Release 2.8.0

2.8.0

New features

• Improve add_documents memory efficiency and throughput for CLIP and Open_CLIP models when indexing documents with images when no patch method is used (#849). The image downloading and preprocessing logic has been improved. Marqo now converts the images to tensors directly after downloading. In our tests, the memory usage has been reduced by 37.5% and the throughput has been increased by 7.5% (subject to your settings). Marqo is also more stable when indexing documents in a multi-threading scenario.
• Add support for pre-warming patch models (#847). See usage (here)

Bug fixes and minor changes

• Replace the requests package with pycurl for faster image downloads (#849). Marqo now downloads images 2-3x faster in our tests and the overall add_documents throughput is increased by 7.5%

Contributor shout-outs

• Shoutouts to our valuable 4.2k stargazers!
• Thanks a lot for the discussion and suggestions in our community. We love to hear your thoughts and requests. Join our Slack channel and forum now.

Release 2.7.2

2.7.2

Bug fixes and minor changes

• Fix an issue causing an error during the Marqo shutdown process (#850). Marqo now shuts down properly without encountering errors.

Release 2.7.1

2.7.1

Bug fixes and minor changes

• Resolve an issue where Marqo could not create or delete an index when not connected to the Zookeeper server (#848). Users can now create or delete an index without needing to connect to the Zookeeper server. However, please note that without the Zookeeper server, your request is not protected in concurrent scenarios. For guidance on configuring your Zookeeper server, refer to this documentation.

Release 2.7.0

2.7.0

New features

• Update Open CLIP version and support new families of models, e.g., MetaCLIP, DatacompCLIP (#833). Update the Open CLIP version to 2.24.0 which includes new and state-of-the-art multimodal models. You can choose these models to build your index. Check here for the available models.
• Support lexical search with only a filter (#840). Marqo now supports a match-all query ("*") with a filter in lexical search. This allows you to search your documents solely based on the filter content without considering the relevance. This is a community-requested feature (#770, #771) and we love to hear from our users.

Bug fixes and minor changes

• Improve the thread safety of index creation and deletion operations (#838). Marqo now returns an operation_conflict_error(409) if users try to delete or create an index when there is another index creation or deletion in progress.
• Fix a bug that an empty string lexical search query ("") returns a 500 error (#840). Marqo now returns an empty search result for such a query.
• Address verbose logging at the WARNING level when attributes_to_retrieve excludes fields required to build highlights. (#837)

Contributor shout-outs

• Shoutouts to our valuable 4.2k stargazers!
• Thanks @jesse-lord and @afroozsheikh for requesting valuable features to improve Marqo!
• Thanks a lot for the discussion and suggestions in our community. We love to hear your thoughts and requests. Join our Slack channel and forum now.

Release 2.6.0

2.6.0

New features

• Support for custom and default prefixes (#821 and #832) in the index creation, adding documents, search, and embed endpoints.

Bug fixes and minor changes

• Improved recommender with structured indexes (#830)
• Better handling of image download errors (#829). Image download errors will now return a 200 overall and log errors per document.

Release 2.5.1

2.5.1

Bug fixes and minor changes

• More stable recommend endpoint (#825).
• Change error code when using IN filter operator on an unstructured index (#823).
• New index settings validation endpoint for Cloud use (#809).

Release 2.5.0

2.5.0

New features

• New ‘embed’ endpoint (POST /indexes/{index_name}/embed) (#803). Marqo can now perform inference and return the embeddings for a single piece or list of content, where content can be either a string or weighted dictionary of strings. See usage here.
• New ‘recommend’ endpoint (POST /indexes/{index_name}/recommend) (#816). Given a list of existing document IDs, Marqo can now recommend similar documents by performing a search on interpolated vectors from the documents. See usage here.
• Add Inference Cache to speed up frequent search and embed requests (#802). Marqo now caches embeddings generated during inference. The cache size and type can be configured with MARQO_INFERENCE_CACHE_SIZE and MARQO_INFERENCE_CACHE_TYPE. See configuration instructions here.
• Add configurable search timeout (#813). Backend timeout now defaults to 1s, but can be configured with the environment variable VESPA_SEARCH_TIMEOUT_MS. See configuration instructions here.
• More informative get_cuda_info response (#811). New keys: utilization memory_used_percent have been added for easier tracking of cuda device status. See here for more information.

Bug fixes and minor changes

• Upgraded open_clip_torch, timm, and safetensors for access to new models (#810)

Contributor shout-outs

• Shoutout to all our 4.1k stargazers! Thanks for continuing to use our product and helping Marqo grow.
• Keep on sharing your questions and feedback on our forum and Slack channel! If you have any more inquiries or thoughts, please don’t hesitate to reach out.

Release 2.4.3

2.4.3

Bug fixes and minor changes

• Fix incorrect Marqo version number (#805). Version number updated from 2.4.1 to 2.4.3

2.4.2

Bug fixes and minor changes

• Better response for truncated images in add_documents (#797). Truncated images no longer cause a 500 error. The individual document will fail and return a 400 error in add docs response (full response will be a 200).

2.4.1

Bug fixes and minor changes

• Improve telemetry memory management (#800).

Release 2.2.2

2.2.2

Bug fixes and minor changes

• Improve telemetry memory management (#804).

Release 2.4.0

2.4.0

New features

• Add IN operator to the query filter string DSL (#790, #793, & #795).
  For structured indexes, you can now use the IN keyword to restrict text and integer fields to be within a list of values. See usage here.

• Add no_model option for index creation (#789). This allows for indexes that do no vectorisation,
  providing easy use of custom vectors with no risk of accidentally mixing them up with Marqo-generated vectors. See usage here.

• Optional q parameter for the search endpoint if context vectors are provided. (#789).
  This is particularly useful when using context vectors to search across your documents that have custom vector fields. See usage here.

Bug fixes and minor changes

• Improve error message for defining tensorFields when adding documents to a structured index (#788).

Contributor shout-outs

• A huge thank you to all our 4.1k stargazers! We appreciate all of you continuing to use our product and helping Marqo grow.
• Thanks for sharing your questions and feedback on our forum and
  Slack channel!
  If you have any more inquiries or thoughts, please don’t hesitate to reach out.