seekdb-rs – Rust SDK for SeekDB (Server Mode)

Also available in: 简体中文

seekdb-rs is the official Rust SDK for SeekDB, currently focused on the Server mode and talking to SeekDB / OceanBase over the MySQL protocol.
The APIs are designed to closely mirror the Python SDK (pyseekdb), but this crate is still experimental / incomplete and may evolve.

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Table of Contents

1. Installation
2. Client Connection
3. AdminClient and Database Management
4. Collection Management
5. DML Operations
6. DQL Operations
7. Embedding Functions
8. Sync Client
9. Testing
10. Feature Matrix

---

Installation

seekdb-rs is published on crates.io. The usual way to use it is to depend on the released crate:

# Cargo.toml in your application / workspace crate
[dependencies]
seekdb-rs = "0.1"

If you are hacking on the SDK in this repository, you can instead use a local path dependency:

[dependencies]
seekdb-rs = { path = "/path/to/seekdb-rs" } # adjust to where you cloned this repo

Build:

cargo build

Features:

• server (enabled by default): async client for the remote SeekDB / OceanBase server.
• embedding (enabled by default): built‑in ONNX‑based embedding implementation (DefaultEmbedding), depends on reqwest / tokenizers / ort / hf-hub.
• sync (optional): blocking wrapper around the async client (SyncServerClient, SyncCollection), backed by an internal Tokio runtime.

Example enabling sync and embedding explicitly from crates.io:

[dependencies]
seekdb-rs = { version = "0.1", features = ["server", "embedding", "sync"] }

---

1. Client Connection

The Python SDK exposes a single Client factory that hides embedded vs remote server.
In Rust we currently only support the remote server client, represented by ServerClient.

Embedded mode (equivalent to Python’s embedded client) is not implemented in Rust yet.

1.1 Connecting with ServerClient

use seekdb_rs::{ServerClient, SeekDbError};

#[tokio::main]
async fn main() -> Result<(), SeekDbError> {
    // Build a client using a fluent builder
    let client = ServerClient::builder()
        .host("127.0.0.1") // host
        .port(2881)        // port
        .tenant("sys")     // tenant
        .database("demo")  // database
        .user("root")      // user (without tenant suffix)
        .password("")      // password
        .max_connections(5)
        .build()
        .await?;

    // Run an arbitrary SQL statement
    let _ = client.execute("SELECT 1").await?;
    Ok(())
}

The Rust ServerClient behaves similarly to Python’s RemoteServerClient:

• Uses user@tenant behind the scenes to connect.
• Talks to SeekDB / OceanBase via the MySQL protocol.

1.2 Configuration from Environment Variables

For parity with Python’s “read config from environment variables” pattern, Rust exposes ServerConfig::from_env() and helpers on ServerClient.

Environment variables:

• SERVER_HOST
• SERVER_PORT (default: 2881)
• SERVER_TENANT
• SERVER_DATABASE
• SERVER_USER
• SERVER_PASSWORD
• SERVER_MAX_CONNECTIONS (default: 5)

export SERVER_HOST=127.0.0.1
export SERVER_PORT=2881
export SERVER_TENANT=sys
export SERVER_DATABASE=demo
export SERVER_USER=root
export SERVER_PASSWORD=your_password

use seekdb_rs::{ServerClient, ServerConfig, SeekDbError};

#[tokio::main]
async fn main() -> Result<(), SeekDbError> {
    // Build config from env
    let config = ServerConfig::from_env()?;

    // Connect from config
    let client = ServerClient::from_config(config).await?;

    // Or in a single step:
    let client = ServerClient::from_env().await?;

    // Or mix env defaults with manual overrides
    let client = ServerClient::builder()
        .from_env()? // prefill from env
        .database("demo_override")
        .build()
        .await?;

    client.execute("SELECT 1").await?;
    Ok(())
}

1.3 Core Methods

There is no universal “mode‑switching” Client type in Rust; use ServerClient directly.

Key async APIs:

Method / Property	Description
ServerClient::builder()	Fluent builder for creating a remote client
ServerClient::from_config(ServerConfig)	Connect from an explicit config
ServerClient::from_env()	Load config from env and connect
ServerClient::pool()	Access the underlying MySqlPool
ServerClient::tenant() / database()	Inspect current tenant / database
ServerClient::execute(sql)	Execute a statement that does not return rows (INSERT / UPDATE /…)
ServerClient::fetch_all(sql)	Execute a query and return all rows
ServerClient::create_collection(...)	Create a collection (see below)
ServerClient::get_collection(...)	Get a Collection handle for an existing collection
ServerClient::get_or_create_collection(...)	Get or create a collection
ServerClient::delete_collection(name)	Drop a collection
ServerClient::list_collections()	List all collection names in the current database
ServerClient::has_collection(name)	Check if a collection exists
ServerClient::count_collection()	Count collections in the current database

---

2. AdminClient and Database Management

Python exposes an AdminClient for managing databases. Rust provides:

• AdminApi trait: abstract admin interface.
• AdminClient: thin wrapper around ServerClient.
• ServerClient itself implements AdminApi, so you can call admin methods on it directly.

2.1 Creating an AdminClient

use seekdb_rs::{AdminClient, AdminApi, ServerClient, ServerConfig, SeekDbError};
use std::sync::Arc;

#[tokio::main]
async fn main() -> Result<(), SeekDbError> {
    let config = ServerConfig::from_env()?;
    let client = ServerClient::from_config(config).await?;

    // Use a dedicated AdminClient (holds Arc<ServerClient>)
    let admin = AdminClient::new(Arc::new(client));

    // Or call the same methods directly on ServerClient
    // let admin: &dyn AdminApi = &client;

    Ok(())
}

2.2 Database CRUD APIs

// Create a database
admin.create_database("my_db", Some("sys")).await?;

// Get metadata
let db = admin.get_database("my_db", Some("sys")).await?;
println!("name = {}, tenant = {:?}", db.name, db.tenant);

// List databases (with optional limit/offset/tenant)
let list = admin.list_databases(None, None, None).await?;

// Delete database
admin.delete_database("my_db", Some("sys")).await?;

Database corresponds to the Python struct:

pub struct Database {
    pub name: String,
    pub tenant: Option<String>,
    pub charset: Option<String>,
    pub collation: Option<String>,
}

---

3. Collection Management

Collection<Ef> in Rust mirrors Python’s Collection class, with a few important differences:

• Rust uses a generic parameter: Collection<Ef = Box<dyn EmbeddingFunction>>.
• All operations are async and return Result<_, SeekDbError>.
• With the sync feature enabled you also get SyncCollection<Ef> as a blocking wrapper.

3.1 Creating a Collection

When creating a collection you must provide HnswConfig (dimension + distance metric):

use seekdb_rs::{DistanceMetric, HnswConfig, ServerClient, SeekDbError};

#[tokio::main]
async fn main() -> Result<(), SeekDbError> {
    let config = seekdb_rs::ServerConfig::from_env()?;
    let client = ServerClient::from_config(config).await?;

    let hnsw = HnswConfig {
        dimension: 384,
        distance: DistanceMetric::Cosine,
    };

    // Create a collection without automatic embeddings
    let coll = client
        .create_collection::<Box<dyn seekdb_rs::EmbeddingFunction>>(
            "my_collection",
            Some(hnsw),
            None,
        )
        .await?;

    Ok(())
}

If HnswConfig is missing, collection creation fails with: SeekDbError::Config("HnswConfig must be provided when creating a collection").

3.2 Getting a Collection

let coll = client
    .get_collection::<Box<dyn seekdb_rs::EmbeddingFunction>>("my_collection", None)
    .await?;

println!(
    "Collection name = {}, dim = {}, distance = {:?}",
    coll.name(),
    coll.dimension(),
    coll.distance()
);

Under the hood, SeekDB is introspected using DESCRIBE / SHOW CREATE TABLE:

• Vector dimension is parsed from the embedding column type (e.g. vector(384)).
• Distance metric is parsed from the vector index options (e.g. distance=cosine).

3.3 Listing / Counting / Deleting Collections

// List all collections
let names = client.list_collections().await?;

// Count collections
let count = client.count_collection().await?;

// Check existence
if client.has_collection("my_collection").await? {
    println!("collection exists");
}

// Drop collection
client.delete_collection("my_collection").await?;

3.4 Collection Properties

Collection<Ef> exposes a few read‑only accessors:

• name() -> &str
• id() -> Option<&str> (internal ID; table name still uses c$v1$ prefix)
• dimension() -> u32
• distance() -> DistanceMetric
• metadata() -> Option<&serde_json::Value>

---

4. DML Operations

Rust implements DML operations with semantics close to Python:

• Explicit embeddings are always supported.
• When a collection has an embedding_function, add / update / upsert can generate embeddings automatically from documents.

4.1 add – insert new rows

use seekdb_rs::{Embedding, Metadata};
use serde_json::json;

let ids = vec!["item1".to_string(), "item2".to_string()];
let embeddings: Vec<Embedding> = vec![vec![0.1, 0.2, 0.3], vec![0.4, 0.5, 0.6]];
let documents = vec!["Document 1".to_string(), "Document 2".to_string()];
let metadatas: Vec<Metadata> = vec![
    json!({"category": "AI", "score": 95}),
    json!({"category": "ML", "score": 88}),
];

coll.add(&ids, Some(&embeddings), Some(&metadatas), Some(&documents))
    .await?;

When the collection was created with an EmbeddingFunction, you can skip the embeddings parameter and let the SDK embed the documents:

use seekdb_rs::{DistanceMetric, HnswConfig, ServerClient, embedding::DefaultEmbedding};

let config = seekdb_rs::ServerConfig::from_env()?;
let client = ServerClient::from_config(config).await?;

// Requires the `embedding` feature
let ef = DefaultEmbedding::new()?;
let hnsw = HnswConfig {
    dimension: ef.dimension() as u32,
    distance: DistanceMetric::Cosine,
};

let coll = client
    .create_collection::<DefaultEmbedding>("auto_emb", Some(hnsw), Some(ef))
    .await?;

let ids = vec!["auto1".to_string(), "auto2".to_string()];
let docs = vec!["hello rust".to_string(), "seekdb vector".to_string()];

// No explicit embeddings: documents are embedded automatically
coll.add(&ids, None, None, Some(&docs)).await?;

4.2 update – update existing rows

// Metadata‑only update
coll.update(
    &["item1".to_string()],
    None,
    Some(&[serde_json::json!({"category": "AI", "score": 98})]),
    None,
)
.await?;

// Update embeddings + metadata + documents
coll.update(
    &["item1".to_string(), "item2".to_string()],
    Some(&[vec![0.9, 0.8, 0.7], vec![0.6, 0.5, 0.4]]),
    Some(&[
        serde_json::json!({"category": "AI"}),
        serde_json::json!({"category": "ML"}),
    ]),
    Some(&[
        "Updated document 1".to_string(),
        "Updated document 2".to_string(),
    ]),
)
.await?;

Validation rules:

• embeddings (if present) must match ids in length.
• Each embedding must have the same dimension as Collection::dimension().
• documents / metadatas can be omitted; only provided fields are updated.
• If no embeddings are provided but documents are, and the collection has an embedding_function, the SDK generates embeddings automatically.

4.3 upsert – insert or update

let id = "item1".to_string();

// 1) Insert
coll.upsert(
    &[id.clone()],
    Some(&[vec![1.0, 2.0, 3.0]]),
    Some(&[serde_json::json!({"tag": "init", "cnt": 1})]),
    Some(&["doc1".to_string()]),
)
.await?;

// 2) Metadata‑only upsert: keep doc and embedding
coll.upsert(
    &[id.clone()],
    None,
    Some(&[serde_json::json!({"tag": "init", "cnt": 2})]),
    None,
)
.await?;

// 3) Document‑only upsert
coll.upsert(
    &[id.clone()],
    None,
    None,
    Some(&["new_doc".to_string()]),
)
.await?;

Semantics:

• ids must be non‑empty.
• If embeddings / documents / metadatas are all None, you get SeekDbError::InvalidInput.
• When the row exists:
  • Only fields provided in the call are updated.
  • Others keep their previous values.
• When the row does not exist:
  • A new row is inserted; missing fields use default values (NULL / empty).
  • If only documents are given and the collection has an embedding_function, embeddings are generated; otherwise only the document field is updated.

4.4 delete

Rust mirrors Python’s collection.delete(ids=..., where=..., where_document=...) using strongly typed filters.

use seekdb_rs::{Filter, DocFilter};
use serde_json::json;

// Delete by IDs
coll.delete(Some(&vec!["id1".to_string(), "id2".to_string()]), None, None)
    .await?;

// Delete by metadata filter
let where_meta = Filter::Gte {
    field: "score".into(),
    value: json!(90),
};
coll.delete(None, Some(&where_meta), None).await?;

// Delete by document filter
let where_doc = DocFilter::Contains("machine learning".into());
coll.delete(None, None, Some(&where_doc)).await?;

If all of ids, where_meta, and where_doc are None, SeekDbError::InvalidInput is returned.

---

5. DQL Operations

On the Python side, collections expose query (vector search), get (filtered read), and hybrid_search. Rust supports the same concepts:

• query_embeddings – search using explicit query embeddings.
• query_texts – search using raw text; embeddings are computed using the collection’s EmbeddingFunction.
• get – filter‑only reads.
• hybrid_search / hybrid_search_advanced – hybrid vector + text + metadata search.

You will find the complete set of examples (including hybrid search and filter operators) in the Simplified Chinese README: README_zh-CN.md.

---

6. Embedding Functions

Python defines an EmbeddingFunction protocol and ships a default ONNX model.
Rust mirrors this with an EmbeddingFunction trait and an optional DefaultEmbedding implementation behind the embedding feature.

6.1 EmbeddingFunction trait

use seekdb_rs::{EmbeddingFunction, Embeddings, Result};

#[async_trait::async_trait]
pub trait EmbeddingFunction: Send + Sync {
    async fn embed_documents(&self, docs: &[String]) -> Result<Embeddings>;
    fn dimension(&self) -> usize;
}

You can implement this trait for your own models (local, remote, or SaaS).
When attached to a collection, it is used for:

• add / update / upsert when you only pass documents.
• query_texts and text‑based hybrid_search.

6.2 Default ONNX embedding (optional)

With the embedding feature enabled, seekdb-rs provides a built‑in DefaultEmbedding based on an ONNX export of a sentence‑transformers model (similar to all-MiniLM-L6-v2):

use seekdb_rs::embedding::DefaultEmbedding;

let ef = DefaultEmbedding::new()?;        // model is downloaded / loaded on demand
let dim = ef.dimension();                 // e.g. 384
let embs = ef.embed_documents(&["hello".into(), "world".into()]).await?;

---

7. Sync Client (optional sync feature)

For codebases that cannot adopt async/await yet, the sync feature enables blocking wrappers SyncServerClient and SyncCollection. They internally own a Tokio runtime and simply block_on the async implementations.

[dependencies]
seekdb-rs = { path = "/path/to/seekdb-rs", features = ["sync"] }

use seekdb_rs::{ServerConfig, SyncServerClient, SyncCollection, SeekDbError};

fn main() -> Result<(), SeekDbError> {
    let config = ServerConfig::from_env()?;
    let client = SyncServerClient::from_config(config)?;

    let hnsw = seekdb_rs::HnswConfig {
        dimension: 3,
        distance: seekdb_rs::DistanceMetric::Cosine,
    };

    let coll: SyncCollection = client
        .create_collection::<seekdb_rs::DummyEmbedding>("sync_demo", Some(hnsw), None::<seekdb_rs::DummyEmbedding>)?;

    let ids = vec!["id1".to_string(), "id2".to_string()];
    let embs = vec![vec![1.0, 2.0, 3.0], vec![2.0, 3.0, 4.0]];
    coll.add(&ids, Some(&embs), None, Some(&["doc1".into(), "doc2".into()]))?;

    let cnt = coll.count()?;
    assert_eq!(cnt, 2);

    Ok(())
}

Do not call the blocking APIs (SyncServerClient, SyncCollection) from within an existing Tokio runtime; use them only in non‑async contexts.

---

8. Testing

This crate ships both unit tests and async integration tests.

• Unit tests live alongside modules under src/ and can be run with cargo test.
• Integration tests live under tests/ and require a real SeekDB / OceanBase instance, controlled by env variables.

Run integration tests:

SEEKDB_INTEGRATION=1 \
SERVER_HOST=127.0.0.1 \
SERVER_PORT=2881 \
SERVER_TENANT=sys \
SERVER_DATABASE=test \
SERVER_USER=root \
SERVER_PASSWORD='' \
cargo test --tests

Integration tests cover:

• Database CRUD and admin APIs.
• Collection DML semantics and metadata handling.
• ONNX‑based default embedding (with the embedding feature).
• Hybrid search behavior.
• Sync client wrappers (with the sync feature).

---

9. Feature Matrix

A high‑level comparison with the Python SDK:

Area	Status	Notes
Error type SeekDbError	✅	Unified error type, aligned with the design docs
Config types ServerConfig / HnswConfig / DistanceMetric	✅	Includes from_env helpers
Common structs QueryResult / GetResult / IncludeField / Database	✅	Struct shapes match Python
Server client ServerClient	✅	connect/from_config/from_env/execute/fetch_all
Collection mgmt: create/get/get_or_create/delete/list/has/count	✅	Table naming, vector column/index follow Python conventions
Collection DML: add / update / upsert / delete (explicit embeddings)	✅	Length & dimension checks; semantics aligned with Python
Collection DQL: query_embeddings / query_texts / get / count / peek	✅	Supports metadata/document filters and include flags
Filter expressions Filter / DocFilter	✅	Typed equivalents of $eq/$ne/$gt/... and $contains/$regex
Integration tests (server mode)	✅	Require real SeekDB / OceanBase
EmbeddingFunction trait	✅	Custom implementations supported
Default embedding implementation DefaultEmbedding	✅	ONNX‑based, behind the embedding feature
Auto‑embedding for add / update / upsert	✅	When a collection has an embedding_function
Text queries: Collection::query_texts	✅	Uses attached EmbeddingFunction
Sync wrappers: SyncServerClient / SyncCollection	✅	Provided behind the sync feature
Hybrid search (hybrid_search, hybrid_search_advanced)	✅	Hybrid vector + text + metadata search
Embedded client (on‑disk, non‑server mode)	❌	Not implemented in Rust yet
RAG demo (end‑to‑end example)	❌	Only available in Python for now

For more detailed, API‑by‑API explanations (currently in Simplified Chinese), see README_zh-CN.md.