Hoarder (Now, Karakeep) - Mymind alternative - The Ultimate All-In-One Bookmark and Note Taking App
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https://github.com/karakeep-app/karakeep/releases/tag/v0.33.1
Brings semantic search(!) and offline-reading(!) in the mobile apps.
Semantic search requires embeddings:Enabling Embeddings
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Karakeep's embedding uses your existing meilisearch installation as the default vector store.
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If you're an OG, and running an old meilisearch version, you'll need to ensure you're on meilisearch version (1.13 or higher). Check this guide for info on how to update.
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If you're using the default OpenAI based configuration, auto embeddings of new bookmarks will be enabled automatically and will use the text-embedding-3-small model.
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If you're using a custom provider, you'll need to pass in the EMBEDDING_TEXT_MODEL=<your_mode>, the size of the dimension of the model via EMBEDDING_DIMENSIONS and then pass EMBEDDING_ENABLE_AUTO_INDEXING=true to enable embeddings. Check out our docs for example models and configurations.
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Once you've enabled embeddings, you'll need to regenerate embeddings for all existing bookmarks. Head to the admin panel's Background Jobs page (new "Embeddings" card) and regenerate embeddings for all/pending bookmarks. This might take a while depending on how many bookmarks you have, and will cost you money (though embeddings are usually pretty cheap).
NOTE: Changing the model or its dimension after embedding even a single bookmark will require you to regenerate embeddings for all bookmarks.
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https://github.com/karakeep-app/karakeep/releases/tag/v0.33.1
Brings semantic search(!) and offline-reading(!) in the mobile apps.
Semantic search requires embeddings:Enabling Embeddings
-
Karakeep's embedding uses your existing meilisearch installation as the default vector store.
-
If you're an OG, and running an old meilisearch version, you'll need to ensure you're on meilisearch version (1.13 or higher). Check this guide for info on how to update.
-
If you're using the default OpenAI based configuration, auto embeddings of new bookmarks will be enabled automatically and will use the text-embedding-3-small model.
-
If you're using a custom provider, you'll need to pass in the EMBEDDING_TEXT_MODEL=<your_mode>, the size of the dimension of the model via EMBEDDING_DIMENSIONS and then pass EMBEDDING_ENABLE_AUTO_INDEXING=true to enable embeddings. Check out our docs for example models and configurations.
-
Once you've enabled embeddings, you'll need to regenerate embeddings for all existing bookmarks. Head to the admin panel's Background Jobs page (new "Embeddings" card) and regenerate embeddings for all/pending bookmarks. This might take a while depending on how many bookmarks you have, and will cost you money (though embeddings are usually pretty cheap).
NOTE: Changing the model or its dimension after embedding even a single bookmark will require you to regenerate embeddings for all bookmarks.
If you're an OG, and running an old meilisearch version, you'll need to ensure you're on meilisearch version (1.13 or higher). Check this guide for info on how to update.
The Meilisearch Cloudron Community Package is Meilisearch v1.51.0, if anybody is interested.
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https://github.com/karakeep-app/karakeep/releases/tag/v0.33.1
Brings semantic search(!) and offline-reading(!) in the mobile apps.
Semantic search requires embeddings:Enabling Embeddings
-
Karakeep's embedding uses your existing meilisearch installation as the default vector store.
-
If you're an OG, and running an old meilisearch version, you'll need to ensure you're on meilisearch version (1.13 or higher). Check this guide for info on how to update.
-
If you're using the default OpenAI based configuration, auto embeddings of new bookmarks will be enabled automatically and will use the text-embedding-3-small model.
-
If you're using a custom provider, you'll need to pass in the EMBEDDING_TEXT_MODEL=<your_mode>, the size of the dimension of the model via EMBEDDING_DIMENSIONS and then pass EMBEDDING_ENABLE_AUTO_INDEXING=true to enable embeddings. Check out our docs for example models and configurations.
-
Once you've enabled embeddings, you'll need to regenerate embeddings for all existing bookmarks. Head to the admin panel's Background Jobs page (new "Embeddings" card) and regenerate embeddings for all/pending bookmarks. This might take a while depending on how many bookmarks you have, and will cost you money (though embeddings are usually pretty cheap).
NOTE: Changing the model or its dimension after embedding even a single bookmark will require you to regenerate embeddings for all bookmarks.
necrevistonnezr said:
https://github.com/karakeep-app/karakeep/releases/tag/v0.33.1
Wow, already updated, thanks @andreasdueren !
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necrevistonnezr said:
https://github.com/karakeep-app/karakeep/releases/tag/v0.33.1
Wow, already updated, thanks @andreasdueren !
@necrevistonnezr the magic of CI/CD.
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Newest Release (https://github.com/karakeep-app/karakeep/releases/tag/v0.33.2) has some caveats:
We're migrating to a custom karakeep chrome container (based on https://github.com/chromedp/docker-headless-shell) now that the old alpine-chrome is no longer fetch-able (and has been long abandoned by the maintainer). Check the migration guide here. The old image will continue to work, but it's recommended that you migrate to the new one as it also upgrades chrome to 151 (compared to 124 in the old image). If you've been using browserless (e.g. on unraid), you're not impacted by this, and you don't need to migrate.
BTW, I'm super happy with Karakeep. Though Linkding might have a more elegant interface, the fulltext and/or semantic search in Karakeep is so much better; AI-tagging works well.
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Newest Release (https://github.com/karakeep-app/karakeep/releases/tag/v0.33.2) has some caveats:
We're migrating to a custom karakeep chrome container (based on https://github.com/chromedp/docker-headless-shell) now that the old alpine-chrome is no longer fetch-able (and has been long abandoned by the maintainer). Check the migration guide here. The old image will continue to work, but it's recommended that you migrate to the new one as it also upgrades chrome to 151 (compared to 124 in the old image). If you've been using browserless (e.g. on unraid), you're not impacted by this, and you don't need to migrate.
BTW, I'm super happy with Karakeep. Though Linkding might have a more elegant interface, the fulltext and/or semantic search in Karakeep is so much better; AI-tagging works well.
@necrevistonnezr The guide did not directly apply to our package because we never used the abandoned alpine-chrome:124 image. We installed Debianβs Chromium inside the single Cloudron container, so nothing was broken or unavailable.
However, our browser was independently maintained by Debian rather than the exact Chrome build Karakeep tests. Iβve now migrated the package to:
Package
0.1.11:- Karakeep
0.33.2 - Official Karakeep Chrome
151.0.7922.47 - Chrome image pinned by immutable tag and digest
- Fresh Cloudron installation healthy
- Meilisearch, web, workers, and Chrome all running
- Real crawl of example.com produced:
- Screenshot: JPEG, 18,511 bytes
- PDF: 13,850 bytes
- Karakeep
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Great, thank you!
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Karakeep 0.3.4 is out: https://github.com/karakeep-app/karakeep/releases/tag/v0.34.0
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Karakeep 0.3.4 is out: https://github.com/karakeep-app/karakeep/releases/tag/v0.34.0
@necrevistonnezr Please give my pipeline a few hours to recognize new releases and build them for Cloudron
It's out now -
@necrevistonnezr Please give my pipeline a few hours to recognize new releases and build them for Cloudron
It's out now@necrevistonnezr Please give my pipeline a few hours to recognize new releases and build them for Cloudron
It's out nowThanks so much!
Error - Unable to pull image registry.docker.due.ren/andreasdueren/karakeep-cloudron:0.1.12. Please check the network or if the image needs authentication. statusCode: 401Did something change?
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