{ "version": "https://jsonfeed.org/version/1.1", "title": "fantasy biji", "home_page_url": "https://biji.6996688.xyz/en/", "feed_url": "https://biji.6996688.xyz/en/feed.json", "description": "fantasy biji", "items": [ { "title": "Custom Component", "url": "https://biji.6996688.xyz/en/article/3rjl4t2h/", "id": "https://biji.6996688.xyz/en/article/3rjl4t2h/", "summary": "VuePress pages are Vue applications under the hood, so Vue components can be used directly in Markdown. This article shows how to create, register and use a custom component wit...", "content_html": "

VuePress pages are Vue applications under the hood, so Vue components can be used directly in Markdown. This article shows how to create, register and use a custom component with the plume theme — the colored cards on this page are the final result.

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1. Create the component

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Create DemoCard.vue under docs/.vuepress/theme/components/:

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<script setup>\ndefineProps({\n  title: { type: String, default: '' },\n  color: { type: String, default: '#2a9dff' },\n})\n</script>\n\n<template>\n  <div class=\"demo-card\" :style=\"{ '--demo-card-color': color }\">\n    <p v-if=\"title\" class=\"demo-card-title\">{{ title }}</p>\n    <div class=\"demo-card-body\">\n      <slot />\n    </div>\n  </div>\n</template>\n\n<style scoped>\n.demo-card {\n  margin: 16px 0;\n  padding: 14px 18px;\n  border: 1px solid var(--demo-card-color);\n  border-left-width: 4px;\n  border-radius: 8px;\n}\n</style>
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The component accepts title and color props, and receives nested content written in Markdown through <slot />.

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2. Register the component

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Register it globally in docs/.vuepress/client.ts:

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import { defineClientConfig } from 'vuepress/client'\nimport DemoCard from './theme/components/DemoCard.vue'\n\nexport default defineClientConfig({\n  enhance({ app }) {\n    app.component('DemoCard', DemoCard)\n  },\n})
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3. Use it in Markdown

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Once registered, the component tag can be used directly in any Markdown file:

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<DemoCard title=\"This is a custom component\" color=\"#8b5cf6\">\nIt works right inside Markdown, with `props` and slots.\n</DemoCard>
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Actual rendered result:

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Notes

\n\n", "date_published": "2026-10-03T14:15:19.000Z", "date_modified": "2026-10-03T14:15:19.000Z", "authors": [], "tags": [] }, { "title": "Full-Text Search for Websites Using Algolia", "url": "https://biji.6996688.xyz/en/blog/yzgd3xv1/", "id": "https://biji.6996688.xyz/en/blog/yzgd3xv1/", "summary": "1. Introduction ​ I was using local search for my notes, but there were always some contents that couldn't be found. After searching online, I found the third-party search servi...", "content_html": "

1. Introduction

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​\tI was using local search for my notes, but there were always some contents that couldn't be found. After searching online, I found the third-party search service, Algolia DocSearch, to implement full-text search for my personal website.

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2. Algolia

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​\tThe official VuePress documentation uses Algolia search. The biggest advantage of using Algolia is its convenience: it automatically crawls the website content and builds an index. You only need to apply for an Algolia service, add some code to the website, just like adding analytics code, and then you can have full-text search functionality.

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3. Implementing Full-Text Search

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1. Apply for the Algolia DocSearch Service
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​\tGo to the Algolia DocSearch Apply website, fill in your website address, email, repository address, and other information, and submit the application.

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Note: The website address must be public, complete, and stable. If the website is still in the testing phase, the chances of approval are low.

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2. Respond to the Confirmation Email
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​\tOnce your application is approved, Algolia DocSearch will send a confirmation email to the email address you provided in the previous step. You will need to reply confirming that you are responsible for the website's development and maintenance and can modify the website's code.

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Reply content: Thanks! I am the maintainer of the website, I can modify the code.
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​\tAfter that, the next day, you'll receive an email containing the appId, apiKey, and indexName, which are needed to configure the website framework:

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3. Activate the Search Service
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​\tThe email from Algolia DocSearch includes the appId, apiKey, and indexName that need to be configured in your website framework. My note template already provides this configuration, and other frameworks are similar:

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​\tThe email also provides a link to accept the invitation. After setting a password (the account is the email you used when applying), you can log in to Algolia.

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​\tAfter logging in, select the corresponding project, which should have the same name as the indexName:

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​\tClick "Go To Crawler" (the blue button in the image above) to enter the crawler backend, which will prompt you to visit the :

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Click to enter the crawler:

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​\tIf the number in the red box in the image above is 0, proceed to the next step:

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​\tClick "Editor" on the left menu to view and edit the crawler code. Pay attention to the pathsToMatch path in the code (the white box in the image), which is obviously incorrect. It has an extra docs. Change it to the correct website path https://biji.6996688.xyz/**:

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The reason is that our website homepage is https://biji.6996688.xyz/, and the content we want to search is also here.

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​\tAfter making the modification, run a test (as shown in the red box in the image). If data is successfully extracted (as shown in the yellow box in the image), click the "Save" button in the top-right corner to save the code. Then, return to the "Overview" section and click "Restart crawling" in the top-right corner to re-crawl the data.

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If you still can't extract data, refer to: https://github.com/mqyqingfeng/Blog/issues/267#issuecomment-1078620438

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Done.

\n", "image": "https://my-img.6996688.xyz/fantasy-biji/2024/09/a26c594128435ec52eae983b79839dae.png", "date_published": "2024-12-13T06:49:21.000Z", "date_modified": "2026-10-03T14:15:19.000Z", "authors": [], "tags": [] }, { "title": "How to Introduce and Install the BBR Congestion Algorithm on Windows 11", "url": "https://biji.6996688.xyz/en/blog/yckscddw/", "id": "https://biji.6996688.xyz/en/blog/yckscddw/", "summary": "​ Windows 11 22H2 now supports TCP BBR v2 congestion control. This article shows how to easily switch from the default Cubic congestion control to BBR v2, without restarting you...", "content_html": "

​\tWindows 11 22H2 now supports TCP BBR v2 congestion control. This article shows how to easily switch from the default Cubic congestion control to BBR v2, without restarting your computer, for a faster network experience on Windows 11.

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1. What is the BBR Algorithm?

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​\tBBR (Bottleneck Bandwidth and Round-trip propagation time) is a congestion control algorithm designed to optimize TCP performance in high bandwidth, high packet loss network environments. It adapts the sending rate based on the current network congestion and latency to achieve maximum throughput and minimal delay. BBR algorithm dynamically measures and estimates parameters such as network bandwidth and latency to determine the optimal congestion window size, ensuring better transmission performance. BBR is widely used in Google’s network services, including YouTube and Google Cloud.

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2. What is the Default Algorithm in Windows?

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​\tCUBIC (Cubic TCP) is a congestion control algorithm similar to the BB-Reno algorithm, but it differs by using a nonlinear congestion window growth approach, better suited for high bandwidth, high-latency network environments.

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​\tCUBIC’s congestion control window grows like a cubic curve. It uses a curve fitting mechanism based on the congestion window size, adjusting it by monitoring packet loss events to manage congestion avoidance and recovery.

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​\tCUBIC is widely used in Linux TCP modules and various wide-area network (WAN) and Internet environments, making it a very practical congestion control algorithm.

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3. What Are the Differences Between BBR and CUBIC?

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BBR and CUBIC differ in several key aspects:

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    \n
  1. Algorithm Philosophy: BBR focuses on maintaining the bandwidth and latency of the network’s bottleneck link, adjusting congestion based on the minimum bandwidth and maximum latency in the network. CUBIC, on the other hand, uses a fitting curve to calculate the congestion window size.
    2. \n
  2. Algorithm Parameters: BBR requires dynamic measurement and estimation of network parameters such as bandwidth and latency, while CUBIC adjusts based on changes in the congestion window size.
    3. \n
  3. Suitable Environments: BBR is better suited for high bandwidth, high latency, small packet networks, such as Google’s services, while CUBIC is more suitable for high bandwidth, long-distance WAN environments.
    4. \n
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4. Which Algorithm Should Be Used in Different Environments?

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​\tIn short, the choice of congestion control algorithm should depend on the network environment. BBR performs better in networks with large bandwidth and low packet loss, as it can quickly detect and fully utilize the available bandwidth. CUBIC is better for networks with smaller bandwidth and higher packet loss, as it can adapt better to network conditions, reducing packet loss and congestion. When selecting an algorithm, it is important to consider the actual network situation and requirements.

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5. Switching to BBR Algorithm on Windows 11

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5.1 Check the Current Algorithm

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5.2 Switch to BBR Algorithm

\n\n", "image": "https://my-img.6996688.xyz/fantasy-biji/2024/09/a7a4266ed457809cbb55f3fb2f74e166.png", "date_published": "2024-12-13T06:49:21.000Z", "date_modified": "2026-10-03T14:15:19.000Z", "authors": [], "tags": [] }, { "title": "Markdown", "url": "https://biji.6996688.xyz/en/article/vit5t0xa/", "id": "https://biji.6996688.xyz/en/article/vit5t0xa/", "summary": "Heading 2 Heading 3 Heading 4 Heading 5 Heading 6 Bold: Bold text Italic: Italic text Content Highlight Mathematical expression: −(2n−1) ~ 2n−1−1 ∂ωr∂r​(ωyω​)=(ωyω​){(logy)r+∑i=...", "content_html": "

Heading 2

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Heading 3

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Heading 4

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Heading 5
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Heading 6
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Bold: Bold text

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Italic: Italic text

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Deleted text

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Content Highlight

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Mathematical expression: −(2n−1)-(2^{n-1})−(2n−1) ~ 2n−1−12^{n-1} -12n−1−1

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∂r∂ωr(yωω)=(yωω){(log⁡y)r+∑i=1r(−1)Ir⋯(r−i+1)(log⁡y)riωi}\\frac {\\partial^r} {\\partial \\omega^r} \\left(\\frac {y^{\\omega}} {\\omega}\\right)\n= \\left(\\frac {y^{\\omega}} {\\omega}\\right) \\left\\{(\\log y)^r + \\sum_{i=1}^r \\frac {(-1)^ Ir \\cdots (r-i+1) (\\log y)^{ri}} {\\omega^i} \\right\\}∂ωr∂r​(ωyω​)=(ωyω​){(logy)r+∑i=1r​ωi(−1)Ir⋯(r−i+1)(logy)ri​}

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19th

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H2O

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content center

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content right

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  1. Ordered List 1
    2. \n
  2. Ordered List 2
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  3. Ordered List 3
    4. \n
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| Tables | Are | Cool |\n|

\n", "date_published": "2024-12-12T05:07:31.000Z", "date_modified": "2026-10-03T14:15:19.000Z", "authors": [], "tags": [] }, { "title": "bar", "url": "https://biji.6996688.xyz/en/demo/q7w72mvx/", "id": "https://biji.6996688.xyz/en/demo/q7w72mvx/", "content_html": "

\n", "date_published": "2024-12-12T05:07:31.000Z", "date_modified": "2026-10-03T14:15:19.000Z", "authors": [], "tags": [] }, { "title": "foo", "url": "https://biji.6996688.xyz/en/demo/921i08bb/", "id": "https://biji.6996688.xyz/en/demo/921i08bb/", "content_html": "

\n", "date_published": "2024-12-12T05:07:31.000Z", "date_modified": "2026-10-03T14:15:19.000Z", "authors": [], "tags": [] }, { "title": "Demo", "url": "https://biji.6996688.xyz/en/demo/", "id": "https://biji.6996688.xyz/en/demo/", "content_html": "\n", "date_published": "2024-12-12T05:07:31.000Z", "date_modified": "2026-10-03T14:15:19.000Z", "authors": [], "tags": [] } ] }