Memvid Files

Release Date: February 6, 2026

Overview

This release adds frame-level ACL (Access Control Lists), vector index model consistency enforcement, symspell data corruption fixes, and several CI/build improvements. It also includes README documentation updates and ONNX Runtime noise suppression on macOS.

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🚀 New Features

Frame-Level ACL Enforcement

• Added ACL (Access Control List) plumbing across search, ask, and replay paths
• Per-frame access control enables fine-grained permission enforcement on chunks
• Robustness fixes for ACL boundary conditions
• New tests and benchmark/example updates for ACL workflows

Vector Index Model Consistency (PR [#188])

• Enforces strict binding between vector index and embedding model
• Prevents silent model mismatch corruption when switching embedding providers
• Ensures vector search results are always consistent with the model used at index time

SymSpell Cleanup Fix & Dictionary Tooling (PR [#187])

• Fixed symspell_cleanup data corruption bug
• Added dictionary download tooling for easier setup
• More reliable spell-correction preprocessing for search queries

OpenAI API Embedding Provider (PR [#173])

• Added OpenAI API as an embedding provider option
• Enables using OpenAI embeddings alongside local ONNX models
• Flexible embedding backend selection

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🐛 Bug Fixes

ONNX Runtime Stderr Suppression (macOS)

• Suppressed noisy ONNX Runtime warnings on macOS stderr
• Cleaner console output during normal operation

CI Build Fixes

• Added missing #[cfg(feature = "lex")] guards for tantivy-dependent code
• Fixed CI cache key to use Cargo.toml hash instead of missing Cargo.lock
• Committed Cargo.lock for reproducible CI builds
• Moved target-specific deps section after main dependencies
• Ran cargo fmt on clip.rs and text_embed.rs

Lint Fixes

• Resolved redundant closure lints in tantivy.rs and search/mod.rs
• General lint formatting cleanup

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📝 Documentation

• Added Memvid v1 deprecation warning to README (@sharafdin)
• README updates and improvements (@mo-omar-0197)

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📊 Performance & Reliability

• ACL enforcement: Zero-overhead when no ACL policy is set
• Model consistency: Prevents silent search quality degradation from model mismatch
• SymSpell fix: Eliminates data corruption in spell-correction preprocessing

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📚 Related Pull Requests

• [#188] — feat: enforce vector index model consistency (@0x-pankaj)
• [#187] — feat: fix symspell_cleanup data corruption and add dictionary tooling (@0x-pankaj)
• [#173] — feat: add OpenAI API embedding provider (@0x-pankaj)
• Direct push — Frame-level ACL enforcement across search/ask/replay (@Olow304)

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🎯 Migration Notes

For Users

• No breaking changes — all existing .mv2 files remain compatible
• ACL is opt-in; existing memories work without any ACL configuration
• Vector model consistency is enforced automatically on new indexes

For Developers

• New aclScope field available on API keys (nullable, no migration needed)
• ACL types available in types/acl.rs
• Embedding model is now strictly bound to vector index at creation time

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🙏 Contributors

Thank you to all contributors who made this release possible:

• @Olow304 — ACL enforcement, CI fixes, lint cleanup
• @0x-pankaj — Vector model consistency, symspell fix, OpenAI embeddings
• @sharafdin — Documentation (deprecation notice)
• @mo-omar-0197 — README updates