Agents

Note: Agents are deprecated, use Agent Workflows instead.

An “agent” is an automated reasoning and decision engine. It takes in a user input/query and can make internal decisions for executing that query in order to return the correct result. The key agent components can include, but are not limited to:

Breaking down a complex question into smaller ones
Choosing an external Tool to use + coming up with parameters for calling the Tool
Planning out a set of tasks
Storing previously completed tasks in a memory module

Getting Started

LlamaIndex.TS comes with a few built-in agents, but you can also create your own. The built-in agents include:

OpenAI Agent
Anthropic Agent both via Anthropic and Bedrock (in @llamaIndex/community)
Gemini Agent
ReACT Agent
Meta3.1 504B via Bedrock (in @llamaIndex/community)

Api References

Note for AI agents: this documentation is built for programmatic access. - Overview of all docs: https://developers.llamaindex.ai/llms.txt - Any page is available as raw Markdown by appending index.md to its URL — e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md - Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ — search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters. - A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/