Skip to content

v0.2.0 - Updated knowledge vault and portable local RAG

Choose a tag to compare

View all tags
@LLK-LL LLK-LL released this 26 Jun 09:21
v0.2.0
db2d167

v0.2.0 - Updated knowledge vault and portable local RAG

Self-Learning Library v0.2.0 refreshes the public knowledge vault with the latest rule-layer iteration and makes the retrieval scripts easier to run outside the original workstation.

What is upgraded

  • Updated the layered paper_writing_obsidian_vault through the 2026-06-26 iteration.
  • Added new SCI paper-structure rules for abstract, introduction, theory, numerical simulation, discussion, and conclusion sections.
  • Added mentor-derived SCI English translation and grammar rules as focused reusable notes instead of one large source note.
  • Added workflow-governance rules for mandatory lightweight RAG startup, RAG repair, script reuse before creating helpers, knowledge-base maintenance ownership, and skill-promotion review.
  • Refreshed supervision and no-regression notes for DOCX formula formatting, manuscript-body purity, chat-first Word insertion, and translation checks.
  • Added a local fallback retrieval path in tools/kb_rag.py so the repository can run without a private total-agent-memory checkout.
  • Made local paths configurable through environment variables instead of hard-coding one workstation layout.
  • Redacted public export artifacts that could expose local absolute paths or full private source text.

Advantages over v0.1.0

  • More complete rule coverage: v0.1.0 mainly demonstrated the harness shape; v0.2.0 includes a richer, iterated knowledge base with 96 change-log notes, 85 paper memories, 15 intermediate writing rules, 12 workflow-governance rules, 15 final generalized rules, and 15 supervision notes.
  • Better translation behavior: SCI English grammar rules are now split into targeted retrieval units, making article translation and polishing easier to govern with lightweight RAG.
  • Safer publishing posture: raw source-material exports and full-evidence JSON snapshots are omitted from the public release, while derived reusable rules remain available.
  • Better portability: the core scripts compile and the lightweight RAG command can run in a fresh clone without private local modules.
  • Stronger workflow discipline: the harness now records explicit boundaries for ordinary writing tasks, workflow-governance retrieval, no-regression checks, and script reuse.

Quick verification

The release was checked with:

py -m py_compile tools\kb_rag.py tools\paper_iteration.py
py tools\kb_rag.py --query "SCI English grammar translation article rules" --limit 3
powershell -NoProfile -ExecutionPolicy Bypass -File .\run_paper_iteration.ps1

Current limitations

  • The included vault is still a real exported paper-writing workflow, not a synthetic demo vault.
  • Some notes mention manuscript filenames as evidence labels, but the manuscript files themselves are not included.
  • Convenience commands remain Windows/PowerShell-first.
  • The local fallback RAG is intentionally simple; users with a richer memory backend can set TOTAL_MEMORY_SRC to reuse their own retrieval implementation.

Upgrade guidance

Existing users can pull the new release and rerun:

py tools\kb_rag.py --query "your task keywords" --limit 3
powershell -NoProfile -ExecutionPolicy Bypass -File .\run_paper_iteration.ps1

Optional environment variables:

$env:TOTAL_MEMORY_SRC = "C:\path\to\total-agent-memory\src"
$env:TAM_MEMORY_DB = "C:\path\to\memory.db"
$env:SCI_MEMORY_SKILL = "C:\path\to\SCI-memory\SKILL.md"
$env:SELF_LEARNING_LIBRARY_PYTHON = "C:\path\to\python.exe"
Assets 2
Loading