v1.1.0

Highlights

• Binary vector index — vectors now live in a flat vectors.bin (Float32Array) alongside a slim index.json (id + title only). Smaller index, faster loads.
• L1 index cache — parsed index is cached in-memory and invalidated by mtime, avoiding re-parsing on every injection.
• Similarity score in references — injected <memory_reference> entries now show their cosine score.

Config unification

semanticModel and remoteModel are removed. Use a single option for both backends:

{
  "plugin": [
    [
      "opencode-md-memory",
      {
        "embeddingBackend": "remote",
        "embeddingModel": "text-embedding-3-small"
      }
    ]
  ]
}

• embeddingModel is passed to the OpenAI-compatible /embeddings API (remote backend).
• For the python backend it resolves the model directory at ~/.opencode-md-memory/models/{model}/onnx/, and is forwarded to the embed server via the new --model-name flag.

Bug fix

• Dimension-mismatch safety — switching embedding models (a different output dimension) now rebuilds the index from scratch instead of mixing old/new vectors, which previously could corrupt vectors.bin or surface NaN scores. A defensive check in writeIndex fails loudly on any mixed-dimension write.

Breaking change

• semanticModel / remoteModel config keys removed → use embeddingModel.

Full Changelog: https://github.com/xykbear/opencode-md-memory/commits/v1.1.0