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How to Make Automated Pinterest Posts with APIs, A Comprehensive Guide


Pinterest is a goldmine for website traffic. Imagine automating engaging content creation and seamless posting – that's the power we'll unlock in this tutorial. We'll explore a workflow that leverages AI to generate fitness tips, create stunning visuals, and publish them directly to Pinterest using APIs.

Let's break down the process step-by-step, transforming your Pinterest game with automation.

Generating Content Ideas with AI

First, we'll harness the power of AI to generate engaging content ideas. We'll use the Claude 3.7 Sonnet model, accessed through OpenRouter, to craft compelling fitness tips.

  1. Global Variables:

    We'll use an "Edit Fields" node to define global variables that will be used throughout the workflow.

    • Post Topic: The overall theme of our Pinterest posts (e.g., "Fitness Tips").

    • Unique ID: A unique identifier for the entire run, ensuring no overlap between posts.

    • Website URL: Your website's address, which will be linked in the Pinterest posts.

    • Total Images: The desired number of Pinterest posts to generate.

  2. Creating an Image Loop:

    We use a "Code" node with JavaScript to create an array of numbers from zero to the total images so we can loop all the images for further steps.

          // Create an array of numbers from 0 to Total Image.
const totalImages = parseInt(items[0].json.TotalImage);
const result = [];
for (let i = 0; i < totalImages; i++) {
  result.push({ index: i });
}

return result;

  3. Splitting the Array:

    The "Split Out" node divides this array into individual items, allowing us to process each image independently.

  4. Looping over Items:

    The "Loop Over Items" node iterates through each item in the array, ensuring that each image gets its own unique content.

  5. Generating Pinterest Idea Data:

    The "Advanced AI Basic LM Chain" node is where the magic happens. We use a carefully crafted prompt to instruct Claude 3.7 Sonnet to generate engaging Pinterest post content.

    • Prompt:

            Create an engaging Pinterest post that highlights the following content in a bold, concise, and visually appealing format. Use vibrant language and a friendly tone. Structure the story as follows: include top headings, bottom headings, and step sections.

Output format:
{
  "top_heading": "...",
  "bottom_heading": "...",
  "steps": [
    {"number": 1, "text": "..."},
    {"number": 2, "text": "..."},
    ...
  ],
  "image_title": "...",
  "image_description": "..."
}

Follow these style guidelines:
- Tone: Friendly, motivational, and energetic
- Avoid jargon

    • Credentials:

      • Model: Claude 3.7 Sonnet

      • OpenRouter API Key: Retrieve this from your OpenRouter account (Settings > Keys).

      • Base URL: https://openrouter.ai/api/v1 (This might vary, so double-check OpenRouter's documentation.)

    • Structured Output Parser: This ensures that the AI's output is formatted in a predictable way, making it easy to use in subsequent nodes.

Crafting Visually Stunning Images with the Flux Model

Now that we have compelling content, let's create eye-catching visuals using the Flux image model.

  1. Generating an Image Prompt:

    We'll use another "Advanced AI Basic LM Chain" node to generate a detailed image prompt for the Flux model.

    • Prompt:

            Act as an expert prompt engineer for hyperrealistic photography. Generate a detailed image prompt for a healthy food item adhering to these rules:

- Focus on a single, visually appealing food item.
- Use descriptive adjectives to enhance realism and detail.
- Specify lighting, composition, and background elements.
- Keep the prompt concise and focused.

Output JSON format:
{
  "prompt": "Detailed image prompt for the Flux model"
}

Inspirations:
- A vibrant close-up of a ripe strawberry with water droplets, bathed in soft, natural light.
- A perfectly sliced avocado on a wooden board, with a shallow depth of field and a blurred background.

    • Preventing Duplicate Images: To avoid the image model generating the same food image multiple times, we use "IF" and "Set" nodes to track the previously used food items. This list is then included in the prompt to guide the model to create unique images.

  2. Fetching the Image with HTTP Request:

    The "HTTP Request" node sends a request to the Flux image model API.

    • Method: POST

    • URL: (This will depend on the specific Flux API endpoint)

    • Headers:

      • Authorization: Bearer YOUR_FLUX_API_KEY (Replace with your actual Flux API key)

    • Body: (JSON format)

            {
  "model": "BlackForestLab/Flux",
  "prompt": "{{$json.prompt}}",
  "negative_prompt": "...",
  "num_steps": 30,
  "response_format": "base64"
}

  3. Converting to an Image File:

    The "Convert to File" node takes the base64 encoded image data from the Flux API and converts it into an image file.

    • Operation: Convert base64 string to file

    • Input Field: data (This assumes the base64 data is in a field called "data")

    • Output File in Field: data

  4. Saving the Image to Google Cloud Storage:

    The "Google Cloud Storage" node saves the generated image to your Google Cloud Storage bucket.

    • Resource: Object

    • Operation: Create

    • Bucket Name: Your Google Cloud Storage bucket name

    • Object Name: image-{{$global.uniqueID}}-{{$node.LoopOverItems.runIndex + 1}}.jpg (This creates a unique filename for each image)

    • Use Input Binary Field: Enabled

    • Input Binary Field: data

  5. Constructing the Image URL:

    The "Edit Fields" node creates the public URL for the image stored in Google Cloud Storage. This URL will be used in the Pinterest post.

Crafting the Pinterest Post

With content and visuals ready, let's assemble the Pinterest post.

  1. Edit Fields:

    We use the "Edit Fields" node to assemble the data needed for the Pinterest post.

    • Top Heading

    • Bottom Heading

    • Website URL

    • Image URL

  2. Encoding the URL:

    The "Encode URI Component" node encodes all the components for security URL.

  3. Requesting a Screenshot:

    We'll use another "HTTP Request" node to take a screenshot of the preview link in the previous step.

    • URL: (This will depend on the specific Screenshot API endpoint)

Uploading to Pinterest

Finally, let's automate the process of uploading to Pinterest.

  1. Setting up Pinterest API Credentials:

    To interact with the Pinterest API, you'll need to create an app within your Pinterest developer account and obtain an access token. Make sure your configuration in Pinterest Developer meet the requirement for production usage, otherwise, you will only be able to post to sandbox environment.

  2. Creating a Board (Optional):

    If you don't already have a board to post to, you can create one programmatically using the Pinterest API.

    • Method: POST

    • URL: https://api.pinterest.com/v5/boards (Use the production URL once your app is approved)

    • Headers:

      • Authorization: Bearer YOUR_PINTEREST_ACCESS_TOKEN

    • Body: (JSON format)

            {
  "name": "Your Board Name",
  "description": "A description of your board",
  "privacy": "public"
}

  3. Getting Board ID from Redis:

    We use Redis to store and retrieve the Pinterest board ID. This allows us to easily update the board ID if needed.

    • Operation: Get

    • Key: boardID

    • Credential: Use your Redis credential. You can obtain your credential on Redis Cloud Console.

  4. Creating the Media:

    The "HTTP Request" node sends a request to the Pinterest API to create the media object (the image) that will be used in the post.

    • Method: POST

    • URL: https://api.pinterest.com/v5/media (Use the production URL once your app is approved)

    • Headers:

      • Authorization: Bearer YOUR_PINTEREST_ACCESS_TOKEN

    • Body: (JSON format)

            {
  "source_type": "image_url",
  "source_url": "{{$json.image_url}}"
}

  5. Creating the Pin:

    Another "HTTP Request" node sends a request to the Pinterest API to create the pin (the actual post).

    • Method: POST

    • URL: https://api.pinterest.com/v5/pins (Use the production URL once your app is approved)

    • Headers:

      • Authorization: Bearer YOUR_PINTEREST_ACCESS_TOKEN

    • Body: (JSON format)

            {
  "board_id": "{{$node.GetBoardID.json.value}}",
  "media_source": {
    "source_type": "image_url",
    "source_url": "{{$json.image_url}}"
  },
  "title": "{{$json.title}}",
  "description": "{{$json.description}}",
  "link": "{{$json.website_url}}"
}

  6. Updating Google Sheets:

    Finally, the "Google Sheets" node updates the Google Sheet to reflect the post's status and date.

    • Operation: Update Row

    • Document ID: Your Google Sheet's ID

    • Sheet Name: The name of the sheet containing your data

    • Column to Match On: "Row Number"

    • Row Number: The row number of the post that was just published

    • Status: "Posted"

    • Post Date: (Current date and time)

Joining the Community

Automating Pinterest is a game-changer. It allows you to focus on strategy while the system handles content creation and publishing. If you have any questions or need assistance setting up your workflow, our community is here to help. Join us to explore more templates, get expert support, and unlock the full potential of no-code automation.

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