Attention: The code in this repository is intended for experimental use only and is not fully tested, documented, or supported by SingleStore. Visit the SingleStore Forums to ask questions about this repository.
The Elegance SDK is an SDK for quickly building real-time AI full-stack JavaScript applications using SingleStoreDB with support for MySQL and Kai (support for Mongo APIs) connection types and the OpenAI API. It provides a set of ready-made tools for implementing various types of functionality when you need to transact, analyze, and contextualize data in real-time or build real-time AI apps.
- Dot product search
- Chat completions
- File embeddings generation (csv, pdf)
- SQL and aggregate queries
- SQL and Kai (MongoDB) database connections support
- Ready-to-use Node.js controllers and React.js hooks
npm install @singlestore/elegance-sdk
This guide will show you how to use the SDK in Express.js and React.js.
- Create a
eleganceServerClient.ts
file - Import the
createEleganceServerClient
function from@singlestore/elegance-sdk/server
import { createEleganceServerClient } from "@singlestore/elegance-sdk/server";
export const eleganceServerClient = createEleganceServerClient("mysql", {
connection: {
host: "<DB_HOST>"
user: "<DB_USER>"
password: "<DB_PASSWORD>"
database: "<DB_NAME>"
},
ai: {
openai: {
apiKey: "<OPENAI_API_KEY>"
}
}
});
In case if you don't want to use OpenAI, you can replace the existing AI SDK logic with customizers:
...
import {
EmbeddingInput,
CreateEmbeddingResult,
CreateChatCompletionParams,
CreateChatCompletionResult
} from "@singlestore/elegance-sdk/types";
...
ai: {
customizers: {
createEmbedding: async (input: EmbeddingInput): Promise<CreateEmbeddingResult> => {
const embedding = await customFn(input);
return embedding;
},
createChatCompletion: async (params: CreateChatCompletionParams): Promise<CreateChatCompletionResult> => {
const chatCompletion = await customFn(params);
return chatCompletion;
}
}
}
...
- Create a route handler for
elegance/:route
(using Express.js as an example).
import express from "express";
import type { Routes } from "@singlestore/elegance-sdk/server";
import { eleganceServerClient } from "@/services/eleganceServerClient";
export const eleganceRouter = express.Router();
eleganceRouter.post("/elegance/:route", async (req, res) => {
try {
const route = req.params.route as Routes;
const result = await eleganceServerClient.handleRoute(route, req.body);
return res.status(200).json(result);
} catch (error: any) {
return res.status(error.status).json(error);
}
});
- Import the eleganceRouter into the
./server/index.ts
import express from "express";
import { eleganceRouter } from "./routes/elegance";
const app = express();
app.use(eleganceRouter);
app.listen(4000, () => {
console.log(`Server started on port: ${4000}`);
});
- Run the server
- Create a
eleganceClient.ts
file - Import the
createEleganceClient
function from@singlestore/elegance-sdk
import { createEleganceClient } from "@singlestore/elegance-sdk";
export const eleganceClient = createEleganceClient("mysql", {
baseURL: "http://localhost:4000",
});
- Import the
eleganceClient
to your component
import { useEffect } from "react";
import { eleganceClient } from "@/services/eleganceClient";
export function ExampleComponent() {
const query = eleganceClient.hooks.useQuery<{ name: string }[]>({
initialValue: [],
initialIsLoading: true,
});
const { execute: executeQuery } = query;
useEffect(() => {
executeQuery({ query: "SELECT name FROM table LIMIT 3" });
}, [executeQuery]);
if (query.isLoading) return "Loading...";
return (
<div>
{query.value.map((item) => (
<h4 key={item.name}>{item.name}</h4>
))}
</div>
);
}
- Run your client
You can find templates using the Elegance SDK here:
You can find example apps using the Elegance SDK here:
Creates an EleganceServerClient instance for a server.
Parameters:
connectionType: "kai" | "mysql"
-
config: { connection: KaiConnectionConfig | MySQLConnectionConfig; ai?: { openai?: OpenAIConfig; customizers?: { createEmbedding?: (input: EmbeddingInput) => Promise<CreateEmbeddingResult>; createChatCompletion?: (params: CreateChatCompletionParams) => Promise<CreateChatCompletionResult>; } // You can use your own functions to create an embedding or a chat completion. }; }
Returns: eleganceServerClient
Server client that includes a database connection, controllers and AI client. It's used on the server to handle requests from the client and execute logic.
MySQL or MongoDB connection to interact with a database
Accepts a route and executes the controller for that route.
Parameters:
route: string
- controller route namebody: object
- controller body
Inserts one record.
Parameters:
Kai
body: {
db?: string;
collection: string;
generateId?: boolean;
value: MongoOptionalUnlessRequiredId<T>;
options?: MongoInsertOneOptions;
}
MySQL
body: {
db?: string;
collection: string;
generateId?: boolean;
value: T;
}
Returns: T
Inserts many records.
Parameters:
Kai
body: {
db?: string;
collection: string;
values: Array<MongoOptionalUnlessRequiredId<T[number]>>;
generateId?: boolean;
options?: MongoBulkWriteOptions;
}
MySQL
body: {
db?: string;
collection: string;
generateId?: boolean;
values: Array<T>;
}
Returns: Array<T>
Updates many records.
Parameters:
Kai
body: {
db?: string;
collection: string;
filter: MongoFilter<T[number]>;
update: MongoUpdateFilter<T[number]>;
options?: MongoUpdateOptions;
updatedFilter?: MongoFilter<T[number]>;
}
MySQL
body: {
db?: string;
collection: string;
where: MySQLWhere;
set: MySQLSet;
updatedWhere: MySQLWhere;
}
Returns: Array<T>
Deletes many records.
Parameters:
Kai
body: {
db?: string;
collection: string;
filter: MongoFilter<T>;
options?: MongoDeleteOptions;
}
MySQL
body: {
db?: string;
collection: string;
where: MySQLWhere;
}
Returns: { message: string }
Gets one record.
Parameters:
Kai
body: {
db?: string;
collection: string;
filter?: MongoFilter<T>;
options?: MongoFindOptions;
}
MySQL
body: {
db?: string;
collection: string;
columns?: string[];
where?: MySQLWhere;
extra?: string;
}
Returns: T
Gets many records.
Parameters: Kai
body: {
db?: string;
collection: string;
filter?: MongoFilter<T[number]>;
options?: MongoFindOptions;
}
MySQL
body: {
db?: string;
collection: string;
columns?: string[];
where?: MySQLWhere;
skip?: number;
limit?: number;
extra?: string;
}
Returns: Array<object>
Executes MySQL or aggregate query.
Parameters:
Kai
body: {
db?: string;
collection: string;
query: object[];
options?: MongoAggregateOptions;
}
MySQL
body: {
query: string;
}
Returns: Array<T>
Creates embedding.
Parameters:
body: {
input: string | string[] | object | object[];
}
Returns: Embedding
Accepts a CSV or PDF file, splits it into chunks and creates embeddings.
Parameters:
body: {
dataURL: string;
textField?: string;
embeddingField?: string;
chunkSize?: number;
}
Returns: Array<{ text: string; embedding: Embedding; }>
Accepts a CSV or PDF file, splits it into chunks, creates embeddings, and inserts them into a database.
Parameters:
body: {
db?: string;
collection: string;
dataURL: string;
textField?: string;
embeddingField?: string;
chunkSize?: number;
}
Returns: Array<{ text: string; embedding: Embedding; }>
Accepts a prompt and creates chat completion.
Parameters:
body: {
model?: ChatCompletionCreateParamsNonStreaming["model"];
prompt?: string;
systemRole?: string;
messages?: ChatCompletionMessage[];
temperature?: number;
maxTokens?: number;
}
Returns:
string | null;
Accepts a prompt, performs dot product search, and creates chat completion for the found records.
Parameters:
body: {
db?: string;
collection: string;
model?: ChatCompletionCreateParamsNonStreaming["model"];
prompt: string;
systemRole?: string;
messages?: ChatCompletionMessage[];
temperature?: number;
maxTokens?: number;
textField?: string;
embeddingField?: string;
minSimilarity?: number;
maxContextLength?: number;
}
Returns:
{
content: string;
context: string;
}
Performs dot product search in the collection based on the query.
Parameters:
body: {
db?: string;
collection: string;
query: string;
queryEmbedding?: Embedding;
embeddingField: string;
limit?: number;
minSimilarity?: number;
includeEmbedding?: boolean;
}
Returns: Array<any>
Creates embedding
Parameters:
input: string | Array<string> | object | Array<object>
Returns: Embedding
Converts an embedding into a buffer that is then inserted into the database (for Kai).
Parameters:
embedding: Embedding
Returns: Buffer
Converts text into embeddings by splitting the text into chunks.
Parameters:
text: string
-
options?: { chunkSize?: number; textField?: string; embeddingField?: string; }
Converts a DataURL (csv, pdf) into an embedding by splitting the text into chunks.
Parameters:
dataURL: string
-
options?: { chunkSize?: number; textField?: string; embeddingField?: string; }
Returns: Array<{ text: string; embedding: Embedding }>
Creates a chat completion.
Parameters:
-
params: { model?: ChatCompletionCreateParamsNonStreaming["model"]; prompt?: string; systemRole?: string; messages?: ChatCompletionMessage[]; temperature?: number; maxTokens?: number; }
Returns: string
Creates an EleganceClient instance for a client.
Parameters:
connectionType: "kai" | "mysql"
-
config: { baseURL: string; }
Returns: eleganceServerClient
Client that includes requests and hooks. It is used to make requests to the server.
Clean functions to make requests to the server. They can be used anywhere within a project and are handled like typical async functions. The parameters for each request correspond to the controller parameters by name. To familiarize with the parameters, refer to the eleganceServerClient.controllers.<requestName>
section.
Ready-to-use React.js hooks with state handlers that use requests. Each hook has the following type:
<R = any,>(options?: {
initialValue?: R;
initialIsLoading?: boolean;
onError?: (error: DefaultError) => void;
}) => {
value: R | undefined;
error: DefaultError | undefined;
isLoading: boolean;
setValue: react.Dispatch<react.SetStateAction<Awaited<R> | undefined>>;
setError: react.Dispatch<react.SetStateAction<DefaultError | undefined>>;
setIsLoading: react.Dispatch<react.SetStateAction<boolean>>;
execute: (body: object) => Promise<Awaited<R> | undefined>;
};
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