📦 Bundles

What Are Bundles?

A bundle is a named collection of Beepack packages that solve a common problem together. For example, a "RAG Pipeline" bundle might include packages for embeddings generation and vector database storage - everything you need to build a retrieval-augmented generation system.

Bundles help you:

• Quickly bootstrap a project with proven package combinations
• Discover packages that work well together
• Share your own curated stacks with the community

Browsing Bundles

Via the CLI

List all available bundles:

beepack bundles

View details about a specific bundle:

beepack bundles rag-pipeline

Via the API

List all bundles:

GET /api/v1/bundles

Get a specific bundle by slug:

GET /api/v1/bundles/rag-pipeline

Installing a Bundle

Install all packages from a bundle with a single command:

beepack pull --bundle rag-pipeline

This installs every package included in the bundle. You can also cherry-pick individual packages from a bundle after inspecting its contents.

Creating a Bundle

Share your own curated package combination with the community:

Via the CLI

beepack bundle rag-pipeline openai-embeddings qdrant-client \
  -d "Complete RAG pipeline with OpenAI embeddings and Qdrant vector store" \
  -u "Build retrieval-augmented generation systems"

Via the API

POST /api/v1/bundles
Content-Type: application/json

{
  "name": "rag-pipeline",
  "description": "Complete RAG pipeline with OpenAI embeddings and Qdrant vector store",
  "useCase": "Build retrieval-augmented generation systems",
  "packages": ["openai-embeddings", "qdrant-client"]
}

Example: RAG Pipeline Bundle

Here is an example of what a bundle looks like:

{
  "slug": "rag-pipeline",
  "name": "RAG Pipeline",
  "description": "Complete RAG pipeline with OpenAI embeddings and Qdrant vector store",
  "useCase": "Build retrieval-augmented generation systems",
  "packages": [
    {
      "slug": "openai-embeddings",
      "description": "Generate text embeddings using OpenAI's API",
      "version": "1.2.0"
    },
    {
      "slug": "qdrant-client",
      "description": "Vector storage and similarity search with Qdrant",
      "version": "2.0.1"
    }
  ],
  "author": "guillaume",
  "downloads": 340,
  "createdAt": "2026-01-15T10:00:00Z"
}

API Reference