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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.

ReMe Auto Dream and Proactive flow from daily to digest to proactive

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:

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:

ParameterPurpose
dateDate to process in YYYY-MM-DD format. When empty, use today in the application's timezone.
hintAdditional guidance from the caller for the Extract and Integrate stages.
scan_daysRecent-date window ending at date; defaults to 2 and has a minimum of 1.
max_unitsMaximum reusable units extracted in one run; defaults to 5.
topic_countMaximum number of topics written to interests.yaml. Defaults to 3.
topic_diversity_daysNumber 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:

text
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:

OutputDescription
digest/procedure/*.mdMethods, workflows, runbooks, and executable experience.
digest/personal/*.mdUser-, team-, and project-related preferences, facts, and long-term context.
digest/wiki/*.mdGeneral knowledge, concepts, observations, and decision precedents.
daily/<date>/interests.yamlTopics 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:

  1. Refresh each daily/<date>.md in the scan window.
  2. Scan those day indexes and daily/<date>/**/*.md, comparing mtimes with file_catalog: dream.
  3. Send all changed files together to the LLM and globally extract two structured result types: units and topics.

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:

text
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:

ActionMeaning
CREATENo equivalent abstraction exists; create a new digest node.
CORROBORATEThe same memory appeared again; append a source or strengthen the description.
REFINENew material adds boundaries, steps, prerequisites, applicability, or detail.
CORRECTNew 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:

text
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:

yaml
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:

  1. Write successfully processed changed paths to file_catalog: dream.
  2. Also write the target daily/<date>/interests.yaml and every refreshed day-index page in the scan window to the catalog.
  3. Persist the dream catalog if there were upserts or deletions.
  4. 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:

bash
reme auto_dream date=2026-06-20

With caller guidance:

bash
reme auto_dream date=2026-06-20 hint="Prioritize engineering decisions and long-term preferences"

Override the default scan window and unit cap:

bash
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:

yaml
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.

Released under the Apache-2.0 License.