Add ML Predict, Train APIs

[nathaliellenaa]

Description

Added missing ML Predict and Train APIs.

Issues Resolved

Part of opensearch-project/opensearch-py#867.

ML Predict, Train APIs to add

• POST /_plugins/_ml/_predict/{algorithm_name}/{model_id}
• POST /_plugins/_ml/_train/{algorithm_name}
• POST /_plugins/_ml/_train_predict/{algorithm_name}

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[github-actions]

Changes Analysis

Commit SHA: bb1b52b
Comparing To SHA: edf9d6f

API Changes

Summary

├─┬Paths
│ ├──[➕] path (4632:3)
│ ├──[➕] path (4650:3)
│ └──[➕] path (4667:3)
└─┬Components
  ├──[➕] requestBodies (27282:7)
  ├──[➕] requestBodies (27297:7)
  ├──[➕] requestBodies (27157:7)
  ├──[➕] responses (30386:7)
  ├──[➕] responses (30392:7)
  ├──[➕] responses (30345:7)
  ├──[➕] parameters (22937:7)
  ├──[➕] parameters (22919:7)
  ├──[➕] parameters (22925:7)
  ├──[➕] parameters (22931:7)
  ├──[➕] schemas (54307:7)
  ├──[➕] schemas (53802:7)
  ├──[➕] schemas (54338:7)
  ├──[➕] schemas (54030:7)
  ├──[➕] schemas (53863:7)
  ├──[➕] schemas (54316:7)
  ├──[➕] schemas (53888:7)
  ├──[➕] schemas (53895:7)
  ├──[➕] schemas (54068:7)
  ├──[➕] schemas (53840:7)
  ├──[➕] schemas (54058:7)
  ├──[➕] schemas (53991:7)
  ├──[➕] schemas (53909:7)
  ├──[➕] schemas (54041:7)
  ├──[➕] schemas (53811:7)
  ├──[➕] schemas (54289:7)
  ├──[➕] schemas (54227:7)
  ├──[➕] schemas (54052:7)
  └─┬ml._common___Task
    └─┬state
      ├──[➕] enum (54247:15)
      └──[➕] enum (54251:15)

Document Element	Total Changes	Breaking Changes
paths	3	0
components	30	0

• Total Changes: 33
• Additions: 33

Report

The full API changes report is available at: https://github.com/opensearch-project/opensearch-api-specification/actions/runs/12550254156/artifacts/2372208653

API Coverage

	Before	After	Δ
Covered (%)	606 (59.35 %)	609 (59.65 %)	3 (0.3 %)
Uncovered (%)	415 (40.65 %)	412 (40.35 %)	-3 (-0.3 %)
Unknown	43	43	0

[Tokesh]

Awesome! Brilliant job!
I might have made a mistake somewhere since I haven’t worked much with these APIs, but this is an outsider’s perspective.

[nathaliellenaa]

Awesome! Brilliant job! I might have made a mistake somewhere since I haven’t worked much with these APIs, but this is an outsider’s perspective.

Thank you for your feedback @Tokesh ! They are really helpful, appreciate it :)

[Tokesh]

Looks good, fix vale complaints pls? See the diff.

[dblock]

This is good. Sorry to be annoying, can we please use examples from the movies/books themes? Make up something in that vein (e.g. best sellers in certain years). We plan to use these examples in docs and would like to keep things consistent.

[dblock]

@Tokesh You good with this? Re-review/merge pls?

[Tokesh]

LGTM, Thank you very much! :)
Happy upcoming New Year!