Your agents deserve fresh context.
CocoIndex turns codebases, meeting notes, inboxes, Slack, PDFs, and videos into live, continuously fresh context for your AI agents and LLM apps to reason over effectively — with minimal incremental processing. Get your production AI agent ready in 10 minutes with reliable, continuously fresh data — no stale batches, no context gap
Incremental · only the delta · Any scale · parallel by default · Declarative · Python, 5 min
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Built with CocoIndex ❤️
See all 20+ examples · updated every week →
Get started
pip install -U cocoindex
Declare what should be in your target — CocoIndex keeps it in sync forever, recomputing only the Δ.
import cocoindex as coco
from cocoindex.connectors import localfs, postgres
from cocoindex.ops.text import RecursiveSplitter
@coco.fn(memo=True) # ← cached by hash(input) + hash(code)
async def index_file(file, table):
for chunk in RecursiveSplitter().split(await file.read_text()):
table.declare_row(text=chunk.text, embedding=embed(chunk.text))
@coco.fn
async def main(src):
table = await postgres.mount_table_target(PG, table_name="docs")
table.declare_vector_index(column="embedding")
await coco.mount_each(index_file, localfs.walk_dir(src).items(), table)
coco.App(coco.AppConfig(name="docs"), main, src="./docs").update_blocking()
Run once to backfill. Re-run anytime — only the changed files re-embed.
Building with an AI coding agent?
Drop in our CocoIndex skill so your agent writes correct v1 code — concepts, APIs, patterns, all in one file.
See Use with AI coding agents for install steps.
React — for data engineering
See the React ↔ CocoIndex mental model →
Incremental engine for long-horizon agents
Data transformation for any engineer, designed for AI workloads —
with a smart incremental engine for always-fresh, explainable data.
Why incremental?
Your agents are only as good as the data they see.
Batch pipelines drift stale. CocoIndex stays live — and only runs the Δ.
What can you build?
See all 20+ examples · updated every week →
Working starters from the examples tree — clone, plug your source, ship.
Building something with CocoIndex? We want to see it.
Tag @cocoindex_io on X or drop a link in #showcase on Discord. We'll boost it. 🥥
Community
We are so excited to meet you.
Every typo fix, new connector, doc tweak, or full-on rewrite makes CocoIndex better.
Come hang out — big PRs and small ones, both welcome.
📝 Read the contributing guide · 🐛 good first issues · 💬 Say hi on Discord
CocoIndex Enterprise
Large corpus — built for enterprise scale.
Incremental compute is the only way to keep large corpora fresh without re-embedding them every cycle.
CocoIndex scales from a single repo to petabyte-scale stores — parallel by default, delta-only by design.
Process once. Reconcile forever.
When a source changes, CocoIndex identifies the affected records, propagates the change
across joins and lookups, updates the target, and retires stale rows —
without touching anything that didn't change.
Built on a Rust engine.
The core is Rust — production-grade from day zero.
Parallel chunking, zero-copy transforms where possible, and failure isolation
so one bad record doesn't stall the flow.
Apache 2.0 · © CocoIndex contributors 🥥