Apify Integration for Dify

This repository contains a plugin for the Dify.ai platform, enabling seamless integration with the Apify web scraping and automation platform.

Features

• Run Actor – Start any Apify actor by its unique actorId with custom input.
• Run Task – Execute predefined Apify tasks with one click.
• Scrape Single URL – Quickly scrape data from a single web page without configuring a full crawl.
• Get Dataset Items – Retrieve results stored in an Apify dataset.
• Get Key-Value Store Record – Fetch a record from an Apify key-value store.
• Actor Run Finished Trigger – Trigger downstream actions in Dify when an Apify actor or task run finishes.
• Flexible Execution Modes – Choose between asynchronous (fast return) and synchronous (wait for results) execution.
• Finished Trigger (Webhook) – Trigger Dify workflows automatically upon the completion of an Apify Actor or task.

Prerequisites

Before you begin, ensure you have the following installed and configured:

• Python: Version 3.12 or newer is required.
• UV: You also need pre-installed UV package manager for Python
• Apify Account: You will need an Apify account and your personal API Token. You can find your token in the Apify Console.
• Dify Account: A Dify account to test the plugin.

Installation & Setup

Follow these steps to set up the project for local development.

1. Install with Standalone Binary (macOS / Linux)

Download the right binary from the Dify Plugin CLI release page.

• macOS (ARM — Apple Silicon): e.g. dify-plugin-darwin-arm64
• macOS (Intel): dify-plugin-darwin-amd64
• Linux (amd64 or arm64): dify-plugin-linux-amd64

2. Make the binary executable:

chmod +x dify-plugin-<platform-arch>

3. Run version check:

./dify-plugin-<platform-arch> version

4. Rename and move it to your system PATH:

mv dify-plugin-<platform-arch> dify
sudo mv dify /usr/local/bin/

5. Confirm installation with:

dify version

6. Clone the Repository

git clone https://github.com/apify/apify-dify-integration.git
cd apify-dify-integration

7. Create and Activate a Virtual Environment

It is highly recommended to use a virtual environment to manage project dependencies.

# Create the virtual environment
uv venv

# Activate it (on macOS/Linux)
uv pip install -e ".[dev]"

8. Install Dependencies

This project uses a requirements.txt file to manage its dependencies.

pip install -r requirements.txt

And we are pretty much ready!

Debugging & Development

To enable interactive debugging, follow these steps:

1. Create an environment file
   Copy .env.example to .env.

2. Obtain your debugging key

   • Go to the Dify Plugins page.

   • Click the bug icon in the upper right corner to generate a debugging key.

   • Replace the default value of REMOTE_INSTALL_KEY in your .env file with this key.

     

3. Run the project
   Start the project in debug mode with:

   python -m main

Usage Example: Running an Actor

This section shows how to run an Apify actor inside a Dify workflow.
We will use the Google Maps Extractor actor (2Mdma1N6Fd0y3QEjR) as an example.

Step 1: Create a New Workflow

1. Open your Dify project.
2. Create a new Workflow from Blank.

4. Drag and drop the Run Actor (Apify Plugin) block onto the canvas.

Step 2: Configure the Run Actor Block

1. Select the Run Actor block.
2. Fill in the following settings:
   • Actor ID:

     2Mdma1N6Fd0y3QEjR
     

   • Example Input Body (JSON):

     {
       "categoryFilterWords": ["abbey"],
       "countryCode": "af",
       "language": "en",
       "locationQuery": "New York, USA",
       "maxCrawledPlacesPerSearch": 1,
       "placeMinimumStars": "two",
       "searchMatching": "all",
       "searchStringsArray": ["restaurant"],
       "skipClosedPlaces": false,
       "website": "allPlaces"
     }

   • Wait for Finish:
     Set to false (the workflow will return immediately without waiting for the actor to complete).

Step 3: Connect Workflow Blocks

1. Put End block in a workflow.

2. Connect the Run Actor block to the End block.
3. Create a variable to store results:
   • Open the output of the End block.
   • Add a variable, e.g., result, that maps to the actor’s response.

Step 4: Run the Workflow

1. Click the Run button.
2. Dify will trigger the Apify actor 2Mdma1N6Fd0y3QEjR.
3. Since wait_for_finish = false, the workflow will immediately return with the run details (including the run ID).
4. You can check results in Apify Console Runs Page.

Support

• For Apify documentation, visit docs.apify.com.
• For Dify plugin development, check Dify Plugin Docs.