David Snelling
d05d381a5d
- Introduced `calculateSimilarity` method in `types.d.ts` for comparing vectors or textual inputs: - Added support for custom options, including `forceEmbed` and a custom `distanceFunction`. - Enhanced functionality in `embed` to convert text inputs into vector representations. - Added new test cases in `vector-operations.test.ts`: - Validated similarity calculations between identical and different vectors. - Tested similarity scoring for similar and dissimilar text inputs. - Updated `README.md`: - Documented `calculateSimilarity` usage examples, including advanced options. - Clarified the integration of the similarity function into workflows. **Purpose**: Enable calculation of similarity scores for vectors and text inputs to facilitate advanced data comparison and retrieval tasks. |
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| .. | ||
| src | ||
| brainy-wrapper.js | ||
| cli-wrapper.js | ||
| package-lock.json | ||
| package.json | ||
| README.md | ||
| rollup.config.js | ||
| tsconfig.json | ||
| types.d.ts | ||
@soulcraft/brainy-cli
Command-line interface for the Brainy vector graph database.
Installation
# Install globally
npm install -g @soulcraft/brainy-cli
Usage
Once installed, you can use the brainy command from anywhere:
# Show help
brainy --help
# Initialize a new database
brainy init
# Add data
brainy add "Cats are independent pets" '{"noun":"Thing","category":"animal"}'
# Search
brainy search "feline pets" --limit 5
# Add relationships
brainy addVerb id1 id2 RelatedTo '{"description":"Both are pets"}'
# Visualize the graph
brainy visualize
brainy visualize --root <id> --depth 3
# Generate random test data
brainy generate-random-graph --noun-count 20 --verb-count 30 --clear
Features
- Full access to all Brainy database functionality from the command line
- Autocomplete support for commands and options
- Visualization of graph data
- Import/export capabilities
- Augmentation pipeline testing
Requirements
- Node.js >= 24.4.0
License
MIT