n8n-docs
Typesense
Our great sponsors
n8n-docs | Typesense | |
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6 | 129 | |
122 | 17,796 | |
3.3% | 3.9% | |
9.9 | 9.8 | |
6 days ago | 6 days ago | |
HTML | C++ | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
n8n-docs
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The 20 Most Trending Open Source Tools for Ecommerce
n8n (27.2k)
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Retrospective: Making a contribution to n8n
n8n documentation
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How to get more GitHub Stars and Followers on Open Source Projects ?
Focus on Documentation We get more traffic to our documentation than our main website. A well-documented project is always loved by the community. Open-source projects like Docusaurus make it super easy to build documentation portals that look great just out of the box. Adding links to the repository from the documentation can drive more visitors to your repository. What to include in documentation How to install/deploy the project If the project has a compiled software as the final product, make sure to add installation instructions. If the project is the codebase for a library such as an npm package or a Ruby gem, include details on how to import and use the library. If the project needs to be or can be deployed on platforms like Kubernetes, Docker, Heroku, and others, include separate guides for each of the options. Contributing guide Apart from the contributing guide doc in the codebase, add one to the documentation, too. It should include guides for setting up a local environment on different platforms like Docker, Mac OS, Ubuntu, Windows, and so on. Tutorials and code examples If this is applicable, it can be really helpful. How to guides on using using the project will show other devs how they can actually get started. It can be code examples if the project is a library. Architecture reference It will be helpful for the contributors if the documentation has details on different components of the project. For example, if the project has server and client components, include a diagram on how everything works together. Here are some projects with great documentation: https://docs.nestjs.com/ https://docs.n8n.io/ https://guides.rubyonrails.org/ https://plotly.com/python/ https://docs.mapbox.com/ https://www.github-stars.com or Github24.
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12 ways to get more GitHub stars for your open-source project
Here are some projects with great documentation: a) https://docs.nestjs.com/ b) https://docs.n8n.io/ c) https://guides.rubyonrails.org/ d) https://plotly.com/python/ e) https://docs.mapbox.com/
- Stock market and crypto tracking with open source tools
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How to automatically manage contributions to open-source projects 🏷️
Contribute to n8n: You can work on open issues, create nodes, improve our docs, or write a blog post.
Typesense
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Website Search Hurts My Feelings
There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).
- Typesense (https://github.com/typesense/typesense)
- Algolia
- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)
- Remote Machine Learning and Searching on a Raspberry Pi 5
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Open Source alternatives to tools you Pay for
Typesense - Open Source Alternative to Algolia
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DNS record "hn.algolia.com" is gone
If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.
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Vector databases: analyzing the trade-offs
I work on Typesense [1] (historically considered an open source alternative to Algolia).
We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.
You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]
You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).
You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.
[1] https://github.com/typesense/typesense
[2] https://typesense.org/docs/0.25.0/api/vector-search.html
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Creating an advanced search engine with PostgreSQL
For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense
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Obsidian Publish full text search
I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.
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DynamoDB search options
A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try tigris | typesense for faster search
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Is it worth using Postgres' builtin full-text search or should I go straight to Elastic?
I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/
What are some alternatives?
Docker Compose - Define and run multi-container applications with Docker
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
good-first-issue - Make your first open-source contribution.
Apache Solr - Apache Lucene and Solr open-source search software
Strapi - 🚀 Strapi is the leading open-source headless CMS. It’s 100% JavaScript/TypeScript, fully customizable and developer-first.
meilisearch-laravel-scout - MeiliSearch integration for Laravel Scout
Nest - A progressive Node.js framework for building efficient, scalable, and enterprise-grade server-side applications with TypeScript/JavaScript 🚀
loki - Like Prometheus, but for logs.
n8n - Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.