AI models are evolving fast, and DeepSeek is one of the newest players shaking things up. Integrating advanced AI models into your projects has become increasingly accessible, thanks to platforms like BuildShip and models such as DeepSeek. DeepSeek, a Chinese AI startup, has recently introduced DeepSeek-R1, an open-source AI model that matches the performance of leading models like OpenAI's initial reasoning model but at a fraction of the cost.
Whether you're working with DeepSeek Chat for conversational AI or DeepSeek Reasoner for advanced problem-solving, integrating these models into your BuildShip workflows is easier than you think. No complex code—just simple, intuitive blocks that get the job done.
BuildShip makes it incredibly easy to use DeepSeek, letting you skip the hassle of writing API calls and focus on building awesome AI-powered tools with a simple drag-and-drop workflow.
Getting Started: Setting Up DeepSeek in BuildShip
First things first, let’s get DeepSeek running inside BuildShip.
Create a new workflow: Open BuildShip and start with an empty canvas.
Access the Nodes Library: Scroll down to the DeepSeek integration group.
Pick Your Node: You’ll find three integration nodes:
Text Generator Node (for AI-generated responses)
JSON Generator Node (for structured outputs)
Stream Response Node (for real-time responses)
We’ll start with the Text Generator Node, which works similarly to OpenAI’s text generation models.
Setting Up the Text Generator Node
Drag the node into your workflow.
Enter your DeepSeek API key. If this is your first time using DeepSeek, grab your API key from the DeepSeek API platform and add it here.
Set instructions for the AI. Example: “You are a helpful assistant.”
Enter a prompt. Let’s test with: “What’s the capital of France?”
Adjust settings (optional). You can tweak model temperature and max tokens based on your needs.
Test the Node. Click run and watch as DeepSeek generates: “The capital of France is Paris.” Perfect!
Experimenting with DeepSeek Reasoner (R1)
Now, let’s test something more advanced: DeepSeek’s reasoning model (R1).
Switch the model from DeepSeek Chat to DeepSeek Reasoner.
Use the same instructions and prompt. (We’re still asking for a love poem.)
Run the test.
This time, the response takes a bit longer—because DeepSeek R1 is actually thinking through its response before generating it. The result? A poem that feels more thoughtful and structured. If you check the API response, you’ll notice it includes a “reasoning content” field—this logs the AI’s thought process before generating its final output.
Structured Outputs: Using DeepSeek for JSON Responses
Sometimes, you need structured data instead of free-text responses. That’s where the JSON Generator Node comes in handy.
Drag in the JSON Generator Node.
Set up instructions and a schema. Example:
{ "question": "What is the highest mountain in the world?", "answer": "Mount Everest" }
Test the Node.
The AI now returns structured JSON, which is perfect for database storage, dashboards, or API integrations.
Streaming AI Responses in Real-Time
Want to stream AI responses as they come in (like ChatGPT does)? Use the Stream Response Node.
Add the Stream Response Node to your workflow.
Set up a trigger (REST API Call). This lets external apps interact with your workflow.
Choose how responses are streamed. You can use:
Clean text chunks (simple text streaming)
Server-Sent Events (SSE) (ideal for front-end tools like FlutterFlow)
Test it! Once you call the workflow’s public API URL, you’ll see responses streaming in live.
Alternative Approach: Using DeepSeek via Grok
If you’d rather not use the native DeepSeek API, there’s another way: running DeepSeek’s distilled model through Grok.
BuildShip already integrates with Grok, making this process seamless.
Add the Grok Chat Node to your workflow.
Enter your Grok API key.
Set up instructions and prompts. Example: “Recommend a birthday gift for my mom who loves gardening and reading.”
Select the DeepSeek R1 model under ‘More Settings.’
Run the test.
Like before, Grok also returns a reasoning section before delivering a final answer, giving you deeper insights into AI decision-making.
For a comprehensive tutorial, please click below:
Final Thoughts: AI Without the Code Headaches
DeepSeek is an exciting addition to the AI landscape, and with BuildShip, you can tap into its potential without worrying about complex coding. Whether you’re building chatbots, automating structured outputs, or streaming AI responses, this integration gives you the flexibility to create powerful AI-driven workflows in just a few clicks.
And the best part? As DeepSeek evolves, BuildShip evolves with it—so you can always
stay on the cutting edge of AI innovation.
Until next time, happy building! 🚀
AI models are evolving fast, and DeepSeek is one of the newest players shaking things up. Integrating advanced AI models into your projects has become increasingly accessible, thanks to platforms like BuildShip and models such as DeepSeek. DeepSeek, a Chinese AI startup, has recently introduced DeepSeek-R1, an open-source AI model that matches the performance of leading models like OpenAI's initial reasoning model but at a fraction of the cost.
Whether you're working with DeepSeek Chat for conversational AI or DeepSeek Reasoner for advanced problem-solving, integrating these models into your BuildShip workflows is easier than you think. No complex code—just simple, intuitive blocks that get the job done.
BuildShip makes it incredibly easy to use DeepSeek, letting you skip the hassle of writing API calls and focus on building awesome AI-powered tools with a simple drag-and-drop workflow.
Getting Started: Setting Up DeepSeek in BuildShip
First things first, let’s get DeepSeek running inside BuildShip.
Create a new workflow: Open BuildShip and start with an empty canvas.
Access the Nodes Library: Scroll down to the DeepSeek integration group.
Pick Your Node: You’ll find three integration nodes:
Text Generator Node (for AI-generated responses)
JSON Generator Node (for structured outputs)
Stream Response Node (for real-time responses)
We’ll start with the Text Generator Node, which works similarly to OpenAI’s text generation models.
Setting Up the Text Generator Node
Drag the node into your workflow.
Enter your DeepSeek API key. If this is your first time using DeepSeek, grab your API key from the DeepSeek API platform and add it here.
Set instructions for the AI. Example: “You are a helpful assistant.”
Enter a prompt. Let’s test with: “What’s the capital of France?”
Adjust settings (optional). You can tweak model temperature and max tokens based on your needs.
Test the Node. Click run and watch as DeepSeek generates: “The capital of France is Paris.” Perfect!
Experimenting with DeepSeek Reasoner (R1)
Now, let’s test something more advanced: DeepSeek’s reasoning model (R1).
Switch the model from DeepSeek Chat to DeepSeek Reasoner.
Use the same instructions and prompt. (We’re still asking for a love poem.)
Run the test.
This time, the response takes a bit longer—because DeepSeek R1 is actually thinking through its response before generating it. The result? A poem that feels more thoughtful and structured. If you check the API response, you’ll notice it includes a “reasoning content” field—this logs the AI’s thought process before generating its final output.
Structured Outputs: Using DeepSeek for JSON Responses
Sometimes, you need structured data instead of free-text responses. That’s where the JSON Generator Node comes in handy.
Drag in the JSON Generator Node.
Set up instructions and a schema. Example:
{ "question": "What is the highest mountain in the world?", "answer": "Mount Everest" }
Test the Node.
The AI now returns structured JSON, which is perfect for database storage, dashboards, or API integrations.
Streaming AI Responses in Real-Time
Want to stream AI responses as they come in (like ChatGPT does)? Use the Stream Response Node.
Add the Stream Response Node to your workflow.
Set up a trigger (REST API Call). This lets external apps interact with your workflow.
Choose how responses are streamed. You can use:
Clean text chunks (simple text streaming)
Server-Sent Events (SSE) (ideal for front-end tools like FlutterFlow)
Test it! Once you call the workflow’s public API URL, you’ll see responses streaming in live.
Alternative Approach: Using DeepSeek via Grok
If you’d rather not use the native DeepSeek API, there’s another way: running DeepSeek’s distilled model through Grok.
BuildShip already integrates with Grok, making this process seamless.
Add the Grok Chat Node to your workflow.
Enter your Grok API key.
Set up instructions and prompts. Example: “Recommend a birthday gift for my mom who loves gardening and reading.”
Select the DeepSeek R1 model under ‘More Settings.’
Run the test.
Like before, Grok also returns a reasoning section before delivering a final answer, giving you deeper insights into AI decision-making.
For a comprehensive tutorial, please click below:
Final Thoughts: AI Without the Code Headaches
DeepSeek is an exciting addition to the AI landscape, and with BuildShip, you can tap into its potential without worrying about complex coding. Whether you’re building chatbots, automating structured outputs, or streaming AI responses, this integration gives you the flexibility to create powerful AI-driven workflows in just a few clicks.
And the best part? As DeepSeek evolves, BuildShip evolves with it—so you can always
stay on the cutting edge of AI innovation.
Until next time, happy building! 🚀
AI models are evolving fast, and DeepSeek is one of the newest players shaking things up. Integrating advanced AI models into your projects has become increasingly accessible, thanks to platforms like BuildShip and models such as DeepSeek. DeepSeek, a Chinese AI startup, has recently introduced DeepSeek-R1, an open-source AI model that matches the performance of leading models like OpenAI's initial reasoning model but at a fraction of the cost.
Whether you're working with DeepSeek Chat for conversational AI or DeepSeek Reasoner for advanced problem-solving, integrating these models into your BuildShip workflows is easier than you think. No complex code—just simple, intuitive blocks that get the job done.
BuildShip makes it incredibly easy to use DeepSeek, letting you skip the hassle of writing API calls and focus on building awesome AI-powered tools with a simple drag-and-drop workflow.
Getting Started: Setting Up DeepSeek in BuildShip
First things first, let’s get DeepSeek running inside BuildShip.
Create a new workflow: Open BuildShip and start with an empty canvas.
Access the Nodes Library: Scroll down to the DeepSeek integration group.
Pick Your Node: You’ll find three integration nodes:
Text Generator Node (for AI-generated responses)
JSON Generator Node (for structured outputs)
Stream Response Node (for real-time responses)
We’ll start with the Text Generator Node, which works similarly to OpenAI’s text generation models.
Setting Up the Text Generator Node
Drag the node into your workflow.
Enter your DeepSeek API key. If this is your first time using DeepSeek, grab your API key from the DeepSeek API platform and add it here.
Set instructions for the AI. Example: “You are a helpful assistant.”
Enter a prompt. Let’s test with: “What’s the capital of France?”
Adjust settings (optional). You can tweak model temperature and max tokens based on your needs.
Test the Node. Click run and watch as DeepSeek generates: “The capital of France is Paris.” Perfect!
Experimenting with DeepSeek Reasoner (R1)
Now, let’s test something more advanced: DeepSeek’s reasoning model (R1).
Switch the model from DeepSeek Chat to DeepSeek Reasoner.
Use the same instructions and prompt. (We’re still asking for a love poem.)
Run the test.
This time, the response takes a bit longer—because DeepSeek R1 is actually thinking through its response before generating it. The result? A poem that feels more thoughtful and structured. If you check the API response, you’ll notice it includes a “reasoning content” field—this logs the AI’s thought process before generating its final output.
Structured Outputs: Using DeepSeek for JSON Responses
Sometimes, you need structured data instead of free-text responses. That’s where the JSON Generator Node comes in handy.
Drag in the JSON Generator Node.
Set up instructions and a schema. Example:
{ "question": "What is the highest mountain in the world?", "answer": "Mount Everest" }
Test the Node.
The AI now returns structured JSON, which is perfect for database storage, dashboards, or API integrations.
Streaming AI Responses in Real-Time
Want to stream AI responses as they come in (like ChatGPT does)? Use the Stream Response Node.
Add the Stream Response Node to your workflow.
Set up a trigger (REST API Call). This lets external apps interact with your workflow.
Choose how responses are streamed. You can use:
Clean text chunks (simple text streaming)
Server-Sent Events (SSE) (ideal for front-end tools like FlutterFlow)
Test it! Once you call the workflow’s public API URL, you’ll see responses streaming in live.
Alternative Approach: Using DeepSeek via Grok
If you’d rather not use the native DeepSeek API, there’s another way: running DeepSeek’s distilled model through Grok.
BuildShip already integrates with Grok, making this process seamless.
Add the Grok Chat Node to your workflow.
Enter your Grok API key.
Set up instructions and prompts. Example: “Recommend a birthday gift for my mom who loves gardening and reading.”
Select the DeepSeek R1 model under ‘More Settings.’
Run the test.
Like before, Grok also returns a reasoning section before delivering a final answer, giving you deeper insights into AI decision-making.
For a comprehensive tutorial, please click below:
Final Thoughts: AI Without the Code Headaches
DeepSeek is an exciting addition to the AI landscape, and with BuildShip, you can tap into its potential without worrying about complex coding. Whether you’re building chatbots, automating structured outputs, or streaming AI responses, this integration gives you the flexibility to create powerful AI-driven workflows in just a few clicks.
And the best part? As DeepSeek evolves, BuildShip evolves with it—so you can always
stay on the cutting edge of AI innovation.
Until next time, happy building! 🚀
