官方说明开源项目2 天前
cocoindex-io/cocoindex
Incremental engine for long horizon agents 🌟 Star if you like it
在 GitHub 查看 ↗直链 · 无中转页
官方说明rprise-hero-light.svg"> <img src="cocoindex.io alt="Enterprise corpus — codebase, Slack, meeting notes, and documentation — flowing continuously through the CocoIndex incremental sync engine into a production AI agent with always-fresh context.
- ★ 数取值
- 11,710 ★ · cocoindex-io/cocoindex · 取自 GitHub 搜索 API · （2026-10-16 20:00:20 核对）
- 来源明细
- 从该仓库的 GitHub 页面直接读取 · 条目类型：开源项目
- 收录与活跃
- 收录于 2026-10-15 · 最近见到 2026-10-16 · 共见到 2 次 · 被 1 个来源列出
- 评分构成
- 综合分 126 · 11,710 ★ · 1 个来源 · repo
常见问题（答案都来自我们的记录）
怎么安装？
我们【没有】从该仓库取到安装命令（我们的 install 覆盖率只有约 4%）。请看它的 README 或 releases 页。
它适合谁 / 用来做什么？
我们把它归在这些标签下: 开源项目。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
仓库
cocoindex-io/cocoindex；我们收录于 2026-10-15；最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。第三方质量标记
Your agents deserve fresh context.
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
Star us ❤️ → ·
·
·
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
Deutsch |
English |
Español |
français |
日本語 |
한국어 |
Português |
Русский |
中文
Built with CocoIndex ❤️
See all 20+ examples · updated every week →
Get started
Declare *what* should be in your target — CocoIndex keeps it in sync forever, recomputing only the Δ.
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 —
·
·
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
Deutsch |
English |
Español |
français |
日本語 |
한국어 |
Português |
Русский |
中文
Built with CocoIndex ❤️
See all 20+ examples · updated every week →
Get started
Declare *what* should be in your target — CocoIndex keeps it in sync forever, recomputing only the Δ.
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 —
- 来源
- github · https://github.com/cocoindex-io/cocoindex
- 按领域浏览
- 开源项目
- Traction
- 11,710 ★
- 收录于
- 昨天
更多开源项目
所属领域与标签
每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。