kolchfa-aws a97c719591
Add multimodal search/sparse search/pre- and post-processing function documentation (#5168)
* Add multimodal search documentation

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Text image embedding processor

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add prerequisite

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Change query text

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Added bedrock connector tutorial and renamed ML TOC

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Name changes and rewording

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Change connector link

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Change link

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Implemented tech review comments

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Link fix and field name fix

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add default text embedding preprocessing and post-processing functions

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add sparse search documentation

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Fix links

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Pre/post processing function tech review comments

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Fix link

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Sparse search tech review comments

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Apply suggestions from code review

Co-authored-by: Melissa Vagi <vagimeli@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>

* Implemented doc review comments

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add actual test sparse pipeline response

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Added tested examples

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Added model choice for sparse search

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Remove Bedrock connector

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Implemented tech review feedback

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add that the model must be deployed to neural search

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Apply suggestions from code review

Co-authored-by: Nathan Bower <nbower@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>

* Link fix

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Add session token to sagemaker blueprint

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Formatted bullet points the same way

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Specified both model types in neural sparse query

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Added more explanation for default pre/post-processing functions

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Remove framework and extensibility references

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

* Minor rewording

Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>

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Signed-off-by: Fanit Kolchina <kolchfa@amazon.com>
Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>
Co-authored-by: Melissa Vagi <vagimeli@amazon.com>
Co-authored-by: Nathan Bower <nbower@amazon.com>
2023-10-16 10:45:35 -04:00

1.3 KiB

layout title has_children nav_order has_toc
default Specialized queries true 65 false

Specialized queries

OpenSearch supports the following specialized queries:

  • distance_feature: Calculates document scores based on the dynamically calculated distance between the origin and a document's date, date_nanos, or geo_point fields. This query can skip non-competitive hits.

  • more_like_this: Finds documents similar to the provided text, document, or collection of documents.

  • neural: Used for vector field search in neural search.

  • neural_sparse: Used for vector field search in sparse neural search.

  • percolate: Finds queries (stored as documents) that match the provided document.

  • rank_feature: Calculates scores based on the values of numeric features. This query can skip non-competitive hits.

  • script: Uses a script as a filter.

  • script_score: Calculates a custom score for matching documents using a script.

  • wrapper: Accepts other queries as JSON or YAML strings.