CocoIndex examples and implementation guides
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In this blog we will walk through a comprehensive example of indexing research papers with extracting different metadata — beyond full text chunking and embedding — and build semantic embeddings for indexing and querying.
CocoIndex now provides native support for Kuzu as a target graph data store. This integration features a high performance knowledge graph stack with real-time updates.
CocoIndex now provides native support for Amazon S3 as a data source. Additionally, CocoIndex integrates with AWS Simple Queue Service (SQS), enabling true real-time incremental processing of your S3 data.
In this project, we will build image search and query it with natural language. You can search for “a cute animal” or “a red car”, and the system returns visually relevant results — no manual tagging needed.
In this blog, we will build index with text embeddings and query it with natural language. We try to keep it minimalistic and focus on the gist of the indexing flow.
In this blog, we will build a real-time product recommendation engine with LLM and graph database. In particular, we will use LLM to understand the category (taxonomy) of a product. In addition, we will use LLM to enumerate the complementary products - users are likely to buy together with the current product (pencil and notebook). We will use Graph to explore the relationships between products that can be further used for product recommendations or labeling.
CocoIndex makes it easy to build and maintain knowledge graphs with continuous source updates. In this blog, we will process a list of documents (using CocoIndex documentation as an example). We will use LLM to extract relationships between the concepts in each document.
In this blog, we will show you how to use OpenAI API to extract structured data from patient intake forms with different formats, like PDF, DOCX, etc.
In this blog, we will show you how to use CocoIndex to build text embeddings from Google Drive for RAG step by step including how to setup Google Cloud Service Account for Google Drive. CocoIndex is an open source framework to build fresh indexes from your data for AI. It is designed to be easy to use and extend.
In this blog, we will show you how to index a codebase for RAG with CocoIndex. CocoIndex provides built-in support for codebase chunking, with native Tree-sitter support and real-time update.
In this blog, we will show you how to use Ollama to extract structured data that you can run locally and deploy on your own cloud/server.