Claude Cookbooks vs LlamaIndex
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A set of Jupyter notebook recipes showing how to build with the Claude API.
Open source · MIT
Python framework for building LLM apps that query your own documents and data.
Our verdict
Claude Cookbooks is a collection of Jupyter notebook examples showing how to call the Claude API for specific tasks like classification, tool use, vision, and prompt caching; you copy the snippets into your own code. LlamaIndex is a Python library you install to build apps that answer questions over your own documents and data, using retrieval to feed relevant content to a language model. They serve different purposes: pick Cookbooks to learn and borrow Claude-specific code, and LlamaIndex when you need a framework for document-based question answering.
Pick Claude Cookbooks if you want working Claude API examples to copy into a Python project for tasks like vision, tool use, or summarization.
Pick LlamaIndex if you are building a Python app that answers questions over private PDFs, documents, or databases and want swappable model and storage components.
| Key difference | Claude Cookbooks | LlamaIndex |
|---|---|---|
| Type | Learning resource of example notebooks and guides | Python library you install and run yourself |
| Best at | Showing Claude API calls across many common tasks | Retrieval over your own documents and data sources |
| Setup | Clone the repo and build from source; some recipes need extra accounts | Install with a package manager; choose and install integration packages you need |
| Model support | Built around Claude through the Claude API | Lets you swap LLM, embedding, and vector store providers |
| Maintenance signal | Code updated in the last day; check docs for current API details | Last code update 3 days ago; README notes focus shifted to LlamaParse |
Written with AI from both products' catalogue entries · updated 2026-10-29
Who each one is for
Choose Claude Cookbooks if you need…
- Python developers who want working examples of Claude API calls
- Developers exploring tool use or retrieval augmented generation with Claude
- Teams evaluating how to add vision or PDF handling to an application
- People new to the Claude API who want to follow guided examples
Choose LlamaIndex if you need…
- Python developers building retrieval-augmented generation (RAG) apps over private documents
- Teams wanting a modular toolkit where they can swap LLM, embedding and vector store providers
- Developers building agent workflows that query their own data
- Beginners who want a short path to a working document question-answering prototype
Side-by-side
| Claude Cookbooks | LlamaIndex | |
|---|---|---|
| Type | Learning resource | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 54.1k | 52.8k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Clone and build from source | Install with a package manager |
| Main language | Jupyter Notebook | Python |
| Last code update | 7 days ago | 10 days ago |
What each one is
Claude Cookbooks
This repository is a collection of Jupyter notebooks and guides with copy-able code examples for using Claude, Anthropic's AI model, through its API. Each recipe covers a specific task, such as classification, retrieval augmented generation, tool use, vision, summarization, prompt caching, or automated evaluations. Developers use it as a starting point and adapt the snippets into their own projects.
LlamaIndex
LlamaIndex is an open-source Python framework for connecting large language models to your own data, such as PDFs, documents, APIs and SQL databases. It provides connectors to load data, ways to structure it into indexes, and retrieval tools that feed relevant context to an LLM. The README also notes that the company's main focus has shifted toward its commercial LlamaParse document platform, with the open-source framework still available.
Best for
Claude Cookbooks
- Python developers who want working examples of Claude API calls
- Developers exploring tool use or retrieval augmented generation with Claude
- Teams evaluating how to add vision or PDF handling to an application
- People new to the Claude API who want to follow guided examples
LlamaIndex
- Python developers building retrieval-augmented generation (RAG) apps over private documents
- Teams wanting a modular toolkit where they can swap LLM, embedding and vector store providers
- Developers building agent workflows that query their own data
- Beginners who want a short path to a working document question-answering prototype
Strengths
Claude Cookbooks
- Covers many common tasks, from classification to vision to agents, in one place
- Code is meant to be copied and integrated into real projects
- Released under the MIT license, which permits reuse
LlamaIndex
- Large ecosystem of over 300 integration packages, per the README
- Modular design lets you customize or replace components like retrievers and query engines
- Offers both a high-level API for quick starts and lower-level APIs for advanced control
Not ideal for
Claude Cookbooks
- Non-programmers, since the recipes are code notebooks that assume coding knowledge
- People looking for a finished end-user app, because this is example code rather than a product
- Anyone needing non-Python examples, since the README says the code is primarily Python and other languages must be adapted
LlamaIndex
- Non-programmers, since it is a Python library that requires writing code
- Projects that need a fully managed hosted service, because the README points to LlamaParse for the hosted offering and the framework is a toolkit you run yourself
- Users who only need simple one-off document parsing, where a standalone parser may be simpler
Trade-offs
Claude Cookbooks
- The README is short and does not list versions or detailed setup steps, so you must read each notebook for specifics
- Some recipes link to external repositories or third-party services that need their own accounts or setup
- Examples may reflect the Claude API at the time they were written, so check current docs before relying on them
LlamaIndex
- The README says the company's primary focus has shifted to LlamaParse, so the open-source framework is secondary to its commercial product
- The README is not updated as often as the documentation, so you should check the docs for current details
- Many separate integration packages means you must choose and install the ones you need
Getting started
Claude Cookbooks
Clone the repository
git clone https://github.com/anthropics/claude-cookbooksLlamaIndex
Install core and selected integrations
pip install llama-index-coreAdd an LLM integration
pip install llama-index-llms-openaiFrequently asked questions
Should I use Claude Cookbooks or LlamaIndex?
Claude Cookbooks is a collection of Jupyter notebook examples showing how to call the Claude API for specific tasks like classification, tool use, vision, and prompt caching; you copy the snippets into your own code. LlamaIndex is a Python library you install to build apps that answer questions over your own documents and data, using retrieval to feed relevant content to a language model. They serve different purposes: pick Cookbooks to learn and borrow Claude-specific code, and LlamaIndex when you need a framework for document-based question answering. Pick Claude Cookbooks if you want working Claude API examples to copy into a Python project for tasks like vision, tool use, or summarization. Pick LlamaIndex if you are building a Python app that answers questions over private PDFs, documents, or databases and want swappable model and storage components.
What is the difference between Claude Cookbooks and LlamaIndex?
Claude Cookbooks: A set of Jupyter notebook recipes showing how to build with the Claude API. LlamaIndex: Python framework for building LLM apps that query your own documents and data. Claude Cookbooks suits python developers who want working examples of claude api calls, while LlamaIndex suits python developers building retrieval-augmented generation (rag) apps over private documents.
Are Claude Cookbooks and LlamaIndex free?
Claude Cookbooks: Free and open source. LlamaIndex: Free and open source.
Is Claude Cookbooks or LlamaIndex more popular?
Claude Cookbooks has more GitHub stars (54.1k) than LlamaIndex (52.8k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to Claude Cookbooks and LlamaIndex?
Other options people compare them with include LangChain, OpenAI Cookbook, LangGraph, PageIndex, OpenAI Agents SDK.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.