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* feat(dream): replace digester with abstraction-layer dreamer pipeline
Reframe digest as the abstract memory layer (details stay in the daily/
resource material; digest holds principles, patterns, precedents reachable
via derived_from provenance edges). Replaces the old digester with a
2-phase ReAct workflow + a daily-tick wrapper:
- Phase 1 (Dreamer extract): clusters material into orthogonal memory
sub-units; each sub-unit maps 1:1 to a digest node (no inner atom
enumeration). Biases toward fewer / richer sub-units.
- Phase 2 (Dreamer integrate per sub-unit): cross-bucket recall +
exactly one write decision (CREATE / UPDATE / SKIP); UPDATE shapes
surfaced explicitly (corroborate / refine / correct).
- CronDreamer: scans <daily_dir>/<today>.md + <daily_dir>/<today>/**
+ <resource_dir>/<today>/** and runs dream_one per file.
Write tools are proper subclasses of the canonical file_io WriteStep /
EditStep with only path-shape + bucket + E-1 edge-conservation rules
layered on top:
- DigestWriteStep(WriteStep): path = <digest_dir>/<bucket>/<slug>.md,
must-not-exist, schema mirrors `write` (path / name / description /
content) so frontmatter lands automatically.
- DigestEditStep(EditStep): body-only find-and-replace + must-exist +
E-1 conservation preflight (refuses if any outbound wikilink would
be dropped).
Configuration:
- Bucket vocabulary structured in code (tuple[{name, description}]);
prompt renders the heuristic block at runtime via {buckets}.
- digest_dir / daily_dir / resource_dir come from app config (not tool
params); prompts use {digest_dir} placeholder.
- BaseStep walks class MRO when loading prompts, so subclasses inherit
parent yaml without duplication.
Tooling: agentscope register_tool_function schemas now wrap in the
proper {"type":"function","function":{...}} envelope. OpenAIAsLLM
routes base_url through client_kwargs so non-default endpoints work.
Smoke: tests4/smoke/{_dreamer_fixture.py,test_dreamer_inproc.py,
test_dreamer_cli.sh} drive the end-to-end pipeline.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* refactor(dreamer): split long description string across multiple lines
* refactor(dream): remove hardcoded DEFAULT_DIGEST_DIR and use app_config
* docs(auto-cognition): add comprehensive design document for auto-cognition system
* refactor(steps): remove deprecated digest edit/write steps
* refactor(config): remove redundant LLM formatter backend configuration
* refactor(dreamer): improve code formatting and line breaks
* feat(auto-dream): implement three-bucket classification system for knowledge organization
* feat: rename dream_today step to auto-dream and refactor extraction logic
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# LLM (required for most flows)
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LLM_API_KEY=sk-xxxx
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LLM_BASE_URL=https://xxxx/v1
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LLM_MODEL_NAME=xxxx
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LLM_BACKEND=XXX
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#EMBEDDING_API_KEY=sk-xxxx
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#EMBEDDING_BASE_URL=https://xxxx/v1 |