cocoindex 1.0.0a21

With CocoIndex, users declare the transformation, CocoIndex creates & maintains an index, and keeps the derived index up to date based on source update, with minimal computation and changes.

Data transformation for AI

Ultra performant data transformation framework for AI, with core engine written in Rust. Support incremental processing and data lineage out-of-box. Exceptional developer velocity. Production-ready at day 0.

⭐ Drop a star to help us grow!

Deutsch | English | Español | français | 日本語 | 한국어 | Português | Русский | 中文

CocoIndex makes it effortless to transform data with AI, and keep source data and target in sync. Whether you’re building a vector index, creating knowledge graphs for context engineering or performing any custom data transformations — goes beyond SQL.

Exceptional velocity

Just declare transformation in dataflow with ~100 lines of python

# import
data['content'] = flow_builder.add_source(...)

# transform
data['out'] = data['content']
    .transform(...)
    .transform(...)

# collect data
collector.collect(...)

# export to db, vector db, graph db ...
collector.export(...)

CocoIndex follows the idea of Dataflow programming model. Each transformation creates a new field solely based on input fields, without hidden states and value mutation. All data before/after each transformation is observable, with lineage out of the box.

Particularly, developers don't explicitly mutate data by creating, updating and deleting. They just need to define transformation/formula for a set of source data.

Plug-and-Play Building Blocks

Native builtins for different source, targets and transformations. Standardize interface, make it 1-line code switch between different components - as easy as assembling building blocks.

Data Freshness

CocoIndex keep source data and target in sync effortlessly.

It has out-of-box support for incremental indexing:

• minimal recomputation on source or logic change.
• (re-)processing necessary portions; reuse cache when possible

Quick Start

If you're new to CocoIndex, we recommend checking out

• 📖 Documentation
• ⚡ Quick Start Guide
• 🎬 Quick Start Video Tutorial

Setup

1. Install CocoIndex Python library

Note: CocoIndex v1 is currently in preview (pre-release). Use the --pre flag with pip, or configure your package manager to allow pre-releases.

pip install -U --pre cocoindex

1. Install Postgres if you don't have one. CocoIndex uses it for incremental processing.

2. (Optional) Install Claude Code skill for enhanced development experience. Run these commands in Claude Code:

/plugin marketplace add cocoindex-io/cocoindex-claude
/plugin install cocoindex-skills@cocoindex

📖 Documentation

For detailed documentation, visit CocoIndex Documentation, including a Quickstart guide.

🤝 Contributing

We love contributions from our community ❤️. For details on contributing or running the project for development, check out our contributing guide.

👥 Community

Welcome with a huge coconut hug 🥥⋆｡˚🤗. We are super excited for community contributions of all kinds - whether it's code improvements, documentation updates, issue reports, feature requests, and discussions in our Discord.

Join our community here:

• 🌟 Star us on GitHub
• 👋 Join our Discord community
• ▶️ Subscribe to our YouTube channel
• 📜 Read our blog posts

Support us

We are constantly improving, and more features and examples are coming soon. If you love this project, please drop us a star ⭐ at GitHub repo to stay tuned and help us grow.

License

CocoIndex is Apache 2.0 licensed.