Deepseek

When using Deepseek models, llm-exe will make POST requests to https://api.deepseek.com/v1/chat/completions. All models are supported if you pass deepseek.chat.v1 as the first argument, and then specify a model in the options.

llm-exe ships typed shorthands for the most common Deepseek models so you do not have to remember the exact model strings:

Shorthand	Default model
deepseek.chat.v1	none — set model
deepseek.chat	deepseek-chat
deepseek.v4-flash	deepseek-v4-flash
deepseek.v4-pro	deepseek-v4-pro

Basic Usage

Deepseek Chat

const llm = useLlm("deepseek.chat.v1", {
  model: "deepseek-chat", // specify a model
});

Deepseek Chat By Model

const llm = useLlm("deepseek.chat", {
  // other options,
  // no model needed, using deepseek-chat model
});

const llm = useLlm("deepseek.v4-flash", {
  // other options,
  // no model needed, using deepseek-v4-flash model
});

const llm = useLlm("deepseek.v4-pro", {
  // other options,
  // no model needed, using deepseek-v4-pro model
});

INFO

You can use the following models using this shorthand:

• deepseek.chat
• deepseek.v4-flash
• deepseek.v4-pro

Authentication

To authenticate, you need to provide a Deepseek API Key. You can provide the API key various ways, depending on your use case.

1. Pass in as execute options using deepseekApiKey
2. Pass in as setup options using deepseekApiKey
3. Use a default key by setting an environment variable of DEEPSEEK_API_KEY

Generally you pass the LLM instance off to an LLM Executor and call that. However, it is possible to interact with the LLM object directly, if you wanted.

// call the LLM directly with a prompt
await llm.call(prompt);

Deepseek-Specific Options

In addition to the generic options, the following options are Deepseek-specific and can be passed in when creating a llm function.

Option	Type	Default	Description
model	string	—	The model to use. Must be specified when using deepseek.chat.v1. Can be any valid chat model. See Deepseek Docs
deepseekApiKey	string	undefined	API key for Deepseek. See authentication
topP	number	undefined	Maps to top_p. See Deepseek Docs
stopSequences	array	undefined	Maps to stop. See Deepseek Docs
frequencyPenalty	number	undefined	Maps to frequency_penalty. See Deepseek Docs
logitBias	object	undefined	Maps to logit_bias. See Deepseek Docs
useJson	boolean	undefined	When true, sets response_format to json_object
effort	string	undefined	Maps to reasoning_effort. Valid values: "low", "high", "max". Sent for deepseek-flash, deepseek-v4-pro, and legacy deepseek-v4-* ids; ignored for deepseek-chat.

See Deepseek API Reference for details on these parameters.

Thinking and provider-specific body fields

Disable thinking with extraBody:

const llm = useLlm("deepseek.v4-flash", {
  extraBody: { thinking: { type: "disabled" } },
});

To control thinking effort instead, set effort: "low", "high", or "max". See DeepSeek thinking mode.

extraBody accepts raw request fields and is shallow-merged after normal options and executor schema/tool mappings. Its fields take precedence; nested objects are replaced in full. See generic options.

Schema-typed JSON

A JSON parser with a schema requests response_format: { type: "json_object" } on DeepSeek's chat completions endpoint, which does not support json_schema. The parser retains TypeScript inference and validates the response locally by default. Include instructions for the expected JSON shape in your prompt; JSON mode does not enforce that shape on the server.