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4920: Change OpenAI default model r=dureuill a=dureuill # Pull Request ## Related issue Fixes #4856 See also [public usage](https://meilisearch.notion.site/v1-11-AI-search-changes-0e37727193884a70999f254fa953ce6e#b4685a48c4784262a149ec307ec58671) ## What does this PR do? - make the `text-embedding-3-small` the default model for OpenAI instead of `text-embedding-ada-002`. Existing embedders are not impacted Co-authored-by: Louis Dureuil <louis@meilisearch.com> |
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Website | Roadmap | Meilisearch Cloud | Blog | Documentation | FAQ | Discord
⚡ A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow 🔍
Meilisearch helps you shape a delightful search experience in a snap, offering features that work out of the box to speed up your workflow.
🖥 Examples
- Movies — An application to help you find streaming platforms to watch movies using hybrid search.
- Ecommerce — Ecommerce website using disjunctive facets, range and rating filtering, and pagination.
- Songs — Search through 47 million of songs.
- SaaS — Search for contacts, deals, and companies in this multi-tenant CRM application.
See the list of all our example apps in our demos repository.
✨ Features
- Hybrid search: Combine the best of both semantic & full-text search to get the most relevant results
- Search-as-you-type: Find & display results in less than 50 milliseconds to provide an intuitive experience
- Typo tolerance: get relevant matches even when queries contain typos and misspellings
- Filtering and faceted search: enhance your users' search experience with custom filters and build a faceted search interface in a few lines of code
- Sorting: sort results based on price, date, or pretty much anything else your users need
- Synonym support: configure synonyms to include more relevant content in your search results
- Geosearch: filter and sort documents based on geographic data
- Extensive language support: search datasets in any language, with optimized support for Chinese, Japanese, Hebrew, and languages using the Latin alphabet
- Security management: control which users can access what data with API keys that allow fine-grained permissions handling
- Multi-Tenancy: personalize search results for any number of application tenants
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- RESTful API: integrate Meilisearch in your technical stack with our plugins and SDKs
- Easy to install, deploy, and maintain
📖 Documentation
You can consult Meilisearch's documentation at meilisearch.com/docs.
🚀 Getting started
For basic instructions on how to set up Meilisearch, add documents to an index, and search for documents, take a look at our documentation guide.
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🧰 SDKs & integration tools
Install one of our SDKs in your project for seamless integration between Meilisearch and your favorite language or framework!
Take a look at the complete Meilisearch integration list.
⚙️ Advanced usage
Experienced users will want to keep our API Reference close at hand.
We also offer a wide range of dedicated guides to all Meilisearch features, such as filtering, sorting, geosearch, API keys, and tenant tokens.
Finally, for more in-depth information, refer to our articles explaining fundamental Meilisearch concepts such as documents and indexes.
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Meilisearch collects anonymized user data to help us improve our product. You can deactivate this whenever you want.
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If you want to know more about the kind of data we collect and what we use it for, check the telemetry section of our documentation.
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Meilisearch is, and will always be, open-source! If you want to contribute to the project, please look at our contribution guidelines.
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The binaries are versioned following SemVer conventions. To know more, read our versioning policy.
Differently from the binaries, crates in this repository are not currently available on crates.io and do not follow SemVer conventions.