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Automate image analysis at scale: Firecrawl extracts images from websites, then OpenAI Vision analyzes them. Latenode's visual editor and affordable execution costs make processing thousands of images simple and cost-effective.
Connect Firecrawl and OpenAI Vision in minutes with Latenode.
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In the workspace, click the βCreate New Scenarioβ button.

Add the first node β a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Firecrawl, triggered by another scenario, or executed manually (for testing purposes). In most cases, Firecrawl or OpenAI Vision will be your first step. To do this, click "Choose an app," find Firecrawl or OpenAI Vision, and select the appropriate trigger to start the scenario.

Select the Firecrawl node from the app selection panel on the right.

Firecrawl
Click on the Firecrawl node to configure it. You can modify the Firecrawl URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Next, click the plus (+) icon on the Firecrawl node, select OpenAI Vision from the list of available apps, and choose the action you need from the list of nodes within OpenAI Vision.

Firecrawl
β
OpenAI Vision
Now, click the OpenAI Vision node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OpenAI Vision settings. Authentication allows you to use OpenAI Vision through Latenode.
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Use various Latenode nodes to transform data and enhance your integration:

JavaScript
β
AI Anthropic Claude 3
β
OpenAI Vision
Trigger on Webhook
β
Firecrawl
β
β
Iterator
β
Webhook response
After configuring Firecrawl, OpenAI Vision, and any additional nodes, donβt forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Run the scenario by clicking βRun onceβ and triggering an event to check if the Firecrawl and OpenAI Vision integration works as expected. Depending on your setup, data should flow between Firecrawl and OpenAI Vision (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Firecrawl + Slack: Monitor a competitor's website for changes. When the website is crawled, send a notification to a designated Slack channel to alert the team about the update.
Firecrawl + Google Sheets: Extract data from a website using Firecrawl and store the extracted information in a Google Sheet. The origin of the data is tracked through the crawl URL and stored alongside the extracted data.
About Firecrawl
Use Firecrawl in Latenode to extract structured data from websites at scale. Monitor product prices, track competitors, or collect research data automatically. Unlike standalone scrapers, Latenode lets you integrate scraped data into complex workflows with custom logic and direct API connections, all without code.
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About OpenAI Vision
Use OpenAI Vision in Latenode to automate image analysis tasks. Detect objects, read text, or classify images directly within your workflows. Integrate visual data with databases or trigger alerts based on image content. Latenode's visual editor and flexible integrations make it easy to add AI vision to any process. Scale automations without per-step pricing.
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How can I connect my Firecrawl account to OpenAI Vision using Latenode?
To connect your Firecrawl account to OpenAI Vision on Latenode, follow these steps:
Can I analyze website screenshots for specific elements?
Yes, you can! Latenode lets you visually automate the flow, sending Firecrawl's screenshots to OpenAI Vision for analysis. This unlocks opportunities to automatically identify logos or text.
What types of tasks can I perform by integrating Firecrawl with OpenAI Vision?
Integrating Firecrawl with OpenAI Vision allows you to perform various tasks, including:
How does Latenode handle large-scale Firecrawl data processing?
Latenode's serverless architecture enables processing Firecrawl data at scale. Parallelization ensures speedy large image analysis using OpenAI Vision.
Are there any limitations to the Firecrawl and OpenAI Vision integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: