* docs: update ReMe documentation URL * docs: localize ReMe Studio social image * docs(AGENTS): update agent guidelines and repository documentation structure - Clarify coding agent guidance for keeping changes small and consistent - Revise project principle descriptions for clarity and modern terminology - Expand repository map with detailed component and folder explanations - Add configuration and CLI usage instructions, including syntax and merging rules - Elaborate on component, step registration, and application lifecycle processes - Define jobs, steps, and state handling conventions for stateless design - Specify workspace and file safety policies, including path restrictions and locking - Update validation commands and testing environment recommendations - Clarify coding and test conventions, including style and dependency policies - Distinguish documentation boundaries and update website content contribution notes - Reinforce change guardrails to avoid breaking backward compatibility and data loss - Improve svg diagram formatting and textual details in auto dream and proactive flow image * style(docs): fix font-family syntax in SVG style definitions - Correct quotation marks around font-family names in memory-as-file.svg - Standardize font-family formatting by removing unnecessary quotes in reme-blog-architecture.svg - Ensure consistent CSS style formatting within SVG files for better rendering fidelity * docs: add ReMe blog to news * style(docs): inline svg styles and improve text formatting - Convert multiline SVG style tags into single-line for compactness in multiple figures - Remove redundant line breaks in subtitle text elements for consistency - Shorten descriptive texts in SVG figures for clarity and conciseness - Adjust font sizes and text for better readability in SVG elements - Correct whitespace issues in Chinese markdown document for improved formatting - Remove unused style blocks from framework structure SVG for cleaner code
10 KiB
Auto Dream
auto_dream is ReMe's long-term memory distillation flow from daily to digest. By default it scans the target date and
the previous day, processes only files changed since the previous dream, extracts a small set of high-value memory units
across that window, integrates them into digest/, and writes the target day's interests.yaml for proactive use.
Its daily inputs usually come from Auto Memory and Auto Resource. For the file
semantics of digest/, Sources sections, and wikilinks, see Memory as File. For the linking
strategy used during Integrate, see Auto Link. To read interests.yaml,
use Proactive.
Configuration
The default configuration is in reme/config/default.yaml:
auto_dream:
backend: base
parameters:
date:
type: string
default: ""
hint:
type: string
default: ""
scan_days:
type: integer
default: 2
max_units:
type: integer
default: 5
topic_count:
type: integer
default: 3
topic_diversity_days:
type: integer
default: 7
steps:
- backend: dream_extract_step
file_catalog: dream
topic_session_id: interests
scan_days: 2
max_units: 5
- backend: dream_integrate_step
- backend: dream_topics_step
topic_count: 3
topic_diversity_days: 7
- backend: dream_finish_step
file_catalog: dream
Parameters:
| Parameter | Purpose |
|---|---|
date |
Date to process in YYYY-MM-DD format. When empty, use today in the application's timezone. |
hint |
Additional guidance from the caller for the Extract and Integrate stages. |
scan_days |
Recent-date window ending at date; defaults to 2 and has a minimum of 1. |
max_units |
Maximum reusable units extracted in one run; defaults to 5. |
topic_count |
Maximum number of topics written to interests.yaml. Defaults to 3. |
topic_diversity_days |
Number of past days of interests.yaml files considered when avoiding duplicate topics. Defaults to 7. |
Inputs and Outputs
Inputs are daily Markdown files from the most recent scan_days ending at the specified date. For example,
date=2026-06-20 with scan_days=2 scans:
daily/2026-06-19.md
daily/2026-06-19/**/*.md
daily/2026-06-20.md
daily/2026-06-20/**/*.md
Every daily/<date>/interests.yaml in the scan window is excluded from extraction so previous proactive output cannot
feed back into the next run. Final topics are written only for the target date.
The main outputs are:
| Output | Description |
|---|---|
digest/procedure/*.md |
Methods, workflows, runbooks, and executable experience. |
digest/personal/*.md |
User-, team-, and project-related preferences, facts, and long-term context. |
digest/wiki/*.md |
General knowledge, concepts, observations, and decision precedents. |
daily/<date>/interests.yaml |
Topics worth proactive attention from the host agent that day. |
metadata/file_catalog/dream* |
Dream-specific catalog used to detect changes in daily inputs. |
Four Stages
1. Extract
dream_extract_step performs three tasks:
- Refresh each
daily/<date>.mdin the scan window. - Scan those day indexes and
daily/<date>/**/*.md, comparing mtimes withfile_catalog: dream. - Send all changed files together to the LLM and globally extract two structured result types:
unitsandtopics.
units are long-term memory units ready to be distilled into digest. Each has name, bucket, summary, and paths.
A run returns at most max_units; extraction merges cross-file evidence for the same abstraction and drops passing
mentions, per-file summaries, and weak candidates without reusable value. bucket may only be procedure, personal,
or wiki; unknown values are routed to wiki.
topics are proactive-interest candidates for the day. They contain title, reason, evidence, keywords, and
paths and are filtered again in the Topics stage.
If there are no changed files, Extract succeeds with no units; Integrate then has no unit work, Topics preserves any existing target-day topics, and Finish still performs its normal catalog summary. If files changed but no LLM is configured, Extract fails because extraction requires an LLM.
2. Integrate
dream_integrate_step invokes an agent independently for each unit and integrates that unit into one digest node. It
exposes these tools to the agent:
node_search, read, frontmatter_read, write, edit, frontmatter_update
This stage carries the core responsibility of auto_link. It first uses node_search to recall similar or related
nodes at digest-node granularity, decides whether to create or update a node, and finally writes sources and related
digest nodes as wikilinks. See Auto Link for the recall, deduplication, and edge-writing rules.
Extract is the gate for deciding whether material is worth remembering, so Integrate has no SKIP action: each admitted
unit must land in exactly one digest node. Creates and updates must retain provenance and weave related digest links
into contextual sentences; bare wikilinks and standalone relationship fields are not valid output.
There are four integration actions:
| Action | Meaning |
|---|---|
CREATE |
No equivalent abstraction exists; create a new digest node. |
CORROBORATE |
The same memory appeared again; append a source or strengthen the description. |
REFINE |
New material adds boundaries, steps, prerequisites, applicability, or detail. |
CORRECT |
New material corrects errors, omissions, or conflicts in the existing node. |
Successfully integrated units are recorded in integrate_results. Failed units enter failed_units, and their source
paths enter failed_paths. The Finish stage does not checkpoint failed paths, ensuring that they can be retried later.
3. Topics
dream_topics_step turns topic candidates from Extract into the final daily/<date>/interests.yaml for the day.
It reads:
daily/<date>/interests.yaml
daily/<each of the previous topic_diversity_days dates>/interests.yaml
Existing topics from the same day are preserved, while similar topics from the previous topic_diversity_days days are
deduplicated. At most three topics are written by default. With an LLM configured, the LLM selects topics that are more
specific, actionable, and non-repetitive. Without an LLM, the step falls back to local normalization and deduplication.
Example output format. See Proactive for the interface that reads this file:
date: 2026-06-20
topic_count: 3
diversity_days: 7
topics:
- title: Quality regression in the memory retrieval pipeline
reason: The user has recently made repeated changes to search, node_search, and dream integration.
evidence: daily/2026-06-20/session.md
keywords:
- memory search
- auto dream
paths:
- daily/2026-06-20/session.md
4. Finish
dream_finish_step completes the run:
- Write successfully processed changed paths to
file_catalog: dream. - Also write the target
daily/<date>/interests.yamland every refreshed day-index page in the scan window to the catalog. - Persist the dream catalog if there were upserts or deletions.
- Return a summary containing counts for scanned, changed, integrated, topics, checkpoints, and related values.
Failed paths are not checkpointed. The next auto_dream run therefore continues to treat them as changed inputs until
integration succeeds.
Running Auto Dream
CLI:
reme auto_dream date=2026-06-20
With caller guidance:
reme auto_dream date=2026-06-20 hint="Prioritize engineering decisions and long-term preferences"
Override the default scan window and unit cap:
reme auto_dream date=2026-06-20 scan_days=3 max_units=8
The same set of steps can also be placed in a cron Job, for example to run every morning:
jobs:
daily_auto_dream:
backend: cron
cron: "30 3 * * *"
steps:
- backend: dream_extract_step
file_catalog: dream
- backend: dream_integrate_step
- backend: dream_topics_step
- backend: dream_finish_step
file_catalog: dream
Important Boundaries
auto_dream consumes only daily inputs and does not rewrite daily bodies. Daily preserves facts and the original
situation; digest is the abstracted long-term memory layer.
digest is not a copy of the source text. Its body should preserve reusable abstractions, while a Sources section
points back with contextual sentences such as The decision was recorded in [[daily/<date>/decision.md]]. Links follow
the workspace-relative wikilink semantics described in
Memory as File.
auto_dream does not invent an overview from nothing. Only content that actually appears in daily input and is
extracted as a unit or topic can enter digest or interests.yaml.
The complete flow depends on an LLM for Extract and Integrate. Topics can perform local deduplication without an LLM, but that does not mean the full dream flow can run offline.