Release Notes

v1.22.0

⭐️ Highlights

Some additions to Haystack 2.0 preview:

New additions include a ByteStream type for binary data abstraction and the ChatMessage data class to streamline chat LLM component integration. AzureOCRDocumentConverter, HTMLToDocument and PyPDFToDocument further expand capability in document conversion. TransformersSimilarityRanker and TopPSampler improve document ranking and query handling capabilities. HuggingFaceLocalGenerator adds to ever-growing LLM components. These significant updates, along with a host of minor fixes and refinements, mark a significant step towards the upcoming Haystack 2.0 beta release.

⬆️ Upgrade Notes

• This update enables all Pinecone index types to be used, including Starter. Previously, Pinecone Starter index type couldn't be used as document store. Due to limitations of this index type (https://docs.pinecone.io/docs/starter-environment), in current implementation fetching documents is limited to Pinecone query vector limit (10000 vectors). Accordingly, if the number of documents in the index is above this limit, some of PineconeDocumentStore functions will be limited.
• Removes the audio, ray, onnx and beir extras from the extra group all.

🚀 New Features

• Add experimental support for asynchronous Pipeline run

⚡️ Enhancement Notes

• Added support for Apple Silicon GPU acceleration through "mps pytorch", enabling better performance on Apple M1 hardware.
• Document writer returns the number of documents written.
• added support for using on_final_answer trough Agent callback_manager
• Add asyncio support to the OpenAI invocation layer.
• PromptNode can now be run asynchronously by calling the arun method.
• Add search_engine_kwargs param to WebRetriever so it can be propagated to WebSearch. This is useful, for example, to pass the engine id when using Google Custom Search.
• Upgrade Transformers to the latest version 4.34.1. This version adds support for the new Mistral, Persimmon, BROS, ViTMatte, and Nougat models.
• Make JoinDocuments return only the document with the highest score if there are duplicate documents in the list.
• Add list_of_paths argument to utils.convert_files_to_docs to allow input of list of file paths to be converted, instead of, or as well as, the current dir_path argument.
• Optimize particular methods from PineconeDocumentStore (delete_documents and _get_vector_count)
• Update the deepset Cloud SDK to the new endpoint format for new saving pipeline configs.
• Add alias names for Cohere embed models for an easier map between names

⚠️ Deprecation Notes

• Deprecate OpenAIAnswerGenerator in favor of PromptNode. OpenAIAnswerGenerator will be removed in Haystack 1.23.

🐛 Bug Fixes

• Adds LostInTheMiddleRanker, DiversityRanker, and RecentnessRanker to haystack/nodes/__init__.py and thus ensures that they are included in JSON schema generation.
• Fixed the bug that prevented the correct usage of ChatGPT invocation layer in 1.21.1. Added async support for ChatGPT invocation layer.
• Added documents_store.update_embeddings call to pipeline examples so that embeddings are calculated for newly added documents.
• Remove unsupported medium and finance-sentiment models from supported Cohere embed model list

🩵 Haystack 2.0 preview

• Add AzureOCRDocumentConverter to convert files of different types using Azure's Document Intelligence Service.
• Add ByteStream type to send binary raw data across components in a pipeline.
• Introduce ChatMessage data class to facilitate structured handling and processing of message content within LLM chat interactions.
• Adds ChatMessage templating in PromptBuilder
• Adds HTMLToDocument component to convert HTML to a Document.
• Adds SimilarityRanker, a component that ranks a list of Documents based on their similarity to the query.
• Introduce the StreamingChunk dataclass for efficiently handling chunks of data streamed from a language model, encapsulating both the content and associated metadata for systematic processing.
• Adds TopPSampler, a component selects documents based on the cumulative probability of the Document scores using top p (nucleus) sampling.
• Add dumps, dump, loads and load methods to save and load pipelines in Yaml format.
• Adopt Hugging Face token instead of the deprecated use_auth_token. Add this parameter to ExtractiveReader and SimilarityRanker to allow loading private models. Proper handling of token during serialization: if it is a string (a possible valid token) it is not serialized.
• Add mime_type field to ByteStream dataclass.
• The Document dataclass checks if id_hash_keys is None or empty in __post_init__. If so, it uses the default factory to set a default valid value.
• Rework Document.id generation, if an id is not explicitly set it's generated using all Document field' values, score is not used.
• Change Document's embedding field type from numpy.ndarray to List[float]
• Fixed a bug that caused TextDocumentSplitter and DocumentCleaner to ignore id_hash_keys and create Documents with duplicate ids if the documents differed only in their metadata.
• Fix TextDocumentSplitter failing when run with an empty list
• Better management of API key in GPT Generator. The API key is never serialized. Make the api_base_url parameter really used (previously it was ignored).
• Add a minimal version of HuggingFaceLocalGenerator, a component that can run Hugging Face models locally to generate text.
• Migrate RemoteWhisperTranscriber to OpenAI SDK.
• Add OpenAI Document Embedder. It computes embeddings of Documents using OpenAI models. The embedding of each Document is stored in the embedding field of the Document.
• Add the TextDocumentSplitter component for Haystack 2.0 that splits a Document with long text into multiple Documents with shorter texts. Thereby the texts match the maximum length that the language models in Embedders or other components can process.
• Refactor OpenAIDocumentEmbedder to enrich documents with embeddings instead of recreating them.
• Refactor SentenceTransformersDocumentEmbedder to enrich documents with embeddings instead of recreating them.
• Remove "api_key" from serialization of AzureOCRDocumentConverter and SerperDevWebSearch.
• Removed implementations of from_dict and to_dict from all components where they had the same effect as the default implementation from Canals: https://github.com/deepset-ai/canals/blob/main/canals/serialization.py#L12-L13 This refactoring does not change the behavior of the components.
• Remove array field from Document dataclass.
• Remove id_hash_keys field from Document dataclass. id_hash_keys has been also removed from Components that were using it:
  • DocumentCleaner
  • TextDocumentSplitter
  • PyPDFToDocument
  • AzureOCRDocumentConverter
  • HTMLToDocument
  • TextFileToDocument
  • TikaDocumentConverter
• Enhanced file routing capabilities with the introduction of ByteStream handling, and improved clarity by renaming the router to FileTypeRouter.
• Rename MemoryDocumentStore to InMemoryDocumentStore Rename MemoryBM25Retriever to InMemoryBM25Retriever Rename MemoryEmbeddingRetriever to InMemoryEmbeddingRetriever
• Renamed ExtractiveReader's input from document to documents to match its type List[Document].
• Rename SimilarityRanker to TransformersSimilarityRanker, as there will be more similarity rankers in the future.
• Allow specifying stopwords to stop text generation for HuggingFaceLocalGenerator.
• Add basic telemetry to Haystack 2.0 pipelines
• Added DocumentCleaner, which removes extra whitespace, empty lines, headers, etc. from Documents containing text. Useful as a preprocessing step before splitting into shorter text documents.
• Add TextLanguageClassifier component so that an input string, for example a query, can be routed to different components based on the detected language.
• Upgrade canals to 0.9.0 to support variadic inputs for Joiner components and "/" in connection names like "text/plain"