DeepSeek

Use DeepSeek AI models through their OpenAI-compatible API.

Overview

DeepSeek provides powerful language models including:

• deepseek-chat - General purpose conversational model
• deepseek-reasoner - Reasoning and problem-solving capabilities

Prerequisites

1. Sign up at https://platform.deepseek.com/

2. Create an API key

3. Add the key to your environment:

   # .env
   DEEPSEEK_API_KEY=your-api-key-here
   

Usage

Basic Generation

Since DeepSeek models are not yet in the LLMDB catalog, use an inline model spec:

# Using inline model spec (recommended)
{:ok, response} = ReqLLM.generate_text(
  %{provider: :deepseek, id: "deepseek-chat"},
  "Hello, how are you?"
)

# Or normalize first
model = ReqLLM.model!(%{provider: :deepseek, id: "deepseek-chat"})
{:ok, response} = ReqLLM.generate_text(model, "Hello!")

Code Generation

model = ReqLLM.model!(%{provider: :deepseek, id: "deepseek-reasoner"})

{:ok, response} = ReqLLM.generate_text(
  model,
  "Write a Python function to calculate fibonacci numbers",
  temperature: 0.2,
  max_tokens: 2000
)

Streaming

model = ReqLLM.model!(%{provider: :deepseek, id: "deepseek-chat"})

{:ok, stream} = ReqLLM.stream_text(model, "Tell me a story about space exploration")

for chunk <- stream do
  IO.write(chunk.text || "")
end

With System Context

context = ReqLLM.Context.new([
  ReqLLM.Context.system("You are a helpful coding assistant."),
  ReqLLM.Context.user("How do I parse JSON in Elixir?")
])

model = ReqLLM.model!(%{provider: :deepseek, id: "deepseek-reasoner"})

{:ok, response} = ReqLLM.generate_text(model, context)

Helper Module

For convenience, create a wrapper module:

defmodule MyApp.DeepSeek do
  def chat(prompt, opts \\ []) do
    model = ReqLLM.model!(%{provider: :deepseek, id: "deepseek-chat"})
    ReqLLM.generate_text(model, prompt, opts)
  end

  def think(prompt, opts \\ []) do
    model = ReqLLM.model!(%{provider: :deepseek, id: "deepseek-reasoner"})
    ReqLLM.generate_text(model, prompt, Keyword.merge([temperature: 0.2], opts))
  end

  def stream_chat(prompt, opts \\ []) do
    model = ReqLLM.model!(%{provider: :deepseek, id: "deepseek-chat"})
    ReqLLM.stream_text(model, prompt, opts)
  end
end

# Usage
MyApp.DeepSeek.chat("Explain quantum computing")
MyApp.DeepSeek.think("Write a React component for a todo list")

Configuration

Environment Variables

• DEEPSEEK_API_KEY - Required. Your DeepSeek API key

Per-Request API Key

ReqLLM.generate_text(
  %{provider: :deepseek, id: "deepseek-chat"},
  "Hello!",
  api_key: "sk-..."
)

Available Models

Check https://platform.deepseek.com/docs for the latest model information.

Troubleshooting

{:error, :not_found} when using string spec

DeepSeek models are not yet in the LLMDB registry. Use an inline model spec instead:

# ❌ Won't work (model not in LLMDB)
ReqLLM.generate_text("deepseek:deepseek-chat", "Hello!")

# ✅ Works (inline model spec)
ReqLLM.generate_text(
  %{provider: :deepseek, id: "deepseek-chat"},
  "Hello!"
)

Authentication Errors

• Ensure DEEPSEEK_API_KEY is set in your .env file
• Check that the API key is valid at https://platform.deepseek.com/

Rate Limits

DeepSeek API has rate limits. If you encounter rate limiting:

• Implement exponential backoff
• Consider batching requests
• Check your plan limits at https://platform.deepseek.com/

Resources

• DeepSeek Platform
• DeepSeek API Documentation
• Model Specs Guide - For more on inline model specifications