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justshare.xcodeproj}/project.xcworkspace/xcuserdata/hacked.xcuserdatad/UserInterfaceState.xcuserstate (100%) rename swift/{lunabrain.xcodeproj => justshare.xcodeproj}/xcuserdata/hacked.xcuserdatad/xcdebugger/Breakpoints_v2.xcbkptlist (92%) rename swift/{lunabrain.xcodeproj => justshare.xcodeproj}/xcuserdata/hacked.xcuserdatad/xcschemes/xcschememanagement.plist (74%) rename swift/{lunabrain => justshare}/AIViewModel.swift (98%) rename swift/{lunabrain => justshare}/Assets.xcassets/AccentColor.colorset/Contents.json (100%) rename swift/{lunabrain => justshare}/Assets.xcassets/AppIcon.appiconset/Contents.json (100%) rename swift/{lunabrain => justshare}/Assets.xcassets/AppIcon.appiconset/appstore.png (100%) rename swift/{lunabrain => justshare}/Assets.xcassets/Contents.json (100%) rename swift/{lunabrain => justshare}/AudioRecorder.swift (100%) rename swift/{lunabrain => justshare}/ContentView.swift (100%) rename swift/{lunabrain => justshare}/EditableListItem.swift (100%) rename swift/{lunabrain => justshare}/Info.plist (100%) rename swift/{lunabrain => justshare}/Preview Content/Preview Assets.xcassets/Contents.json (100%) rename swift/{lunabrain => justshare}/RecordingsView.swift (100%) rename swift/{lunabrain => justshare}/TranscriptionViewModel.swift (100%) rename swift/{lunabrain => justshare}/lunabrainApp.swift (75%) diff --git a/.github/workflows/build.yaml b/.github/workflows/build.yaml index e2aaf9b4..a19f6da7 100644 --- a/.github/workflows/build.yaml +++ b/.github/workflows/build.yaml @@ -24,7 +24,7 @@ jobs: yq: "4.16.2" - name: Docker Build - run: docker build . -t lunabrain + run: docker build . -t justshare # - if: ${{ !(github.event_name == 'push' && github.ref == 'refs/heads/main') }} # run: exit 0 @@ -53,10 +53,10 @@ jobs: # echo SERVER_IMAGE_ID=$SERVER_IMAGE_ID # echo VERSION=$VERSION # -# docker tag lunabrain $SERVER_IMAGE_ID:$VERSION +# docker tag justshare $SERVER_IMAGE_ID:$VERSION # docker push $SERVER_IMAGE_ID:$VERSION # -# yq -i e ".services.lunabrain.image |= \"$(docker inspect --format='{{index .RepoDigests 0}}' $SERVER_IMAGE_ID:$VERSION)\"" docker-compose.prod.yaml +# yq -i e ".services.justshare.image |= \"$(docker inspect --format='{{index .RepoDigests 0}}' $SERVER_IMAGE_ID:$VERSION)\"" docker-compose.prod.yaml # - name: Create commit # id: create-commit # if: github.ref == 'refs/heads/main' diff --git a/.gitignore b/.gitignore index 845bb686..176dbf72 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,4 @@ tmp/ -.lunabrain.yaml .idea/ data/ node_modules/ @@ -25,6 +24,6 @@ venv3.*/ *.egg *.egg-info/ -.lunabrain.yaml +.justshare.yaml chat.yaml openaif.json \ No newline at end of file diff --git a/.gitmodules b/.gitmodules index 6f71529d..913285f9 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,3 @@ [submodule "third_party/whisper.cpp"] path = third_party/whisper.cpp - url = https://github.com/lunabrain-ai/whisper.cpp.git + url = https://github.com/justshare-io/whisper.cpp.git diff --git a/README.md b/README.md index db54745e..e7637b5c 100644 --- a/README.md +++ b/README.md @@ -1,24 +1,24 @@ -# LunaBrain +# justshare Build shared context with you and your homies. -[![LunaBrain Demo](docs/assets/images/demo.png)](https://www.youtube.com/live/UoRi3Fqh6Jg?si=CQVxzNWAqL6KOMa1&t=268 "LunaBrain Demo") +[![justshare Demo](docs/assets/images/demo.png)](https://www.youtube.com/live/UoRi3Fqh6Jg?si=CQVxzNWAqL6KOMa1&t=268 "justshare Demo") ### Library -- To use LunaBrain as a Go library, refer to the [documentation](https://pkg.go.dev/github.com/lunabrain-ai/lunabrain) (Note: This code is still like pre-alpha, so the API is subject to change) +- To use justshare as a Go library, refer to the [documentation](https://pkg.go.dev/github.com/justshare-io/justshare) (Note: This code is still like pre-alpha, so the API is subject to change) ## License -LunaBrain is licensed under the Apache 2.0 license. See the `LICENSE` file for more details. +justshare is licensed under the Apache 2.0 license. See the `LICENSE` file for more details. ## Getting Started -To get started with LunaBrain, follow these steps: +To get started with justshare, follow these steps: ### Setup Repo ```shell -git clone --recursive https://github.com/lunabrain-ai/lunabrain.git +git clone --recursive https://github.com/justshare-io/justshare.git ``` ### Running @@ -60,7 +60,7 @@ go generate -x ./... ## Contributing -We welcome contributions to LunaBrain! To contribute, please follow these steps: +We welcome contributions to justshare! To contribute, please follow these steps: 1. Fork the repository 2. Create a new branch for your feature diff --git a/buf.gen.yaml b/buf.gen.yaml index 32e88031..a24f5275 100644 --- a/buf.gen.yaml +++ b/buf.gen.yaml @@ -2,7 +2,7 @@ version: v1 managed: enabled: true go_package_prefix: - default: github.com/lunabrain-ai/lunabrain/pkg/gen + default: github.com/justshare-io/justshare/pkg/gen plugins: - plugin: buf.build/protocolbuffers/go out: ./pkg/gen diff --git a/deploy/docker-compose.yaml b/deploy/docker-compose.yaml index 9f3a80f0..8f9558d7 100644 --- a/deploy/docker-compose.yaml +++ b/deploy/docker-compose.yaml @@ -1,10 +1,10 @@ version: '3.6' services: - lunabrain: -# image: ghcr.io/lunabrain/lunabrain + justshare: +# image: ghcr.io/justshare/justshare build: context: .. - hostname: lunabrain + hostname: justshare ports: - "80:8080" volumes: diff --git a/docs/.editorconfig b/docs/.editorconfig deleted file mode 100644 index dad6b582..00000000 --- a/docs/.editorconfig +++ /dev/null @@ -1,11 +0,0 @@ -# editorconfig.org - -root = true - -[*] -indent_style = space -indent_size = 2 -end_of_line = lf -charset = utf-8 -trim_trailing_whitespace = true -insert_final_newline = true \ No newline at end of file diff --git a/docs/.eslintignore b/docs/.eslintignore deleted file mode 100644 index 57d00579..00000000 --- a/docs/.eslintignore +++ /dev/null @@ -1,4 +0,0 @@ -assets/js/index.js -assets/js/katex.js -assets/js/vendor -node_modules \ No newline at end of file diff --git a/docs/.eslintrc.json b/docs/.eslintrc.json deleted file mode 100644 index c926994d..00000000 --- a/docs/.eslintrc.json +++ /dev/null @@ -1,31 +0,0 @@ -{ - "env": { - "browser": true, - "commonjs": true, - "es6": true, - "node": true - }, - "extends": "eslint:recommended", - "globals": { - "Atomics": "readonly", - "SharedArrayBuffer": "readonly" - }, - "parserOptions": { - "ecmaVersion": 2018, - "sourceType": "module" - }, - "rules": { - "no-console": 0, - "quotes": ["error", "single"], - "comma-dangle": [ - "error", - { - "arrays": "always-multiline", - "objects": "always-multiline", - "imports": "always-multiline", - "exports": "always-multiline", - "functions": "ignore" - } - ] - } -} \ No newline at end of file diff --git a/docs/.gitignore b/docs/.gitignore deleted file mode 100644 index 85ea9156..00000000 --- a/docs/.gitignore +++ /dev/null @@ -1,5 +0,0 @@ -node_modules -public -resources -.netlify -.hugo_build.lock \ No newline at end of file diff --git a/docs/.markdownlint-cli2.jsonc b/docs/.markdownlint-cli2.jsonc deleted file mode 100644 index 3c793744..00000000 --- a/docs/.markdownlint-cli2.jsonc +++ /dev/null @@ -1,11 +0,0 @@ -{ - "config": { - "default": true, - "MD013": false, - "MD024": false, - "MD026": false, - "MD033": false, - "MD034": false - }, - "ignores": ["node_modules", "CHANGELOG.md", "README.md"] -} \ No newline at end of file diff --git a/docs/.stylelintignore b/docs/.stylelintignore deleted file mode 100644 index 3972095a..00000000 --- a/docs/.stylelintignore +++ /dev/null @@ -1,3 +0,0 @@ -assets/scss/components/_syntax.scss -assets/scss/vendor -node_modules \ No newline at end of file diff --git a/docs/.stylelintrc.json b/docs/.stylelintrc.json deleted file mode 100644 index 191d0938..00000000 --- a/docs/.stylelintrc.json +++ /dev/null @@ -1,48 +0,0 @@ -{ - "extends": "stylelint-config-standard-scss", - "rules": { - "no-empty-source": null, - "string-quotes": "double", - "scss/comment-no-empty": null, - "max-line-length": null, - "scss/at-extend-no-missing-placeholder": null, - "scss/dollar-variable-colon-space-after": null, - "scss/dollar-variable-empty-line-before": null, - "color-function-notation": null, - "alpha-value-notation": null, - "selector-id-pattern": null, - "selector-class-pattern": null, - "scss/no-global-function-names": null, - "number-max-precision": null, - "hue-degree-notation": null, - "value-no-vendor-prefix": null, - "property-no-vendor-prefix": null, - "at-rule-no-unknown": [ - true, - { - "ignoreAtRules": [ - "extend", - "at-root", - "debug", - "warn", - "error", - "if", - "else", - "for", - "each", - "while", - "mixin", - "include", - "content", - "return", - "function", - "tailwind", - "apply", - "responsive", - "variants", - "screen" - ] - } - ] - } -} \ No newline at end of file diff --git a/docs/CHANGELOG.md b/docs/CHANGELOG.md deleted file mode 100644 index 26975b03..00000000 --- a/docs/CHANGELOG.md +++ /dev/null @@ -1,112 +0,0 @@ -### Changelog - -All notable changes to this project will be documented in this file. Dates are displayed in UTC. - -Generated by [`auto-changelog`](https://github.com/CookPete/auto-changelog). - -#### [v0.5.0](https://github.com/h-enk/doks-child-theme/compare/v0.4.3...v0.5.0) - -- feat: update for Doks v0.5.0 [`0df89d5`](https://github.com/h-enk/doks-child-theme/commit/0df89d51fbf706aea17d68d07bcfaeba422a1b60) -- content: update content for Doks v0.5.0 [`63d4412`](https://github.com/h-enk/doks-child-theme/commit/63d4412ba65217ca21092565bf3e6bcc2706e575) -- meta: update README.md [`5a8fa90`](https://github.com/h-enk/doks-child-theme/commit/5a8fa9081ce203d594c4ad7b5193f87bd51f3d6e) - -#### [v0.4.3](https://github.com/h-enk/doks-child-theme/compare/v0.4.2...v0.4.3) - -> 18 May 2022 - -- deps: bump versions to latest [`8ee2cb6`](https://github.com/h-enk/doks-child-theme/commit/8ee2cb6b8f2a7b38562f266c7db9c028a24c4523) -- meta: update changelog [`48499b6`](https://github.com/h-enk/doks-child-theme/commit/48499b6e66bf9bf5bc3d27597b2840618882b16b) - -#### [v0.4.2](https://github.com/h-enk/doks-child-theme/compare/v0.4.1...v0.4.2) - -> 1 April 2022 - -- deps: bump @hyas/doks from 0.4.1 to 0.4.2 [`eda0e36`](https://github.com/h-enk/doks-child-theme/commit/eda0e360262707c7baa1af2b7d373865d5e534fd) -- meta: update changelog [`4e8f1a8`](https://github.com/h-enk/doks-child-theme/commit/4e8f1a8e51292c4010ee48a1f94b22db441d0998) -- meta: update sponsors + backers sections [`788e1e3`](https://github.com/h-enk/doks-child-theme/commit/788e1e3ab5b5447b4464018a0959e3cd1338a486) - -#### [v0.4.1](https://github.com/h-enk/doks-child-theme/compare/v0.4.0...v0.4.1) - -> 31 March 2022 - -- deps: bump versions to latest [`a85f35d`](https://github.com/h-enk/doks-child-theme/commit/a85f35dc3fe0ca5a3080d4fe7d567f7e8863566e) -- ops: add continuous integration + stale workflows [`8134f51`](https://github.com/h-enk/doks-child-theme/commit/8134f518b7873be39ff2cd6eb3472bf681fa3390) -- feat: add files for custom scss + js [`12bf689`](https://github.com/h-enk/doks-child-theme/commit/12bf689da853e90ed51f25b8103e7beca68c23b0) - -#### [v0.4.0](https://github.com/h-enk/doks-child-theme/compare/v0.3.5...v0.4.0) - -> 4 February 2022 - -- deps: bump versions to latest [`fe5bf72`](https://github.com/h-enk/doks-child-theme/commit/fe5bf729e6e6754f3b6957b5d6c657c84326d070) -- fix: comment out mount content [`477ed68`](https://github.com/h-enk/doks-child-theme/commit/477ed686336826296a8b8e83c90af45b7a904bf4) -- config: update for doks v0.4.0 [`d00d595`](https://github.com/h-enk/doks-child-theme/commit/d00d595bc6add83780cf577d58099bbcecfbbe40) - -#### [v0.3.5](https://github.com/h-enk/doks-child-theme/compare/v0.3.4...v0.3.5) - -> 5 October 2021 - -- chore(deps-dev): bump bootstrap from 5.1.0 to 5.1.1 [`#64`](https://github.com/h-enk/doks-child-theme/pull/64) -- chore(deps-dev): bump @babel/preset-env from 7.15.4 to 7.15.6 [`#65`](https://github.com/h-enk/doks-child-theme/pull/65) -- chore(deps-dev): bump autoprefixer from 10.3.4 to 10.3.7 [`#71`](https://github.com/h-enk/doks-child-theme/pull/71) -- feat: update for doks 0.3.5 [`3782cf5`](https://github.com/h-enk/doks-child-theme/commit/3782cf57ed43acadc426305dc64764048b78138a) -- meta: update changelog [`36436ff`](https://github.com/h-enk/doks-child-theme/commit/36436fff6fd1ba412fdc991f4acca35a2835d09c) -- meta: bump version doks-child-theme to 0.3.5 [`57eae76`](https://github.com/h-enk/doks-child-theme/commit/57eae76694755ab1b06691a3c5427f224b806661) - -#### [v0.3.4](https://github.com/h-enk/doks-child-theme/compare/v0.3.3...v0.3.4) - -> 7 September 2021 - -- feat: update for doks 0.3.4 [`b08cb80`](https://github.com/h-enk/doks-child-theme/commit/b08cb80fadc09f7ad7e7e960d09dc482666fa108) -- deps: bump versions to latest [`a790bbe`](https://github.com/h-enk/doks-child-theme/commit/a790bbe7fa9ac52d15270339bf1ec24be385a2a8) -- Create FUNDING.yml [`8613d4c`](https://github.com/h-enk/doks-child-theme/commit/8613d4caad869c0f1f80b5610f6e49b766935541) - -#### [v0.3.3](https://github.com/h-enk/doks-child-theme/compare/v0.3.0...v0.3.3) - -> 5 July 2021 - -- feat: update for doks v0.3.3 [`f7b5720`](https://github.com/h-enk/doks-child-theme/commit/f7b57204c9de70f14e17337a8baa44815beb2b50) -- content: update readme [`14f1a3f`](https://github.com/h-enk/doks-child-theme/commit/14f1a3fede35e7f4a88d8ea063416958c2900a56) -- Update for doks v0.3.3 [`babdd77`](https://github.com/h-enk/doks-child-theme/commit/babdd7791e6002fd2272b1bc3c95c58654933454) - -#### [v0.3.0](https://github.com/h-enk/doks-child-theme/compare/v0.2.3...v0.3.0) - -> 25 June 2021 - -- feat: update for doks v0.3.0 [`630c2a2`](https://github.com/h-enk/doks-child-theme/commit/630c2a2edd246f3fc26fbb799d2debb77857882c) -- fix: add data directory [`69cdc3c`](https://github.com/h-enk/doks-child-theme/commit/69cdc3cccea6a976552e654a86a85475a19ef448) - -#### [v0.2.3](https://github.com/h-enk/doks-child-theme/compare/v0.2.2...v0.2.3) - -> 2 April 2021 - -- feat: update for doks v0.2.3 [`e517462`](https://github.com/h-enk/doks-child-theme/commit/e517462127252a50d78cf34180ea10f898993585) -- chore(release): 0.2.3 [`1fcbc4e`](https://github.com/h-enk/doks-child-theme/commit/1fcbc4e2cb297f780004582612d904920044b181) - -#### v0.2.2 - -> 26 March 2021 - -- feat: add doks as a node module [`cfed05e`](https://github.com/h-enk/doks-child-theme/commit/cfed05efaf7b4191b2bdca4c91405c6cabc8396c) -- deps: bump versions to latest [`997a7dd`](https://github.com/h-enk/doks-child-theme/commit/997a7dd7250b3dc0fe23c92ebf83ed21c9ba2d6b) -- config: update for doks v0.2.2 [`03f51d5`](https://github.com/h-enk/doks-child-theme/commit/03f51d5fd1f66f7afa0957d92adf779d438a3946) - - - -### [0.2.3](https://github.com/h-enk/doks/compare/v0.2.2...v0.2.3) (2021-04-02) - - -### Features - -* update for doks v0.2.3 ([e517462](https://github.com/h-enk/doks/commit/e517462127252a50d78cf34180ea10f898993585)) - -### 0.2.2 (2021-03-26) - - -### Features - -* add doks as a node module ([cfed05e](https://github.com/h-enk/doks/commit/cfed05efaf7b4191b2bdca4c91405c6cabc8396c)) - - -### Dependencies - -* bump versions to latest ([997a7dd](https://github.com/h-enk/doks/commit/997a7dd7250b3dc0fe23c92ebf83ed21c9ba2d6b)) diff --git a/docs/CODE_OF_CONDUCT.md b/docs/CODE_OF_CONDUCT.md deleted file mode 100644 index 77366b2e..00000000 --- a/docs/CODE_OF_CONDUCT.md +++ /dev/null @@ -1,76 +0,0 @@ -# Contributor Covenant Code of Conduct - -## Our Pledge - -In the interest of fostering an open and welcoming environment, we as -contributors and maintainers pledge to making participation in our project and -our community a harassment-free experience for everyone, regardless of age, body -size, disability, ethnicity, sex characteristics, gender identity and expression, -level of experience, education, socio-economic status, nationality, personal -appearance, race, religion, or sexual identity and orientation. - -## Our Standards - -Examples of behavior that contributes to creating a positive environment -include: - -* Using welcoming and inclusive language -* Being respectful of differing viewpoints and experiences -* Gracefully accepting constructive criticism -* Focusing on what is best for the community -* Showing empathy towards other community members - -Examples of unacceptable behavior by participants include: - -* The use of sexualized language or imagery and unwelcome sexual attention or - advances -* Trolling, insulting/derogatory comments, and personal or political attacks -* Public or private harassment -* Publishing others' private information, such as a physical or electronic - address, without explicit permission -* Other conduct which could reasonably be considered inappropriate in a - professional setting - -## Our Responsibilities - -Project maintainers are responsible for clarifying the standards of acceptable -behavior and are expected to take appropriate and fair corrective action in -response to any instances of unacceptable behavior. - -Project maintainers have the right and responsibility to remove, edit, or -reject comments, commits, code, wiki edits, issues, and other contributions -that are not aligned to this Code of Conduct, or to ban temporarily or -permanently any contributor for other behaviors that they deem inappropriate, -threatening, offensive, or harmful. - -## Scope - -This Code of Conduct applies both within project spaces and in public spaces -when an individual is representing the project or its community. Examples of -representing a project or community include using an official project e-mail -address, posting via an official social media account, or acting as an appointed -representative at an online or offline event. Representation of a project may be -further defined and clarified by project maintainers. - -## Enforcement - -Instances of abusive, harassing, or otherwise unacceptable behavior may be -reported by contacting the project team at hello@getdoks.org. All -complaints will be reviewed and investigated and will result in a response that -is deemed necessary and appropriate to the circumstances. The project team is -obligated to maintain confidentiality with regard to the reporter of an incident. -Further details of specific enforcement policies may be posted separately. - -Project maintainers who do not follow or enforce the Code of Conduct in good -faith may face temporary or permanent repercussions as determined by other -members of the project's leadership. - -## Attribution - -This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, -available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html - -[homepage]: https://www.contributor-covenant.org - -For answers to common questions about this code of conduct, see -https://www.contributor-covenant.org/faq diff --git a/docs/LICENSE b/docs/LICENSE deleted file mode 100644 index be44e1fc..00000000 --- a/docs/LICENSE +++ /dev/null @@ -1,22 +0,0 @@ -MIT License - -Copyright (c) 2018-present, Gridsome -Copyright (c) 2020-present, Henk Verlinde - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. \ No newline at end of file diff --git a/docs/README.md b/docs/README.md deleted file mode 100644 index 651bbba1..00000000 --- a/docs/README.md +++ /dev/null @@ -1,156 +0,0 @@ -

- - Doks - -

- -

- Doks -

- -

- Doks Child Theme -

- -

- Doks is a Hugo theme for building secure, fast, and SEO-ready documentation websites, which you can easily update and customize. -

- -

- - GitHub - - - GitHub release (latest SemVer including pre-releases) - - - GitHub Workflow Status (branch) - - - Netlify - -

- -![Doks — Modern Documentation Theme](https://raw.githubusercontent.com/h-enk/doks/master/images/doks.png) - -## Demo - -- [doks-child-theme.netlify.app](https://doks-child-theme.netlify.app/) - -## Why Doks? - -Nine main reasons why you should use Doks: - -1. __Security aware__. Get A+ scores on [Mozilla Observatory](https://observatory.mozilla.org/analyze/doks.netlify.app) out of the box. Easily change the default Security Headers to suit your needs. - -2. __Fast by default__. Get 100 scores on [Google Lighthouse](https://googlechrome.github.io/lighthouse/viewer/?gist=59aafe464a68f8bc30b8e9a636d5b053) by default. Doks removes unused css, prefetches links, and lazy loads images. - -3. __SEO-ready__. Use sensible defaults for structured data, open graph, and Twitter cards. Or easily change the SEO settings to your liking. - -4. __Development tools__. Code with confidence. Check styles, scripts, and markdown for errors and fix automatically or manually. - -5. __Bootstrap framework__. Build robust, flexible, and intuitive websites with Bootstrap 5. Easily customize your Doks site with the source Sass files. - -6. __Netlify-ready__. Deploy to Netlify with sensible defaults. Easily use Netlify Functions, Netlify Redirects, and Netlify Headers. - -7. __Full text search__. Search your Doks site with FlexSearch. Easily customize index settings and search options to your liking. - -8. __Page layouts__. Build pages with a landing page, blog, or documentation layout. Add custom sections and components to suit your needs. - -9. __Dark mode__. Switch to a low-light UI with the click of a button. Change colors with variables to match your branding. - -### Other features - -- __Multilingual and i18n__ support -- __Versioning__ documentation support -- __KaTeX__ math typesetting -- __Mermaid__ diagrams and visualization -- __highlight.js__ syntax highlighting - -## Requirements - -- [Git](https://git-scm.com/) — latest source release -- [Node.js](https://nodejs.org/) — latest LTS version or newer - -
-Why Node.js? - -Doks uses npm (included with Node.js) to centralize dependency management, making it [easy to update](https://getdoks.org/docs/help/how-to-update/) resources, build tooling, plugins, and build scripts. - -
- -## Get started - -Start a new Doks project in three steps: - -### 1. Create a new site - -Doks is available as a child theme and a starter theme. - -#### Child theme - -- Intended for novice to intermediate users -- Intended for minor customizations -- [Easily update npm packages](https://getdoks.org/docs/help/how-to-update/) — __including__ [Doks](https://www.npmjs.com/package/@hyas/doks) - -```bash -git clone https://github.com/h-enk/doks-child-theme.git my-doks-site && cd my-doks-site -``` - -#### Starter theme - -- Intended for intermediate to advanced users -- Intended for major customizations -- [Easily update npm packages](https://getdoks.org/docs/help/how-to-update/) - -```bash -git clone https://github.com/h-enk/doks.git my-doks-site && cd my-doks-site -``` - -
-Help me choose - -Not sure which one is for you? Pick the child theme. - -
- -### 2. Install dependencies - -```bash -npm install -``` - -### 3. Start development server - -```bash -npm run start -``` - -## Other commands - -Doks comes with [commands](https://getdoks.org/docs/prologue/commands/) for common tasks. - -## Documentation - -- [Netlify](https://docs.netlify.com/) -- [Hugo](https://gohugo.io/documentation/) -- [Doks](https://getdoks.org/) - -## Communities - -- [Netlify Community](https://community.netlify.com/) -- [Hugo Forums](https://discourse.gohugo.io/) -- [Doks Discussions](https://github.com/h-enk/doks/discussions) - -## Sponsors - -Support this project by becoming a sponsor. Your logo will show up here with a link to your website. - -[![OC sponsor 0](https://opencollective.com/doks/tiers/sponsor/0/avatar.svg)](https://opencollective.com/doks/tiers/sponsor/0/website) -[![OC sponsor 1](https://opencollective.com/doks/tiers/sponsor/1/avatar.svg)](https://opencollective.com/doks/tiers/sponsor/1/website) - -## Backers - -Support this project by becoming a backer. Your avatar will show up here. - -[![Backers](https://opencollective.com/doks/tiers/backer.svg?49741992)](https://opencollective.com/doks) diff --git a/docs/SECURITY.md b/docs/SECURITY.md deleted file mode 100644 index 4ad3369f..00000000 --- a/docs/SECURITY.md +++ /dev/null @@ -1,7 +0,0 @@ -# Reporting Security Issues - -The Doks team and community take security issues in Doks seriously. 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{ - "title": "ML Wiki", - "content": "Stay connected to what is happening in the wild west of AI!\n\n- Learn fundamentals\n- Stay in the know about what is going on with [[News Sources]]\n- [[Text Processing]] is important for AI", - "lastmodified": "2023-04-11T12:16:18.114044222-07:00", - "tags": null - }, - "/Applications/Chat-Bots": { - "title": "Chat Bots", - "content": "- [Knowledge Graph-Based Chatbot With GPT-3 and Neo4j](https://medium.com/neo4j/knowledge-graph-based-chatbot-with-gpt-3-and-neo4j-c4ebbd325ed)\n-", - "lastmodified": "2023-04-11T12:16:18.110710908-07:00", - "tags": null - }, - "/FAISS": { - "title": "FAISS", - "content": "Project URL: https://github.com/facebookresearch/faiss\n\n### Pinecone FAISS Book\nhttps://www.pinecone.io/learn/faiss/\n\n#### Notes\n- Using the `IndexFlatL2` index alone is computationally expensive, it doesn’t scale well.\n-", - "lastmodified": "2023-04-11T12:16:18.110710908-07:00", - "tags": null - }, - "/Fundamentals": { - "title": "Fundamentals", - "content": "## Learn\n- [Amazing video series from 3 blue 1 brown](https://www.youtube.com/watch?v=aircAruvnKk\u0026list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi)", - "lastmodified": "2023-04-11T12:16:18.110710908-07:00", - "tags": null - }, - "/Hugging-Face": { - "title": "Hugging Face", - "content": "https://huggingface.co/", - "lastmodified": "2023-04-11T12:16:18.114044222-07:00", - "tags": null - }, - "/Models": { - "title": "Models", - "content": "Machine learning (ML) models are increasingly important in various industries as they enable automated predictions, decision-making, and insights from large and complex datasets. These models are designed to improve with time as they receive more data and learn to identify patterns, allowing businesses to make more accurate predictions and informed decisions. One of the prominent platforms for building and deploying state-of-the-art natural language processing (NLP) models is [[Hugging Face]]. Hugging Face provides easy-to-use libraries and tools for building and fine-tuning NLP models and is widely used by developers, data scientists, and researchers to create and train custom NLP models for various use cases, such as chatbots, sentiment analysis, and language translation.\n\n- 03/29/23 - Lit Review of currently available models https://kipp.ly/blog/transformer-taxonomy/", - "lastmodified": "2023-04-11T12:16:18.114044222-07:00", - "tags": null - }, - "/News-Sources": { - "title": "News Sources", - "content": "Places you can go to stay plugged in about AI advancements!\n\n## Awesome Lists\n- https://github.com/imaurer/awesome-decentralized-llm\n\n## Feeds\n\n- [HackerNews](https://news.ycombinator.com/)\n\n## Discord\n- [LunaBrain](https://discord.gg/4KhauRRA)\n- [LangChain](https://discord.gg/S7qDt6Qh)\n- [LlamaIndex](https://discord.gg/UTvXb2Tp)\n- [Replicate](https://discord.gg/replicate)", - "lastmodified": "2023-04-11T12:16:18.114044222-07:00", - "tags": null - }, - "/Text-Processing": { - "title": "Text Processing", - "content": "Text normalization is a critical step in natural language processing, and machine learning (ML) techniques have proven to be effective in this domain. ML text normalization techniques involve training models on large corpora of text to learn patterns and rules for standardizing text. These models can then be used to automatically correct spelling errors, expand contractions, and transform abbreviations to their full forms. By using ML text normalization techniques, NLP applications can better understand and process text data, leading to more accurate and efficient analysis.\n\n## Text Normalization Techniques for Machine Learning\n\n### Introduction\n- Definition of text normalization\n- Importance of text normalization in NLP\n\n### Rule-Based Text Normalization\n- Overview of rule-based text normalization\n- Techniques for rule-based text normalization (e.g., stemming, lemmatization, stop-word removal)\n- Advantages and disadvantages of rule-based text normalization\n\n### Machine Learning Text Normalization\n- Overview of machine learning text normalization\n- Techniques for machine learning text normalization (e.g., sequence labeling, deep learning, unsupervised learning)\n- Advantages and disadvantages of machine learning text normalization\n\n### Comparison of Rule-Based and Machine Learning Text Normalization\n- Differences between rule-based and machine learning text normalization\n- Use cases for each technique\n- Best practices for selecting the appropriate technique\n\n### Applications of Text Normalization in NLP\n- Overview of NLP applications that require text normalization (e.g., sentiment analysis, named entity recognition, machine translation)\n- Case studies demonstrating the importance of text normalization in NLP applications", - "lastmodified": "2023-04-11T12:16:18.114044222-07:00", - "tags": null - }, - "/Vector-Search": { - "title": "Vector Search", - "content": "[Awesome List](https://github.com/currentslab/awesome-vector-search)\n\n## Tools\n### Open Source\n- [[FAISS]] - Facebook Vector Search\n- https://github.com/nmslib/hnswlib/ \"supposedly lower memory requirements and allows for adding new vectors to an existing index\"\n- \"If you do have a tiny index and want to try Google's version of vector search (as an alternative to Faiss), you can easily run ScaNN locally\" https://github.com/google-research/google-research/tree/master/scann\n\n\n- https://github.com/qdrant/qdrant\n- https://github.com/hora-search/hora\n- [OpenAI Plugin](https://github.com/openai/chatgpt-retrieval-plugin)", - "lastmodified": "2023-04-11T12:16:18.114044222-07:00", - "tags": null - } -} \ No newline at end of file diff --git a/docs/assets/indices/linkIndex.json b/docs/assets/indices/linkIndex.json deleted file mode 100644 index ed062ba8..00000000 --- a/docs/assets/indices/linkIndex.json +++ /dev/null @@ -1,84 +0,0 @@ -{ - "index": { - "links": { - "/": [ - { - "source": "/", - "target": "/News-Sources", - "text": "News Sources" - }, - { - "source": "/", - "target": "/Text-Processing", - "text": "Text Processing" - } - ], - "/Models": [ - { - "source": "/Models", - "target": "/Hugging-Face", - "text": "Hugging Face" - } - ], - "/Vector-Search": [ - { - "source": "/Vector-Search", - "target": "/FAISS", - "text": "FAISS" - } - ] - }, - "backlinks": { - "/FAISS": [ - { - "source": "/Vector-Search", - "target": "/FAISS", - "text": "FAISS" - } - ], - "/Hugging-Face": [ - { - "source": "/Models", - "target": "/Hugging-Face", - "text": "Hugging Face" - } - ], - "/News-Sources": [ - { - "source": "/", - "target": "/News-Sources", - "text": "News Sources" - } - ], - "/Text-Processing": [ - { - "source": "/", - "target": "/Text-Processing", - "text": "Text Processing" - } - ] - } - }, - "links": [ - { - "source": "/Models", - "target": "/Hugging-Face", - "text": "Hugging Face" - }, - { - "source": "/Vector-Search", - "target": "/FAISS", - "text": "FAISS" - }, - { - "source": "/", - "target": "/News-Sources", - "text": "News Sources" - }, - { - "source": "/", - "target": "/Text-Processing", - "text": "Text Processing" - } - ] -} \ No newline at end of file diff --git a/docs/assets/js/app.js b/docs/assets/js/app.js deleted file mode 100644 index 9c6c6967..00000000 --- a/docs/assets/js/app.js +++ /dev/null @@ -1 +0,0 @@ -/** Custom scripts */ diff --git a/docs/assets/js/callouts.js b/docs/assets/js/callouts.js deleted file mode 100644 index 080bbb48..00000000 --- a/docs/assets/js/callouts.js +++ /dev/null @@ -1,6 +0,0 @@ -const addCollapsibleCallouts = () => { - const collapsibleCallouts = document.querySelectorAll("blockquote.callout-collapsible"); - collapsibleCallouts.forEach(el => el.addEventListener('click', event => { - event.currentTarget.classList.toggle("callout-collapsed"); - })); -} diff --git a/docs/assets/js/clipboard.js b/docs/assets/js/clipboard.js deleted file mode 100644 index 10e02c68..00000000 --- a/docs/assets/js/clipboard.js +++ /dev/null @@ -1,45 +0,0 @@ -const svgCopy = - ''; -const svgCheck = - ''; - - -const addCopyButtons = () => { - let els = document.getElementsByClassName("highlight"); - // for each highlight - for (let i = 0; i < els.length; i++) { - try { - if (els[i].getElementsByClassName("clipboard-button").length) continue; - - // find pre > code inside els[i] - let codeBlocks = els[i].getElementsByTagName("code"); - - // line numbers are inside first code block - let lastCodeBlock = codeBlocks[codeBlocks.length - 1]; - const button = document.createElement("button"); - button.className = "clipboard-button"; - button.type = "button"; - button.innerHTML = svgCopy; - button.ariaLabel = "opy the shown code"; - // remove every second newline from lastCodeBlock.innerText - button.addEventListener("click", () => { - navigator.clipboard.writeText(lastCodeBlock.innerText.replace(/\n\n/g, "\n")).then( - () => { - button.blur(); - button.innerHTML = svgCheck; - setTimeout(() => { - button.innerHTML = svgCopy - button.style.borderColor = "" - }, 2000); - }, - (error) => (button.innerHTML = "Error") - ); - }); - // find chroma inside els[i] - let chroma = els[i].getElementsByClassName("chroma")[0]; - els[i].insertBefore(button, chroma); - } catch(error) { - console.debug(error); - } - } -} diff --git a/docs/assets/js/code-title.js b/docs/assets/js/code-title.js deleted file mode 100644 index 325e16d5..00000000 --- a/docs/assets/js/code-title.js +++ /dev/null @@ -1,17 +0,0 @@ - -function addTitleToCodeBlocks() { - const els = document.getElementsByClassName("highlight"); - for (let i = 0; i < els.length; i++) { - try { - if (els[i].title.length) { - let div = document.createElement("div"); - if (els[i].getElementsByClassName("code-title").length) continue; - div.textContent = els[i].title; - div.classList.add("code-title") - els[i].insertBefore(div, els[i].firstChild); - } - } catch (error) { - console.debug(error); - } - } -} diff --git a/docs/assets/js/full-text-search.js b/docs/assets/js/full-text-search.js deleted file mode 100644 index 709a3b36..00000000 --- a/docs/assets/js/full-text-search.js +++ /dev/null @@ -1,61 +0,0 @@ -; (async function() { - const encoder = (str) => str.toLowerCase().split(/([^a-z]|[^\x00-\x7F])/) - const contentIndex = new FlexSearch.Document({ - cache: true, - charset: "latin:extra", - optimize: true, - index: [ - { - field: "content", - tokenize: "reverse", - encode: encoder, - }, - { - field: "title", - tokenize: "forward", - encode: encoder, - }, - ], - }) - - const { content } = await fetchData - for (const [key, value] of Object.entries(content)) { - contentIndex.add({ - id: key, - title: value.title, - content: removeMarkdown(value.content), - }) - } - - const formatForDisplay = (id) => ({ - id, - url: id, - title: content[id].title, - content: content[id].content, - }) - - registerHandlers((e) => { - const term = e.target.value - const searchResults = contentIndex.search(term, [ - { - field: "content", - limit: 10, - }, - { - field: "title", - limit: 5, - }, - ]) - const getByField = (field) => { - const results = searchResults.filter((x) => x.field === field) - if (results.length === 0) { - return [] - } else { - return [...results[0].result] - } - } - const allIds = new Set([...getByField("title"), ...getByField("content")]) - const finalResults = [...allIds].map(formatForDisplay) - displayResults(term, finalResults, true) - }) -})() diff --git a/docs/assets/js/graph.js b/docs/assets/js/graph.js deleted file mode 100644 index ce0c73b7..00000000 --- a/docs/assets/js/graph.js +++ /dev/null @@ -1,279 +0,0 @@ -async function drawGraph(baseUrl, isHome, pathColors, graphConfig) { - - let { - depth, - enableDrag, - enableLegend, - enableZoom, - opacityScale, - scale, - repelForce, - fontSize } = graphConfig; - - const container = document.getElementById("graph-container") - const { index, links, content } = await fetchData - - // Use .pathname to remove hashes / searchParams / text fragments - const cleanUrl = window.location.origin + window.location.pathname - - const curPage = cleanUrl.replace(/\/$/g, "").replace(baseUrl, "") - - const parseIdsFromLinks = (links) => [ - ...new Set(links.flatMap((link) => [link.source, link.target])), - ] - - // Links is mutated by d3. We want to use links later on, so we make a copy and pass that one to d3 - // Note: shallow cloning does not work because it copies over references from the original array - const copyLinks = JSON.parse(JSON.stringify(links)) - - const neighbours = new Set() - const wl = [curPage || "/", "__SENTINEL"] - if (depth >= 0) { - while (depth >= 0 && wl.length > 0) { - // compute neighbours - const cur = wl.shift() - if (cur === "__SENTINEL") { - depth-- - wl.push("__SENTINEL") - } else { - neighbours.add(cur) - const outgoing = index.links[cur] || [] - const incoming = index.backlinks[cur] || [] - wl.push(...outgoing.map((l) => l.target), ...incoming.map((l) => l.source)) - } - } - } else { - parseIdsFromLinks(copyLinks).forEach((id) => neighbours.add(id)) - } - - const data = { - nodes: [...neighbours].map((id) => ({ id })), - links: copyLinks.filter((l) => neighbours.has(l.source) && neighbours.has(l.target)), - } - - const color = (d) => { - if (d.id === curPage || (d.id === "/" && curPage === "")) { - return "var(--g-node-active)" - } - - for (const pathColor of pathColors) { - const path = Object.keys(pathColor)[0] - const colour = pathColor[path] - if (d.id.startsWith(path)) { - return colour - } - } - - return "var(--g-node)" - } - - const drag = (simulation) => { - function dragstarted(event, d) { - if (!event.active) simulation.alphaTarget(1).restart() - d.fx = d.x - d.fy = d.y - } - - function dragged(event, d) { - d.fx = event.x - d.fy = event.y - } - - function dragended(event, d) { - if (!event.active) simulation.alphaTarget(0) - d.fx = null - d.fy = null - } - - const noop = () => { } - return d3 - .drag() - .on("start", enableDrag ? dragstarted : noop) - .on("drag", enableDrag ? dragged : noop) - .on("end", enableDrag ? dragended : noop) - } - - const height = Math.max(container.offsetHeight, isHome ? 500 : 250) - const width = container.offsetWidth - - const simulation = d3 - .forceSimulation(data.nodes) - .force("charge", d3.forceManyBody().strength(-100 * repelForce)) - .force( - "link", - d3 - .forceLink(data.links) - .id((d) => d.id) - .distance(40), - ) - .force("center", d3.forceCenter()) - - const svg = d3 - .select("#graph-container") - .append("svg") - .attr("width", width) - .attr("height", height) - .attr('viewBox', [-width / 2 / scale, -height / 2 / scale, width / scale, height / scale]) - - if (enableLegend) { - const legend = [{ Current: "var(--g-node-active)" }, { Note: "var(--g-node)" }, ...pathColors] - legend.forEach((legendEntry, i) => { - const key = Object.keys(legendEntry)[0] - const colour = legendEntry[key] - svg - .append("circle") - .attr("cx", -width / 2 + 20) - .attr("cy", height / 2 - 30 * (i + 1)) - .attr("r", 6) - .style("fill", colour) - svg - .append("text") - .attr("x", -width / 2 + 40) - .attr("y", height / 2 - 30 * (i + 1)) - .text(key) - .style("font-size", "15px") - .attr("alignment-baseline", "middle") - }) - } - - // draw links between nodes - const link = svg - .append("g") - .selectAll("line") - .data(data.links) - .join("line") - .attr("class", "link") - .attr("stroke", "var(--g-link)") - .attr("stroke-width", 2) - .attr("data-source", (d) => d.source.id) - .attr("data-target", (d) => d.target.id) - - // svg groups - const graphNode = svg.append("g").selectAll("g").data(data.nodes).enter().append("g") - - // calculate radius - const nodeRadius = (d) => { - const numOut = index.links[d.id]?.length || 0 - const numIn = index.backlinks[d.id]?.length || 0 - return 2 + Math.sqrt(numOut + numIn) - } - - // draw individual nodes - const node = graphNode - .append("circle") - .attr("class", "node") - .attr("id", (d) => d.id) - .attr("r", nodeRadius) - .attr("fill", color) - .style("cursor", "pointer") - .on("click", (_, d) => { - // SPA navigation - const targ = `${baseUrl}${decodeURI(d.id).replace(/\s+/g, "-")}/` - window.Million.navigate(new URL(targ), ".singlePage") - plausible("Link Click", { - props: { - href: targ, - broken: false, - internal: true, - graph: true, - } - }) - }) - .on("mouseover", function(_, d) { - d3.selectAll(".node").transition().duration(100).attr("fill", "var(--g-node-inactive)") - - const neighbours = parseIdsFromLinks([ - ...(index.links[d.id] || []), - ...(index.backlinks[d.id] || []), - ]) - const neighbourNodes = d3.selectAll(".node").filter((d) => neighbours.includes(d.id)) - const currentId = d.id - window.Million.prefetch(new URL(`${baseUrl}${decodeURI(d.id).replace(/\s+/g, "-")}/`)) - const linkNodes = d3 - .selectAll(".link") - .filter((d) => d.source.id === currentId || d.target.id === currentId) - - // highlight neighbour nodes - neighbourNodes.transition().duration(200).attr("fill", color) - - // highlight links - linkNodes.transition().duration(200).attr("stroke", "var(--g-link-active)") - - const bigFont = fontSize * 1.5 - - // show text for self - d3.select(this.parentNode) - .raise() - .select("text") - .transition() - .duration(200) - .attr('opacityOld', d3.select(this.parentNode).select('text').style("opacity")) - .style('opacity', 1) - .style('font-size', bigFont + 'em') - .attr('dy', d => nodeRadius(d) + 20 + 'px') // radius is in px - }) - .on("mouseleave", function(_, d) { - d3.selectAll(".node").transition().duration(200).attr("fill", color) - - const currentId = d.id - const linkNodes = d3 - .selectAll(".link") - .filter((d) => d.source.id === currentId || d.target.id === currentId) - - linkNodes.transition().duration(200).attr("stroke", "var(--g-link)") - - d3.select(this.parentNode) - .select("text") - .transition() - .duration(200) - .style('opacity', d3.select(this.parentNode).select('text').attr("opacityOld")) - .style('font-size', fontSize + 'em') - .attr('dy', d => nodeRadius(d) + 8 + 'px') // radius is in px - }) - .call(drag(simulation)) - - // draw labels - const labels = graphNode - .append("text") - .attr("dx", 0) - .attr("dy", (d) => nodeRadius(d) + 8 + "px") - .attr("text-anchor", "middle") - .text((d) => content[d.id]?.title || (d.id.charAt(1).toUpperCase() + d.id.slice(2)).replace("-", " ")) - .style('opacity', (opacityScale - 1) / 3.75) - .style("pointer-events", "none") - .style('font-size', fontSize + 'em') - .raise() - .call(drag(simulation)) - - // set panning - - if (enableZoom) { - svg.call( - d3 - .zoom() - .extent([ - [0, 0], - [width, height], - ]) - .scaleExtent([0.25, 4]) - .on("zoom", ({ transform }) => { - link.attr("transform", transform) - node.attr("transform", transform) - const scale = transform.k * opacityScale; - const scaledOpacity = Math.max((scale - 1) / 3.75, 0) - labels.attr("transform", transform).style("opacity", scaledOpacity) - }), - ) - } - - // progress the simulation - simulation.on("tick", () => { - link - .attr("x1", (d) => d.source.x) - .attr("y1", (d) => d.source.y) - .attr("x2", (d) => d.target.x) - .attr("y2", (d) => d.target.y) - node.attr("cx", (d) => d.x).attr("cy", (d) => d.y) - labels.attr("x", (d) => d.x).attr("y", (d) => d.y) - }) -} diff --git a/docs/assets/js/highlight.js b/docs/assets/js/highlight.js deleted file mode 100644 index cfcbfba4..00000000 --- a/docs/assets/js/highlight.js +++ /dev/null @@ -1,28 +0,0 @@ -import hljs from 'highlight.js/lib/core'; - -import javascript from 'highlight.js/lib/languages/javascript'; -import typescript from 'highlight.js/lib/languages/typescript'; -import json from 'highlight.js/lib/languages/json'; -import bash from 'highlight.js/lib/languages/bash'; -import ini from 'highlight.js/lib/languages/ini'; -import yaml from 'highlight.js/lib/languages/yaml'; -import markdown from 'highlight.js/lib/languages/markdown'; -import python from 'highlight.js/lib/languages/python'; - -hljs.registerLanguage('javascript', javascript); -hljs.registerLanguage('typescript', typescript); - -hljs.registerLanguage('json', json); -hljs.registerLanguage('bash', bash); -hljs.registerLanguage('ini', ini); -hljs.registerLanguage('toml', ini); -hljs.registerLanguage('yaml', yaml); -hljs.registerLanguage('md', markdown); -hljs.registerLanguage('python', python); - - -document.addEventListener('DOMContentLoaded', () => { - document.querySelectorAll('pre code').forEach((block) => { - hljs.highlightBlock(block); - }); -}); diff --git a/docs/assets/js/popover.js b/docs/assets/js/popover.js deleted file mode 100644 index 101d1c0c..00000000 --- a/docs/assets/js/popover.js +++ /dev/null @@ -1,79 +0,0 @@ -function htmlToElement(html) { - const template = document.createElement("template") - html = html.trim() - template.innerHTML = html - return template.content.firstChild -} - -function initPopover(baseURL, useContextualBacklinks) { - const basePath = baseURL.replace(window.location.origin, "") - fetchData.then(({ content }) => { - const links = [...document.getElementsByClassName("internal-link")] - links - .filter(li => li.dataset.src || (li.dataset.idx && useContextualBacklinks)) - .forEach(li => { - let el - if (li.dataset.ctx) { - const linkDest = content[li.dataset.src] - const popoverElement = `
-

${linkDest.title}

-

${highlight(removeMarkdown(linkDest.content), li.dataset.ctx)}...

-

${new Date(linkDest.lastmodified).toLocaleDateString()}

-
` - el = htmlToElement(popoverElement) - } else { - const linkDest = content[li.dataset.src.replace(/\/$/g, "").replace(basePath, "")] - if (linkDest) { - let splitLink = li.href.split("#") - let cleanedContent = removeMarkdown(linkDest.content) - if (splitLink.length > 1) { - let headingName = decodeURIComponent(splitLink[1]).replace(/\-/g, " ") - let headingIndex = cleanedContent.toLowerCase().indexOf("" + headingName + "") - cleanedContent = cleanedContent.substring(headingIndex, cleanedContent.length) - } - const popoverElement = `
-

${linkDest.title}

-

${cleanedContent.split(" ", 20).join(" ")}...

-

${new Date(linkDest.lastmodified).toLocaleDateString()}

-
` - el = htmlToElement(popoverElement) - } - } - - if (el) { - li.appendChild(el) - if (LATEX_ENABLED) { - renderMathInElement(el, { - delimiters: [ - { left: '$$', right: '$$', display: false }, - { left: '$', right: '$', display: false }, - ], - throwOnError: false - }) - } - - li.addEventListener("mouseover", () => { - // fix tooltip positioning - window.FloatingUIDOM.computePosition(li, el, { - middleware: [window.FloatingUIDOM.offset(10), window.FloatingUIDOM.inline(), window.FloatingUIDOM.shift()], - }).then(({ x, y }) => { - Object.assign(el.style, { - left: `${x}px`, - top: `${y}px`, - }) - }) - - el.classList.add("visible") - plausible("Popover Hover", { - props: { - href: li.dataset.src - } - }) - }) - li.addEventListener("mouseout", () => { - el.classList.remove("visible") - }) - } - }) - }) -} diff --git a/docs/assets/js/router.js b/docs/assets/js/router.js deleted file mode 100644 index c29ab773..00000000 --- a/docs/assets/js/router.js +++ /dev/null @@ -1,25 +0,0 @@ -import { - apply, - navigate, - prefetch, - router, -} from "https://unpkg.com/million@1.11.5/dist/router.mjs" - -export const attachSPARouting = (init, rerender) => { - // Attach SPA functions to the global Million namespace - window.Million = { - apply, - navigate, - prefetch, - router, - } - - const render = () => requestAnimationFrame(rerender) - window.addEventListener("DOMContentLoaded", () => { - apply((doc) => init(doc)) - init() - router(".singlePage") - render() - }) - window.addEventListener("million:navigate", render) -} diff --git a/docs/assets/js/semantic-search.js b/docs/assets/js/semantic-search.js deleted file mode 100644 index fca2851e..00000000 --- a/docs/assets/js/semantic-search.js +++ /dev/null @@ -1,54 +0,0 @@ -// Note: Currently, we use the REST API for Operand because of some unpkg/webpack issues. -// In the future, we'd like to use the SDK (https://github.com/operandinc/typescript-sdk). -// If someone knows how to do this w/o breaking the Operand typescript-sdk for npm users, -// please let Morgan (@morgallant) and/or (@_jzhao) know! <3 - -const apiKey = "{{$.Site.Data.config.search.operandApiKey}}" -const indexId = "{{$.Site.Data.config.search.operandIndexId}}" - -function parseSearchResults(searchResults) { - return searchResults.matches.map((m) => ({ - content: m.content, - title: searchResults.objects[m.objectId].properties.properties._title.text, - url: searchResults.objects[m.objectId].properties.properties._url.text, - })) -} - -async function searchContents(query) { - const result = await fetch("https://api.operand.ai/operand.v1.ObjectService/SearchWithin", { - method: "POST", - headers: { - "Content-Type": "application/json", - Authorization: `${apiKey}`, - "Operand-Index-ID": `${indexId}`, - }, - body: JSON.stringify({ - query: query, - limit: 10, - }), - }) - if (result.ok) { - return parseSearchResults(await result.json()) - } else { - console.error(result) - } -} - -function debounce(func, timeout = 200) { - let timer - return (...args) => { - clearTimeout(timer) - timer = setTimeout(() => { - func.apply(this, args) - }, timeout) - } -} - -registerHandlers( - debounce((e) => { - let term = e.target.value - if (term !== "") { - searchContents(term).then((results) => displayResults(term, results)) - } - }), -) diff --git a/docs/assets/js/util.js b/docs/assets/js/util.js deleted file mode 100644 index 530bd7dc..00000000 --- a/docs/assets/js/util.js +++ /dev/null @@ -1,226 +0,0 @@ -// code from https://github.com/danestves/markdown-to-text -const removeMarkdown = ( - markdown, - options = { - listUnicodeChar: false, - stripListLeaders: true, - gfm: true, - useImgAltText: false, - preserveLinks: false, - }, -) => { - let output = markdown || "" - output = output.replace(/^(-\s*?|\*\s*?|_\s*?){3,}\s*$/gm, "") - - try { - if (options.stripListLeaders) { - if (options.listUnicodeChar) - output = output.replace(/^([\s\t]*)([\*\-\+]|\d+\.)\s+/gm, options.listUnicodeChar + " $1") - else output = output.replace(/^([\s\t]*)([\*\-\+]|\d+\.)\s+/gm, "$1") - } - if (options.gfm) { - output = output - .replace(/\n={2,}/g, "\n") - .replace(/~{3}.*\n/g, "") - .replace(/~~/g, "") - .replace(/`{3}.*\n/g, "") - } - if (options.preserveLinks) { - output = output.replace(/\[(.*?)\][\[\(](.*?)[\]\)]/g, "$1 ($2)") - } - output = output - .replace(/<[^>]*>/g, "") - .replace(/^[=\-]{2,}\s*$/g, "") - .replace(/\[\^.+?\](\: .*?$)?/g, "") - .replace(/(#{1,6})\s+(.+)\1?/g, "$2") - .replace(/\s{0,2}\[.*?\]: .*?$/g, "") - .replace(/\!\[(.*?)\][\[\(].*?[\]\)]/g, options.useImgAltText ? "$1" : "") - .replace(/\[(.*?)\][\[\(].*?[\]\)]/g, "
$1") - .replace(/!?\[\[\S[^\[\]\|]*(?:\|([^\[\]]*))?\S\]\]/g, "$1") - .replace(/^\s{0,3}>\s?/g, "") - .replace(/(^|\n)\s{0,3}>\s?/g, "\n\n") - .replace(/^\s{1,2}\[(.*?)\]: (\S+)( ".*?")?\s*$/g, "") - .replace(/([\*_]{1,3})(\S.*?\S?)\1/g, "$2") - .replace(/([\*_]{1,3})(\S.*?\S?)\1/g, "$2") - .replace(/(`{3,})(.*?)\1/gm, "$2") - .replace(/`(.+?)`/g, "$1") - .replace(/\n{2,}/g, "\n\n") - .replace(/\[![a-zA-Z]+\][-\+]? /g, "") - } catch (e) { - console.error(e) - return markdown - } - return output -} - -const highlight = (content, term) => { - const highlightWindow = 20 - // try to find direct match first - const directMatchIdx = content.indexOf(term) - if (directMatchIdx !== -1) { - const h = highlightWindow - const before = content.substring(0, directMatchIdx).split(" ").slice(-h) - const after = content - .substring(directMatchIdx + term.length, content.length - 2) - .split(" ") - .slice(0, h) - return ( - (before.length === h ? `...${before.join(" ")}` : before.join(" ")) + - `${term}` + - after.join(" ") - ) - } - - const tokenizedTerm = term.split(/\s+/).filter((t) => t !== "") - const splitText = content.split(/\s+/).filter((t) => t !== "") - const includesCheck = (token) => - tokenizedTerm.some((term) => token.toLowerCase().startsWith(term.toLowerCase())) - - const occurrencesIndices = splitText.map(includesCheck) - - // calculate best index - let bestSum = 0 - let bestIndex = 0 - for (let i = 0; i < Math.max(occurrencesIndices.length - highlightWindow, 0); i++) { - const window = occurrencesIndices.slice(i, i + highlightWindow) - const windowSum = window.reduce((total, cur) => total + cur, 0) - if (windowSum >= bestSum) { - bestSum = windowSum - bestIndex = i - } - } - - const startIndex = Math.max(bestIndex - highlightWindow, 0) - const endIndex = Math.min(startIndex + 2 * highlightWindow, splitText.length) - const mappedText = splitText - .slice(startIndex, endIndex) - .map((token) => { - if (includesCheck(token)) { - return `${token}` - } - return token - }) - .join(" ") - .replaceAll(' ', " ") - return `${startIndex === 0 ? "" : "..."}${mappedText}${endIndex === splitText.length ? "" : "..." - }` -} - -// Common utilities for search -const resultToHTML = ({ url, title, content }) => { - return `` -} - -const redir = (id, term) => { - const shouldTrim = PRODUCTION && SEARCH_ENABLED - const baseURLPrefix = shouldTrim ? "" : BASE_URL.replace(/\/$/g, "") - const urlString = `${baseURLPrefix}${id}#:~:text=${encodeURIComponent(term)}/` - window.Million.navigate( - new URL(urlString), - ".singlePage", - ) - closeSearch() - plausible("Search", { - props: { - term - } - }) -} - -function openSearch() { - const source = document.getElementById("search-bar") - const results = document.getElementById("results-container") - const searchContainer = document.getElementById("search-container") - if (searchContainer.style.display === "none" || searchContainer.style.display === "") { - source.value = "" - results.innerHTML = "" - searchContainer.style.display = "block" - source.focus() - } else { - searchContainer.style.display = "none" - } -} - -function closeSearch() { - const searchContainer = document.getElementById("search-container") - searchContainer.style.display = "none" -} - -const registerHandlers = (onInputFn) => { - const source = document.getElementById("search-bar") - const searchContainer = document.getElementById("search-container") - let term - source.addEventListener("keyup", (e) => { - if (e.key === "Enter") { - const anchor = document.getElementsByClassName("result-card")[0] - redir(anchor.id, term) - } - }) - source.addEventListener("input", onInputFn) - document.addEventListener("keydown", (event) => { - if (event.key === "k" && (event.ctrlKey || event.metaKey)) { - event.preventDefault() - openSearch() - } - if (event.key === "Escape") { - event.preventDefault() - closeSearch() - } - }) - - const searchButton = document.getElementById("search-icon") - searchButton.addEventListener("click", (_) => { - openSearch() - }) - searchButton.addEventListener("keydown", (_) => { - openSearch() - }) - searchContainer.addEventListener("click", (_) => { - closeSearch() - }) - document.getElementById("search-space").addEventListener("click", (evt) => { - evt.stopPropagation() - }) -} - -const displayResults = (term, finalResults, extractHighlight = false) => { - const results = document.getElementById("results-container") - if (finalResults.length === 0) { - results.innerHTML = `` - } else { - results.innerHTML = finalResults - .map((result) => { - if (extractHighlight) { - return resultToHTML({ - url: result.url, - title: highlight(result.title, term), - content: highlight(removeMarkdown(result.content), term) - }) - } else { - return resultToHTML(result) - } - } - ) - .join("\n") - if (LATEX_ENABLED) { - renderMathInElement(results, { - delimiters: [ - { left: '$$', right: '$$', display: false }, - { left: '$', right: '$', display: false }, - ], - throwOnError: false - }) - } - - const anchors = [...document.getElementsByClassName("result-card")] - anchors.forEach((anchor) => { - anchor.onclick = () => redir(anchor.id, term) - }) - } -} diff --git a/docs/assets/scss/app.scss b/docs/assets/scss/app.scss deleted file mode 100644 index 3cc821b2..00000000 --- a/docs/assets/scss/app.scss +++ /dev/null @@ -1,38 +0,0 @@ -/** Import Bootstrap functions */ -@import "bootstrap/scss/functions"; - -/** Import theme variables */ -@import "common/variables"; - -/** Import Bootstrap */ -@import "bootstrap/scss/bootstrap"; - -/** Import highlight.js */ -@import "highlight.js/scss/sunburst"; - -/** Import KaTeX */ -@import "katex/dist/katex"; - -/** Import theme styles */ -@import "common/fonts"; -@import "common/global"; -@import "common/dark"; -@import "components/alerts"; -@import "components/buttons"; -@import "components/code"; -@import "components/details"; -@import "components/syntax"; -@import "components/comments"; -@import "components/forms"; -@import "components/images"; -@import "components/mermaid"; -@import "components/search"; -@import "components/tables"; -@import "layouts/footer"; -@import "layouts/header"; -@import "layouts/pages"; -@import "layouts/posts"; -@import "layouts/sidebar"; - -/** Import custom styles */ -@import "common/custom"; diff --git a/docs/assets/scss/common/_custom.scss b/docs/assets/scss/common/_custom.scss deleted file mode 100644 index b4737b78..00000000 --- a/docs/assets/scss/common/_custom.scss +++ /dev/null @@ -1,6 +0,0 @@ -/** Custom styles */ - - -//code { -// background: #373737 !important; -//} diff --git a/docs/assets/styles/_callouts.scss b/docs/assets/styles/_callouts.scss deleted file mode 100644 index 04fd2f66..00000000 --- a/docs/assets/styles/_callouts.scss +++ /dev/null @@ -1,170 +0,0 @@ -:root { - --callout-summary: #00b0ff; - --callout-summary-accent: #7fd7ff; - --callout-bug: #f50057; - --callout-bug-accent: #ff7aa9; - --callout-danger: #ff1744; - --callout-danger-accent: #ff8aa1; - --callout-example: #7c4dff; - --callout-example-accent: #bda5ff; - --callout-fail: #ff5252; - --callout-fail-accent: #ffa8a8; - --callout-info: #00b8d4; - --callout-info-accent: #69ebff; - --callout-note: #448aff; - --callout-note-accent: #a1c4ff; - --callout-question: #64dd17; - --callout-question-accent: #b0f286; - --callout-quote: #9e9e9e; - --callout-quote-accent: #cecece; - --callout-done: #00c853; - --callout-done-accent: #63ffa4; - --callout-important: #00bfa5; - --callout-important-accent: #5fffe9; - --callout-warning: #ff9100; - --callout-warning-accent: #ffc87f; -} - -[saved-theme=dark] { - --callout-summary: #00b0ff !important; - --callout-summary-accent: #00587f !important; - --callout-bug: #f50057 !important; - --callout-bug-accent: #7a002b !important; - --callout-danger: #ff1744 !important; - --callout-danger-accent: #8b001a !important; - --callout-example: #7c4dff !important; - --callout-example-accent: #2b00a6 !important; - --callout-fail: #ff5252 !important; - --callout-fail-accent: #a80000 !important; - --callout-info: #00b8d4 !important; - --callout-info-accent: #005c6a !important; - --callout-note: #448aff !important; - --callout-note-accent: #003ca1 !important; - --callout-question: #64dd17 !important; - --callout-question-accent: #006429 !important; - --callout-quote: #9e9e9e !important; - --callout-quote-accent: #4f4f4f !important; - --callout-done: #00c853 !important; - --callout-done-accent: #006429 !important; - --callout-important: #00bfa5 !important; - --callout-important-accent: #005f52 !important; - --callout-warning: #ff9100 !important; - --callout-warning-accent: #7f4800 !important; -} - -blockquote.callout-collapsible { - cursor: pointer; - - &.callout-collapsible::after { - content: '-'; - right: 6px; - font-weight: bolder; - font-family: Courier New, Courier, monospace; - } -} - -blockquote.callout-collapsed { - & > p { border-bottom-right-radius: 5px !important; } - padding-bottom: 0 !important; - &::after { - content: '+' !important; - } - & > *:not(:first-child) { - display: none !important; - } -} - -blockquote[class*="-callout"] { - margin-right: 0; - border-radius: 5px; - position: relative; - padding-left: 0 !important; - padding-bottom: 0.25em; - color: var(--dark); - background-color: var(--lightgray); - border-left: 6px solid var(--primary) !important; - & > p { - border-top-right-radius: 5px; - padding: 0.5em 1em; - margin: 0; - color: var(--gray); - &:first-child { - font-weight: 600; - color: var(--dark); - padding: 0.4em 30px; - } - } -} - -blockquote[class*="-callout"] > p:first-child::after, blockquote.callout-collapsible::after { - display: inline-block; - height: 18px; - width: 18px; - position: absolute; - top: 0.4em; - margin: 0.2em 0.4em; -} - -blockquote[class*="-callout"] > p:first-child { - font-weight: bold; - padding: 0.4em 35px; - - &::after { - left: 0; - } -} - -$summary: summary, abstract, tldr; -$bug: bug; -$danger: danger, error; -$example: example; -$fail: fail, failure, missing; -$info: info, todo; -$note: note; -$question: question, help, faq; -$quote: quote, cite; -$done: done, success, check; -$important: important, tip, hint; -$warning: warning, caution, attention; -$types: $summary, $bug, $danger, $example, $fail, $info, $note, $question, $quote, $done, $important, $warning; -$svgs: (); -$svgs: map-merge($svgs, ($summary: url("data:image/svg+xml,%3Csvg aria-hidden='true' focusable='false' data-icon='book' class='svg-inline--callout-fa fa-book fa-w-14' role='img' xmlns='http://www.w3.org/2000/svg' viewBox='0 0 448 512'%3E%3Cpath fill='currentColor' d='M448 360V24c0-13.3-10.7-24-24-24H96C43 0 0 43 0 96v320c0 53 43 96 96 96h328c13.3 0 24-10.7 24-24v-16c0-7.5-3.5-14.3-8.9-18.7-4.2-15.4-4.2-59.3 0-74.7 5.4-4.3 8.9-11.1 8.9-18.6zM128 134c0-3.3 2.7-6 6-6h212c3.3 0 6 2.7 6 6v20c0 3.3-2.7 6-6 6H134c-3.3 0-6-2.7-6-6v-20zm0 64c0-3.3 2.7-6 6-6h212c3.3 0 6 2.7 6 6v20c0 3.3-2.7 6-6 6H134c-3.3 0-6-2.7-6-6v-20zm253.4 250H96c-17.7 0-32-14.3-32-32 0-17.6 14.4-32 32-32h285.4c-1.9 17.1-1.9 46.9 0 64z'%3E%3C/path%3E%3C/svg%3E"))); -$svgs: map-merge($svgs, ($bug: url("data:image/svg+xml,%3Csvg aria-hidden='true' focusable='false' data-icon='bug' class='svg-inline--callout-fa fa-bug fa-w-16' role='img' xmlns='http://www.w3.org/2000/svg' viewBox='0 0 512 512'%3E%3Cpath fill='currentColor' d='M511.988 288.9c-.478 17.43-15.217 31.1-32.653 31.1H424v16c0 21.864-4.882 42.584-13.6 61.145l60.228 60.228c12.496 12.497 12.496 32.758 0 45.255-12.498 12.497-32.759 12.496-45.256 0l-54.736-54.736C345.886 467.965 314.351 480 280 480V236c0-6.627-5.373-12-12-12h-24c-6.627 0-12 5.373-12 12v244c-34.351 0-65.886-12.035-90.636-32.108l-54.736 54.736c-12.498 12.497-32.759 12.496-45.256 0-12.496-12.497-12.496-32.758 0-45.255l60.228-60.228C92.882 378.584 88 357.864 88 336v-16H32.666C15.23 320 .491 306.33.013 288.9-.484 270.816 14.028 256 32 256h56v-58.745l-46.628-46.628c-12.496-12.497-12.496-32.758 0-45.255 12.498-12.497 32.758-12.497 45.256 0L141.255 160h229.489l54.627-54.627c12.498-12.497 32.758-12.497 45.256 0 12.496 12.497 12.496 32.758 0 45.255L424 197.255V256h56c17.972 0 32.484 14.816 31.988 32.9zM257 0c-61.856 0-112 50.144-112 112h224C369 50.144 318.856 0 257 0z'%3E%3C/path%3E%3C/svg%3E"))); -$svgs: map-merge($svgs, ($danger: url("data:image/svg+xml,%3Csvg aria-hidden='true' focusable='false' data-icon='bolt' class='svg-inline--callout-fa fa-bolt 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fill='currentColor' d='M504 256c0 136.967-111.033 248-248 248S8 392.967 8 256 119.033 8 256 8s248 111.033 248 248zM227.314 387.314l184-184c6.248-6.248 6.248-16.379 0-22.627l-22.627-22.627c-6.248-6.249-16.379-6.249-22.628 0L216 308.118l-70.059-70.059c-6.248-6.248-16.379-6.248-22.628 0l-22.627 22.627c-6.248 6.248-6.248 16.379 0 22.627l104 104c6.249 6.249 16.379 6.249 22.628.001z'%3E%3C/path%3E%3C/svg%3E"))); -$svgs: map-merge($svgs, ($important: url("data:image/svg+xml,%3Csvg aria-hidden='true' focusable='false' data-icon='fire' class='svg-inline--callout-fa fa-fire fa-w-12' role='img' xmlns='http://www.w3.org/2000/svg' viewBox='0 0 384 512'%3E%3Cpath fill='currentColor' d='M216 23.86c0-23.8-30.65-32.77-44.15-13.04C48 191.85 224 200 224 288c0 35.63-29.11 64.46-64.85 63.99-35.17-.45-63.15-29.77-63.15-64.94v-85.51c0-21.7-26.47-32.23-41.43-16.5C27.8 213.16 0 261.33 0 320c0 105.87 86.13 192 192 192s192-86.13 192-192c0-170.29-168-193-168-296.14z'%3E%3C/path%3E%3C/svg%3E"))); -$svgs: map-merge($svgs, ($warning: url("data:image/svg+xml,%3Csvg aria-hidden='true' focusable='false' data-icon='exclamation-triangle' class='svg-inline--callout-fa fa-exclamation-triangle fa-w-18' role='img' xmlns='http://www.w3.org/2000/svg' viewBox='0 0 576 512'%3E%3Cpath fill='currentColor' d='M569.517 440.013C587.975 472.007 564.806 512 527.94 512H48.054c-36.937 0-59.999-40.055-41.577-71.987L246.423 23.985c18.467-32.009 64.72-31.951 83.154 0l239.94 416.028zM288 354c-25.405 0-46 20.595-46 46s20.595 46 46 46 46-20.595 46-46-20.595-46-46-46zm-43.673-165.346l7.418 136c.347 6.364 5.609 11.346 11.982 11.346h48.546c6.373 0 11.635-4.982 11.982-11.346l7.418-136c.375-6.874-5.098-12.654-11.982-12.654h-63.383c-6.884 0-12.356 5.78-11.981 12.654z'%3E%3C/path%3E%3C/svg%3E"))); - -@function getstr($l) { - $v: nth($l, 1); - @return $v; -} - -@each $type in $types { - @each $s in $type { - blockquote.#{$s}-callout { - border-left: 6px solid var(--callout-#{getstr($type)}) !important; - & > p:first-child { - background-color: var(--callout-#{getstr($type)}-accent) !important; - &::after { - content: ''; - -webkit-mask: map-get($svgs, $type); - mask: map-get($svgs, $type); - background-color: var(--callout-#{getstr($type)}) !important; - -webkit-mask-size: contain; - mask-size: contain; - -webkit-mask-repeat: no-repeat; - mask-repeat: no-repeat; - -webkit-mask-position: center; - mask-position: center; - } - } - } - } -} diff --git a/docs/assets/styles/_dark_syntax.scss b/docs/assets/styles/_dark_syntax.scss deleted file mode 100644 index 9d2019a8..00000000 --- a/docs/assets/styles/_dark_syntax.scss +++ /dev/null @@ -1,85 +0,0 @@ -/* Background */ .bg { color: #f8f8f2; background-color: #282a36; } -/* PreWrapper */ .chroma { color: #f8f8f2; background-color: #282a36; } -/* Other */ .chroma .x { } -/* Error */ .chroma .err { } -/* CodeLine */ .chroma .cl { } -/* LineTableTD */ .chroma .lntd { vertical-align: top; padding: 0; margin: 0; border: 0; } -/* LineTable */ .chroma .lntable { border-spacing: 0; padding: 0; margin: 0; border: 0; } -/* LineHighlight */ .chroma .hl { background-color: #ffffcc } -/* LineNumbersTable */ .chroma .lnt { white-space: pre; user-select: none; margin-right: 0.4em; padding: 0 0.4em 0 0.4em;color: #7f7f7f } -/* LineNumbers */ .chroma .ln { white-space: pre; user-select: none; margin-right: 0.4em; padding: 0 0.4em 0 0.4em;color: #7f7f7f } -/* Line */ .chroma .line { display: flex; } -/* Keyword */ .chroma .k { color: #ff79c6 } -/* KeywordConstant */ .chroma .kc { color: #ff79c6 } -/* KeywordDeclaration */ .chroma .kd { color: #8be9fd; font-style: italic } -/* KeywordNamespace */ .chroma .kn { color: #ff79c6 } -/* KeywordPseudo */ .chroma .kp { color: #ff79c6 } -/* KeywordReserved */ .chroma .kr { color: #ff79c6 } -/* KeywordType */ .chroma .kt { color: #8be9fd } -/* Name */ .chroma .n { } -/* NameAttribute */ .chroma .na { color: #50fa7b } -/* NameBuiltin */ .chroma .nb { color: #8be9fd; font-style: italic } -/* NameBuiltinPseudo */ .chroma .bp { } -/* NameClass */ .chroma .nc { color: #50fa7b } -/* NameConstant */ .chroma .no { } -/* NameDecorator */ .chroma .nd { } -/* NameEntity */ .chroma .ni { } -/* NameException */ .chroma .ne { } -/* NameFunction */ .chroma .nf { color: #50fa7b } -/* NameFunctionMagic */ .chroma .fm { } -/* NameLabel */ .chroma .nl { color: #8be9fd; font-style: italic } -/* NameNamespace */ .chroma .nn { } -/* NameOther */ .chroma .nx { } -/* NameProperty */ .chroma .py { } -/* NameTag */ .chroma .nt { color: #ff79c6 } -/* NameVariable */ .chroma .nv { color: #8be9fd; font-style: italic } -/* NameVariableClass */ .chroma .vc { color: #8be9fd; font-style: italic } -/* NameVariableGlobal */ .chroma .vg { color: #8be9fd; font-style: italic } -/* NameVariableInstance */ .chroma .vi { color: #8be9fd; font-style: italic } -/* NameVariableMagic */ .chroma .vm { } -/* Literal */ .chroma .l { } -/* LiteralDate */ .chroma .ld { } -/* LiteralString */ .chroma .s { color: #f1fa8c } -/* LiteralStringAffix */ .chroma .sa { color: #f1fa8c } -/* LiteralStringBacktick */ .chroma .sb { color: #f1fa8c } -/* LiteralStringChar */ .chroma .sc { color: #f1fa8c } -/* LiteralStringDelimiter */ .chroma .dl { color: #f1fa8c } -/* LiteralStringDoc */ .chroma .sd { color: #f1fa8c } -/* LiteralStringDouble */ .chroma .s2 { color: #f1fa8c } -/* LiteralStringEscape */ .chroma .se { color: #f1fa8c } -/* LiteralStringHeredoc */ .chroma .sh { color: #f1fa8c } -/* LiteralStringInterpol */ .chroma .si { color: #f1fa8c } -/* LiteralStringOther */ .chroma .sx { color: #f1fa8c } -/* LiteralStringRegex */ .chroma .sr { color: #f1fa8c } -/* LiteralStringSingle */ .chroma .s1 { color: #f1fa8c } -/* LiteralStringSymbol */ .chroma .ss { color: #f1fa8c } -/* LiteralNumber */ .chroma .m { color: #bd93f9 } -/* LiteralNumberBin */ .chroma .mb { color: #bd93f9 } -/* LiteralNumberFloat */ .chroma .mf { color: #bd93f9 } -/* LiteralNumberHex */ .chroma .mh { color: #bd93f9 } -/* LiteralNumberInteger */ .chroma .mi { color: #bd93f9 } -/* LiteralNumberIntegerLong */ .chroma .il { color: #bd93f9 } -/* LiteralNumberOct */ .chroma .mo { color: #bd93f9 } -/* Operator */ .chroma .o { color: #ff79c6 } -/* OperatorWord */ .chroma .ow { color: #ff79c6 } -/* Punctuation */ .chroma .p { } -/* Comment */ .chroma .c { color: #6272a4 } -/* CommentHashbang */ .chroma .ch { color: #6272a4 } -/* CommentMultiline */ .chroma .cm { color: #6272a4 } -/* CommentSingle */ .chroma .c1 { color: #6272a4 } -/* CommentSpecial */ .chroma .cs { color: #6272a4 } -/* CommentPreproc */ .chroma .cp { color: #ff79c6 } -/* CommentPreprocFile */ .chroma .cpf { color: #ff79c6 } -/* Generic */ .chroma .g { } -/* GenericDeleted */ .chroma .gd { color: #ff5555 } -/* GenericEmph */ .chroma .ge { text-decoration: underline } -/* GenericError */ .chroma .gr { } -/* GenericHeading */ .chroma .gh { font-weight: bold } -/* GenericInserted */ .chroma .gi { color: #50fa7b; font-weight: bold } -/* GenericOutput */ .chroma .go { color: #44475a } -/* GenericPrompt */ .chroma .gp { } -/* GenericStrong */ .chroma .gs { } -/* GenericSubheading */ .chroma .gu { font-weight: bold } -/* GenericTraceback */ .chroma .gt { } -/* GenericUnderline */ .chroma .gl { text-decoration: underline } -/* TextWhitespace */ .chroma .w { } diff --git a/docs/assets/styles/_light_syntax.scss b/docs/assets/styles/_light_syntax.scss deleted file mode 100644 index d0f452e0..00000000 --- a/docs/assets/styles/_light_syntax.scss +++ /dev/null @@ -1,85 +0,0 @@ -/* Background */ .bg { color: #272822; background-color: #fafafa; } -/* PreWrapper */ .chroma { color: #272822; background-color: #fafafa; } -/* Other */ .chroma .x { } -/* Error */ .chroma .err { } -/* CodeLine */ .chroma .cl { } -/* LineTableTD */ .chroma .lntd { vertical-align: top; padding: 0; margin: 0; border: 0; } -/* LineTable */ .chroma .lntable { border-spacing: 0; padding: 0; margin: 0; border: 0; } -/* LineHighlight */ .chroma .hl { background-color: #ffffcc } -/* LineNumbersTable */ .chroma .lnt { white-space: pre; user-select: none; margin-right: 0.4em; padding: 0 0.4em 0 0.4em;color: #7f7f7f } -/* LineNumbers */ .chroma .ln { white-space: pre; user-select: none; margin-right: 0.4em; padding: 0 0.4em 0 0.4em;color: #7f7f7f } -/* Line */ .chroma .line { display: flex; } -/* Keyword */ .chroma .k { color: #00a8c8 } -/* KeywordConstant */ .chroma .kc { color: #00a8c8 } -/* KeywordDeclaration */ .chroma .kd { color: #00a8c8 } -/* KeywordNamespace */ .chroma .kn { color: #f92672 } -/* KeywordPseudo */ .chroma .kp { color: #00a8c8 } -/* KeywordReserved */ .chroma .kr { color: #00a8c8 } -/* KeywordType */ .chroma .kt { color: #00a8c8 } -/* Name */ .chroma .n { color: #111111 } -/* NameAttribute */ .chroma .na { color: #75af00 } -/* NameBuiltin */ .chroma .nb { color: #111111 } -/* NameBuiltinPseudo */ .chroma .bp { color: #111111 } -/* NameClass */ .chroma .nc { color: #75af00 } -/* NameConstant */ .chroma .no { color: #00a8c8 } -/* NameDecorator */ .chroma .nd { color: #75af00 } -/* NameEntity */ .chroma .ni { color: #111111 } -/* NameException */ .chroma .ne { color: #75af00 } -/* NameFunction */ .chroma .nf { color: #75af00 } -/* NameFunctionMagic */ .chroma .fm { color: #111111 } -/* NameLabel */ .chroma .nl { color: #111111 } -/* NameNamespace */ .chroma .nn { color: #111111 } -/* NameOther */ .chroma .nx { color: #75af00 } -/* NameProperty */ .chroma .py { color: #111111 } -/* NameTag */ .chroma .nt { color: #f92672 } -/* NameVariable */ .chroma .nv { color: #111111 } -/* NameVariableClass */ .chroma .vc { color: #111111 } -/* NameVariableGlobal */ .chroma .vg { color: #111111 } -/* NameVariableInstance */ .chroma .vi { color: #111111 } -/* NameVariableMagic */ .chroma .vm { color: #111111 } -/* Literal */ .chroma .l { color: #ae81ff } -/* LiteralDate */ .chroma .ld { color: #d88200 } -/* LiteralString */ .chroma .s { color: #d88200 } -/* LiteralStringAffix */ .chroma .sa { color: #d88200 } -/* LiteralStringBacktick */ .chroma .sb { color: #d88200 } -/* LiteralStringChar */ .chroma .sc { color: #d88200 } -/* LiteralStringDelimiter */ .chroma .dl { color: #d88200 } -/* LiteralStringDoc */ .chroma .sd { color: #d88200 } -/* LiteralStringDouble */ .chroma .s2 { color: #d88200 } -/* LiteralStringEscape */ .chroma .se { color: #8045ff } -/* LiteralStringHeredoc */ .chroma .sh { color: #d88200 } -/* LiteralStringInterpol */ .chroma .si { color: #d88200 } -/* LiteralStringOther */ .chroma .sx { color: #d88200 } -/* LiteralStringRegex */ .chroma .sr { color: #d88200 } -/* LiteralStringSingle */ .chroma .s1 { color: #d88200 } -/* LiteralStringSymbol */ .chroma .ss { color: #d88200 } -/* LiteralNumber */ .chroma .m { color: #ae81ff } -/* LiteralNumberBin */ .chroma .mb { color: #ae81ff } -/* LiteralNumberFloat */ .chroma .mf { color: #ae81ff } -/* LiteralNumberHex */ .chroma .mh { color: #ae81ff } -/* LiteralNumberInteger */ .chroma .mi { color: #ae81ff } -/* LiteralNumberIntegerLong */ .chroma .il { color: #ae81ff } -/* LiteralNumberOct */ .chroma .mo { color: #ae81ff } -/* Operator */ .chroma .o { color: #f92672 } -/* OperatorWord */ .chroma .ow { color: #f92672 } -/* Punctuation */ .chroma .p { color: #111111 } -/* Comment */ .chroma .c { color: #75715e } -/* CommentHashbang */ .chroma .ch { color: #75715e } -/* CommentMultiline */ .chroma .cm { color: #75715e } -/* CommentSingle */ .chroma .c1 { color: #75715e } -/* CommentSpecial */ .chroma .cs { color: #75715e } -/* CommentPreproc */ .chroma .cp { color: #75715e } -/* CommentPreprocFile */ .chroma .cpf { color: #75715e } -/* Generic */ .chroma .g { } -/* GenericDeleted */ .chroma .gd { } -/* GenericEmph */ .chroma .ge { font-style: italic } -/* GenericError */ .chroma .gr { } -/* GenericHeading */ .chroma .gh { } -/* GenericInserted */ .chroma .gi { } -/* GenericOutput */ .chroma .go { } -/* GenericPrompt */ .chroma .gp { } -/* GenericStrong */ .chroma .gs { font-weight: bold } -/* GenericSubheading */ .chroma .gu { } -/* GenericTraceback */ .chroma .gt { } -/* GenericUnderline */ .chroma .gl { } -/* TextWhitespace */ .chroma .w { } diff --git a/docs/assets/styles/base.scss b/docs/assets/styles/base.scss deleted file mode 100644 index 85eb8bcf..00000000 --- a/docs/assets/styles/base.scss +++ /dev/null @@ -1,625 +0,0 @@ -// Replace this with your own font imports! -@import url('https://fonts.googleapis.com/css2?family=Fira+Code:wght@400;700&family=Inter:wght@400;600;700&family=Source+Sans+Pro:wght@400;600&display=swap'); -:root { - --font-body: "Source Sans Pro"; - --font-header: "Inter"; - --font-mono: "Fira Code" -} - -// typography -html { - scroll-behavior: smooth; - &:lang(ar) { - & p, & h1, & h2, & h3, article, header { - direction: rtl; - text-align: right; - } - } - & footer > p { - text-align: center !important; - } -} - -.singlePage { - padding: 4em 30vw; - margin: 0 auto; - max-width: 1000px; - @media all and (max-width: 1200px) { - padding: 25px 5vw; - } -} - - -body { - margin: 0; - height: 100vh; - width: 100vw; - max-width: 100%; - box-sizing: border-box; - background-color: var(--light); -} - -h1, h2, h3, h4, h5, h6, thead { - font-family: var(--font-header); - color: var(--dark); - font-weight: revert; - margin: 2rem 0 0; - padding: 2rem auto 1rem; - - &:hover > .hanchor { - color: var(--secondary); - } -} - -.hanchor { - font-family: var(--font-header); - opacity: 0.8; - transition: color 0.3s ease; - color: var(--dark); -} - -p, ul, text, a, tr, td, li, ol, ul { - font-family: var(--font-body); - color: var(--gray); - fill: var(--gray); - font-weight: revert; - margin: revert; - padding: revert; -} - -tbody, li, p { - line-height: 1.5em; -} - -.mainTOC { - border-radius: 5px; - padding: 0.75em 0; - - & details { - & summary { - cursor: zoom-in; - font-family: var(--font-header); - color: var(--dark); - font-weight: 700; - } - - &[open] summary { - cursor: zoom-out; - } - } -} - -#TableOfContents > ol { - counter-reset: section; - margin-left: 0; - padding-left: 1.5em; - & > li { - counter-increment: section; - & > ol { - counter-reset: subsection; - & > li { - counter-increment: subsection; - &::marker { - content: counter(section) "." counter(subsection) " "; - } - } - } - } - - & > li::marker { - content: counter(section) " "; - } - - & > li::marker, & > li > ol > li::marker { - font-family: var(--font-body); - font-weight: 700; - } -} - -table { - border: 1px solid var(--outlinegray); - width: 100%; - padding: 1.5em; - border-collapse: collapse; -} - -td, th { - padding: 0.2em 1em; - border: 1px solid var(--outlinegray); -} - -img { - max-width: 100%; - border-radius: 3px; - margin: 1em 0; -} - -p > img + em { - display: block; - transform: translateY(-1em); -} - -sup { - line-height: 0 -} - -blockquote { - margin-left: 0; - border-left: 3px solid var(--secondary); - padding-left: 1em; - transition: border-color 0.2s ease; -} - -.footnotes p { - margin: 0.5em 0; -} - -.pagination { - list-style: none; - padding-left: 0; - display: flex; - margin-top: 2em; - gap: 1.5em; - justify-content: center; - - .disabled { - opacity: 0.2; - } - - & > li { - text-align: center; - display: inline-block; - - & a { - background-color: transparent !important; - } - - & a[href$="#"], &.active a { - opacity: 0.2; - } - } -} - -article { - & > h1 { - margin-top: 2em; - font-size: 2em; - } - - & > .meta { - margin: 0 0 1em 0; - opacity: 0.7; - } - - & a { - font-weight: 600; - - &.internal-link { - text-decoration: none; - background-color: transparentize(#8f9fa9, 0.85); - padding: 0 0.1em; - margin: auto -0.1em; - border-radius: 3px; - - &.broken { - opacity: 0.5; - background-color: transparent; - } - } - } - - & p { - overflow-wrap: anywhere; - } -} - -.tags { - list-style: none; - padding-left: 0; - - & .meta { - margin: 1.5em 0; - & > h1 { - margin: 0; - } - & > p { - margin: 0; - } - } - - & > li { - display: inline-block; - margin: 0.4em 0.2em; - } - - & > li > a { - border-radius: 8px; - border: var(--outlinegray) 1px solid; - padding: 0.2em 0.5em; - &::before { - content: "#"; - margin-right: 0.3em; - color: var(--outlinegray); - } - } -} - -.backlinks a { - font-weight: 600; - font-size: 0.9rem; -} - -sup > a { - text-decoration: none; - padding: 0 0.1em 0 0.2em; -} - -#page-title { - margin: 0; - & > a { - font-family: var(--font-header); - } -} - -a { - font-size: 1em; - font-weight: 700; - text-decoration: none; - transition: all 0.2s ease; - color: var(--secondary); - &:hover { - color: var(--tertiary) !important; - } -} - -pre { - font-family: var(--font-mono); - padding: 0.75em; - border-radius: 3px; - overflow-x: scroll; -} - -code { - font-family: var(--font-mono); - font-size: 0.85em; - padding: 0.15em 0.3em; - border-radius: 5px; - background: var(--lightgray); -} - -@keyframes fadeIn { - 0% {opacity:0;} - 100% {opacity:1;} -} - -footer { - margin-top: 4em; - text-align: center; - & ul { - padding-left: 0; - } -} - -hr { - width: 100%; - margin: 2em auto; - height: 1px; - border: none; - background-color: var(--outlinegray); -} - -.page-end { - display: flex; - flex-direction: row; - gap: 2em; - - @media all and (max-width: 780px) { - flex-direction: column; - } - - & > * { - flex: 1 0 0; - } - - & > .backlinks-container { - & > ul { - list-style: none; - padding: 0; - margin: 0; - - & > li { - margin: 0.5em 0; - padding: 0.25em 1em; - border: var(--outlinegray) 1px solid; - border-radius: 5px - } - } - } - - & #graph-container { - border: var(--outlinegray) 1px solid; - border-radius: 5px; - box-sizing: border-box; - min-height: 250px; - margin: 0.5em 0; - - & > svg { - margin-bottom: -5px; - - } - } -} - -.centered { - margin-top: 30vh; -} - -.spacer { - flex: 1 1 auto; -} - -header { - display: flex; - flex-direction: row; - align-items: center; - margin: 1em 0 2em; - - & > h1 { - font-size: 2em; - } - - & > nav { - @media all and (max-width: 600px) { - display: none; - } - } - - #search-icon { - background-color: var(--lightgray); - border-radius: 4px; - height: 2em; - display: flex; - align-items: center; - cursor: pointer; - & > p { - display: inline; - padding: 0 1.5em 0 2em; - } - } - - & svg { - cursor: pointer; - width: 18px; - min-width: 18px; - margin: 0 0.5em; - - &:hover .search-path { - stroke: var(--tertiary); - } - - .search-path { - stroke: var(--gray); - stroke-width: 2px; - transition: stroke 0.5s ease; - } - } -} - -#search-container { - position: fixed; - z-index: 9999; - left: 0; - top: 0; - width: 100vw; - height: 100%; - overflow: scroll; - display: none; - backdrop-filter: blur(4px); - -webkit-backdrop-filter: blur(4px); - - & > div { - width: 50%; - margin-top: 15vh; - margin-left: auto; - margin-right: auto; - - @media all and (max-width: 1200px) { - width: 90%; - } - - & > * { - width: 100%; - border-radius: 4px; - background: var(--light); - box-shadow: 0 14px 50px rgba(27, 33, 48, 0.12), 0 10px 30px rgba(27, 33, 48, 0.16); - margin-bottom: 2em; - } - - & > input { - box-sizing: border-box; - padding: 0.5em 1em; - font-family: var(--font-body); - color: var(--dark); - font-size: 1.1em; - border: 1px solid var(--outlinegray); - - &:focus { - outline: none; - } - } - - & > #results-container { - & .result-card { - padding: 1em; - cursor: pointer; - transition: background 0.2s ease; - border: 1px solid var(--outlinegray); - border-bottom: none; - width: 100%; - - // normalize button props - font-family: inherit; - font-size: 100%; - line-height: 1.15; - margin: 0; - overflow: visible; - text-transform: none; - text-align: left; - background: var(--light); - outline: none; - - &:hover, &:focus { - background: rgba(180, 180, 180, 0.15); - } - - &:first-of-type { - border-top-left-radius: 5px; - border-top-right-radius: 5px; - } - - &:last-of-type { - border-bottom-left-radius: 5px; - border-bottom-right-radius: 5px; - border-bottom: 1px solid var(--outlinegray); - } - - & > h3, & > p { - margin: 0; - } - } - } - } -} - -.search-highlight { - background-color: #afbfc966; - padding: 0.05em 0.2em; - border-radius: 3px; -} - -.section-ul { - list-style: none; - margin-top: 2em; - padding-left: 0; - -} - -.section-li { - margin-bottom: 1em; - - & > .section { - display: flex; - align-items: center; - - @media all and (max-width: 600px) { - & .tags { - display: none; - } - } - - & h3 > a { - font-weight: 700; - margin: 0; - } - - & p { - margin: 0; - padding-right: 1em; - flex-basis: 6em; - } - } - - & h3 { - opacity: 1; - font-weight: 700; - margin: 0; - } - - & .meta { - opacity: 0.6; - } -} - -@keyframes dropin { - 0% { - display: none; - opacity: 0; - visibility: hidden; - } - 1% { - display: inline-block; - opacity: 0; - } - 100% { - opacity: 1; - visibility: visible; - } -} - -.popover { - z-index: 999; - position: absolute; - width: 20rem; - display: none; - background-color: var(--light); - padding: 1rem; - margin: 1rem; - border: 1px solid var(--outlinegray); - border-radius: 5px; - pointer-events: none; - transition: opacity 0.2s ease, transform 0.2s ease; - user-select: none; - overflow-wrap: anywhere; - box-shadow: 6px 6px 36px 0 rgba(0,0,0,0.25); - - @media all and (max-width: 600px) { - display: none !important; - } - - &.visible { - opacity: 1; - visibility: visible; - display: inline-block; - animation: dropin 0.2s ease; - } - - & > h3 { - font-size: 1rem; - margin: 0.25rem 0; - } - - & .meta { - margin-top: 0.25rem; - opacity: 0.5; - font-family: var(--font-mono); - font-size: 0.8rem; - } - - & > p { - margin: 0; - padding: 0.5rem 0; - } - - & > p, & > a { - font-size: 1rem; - font-weight: 400; - user-select: none; - } -} - -#contact_buttons ul { - list-style-type: none; - - li { - display: inline-block; - } - - li a { - padding: 0 1em; - } -} - -mark { - background-color: var(--highlighted); - color: var(--gray); -} diff --git a/docs/assets/styles/clipboard.scss b/docs/assets/styles/clipboard.scss deleted file mode 100644 index 7989e248..00000000 --- a/docs/assets/styles/clipboard.scss +++ /dev/null @@ -1,47 +0,0 @@ -.clipboard-button { - position: absolute; - display: flex; - float: right; - right: 0; - padding: 0.69em; - margin: 0.5em; - color: var(--outlinegray); - border-color: var(--dark); - background-color: var(--lightgray); - filter: contrast(1.1); - border: 2px solid; - border-radius: 6px; - font-size: 0.8em; - z-index: 1; - opacity: 0; - transition: 0.12s; - - & > svg { - fill: var(--light); - filter: contrast(0.3); - } - - &:hover { - cursor: pointer; - border-color: var(--primary); - - & > svg { - fill: var(--primary); - } - } - - &:focus { - outline: 0; - } -} - -.highlight { - position: relative; - - &:hover > .clipboard-button { - opacity: 1; - transition: 0.2s; - } -} - - diff --git a/docs/assets/styles/code-title.scss b/docs/assets/styles/code-title.scss deleted file mode 100644 index b384743b..00000000 --- a/docs/assets/styles/code-title.scss +++ /dev/null @@ -1,20 +0,0 @@ -.code-title { - color: var(--primary) ; - font-family: var(--font-mono); - width: max-content; - overflow-x: auto; - display: inline-block; - vertical-align: middle; - font-weight: normal; - line-height: 1em; - position: relative; - padding: 0.5em 0.6em 0.6em; // + 1.2 em - max-width: calc(100% - 1.2em); // (-1.2 em) fits article width exactly - margin-bottom: -0.2em; - z-index: -1; - border-top-left-radius: 0.3em; - border-top-right-radius: 0.3em; - font-size: 0.9em; - background-color: var(--lightgray); - filter: hue-rotate(-30deg) contrast(1.0) opacity(0.8); -} \ No newline at end of file diff --git a/docs/assets/styles/custom.scss b/docs/assets/styles/custom.scss deleted file mode 100644 index fc0108a5..00000000 --- a/docs/assets/styles/custom.scss +++ /dev/null @@ -1,31 +0,0 @@ -// Add your own CSS here! - -:root { - --light: #faf8f8; - --dark: #141021; - --secondary: #284b63; - --tertiary: #84a59d; - --visited: #afbfc9; - --primary: #f28482; - --gray: #4e4e4e; - --lightgray: #f0f0f0; - --outlinegray: #dadada; - --million-progress-bar-color: var(--secondary); - --highlighted: #f5dfaf88; -} - -[saved-theme="dark"] { - --light: #1e1e21 !important; - --dark: #fbfffe !important; - --secondary: #6b879a !important; - --visited: #4a575e !important; - --tertiary: #84a59d !important; - --primary: #f58382 !important; - --gray: #d4d4d4 !important; - --lightgray: #292633 !important; - --outlinegray: #343434 !important; - --highlighted: #574010; -} - - - diff --git a/docs/assets/styles/darkmode.scss b/docs/assets/styles/darkmode.scss deleted file mode 100644 index 61967d79..00000000 --- a/docs/assets/styles/darkmode.scss +++ /dev/null @@ -1,44 +0,0 @@ -.darkmode { - float: right; - padding: 1em; - min-width: 30px; - position: relative; - - @media all and (max-width: 450px) { - padding: 1em; - } - - & > .toggle { - display: none; - box-sizing: border-box; - } - - & svg { - opacity: 0; - position: absolute; - width: 20px; - height: 20px; - top: calc(50% - 10px); - margin: 0 7px; - fill: var(--gray); - transition: opacity 0.1s ease; - } -} - -.toggle:checked ~ label { - & > #dayIcon { - opacity: 0; - } - & > #nightIcon { - opacity: 1; - } -} - -.toggle:not(:checked) ~ label { - & > #dayIcon { - opacity: 1; - } - & > #nightIcon { - opacity: 0; - } -} \ No newline at end of file diff --git a/docs/assets/styles/syntax.scss b/docs/assets/styles/syntax.scss deleted file mode 100644 index 6267f5cf..00000000 --- a/docs/assets/styles/syntax.scss +++ /dev/null @@ -1,66 +0,0 @@ -// Overrides -/* Background */ -.chroma { - overflow: hidden !important; - background-color: var(--lightgray) !important; -} - -/* LineTable */ -.chroma .lntable { - width: auto !important; - overflow: auto !important; - display: block !important; -} - -/* LineHighlight */ -.chroma .hl { - display: block !important; - width: 100% !important; -} - -/* LineNumbersTable */ -.chroma .lnt { - margin-right: 0.0em !important; - padding: 0 0.0em 0 0.0em !important; -} - -/* LineNumbers */ -.chroma .ln { - margin-right: 0.0em !important; - padding: 0 0.0em 0 0.0em !important; -} - -/* GenericDeleted */ -.chroma .gd { - color: #8b080b !important; -} - -/* GenericInserted */ -.chroma .gi { - font-weight: bold !important; -} - -.lntd:first-of-type > .chroma { - padding-right: 0 !important; -} - -.chroma code { - font-family: var(--font-mono) !important; - font-size: 0.85em !important; - line-height: 2em !important; - background: none !important; - padding: 0 !important; -} - -.chroma { - border-radius: 3px !important; - margin: 0 !important; -} - -pre.chroma { - -moz-tab-size:4;-o-tab-size:4;tab-size:4; -} - -.katex { - font-size: 1.1em !important; -} diff --git a/docs/babel.config.js b/docs/babel.config.js deleted file mode 100644 index ce9c9de0..00000000 --- a/docs/babel.config.js +++ /dev/null @@ -1,17 +0,0 @@ -module.exports = { - presets: [ - [ - '@babel/preset-env', - { - targets: { - browsers: [ - // Best practice: https://github.com/babel/babel/issues/7789 - '>=1%', - 'not ie 11', - 'not op_mini all' - ] - } - } - ] - ] -}; \ No newline at end of file diff --git a/docs/config/_default/config.toml b/docs/config/_default/config.toml deleted file mode 100644 index 77e93d56..00000000 --- a/docs/config/_default/config.toml +++ /dev/null @@ -1,63 +0,0 @@ -baseurl = "https://lunabrain.com/" -canonifyURLs = false -disableAliases = true -disableHugoGeneratorInject = true -enableEmoji = true -enableGitInfo = false -enableRobotsTXT = true -paginate = 7 -rssLimit = 10 - -# Multilingual -defaultContentLanguage = "en" -# defaultContentLanguageInSubdir = true - -# add redirects/headers -[outputs] -home = ["HTML", "RSS"] -section = ["HTML", "RSS", "SITEMAP"] - -# add output format for section sitemap.xml -[outputFormats.SITEMAP] -mediaType = "application/xml" -baseName = "sitemap" -isHTML = false -isPlainText = true -noUgly = true -rel = "sitemap" - -[caches] - [caches.getjson] - dir = ":cacheDir/:project" - maxAge = "10s" - -[sitemap] - changefreq = "weekly" - filename = "sitemap.xml" - priority = 0.5 - -[taxonomies] - contributor = "contributors" - category = "categories" - tag = "tags" - -[permalinks] - blog = "/blog/:title/" -# docs = "/docs/1.0/:sections[1:]/:title/" - -[minify.tdewolff.html] - keepWhitespace = false - -[related] - threshold = 80 - includeNewer = true - toLower = false - [[related.indices]] - name = "categories" - weight = 100 - [[related.indices]] - name = "tags" - weight = 80 - [[related.indices]] - name = "date" - weight = 10 diff --git a/docs/config/_default/languages.toml b/docs/config/_default/languages.toml deleted file mode 100644 index d6eb3154..00000000 --- a/docs/config/_default/languages.toml +++ /dev/null @@ -1,7 +0,0 @@ -[en] - languageName = "English" - contentDir = "content" - weight = 10 - [en.params] - languageISO = "EN" - languageTag = "en-US" diff --git a/docs/config/_default/markup.toml b/docs/config/_default/markup.toml deleted file mode 100644 index 2880e305..00000000 --- a/docs/config/_default/markup.toml +++ /dev/null @@ -1,29 +0,0 @@ -defaultMarkdownHandler = "goldmark" - -[goldmark] - [goldmark.extensions] - linkify = false - [goldmark.parser] - autoHeadingID = true - autoHeadingIDType = "github" - [goldmark.parser.attribute] - block = true - title = true - [goldmark.renderer] - unsafe = true - -[highlight] - codeFences = false - guessSyntax = false - hl_Lines = "" - lineNoStart = 1 - lineNos = false - lineNumbersInTable = true - noClasses = false - style = "dracula" - tabWidth = 4 - -[tableOfContents] - endLevel = 3 - ordered = false - startLevel = 2 diff --git a/docs/config/_default/menus/menus.en.toml b/docs/config/_default/menus/menus.en.toml deleted file mode 100644 index be24bbad..00000000 --- a/docs/config/_default/menus/menus.en.toml +++ /dev/null @@ -1,46 +0,0 @@ -[[docs]] - name = "Setup" - weight = 10 - identifier = "setup" - url = "/docs/setup/" - -[[main]] - name = "Blog" - url = "/blog/" - weight = 20 - -[[main]] - name = "ML Wiki" - url = "/wiki/" - weight = 20 - -[[main]] - name = "Get Started" - weight = 30 - identifier = "get-started" - url = "/docs/setup/introduction/" - -[[main]] - name = "Quick Start" - weight = 40 - identifier = "quick-start" - url = "/docs/setup/quick-start/" - parent = "get-started" - -[[social]] - name = "GitHub" - pre = "" - url = "https://github.com/lunabrain-ai/lunabrain" - post = "v0.1.0" - weight = 10 - -[[social]] - name = "Twitter" - pre = "" - url = "https://twitter.com/lunabrainai" - weight = 20 - -# [[footer]] -# name = "Privacy" -# url = "/privacy-policy/" -# weight = 10 diff --git a/docs/config/_default/module.toml b/docs/config/_default/module.toml deleted file mode 100644 index ea4b46dd..00000000 --- a/docs/config/_default/module.toml +++ /dev/null @@ -1,68 +0,0 @@ -[hugoVersion] - extended = true - min = "0.80.0" - max = "" - -[[mounts]] - source = "node_modules/@hyas/doks/archetypes" - target = "archetypes" - -[[mounts]] - source = "node_modules/@hyas/doks/assets" - target = "assets" - -# [[mounts]] -# source = "node_modules/@hyas/doks/content" -# target = "content" - -[[mounts]] - source = "node_modules/@hyas/doks/data" - target = "data" - -[[mounts]] - source = "node_modules/@hyas/doks/layouts" - target = "layouts" - -[[mounts]] - source = "node_modules/@hyas/doks/static" - target = "static" - -[[mounts]] - source = "node_modules/flexsearch" - target = "assets/js/vendor/flexsearch" - -[[mounts]] - source = "node_modules/katex" - target = "assets/js/vendor/katex" - -[[mounts]] - source = "node_modules/mermaid" - target = "assets/js/vendor/mermaid" - -[[mounts]] - source = "assets" - target = "assets" - -[[mounts]] - source = "static" - target = "static" - -# [[mounts]] -# source = "content" -# target = "content" - -[[mounts]] - source = "layouts" - target = "layouts" - -[[mounts]] - source = "archetypes" - target = "archetypes" - -[[mounts]] - source = "data" - target = "data" - -[[mounts]] - source = "node_modules/@hyas/images/layouts" - target = "layouts" diff --git a/docs/config/_default/params.toml b/docs/config/_default/params.toml deleted file mode 100644 index 8acaed79..00000000 --- a/docs/config/_default/params.toml +++ /dev/null @@ -1,114 +0,0 @@ -# Meta Data for SEO - -## Homepage -title = "LunaBrain" -titleSeparator = "-" -titleAddition = "Stay on top of information, always." -description = "" - -## Documentation -# docsVersion = "0.3" - -## Open Graph -images = ["doks.png"] -ogLocale = "en_US" -domainTLD = "lunabrain.com" -titleHome = "LunaBrain" - -## Twitter Cards -twitterSite = "@lunabrainai" -twitterCreator = "@lunabrainai" - -## JSON-LD -# schemaType = "Person" -schemaType = "Organization" -schemaName = "LunaBrain" -schemaAuthor = "LunaBrain" -schemaAuthorTwitter = "https://twitter.com/lunabrainai" -schemaAuthorLinkedIn = "https://www.linkedin.com/in/henkverlinde/" -schemaAuthorGitHub = "https://github.com/h-enk" -schemaLocale = "en-US" -schemaLogo = "logo-doks.png" -schemaLogoWidth = 512 -schemaLogoHeight = 512 -schemaImage = "doks.png" -schemaImageWidth = 1280 -schemaImageHeight = 640 -schemaTwitter = "https://twitter.com/lunabrainai" -schemaLinkedIn = "" -schemaGitHub = "https://github.com/lunabrain-ai/lunabrain" -schemaSection = "blog" - -## Sitelinks Search Box -siteLinksSearchBox = false - -## Chrome Browser -themeColor = "#fff" - -# Images - Temporarily left in place for backward compatibility -quality = 85 -bgColor = "#fff" -landscapePhotoWidths = [900, 800, 700, 600, 500] -portraitPhotoWidths = [800, 700, 600, 500] -lqipWidth = "20x" -smallLimit = "300" - -# Images -imageResponsive = true -imageConvertTo = "webp" -imageImageSizes = ["480","720","1080","1280","1600","2048"] -singleSize = false -imageAddClass = "img-fluid lazyload blur-up" - -### Image template -defaultImage = "default-image.png" # put in `./assets/images/` -fillImage = "1270x740 Center" # normalize image size - -# Footer -footer = "Powered by Hugo and Doks" - -# Feed -copyRight = "Copyright (c) 2023 LunBrain" - -# Alert -alert = true -alertDismissable = true -# alertText = "Introducing the Doks child theme, several DX + UX updates, and more! Check out Doks v0.2" -alertText = "Join our Discord server to get help, share ideas, and stay up to date with the latest news and updates." - -# Edit Page -# repoHost [Github | Gitea | GitLab | Bitbucket | BitbucketServer ] is used for building the edit link based on git hoster -repoHost = "GitHub" -#repoHost = "Gitea" -docsRepo = "https://github.com/h-enk/doks" -docsRepoBranch = "master" -docsRepoSubPath = "" -editPage = false -lastMod = false - -[sections] - sectionNav = ["docs", "guides"] - -[options] - lazySizes = true - clipBoard = true - instantPage = true - flexSearch = true - searchSectionsShow = [] - searchSectionsIndex = [] - darkMode = true - bootStrapJs = true - breadCrumb = false - highLight = true - kaTex = false - multilingualMode = false - docsVersioning = false - fullWidth = false - navbarSticky = true - toTopButton = false - scrollSpy = false # experimental; needs Bootstrap >= 5.2.0-beta1 - -[menu] - [menu.section] - auto = true - collapsibleSidebar = true diff --git a/docs/config/next/config.toml b/docs/config/next/config.toml deleted file mode 100644 index 9c5e90da..00000000 --- a/docs/config/next/config.toml +++ /dev/null @@ -1 +0,0 @@ -canonifyURLs = false diff --git a/docs/config/postcss.config.js b/docs/config/postcss.config.js deleted file mode 100644 index e8c3b39d..00000000 --- a/docs/config/postcss.config.js +++ /dev/null @@ -1,40 +0,0 @@ -const autoprefixer = require('autoprefixer'); -const purgecss = require('@fullhuman/postcss-purgecss'); -const whitelister = require('purgecss-whitelister'); - -module.exports = { - plugins: [ - autoprefixer(), - purgecss({ - content: [ - './node_modules/@hyas/doks/layouts/**/*.html', - './node_modules/@hyas/doks/content/**/*.md', - './layouts/**/*.html', - './content/**/*.md', - ], - safelist: [ - 'lazyloaded', - 'table', - 'thead', - 'tbody', - 'tr', - 'th', - 'td', - 'h5', - 'alert-link', - 'container-xxl', - 'container-fluid', - ...whitelister([ - './node_modules/@hyas/doks/assets/scss/common/_variables.scss', - './node_modules/@hyas/doks/assets/scss/components/_alerts.scss', - './node_modules/@hyas/doks/assets/scss/components/_buttons.scss', - './node_modules/@hyas/doks/assets/scss/components/_code.scss', - './node_modules/@hyas/doks/assets/scss/components/_syntax.scss', - './node_modules/@hyas/doks/assets/scss/components/_search.scss', - './node_modules/@hyas/doks/assets/scss/common/_dark.scss', - './node_modules/katex/dist/katex.css', - ]), - ], - }), - ], -} diff --git a/docs/config/production/config.toml b/docs/config/production/config.toml deleted file mode 100644 index 9c5e90da..00000000 --- a/docs/config/production/config.toml +++ /dev/null @@ -1 +0,0 @@ -canonifyURLs = false diff --git a/docs/content/_index.md b/docs/content/_index.md deleted file mode 100644 index 37d8c89e..00000000 --- a/docs/content/_index.md +++ /dev/null @@ -1,9 +0,0 @@ ---- -title : "LunaBrain" -description: "Lets make AI what it really is: a tool for humans. 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a/docs/content/blog/cerebras-gpt-vs-llama-ai-model-comparison/index.md +++ /dev/null @@ -1,131 +0,0 @@ ---- -title: "Cerebras-GPT vs LLaMA AI Model Comparison" -description: "Comparing the real-world performance of GPT-like AI models with public weights" -slug: cerebras-gpt-vs-llama-ai-model-comparison -date: 2023-03-29T07:00:00.000Z -keywords: [gpt, llama, open-source, cerebras, cerebras-gpt] -tags: [gpt, ai, open-source] -contributors: [free] -images: [cerebras-wse-nvidia-v100-featured-image.jpg] ---- - - - -On March 28th, Cerebras released on [HuggingFace](https://huggingface.co/cerebras/Cerebras-GPT-13B) a new Open -SourcePage model trained on [The Pile](https://pile.eleuther.ai/) dataset called "Cerebras-GPT" with GPT-3-like -performance. ( -[Link to press release](https://www.cerebras.net/blog/cerebras-gpt-a-family-of-open-compute-efficient-large-language-models/)) - -## What makes Cerebras interesting? - -While Cerebras isn't as capable of a model for performing tasks when compared directly to models like [LLaMA](https://en.wikipedia.org/wiki/LLaMA), -ChatGPT, or GPT-4, it has one important quality that sets it apart: It's been released under the Apache 2.0 licence, -a fully -permissive Open SourcePage license, and the weights are available for anybody to download and try out. - -This is different from other models like LLaMA that, while their weights are freely available, their [license](https://huggingface.co/decapoda-research/llama-7b-hf/blob/main/LICENSE) -restricts LLaMAs usage to only "Non-Commercial" use cases like academic research or personal tinkering. - -That means if you'd like to check out LLaMA you'll have to get access to a powerful GPU to run it or use a -volunteer-run service like [KoboldAI](https://lite.koboldai.net/#). You can't just go to a website like you can with -ChatGPT and expect to start feeding it prompts. (At least without running the risk of Meta sending you a [DMCA takedown -request](https://news.ycombinator.com/item?id=35287733).) - -## Proof-of-Concept to demonstrate Cerebras Training Hardware - -The real reason that this model is being released is showcase the crazy silicon that Cerebras has been spending years -building. - -![Cerebras vs NVIDIA silicon die show](cerebras-wse-nvidia-v100-featured-image.jpg) - -

A comparison of "one" Cerebras chip compared to an NVIDIA V100 - chip. -
-
- - - -These new chips are impressive because they use a silicon architecture that hasn't been deployed in production for AI -training before: Instead of networking together a bunch of computers that each have a handful of NVIDIA GPUs, Cerebras -has instead "networked" together the chips at the die-level. - -By releasing Cerebras-GPT and showing that the results are comparable to existing OSS models, Cerebras is able to -"prove" that their product is competitive with what NVIDIA and AMD have on the market today. (And healthy -competition benefits all of us!) - -## Cerebras vs LLaMA vs ChatGPT vs GPT-J vs NeoX - -To put it in simple terms: Cerebras isn't as advanced as either LLaMA or ChatGPT (`gpt-3.5-turbo`). It's a -much smaller model at 13B parameters and it's been intentionally "undertrained" relative to the other models. -Cerebras is ~6% of the size of GPT-3 and ~25% of the size of LLaMA's full-size, 60B parameter model, and they -intentionally limited how long the model was trained in order to reach a "training compute optimal" state. - -That doesn't mean that it's useless though. As you'll see from the data released in the Cerebras paper, this model -is still a welcome addition to the available Open SourcePage models like [GPT-2 (1.5B)](https://huggingface.co/gpt2), -[GPT-J (6B)](https://huggingface.co/EleutherAI/gpt-j-6B), and -[GPT NeoX (20B)](https://huggingface.co/EleutherAI/gpt-neox-20b). -It's also possible that the model can improve with additional tweaking by the community (like fine-tuning or -creating LORAs for it.) - -It's also just valuable for anybody building around AI that can't depend on -[OpenAI's monopoly](/openai-not-so-open/) for what they're building (enterprises with -strict security requirements, foreign governments, or just people that want to have control over their infrastructure). - -## Benchmark Comparison - -| Model | Params | Hella-Swag | PIQA | Wino-Grande | Lambada | ARC-e | ARC-c | OpenBookQA | BoolQ | SIQA | -|--------------|--------|------------|-------|-------------|---------|-------|-------|------------|-------|------| -| Cerebras-GPT | 13B | 51.3 | 76.6 | 64.6 | 69.6 | 71.4 | 36.7 | 28.6 | - | - | -| GPT-3 (175B) | 175B | 78.9 | 81.0 | 70.2 | 75.0 | 68.8 | 51.4 | 57.6 | 60.5 | 81.0 | -| GPT-4 (?B) | ? | 95.3 | - | 87.3 | - | - | 96.3 | - | - | - | -| LLaMA (13B) | 13B | 79.2 | 80.1 | 73.0 | - | 74.8 | 52.7 | 56.4 | 78.1 | 50.4 | -| LLaMA (60B) | 60B | 84.2 | 82.8 | 77.0 | - | 78.9 | 56.0 | 60.2 | 76.5 | 52.3 | -| GPT-J (6B) | 6B | 66.1 | 76.5 | 65.3 | 69.7 | - | - | - | - | - | -| GPT-NeoX-20B | 20B | - | 77.9 | ~67.0 | 72.0 | ~72.0 | ~39.0 | ~31.0 | - | - | -
If you'd like to add data for another model, you can edit - this table on - GitHub here. -
-
-It's a bit difficult to compare apples-to-apples between all of these different models, but I did my best to squeeze -the data together in a way that made it easier to understand. - -As you can see from looking at this table: Cerebras-GPT is roughly the same as GPT-J and GPT NeoX, and sometimes even -worse, for tasks like OpenBookQA and ARC-c ("complex"). From looking at what these tests actually involve, it seems -that both of those tasks rely on some amount of "common sense" knowledge to get right (determing the correct answer -requires using knowledge that isn't included in the question anywhere). - -![open your wallet discord message](chat-gpt-bad-math.png) -
But even the mighty ChatGPT often can't do simple math
- -
- -...and then there is GPT-4 crushing everything else in this table! - -## Is Cerebras-GPT worth using? - -Based on the data above it's not really better than any existing OSS models so it's hard to say if it's a -better choice than GPT-J, GPT NeoX, or other AI models for any tasks. Perhaps with some fine-tuning the model may be able to perform -better than either of those, but I'll let somebody more qualified than me answer that question instead! - -## Want to learn more? - -Come [join our Discord](https://discord.gg/2EbHdAR5w7) and share your thoughts with us. 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Dive into the hype of the Vector Database landscape, how they work, and its impact on machine learning." -slug: riding-the-ai-wave-with-vector-databases -date: 2023-04-14T03:04:00.000Z -keywords: [gpt, embeddings, ai, vector-databases] -tags: [gpt, ai, open-source, embeddings, vector-databases] -contributors: [free] -images: [laptop11-hi.png] ---- - - - -## Exploring the World of Vector Databases in 2023 - -In recent times, Vector Databases have been gaining popularity at an alarming rate due to their synergies with AI models -like ChatGPT. Large Language Models (LLMs) like ChatGPT were trained on data that cut off in late 2021 which means they're -stuck in the past. They're operating on a snapshot of the world that's roughly 2 years out of date! - -That's still fine for many use cases, but what if you want to ask a question about something *current* like the weather -or some latest news? You're stuck (or they'll pretend to know and -[hallucinate a fake answer](https://en.wikipedia.org/wiki/Hallucination_(artificial_intelligence)) for you). - -Fortunately there is a workaround: You can BYOD ("Bring Your Own Data") to provide these models -with the specific information needed to answer your questions. - -But now you have a new problem: How do you figure out what data to pass in when your dataset is big? - -That's where Vector Databases come in and what we'll be examining in this post. But before we go into the technical -details later, let's divert our attention to take a look at how recent events happening in the Vector Database space -are fueling their development and rapid growth. - -### Riding the AI Wave - -![Surfboard floating in the AI ocean](wave1-hi-crop.png) - -The Venture Capital (VC) firms of the world have been busy throwing money at several Vector Database companies with -Weaviate, a company built around [an Open SourcePage product](https://github.com/weaviate/weaviate), closing a -[$16 million Series A round](https://www.prnewswire.com/news-releases/semi-technologies-16m-series-a-round-highlights-a-new-wave-of-ai-first-database-tech-301486766.html) -last month. - -That may sound like a lot of dough, but there two other Vector Database startups that raised even bigger rounds with -Chroma, a YC-backed [Open SourcePage product](https://github.com/chroma-core/chroma), raising -$18 million with *just* 1.2k GitHub stars and Pinecone, a proprietary Cloud-Only startup, -[raising a $28 million](https://techcrunch.com/2022/03/29/pinecone-announces-28m-series-a-for-purpose-built-database-aimed-at-data-scientists/) -at an almost-unicorn valuation of $700 million. - -With that much cash being splashed around it's going to be interesting to see how these companies develop. How will they -plan to differentiate themselves as more competition pops up? How long until we see big cloud companies like Amazon and -Google entering this market too? Are these companies simply riding on the coattails of the success of giants like -OpenAI, or is this the beginning of a new era of AI-first database technology? - -I won't be attempting to answer those questions in this post, but they're helpful context to keep in mind as you dive -into the technical details of how Vector Databases work, where they fit into the current database landscape, and how -they're being applied to augment AI models like ChatGPT. - -### What is a Vector Database? - -A Vector Database stores a collection of "Vectors" which, in programming terms, are just -"one-dimensional arrays of numbers". Vectors are ubiquitous and used all the time in Machine Learning contexts, in any -code that touches with 3D graphics, and a number of other places. (You can skip ahead if you've used vectors in any -language before.) - -They're really just arrays of numbers though and the only real difference with a vanilla array is that the term -"vector" implies tree things: -- The data is an array of *floating point numbers* (as opposed to integers, strings, etc.) -- They're usually referred to by their *dimension* (how many numbers are in the array) - - For example, a `vector3` is a 3-element array of floating point numbers. A `vector4` is (you guessed it!) a 4-element - array of floating point numbers. Simple! -- There are special functions to operate on them like `normalize`, `dot`, `cross`, etc. - - These are just helpers though, and you can always just write your own functions to do the same thing. - -The term "vector" itself comes from linear algebra, which is a branch of mathematics that deals primarily with matrices, -tensors, and other array-like structures, but at the end of the day, they're just fancy float arrays! - -That does beg the question though: If they're just float arrays, and since databases can already store arrays, do we -*really* need a whole new database just for them? - ------ - -![Hype Cycle](Gartner_Hype_Cycle.svg) - -*Are VCs creating another bubble like they did with [NoSQL databases](https://stackoverflow.blog/2021/01/14/have-the-tables-turned-on-nosql/)?* - ------ - -### Why are Vector Databases necessary? - -Fortunately, the answer is simple: **Performance**. - -Vector Databases are optimized for storing and performing operations on large amounts of vector data, often processing -hundreds of millions of vectors per query, and doing it significantly faster than traditional databases are able to. - -Here are some of the features that Vector Databases provide: -- Perform complex mathematical operations to filter and locate "nearby" vectors using clustering techniques like - "Cosine Similarity" (which I'll explain later) -- Provide [specialized Vector indexes](https://weaviate.io/developers/weaviate/more-resources/performance) to make retrieval - of data significantly faster and deterministic -- Store vectors in a way that makes them more compact, like by [compressing and quantizing them](https://weaviate.io/blog/ann-algorithms-hnsw-pq), - to keep as much data in memory as possible (further reducing load + query latency) -- Sharding data across multiple machines to handle large amounts of data (which many databases can do, but - SQL databases in particular take more effort to scale out) - -### Relational vs Document vs Vector Databases - ------ - -![Logos of the 3 top databases in each category](3databases.png) - ------ - -#### Relational Databases (SQL) - -Examples include: -PostgreSQL, MySQL, and MariaDB. - -They use rows and columns to store data, similar to an Excel spreadsheet, and they support Vectors with extensions like -[pgvector](https://github.com/pgvector/pgvector). They're not as trivially scalable as a dedicated Vector Database, but -they're much easier to deploy and manage due to their popularity with services like AWS RDS letting you spin up a -production box in a few minutes. - -#### Document Databases (often "NoSQL") - -MongoDB and CouchDB are the quintessential examples here, but technically Redis also sits in this space. - -They tend to store data in JSON-like structures, called "documents", that can are easy to work with, but they aren't -being used in the AI world very much today (most likely because they're not as popular as SQL databases today). The -exception is Redis which does have -[Vector support](https://redis.io/docs/stack/search/reference/vectors/) and is quite popular for in-memory use cases. - -#### Vector Databases - -These databases are very "niche" in the problem they solve. They are not general databases that you can use to build the -back-end of your application. They only provide functionality to quickly locate multiple documents that contain similar -text (this is done via a process known as "clustering" which we'll discuss later). - -That means that most applications will use a combination of a SQL database alongside a Vector database dedicated to -provide document search and feed data into AI Models like OpenAI's ChatGPT and other Large Language Models (LLMs). -(This pattern is similar to other databases like [ElasticSearch](https://github.com/elastic/elasticsearch) that provide -important functionality for specific use cases.) - -This is by no means an exhaustive list, but here are the most popular ones that I've seen people using: - -- [Weaviate](https://github.com/weaviate/weaviate) (Open SourcePage) -- [Milvus](https://github.com/milvus-io/milvus) (Open SourcePage) -- [FAISS](https://www.pinecone.io/learn/faiss/) (Open SourcePage) -- [Pinecone](https://www.pinecone.io/) (Cloud Only) -- [Chroma](https://github.com/chroma-core/chroma) (Open SourcePage) -- [Qdrant](https://qdrant.tech/) (Open SourcePage) - -For an up-to-date list of Vector Databases... Well, there isn't one that I could find yet, so check back and I'll add -an Awesome List here to bookmark. - -### How do Vector Databases work with AI? - -Language is complicated and our brains are *amazing*. In fact, we perform all sorts of complex operations -automatically, without even thinking, and our brains are able to seamlessly understand the meaning behind certain words -and phrases that we hear. - -We're so good at it that, until quite recently, computers have struggled to replicate even a fraction of this ability of -ours. LLMs like GPT-3/ChatGPT are breakthrough models primarily because they excel at *processing input* and -*generating* new, useful output (which feels very magical when it gets it right). - -The problem is that these models have limited context. You can only fit in a few thousands words into them at a time. -If you need to squeeze in more, tough luck! You've either got to fine-tune the model by training it on the data (which -you can't do with ChatGPT, only the older GPT-3 model) or, what is usually the better option, you need to extract -*only the relevant text* for your specific prompt. - -To give an example: If you want to have an answer to the question "What's the best way to grill a steak?" you can't just -feed ChatGPT an entire cookbook all at once. These models can only understand 3000-6000 words at once, so you've got to -be clever about which content you feed it. - -Of course, a naive approach would be to just run a regex for "steak" and include those pages, but you'll miss out on all -the pages that talk about "beef", "red meat", "burgers", and many other similarly related concepts. It's easy as a human -reading through the index to relate these items, but it's very difficult to write a program to exhaustively map every -related concept (without a significant time investment). - -And that's where embeddings come in. They're a clever way to slice up the cookbook into smaller, more manageable chunks -that can be fed into the limited context of a language model like ChatGPT. - -### What is an Embedding? - -A "Text Embeddings", or an "embedding" for short, is just an AI-specific term for "a bunch of vectors", but where those -vectors represent the *semantic meaning* behind how a word is being used *in a specific context*. - -That's a lot to unpack, so let me explain it in pieces. - -(If you're already familiar with embeddings, feel free to skip ahead. And if you'd like a more rigorous definition, check -out this [blog post](https://huggingface.co/blog/getting-started-with-embeddings).) - ------ - -

-{{Visual image showing data clustering}} -
- -*A visual representation of how embeddings are used to cluster data* - ------ - -Going back to our analogy: Beef, steak, and burger all have a similar "Semantic Meaning" to each other in the context of -a recipe. They're technically different words, but they all refer to the same thing: A piece of meat that you can cook -and eat that comes from a cow. - -Computers are dumb though -- almost like they're just rocks we tricked into doing math -- and some really smart people at Google -figured out how to build an AI model that could understand the association between different words by feeding it a large -corpus of text. - -In 2013 those smart Googlers published their model under the name "[Word2Vec](https://en.wikipedia.org/wiki/Word2vec)". It -was a huge breakthrough at the time (so much so that -[Google patented it](https://worldwide.espacenet.com/patent/search/family/053054725/publication/US9037464B1?q=pn%3DUS9037464)) -and it was one of the first big "breakthroughs" that took AI from "cool, but not useful" to "kinda maybe useful". - -But "kinda maybe useful" still wasn't good enough for Google and they kept working on the problem until they published -their next big paper called "[Attention Is All You Need](https://arxiv.org/abs/1706.03762)", which became better known -as laying the foundation for the [Transformer Models](https://en.wikipedia.org/wiki/Transformer_(machine_learning_model)) -that have since taken over the NLP scene. - -### What is a Transformer? - -A Transformer is a type of neural network that's designed to process sequential data, usually text but not always, and -figure out which parts of it are the most important (they're modeled after how human "attention" works). - ------ - -![SourcePage: https://news.tfw2005.com/wp-content/uploads/sites/10/2014/12/3A-Transformers-Bumblebee-010_1417704751.jpg](transformer-crop-full-sm.jpg) - -*NLP Goes Mainstream With Transformers* - ------ - -They're important to be aware of because they're the backbone of many of the most popular NLP models today, including -generative models like GPT-3 and ChatGPT, as well as the modern Embeddings models that replace Word2Vec -(models such as [BERT](https://en.wikipedia.org/wiki/BERT_(language_model)) (2018) and -[T5](https://huggingface.co/docs/transformers/model_doc/t5) (2020)). - -(If you've ever wondered what the "T" in GPT-3 stands for... it's "Transformer". The full name being -"Generative Pre-trained Transformer"!) - -Both GPT and BERT are Transformers models that are good at understanding text, but they serve very different functions. -While GPT is good at understanding and generating text, BERT is good at understanding *the meaning behind the text* and -generating *embeddings* to represent that meaning. -(Technically this is just [one of many application of BERT](https://huggingface.co/blog/bert-101#1-what-is-bert-used-for), -but it's the one we'll focus on for this blog post.) - -They're siblings, in a sense, and, when combined, they make a powerful duo! - -### How to use BERT to generate Embeddings - -To get started, you'll want to setup a Python environment and install the `sentence-transformers` library. Feel free to -follow along here in your own environment, but I'll paste the outputs here for you to view also. (This is -basically just a modified version of the tutorial from -[sentence-transformers](https://www.sbert.net/examples/applications/computing-embeddings/README.html?highlight=embedding).) - -#### Setup Python Environment -```shell -python -m pip install virtualenv -virtualenv venv -source venv/bin/activate -python -m pip install --upgrade pip -``` - -#### Setup `sentence-transformers` -```shell -python -m pip install sentence-transformers -``` - -Then you can start using BERT to generate embeddings for your text! - -#### Running Embeddings Generator Code - -```python -from sentence_transformers import SentenceTransformer -model = SentenceTransformer('all-MiniLM-L6-v2') - -# The sentences that we wish to generate embeddings for -sentences = ['Here’s a cheffy way to cook steak that really makes the most of a good cut!', - 'These burger patties are made with ground beef and an easy bread crumb mixture.', - 'You can use any cut of beef for this sausage recipe, but a rib-eye is the best.'] - -# Generate the embeddings for our sentences -embeddings = model.encode(sentences) - -# Print out the embeddings/vectors -for sentence, embedding in zip(sentences, embeddings): - print("Sentence:", sentence) - print("Embedding:", embedding) - print("") -``` - -Notice that I chose specific sentences without overlapping words, but with similar semantic meanings. (Steak, burgers, and beef) - -The output of this program looks like this (each array contains 768 values): -```shell -$ python 1_print-embeddings.py -Sentence: Here’s a cheffy way to cook steak that really makes the most of a good cut! -Embedding: [-5.09411469e-02 -5.33863381e-02 -3.47178197e-03 -1.47095160e-03, ...] - -Sentence: These burger patties are made with ground beef and an easy bread crumb mixture. -Embedding: [-2.56301872e-02 -9.13281962e-02 2.03740299e-02 -2.06439048e-02, ...] - -Sentence: You can use any cut of beef for this recipe, but a rib-eye is the best. -Embedding: [ 1.14344181e-02 -3.60496975e-02 -2.92477775e-02 -2.06532031e-02, ...] -``` - -As you can see, this data is totally meaningless to a human! It's really only useful when you feed into an algorithm like -"Cosine Similarity" to measure the "distance" between both sentences. In this case, the distance between these -sentences should be very small (closer to 1 than 0). - -But the proof is in the [pudding](https://www.mentalfloss.com/article/635112/proof-is-in-the-pudding-origin), so let's -try it out! - -#### Running Cosine Similarity Code - -Let's tweak our example above to add in a question. - -```python -from sentence_transformers import SentenceTransformer, util -model = SentenceTransformer('all-MiniLM-L6-v2') - -# The sentences that we wish to generate embeddings for -sentences = ['Here’s a cheffy way to cook steak that really makes the most of a good cut!', - 'These burger patties are made with ground beef and an easy bread crumb mixture.', - 'You can use any cut of beef for this sausage recipe, but a rib-eye is the best.'] - -# The question we want to ask -question = 'What is the best cut of beef for sausage?' - -# Generate the embeddings for our sentences (note that we added `convert_to_tensor=True`) -sentence_embeddings = model.encode(sentences, convert_to_tensor=True) -question_embeddings = model.encode(question, convert_to_tensor=True) - -# Compute cosine-similarities -cosine_scores = util.cos_sim(question_embeddings, sentence_embeddings) - -print("Question: " + question) - -# Output the pairs with their score -for i in range(len(sentence_embeddings)): - print("\t Score: {:.4f}\t \"{}\"".format(cosine_scores[0][i], sentences[i])) -``` - -The output should look like: - -```shell -$ python 2_cosine-distance.py -Question: What is the best cut of beef for sausage? - Score: 0.541 "Here’s a cheffy way to cook steak that really makes the most of a good cut!" - Score: 0.365 "These burger patties are made with ground beef and an easy bread crumb mixture." - Score: 0.806 "You can use any cut of beef for this sausage recipe, but a rib-eye is the best." -``` - -As you can see, the sentence that is most similar to the question is the last one, which is exactly what we'd expect! - -### Using a Vector Database instead of a library - -I'm going to stop short of showing you how to use a dedicated Vector Database since the scope of that is a bit larger -than what I'd intended for this post. (This already is much longer than I'd planned for!) - -To help nudge you in the right direction though here is a guide on -[how to use Chroma with Sentence Transformers](https://docs.trychroma.com/usage-guide) which should get you pretty close. - -If you *would* like me to write a follow-up post on how to setup and use a Vector Database for an embeddings search -engine though, please drop me a line on the [LunaBrain Discord](https://discord.gg/2EbHdAR5w7) with some of your thoughts! -(It helps me a lot when writing to have feedback, especially when getting started with a new post.) - -### Conclusion - -Vector Databases come into play when you need to store and query these embeddings quickly. They store data differently -from traditional databases and provide indexes for efficient clustering and searching. They're niche databases today, -but we're likely to see them grow to become household names like how ElasticSearch or Redis have become. - -In the meantime, thank you so much for reading! I hope it was useful and that you learned something new -- I certainly -did while writing it! - -## Want to stay informed about the latest AI news? - -Come [join our Discord](https://discord.gg/2EbHdAR5w7) and share your thoughts with us. We've been building a community -of AI hackers to help keep up with the *insane* pace of development happening right now in the AI world, and we'd -love to have you join us! diff --git a/docs/content/blog/embeddings-database-news-april-2023/laptop11-hi.png b/docs/content/blog/embeddings-database-news-april-2023/laptop11-hi.png deleted file mode 100644 index c1a975e856fe3aea22ac7db827f285fa172bf489..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 3172333 zcmc$_RahKN)IW&32KT`U!QI^<_~7n3gADHOPH>mt7Bn~n4Nh>k0Kwg5dB5+!&+gUU z?!|OfAFJOvb)N1%RW(tn%ChJv#3)cuQ0Ves10167`GelYk z;$-S#>SzhEba92UFol?!nYvms0c)?j zcLPC8Z9ioG@7@R7$wg$OoB%TcJism%A4D5BN7D})*!{n8&22tHYyJ`0kHENp1mL6nUu++O5D)PG`1sLv zbaQ~%IyqSW?>&kJ#L~%C0Kmb`1kf;b{GhuC0HobM8o)<%BxPg)AD|s91pvGsd`n9U z0RSf-H#ZwUFFzmK2gTO=gT>Cq!R5)z!^Z^p3bwFx_`vOIBLLtrw`61IVdvrF|37pA zfIB-gH?xzA8_3dv+0xMz408CG4=GC!*w)n+WDRhIxLAU$As@PIEPNba%8`jaawq10 zlI9~FK4N2T>H41_lN)j|xgM5>EPERm#yMlKbdP+c|{ig%7}D{no~ 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