What Changed

The new release comes with significant changes in how pipelines and components work bringing you more freedom and flexibility when building your apps. With this update, you'll find:

New components that replace pipeline nodes to expand your capabilities.
Enhanced connections within pipelines for streamlined workflows, including loops and multiple branches.
Clear validation and meaningful error messages.

Pipelines

Pipelines in version 2.0 are much more flexible. You can use them to create sophisticated loops that cycle back to a component, branch out, loop back and retry, allowing for the integration of complex AI tasks. Components remain the building blocks of pipelines. Read more in Pipelines.

Version 2.0 also introduces changes to the YAML configuration file, including new formatting, component connections, and explicit pipeline inputs and outputs definitions.

Nodes

Pipeline nodes in deepset Cloud 2.0 are called components. Components are the core elements of pipelines. In new pipelines, you explicitly define how components connect and which outputs they send or receive. For details on how specific components work, see Pipeline Components.

This table summarizes the components that replace nodes from the previous version:

Version 1.0	Description	Version 2.0
AnswerDeduplication	Used in extractive QA pipelines to ensure there are no overlapping answers from the same document.	Not available, this functionality is built into ExtractiveReader, so no additional component is needed.
Converters	Convert files to documents. There are various converters available for different file types.	Converters
InterleaveDocuments	A component for labelling projects.	Not available
DeepsetCloudDocumentStore	A database for storing documents the pipeline can access at search time.	OpenSearchDocumentStore
EntityExtractor	Extracts predefined entities out of the text.	NamedEntityExtractor
FileDownloader	Download source files and stores them locally.	Coming soon
FileTypeClassifer	Routes files to appropriate pipeline branches based on their type.	FileTypeRouter
JoinAnswers	Joins answers from different components into a single list of answers.	Not available. You can use BranchJoiner or DocumentJoiner instead.
JoinDocuments	Joins documents from different components into a single list.	DocumentJoiner
PreProcessor	Cleans and splits documents before writing them into the document store.	Cleaners and Splitters: v2.0 adds a number of preprocessors, each performing a separate task, like cleaning or splitting documents.
PromptNode	Uses an LLM of your choice in the pipeline.	Builders and Generators. v2.0 introduces PromptBuilder that renders the prompt you can then send to a generator. Instead of a single PromptNode, there are generators specific to the model provider you want to use. There's also AnswerBuilder you can use to turn a generator's answer into a proper `GeneratedAnswer` object that can include documents used to generate it.
QueryClassifier	Categorizes queries into keyword-based and natural language queries.	TransformersZeroShotTextRouter and TransformersTextRouter
RetrievalScoreAdjuster	Adjusts document scores assigned by a retriever or a ranker.	This is now handled by TransformersSimilarityRanker through the `calibration_factor` and `score_threshold` parameters.
ReturnError	Attaches an error message to the answer's metadata.	ReturnError (coming soon)
Ranker	Ranks documents based on specific criteria, such as their similarity to the query.	Rankers
Reader	Locates and highlights answers in documents.	ExtractiveReader
ReferencePredictor	Predicts references for the generated answer.	ReferencePredictor
Retriever	Retrieves documents from the document store based on their relevance to the query.	Retrievers
Shaper	Modifies the input and output types.	OutputAdapter

Filters

Version v2.0 changes the syntax of filters towards a more Pythonic approach with logical operators explicitly defined. The filter syntax used in v1.0 will continue to be supported.

For details on how to construct filters in v2.0, see Filtering Logic.