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- Add LibSQLVectorStore implementation using @mastra/libsql for local SQLite-based vector storage - Add FastEmbedEmbedder implementation using @mastra/fastembed for local CPU-based embeddings - Support bge-small-en-v1.5 and bge-base-en-v1.5 embedding models - Update configuration system to support "local" vector store type and "fastembed" embedder provider - Add comprehensive test coverage for new implementations - Maintain backward compatibility with existing Qdrant and OpenAI integrations - Enable zero-cost, privacy-focused code indexing without external dependencies Resolves #5682 |
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| eslint.config.mjs | ||
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| README.md | ||
| tsconfig.json | ||
| tsup.config.ts | ||
| vitest.config.ts | ||
@roo-code/types
Publish to NPM
First authenticate with NPM:
npm login
Next, manually bump the NPM package version:
cd packages/types/npm && npm version minor && cd -
Finally, publish to NPM:
pnpm --filter @roo-code/types npm:publish
Note that you'll be asked for an MFA code to complete the publish.