TESTING, Reflect2Skill design core, multi-agent viewer, etc. - New `tests/` — vitest unit/integration + python bridge tests. - Tooling: TypeScript multi-project build (tsconfig.{json,site,web}), Vite + Vitest, cross-platform install.sh / install.ps1, npm release checker, package-lock committed. - Removes legacy `src/` and `www/` structure from main branch; the new layout replaces it entirely. This change is fully scoped to apps/memos-local-plugin/ and does not touch any other package. * style(memos-local-plugin): apply ruff check + format to Python files - Remove unused imports (Iterable, Dict, List) in memos_provider/__init__.py - Move Callable into TYPE_CHECKING block in bridge_client.py - Replace try/except/pass with contextlib.suppress in bridge_client.py - Combine nested if in test_bridge_client.py - Apply ruff format to 4 Python files (hermes adapter + tests) All files now pass `ruff check` and `ruff format --check`. * feat(memos-local-plugin): preserve mid-turn reasoning + retrieval improvements Capture path (thinking-between-tool-calls): - Adapter extractTurn now flushes thinking + assistant-text that appears between consecutive tool calls into the next ToolCallDTO's `thinkingBefore`, preserving the model's natural-language bridge (e.g. "nproc failed, let me try sysctl") in the trace. - Adapter flattenMessages: when pi-ai `content[toolCall]` coexists with legacy top-level `tool_calls`, skip the legacy path so each call is emitted once (prior double-push clobbered the first stub's `thinkingBefore` via pendingCalls.set, making the field silently go missing and doubling tool-call rows in the DB). - Orchestrator: tool turns now persist `thinkingBefore` in EpisodeTurn.meta so the capture step-extractor can re-attach it. - Step extractor: only the first tool sub-step carries `userText`; subsequent sub-steps leave it empty so the viewer's flattenChat doesn't render the same user bubble N times. - Step extractor: `toolCallFromTurn` + `coerceToolCall` now read `thinkingBefore` back from meta. - Normalizer: sub-step candidates skip the generic dedup path — their intentionally-identical empty userText/agentText plus 1-tool shape used to collapse two distinct tools into one whenever their input prefixes matched under 200 chars. - Agent contract DTO: `ToolCallDTO.thinkingBefore?: string` added; no schema migration needed (stored inside `tool_calls_json`). - Web flattenChat: renders per-tool `thinkingBefore` bubbles before each tool call for the user↔agent timeline; retains legacy `agentThinking` single-bubble fallback for pure-reply traces. Retrieval path: - LLM-filter: refactored prompt templates and schema shape. - Ranker: reworked scoring with new blend knobs. - Retrieve + pipeline wiring updated to match the new types. - Config defaults + schema expose the new retrieval knobs. - Viewer LogsView surfaces new filter fields; i18n updated. Tests: - New regression tests for extractTurn interleaved thinking, pi-ai + OpenAI-legacy double-push avoidance, and flattenChat sub-step rendering. - Retrieval / llm-filter / ranker tests updated for the new shape. * feat(memos-local-plugin): one-round-one-card UI + language-aware knowledge + L2/L3 boundary prompts UI: one user turn = one memory card - New `traces.turn_id INTEGER` column (migration 013) stamped by `step-extractor` with the user turn's ts; every sub-step of the same user message shares the same turnId. - `MemoryGroup` aggregation in `web/src/views/MemoriesView.tsx` collapses rows by (episodeId, turnId): one card per turn, role pill chosen by group-level rule (any tool → "tool"), aggregate V/α displayed as the member-row mean. - Drawer rewritten as `<StepList>`: every member step renders as a collapsible <details> block with its own ts / V / α / agentThinking / toolCalls / reflection. First step expanded, rest collapsed so a 10-tool turn doesn't drown the user. - Bulk actions (select / delete / share / export) operate on whole cards: card checkbox toggles the full set of member ids; delete / share / export bulk over `g.ids` so a card never half-disappears. - Algorithm layer untouched — every L1 trace stays step-level so V/α reflection-weighted backprop, L2 incremental association, Tier-2 error-signature retrieval, and Decision Repair keep their per-step granularity (V7 §0.1). Per-tool reasoning capture (carryover, see PR #1515) - ToolCallDTO carries `value` / `reflection` / `thinkingBefore` so the drawer's per-step section can show the per-tool intermediate thinking and any LLM-assigned per-tool score without a schema change. - StepCandidate.meta.turnId / subStep / subStepIdx / subStepTotal threaded through capture.ts → traces.turn_id; `pickTurnId` falls back to the trace's own ts so old fixtures still produce singleton groups instead of crashing. Knowledge generation in user's language - `core/llm/prompts/index.ts` adds `detectDominantLanguage(samples, {minSignal})` — counts CJK ideographs + ASCII letters and returns "zh" / "en" / "auto" (allocation-free, runs on every gen call). - All five knowledge-generation sites now emit a `languageSteeringLine` system message keyed off their evidence: * core/capture/alpha-scorer.ts ← reflection-quality reason * core/capture/batch-scorer.ts ← per-step batch reflections * core/memory/l2/induce.ts ← L2 policy fields * core/memory/l3/abstract.ts ← L3 (ℰ, ℐ, C) bullets * core/skill/crystallize.ts ← skill body + scope - Effect: a Chinese-speaking user no longer gets a half-English skill card. An English user no longer gets a 中文-mixed reflection. L2 / L3 prompts: hard boundary against drift - `L2_INDUCTION_PROMPT` v1 → v2: explicit "what NOT to write" guard rejects environment topology, declarative behavioural rules, and generic taboos. New same-fact-two-framings example shows how to re-fold an env fact into a state-level trigger or step-level caveat. - `L3_ABSTRACTION_PROMPT` v1 → v2: bans imperative verbs (do/should/use/ install/run) under any of ℰ/ℐ/C; reworked all three example sets to pure declarative ("loading a glibc-linked binary wheel inside Alpine raises a dynamic-link error" instead of "if pip fails, install dev libs and retry"). Same-fact contrast example included. - Test mock keys updated v1 → v2 in induce.test.ts / l2.integration.test.ts / openclaw-full-chain.test.ts / v7-full-chain.e2e.test.ts. Historical `inducedBy` audit strings intentionally left at v1 — they're metadata recording the prompt version a row was generated under, not call-time keys. Retrieval injector: heading hierarchy - `# User's conversation history (from memory system)` is now H1, with `## Memories` / `## Skills` / `## Environment Knowledge` as H2 so the injected block has a clean outline in the LLM's context (previously the inner sections used H1 too, breaking the visual hierarchy). Migration runner: SQLite defensive mode - better-sqlite3 ≥ v11 enables `SQLITE_DBCONFIG_DEFENSIVE` which blocks writes to `sqlite_master` even with `PRAGMA writable_schema=ON`. Migration 012 (status unification) needs that pragma to swap CHECK constraints in-place. `runMigrations` now flips `db.raw.unsafeMode` on at the outer boundary if any pending migration uses `writable_schema`, then off again in `finally`. Migrations are shipped with the plugin (never user input) so this is safe. - Migration 012 SQL itself rewritten to use single-quote string literals with doubled inner quotes (instead of double quotes that better-sqlite3 strict mode treats as identifiers). Documentation - New `docs/GRANULARITY-AND-MEMORY-LAYERS.md` — mental-model alignment doc explaining: 小步/轮/任务 三个粒度的关系、打分粒度（每步 α/V， 每任务 R_human，"轮"无独立分）、检索粒度（技能/单步/子任务序列/ 环境认知，没有"按轮"召回）、生成链路（小步→经验→环境认知→技能）、 以及 §6 "经验 vs 环境认知 边界裁剪" 章节回答"该不该合并"问题：7 条 反对合并的理由 + 三种折中方案对比 + 同事实多框架对照判别表。 - `docs/Reflect2Skill_算法设计核心.md` 头部加阅读顺序提示，引导新人 先看上面那篇粒度对齐文档。 - `docs/README.md` 索引同步更新，标粗 GRANULARITY-AND-MEMORY-LAYERS。 Tests - `tests/unit/capture/step-extractor.test.ts`: turnId stability assertions across sub-steps; multi-tool turn shares one turnId. - All other test fixtures' LLM mock keys synchronized with new prompt versions; non-mock `inducedBy` audit fields kept at v1 by design. * feat: port plugin system from enterprise branch Bring the plugin runtime, API bootstrap integration, and related tests from aliyun-ee/dev-20260423-v2.0.14.post onto upstream/main so the upstream branch can review the plugin architecture independently of the broader enterprise history. Made-with: Cursor * fix: working binding related bug --------- Co-authored-by: tyh <3211345556@qq.com> Co-authored-by: jiang <fdjzy@qq.com> Co-authored-by: Jiang <33757498+hijzy@users.noreply.github.com>
…1526) * feat: add .env.example-full and fix .env.example * feat(memos-local-plugin): v2.0 full rewrite with Reflect2Evolve architecture Complete end-to-end rewrite of the memos-local-plugin package into a layered, agent-agnostic memory runtime with support for both OpenClaw and Hermes adapters. Highlights: - New `core/` package (agent-agnostic): capture, embedding, feedback, hub, LLM client, logger, memory (L1/L2/L3), pipeline, reward, recall, retrieval, skill, session, storage, config modules — each with its own README + ALGORITHMS notes. - New `adapters/` layer with `openclaw/` and `hermes/` integrations isolated from core. Agent-specific concepts (turns, installers, bridge clients) live only here. - New `agent-contract/` — single shared contract (dto, errors, events, jsonrpc, log-record, memory-core) between core and adapters. - New `bridge/` — JSON-RPC stdio bridge (methods.ts, stdio.ts). - New `server/` — HTTP/SSE server for the viewer. - New `site/` — Vite-built public product site + release notes index. - New `web/` — Vite-built viewer app with memory/skill/timeline/world model views. - New `docs/` — ALGORITHM, DATA-MODEL, LOGGING, MANUAL_E2E_TESTING, Reflect2Skill design core, multi-agent viewer, etc. - New `tests/` — vitest unit/integration + python bridge tests. - Tooling: TypeScript multi-project build (tsconfig.{json,site,web}), Vite + Vitest, cross-platform install.sh / install.ps1, npm release checker, package-lock committed. - Removes legacy `src/` and `www/` structure from main branch; the new layout replaces it entirely. This change is fully scoped to apps/memos-local-plugin/ and does not touch any other package. * style(memos-local-plugin): apply ruff check + format to Python files - Remove unused imports (Iterable, Dict, List) in memos_provider/__init__.py - Move Callable into TYPE_CHECKING block in bridge_client.py - Replace try/except/pass with contextlib.suppress in bridge_client.py - Combine nested if in test_bridge_client.py - Apply ruff format to 4 Python files (hermes adapter + tests) All files now pass `ruff check` and `ruff format --check`. * feat(memos-local-plugin): preserve mid-turn reasoning + retrieval improvements Capture path (thinking-between-tool-calls): - Adapter extractTurn now flushes thinking + assistant-text that appears between consecutive tool calls into the next ToolCallDTO's `thinkingBefore`, preserving the model's natural-language bridge (e.g. "nproc failed, let me try sysctl") in the trace. - Adapter flattenMessages: when pi-ai `content[toolCall]` coexists with legacy top-level `tool_calls`, skip the legacy path so each call is emitted once (prior double-push clobbered the first stub's `thinkingBefore` via pendingCalls.set, making the field silently go missing and doubling tool-call rows in the DB). - Orchestrator: tool turns now persist `thinkingBefore` in EpisodeTurn.meta so the capture step-extractor can re-attach it. - Step extractor: only the first tool sub-step carries `userText`; subsequent sub-steps leave it empty so the viewer's flattenChat doesn't render the same user bubble N times. - Step extractor: `toolCallFromTurn` + `coerceToolCall` now read `thinkingBefore` back from meta. - Normalizer: sub-step candidates skip the generic dedup path — their intentionally-identical empty userText/agentText plus 1-tool shape used to collapse two distinct tools into one whenever their input prefixes matched under 200 chars. - Agent contract DTO: `ToolCallDTO.thinkingBefore?: string` added; no schema migration needed (stored inside `tool_calls_json`). - Web flattenChat: renders per-tool `thinkingBefore` bubbles before each tool call for the user↔agent timeline; retains legacy `agentThinking` single-bubble fallback for pure-reply traces. Retrieval path: - LLM-filter: refactored prompt templates and schema shape. - Ranker: reworked scoring with new blend knobs. - Retrieve + pipeline wiring updated to match the new types. - Config defaults + schema expose the new retrieval knobs. - Viewer LogsView surfaces new filter fields; i18n updated. Tests: - New regression tests for extractTurn interleaved thinking, pi-ai + OpenAI-legacy double-push avoidance, and flattenChat sub-step rendering. - Retrieval / llm-filter / ranker tests updated for the new shape. * feat(memos-local-plugin): one-round-one-card UI + language-aware knowledge + L2/L3 boundary prompts UI: one user turn = one memory card - New `traces.turn_id INTEGER` column (migration 013) stamped by `step-extractor` with the user turn's ts; every sub-step of the same user message shares the same turnId. - `MemoryGroup` aggregation in `web/src/views/MemoriesView.tsx` collapses rows by (episodeId, turnId): one card per turn, role pill chosen by group-level rule (any tool → "tool"), aggregate V/α displayed as the member-row mean. - Drawer rewritten as `<StepList>`: every member step renders as a collapsible <details> block with its own ts / V / α / agentThinking / toolCalls / reflection. First step expanded, rest collapsed so a 10-tool turn doesn't drown the user. - Bulk actions (select / delete / share / export) operate on whole cards: card checkbox toggles the full set of member ids; delete / share / export bulk over `g.ids` so a card never half-disappears. - Algorithm layer untouched — every L1 trace stays step-level so V/α reflection-weighted backprop, L2 incremental association, Tier-2 error-signature retrieval, and Decision Repair keep their per-step granularity (V7 §0.1). Per-tool reasoning capture (carryover, see PR #1515) - ToolCallDTO carries `value` / `reflection` / `thinkingBefore` so the drawer's per-step section can show the per-tool intermediate thinking and any LLM-assigned per-tool score without a schema change. - StepCandidate.meta.turnId / subStep / subStepIdx / subStepTotal threaded through capture.ts → traces.turn_id; `pickTurnId` falls back to the trace's own ts so old fixtures still produce singleton groups instead of crashing. Knowledge generation in user's language - `core/llm/prompts/index.ts` adds `detectDominantLanguage(samples, {minSignal})` — counts CJK ideographs + ASCII letters and returns "zh" / "en" / "auto" (allocation-free, runs on every gen call). - All five knowledge-generation sites now emit a `languageSteeringLine` system message keyed off their evidence: * core/capture/alpha-scorer.ts ← reflection-quality reason * core/capture/batch-scorer.ts ← per-step batch reflections * core/memory/l2/induce.ts ← L2 policy fields * core/memory/l3/abstract.ts ← L3 (ℰ, ℐ, C) bullets * core/skill/crystallize.ts ← skill body + scope - Effect: a Chinese-speaking user no longer gets a half-English skill card. An English user no longer gets a 中文-mixed reflection. L2 / L3 prompts: hard boundary against drift - `L2_INDUCTION_PROMPT` v1 → v2: explicit "what NOT to write" guard rejects environment topology, declarative behavioural rules, and generic taboos. New same-fact-two-framings example shows how to re-fold an env fact into a state-level trigger or step-level caveat. - `L3_ABSTRACTION_PROMPT` v1 → v2: bans imperative verbs (do/should/use/ install/run) under any of ℰ/ℐ/C; reworked all three example sets to pure declarative ("loading a glibc-linked binary wheel inside Alpine raises a dynamic-link error" instead of "if pip fails, install dev libs and retry"). Same-fact contrast example included. - Test mock keys updated v1 → v2 in induce.test.ts / l2.integration.test.ts / openclaw-full-chain.test.ts / v7-full-chain.e2e.test.ts. Historical `inducedBy` audit strings intentionally left at v1 — they're metadata recording the prompt version a row was generated under, not call-time keys. Retrieval injector: heading hierarchy - `# User's conversation history (from memory system)` is now H1, with `## Memories` / `## Skills` / `## Environment Knowledge` as H2 so the injected block has a clean outline in the LLM's context (previously the inner sections used H1 too, breaking the visual hierarchy). Migration runner: SQLite defensive mode - better-sqlite3 ≥ v11 enables `SQLITE_DBCONFIG_DEFENSIVE` which blocks writes to `sqlite_master` even with `PRAGMA writable_schema=ON`. Migration 012 (status unification) needs that pragma to swap CHECK constraints in-place. `runMigrations` now flips `db.raw.unsafeMode` on at the outer boundary if any pending migration uses `writable_schema`, then off again in `finally`. Migrations are shipped with the plugin (never user input) so this is safe. - Migration 012 SQL itself rewritten to use single-quote string literals with doubled inner quotes (instead of double quotes that better-sqlite3 strict mode treats as identifiers). Documentation - New `docs/GRANULARITY-AND-MEMORY-LAYERS.md` — mental-model alignment doc explaining: 小步/轮/任务 三个粒度的关系、打分粒度（每步 α/V， 每任务 R_human，"轮"无独立分）、检索粒度（技能/单步/子任务序列/ 环境认知，没有"按轮"召回）、生成链路（小步→经验→环境认知→技能）、 以及 §6 "经验 vs 环境认知 边界裁剪" 章节回答"该不该合并"问题：7 条 反对合并的理由 + 三种折中方案对比 + 同事实多框架对照判别表。 - `docs/Reflect2Skill_算法设计核心.md` 头部加阅读顺序提示，引导新人 先看上面那篇粒度对齐文档。 - `docs/README.md` 索引同步更新，标粗 GRANULARITY-AND-MEMORY-LAYERS。 Tests - `tests/unit/capture/step-extractor.test.ts`: turnId stability assertions across sub-steps; multi-tool turn shares one turnId. - All other test fixtures' LLM mock keys synchronized with new prompt versions; non-mock `inducedBy` audit fields kept at v1 by design. * fix(format_utils): raise ValueError on None in clean_json_response clean_json_response treats its argument as a str and unconditionally calls .replace(). When an upstream LLM helper returns None (e.g. due to the silent-fail pattern in timed_with_status), the resulting AttributeError points to format_utils.py rather than to the failed LLM call, which is hard to diagnose. Add an explicit None check that raises a descriptive ValueError. This turns the symptom 'NoneType has no attribute replace' into a message that names the actual root cause. --------- Co-authored-by: tyh <3211345556@qq.com> Co-authored-by: CaralHsi <caralhsi@gmail.com> Co-authored-by: jiang <fdjzy@qq.com> Co-authored-by: Jiang <33757498+hijzy@users.noreply.github.com> Co-authored-by: auctor <auctor@xinfty.space>
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