Welcome to the official Rust examples repository for SochDB, the high-performance embedded database designed for AI applications.
Complete, production-ready examples using the official sochdb crate from crates.io.
| Directory | Description |
|---|---|
sochdb-examples/ |
Comprehensive examples using sochdb 0.4.0 from crates.io |
sochdb-rag-example/ |
Full RAG pipeline with Azure OpenAI integration |
- Rust 1.70+ (2021 edition)
- Cargo
cd sochdb-examples
cargo run --releaseThe basic examples demonstrate:
- ✅ Basic key-value operations (Put, Get, Delete)
- ✅ Path-based hierarchical keys
- ✅ Database statistics
- ✅ Using the published crate from crates.io
Add to your Cargo.toml:
[dependencies]
sochdb = "0.4.0"
anyhow = "1"Example code:
use sochdb::Database;
use anyhow::Result;
fn main() -> Result<()> {
// Open database
let db = Database::open("./mydb")?;
// Basic operations
db.put(b"key", b"value")?;
let value = db.get(b"key")?;
// Path-based keys
db.put_path("users/alice/email", b"[email protected]")?;
let email = db.get_path("users/alice/email")?;
Ok(())
}See sochdb-rag-example/ for a complete Retrieval-Augmented Generation system using:
- SochDB as the vector store
- Azure OpenAI for embeddings and chat
- Document chunking and ingestion
Contributions are welcome! Please feel free to submit a Pull Request.
Apache 2.0 - see LICENSE for details. Best for: Users migrating from Zep or needing entity-centric memory.
- Entity Extraction: Automatically extracts and stores named entities (People, Organizations) alongside conversation history.
- User Management: Manages user profiles and metadata associated with conversation threads.
Best for: Managing LLM context under strict token budgets.
- Priority-Based Truncation: Intelligently fits system message, query, history, and retrieval results within token limits.
- Token Budget Management: Automatically truncates lower-priority content when space is tight.
- TOON Integration: Demonstrates using
Database.to_toon()for ultra-compact retrieval formatting. - Flexible Assembly: Supports different priority levels for different content types.
Simple examples demonstrating basic CRUD operations, SQL usage, and connection handling.
| Language | Directory | Description |
|---|---|---|
| Node.js | toondb_node_examples/ |
JavaScript examples for Node.js, showing setup, basic operations, and SQL. |
| Rust | toondb_rust_examples/ |
Rust native examples showing how to embed ToonDB directly. |
| Go | External Repo → | Go examples are maintained in a separate repository. |
Choose your preferred language and navigate to the corresponding directory. Each example folder contains its own README.md with specific setup and running instructions.
- ToonDB Server: For Go, Node.js, and Python SDKs, ensure the
toondbortoondb-serverbinary is installed and available in your system'sPATH.- Python:
pip install toondb-client(includes binaries) - Go:
go install github.com/toondb/toondb/cmd/toondb@latest - Rust: Uses the library directly.
- Python:
- Language Runtimes: Python 3.10+, Node.js 18+, Go 1.21+, or Rust 1.75+ depending on the example.
- API Keys: For RAG examples, you will need an Azure OpenAI API key (or compatible OpenAI endpoint).
- Vector Search: Using ToonDB's HNSW index for fast similarity search.
- Persistence: Storing embeddings and metadata reliably on disk.
- Hybrid Search: Combining vector search with structured filtering (in applicable SDKs).
- Multi-Language Support: Consistent API usage patterns across Python, TS/JS, Go, and Rust.
Feel free to submit Pull Requests with new examples or improvements to existing ones!
Apache License 2.0 - see the LICENSE file for details.
Some of the agent memory examples (Wizard of Oz, Podcast, Zep ports) are referenced and adapted from the following projects: