Embeddings
18 articles
Generating, storing, and serving text and multimodal embeddings.
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Index Your Codebase for AI Agents with CocoIndex V1
Index a codebase for RAG and AI coding agents with CocoIndex V1 and Tree-sitter: language-aware chunking, embedding, and a live vector index in async Python.
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SEC EDGAR financial analytics with Apache Doris
A multi-format CocoIndex v1 pipeline that ingests SEC filings (TXT, JSON), scrubs PII, extracts topics, and powers hybrid search with Apache Doris.
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Adaptive Batching - 5x throughput on your data pipelines
CocoIndex now batches GPU and ML workloads automatically: 5x throughput on text embeddings and AI ops, with zero configuration required.
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Index PDF elements with mixed embedding models
Extract, embed, and store multimodal PDF elements (text with SentenceTransformers, images with CLIP) for unified semantic search with traceable metadata.
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Turn a Postgres table into a semantic index
Use an existing PostgreSQL table as a CocoIndex source: derive fields, embed each row, and store the vectors in Postgres with pgvector, incrementally.
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Index PDFs, images, and slides with ColPali, no OCR
Build a unified visual document index from multiple file formats (including PDFs, images, and slides) using CocoIndex and ColPali. No OCR needed.
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Index Images with ColPali: multi-vector visual search
Index images with ColPali multi-vector patch embeddings and a Qdrant MaxSim collection using CocoIndex v1: incremental, live, in plain async Python.
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Multi-Dimensional Vector Support in CocoIndex
CocoIndex natively handles typed multi-dimensional vectors, from simple arrays to multi-vector embeddings, unlocking multimodal AI pipelines at scale.
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Index faces for visual search: your own Google Photos
Build a scalable face detection and recognition pipeline with CocoIndex: embed faces, structure for search, and export to a vector DB.
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Index academic papers and extract metadata for AI agents
Index academic papers with CocoIndex: read the first page of each PDF, extract title, authors, and abstract with an LLM, and embed them for semantic search.
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CocoIndex Changelog 2025-07-07
CocoIndex updates: in-process setup/drop API, EmbedText building block, SplitRecursively improvements, union/NumPy types, and the Kuzu graph target.
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CocoIndex Changelog 2025-05-31
CocoIndex updates: Amazon S3 as a data source, improved query handling, a standalone runtime mode, and more connector and performance improvements.
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Image search in natural language with CLIP
Build live image search with CocoIndex v1, CLIP, FastAPI, and Qdrant. Embed photos and text in one vector space and search by meaning.
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How to build an index with text embeddings
Text embeddings 101: what they are, why you chunk and embed, and how to build a semantic search index with CocoIndex v1 and Postgres pgvector.
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Search your Google Drive by meaning
Index the documents in a shared Google Drive folder as text embeddings in Postgres with CocoIndex v1, then search them by meaning instead of by filename.
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Build Real-Time Codebase Indexing for AI Code Generation
Indexing codebase for RAG with CocoIndex and Tree-sitter in real-time: chunking, embedding, semantic search, and build vector index for efficient retrieval.
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Customizable Data Indexing Pipelines
What customizable data indexing pipelines are and why custom transformation logic matters, with practical CocoIndex examples.
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CocoIndex - A Data Indexing Platform for AI Applications
CocoIndex is a data indexing platform for AI: ingestion, chunking, embedding, and pipeline management for RAG, semantic search, and knowledge graphs.