VoltAgent provides a TypeScript framework and engineering platform for building AI agents.
Open source
24 alternativesllama-agents
llama-agents provides event-driven agent workflows for controlling AI application execution.
About llama-agents
llama-agents is an open-source framework for building and shipping document-centric agents in Python. It is built on Agent Workflows, an event-driven library where steps are async Python functions that emit and consume events, with support for branching, looping, parallel execution, state persistence, and failure recovery.
It can be used as a library through llama-index-workflows, wrapped as a REST API with streaming and human-in-the-loop support through llama-agents-server, and built and deployed with the llamactl CLI. Deployment targets mentioned include LlamaParse, AWS Bedrock AgentCore, or self-managed infrastructure, and it works with LlamaParse for OCR, structured extraction, classification, and splitting.
Key features
- Define agent steps as async Python functions that emit and consume events
- Branch, loop, and parallelize workflow execution in plain Python
- Persist state and resume runs from file or database
- Expose workflows as REST API with streaming and human review
- Deploy agents via CLI to LlamaParse, Bedrock AgentCore, or own infrastructure
- Integrate with LlamaParse for OCR, extraction, classification, and splitting
Best for: Python developers building document-centric agent pipelines for production use.
Good for
- Open source with workflow steps written in plain Python without a DSL
- Embeds in scripts, notebooks, and servers with minimal dependencies
- Supports file or database persistence for saving and resuming runs
llama-agents at a glance
- Category
- AI & Machine Learning › AI Agent Frameworks
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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llama-agents FAQ
How do I use it as a library?
Install llama-index-workflows, define a workflow with steps, and run it with workflow.run(...).
How can I expose a workflow as an API?
Use llama-agents-server to wrap a workflow as a REST API with streaming, persistence, and human-in-the-loop support, and call it with llama-agents-client.
Where can llamactl deploy agents?
To LlamaParse, AWS Bedrock AgentCore, or your own infrastructure as workflow services, MCP servers, or full-stack apps with a UI.
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