ChatEngine
The chat engine is a quick and simple way to chat with the data in your index.
const retriever = index.asRetriever();const chatEngine = new ContextChatEngine({ retriever });
// start chattingconst response = await chatEngine.chat({ message: query });In short, you can use the chat engine by calling index.asChatEngine(). It will return a ContextChatEngine to start chatting.
const chatEngine = index.asChatEngine();You can also pass in options to the chat engine.
const chatEngine = index.asChatEngine({ similarityTopK: 5, systemPrompt: "You are a helpful assistant.",});The chat function also supports streaming, just add stream: true as an option:
const chatEngine = index.asChatEngine();const stream = await chatEngine.chat({ message: query, stream: true });for await (const chunk of stream) { process.stdout.write(chunk.response);}Api References
Section titled “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/