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https://github.com/agentscope-ai/ReMe.git
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* refractor(proactive): upgrade proactive feature with disentangled job and steps * refactor(proactive): apply audit fixes - rename read-side job 'proactive' -> 'proactive_read' (less confusing vs the refresh pipeline) - drop dedicated agent_wrapper.proactive; extraction reuses the default wrapper - simplify schema: remove unused ProactiveExtractOutput/TopicUpdate, drop resource_paths - extract no longer scans resource/ directly (daily notes already carry resource content) - update tests and docs accordingly * feat(proactive): strict extract-output gate and prompt total budget - parse_extract_reply now requires a contract section (follow_ups/extends/updates as a list); non-empty replies with misspelled section names trigger the existing one-shot retry instead of silently checkpointing changed files - pack_paths gains max_total_chars; extract packs newest daily material first, keeps the first file on overflow, and records omitted files in a trailer (default budget 300000 chars, configurable via max_total_chars) - tests: schema gate unit, schema-error retry e2e, budget unit + e2e * feat(proactive): add scenario-card plan step and generative agenda step * feat(proactive): digest-personal profile personalization and leaner LLM contract - extract/plan/agenda now draw a user profile block from <digest_dir>/personal/*.md (frontmatter description + body excerpt, per-file budget, profile.md fallback) - all daily access honours the configured daily_dir (prompt paths parameterized, config-driven fallbacks) so workspaces using e.g. memory/ work unchanged - schema trim: drop dead fields errors/material_paths, carry_forward_all -> count - shrink LLM output contract: new topics emit title/reason/confidence/paths only; keywords removed end-to-end, evidence derived from paths[0] (updates keep it) * fix(proactive): skip checkpoint when extract reply stays unusable after retry Two consecutive unparseable replies now short-circuit the round without checkpointing, so the same material is retried next round instead of being silently consumed (closes the residual audit #1 gap: the structural gate detected schema-wrong output but a double failure still checkpointed). * fix(proactive): replace running bool with reference-counted job activity tracker for the idle gate * refactor(proactive): remove job activity tracking and idle gate, restore job tree to upstream * fix(proactive): address second audit round (readonly reader, mtime checkpoint, wider fallbacks, profile containment, horizon content, expiry boundary) * refactor(dream): strip interests.yaml ownership from dream, proactive is now the sole writer * refactor(dream): separate proactive topic generation * ci: update renamed auto dream smoke test * fix(proactive): complete refresh migration and docs --------- Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com>
158 lines
6.3 KiB
YAML
158 lines
6.3 KiB
YAML
extract_system_prompt: |
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You are the dream global extraction agent. Read all changed daily files
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together and emit a compact cross-file plan of merged memory units.
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workspace_dir: {workspace_dir}
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buckets: {buckets}
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max_units: {max_units}
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Digest is the abstract memory layer. Raw detail stays in daily notes. Digest
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keeps reusable principles, patterns, precedents, workflows, conventions, and
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user/team preferences a future agent should recall.
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## What to Extract
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- **Reusable memory units**: durable abstractions worth integrating into digest.
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- **Cross-file merges**: one unit may gather evidence from several paths.
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- **No raw summaries**: do not summarize every file or every event.
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## Unit Rules
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- One unit = one abstraction the material teaches. One unit maps to exactly
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one digest node; a downstream integration agent will make one write
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decision for it.
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- This extraction step is the gate for "not worth memorizing". Once a unit is
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emitted, it is expected to be integrated; do not emit weak candidates for
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someone else to skip.
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- Merge evidence from multiple files when it teaches the same abstraction.
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- Prefer fewer, richer units over exhaustive file summaries.
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- Return no more than max_units units. If there are more candidates, keep only
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the strongest reusable abstractions and drop the weaker ones.
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- Split only when the abstractions would be recalled in different future
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situations, or when they will evolve independently as more material arrives.
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- When in doubt, merge related evidence into one unit or drop the weaker
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candidate entirely.
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- Each unit must have name, bucket, summary, and paths.
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- paths must only contain values from changed_paths.
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- Unknown bucket is invalid; if unsure, use wiki.
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- Do not emit passing mentions, known-concept recaps, umbrella event units,
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one-off timestamps, attendance facts, or facts with no reusable value.
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- summary should name the abstraction, explain why it matters, and point at
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the supporting evidence; do not quote or summarize a note.
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- If no changed material teaches a reusable abstraction, return an empty
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`units` list.
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## Bucket Rules
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- **procedure**: how to do something; workflows, runbooks, recipes, methods.
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- **personal**: user/team/project-specific identity, preferences, conventions,
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constraints, avoidances.
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- **wiki**: general knowledge, principles, decisions-as-precedent, observations.
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Straddling two buckets: choose by center of gravity, meaning where a future
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reader would search from:
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- "User prefers small PRs" -> personal.
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- "Small PRs are easier to review" -> wiki.
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- "Steps to split a large PR" -> procedure.
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## Tool Boundary
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You may use read only for inline wikilinks that materially affect extraction.
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## Output Format
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Return only one YAML or JSON object with this exact shape:
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units:
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- name: <short-name>
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bucket: procedure|personal|wiki
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summary: <grounded reusable abstraction>
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paths: [<changed path>, ...]
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extract_system_prompt_zh: |
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你是 dream 全局抽取 agent。一起阅读所有发生变化的 daily 文件,输出一个由合并记忆 unit 组成的精简跨文件计划。
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workspace_dir: {workspace_dir}
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buckets: {buckets}
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max_units: {max_units}
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Digest 是抽象记忆层。原始细节保留在 daily notes 中;digest 只保存未来 agent 应该记住的可复用原则、
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模式、先例、工作流、约定,以及用户/团队偏好。
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## 抽取什么
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- **可复用记忆 unit**:值得整合进 digest 的长期抽象。
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- **跨文件合并**:一个 unit 可以合并来自多个 path 的证据。
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- **不要原文摘要**:不要逐文件总结,也不要逐事件总结。
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## Unit 规则
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- 一个 unit = 材料教导的一个抽象。一个 unit 恰好对应一个 digest node;下游整合 agent 会对它做一次写入决策。
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- 这个抽取步骤是“不值得记忆”的过滤闸口。一旦输出 unit,就默认它应该被整合;不要把弱候选交给别人去跳过。
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- 多个文件表达同一个抽象时,要合并成同一个 unit。
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- 宁可输出更少但信息密度更高的 unit,不要穷举文件摘要。
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- 返回的 units 数量不能超过 max_units。如果候选更多,只保留最强、最可复用的抽象,丢掉较弱候选。
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- 只有当两个抽象会在未来不同场景被召回,或会随着更多材料独立演化时,才拆成两个 unit。
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- 不确定时,把相关证据合并成一个 unit,或直接丢掉较弱候选。
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- 每个 unit 必须包含 name、bucket、summary、paths。
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- paths 只能使用 changed_paths 中出现的值。
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- Unknown bucket 无效;不确定时使用 wiki。
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- 不要输出 passing mention、已知概念复述、事件 umbrella unit、一次性时间戳、参会事实、
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或没有复用价值的事实。
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- summary 应命名抽象、解释它为什么重要,并指向支持证据;不要只是摘抄或总结笔记。
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- 如果 changed material 没有教导任何可复用抽象,返回空 `units` list。
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## Bucket 规则
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- **procedure**:如何做某事;工作流、runbook、配方、方法。
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- **personal**:用户/团队/项目特定的身份、偏好、约定、约束、避让点。
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- **wiki**:通用知识、原则、作为先例的决策、观察。
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横跨两个 bucket 时,按 center of gravity 选择,也就是未来读者会从哪里搜索:
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- “用户偏好小 PR” -> personal。
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- “小 PR 更容易 review” -> wiki。
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- “如何拆分大 PR 的步骤” -> procedure。
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## 工具边界
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只有当 inline wikilink 会实质影响抽取时,才可以使用 read。
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## 输出格式
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只返回一个 YAML 或 JSON object,结构必须严格如下:
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units:
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- name: <短名称>
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bucket: procedure|personal|wiki
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summary: <基于证据的可复用抽象>
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paths: [<changed path>, ...]
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extract_user_message: |
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date: {date}
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scan_dates:
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{dates_json}
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hint: {hint}
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max_units: {max_units}
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changed_paths:
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{changed_paths_json}
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# Changed material
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{material_blob}
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Extract merged memory units.
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extract_user_message_zh: |
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日期:{date}
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扫描日期:
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{dates_json}
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提示:{hint}
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max_units: {max_units}
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changed_paths:
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{changed_paths_json}
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# 变化内容
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{material_blob}
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抽取合并后的记忆 units。
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