* 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>
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| title | description |
|---|---|
| Configuration | ReMe configuration files, environment expansion, command-line overrides, and core components. |
Configuration
ReMe uses YAML or JSON to describe its Service, Jobs, and Components. The built-in default is reme/config/default.yaml. Select another configuration at startup and apply command-line overrides when needed.
Precedence
Configuration is merged in this order, with later values winning:
application_defaultsfrom enabled plugins.- The selected file;
defaultis used when none is specified. - CLI dot-notation overrides.
reme start
reme start config=demo
reme start config=/absolute/path/to/app.yaml
reme start service.port=8181 workspace_dir=/data/reme
config accepts a built-in name or a .yaml, .yml, or .json file. Overrides are deep-merged, so changing service.port preserves sibling service settings.
CLI values
Arguments use key=value; leading - or -- is accepted:
reme start --service.port=8181 --service.web_enabled=false
Values support null, booleans, numbers, JSON arrays and objects, quoted JSON strings, and plain strings. Numeric-looking values with leading zeroes, such as 007, remain strings. Quote values such as "true" in JSON when they must remain strings.
Environment variables
Configuration recursively expands:
api_key: ${LLM_API_KEY}
base_url: ${LLM_BASE_URL:-https://example.com/v1}
${VAR} fails when undefined; ${VAR:-default} uses its fallback. ReMe also searches for .env from the command's working directory through at most five parents.
Keep secrets in .env or the process environment, never in committed configuration.
Application fields
| Field | Default | Purpose |
|---|---|---|
app_name |
ReMe |
Display name |
workspace_dir |
.reme |
User-owned workspace root, normalized to an absolute path |
metadata_dir |
metadata |
Rebuildable indexes, graphs, and catalogs |
session_dir |
session |
Agent sessions; standard transcripts use session/dialog |
mem_session_dir |
mem_session |
Agent-wrapper sessions and configuration |
resource_dir |
resource |
External resources |
daily_dir |
daily |
Daily memory |
digest_dir |
digest |
Consolidated long-term memory |
timezone |
Asia/Shanghai |
IANA timezone used for dates and cron jobs |
language |
empty | Default language for LLM interactions |
plugins |
[] |
Installed plugins enabled for this Application |
service |
HTTP | Service configuration |
jobs |
default Jobs | Job configurations by name |
components |
defaults | Components grouped by type and name |
session_dir must remain workspace-relative.
LLM
The default LLM uses an OpenAI-compatible interface:
components:
as_llm:
default:
backend: openai
model: qwen3.7-plus
context_size: 200000
credential:
api_key: ${LLM_API_KEY:-}
base_url: ${LLM_BASE_URL:-}
Built-in registrations include openai, anthropic, dashscope, deepseek, gemini, moonshot, ollama, and xai. Their detailed model fields follow the corresponding AgentScope wrappers.
File operations, BM25 search, wikilink traversal, and proactive_read do not require an LLM. Evolution workflows such
as auto_memory, auto_resource, auto_dream, and proactive refresh do.
Embeddings
Vector retrieval is disabled by default. Credentials alone do not enable it: configure as_embedding, embedding_store, and connect the store to file_store.
components:
as_embedding:
default:
backend: openai
model: text-embedding-v4
dimensions: 1024
credential:
api_key: ${EMBEDDING_API_KEY}
base_url: ${EMBEDDING_BASE_URL:-https://dashscope.aliyuncs.com/compatible-mode/v1}
embedding_store:
default:
backend: local
as_embedding: default
file_store:
default:
backend: local
embedding_store: default
keyword_index: default
file_graph: default
Rebuild the embedding index after changing the model or dimensions.
Service and Jobs
Minimal HTTP configuration:
service:
backend: http
host: 127.0.0.1
port: 2333
web_enabled: true
mcp_enabled: true
mcp_path: /mcp
A Job declares a backend, parameter schema, and ordered Steps:
jobs:
example:
backend: base
description: Example job
parameters:
type: object
properties:
text: { type: string }
required: [text]
steps:
- backend: example_step
Set enable_serve: false to keep a Job internal. Background and cron Jobs are never service-exposed.
Inspect the effective configuration
reme app_config
The result is the merged, validated configuration with secrets redacted. Use it when diagnosing plugin or override precedence. The authoritative contracts remain reme/schema/application_config.py and reme/config/default.yaml.