DeepSeek LLM
import { Settings } from "llamaindex";import { DeepSeekLLM } from "@llamaindex/deepseek";
Settings.llm = new DeepSeekLLM({ apiKey: "<YOUR_API_KEY>", model: "deepseek-coder", // or "deepseek-chat"});Example
Section titled “Example”import { Document, VectorStoreIndex, Settings } from "llamaindex";import { DeepSeekLLM } from "@llamaindex/deepseek";
const deepseekLlm = new DeepSeekLLM({ apiKey: "<YOUR_API_KEY>", model: "deepseek-coder", // or "deepseek-chat"});
async function main() { const response = await llm.deepseekLlm.chat({ messages: [ { role: "system", content: "You are an AI assistant", }, { role: "user", content: "Tell me about San Francisco", }, ], stream: false, }); console.log(response);}Limitations
Section titled “Limitations”Currently does not support function calling.
Currently does not support json-output param while still is very good at json generating.
API Reference
Section titled “API Reference”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/