LlamaIndex vs OpenAI Agents SDK
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
Python framework for building LLM apps that query your own documents and data.
Open source · MIT
A Python SDK for building AI agents that use tools, hand off tasks, and keep conversation history.
The short answer
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
Choose OpenAI Agents SDK if you need…
- Python developers building multi-step AI workflows
- Teams that want agents to call tools and delegate work to other agents
- Developers building voice assistants with speech-to-text and text-to-speech
- Builders who want built-in tracing to debug agent runs
Side-by-side
| LlamaIndex | OpenAI Agents SDK | |
|---|---|---|
| Type | Library | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 52.8k | 30.5k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Install with a package manager | Install with a package manager |
| Main language | Python | Python |
| Last code update | 10 days ago | 5 days ago |
What each one is
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.
OpenAI Agents SDK
The OpenAI Agents SDK is a Python library for building workflows where one or more LLM-powered agents work together. Each agent can be given instructions, tools, guardrails, and the ability to hand tasks to other agents. The README says it works with the OpenAI Responses and Chat Completions APIs and with 100+ other LLMs.
Best for
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
OpenAI Agents SDK
- Python developers building multi-step AI workflows
- Teams that want agents to call tools and delegate work to other agents
- Developers building voice assistants with speech-to-text and text-to-speech
- Builders who want built-in tracing to debug agent runs
Strengths
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
OpenAI Agents SDK
- Small, focused API: an Agent plus a Runner covers the basic case, per the README examples
- Built-in features such as tools, handoffs, sessions, guardrails, and tracing are listed in the README
- Provider-agnostic design, supporting OpenAI APIs and 100+ other LLMs according to the README
Not ideal for
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
OpenAI Agents SDK
- Non-programmers, since it is a code library with no graphical interface (reason: it is used by writing Python)
- Projects that need a non-Python stack, since the README points to a separate JavaScript/TypeScript version (reason: this repo is Python-only)
- Anyone who cannot use an OpenAI API key or another supported LLM provider (reason: the examples require OPENAI_API_KEY)
Trade-offs
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
OpenAI Agents SDK
- Requires an OpenAI API key or another LLM provider and usage may incur costs (the README sets OPENAI_API_KEY for examples)
- Some features depend on the platform: the sandbox example uses UnixLocalSandboxClient, which the README says is for macOS and Linux, so Windows users need Docker or a hosted client
- Contributions are limited to repository collaborators, so outside pull requests are not accepted per the README
Getting started
LlamaIndex
Install core and selected integrations
pip install llama-index-coreAdd an LLM integration
pip install llama-index-llms-openaiOpenAI Agents SDK
Create and activate a virtual environment
python -m venv .venvInstall the package with pip
pip install openai-agentsFrequently asked questions
What is the difference between LlamaIndex and OpenAI Agents SDK?
LlamaIndex: Python framework for building LLM apps that query your own documents and data. OpenAI Agents SDK: A Python SDK for building AI agents that use tools, hand off tasks, and keep conversation history. LlamaIndex suits python developers building retrieval-augmented generation (rag) apps over private documents, while OpenAI Agents SDK suits python developers building multi-step ai workflows.
Are LlamaIndex and OpenAI Agents SDK free?
LlamaIndex: Free and open source. OpenAI Agents SDK: Free and open source.
Is LlamaIndex or OpenAI Agents SDK more popular?
LlamaIndex has more GitHub stars (52.8k) than OpenAI Agents SDK (30.5k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to LlamaIndex and OpenAI Agents SDK?
Other options people compare them with include LangChain, LangGraph, PageIndex, LightRAG, GraphRAG.
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.