Skip to content

v0.7.11

Choose a tag to compare

View all tags
@yoosefap yoosefap released this 28 Aug 01:18
· 19 commits to main since this release
v0.7.11
c874072
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
Verified
Learn about vigilant mode.

Learning weights now change get_context packet selection, not just persisted graph state.

  • Learning → routing. file_learning_boost aggregates symbol + file reinforcement; learned files enter optional fill via focus-term match or high-bonus saturation; penalized seed files (base_relevance < 0.55) leave the required set.
  • Activation scoring. ActivationScorer adds a learning_lift from access_count / base_relevance so inactive_hints and fallback scores reflect feedback.
  • Explain diagnostics. neuromesh_explain_packet → selection.candidates lists {path, score, learning_bonus, reason, selected} for before/after feedback comparison.
  • Tests. Selector acceptance tests for promote (PromoCodeInput), demote (App.vue), and kosha-style saturation (+50 on routes.py / schema.py).
  • Docs & landing. MCP client lists now include OpenCode, MiMo CLI, and Gemini CLI in README, mcp.md, agent-guide.md, and the GitHub Pages site. OpenCode and MiMo CLI setup sections added to the agent guide.
  • Perf. file_learning_boost_index builds learning scores in one graph pass; fixes gold harness latency regression on Linux CI (>200ms) from per-candidate full-graph scans.
Assets 10
Loading