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Aggregate content insights from Feedly using LlamaCloud to train AI models, enriching your analysis with Latenode's flexible API integration. Scale insights affordably and customize your content strategy via JavaScript coding blocks.
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LlamaCloud
Feedly
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Create a New Scenario to Connect LlamaCloud and Feedly
In the workspace, click the “Create New Scenario” button.
Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a LlamaCloud, triggered by another scenario, or executed manually (for testing purposes). In most cases, LlamaCloud or Feedly will be your first step. To do this, click "Choose an app," find LlamaCloud or Feedly, and select the appropriate trigger to start the scenario.
Add the LlamaCloud Node
Select the LlamaCloud node from the app selection panel on the right.
LlamaCloud
Configure the LlamaCloud
Click on the LlamaCloud node to configure it. You can modify the LlamaCloud URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Feedly Node
Next, click the plus (+) icon on the LlamaCloud node, select Feedly from the list of available apps, and choose the action you need from the list of nodes within Feedly.
LlamaCloud
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Feedly
Authenticate Feedly
Now, click the Feedly node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Feedly settings. Authentication allows you to use Feedly through Latenode.
Configure the LlamaCloud and Feedly Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the LlamaCloud and Feedly Integration
Use various Latenode nodes to transform data and enhance your integration:
JavaScript
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AI Anthropic Claude 3
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Feedly
Trigger on Webhook
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LlamaCloud
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Iterator
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Webhook response
Save and Activate the Scenario
After configuring LlamaCloud, Feedly, and any additional nodes, don’t 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.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the LlamaCloud and Feedly integration works as expected. Depending on your setup, data should flow between LlamaCloud and Feedly (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Feedly + LlamaCloud + Slack: When a new article appears in a Feedly feed, LlamaCloud extracts data from the article content. Based on the extracted data, a message is sent to a specific Slack channel.
Feedly + LlamaCloud + Google docs: Upon a new article appearing in a Feedly feed, LlamaCloud parses the document to extract key insights. The extracted text is then appended to a Google Docs document.
About LlamaCloud
Use LlamaCloud inside Latenode to streamline AI model deployment. Build workflows that automate prompt engineering, A/B testing, and model evaluation. Connect data sources, trigger LlamaCloud jobs, and manage results via webhooks or REST. Scale AI tasks and track performance visually without complex code.
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About Feedly
Aggregate and filter Feedly articles within Latenode to automate content-driven workflows. Track brand mentions, industry trends, or competitor activity, then instantly trigger actions like posting to social media, updating databases, or notifying teams—all based on custom rules and logic.
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How can I connect my LlamaCloud account to Feedly using Latenode?
To connect your LlamaCloud account to Feedly on Latenode, follow these steps:
Can I automatically summarize Feedly articles using LlamaCloud?
Yes, you can! Latenode's visual editor makes it easy to create workflows that trigger LlamaCloud to summarize new Feedly articles, delivering key insights directly to your team.
What types of tasks can I perform by integrating LlamaCloud with Feedly?
Integrating LlamaCloud with Feedly allows you to perform various tasks, including:
How does Latenode handle large volumes of Feedly data with LlamaCloud?
Latenode's scalable architecture ensures efficient processing of large Feedly data volumes using LlamaCloud, without performance bottlenecks or manual intervention.
Are there any limitations to the LlamaCloud and Feedly integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of: