ReasonKit Mem

Memory & Retrieval Infrastructure for ReasonKit

The Long-Term Memory Layer ("Hippocampus") for AI Reasoning

Documentation | ReasonKit Core | Website

ReasonKit Mem is the memory layer ("Hippocampus") for ReasonKit. It provides vector storage, hybrid search, RAPTOR trees, and embedding support.

Features

• Vector Storage - Qdrant-based dense vector storage with embedded mode
• Hybrid Search - Dense (Qdrant) + Sparse (Tantivy BM25) fusion
• RAPTOR Trees - Hierarchical retrieval for long-form QA
• Embeddings - Local (BGE-M3) and remote (OpenAI) embedding support
• Reranking - Cross-encoder reranking for precision

Installation

Add to your Cargo.toml:

[dependencies]
reasonkit-mem = "0.1"
tokio = { version = "1", features = ["full"] }

Usage

Basic Usage (Embedded Mode)

use reasonkit_mem::storage::Storage;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Create embedded storage (automatic file storage fallback)
    let storage = Storage::new_embedded().await?;

    // Use storage...
    Ok(())
}

Advanced Usage (Custom Configuration)

use reasonkit_mem::{
    storage::{Storage, EmbeddedStorageConfig},
    embedding::EmbeddingProvider,
    retrieval::HybridRetriever,
    Document, RetrievalConfig,
};
use std::path::PathBuf;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Create storage with custom config
    let config = EmbeddedStorageConfig::file_only(PathBuf::from("./data"));
    let storage = Storage::new_embedded_with_config(config).await?;

    // Or use Qdrant (requires running server)
    let qdrant_config = EmbeddedStorageConfig::with_qdrant(
        "http://localhost:6333",
        "my_collection",
        1536,
    );
    let storage = Storage::new_embedded_with_config(qdrant_config).await?;

    // Index documents
    storage.store_document(&doc, &context).await?;

    // Hybrid search
    let retriever = HybridRetriever::new(storage.clone());
    let results = retriever.search("query", &RetrievalConfig::default()).await?;

    Ok(())
}

Embedded Mode Documentation

For detailed information about embedded mode, see docs/EMBEDDED_MODE_GUIDE.md.

Architecture

+---------------------------------------------------------------------+
|                      HYBRID RETRIEVAL                               |
+---------------------------------------------------------------------+
|                                                                     |
|   Query --+---> [Dense Encoder] ---> Qdrant ANN ---> Top-K Dense   |
|           |                                                         |
|           +---> [BM25 Tokenizer] ---> Tantivy ---> Top-K Sparse    |
|                                                                     |
|                       v                                             |
|            +----------------------+                                 |
|            | Reciprocal Rank Fusion|                                |
|            +----------+-----------+                                 |
|                       v                                             |
|            +----------------------+                                 |
|            | Cross-Encoder Rerank |                                 |
|            +----------+-----------+                                 |
|                       v                                             |
|                 Final Results                                       |
+---------------------------------------------------------------------+

Technology Stack

Project Structure

reasonkit-mem/
├── src/
│   ├── storage/      # Qdrant vector + file-based storage
│   ├── embedding/    # Dense vector embeddings
│   ├── retrieval/    # Hybrid search, fusion, reranking
│   ├── raptor/       # RAPTOR hierarchical tree structure
│   ├── indexing/     # BM25/Tantivy sparse indexing
│   └── rag/          # RAG pipeline orchestration
├── benches/          # Performance benchmarks
├── examples/         # Usage examples
├── docs/             # Additional documentation
└── Cargo.toml

Feature Flags

License

Apache License 2.0 - see LICENSE

Part of the ReasonKit Ecosystem

ReasonKit Core | ReasonKit Web | Website

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