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Read through this guide to set up DeepSeek & get familiar with how it is used across the different apps.

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Set up DeepSeek

First, go to the DeepSeek Platform and create an account or sign in. Next, navigate to the API keys section and create a new API key. Make sure to save this somewhere safe and do not share it with anyone. Once you have your API key, paste it in your .env file: 
DEEPSEEK_API_KEY=your_deepseek_api_key

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Available Models

DeepSeek models are defined in the unified model registry at lib/ai/models.ts.
ModelIDFeatures
DeepSeek Chatdeepseek-chatThinking/Reasoning
DeepSeek Chat supports thinking/reasoning capability, allowing the model to show its chain of thought before providing a final answer.

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Apps Using DeepSeek

DeepSeek is integrated through the Vercel AI SDK 6.0. Provider routing is handled by lib/ai/ai-utils.ts using customModel(), getProviderFromModelId(), and getModelInstance().

Chat

Multi-provider chat app — DeepSeek is available as an LLM provider

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Structure

The codebase uses Vercel AI SDK 6.0 with a unified model registry. Models are registered in lib/ai/models.ts and routing is managed through lib/ai/ai-utils.ts. The typical flow for an AI request:
  1. The user selects a model from the unified model registry
  2. The request is routed through getModelInstance() in lib/ai/ai-utils.ts
  3. The provider is determined via getProviderFromModelId()
  4. The model is instantiated with customModel()
  5. The response is streamed back to the user
  6. Results are stored in Supabase
More information on structure of the codebase can be found here:

Structure

Understand the project structure of the codebase