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DeepSeek LLM

DeepSeek Platform

import { Settings } from "llamaindex";
import { DeepSeekLLM } from "@llamaindex/deepseek";
Settings.llm = new DeepSeekLLM({
apiKey: "<YOUR_API_KEY>",
model: "deepseek-coder", // or "deepseek-chat"
});
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);
}

Currently does not support function calling.

Currently does not support json-output param while still is very good at json generating.

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/