VectrixDB: Lightweight Vector Database with Embedded Machine Learning Models

Description

A lightweight vector database for text retrieval in R with embedded machine learning models and no external API (Application Programming Interface) keys. Supports dense and hybrid search, optional HNSW (Hierarchical Navigable Small World) approximate nearest-neighbor indexing, faceted filters with ACL (Access Control List) metadata, command-line tools, and a local dashboard built with 'shiny'.

VectrixDB is a lightweight vector database with embedded machine learning models that do not require external API (application programming interface) keys. It supports dense, hybrid, and graph-based search modes and includes a built-in dashboard.

Main Functions

• Vectrix - Simple API for text-in, results-out workflow

• VectrixDB - Advanced database interface

• Collection - Vector collection management

• vectrix_serve - Start REST API server

Search Modes

• dense - Semantic vector search

• sparse - BM25 keyword search

• hybrid - Combined dense + sparse

• ultimate - Full pipeline with reranking

• neural - ColBERT + cross-encoder

Author(s)

Maintainer: Kwadwo Daddy Nyame Owusu Boakye kwadwo.owusuboakye@outlook.com

See Also

Useful links:

• https://knowusuboaky.github.io/vectrixdb-r/

• https://github.com/knowusuboaky/vectrixdb-r

• Report bugs at https://github.com/knowusuboaky/vectrixdb-r/issues

Examples

## Not run: 
# Simple usage
db <- Vectrix$new("my_docs")
db$add(c("Python is great", "R is awesome", "Julia is fast"))
results <- db$search("programming language")
print(results$top()$text)

## End(Not run)

ACL Configuration

Description

ACL configuration for a document or collection

Public fields

Methods

Public methods

• ACLConfig$new()

• ACLConfig$clone()

Method new()

Create a new ACLConfig

Usage

ACLConfig$new(
  read_principals = list(),
  deny_principals = list(),
  is_public = FALSE
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

ACLConfig$clone(deep = FALSE)

Arguments

ACL Filter

Description

Access Control List filter for security-aware search

Public fields

Methods

Public methods

• ACLFilter$new()

• ACLFilter$filter()

• ACLFilter$add_acl()

• ACLFilter$create_filter_condition()

• ACLFilter$clone()

Method new()

Create a new ACLFilter

Usage

ACLFilter$new(acl_field = "_acl")

Arguments

Method filter()

Filter documents based on user's ACL principals

Usage

ACLFilter$filter(documents, user_principals, default_allow = FALSE)

Arguments

Returns

Filtered documents

Method add_acl()

Add ACL to document metadata

Usage

ACLFilter$add_acl(metadata, principals)

Arguments

Returns

Updated metadata

Method create_filter_condition()

Create ACL filter condition for query

Usage

ACLFilter$create_filter_condition(user_principals)

Arguments

Returns

Filter condition list

Method clone()

The objects of this class are cloneable with this method.

Usage

ACLFilter$clone(deep = FALSE)

Arguments

Examples

## Not run: 
acl_filter <- ACLFilter$new()
filtered <- acl_filter$filter(
  documents = results,
  user_principals = c("user:alice", "group:engineering")
)

## End(Not run)

ACL Operator Types

Description

ACL matching operators

Usage

ACLOperator

Format

An object of class list of length 5.

ACL Principal

Description

An ACL principal (user, group, or role)

Public fields

Methods

Public methods

• ACLPrincipal$new()

• ACLPrincipal$matches()

• ACLPrincipal$to_string()

• ACLPrincipal$clone()

Method new()

Create a new ACLPrincipal

Usage

ACLPrincipal$new(type, value)

Arguments

Method matches()

Check if this principal matches another

Usage

ACLPrincipal$matches(other)

Arguments

Returns

Logical

Method to_string()

Convert to string

Usage

ACLPrincipal$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage

ACLPrincipal$clone(deep = FALSE)

Arguments

Advanced Reranker with Learned Weights

Description

Combines multiple signals for better reranking:

• Semantic similarity (word vectors)

• BM25/keyword overlap

• Query coverage

• Position bias

• Length normalization

Public fields

Methods

Public methods

• AdvancedReranker$new()

• AdvancedReranker$set_embedder()

• AdvancedReranker$rerank()

• AdvancedReranker$learn_weights()

• AdvancedReranker$clone()

Method new()

Create a new AdvancedReranker

Usage

AdvancedReranker$new(
  semantic_weight = 0.4,
  bm25_weight = 0.3,
  coverage_weight = 0.2,
  position_weight = 0.1,
  sentence_embedder = NULL
)

Arguments

Method set_embedder()

Set sentence embedder

Usage

AdvancedReranker$set_embedder(embedder)

Arguments

Method rerank()

Rerank results

Usage

AdvancedReranker$rerank(
  query,
  query_vector = NULL,
  results,
  doc_vectors = NULL,
  limit = 10
)

Arguments

Returns

Reranked list of results

Method learn_weights()

Learn optimal weights from relevance judgments

Usage

AdvancedReranker$learn_weights(
  queries,
  results_list,
  relevance_list,
  iterations = 100
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

AdvancedReranker$clone(deep = FALSE)

Arguments

Analyzer Chain

Description

Chain multiple analyzers together

Public fields

Methods

Public methods

• AnalyzerChain$new()

• AnalyzerChain$analyze()

• AnalyzerChain$clone()

Method new()

Create a new AnalyzerChain

Usage

AnalyzerChain$new(analyzers)

Arguments

Method analyze()

Run text through all analyzers

Usage

AnalyzerChain$analyze(text)

Arguments

Returns

Character vector of tokens

Method clone()

The objects of this class are cloneable with this method.

Usage

AnalyzerChain$clone(deep = FALSE)

Arguments

Base Cache

Description

Abstract base class for cache backends

Public fields

Methods

Public methods

• BaseCache$new()

• BaseCache$get()

• BaseCache$set()

• BaseCache$delete()

• BaseCache$exists()

• BaseCache$clear()

• BaseCache$size()

• BaseCache$get_many()

• BaseCache$set_many()

• BaseCache$delete_many()

• BaseCache$make_key()

• BaseCache$clone()

Method new()

Create a new cache

Usage

BaseCache$new(config = NULL)

Arguments

Method get()

Get a value from cache

Usage

BaseCache$get(key)

Arguments

Returns

Cached value or NULL

Method set()

Set a value in cache

Usage

BaseCache$set(key, value, ttl = NULL)

Arguments

Method delete()

Delete a key from cache

Usage

BaseCache$delete(key)

Arguments

Returns

Logical success

Method exists()

Check if key exists

Usage

BaseCache$exists(key)

Arguments

Returns

Logical

Method clear()

Clear all cache entries

Usage

BaseCache$clear()

Method size()

Get cache size

Usage

BaseCache$size()

Returns

Integer count

Method get_many()

Get multiple values

Usage

BaseCache$get_many(keys)

Arguments

Returns

Named list of values

Method set_many()

Set multiple values

Usage

BaseCache$set_many(items, ttl = NULL)

Arguments

Method delete_many()

Delete multiple keys

Usage

BaseCache$delete_many(keys)

Arguments

Returns

Integer count of deleted keys

Method make_key()

Make a prefixed key

Usage

BaseCache$make_key(key)

Arguments

Returns

Prefixed key

Method clone()

The objects of this class are cloneable with this method.

Usage

BaseCache$clone(deep = FALSE)

Arguments

CLI Configuration

Description

Configuration for CLI behavior

Public fields

Methods

Public methods

• CLIConfig$new()

• CLIConfig$clone()

Method new()

Create CLI config

Usage

CLIConfig$new(verbose = TRUE, color = TRUE, data_dir = NULL)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

CLIConfig$clone(deep = FALSE)

Arguments

Cache Backend Types

Description

Available cache backends

Usage

CacheBackend

Format

An object of class list of length 3.

Cache Configuration

Description

Configuration for cache layer

Public fields

Methods

Public methods

• CacheConfig$new()

• CacheConfig$clone()

Method new()

Create a new CacheConfig

Usage

CacheConfig$new(
  backend = "memory",
  memory_max_size = 10000,
  memory_ttl_seconds = 3600,
  file_cache_dir = NULL,
  file_ttl_seconds = 86400,
  prefix = "vectrix:",
  compression = TRUE
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

CacheConfig$clone(deep = FALSE)

Arguments

Cache Entry

Description

A cached entry with metadata

Public fields

Methods

Public methods

• CacheEntry$new()

• CacheEntry$is_expired()

• CacheEntry$clone()

Method new()

Create a new CacheEntry

Usage

CacheEntry$new(value, ttl)

Arguments

Method is_expired()

Check if entry is expired

Usage

CacheEntry$is_expired()

Returns

Logical

Method clone()

The objects of this class are cloneable with this method.

Usage

CacheEntry$clone(deep = FALSE)

Arguments

Cache Statistics

Description

Cache statistics for monitoring

Public fields

Methods

Public methods

• CacheStats$record_hit()

• CacheStats$record_miss()

• CacheStats$record_set()

• CacheStats$record_delete()

• CacheStats$record_eviction()

• CacheStats$hit_rate()

• CacheStats$to_list()

• CacheStats$reset()

• CacheStats$clone()

Method record_hit()

Record a cache hit

Usage

CacheStats$record_hit()

Method record_miss()

Record a cache miss

Usage

CacheStats$record_miss()

Method record_set()

Record a cache set

Usage

CacheStats$record_set()

Method record_delete()

Record a cache delete

Usage

CacheStats$record_delete()

Method record_eviction()

Record a cache eviction

Usage

CacheStats$record_eviction()

Method hit_rate()

Get hit rate

Usage

CacheStats$hit_rate()

Returns

Numeric hit rate

Method to_list()

Convert to list

Usage

CacheStats$to_list()

Returns

List representation

Method reset()

Reset statistics

Usage

CacheStats$reset()

Method clone()

The objects of this class are cloneable with this method.

Usage

CacheStats$clone(deep = FALSE)

Arguments

Collection Class

Description

Vector collection with indexing and search

Public fields

Methods

Public methods

• Collection$new()

• Collection$add()

• Collection$search()

• Collection$keyword_search()

• Collection$hybrid_search()

• Collection$get()

• Collection$delete()

• Collection$count()

• Collection$clear()

• Collection$clone()

Method new()

Create a new Collection

Usage

Collection$new(
  name,
  dimension,
  metric = "cosine",
  storage = NULL,
  language = "en"
)

Arguments

Method add()

Add documents to collection

Usage

Collection$add(ids, vectors, metadata = NULL, texts = NULL)

Arguments

Method search()

Search collection

Usage

Collection$search(query, limit = 10, filter = NULL, include_vectors = FALSE)

Arguments

Returns

Results object

Method keyword_search()

Keyword search

Usage

Collection$keyword_search(query_text, limit = 10, filter = NULL)

Arguments

Returns

Results object

Method hybrid_search()

Hybrid search (dense + sparse)

Usage

Collection$hybrid_search(
  query,
  query_text,
  limit = 10,
  vector_weight = 0.5,
  text_weight = 0.5,
  filter = NULL,
  include_vectors = FALSE,
  rrf_k = 60,
  prefetch_multiplier = 10
)

Arguments

Returns

Results object

Method get()

Get documents by ID

Usage

Collection$get(ids)

Arguments

Returns

List of results

Method delete()

Delete documents by ID

Usage

Collection$delete(ids)

Arguments

Method count()

Get document count

Usage

Collection$count()

Returns

Integer count

Method clear()

Clear collection

Usage

Collection$clear()

Method clone()

The objects of this class are cloneable with this method.

Usage

Collection$clone(deep = FALSE)

Arguments

Community

Description

A community of entities

Public fields

Methods

Public methods

• Community$new()

• Community$size()

• Community$clone()

Method new()

Create a new Community

Usage

Community$new(
  id,
  level = 0,
  entity_ids = character(0),
  summary = NULL,
  parent_id = NULL
)

Arguments

Method size()

Get size

Usage

Community$size()

Returns

Integer

Method clone()

The objects of this class are cloneable with this method.

Usage

Community$clone(deep = FALSE)

Arguments

Simple Community Detector

Description

Detects communities using connected components

Public fields

Methods

Public methods

• CommunityDetector$new()

• CommunityDetector$detect()

• CommunityDetector$clone()

Method new()

Create a new CommunityDetector

Usage

CommunityDetector$new(min_size = 5, max_levels = 3)

Arguments

Method detect()

Detect communities in graph

Usage

CommunityDetector$detect(graph)

Arguments

Returns

List of Community objects

Method clone()

The objects of this class are cloneable with this method.

Usage

CommunityDetector$clone(deep = FALSE)

Arguments

Dense Embedder using word2vec or GloVe

Description

Generates dense vector embeddings using pre-trained word vectors

Public fields

Methods

Public methods

• DenseEmbedder$new()

• DenseEmbedder$set_sentence_embedder()

• DenseEmbedder$embed()

• DenseEmbedder$fit()

• DenseEmbedder$clone()

Method new()

Create a new DenseEmbedder

Usage

DenseEmbedder$new(
  dimension = 100,
  model_path = NULL,
  model_type = "tfidf",
  sentence_embedder = NULL,
  auto_download = FALSE,
  language = "en"
)

Arguments

Method set_sentence_embedder()

Set a SentenceEmbedder to use for embeddings

Usage

DenseEmbedder$set_sentence_embedder(embedder)

Arguments

Method embed()

Embed texts to vectors

Usage

DenseEmbedder$embed(texts)

Arguments

Returns

Matrix of embeddings (rows are documents)

Method fit()

Train embedder on corpus (for TF-IDF)

Usage

DenseEmbedder$fit(texts)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

DenseEmbedder$clone(deep = FALSE)

Arguments

Distance Metric Enumeration

Description

Available distance metrics for vector comparison

Usage

DistanceMetric

Format

An object of class list of length 4.

Document Chunker

Description

Splits documents into text units

Public fields

Methods

Public methods

• DocumentChunker$new()

• DocumentChunker$chunk()

• DocumentChunker$clone()

Method new()

Create a new DocumentChunker

Usage

DocumentChunker$new(chunk_size = 1200, chunk_overlap = 100, by_sentence = TRUE)

Arguments

Method chunk()

Chunk a document

Usage

DocumentChunker$chunk(text, document_id = NULL)

Arguments

Returns

List of TextUnit objects

Method clone()

The objects of this class are cloneable with this method.

Usage

DocumentChunker$clone(deep = FALSE)

Arguments

English Stopwords

Description

Common English stopwords

Usage

ENGLISH_STOPWORDS

Format

An object of class character of length 45.

Enhanced Search Results

Description

Search results with enterprise features

Public fields

Methods

Public methods

• EnhancedSearchResults$new()

• EnhancedSearchResults$to_list()

• EnhancedSearchResults$clone()

Method new()

Create new EnhancedSearchResults

Usage

EnhancedSearchResults$new(
  results,
  facets = list(),
  total_count = 0,
  filtered_count = 0,
  query_time_ms = 0,
  rerank_time_ms = 0,
  facet_time_ms = 0
)

Arguments

Method to_list()

Convert to list

Usage

EnhancedSearchResults$to_list()

Returns

List representation

Method clone()

The objects of this class are cloneable with this method.

Usage

EnhancedSearchResults$clone(deep = FALSE)

Arguments

Entity

Description

An extracted entity

Public fields

Methods

Public methods

• Entity$new()

• Entity$to_list()

• Entity$clone()

Method new()

Create a new Entity

Usage

Entity$new(
  id = NULL,
  name,
  type,
  description = NULL,
  source_chunks = NULL,
  embedding = NULL,
  metadata = NULL
)

Arguments

Method to_list()

Convert to list

Usage

Entity$to_list()

Method clone()

The objects of this class are cloneable with this method.

Usage

Entity$clone(deep = FALSE)

Arguments

Extraction Result

Description

Result of entity extraction

Public fields

Methods

Public methods

• ExtractionResult$new()

• ExtractionResult$clone()

Method new()

Create new ExtractionResult

Usage

ExtractionResult$new(
  entities = list(),
  relationships = list(),
  source_chunk = NULL
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

ExtractionResult$clone(deep = FALSE)

Arguments

Extractor Types

Description

Extractor Types

Usage

ExtractorType

Format

An object of class list of length 4.

Facet Aggregator

Description

Faceted search aggregator for computing aggregations/counts

Methods

Public methods

• FacetAggregator$aggregate()

• FacetAggregator$to_list()

• FacetAggregator$clone()

Method aggregate()

Aggregate facet values from documents

Usage

FacetAggregator$aggregate(documents, facet_configs)

Arguments

Returns

Named list mapping field names to FacetResult

Method to_list()

Convert facet results to list format

Usage

FacetAggregator$to_list(facet_results)

Arguments

Returns

List format suitable for JSON

Method clone()

The objects of this class are cloneable with this method.

Usage

FacetAggregator$clone(deep = FALSE)

Arguments

Examples

## Not run: 
aggregator <- FacetAggregator$new()
facets <- aggregator$aggregate(
  documents = list(
    list(category = "tech", author = "Alice"),
    list(category = "science", author = "Bob")
  ),
  facet_fields = c("category", "author")
)

## End(Not run)

Facet Configuration

Description

Configuration for a facet field

Public fields

Methods

Public methods

• FacetConfig$new()

• FacetConfig$clone()

Method new()

Create a new FacetConfig

Usage

FacetConfig$new(
  field,
  limit = 10,
  min_count = 1,
  sort_by = "count",
  include_zero = FALSE
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

FacetConfig$clone(deep = FALSE)

Arguments

Facet Result

Description

Result of facet aggregation

Public fields

Methods

Public methods

• FacetResult$new()

• FacetResult$to_list()

• FacetResult$clone()

Method new()

Create a new FacetResult

Usage

FacetResult$new(field, values, total_count, other_count = 0)

Arguments

Method to_list()

Convert to list

Usage

FacetResult$to_list()

Method clone()

The objects of this class are cloneable with this method.

Usage

FacetResult$clone(deep = FALSE)

Arguments

Facet Value

Description

A single facet value with count

Public fields

Methods

Public methods

• FacetValue$new()

• FacetValue$clone()

Method new()

Create a new FacetValue

Usage

FacetValue$new(value, count)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

FacetValue$clone(deep = FALSE)

Arguments

File Cache

Description

File-based persistent cache using RDS files

Super class

VectrixDB::BaseCache -> FileCache

Methods

Public methods

• FileCache$new()

• FileCache$get()

• FileCache$set()

• FileCache$delete()

• FileCache$exists()

• FileCache$clear()

• FileCache$size()

• FileCache$cleanup_expired()

• FileCache$clone()

Method new()

Create a new FileCache

Usage

FileCache$new(config = NULL)

Arguments

Method get()

Get value from cache

Usage

FileCache$get(key)

Arguments

Returns

Value or NULL

Method set()

Set value in cache

Usage

FileCache$set(key, value, ttl = NULL)

Arguments

Method delete()

Delete key from cache

Usage

FileCache$delete(key)

Arguments

Returns

Logical success

Method exists()

Check if key exists

Usage

FileCache$exists(key)

Arguments

Returns

Logical

Method clear()

Clear cache

Usage

FileCache$clear()

Method size()

Get cache size

Usage

FileCache$size()

Returns

Integer

Method cleanup_expired()

Cleanup expired entries

Usage

FileCache$cleanup_expired()

Returns

Integer count removed

Method clone()

The objects of this class are cloneable with this method.

Usage

FileCache$clone(deep = FALSE)

Arguments

Filter Class for Metadata Filtering

Description

Build metadata filters for search queries

Public fields

Methods

Public methods

• Filter$new()

• Filter$eq()

• Filter$ne()

• Filter$gt()

• Filter$lt()

• Filter$in_list()

• Filter$to_list()

• Filter$clone()

Method new()

Create a new Filter

Usage

Filter$new(...)

Arguments

Method eq()

Add equality condition

Usage

Filter$eq(field, value)

Arguments

Returns

Self for chaining

Method ne()

Add not-equal condition

Usage

Filter$ne(field, value)

Arguments

Returns

Self for chaining

Method gt()

Add greater-than condition

Usage

Filter$gt(field, value)

Arguments

Returns

Self for chaining

Method lt()

Add less-than condition

Usage

Filter$lt(field, value)

Arguments

Returns

Self for chaining

Method in_list()

Add in-list condition

Usage

Filter$in_list(field, values)

Arguments

Returns

Self for chaining

Method to_list()

Convert to list for API

Usage

Filter$to_list()

Returns

List representation

Method clone()

The objects of this class are cloneable with this method.

Usage

Filter$clone(deep = FALSE)

Arguments

Global Search Result

Description

Result from global community search

Public fields

Methods

Public methods

• GlobalSearchResult$new()

• GlobalSearchResult$clone()

Method new()

Create new GlobalSearchResult

Usage

GlobalSearchResult$new(
  communities = list(),
  summaries = character(0),
  context = NULL,
  score = 0
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

GlobalSearchResult$clone(deep = FALSE)

Arguments

Global Searcher

Description

Community-based graph search

Public fields

Methods

Public methods

• GlobalSearcher$new()

• GlobalSearcher$search()

• GlobalSearcher$clone()

Method new()

Create a new GlobalSearcher

Usage

GlobalSearcher$new(communities, k = 5)

Arguments

Method search()

Search communities

Usage

GlobalSearcher$search(query)

Arguments

Returns

GlobalSearchResult

Method clone()

The objects of this class are cloneable with this method.

Usage

GlobalSearcher$clone(deep = FALSE)

Arguments

GraphRAG Configuration

Description

Configuration for VectrixDB's GraphRAG implementation

Public fields

Methods

Public methods

• GraphRAGConfig$new()

• GraphRAGConfig$with_openai()

• GraphRAGConfig$with_ollama()

• GraphRAGConfig$clone()

Method new()

Create a new GraphRAGConfig

Usage

GraphRAGConfig$new(enabled = FALSE, ...)

Arguments

Method with_openai()

Configure for OpenAI

Usage

GraphRAGConfig$with_openai(model = "gpt-4o-mini", api_key = NULL)

Arguments

Returns

Self

Method with_ollama()

Configure for Ollama

Usage

GraphRAGConfig$with_ollama(
  model = "llama3.2",
  endpoint = "http://localhost:11434"
)

Arguments

Returns

Self

Method clone()

The objects of this class are cloneable with this method.

Usage

GraphRAGConfig$clone(deep = FALSE)

Arguments

Examples

## Not run: 
config <- GraphRAGConfig$new(enabled = TRUE)
db <- Vectrix$new("knowledge_base", graphrag_config = config)

## End(Not run)

GraphRAG Pipeline

Description

Complete GraphRAG processing pipeline

Public fields

Methods

Public methods

• GraphRAGPipeline$new()

• GraphRAGPipeline$process()

• GraphRAGPipeline$search()

• GraphRAGPipeline$stats()

• GraphRAGPipeline$clone()

Method new()

Create a new GraphRAGPipeline

Usage

GraphRAGPipeline$new(config = NULL)

Arguments

Method process()

Process documents

Usage

GraphRAGPipeline$process(texts, document_ids = NULL)

Arguments

Returns

Self

Method search()

Search the graph

Usage

GraphRAGPipeline$search(query, search_type = NULL)

Arguments

Returns

Search result

Method stats()

Get statistics

Usage

GraphRAGPipeline$stats()

Returns

Named list

Method clone()

The objects of this class are cloneable with this method.

Usage

GraphRAGPipeline$clone(deep = FALSE)

Arguments

Graph Search Types

Description

Graph Search Types

Usage

GraphSearchType

Format

An object of class list of length 3.

HNSW Index

Description

High-performance approximate nearest neighbor index

Public fields

Methods

Public methods

• HNSWIndex$new()

• HNSWIndex$add_items()

• HNSWIndex$build()

• HNSWIndex$search()

• HNSWIndex$get_vector()

• HNSWIndex$get_ids()

• HNSWIndex$size()

• HNSWIndex$remove_items()

• HNSWIndex$clear()

• HNSWIndex$save()

• HNSWIndex$load()

• HNSWIndex$clone()

Method new()

Create a new HNSWIndex

Usage

HNSWIndex$new(dimension, metric = "angular", n_trees = 50, search_k = -1)

Arguments

Method add_items()

Add items to the index

Usage

HNSWIndex$add_items(ids, vectors)

Arguments

Returns

Self

Method build()

Build the index (required before searching)

Usage

HNSWIndex$build()

Returns

Self

Method search()

Search for nearest neighbors

Usage

HNSWIndex$search(query, k = 10, include_distances = TRUE)

Arguments

Returns

Data frame with id, distance columns

Method get_vector()

Get vector by ID

Usage

HNSWIndex$get_vector(id)

Arguments

Returns

Vector or NULL

Method get_ids()

Get all IDs

Usage

HNSWIndex$get_ids()

Returns

Character vector

Method size()

Get item count

Usage

HNSWIndex$size()

Returns

Integer

Method remove_items()

Remove items from index

Usage

HNSWIndex$remove_items(ids)

Arguments

Returns

Self

Method clear()

Clear the index

Usage

HNSWIndex$clear()

Returns

Self

Method save()

Save index to file

Usage

HNSWIndex$save(path)

Arguments

Method load()

Load index from file

Usage

HNSWIndex$load(path)

Arguments

Returns

Self

Method clone()

The objects of this class are cloneable with this method.

Usage

HNSWIndex$clone(deep = FALSE)

Arguments

Examples

## Not run: 
# Create index
index <- HNSWIndex$new(dimension = 128, metric = "angular")

# Add vectors
index$add_items(ids = c("a", "b", "c"),
                vectors = matrix(rnorm(384), nrow = 3))

# Search
results <- index$search(query = rnorm(128), k = 5)

## End(Not run)

In-Memory Storage

Description

Fast in-memory storage backend

Public fields

Methods

Public methods

• InMemoryStorage$new()

• InMemoryStorage$set()

• InMemoryStorage$get()

• InMemoryStorage$delete()

• InMemoryStorage$exists()

• InMemoryStorage$keys()

• InMemoryStorage$clear()

• InMemoryStorage$count()

• InMemoryStorage$clone()

Method new()

Create new in-memory storage

Usage

InMemoryStorage$new()

Method set()

Store a value

Usage

InMemoryStorage$set(key, value)

Arguments

Method get()

Retrieve a value

Usage

InMemoryStorage$get(key)

Arguments

Returns

Stored value or NULL

Method delete()

Delete a value

Usage

InMemoryStorage$delete(key)

Arguments

Method exists()

Check if key exists

Usage

InMemoryStorage$exists(key)

Arguments

Returns

Logical

Method keys()

List all keys

Usage

InMemoryStorage$keys()

Returns

Character vector of keys

Method clear()

Clear all data

Usage

InMemoryStorage$clear()

Method count()

Get count of stored items

Usage

InMemoryStorage$count()

Returns

Integer count

Method clone()

The objects of this class are cloneable with this method.

Usage

InMemoryStorage$clone(deep = FALSE)

Arguments

Keyword Analyzer

Description

Treats entire input as single token

Super class

VectrixDB::TextAnalyzer -> KeywordAnalyzer

Methods

Public methods

• KeywordAnalyzer$analyze()

• KeywordAnalyzer$clone()

Method analyze()

Analyze text as single keyword

Usage

KeywordAnalyzer$analyze(text)

Arguments

Returns

Single-element character vector

Method clone()

The objects of this class are cloneable with this method.

Usage

KeywordAnalyzer$clone(deep = FALSE)

Arguments

Knowledge Graph

Description

Graph storage for entities and relationships

Public fields

Methods

Public methods

• KnowledgeGraph$new()

• KnowledgeGraph$add_entity()

• KnowledgeGraph$add_relationship()

• KnowledgeGraph$get_entity()

• KnowledgeGraph$get_all_entities()

• KnowledgeGraph$get_all_relationships()

• KnowledgeGraph$get_neighbors()

• KnowledgeGraph$traverse()

• KnowledgeGraph$entity_count()

• KnowledgeGraph$relationship_count()

• KnowledgeGraph$search_entities()

• KnowledgeGraph$clone()

Method new()

Create a new KnowledgeGraph

Usage

KnowledgeGraph$new(name = "default")

Arguments

Method add_entity()

Add an entity

Usage

KnowledgeGraph$add_entity(entity)

Arguments

Method add_relationship()

Add a relationship

Usage

KnowledgeGraph$add_relationship(relationship)

Arguments

Method get_entity()

Get entity by ID

Usage

KnowledgeGraph$get_entity(entity_id)

Arguments

Returns

Entity or NULL

Method get_all_entities()

Get all entities

Usage

KnowledgeGraph$get_all_entities()

Returns

List of Entity objects

Method get_all_relationships()

Get all relationships

Usage

KnowledgeGraph$get_all_relationships()

Returns

List of Relationship objects

Method get_neighbors()

Get neighbors of an entity

Usage

KnowledgeGraph$get_neighbors(entity_id, direction = "both")

Arguments

Returns

List of Entity objects

Method traverse()

Traverse graph from seed entities

Usage

KnowledgeGraph$traverse(seed_ids, max_depth = 2)

Arguments

Returns

SubGraph object

Method entity_count()

Get entity count

Usage

KnowledgeGraph$entity_count()

Returns

Integer

Method relationship_count()

Get relationship count

Usage

KnowledgeGraph$relationship_count()

Returns

Integer

Method search_entities()

Search entities by name

Usage

KnowledgeGraph$search_entities(query, limit = 10)

Arguments

Returns

List of Entity objects

Method clone()

The objects of this class are cloneable with this method.

Usage

KnowledgeGraph$clone(deep = FALSE)

Arguments

LLM Provider Types

Description

LLM Provider Types

Usage

LLMProvider

Format

An object of class list of length 4.

Late Interaction Embedder (Simplified ColBERT-style)

Description

Token-level embeddings for late interaction scoring

Public fields

Methods

Public methods

• LateInteractionEmbedder$new()

• LateInteractionEmbedder$embed()

• LateInteractionEmbedder$score()

• LateInteractionEmbedder$clone()

Method new()

Create a new LateInteractionEmbedder

Usage

LateInteractionEmbedder$new(dimension = 64, language = "en")

Arguments

Method embed()

Embed texts to token-level embeddings

Usage

LateInteractionEmbedder$embed(texts)

Arguments

Returns

List of matrices (each matrix is token embeddings for a document)

Method score()

Compute late interaction (MaxSim) score

Usage

LateInteractionEmbedder$score(query_embeddings, doc_embeddings)

Arguments

Returns

Numeric score

Method clone()

The objects of this class are cloneable with this method.

Usage

LateInteractionEmbedder$clone(deep = FALSE)

Arguments

Local Search Result

Description

Result from local graph search

Public fields

Methods

Public methods

• LocalSearchResult$new()

• LocalSearchResult$clone()

Method new()

Create new LocalSearchResult

Usage

LocalSearchResult$new(
  entities = list(),
  relationships = list(),
  subgraph = NULL,
  context = NULL,
  score = 0
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

LocalSearchResult$clone(deep = FALSE)

Arguments

Local Searcher

Description

Entity-based graph search

Public fields

Methods

Public methods

• LocalSearcher$new()

• LocalSearcher$search()

• LocalSearcher$clone()

Method new()

Create a new LocalSearcher

Usage

LocalSearcher$new(graph, k = 10, traversal_depth = 2)

Arguments

Method search()

Search the graph

Usage

LocalSearcher$search(query)

Arguments

Returns

LocalSearchResult

Method clone()

The objects of this class are cloneable with this method.

Usage

LocalSearcher$clone(deep = FALSE)

Arguments

Maximal Marginal Relevance (MMR) Reranker

Description

Reranks for diversity using MMR algorithm

Public fields

Methods

Public methods

• MMRReranker$new()

• MMRReranker$rerank()

• MMRReranker$clone()

Method new()

Create a new MMRReranker

Usage

MMRReranker$new(lambda = 0.7)

Arguments

Method rerank()

Rerank for diversity

Usage

MMRReranker$rerank(query_vector, doc_vectors, doc_ids, scores, limit = 10)

Arguments

Returns

Data frame with reranked results

Method clone()

The objects of this class are cloneable with this method.

Usage

MMRReranker$clone(deep = FALSE)

Arguments

Memory Cache

Description

In-memory LRU cache with TTL support

Ultra-low latency, limited by available RAM. Best for hot data, session data, frequently accessed vectors.

Super class

VectrixDB::BaseCache -> MemoryCache

Methods

Public methods

• MemoryCache$new()

• MemoryCache$get()

• MemoryCache$set()

• MemoryCache$delete()

• MemoryCache$exists()

• MemoryCache$clear()

• MemoryCache$size()

• MemoryCache$cleanup_expired()

• MemoryCache$clone()

Method new()

Create a new MemoryCache

Usage

MemoryCache$new(config = NULL)

Arguments

Method get()

Get value from cache

Usage

MemoryCache$get(key)

Arguments

Returns

Value or NULL

Method set()

Set value in cache

Usage

MemoryCache$set(key, value, ttl = NULL)

Arguments

Method delete()

Delete key from cache

Usage

MemoryCache$delete(key)

Arguments

Returns

Logical success

Method exists()

Check if key exists

Usage

MemoryCache$exists(key)

Arguments

Returns

Logical

Method clear()

Clear cache

Usage

MemoryCache$clear()

Method size()

Get cache size

Usage

MemoryCache$size()

Returns

Integer

Method cleanup_expired()

Cleanup expired entries

Usage

MemoryCache$cleanup_expired()

Returns

Integer count removed

Method clone()

The objects of this class are cloneable with this method.

Usage

MemoryCache$clone(deep = FALSE)

Arguments

No-Op Cache

Description

Disabled cache (no caching)

Super class

VectrixDB::BaseCache -> NoCache

Methods

Public methods

• NoCache$get()

• NoCache$set()

• NoCache$delete()

• NoCache$exists()

• NoCache$clear()

• NoCache$size()

• NoCache$clone()

Method get()

Get value from cache (always returns NULL)

Usage

NoCache$get(key)

Arguments

Returns

NULL

Method set()

Set cache value (no-op)

Usage

NoCache$set(key, value, ttl = NULL)

Arguments

Returns

Invisibly returns NULL

Method delete()

Delete key from cache (always FALSE)

Usage

NoCache$delete(key)

Arguments

Returns

FALSE

Method exists()

Check if key exists (always FALSE)

Usage

NoCache$exists(key)

Arguments

Returns

FALSE

Method clear()

Clear cache (no-op)

Usage

NoCache$clear()

Returns

Invisibly returns NULL

Method size()

Get cache size (always 0)

Usage

NoCache$size()

Returns

Integer zero

Method clone()

The objects of this class are cloneable with this method.

Usage

NoCache$clone(deep = FALSE)

Arguments

Regex Entity Extractor

Description

Simple regex-based entity extractor (no external dependencies)

Public fields

Methods

Public methods

• RegexExtractor$new()

• RegexExtractor$extract()

• RegexExtractor$clone()

Method new()

Create a new RegexExtractor

Usage

RegexExtractor$new(entity_types = NULL)

Arguments

Method extract()

Extract entities from text

Usage

RegexExtractor$extract(text, chunk_id = NULL)

Arguments

Returns

ExtractionResult

Method clone()

The objects of this class are cloneable with this method.

Usage

RegexExtractor$clone(deep = FALSE)

Arguments

Relationship

Description

A relationship between entities

Public fields

Methods

Public methods

• Relationship$new()

• Relationship$to_list()

• Relationship$clone()

Method new()

Create a new Relationship

Usage

Relationship$new(
  source_id,
  target_id,
  type,
  description = NULL,
  weight = 1,
  source_chunks = NULL,
  metadata = NULL
)

Arguments

Method to_list()

Convert to list

Usage

Relationship$to_list()

Method clone()

The objects of this class are cloneable with this method.

Usage

Relationship$clone(deep = FALSE)

Arguments

Reranker (Cross-Encoder Style Scoring)

Description

Reranks results using term overlap and semantic similarity

Public fields

Methods

Public methods

• RerankerEmbedder$new()

• RerankerEmbedder$score()

• RerankerEmbedder$clone()

Method new()

Create a new RerankerEmbedder

Usage

RerankerEmbedder$new(language = "en")

Arguments

Method score()

Score query-document pairs

Usage

RerankerEmbedder$score(query, documents)

Arguments

Returns

Numeric vector of scores (0-1)

Method clone()

The objects of this class are cloneable with this method.

Usage

RerankerEmbedder$clone(deep = FALSE)

Arguments

Single Search Result

Description

Represents a single search result with id, text, score, and metadata

Public fields

Methods

Public methods

• Result$new()

• Result$print()

• Result$clone()

Method new()

Create a new Result object

Usage

Result$new(id, text, score, metadata = list())

Arguments

Method print()

Print result summary

Usage

Result$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

Result$clone(deep = FALSE)

Arguments

Search Results Collection

Description

Collection of search results with convenient accessors

Public fields

Methods

Public methods

• Results$new()

• Results$length()

• Results$texts()

• Results$ids()

• Results$scores()

• Results$top()

• Results$get()

• Results$foreach()

• Results$print()

• Results$clone()

Method new()

Create a new Results object

Usage

Results$new(items = list(), query = "", mode = "hybrid", time_ms = 0)

Arguments

Method length()

Get number of results

Usage

Results$length()

Method texts()

Get all result texts

Usage

Results$texts()

Returns

Character vector of texts

Method ids()

Get all result IDs

Usage

Results$ids()

Returns

Character vector of IDs

Method scores()

Get all scores

Usage

Results$scores()

Returns

Numeric vector of scores

Method top()

Get top result

Usage

Results$top()

Returns

Result object or NULL if empty

Method get()

Get result by index

Usage

Results$get(i)

Arguments

Returns

Result object

Method foreach()

Iterate over results

Usage

Results$foreach(fn)

Arguments

Method print()

Print results summary

Usage

Results$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

Results$clone(deep = FALSE)

Arguments

SQLite Storage

Description

Persistent SQLite storage backend

Public fields

Methods

Public methods

• SQLiteStorage$new()

• SQLiteStorage$set()

• SQLiteStorage$get()

• SQLiteStorage$delete()

• SQLiteStorage$exists()

• SQLiteStorage$keys()

• SQLiteStorage$clear()

• SQLiteStorage$count()

• SQLiteStorage$close()

• SQLiteStorage$clone()

Method new()

Create new SQLite storage

Usage

SQLiteStorage$new(path)

Arguments

Method set()

Store a value

Usage

SQLiteStorage$set(key, value)

Arguments

Method get()

Retrieve a value

Usage

SQLiteStorage$get(key)

Arguments

Returns

Stored value or NULL

Method delete()

Delete a value

Usage

SQLiteStorage$delete(key)

Arguments

Method exists()

Check if key exists

Usage

SQLiteStorage$exists(key)

Arguments

Returns

Logical

Method keys()

List all keys

Usage

SQLiteStorage$keys()

Returns

Character vector of keys

Method clear()

Clear all data

Usage

SQLiteStorage$clear()

Method count()

Get count of stored items

Usage

SQLiteStorage$count()

Returns

Integer count

Method close()

Close database connection

Usage

SQLiteStorage$close()

Method clone()

The objects of this class are cloneable with this method.

Usage

SQLiteStorage$clone(deep = FALSE)

Arguments

Search Mode Enumeration

Description

Available search modes for VectrixDB

Usage

SearchMode

Format

An object of class list of length 5.

Sentence Embedder using Word Vectors

Description

Creates sentence embeddings by averaging word vectors with IDF weighting

Public fields

Methods

Public methods

• SentenceEmbedder$new()

• SentenceEmbedder$fit()

• SentenceEmbedder$embed()

• SentenceEmbedder$get_word_vector()

• SentenceEmbedder$has_word()

• SentenceEmbedder$most_similar()

• SentenceEmbedder$clone()

Method new()

Create a new SentenceEmbedder

Usage

SentenceEmbedder$new(word_vectors, use_idf = TRUE, smooth_idf = 1)

Arguments

Method fit()

Fit IDF weights on a corpus

Usage

SentenceEmbedder$fit(texts)

Arguments

Method embed()

Embed texts to sentence vectors

Usage

SentenceEmbedder$embed(texts)

Arguments

Returns

Matrix of embeddings (rows are sentences)

Method get_word_vector()

Get word vector for a single word

Usage

SentenceEmbedder$get_word_vector(word)

Arguments

Returns

Numeric vector or NULL if not found

Method has_word()

Check if word is in vocabulary

Usage

SentenceEmbedder$has_word(word)

Arguments

Returns

Logical

Method most_similar()

Find most similar words

Usage

SentenceEmbedder$most_similar(word, n = 10)

Arguments

Returns

Data frame with word and similarity

Method clone()

The objects of this class are cloneable with this method.

Usage

SentenceEmbedder$clone(deep = FALSE)

Arguments

Simple Stemmer

Description

Simple suffix-stripping stemmer (no external dependencies)

Public fields

Methods

Public methods

• SimpleStemmer$stem()

• SimpleStemmer$stem_words()

• SimpleStemmer$clone()

Method stem()

Stem a word

Usage

SimpleStemmer$stem(word)

Arguments

Returns

Stemmed word

Method stem_words()

Stem multiple words

Usage

SimpleStemmer$stem_words(words)

Arguments

Returns

Stemmed words

Method clone()

The objects of this class are cloneable with this method.

Usage

SimpleStemmer$clone(deep = FALSE)

Arguments

Sparse Embedder (BM25/TF-IDF)

Description

Generates sparse BM25 embeddings for keyword search

Public fields

Methods

Public methods

• SparseEmbedder$new()

• SparseEmbedder$fit()

• SparseEmbedder$embed()

• SparseEmbedder$query_terms()

• SparseEmbedder$clone()

Method new()

Create a new SparseEmbedder

Usage

SparseEmbedder$new(language = "en")

Arguments

Method fit()

Fit the embedder on a corpus

Usage

SparseEmbedder$fit(texts)

Arguments

Method embed()

Embed texts to sparse vectors

Usage

SparseEmbedder$embed(texts)

Arguments

Returns

Sparse matrix of BM25 scores

Method query_terms()

Get term scores for a query

Usage

SparseEmbedder$query_terms(query)

Arguments

Returns

Named vector of term scores

Method clone()

The objects of this class are cloneable with this method.

Usage

SparseEmbedder$clone(deep = FALSE)

Arguments

SubGraph

Description

A subset of a knowledge graph

Public fields

Methods

Public methods

• SubGraph$new()

• SubGraph$to_list()

• SubGraph$clone()

Method new()

Create a new SubGraph

Usage

SubGraph$new(entities = list(), relationships = list())

Arguments

Method to_list()

Convert to list

Usage

SubGraph$to_list()

Method clone()

The objects of this class are cloneable with this method.

Usage

SubGraph$clone(deep = FALSE)

Arguments

Text Analyzer

Description

Text analyzer for search indexing

Provides text processing pipelines:

• Tokenization

• Lowercasing

• Stopword removal

• Stemming

• Synonym expansion

Public fields

Methods

Public methods

• TextAnalyzer$new()

• TextAnalyzer$analyze()

• TextAnalyzer$analyze_query()

• TextAnalyzer$clone()

Method new()

Create a new TextAnalyzer

Usage

TextAnalyzer$new(
  lowercase = TRUE,
  remove_stopwords = FALSE,
  stopwords = NULL,
  use_stemmer = FALSE,
  synonyms = NULL,
  min_token_length = 1,
  max_token_length = 100,
  token_pattern = "[a-zA-Z0-9]+"
)

Arguments

Method analyze()

Analyze text and return tokens

Usage

TextAnalyzer$analyze(text)

Arguments

Returns

Character vector of tokens

Method analyze_query()

Analyze a query string

Usage

TextAnalyzer$analyze_query(query)

Arguments

Returns

Character vector of tokens

Method clone()

The objects of this class are cloneable with this method.

Usage

TextAnalyzer$clone(deep = FALSE)

Arguments

Examples

## Not run: 
analyzer <- TextAnalyzer$english()
tokens <- analyzer$analyze("The quick brown foxes are jumping")
# c("quick", "brown", "fox", "jump")

## End(Not run)

Text Unit

Description

A chunk of text from a document

Public fields

Methods

Public methods

• TextUnit$new()

• TextUnit$clone()

Method new()

Create a new TextUnit

Usage

TextUnit$new(
  id,
  text,
  document_id = NULL,
  chunk_index = 0,
  start_char = 0,
  end_char = 0,
  metadata = NULL
)

Arguments

Method clone()

The objects of this class are cloneable with this method.

Usage

TextUnit$clone(deep = FALSE)

Arguments

Vector Cache

Description

Specialized cache for vector search results

Features:

• Query result caching

• Vector embedding caching

• Automatic cache invalidation

Public fields

Methods

Public methods

• VectorCache$new()

• VectorCache$get_search_results()

• VectorCache$set_search_results()

• VectorCache$get_vector()

• VectorCache$set_vector()

• VectorCache$invalidate_vector()

• VectorCache$stats()

• VectorCache$clone()

Method new()

Create a new VectorCache

Usage

VectorCache$new(cache, prefix = "vec:")

Arguments

Method get_search_results()

Get cached search results

Usage

VectorCache$get_search_results(collection, query, filter = NULL, limit = 10)

Arguments

Returns

Cached results or NULL

Method set_search_results()

Cache search results

Usage

VectorCache$set_search_results(
  collection,
  query,
  results,
  filter = NULL,
  limit = 10,
  ttl = 300
)

Arguments

Method get_vector()

Get cached vector

Usage

VectorCache$get_vector(collection, vector_id)

Arguments

Returns

Cached vector data or NULL

Method set_vector()

Cache vector data

Usage

VectorCache$set_vector(collection, vector_id, data, ttl = 3600)

Arguments

Method invalidate_vector()

Invalidate cached vector

Usage

VectorCache$invalidate_vector(collection, vector_id)

Arguments

Method stats()

Get cache statistics

Usage

VectorCache$stats()

Returns

CacheStats object

Method clone()

The objects of this class are cloneable with this method.

Usage

VectorCache$clone(deep = FALSE)

Arguments

VectrixDB Easy API - The Simplest Vector Database

Description

Zero config. Text in, results out. One line for everything.

Public fields

Methods

Public methods

• Vectrix$new()

• Vectrix$add()

• Vectrix$set_language()

• Vectrix$search()

• Vectrix$delete()

• Vectrix$clear()

• Vectrix$count()

• Vectrix$get()

• Vectrix$similar()

• Vectrix$close()

• Vectrix$print()

• Vectrix$clone()

Method new()

Create or open a VectrixDB collection

Usage

Vectrix$new(
  name = "default",
  path = NULL,
  model = NULL,
  dimension = NULL,
  embed_fn = NULL,
  model_path = NULL,
  language = NULL,
  tier = "dense",
  auto_download = TRUE
)

Arguments

Examples

\dontrun{
# Default TF-IDF embeddings (no external files needed)
db <- Vectrix$new("docs")

# With GloVe 100d word vectors (auto-downloads ~130MB)
db <- Vectrix$new("docs", model = "glove-100")

# With pre-downloaded GloVe
db <- Vectrix$new("docs", model_path = "path/to/glove.6B.100d.txt")

# Custom embedding function
db <- Vectrix$new("docs", embed_fn = my_embed_function, dimension = 768)
}

Method add()

Add texts to the collection

Usage

Vectrix$add(texts, metadata = NULL, ids = NULL)

Arguments

Returns

Self for chaining

Examples

\dontrun{
db$add(c("text 1", "text 2"))
db$add("another text", metadata = list(source = "web"))
}

Method set_language()

Update collection language behavior

Usage

Vectrix$set_language(language = "en")

Arguments

Returns

Self for chaining

Method search()

Search the collection

Usage

Vectrix$search(
  query,
  limit = 10,
  mode = "hybrid",
  rerank = NULL,
  filter = NULL,
  diversity = 0.7
)

Arguments

Returns

Results object with search results

Examples

\dontrun{
results <- db$search("python programming")
results <- db$search("AI", mode = "ultimate", rerank = "mmr")
print(results$top()$text)
}

Method delete()

Delete documents by ID

Usage

Vectrix$delete(ids)

Arguments

Returns

Self for chaining

Method clear()

Clear all documents from collection

Usage

Vectrix$clear()

Returns

Self for chaining

Method count()

Get number of documents

Usage

Vectrix$count()

Returns

Integer count

Method get()

Get documents by ID

Usage

Vectrix$get(ids)

Arguments

Returns

List of Result objects

Method similar()

Find similar documents to a given document

Usage

Vectrix$similar(id, limit = 10)

Arguments

Returns

Results object

Method close()

Close the database connection

Usage

Vectrix$close()

Method print()

Print Vectrix summary

Usage

Vectrix$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

Vectrix$clone(deep = FALSE)

Arguments

Examples

## Not run: 
# Create and add - ONE LINE
db <- Vectrix$new("my_docs")$add(c("Python is great", "Machine learning is fun"))

# Search - ONE LINE
results <- db$search("programming")

# Full power - STILL ONE LINE
results <- db$search("AI", mode = "ultimate")  # dense + sparse + rerank

## End(Not run)


## ------------------------------------------------
## Method `Vectrix$new`
## ------------------------------------------------

## Not run: 
# Default TF-IDF embeddings (no external files needed)
db <- Vectrix$new("docs")

# With GloVe 100d word vectors (auto-downloads ~130MB)
db <- Vectrix$new("docs", model = "glove-100")

# With pre-downloaded GloVe
db <- Vectrix$new("docs", model_path = "path/to/glove.6B.100d.txt")

# Custom embedding function
db <- Vectrix$new("docs", embed_fn = my_embed_function, dimension = 768)

## End(Not run)

## ------------------------------------------------
## Method `Vectrix$add`
## ------------------------------------------------

## Not run: 
db$add(c("text 1", "text 2"))
db$add("another text", metadata = list(source = "web"))

## End(Not run)

## ------------------------------------------------
## Method `Vectrix$search`
## ------------------------------------------------

## Not run: 
results <- db$search("python programming")
results <- db$search("AI", mode = "ultimate", rerank = "mmr")
print(results$top()$text)

## End(Not run)

VectrixDB Database Class

Description

Main database interface managing collections

Usage

vectrixdb(path = NULL, storage_type = "memory")

Arguments

Value

VectrixDB object

Public fields

Methods

Public methods

• VectrixDB$new()

• VectrixDB$create_collection()

• VectrixDB$get_collection()

• VectrixDB$list_collections()

• VectrixDB$delete_collection()

• VectrixDB$has_collection()

• VectrixDB$stats()

• VectrixDB$close()

• VectrixDB$print()

• VectrixDB$clone()

Method new()

Create or open a VectrixDB database

Usage

VectrixDB$new(path = NULL, storage_type = "memory")

Arguments

Method create_collection()

Create a new collection

Usage

VectrixDB$create_collection(
  name,
  dimension,
  metric = "cosine",
  enable_text_index = TRUE
)

Arguments

Returns

Collection object

Method get_collection()

Get an existing collection

Usage

VectrixDB$get_collection(name)

Arguments

Returns

Collection object

Method list_collections()

List all collections

Usage

VectrixDB$list_collections()

Returns

Character vector of collection names

Method delete_collection()

Delete a collection

Usage

VectrixDB$delete_collection(name)

Arguments

Method has_collection()

Check if collection exists

Usage

VectrixDB$has_collection(name)

Arguments

Returns

Logical

Method stats()

Get database statistics

Usage

VectrixDB$stats()

Returns

List with stats

Method close()

Close the database

Usage

VectrixDB$close()

Method print()

Print database summary

Usage

VectrixDB$print()

Method clone()

The objects of this class are cloneable with this method.

Usage

VectrixDB$clone(deep = FALSE)

Arguments

Create ACL Config from List

Description

Create ACLConfig from list of ACL strings

Usage

acl_config_from_list(acl_list)

Arguments

Value

ACLConfig object

VectrixDB Advanced Search Features

Description

Enterprise-grade search capabilities:

• Faceted search with aggregations

• ACL/Security filtering

• Text analyzers (stemming, synonyms, stopwords)

VectrixDB Cache Layer

Description

High-performance caching for low latency

Supports multiple cache backends:

• InMemory LRU: Ultra-fast, limited by RAM

• File-based: Persistent cache using RDS files

Create Cache Config from Environment

Description

Create config from environment variables

Usage

cache_config_from_env()

Value

CacheConfig object

Check if Python module is available

Description

Check if Python module is available

Usage

check_python_module(module)

Arguments

Value

Logical

VectrixDB Command Line Interface

Description

CLI tools for VectrixDB operations

Provides command-line style functions for:

• Creating and managing collections

• Adding and searching documents

• Exporting and importing data

• Database statistics and info

Print CLI Message

Description

Print CLI Message

Usage

cli_print(msg, type = "info")

Arguments

Print Table

Description

Print Table

Usage

cli_table(df, max_rows = 20)

Arguments

Compute cosine similarity

Description

Compute cosine similarity

Usage

cosine_similarity(query_vector, doc_vectors)

Arguments

Value

Numeric vector of similarities

Create Cache

Description

Factory function to create cache backend

Usage

create_cache(config = NULL)

Arguments

Value

Cache object

Create Default GraphRAG Config

Description

Create default config with regex extractor

Usage

create_default_graphrag_config(...)

Arguments

Value

GraphRAGConfig object

Create HNSW Index

Description

Factory function to create HNSW index

Usage

create_hnsw_index(dimension, metric = "angular", n_trees = 50)

Arguments

Value

HNSWIndex object

Create GraphRAG Pipeline

Description

Factory function for GraphRAGPipeline

Usage

create_pipeline(config = NULL)

Arguments

Value

GraphRAGPipeline object

Create a sentence embedder with automatic download

Description

Convenience function to create a SentenceEmbedder with GloVe vectors

Usage

create_sentence_embedder(model = "glove-100", use_idf = TRUE)

Arguments

Value

SentenceEmbedder object

Examples

## Not run: 
# Downloads GloVe if not present
embedder <- create_sentence_embedder("glove-100")

# Embed texts
vectors <- embedder$embed(c("Hello world", "Machine learning is cool"))

## End(Not run)

Create Vector Cache

Description

Create a VectorCache with specified backend

Usage

create_vector_cache(backend = "memory", ...)

Arguments

Value

VectorCache object

Download pre-trained word vectors

Description

Download GloVe or other pre-trained word vectors

Usage

download_vectors(model = "glove-50", dest_dir = NULL)

Arguments

Value

Path to downloaded model

Download pre-trained word vectors

Description

Downloads GloVe or fastText word vectors

Usage

download_word_vectors(model = "glove-100", dest_dir = NULL, overwrite = FALSE)

Arguments

Value

Path to the downloaded vectors file

Examples

## Not run: 
# Download 100-dimensional GloVe vectors (~130MB)
path <- download_word_vectors("glove-100")

# Use with Vectrix
db <- Vectrix$new("docs", model = "glove", model_path = path)

## End(Not run)

VectrixDB Embedders (Pure R Implementation)

Description

Embedding models for text vectorization using R-native packages

Compute euclidean distance

Description

Compute euclidean distance

Usage

euclidean_distance(query_vector, doc_vectors)

Arguments

Value

Numeric vector of distances

Format time duration

Description

Format time duration

Usage

format_time(ms)

Arguments

Value

Formatted string

Generate deterministic ID from text

Description

Generate deterministic ID from text

Usage

generate_id(text)

Arguments

Value

Character string (12 character MD5 hash prefix)

Get CLI Config

Description

Get CLI Config

Usage

get_cli_config()

Value

CLIConfig object

VectrixDB GraphRAG Module

Description

Native GraphRAG implementation for VectrixDB

Features:

• Entity and relationship extraction

• Hierarchical community detection

• Local, global, and hybrid search strategies

• Incremental graph updates

VectrixDB HNSW Index

Description

Hierarchical Navigable Small World graph for fast approximate nearest neighbor search

Uses RcppAnnoy for high-performance ANN search. Falls back to brute-force search if RcppAnnoy is not available.

Load GloVe text format

Description

Load GloVe text format

Usage

load_glove_text(path, max_words = NULL, normalize = TRUE)

Load HNSW Index

Description

Load saved index from file

Usage

load_hnsw_index(path)

Arguments

Value

HNSWIndex object

Load word2vec binary format

Description

Load word2vec binary format

Usage

load_word2vec_binary(path, max_words = NULL, normalize = TRUE)

Load word vectors into memory

Description

Loads pre-trained word vectors from a file

Usage

load_word_vectors(path, max_words = NULL, normalize = TRUE)

Arguments

Value

WordVectors object

Maximal Marginal Relevance (MMR) reranking

Description

Maximal Marginal Relevance (MMR) reranking

Usage

mmr_rerank(
  query_vector,
  doc_vectors,
  doc_ids,
  scores,
  lambda = 0.7,
  limit = 10
)

Arguments

Value

Data frame with reranked results

Normalize language tag to supported values

Description

Normalize language tag to supported values

Usage

normalize_language_tag(language = NULL, default = "en")

Arguments

Value

"en" or "ml"

Normalize vectors for cosine similarity

Description

Normalize vectors for cosine similarity

Usage

normalize_vectors(vectors)

Arguments

Value

Normalized matrix

Parse ACL String

Description

Parse ACL string like 'user:alice' or 'group:engineering'

Usage

parse_acl(acl_string)

Arguments

Value

ACLPrincipal object

Quick search - Index texts and search immediately

Description

Quick search - Index texts and search immediately

Usage

quick_search(texts, query, limit = 5)

Arguments

Value

Results object

Examples

## Not run: 
results <- quick_search(
  texts = c("Python is great", "Java is verbose", "Rust is fast"),
  query = "programming language"
)
print(results$top()$text)

## End(Not run)

Load word2vec model via optional runtime namespace lookup

Description

Load word2vec model via optional runtime namespace lookup

Usage

read_word2vec_model(path, normalize = TRUE)

Arguments