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Christian Tzolov
2024-07-20 16:18:11 +02:00
parent a5682f752d
commit 7dc5f19acb
3 changed files with 7 additions and 1 deletions
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spring-ai-docs/src/main/antora/modules/ROOT/pages/api/etl-pipeline.adoc
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@@ -8,13 +8,19 @@ The RAG use case is text to augment the capabilities of generative models by ret
== API Overview
The ETL pipelines creates, transforms and stores `Document` instances.
image::spring-ai-document1-api.jpg[Spring AI Message API, width=400, align="center"]
The `Document` class contains text, metadata and optionally additionall media types like images, audio and video.
There are three main components of the ETL pipeline,
* `DocumentReader` that implements `Supplier<List<Document>>`
* `DocumentTransformer` that implements `Function<List<Document>, List<Document>>`
* `DocumentWriter` that implements `Consumer<List<Document>>`
The `Document` class contains text and metadata and is created from PDFs, text files and other document types via the `DocumentReader`.
The `Document` class content is created from PDFs, text files and other document types throught the help of `DocumentReader`.
To construct a simple ETL pipeline, you can chain together an instance of each type.