Tools and processors reference
This page is the single entry point for everything Lucenia can do to your data: the tools an agent can call, the ingest processors that run while documents are written, and the search processors that run while queries are served.
The word tool means two different things in these docs. The Ingestion tools and utilities section covers third-party data shippers (Beats, Logstash, Fluentd, OpenTelemetry), the Lucenia CLI, and migration tooling — programs that run outside the cluster. This page covers the tools and processors that ship inside the cluster.
Ask the cluster, not the docs
A running cluster is always the authoritative inventory for the version you are on.
| Surface | Request | Notes |
|---|---|---|
| Agent tools | GET /_plugins/_ml/tools | Returns name, type, description, and version for every registered tool type. |
| Ingest processors | GET /_nodes/ingest?filter_path=nodes.*.ingest.processors | Complete. Includes processors contributed by every installed module. |
| Search processors | GET /_nodes/search_pipelines | Incomplete — see the warning below. |
GET /_nodes/search_pipelines reports only request_processors and response_processors.
It omits search phase results processors, which is where normalization-processor lives —
the processor that makes hybrid search work. Do not treat its output as the full search
processor list. The complete list is in
Search processors.
Agent tools
A tool is a reusable building block an agent calls to perform one specific task —
search an index, run a deployed model, call an external service. You reference a tool by
its type when registering an agent. For parameters, examples, and per-tool detail, see
Tools.
Tool type | What it does |
|---|---|
AgentTool | Runs any agent. |
CatIndexTool | Retrieves index information for the Lucenia cluster. |
IndexMappingTool | Retrieves index mapping and setting information for an index. |
MLModelTool | Runs machine learning models. |
NeuralSparseSearchTool | Performs sparse vector retrieval. |
PPLTool | Translates natural language into a Piped Processing Language (PPL) query. |
RAGTool | Uses neural search or neural sparse search to retrieve documents and integrates a large language model to summarize the answers. |
SearchAlertsTool | Searches for alerts. |
SearchAnomalyDetectorsTool | Searches for anomaly detectors. |
SearchAnomalyResultsTool | Searches anomaly detection results generated by anomaly detectors. |
SearchIndexTool | Searches an index using a query written in query domain-specific language (DSL). |
SearchMonitorsTool | Searches for alerting monitors. |
VectorDBTool | Performs dense vector retrieval. |
VisualizationTool | Finds visualizations in OpenSearch Dashboards. |
Ingest processors
Ingest processors transform documents on the write path, inside an ingest pipeline. The complete table, with a link to each processor's own page, is in Ingest processors.
The processors below have dedicated pages in this version:
| Processor | What it does |
|---|---|
chunk | Splits text content into overlapping chunks using recursive, fixed, semantic, or topic-shift algorithms. Designed for RAG and vector search pipelines. |
content_extract | Extracts structured content blocks from documents in various formats (PDF, DOCX, HTML, images) via inline text, S3/HTTPS references, or base64 attachments. |
embed | Generates vector embeddings from text, image, or multimodal content using Bedrock, OpenAI, or HTTP providers. |
ellipse | Converts an ellipse geometry (WKT or GeoJSON) into a polygon approximation and indexes it as a geo_shape or shape. Useful for directional or asymmetric coverage areas such as cellular sectors. |
image_tiling | Splits large images into fixed-size tiles for multimodal vector search. Supports GeoTIFF/COG with HTTP Range reads and geographic bounding box computation. |
ocr | Performs optical character recognition on image blocks using LLM vision models (Claude on Bedrock). Handles charts, diagrams, tables, and handwriting. |
rerank_prepare | Annotates chunks with document-level metadata and position scores for search-time reranking. |
Search processors
Search processors transform requests, responses, and intermediate phase results on the read path, inside a search pipeline. The complete tables are in Search processors.
They run in three places:
- Request processors rewrite the query before it is executed — for example
query_embedding,oversample. - Response processors transform the hits that come back — for example
multimodal_rerank,retrieval_grounding. - Phase results processors run between search phases on the coordinating node. This is
where
normalization-processorlives, and it is the categoryGET /_nodes/search_pipelinesdoes not report.
Related pages
- Agents and tools — agents and the tools they call.
- Ingest pipelines — building and running write-path pipelines.
- Search pipelines — building and running read-path pipelines.
- Ingestion tools and utilities — Beats, Logstash, the Lucenia CLI, and migration tooling.
- Nodes Info API — the API behind
GET /_nodes/ingest.