# Typesense API Reference for v0.25.2
This section of the documentation details all the API Endpoints available in Typesense and all the parameters you can use with them.
Use the links on the side navigation bar to get to the appropriate section you're looking for.
To learn how to install and run Typesense, see the Guide section instead.
# What's new
This release fixes some important bugs identified in
The changelog below contains aggregates all the changes between
# New Features
- Semantic Search: Search for conceptually related terms in your dataset, even if the exact keyword does not exist in your dataset.
- Hybrid search: Combine both keyword and semantic / vector search results in a single query using rank fusion
- Automatic embedding generation: specify one or more string fields that should be used for generating embeddings during indexing & during search using state-of-the-art embedding models, optionally using a GPU (opens new window).
- Integration with OpenAI API, PaLM API and Vertex AI API: Have Typesense automatically make API calls to remote embedding services like OpenAI / Google, to generate vectors for the JSON data you index in Typesense.
- Query Analytics: Typesense now supports aggregation of popular search queries which can then be used as insights into query patterns. Docs (opens new window)
- Query Suggestions: You can use historical search terms collected by the Query Analytics feature, to power Query Suggestions.
- Update Documents by Query: You can now update all documents that match a
- Range faceting: numerical values can be dynamically faceted at query-time by bucketing them into ranges.
- Pagination using
limit: This is in addition to the existing
per_pagemechanism. This new pagination method offers more flexibility and is also useful for GraphQL compatibility.
- Resolve field names using wildcard: fields can now be resolved in
highlight_full_fieldswhen a wildcard expression is used, e.g.
- Ability to sort grouped hits based on the size of each group, using
- A count is returned for total number of records under each group even if the hits are truncating via
!=filtering operation can now be performed against numerical fields. Previously only string fields were supported for this operator.
- Support use of
presetparameter in embedded API key.
- Support nested dynamic fields.
- Migrated build system to Bazel.
- New server configuration option (
--reset-peers-on-error) that makes the cluster forcefully refresh its peers when an unrecoverable clustering error happens due to sudden change of peer IPs. There's also an equivalent
/operations/reset_peersAPI. Be careful while using this option, as it can lead to transient loss of data.
- [New in v0.25.2] New search parameter flag
prioritize_num_matching_fieldsthat allows you to configure whether the text match score should consider number of matching fields as a ranking criteria. This defaults to
- [New in v0.25.2] Unload embedding model and free memory when no collections use a given model.
- [New in v0.25.2] Allow the hybrid search / keyword search weight (
alpha) to be configurable in
- [New in v0.25.2] Allow the direction of drop tokens to be configurable via
- [New in v0.25.2] Handle zero width non-joiner character for Persian.
- [New in v0.25.2] Ability to apply vector search only on the results of keyword search.
- [New in v0.25.2] Prevent Typesense from loading an embedding model that exceeds available memory.
- [New in v0.25.2] Improvements to range faceting: float value support, min/max ranges by leaving range param blank, support spaces in range label.
- [New in v0.25.2] Support
- [New in v0.25.2] Better isolation of operations across collections.
- [New in v0.25.2] Parameterize compaction of store during collection drop via the
- [New in v0.25.2] Server argument for configuring the periodic DB compaction interval
- [New in v0.25.2] When using
group_by, you can now control if documents with a
nullvalue in the grouped field should be placed in one group together, or should not be grouped using the
# Bug Fixes
- Fixed updates of nested object field values.
- Fix geopoint indexing in nested fields.
- Fixed some special characters not getting highlighted properly in prefix searches.
- Fixed a bug in phrase matches on array.
- Fixed a socket leak on followers of a cluster when import data fails validation.
- Fixed high memory usage incurred in export/import of large datasets.
- Fixed bad unicode characters in export.
- Fixed errors that were caused by presence of bad Japanese unicode characters in import.
- Fixed broken http/2 support on CURL v8.
- Fixed non-curated members of a group appearing in curated override results.
- Fixed override query rule being case-sensitive.
- Fixed phrase search not considering field weights.
- [New in v0.25.1] Handle mismatched vector dimensions during indexing
- [New in v0.25.1] Allow remote embedders to use multiple per-collection credentials
- [New in v0.25.1] Fixed altering of schema involving embedding fields
- [New in v0.25.1] Fixed charset in content-type header of export API response
- [New in v0.25.1] Fixed an issue in analytics query aggregation that caused crash on empty collections
- [New in v0.25.1] Fixed group by on vector search
- [New in v0.25.1] Improved error handling of remote embedding APIs
- [New in v0.25.1] Fixed tokenizer of embedding models that use XLM-RoBERTa
- [New in v0.25.1] Fixed upsert of unchanged docs containing embedding fields, that would cause the embedding field value to be removed.
- [New in v0.25.1] Fixed text match score calculation to consider the presence of dropped tokens when ranking.
- [New in v0.25.2] Improve precision of HNSW index under frequent deletion and updates of vectors.
- [New in v0.25.2] Fixed a regression in analytics aggregation for aggregation intervals configured to > 60 seconds.
- [New in v0.25.2] Fixed a bug that prevented two embedding field names from sharing the same prefix.
- [New in v0.25.2] Fixed reindexing of old documents with embeddings on collection schema update.
- [New in v0.25.2] Fixed group by search that used facet range query.
- [New in v0.25.2] Fixed edge cases in indexing and querying of optional nested fields.
- [New in v0.25.2] Fixed hanging when PaLM API is down.
- [New in v0.25.2] Fixed an edge case in deletion of values from infix search index.
- [New in v0.25.2] Fixed hybrid search not considering
- [New in v0.25.2] Tweaked text embedding mean-pooling code to match the vectors generated by Python libraries.
- [New in v0.25.2] Fixed truncation of certain float values in facet response.
# Deprecations / behavior changes
There are no depreciation or behavior changes in this version.
Before upgrading your existing Typesense cluster to v0.25.2, please review the behavior changes above to prepare your application for the upgrade.
We'd recommend testing on your development / staging environments before upgrading.
# Typesense Cloud
If you're on Typesense Cloud:
- Go to https://cloud.typesense.org/clusters (opens new window).
- Click on your cluster
- Click on "Cluster Configuration" on the left-side pane, and then click on "Modify"
- Schedule a time for the upgrade.
# Self Hosted
If you're self-hosting Typesense, here's how to upgrade:
# Single node deployment
- Trigger a snapshot to create a backup of your data.
- Stop Typesense server.
- Replace the binary via the tar package or via the DEB/RPM installer.
- Start Typesense server back again.
# Multi-node deployment
To upgrade a multi-node cluster, we will be proceeding node by node to ensure the cluster remains healthy during the rolling upgrade.
NOTE: During the upgrade, we have to ensure that the leader of the cluster is using the older Typesense version.
So we will upgrade the leader last. You can determine whether a node is a leader or follower by the value of the
field in the
/debug end-point response.
- Trigger a snapshot to create a backup of your data on the leader node.
- On any follower, stop Typesense and replace the binary via the tar package or via the DEB/RPM installer.
- Start Typesense server back again and wait for node to rejoin the cluster as a follower and catch-up (
/healthshould return healthy).
- Repeat steps 2 and 3 for the other followers, leaving the leader node uninterrupted for now.
- Once all followers have been upgraded to v0.25.2, stop Typesense on the leader.
- The other nodes will elect a new leader and keep working.
- Replace the binary on the old leader and start the Typesense server back again.
- This node will re-join the cluster as a follower, and we are done.
Once you upgrade to
v0.25 of Typesense Server the internal structure of the data directory becomes incompatible with older versions of Typesense.
However, if you need to downgrade to
v0.24, we've released a special version
v0.24.2 that backports these data structure changes back to
0.24 while keeping other
0.24.1 features as is.
v0.25 can only be downgraded to
This documentation itself is open source. If you find any issues, click on the Edit page button at the bottom of the page and send us a Pull Request.