Onboard basic sentiment analysis with defaults

[ohltyler]

Description

Adds a new sentiment analysis preset, with defaults for ingest/search pipelines and index configurations. Based roughly off of this documented example: https://opensearch.org/docs/latest/search-plugins/search-pipelines/ml-inference-search-request/#example-externally-hosted-model

This use case is intended to be used with a specialized sentiment analysis model (or LLM with tuned prompt) that takes in text and returns a sentiment/category (generally Positive/Neutral/Negative). One basic example is for storing and analyzing website reviews. This particular preset is two-fold:

1. Take in a document with text, process the text with an ML ingest processor to generate and store a label field with the returned sentiment as part of the document
2. Search using plaintext, augment with an ML search request processor to generate and replace the label field's value in the request, such that only results with the matching sentiment are returned.

Overall, this use case could be tuned and enhanced in many different ways. Users may want to persist more than just a label. For example, one reasonable use case is being able to perform a hybrid search over some text's vector, it's sentiment/label, and its plaintext, and try out different weights in a hybrid query, etc.

More details:

• adds quick-configure presets and form inputs for sentiment analysis
• adds logic in quick configure modal to inject quick configure values into the config (the "label" field)
• adds metadata defaults and a new preset JSON resource for this use case
• adds default query inputs for vector search use cases (query.term.${text_field}.value) for the ML models. This may be tuned later on and depends on the default queries or if the query editing experience changes.
• remove noisy toast when editing transforms, since we now run it automatically instead of requiring explicit user input

Demo video, showing a basic usecase with a sagemaker sentiment analysis model. Also shows the default values set in the ML search request processor for a vector search use case. Note that now by using all defaults, no further input is needed on this search request processor now.

screen-capture.14.webm

Check List

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