Worked examples and implementation guides for CocoIndex.
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.
Walk through a live CocoIndex pipeline that watches a folder of CSV files and publishes each row as JSON to a Kafka topic incrementally, with no glue code.
Build a pipeline that turns YouTube podcasts into a knowledge graph: extract speakers, statements, and entities with an LLM, then dedupe them with embeddings.
A multi-format CocoIndex v1 pipeline that ingests SEC filings (TXT, JSON), scrubs PII, extracts topics, and powers hybrid search with Apache Doris.
Auto-generate documentation for every project in your codebase: a CocoIndex pipeline writes a wiki page per repo with an LLM, kept fresh as code changes.
Build a CocoIndex v1 pipeline that turns PDF slides into vision-generated speaker notes, local Pocket TTS narration, and searchable LanceDB records.
Extract Pydantic-typed structured data from patient intake forms using DSPy and CocoIndex: OCR vision models with incremental processing.
Build a self-updating Neo4j knowledge graph from meeting notes with CocoIndex v1: LLM-extracted decisions, tasks, and owners, with embedding-based dedupe.
Rank trending HackerNews topics in Postgres with an incremental CocoIndex v1 pipeline: scrape threads and comments, extract topics with an LLM.
Build a custom CocoIndex source for the HackerNews API: fetch threads and comments in async Python, extract topics with an LLM, keep Postgres in sync.
How to use BAML and CocoIndex to extract structured data from patient intake forms in PDF/Word with LLMs continuously for production.
Extract, embed, and store multimodal PDF elements (text with SentenceTransformers, images with CLIP) for unified semantic search with traceable metadata.
Incremental ETL from Azure Blob Storage to Snowflake with CocoIndex v1: LLM invoice extraction from PDFs, processing only new or changed files.
Define query handlers in CocoIndex and trace search results back to source data in CocoInsight to close the loop on indexing strategy.
Use an existing PostgreSQL table as a CocoIndex source: derive fields, embed each row, and store the vectors in Postgres with pgvector, incrementally.
Build a unified visual document index from multiple file formats (including PDFs, images, and slides) using CocoIndex and ColPali. No OCR needed.
Index images with ColPali multi-vector patch embeddings and a Qdrant MaxSim collection using CocoIndex v1: incremental, live, in plain async Python.
Export CocoIndex data anywhere: implement a TargetHandler with a tracking record and an action sink; the engine handles diffing, syncing, and cleanup.
Build a scalable face detection and recognition pipeline with CocoIndex: embed faces, structure for search, and export to a vector DB.
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.
Build a real-time knowledge graph with Kuzu as a native CocoIndex target: incremental updates, high-performance graph queries.
Index Markdown from Amazon S3 into Postgres pgvector with CocoIndex v1: incremental processing re-embeds only the files and chunks that changed.
Search a folder of photos by meaning with CocoIndex v1: CLIP embeds images and text into one vector space, the index runs live inside a FastAPI app, and vectors live in Qdrant.
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.
An LLM extracts each product's taxonomy and complements; CocoIndex turns the labels into a Neo4j knowledge graph that answers 'bought this, also need…'.
Turn a folder of Markdown docs into a Neo4j knowledge graph: an LLM extracts subject-predicate-object triples, and CocoIndex keeps the graph in sync as the docs change.
Extract typed Patient records from PDF and DOCX intake forms with an LLM and CocoIndex v1: the nested schema is the whole prompt; results land in Postgres.
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.
Indexing codebase for RAG with CocoIndex and Tree-sitter in real-time: chunking, embedding, semantic search, and build vector index for efficient retrieval.
Extract structured data from PDF manuals locally with Ollama and CocoIndex: docling converts PDFs to Markdown, a local LLM fills typed Postgres rows.