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Crate argentor_memory

Crate argentor_memory 

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Vector-based semantic memory with hybrid search and query expansion.

Provides persistent vector storage, local embedding generation, BM25 keyword scoring, hybrid (embedding + BM25) search, and rule-based query expansion for improved recall.

§Main types

  • VectorStore — Trait for storing and querying embedding vectors.
  • FileVectorStore — File-backed persistent vector store.
  • LocalEmbedding — Local TF-IDF-based embedding provider.
  • HybridSearcher — Combines embedding similarity with BM25 keyword scoring.
  • Bm25Index — BM25 inverted index for keyword-based retrieval.
  • QueryExpander — Trait for expanding queries to improve search recall.
  • RagPipeline — Retrieval-Augmented Generation pipeline for knowledge base search.

Re-exports§

pub use bm25::Bm25Index;
pub use conversation::ConversationMemory;
pub use conversation::ConversationSummarizer;
pub use conversation::ConversationTurn;
pub use conversation::CustomerProfile;
pub use embedding::EmbeddingProvider;
pub use embedding::LocalEmbedding;
pub use embeddings_providers::parse_cohere_embedding_response;
pub use embeddings_providers::parse_openai_embedding_response;
pub use embeddings_providers::parse_voyage_embedding_response;
pub use embeddings_providers::BatchEmbeddingProvider;
pub use embeddings_providers::CacheStats;
pub use embeddings_providers::CachedEmbeddingProvider;
pub use embeddings_providers::CohereEmbedV4Provider;
pub use embeddings_providers::CohereEmbeddingProvider;
pub use embeddings_providers::EmbeddingConfig;
pub use embeddings_providers::EmbeddingProviderFactory;
pub use embeddings_providers::JinaEmbeddingProvider;
pub use embeddings_providers::MistralEmbedProvider;
pub use embeddings_providers::NomicEmbedProvider;
pub use embeddings_providers::OpenAiEmbeddingProvider;
pub use embeddings_providers::SentenceTransformersProvider;
pub use embeddings_providers::TogetherEmbedProvider;
pub use embeddings_providers::VoyageEmbeddingProvider;
pub use hybrid::HybridSearcher;
pub use knowledge_graph::Entity;
pub use knowledge_graph::EntityType;
pub use knowledge_graph::GraphSummary;
pub use knowledge_graph::KnowledgeGraph;
pub use knowledge_graph::RelationType;
pub use knowledge_graph::Relationship;
pub use pgvector::PgVectorStore;
pub use pinecone::PineconeStore;
pub use qdrant::QdrantStore;
pub use query_expansion::QueryExpander;
pub use query_expansion::RuleBasedExpander;
pub use rag::ChunkingStrategy;
pub use rag::Document;
pub use rag::DocumentChunk;
pub use rag::RagConfig;
pub use rag::RagPipeline;
pub use rag::RagResult;
pub use rag::ScoredChunk;
pub use store::FileVectorStore;
pub use store::InMemoryVectorStore;
pub use store::MemoryEntry;
pub use store::SearchResult;
pub use store::VectorStore;
pub use tiered::MemoryContext;
pub use tiered::ScoredMemory;
pub use tiered::TieredMemory;
pub use tiered::TieredMemoryConfig;
pub use tiered::TieredTurn;
pub use weaviate::WeaviateStore;

Modules§

bm25
BM25 inverted index for keyword-based retrieval.
conversation
Conversation memory for cross-session customer context. Conversation memory system for cross-session customer context.
embedding
Embedding provider trait and local implementation.
embeddings_providers
Multiple embedding provider backends (OpenAI, Cohere, Voyage, cached, batch, factory). Multiple embedding provider backends implementing EmbeddingProvider.
hybrid
Hybrid search combining embeddings and BM25.
knowledge_graph
Knowledge graph for entity-relationship-based memory. In-memory knowledge graph for entity-relationship storage.
pgvector
pgvector (PostgreSQL extension) vector store adapter. pgvector (PostgreSQL extension) vector store adapter.
pinecone
Pinecone vector store adapter. Pinecone vector store adapter.
qdrant
Qdrant vector store adapter. Qdrant vector store adapter.
query_expansion
Query expansion for improved recall.
rag
Retrieval-Augmented Generation pipeline. Retrieval-Augmented Generation (RAG) pipeline for knowledge base search.
store
Vector store trait and file-backed implementation.
tiered
Multi-tier memory: short-term, long-term (episodic), and entity memory. Multi-tier memory system: short-term (working), long-term (episodic), and entity memory.
weaviate
Weaviate vector store adapter. Weaviate vector store adapter.