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Extract and enhance reusable GGUF deserialization + MoE per-expert extraction logic from the rmems/corinth-canal experimental reference implementation into Limen-Neural/engram-parser (the canonical zero-dependency parser crate under the Limen-Neural org for modular reusable libraries).
This continues the modularization program (see LIM-9) and aligns with the existing positioning of engram-parser as the GGUF/parse + raw expert extractor base (see README Scope/Boundaries and open #5 for traits).
engram-parser was initially refactored from logic in corinth-canal (see commit 8dd2af2), deliberately omitting routing/CUDA to stay zero-dep and focused.
corinth-canal (rmems personal/experimental ref repo) still duplicates a full GGUF parser + mmap + dequants + adapters in src/moe/{checkpoint.rs,ggml.rs,...}.
Goal: extract useful code from the experimental corinth-canal into Limen-Neural org's focused library crates. corinth-canal remains the end-to-end research vehicle.
No current GitHub/Linear/beads issue explicitly tracked this parser extraction + coordination (until these).
corinth-canal docs/MODULE_STATUS.md (parser still "reference"), docs/PROMOTION_RULES.md, AGENTS.md
Goal
Make engram-parser the single source of truth for GGUF v3 layout parsing + MoE expert weight ripping (raw bytes only). Enable future adoption by cortex-tensor (and potentially corinth-canal's higher layers).
Non-goals
Do not move routing math, model adapters, full dequant math, Safetensors, CUDA/GPU registration, or SNN orchestration.
Do not change corinth-canal's experimental runtime or validation behavior in this issue (that belongs to the companion migration issue).
Keep engram-parser zero-dependency.
Acceptance criteria
Additional dtypes from corinth-canal's ggml (e.g. IQ3_M=31 as Other or explicit opaque; verify byte_len handling).
Port useful pure helpers where they fit zero-dep contract (e.g. ggml_type_label or equivalent; full value type consts for metadata if missing).
Tests cover additional cases/synthetic patterns inspired by corinth-canal.
README updated with explicit note on extraction source + cross-links to cortex-tensor coordination issue and (future) corinth migration issue; ecosystem table remains accurate.
Crate remains zero-dep; cargo test --all-features + clippy/fmt clean.
Issue cross-links to the new cortex-tensor coordination issue and corinth-canal migration issue.
Validation
# In engram-parser
cargo fmt -- --check
cargo clippy --all-targets --all-features -- -D warnings
cargo test --all-features
# Smoke against real GGUF (use paths from corinth-canal configs or $HOME models)
CHECKPOINT_PATH=... cargo run --example ... (or add simple bin if needed)
Suggested branch
feat/extract-gguf-parser-from-corinth
References
Primary plan and research: this repo's session plan.md (extraction from corinth-canal)
corinth-canal open relicense #110 (prereq for future dep from GPL crate)
Created as part of modularization follow-up to LIM-9 and engram #5.
Summary
Extract and enhance reusable GGUF deserialization + MoE per-expert extraction logic from the
rmems/corinth-canalexperimental reference implementation intoLimen-Neural/engram-parser(the canonical zero-dependency parser crate under the Limen-Neural org for modular reusable libraries).This continues the modularization program (see LIM-9) and aligns with the existing positioning of
engram-parseras the GGUF/parse + raw expert extractor base (see README Scope/Boundaries and open #5 for traits).Sibling tracking issues (created together):
Context
engram-parserwas initially refactored from logic in corinth-canal (see commit 8dd2af2), deliberately omitting routing/CUDA to stay zero-dep and focused.corinth-canal(rmems personal/experimental ref repo) still duplicates a full GGUF parser + mmap + dequants + adapters insrc/moe/{checkpoint.rs,ggml.rs,...}.cortex-tensor(sibling Limen-Neural reusable lib) was also extracted from corinth-canal and has open issues Define MoE extraction traits inside this crate #5 (boundary) + parser: adopt/enhance as canonical GGUF parser by extracting from corinth-canal #7 (traits, notes reusability with engram-parser).Related
Goal
Make
engram-parserthe single source of truth for GGUF v3 layout parsing + MoE expert weight ripping (raw bytes only). Enable future adoption by cortex-tensor (and potentially corinth-canal's higher layers).Non-goals
Acceptance criteria
Otheror explicit opaque; verify byte_len handling).cargo test --all-features+ clippy/fmt clean.Validation
Suggested branch
feat/extract-gguf-parser-from-corinthReferences
Created as part of modularization follow-up to LIM-9 and engram #5.
Siblings (created 2026-07-01/02):