Title: feat: Created DocEmbedder class by patelchaitany · Pull Request #5973 · feast-dev/feast · GitHub
Open Graph Title: feat: Created DocEmbedder class by patelchaitany · Pull Request #5973 · feast-dev/feast
X Title: feat: Created DocEmbedder class by patelchaitany · Pull Request #5973 · feast-dev/feast
Description: What this PR does / why we need it: This PR adds a Document Embedder capability to Feast, allowing users to go from raw documents to embeddings stored in the online vector store in a single step. It handles chunking, embedding generation, and writing the results to the online store — providing an end-to-end ingestion pipeline for RAG workflows within Feast. What changed: sdk/python/feast/chunker.py Defines the document chunking layer. Provides: A BaseChunker abstract class that users can extend with custom chunking strategies A built-in TextChunker that splits plain text by word count with configurable size, overlap, and thresholds A chunk_dataframe() convenience method to chunk all documents in a DataFrame Currently only basic text chunking is implemented. There is room for improvement — future iterations can support more advanced strategies like semantic chunking, sentence-aware splitting, or format-specific chunkers (PDF, HTML, etc.). sdk/python/feast/embedder.py Defines the embedding generation layer. Provides: A BaseEmbedder abstract class with a modality-routing registry for extensibility A MultiModalEmbedder with built-in support for text (via sentence-transformers) and image (via CLIP) embeddings Lazy model loading and configurable batch processing sdk/python/feast/doc_embedder.py The high-level orchestrator that coordinates chunking, embedding, and storage. Provides: A DocEmbedder class that runs the full pipeline: chunk -> embed -> logical layer -> write to online store A user-defined logical layer function to map output to the FeatureView schema Auto-generation of a default FeatureView if the user does not define their own (controlled by create_feature_view). This is a basic implementation intended as a starting point sdk/python/feast/init.py Updated to export DocEmbedder, LogicalLayerFn, BaseChunker, TextChunker, ChunkingConfig, BaseEmbedder, MultiModalEmbedder, and EmbeddingConfig as part of Feast's public API. Which issue(s) this PR fixes: Create DocEmbedder class along with RAGRetriever #5426 Misc
Open Graph Description: What this PR does / why we need it: This PR adds a Document Embedder capability to Feast, allowing users to go from raw documents to embeddings stored in the online vector store in a single step. ...
X Description: What this PR does / why we need it: This PR adds a Document Embedder capability to Feast, allowing users to go from raw documents to embeddings stored in the online vector store in a single step. ...
Opengraph URL: https://github.com/feast-dev/feast/pull/5973
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