adeleke5140

title	description
Storing Embeddings in A Vector Database | Mastra Docs	Guide on vector storage options in Mastra, including embedded and dedicated vector databases for similarity search.

import { Tabs } from "nextra/components";

Storing Embeddings in A Vector Database

After generating embeddings, you need to store them in a database that supports vector similarity search. Mastra provides a consistent interface for storing and querying embeddings across different vector databases.

adeleke5140

---
title: "Storing Embeddings in A Vector Database | Mastra Docs"
description: Guide on vector storage options in Mastra, including embedded and dedicated vector databases for similarity search.
---

import { Tabs } from "nextra/components";

## Storing Embeddings in A Vector Database

After generating embeddings, you need to store them in a database that supports vector similarity search. Mastra provides a consistent interface for storing and querying embeddings across different vector databases.

adeleke5140

---
title: "Storing Embeddings in A Vector Database | Mastra Docs"
description: Guide on vector storage options in Mastra, including embedded and dedicated vector databases for similarity search.
---

import { Tabs } from "nextra/components";

## Storing Embeddings in A Vector Database

After generating embeddings, you need to store them in a database that supports vector similarity search. Mastra provides a consistent interface for storing and querying embeddings across different vector databases.

adeleke5140

---
title: "Storing Embeddings in A Vector Database | Mastra Docs"
description: Guide on vector storage options in Mastra, including embedded and dedicated vector databases for similarity search.
---

import { Tabs } from "nextra/components";

## Storing Embeddings in A Vector Database

After generating embeddings, you need to store them in a database that supports vector similarity search. Mastra provides a consistent interface for storing and querying embeddings across different vector databases.

adeleke5140

.editor-group-watermark > .letterpress{
  background-image: url("https://github.com/Aikoyori/ProgrammingVTuberLogos/blob/main/VSCode/VSCode.png?raw=true");
  opacity: 0.9
}

adeleke5140

const MultiSelect = ({
  options,
  inputId,
  name,
  inputPlaceholder,
  ...rest
}: MultiSelectProps) => {
  return (
    <Select
      {...rest}

adeleke5140

const Notifications = () => {
  const { container, ref } = useModalParent<HTMLDivElement>();
  return (
    <div ref={ref}>
    // rest of code
        <Popover.Portal container={container}>
          // rest of code
        </Popover/>
    </div>
  )

adeleke5140

import axios, { CreateAxiosDefaults } from 'axios'
import { refreshToken as refreshTokenAdapter} from './session'


export const getJSONContentHeaders = () => {
  "Content-Type": "application/json",
  Accept: "application/json"
}

adeleke5140

const blob = b64toBlob(imageSrc.replace(/^data:image\/jpeg;base64,/, ""));
const file = new File([blob], "profile.jpeg", { type: "image/jpeg" });
const blobURl = URL.createObjectURL(file);

adeleke5140

Dependency Injection in ReactJS

This is a conversation on the DI pattern in ReactJS.

This article from the folks at 8th Light is great. The author explains how it makes component very easy to test. It encourages unit testing rather than integration testing.

In essence:

It also allows for substitution of a dependency with a mock, or fake, during testing.