retoorandClaude Sonnet 5
9dbd1fe667
- Plexer: always-active terminal multiplexing. NativePlexerController/ TmuxPlexerController share one interface, chosen by which env var is already set (TAI_PLEXER_SOCKET vs TMUX_PANE); NativePlexerBackend is the pty.fork()-based wrapper (raw mode, SIGWINCH resize forwarding, a Unix-socket control protocol, continuous session logging, a Ctrl+A prefix key distinct from tmux's own Ctrl+B). Auto-wraps new interactive shells via a .bashrc hook mirroring the existing command-not-found install pattern, gated on $TMUX/$TAI_PLEXER_ACTIVE/ a $HOME/.tai-no-plexer bypass. New plexer_send/read/type/status tools, env-gated on a detected controller. - tests/container.py + docker-compose.yml + tests/docker/Dockerfile: a disposable podman/docker image for the tests that must never touch a real machine (installing the plexer hook into a real ~/.bashrc, a live tmux session). Required suite (test_seal.py, test_tai.py, tests/plexer.py, tests/bashrc.py) gates the result; tests/rag.py runs as best-effort since its real-LLM dependency can't be satisfied inside a disposable container with no nested engine. - tests/bashrc.py: real end-to-end hook install + bash -i auto-wrap, anti-recursion, tmux-active skip, non-interactive skip, a live TmuxPlexerController test, and an install/uninstall round-trip. - tests/plexer.py: NativePlexerBackend under a real pty, plus a dedicated robustness pass (file permissions, >64KB payload framing, a malformed control request, a genuine self-deadlock fix in the write-to-child path). - tai_test.py: the shared async process-driving framework (pipe/pty transport, group-wide kill-and-reap, a StdinBridge for --interactive) both test files build on. - ChatClient last-resort backend: when there's no local opencode CLI but the sandbox box is already running, install opencode into it (official Node tarball, not apt -- apt's nodejs/npm pull in webpack/babel/jest as transitive deps) and route through it instead of giving up. Only reachable after the first retry round already failed everything else; never creates the box itself. TmuxPlexerController.status() fixed to use `list-panes` instead of `display-message -p`, which silently fell back to the default pane instead of erroring against a dead target. - Fix 4 pre-existing test_tai.py bugs surfaced by running it in a clean environment for the first time: two stale mock signatures (subprocess.run's stdout= kwarg, Chat.complete's deadline= kwarg), one $TMUX-dependent catalog assertion, one tty-dependent color assertion. - research/: a sourced research archive (Source Dossier/Citation Card/Conclusion tiers) backing the above design decisions, with its own audit.py consistency checker. - .gitignore: fix a blanket *.md rule that was about to silently drop the entire research/ archive from version control; add __pycache__/ and the one-off debug transcript this session started from. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
49 lines
2.5 KiB
Markdown
49 lines
2.5 KiB
Markdown
# YourMemory — Agentic AI memory with Ebbinghaus forgetting curve decay
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## Metadata
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| Field | Value |
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| Institute | Molodetz Institute — Research & Retrieval Division |
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| Subject | agent-memory-recency-tracking |
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| Document type | Source Dossier |
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| Tier | 1 |
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| Source title | YourMemory: Agentic AI memory with Ebbinghaus forgetting curve decay |
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| Source URL | https://github.com/sachitrafa/YourMemory |
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| Source publisher / author | sachitrafa (GitHub, independent/open-source project) |
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| Source type | repository |
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| Source date (published) | Unknown — not stated |
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| Date researched | 2026-10-09 |
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| Researched by | tai (agent), model: Claude Sonnet 5, on behalf of retoor |
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| Research method | web search synthesis |
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| Confidence | Medium |
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| Status | Active |
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## Summary
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An open-source, smaller competitor project to Mem0 that implements agent memory aging explicitly on an Ebbinghaus forgetting-curve model, rather than Mem0's simpler linear-ish 0.3x–1.5x recency multiplier — and claims a measurable recall improvement over Mem0 on a named benchmark.
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## Key findings
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- Every memory is described as aging on an Ebbinghaus forgetting curve: stale, unused facts fade; important and frequently-recalled ones persist.
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- The project claims "+16pp better recall than Mem0 on LoCoMo" (a named long-context-memory benchmark).
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## Pros / strengths
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- Represents a concrete, implemented alternative to Mem0's simpler decay curve, grounded in an actual cognitive-science forgetting model rather than an ad hoc multiplier range — useful as a second data point on "how might decay actually be shaped" if tai ever builds a ranking-integration phase.
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## Cons / limitations / caveats
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- The "+16pp better recall than Mem0" figure is the competing project's own self-reported claim, on its own chosen benchmark, with no independent verification found during this research pass. It should be treated as a marketing/positioning claim, not a verified result, until independently reproduced.
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- Smaller, less established project than Mem0 or Letta — lower confidence that its described behavior matches real-world production experience at scale.
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## Relevance to tai
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A second, independent example (alongside Mem0) that agent-memory products are converging on recency-as-decay-curve for ranking rather than for eviction — reinforces, but does not change, the subject's conclusion that tai's current proposal should stop at raw tracking and defer any decay-curve decision.
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## Changelog
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| Date | Change |
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| 2026-10-09 | Initial dossier created. |
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