How to connect Google Cloud Speech-To-Text and LlamaCloud
Create a New Scenario to Connect Google Cloud Speech-To-Text and LlamaCloud
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 Google Cloud Speech-To-Text, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud Speech-To-Text or LlamaCloud will be your first step. To do this, click "Choose an app," find Google Cloud Speech-To-Text or LlamaCloud, and select the appropriate trigger to start the scenario.

Add the Google Cloud Speech-To-Text Node
Select the Google Cloud Speech-To-Text node from the app selection panel on the right.

Google Cloud Speech-To-Text
Configure the Google Cloud Speech-To-Text
Click on the Google Cloud Speech-To-Text node to configure it. You can modify the Google Cloud Speech-To-Text URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the LlamaCloud Node
Next, click the plus (+) icon on the Google Cloud Speech-To-Text node, select LlamaCloud from the list of available apps, and choose the action you need from the list of nodes within LlamaCloud.

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Authenticate LlamaCloud
Now, click the LlamaCloud node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your LlamaCloud settings. Authentication allows you to use LlamaCloud through Latenode.
Configure the Google Cloud Speech-To-Text and LlamaCloud 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 Google Cloud Speech-To-Text and LlamaCloud Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud Speech-To-Text, LlamaCloud, 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 Google Cloud Speech-To-Text and LlamaCloud integration works as expected. Depending on your setup, data should flow between Google Cloud Speech-To-Text and LlamaCloud (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud Speech-To-Text and LlamaCloud
Google Cloud Speech-To-Text + LlamaCloud + Slack: When a new file is added to a designated storage, Google Cloud Speech-To-Text transcribes the audio. LlamaCloud then summarizes the transcript, and the key takeaways are posted to a specified Slack channel.
Google Cloud Speech-To-Text + LlamaCloud + Google Docs: After Google Cloud Speech-To-Text transcribes an audio file from storage, LlamaCloud extracts key data to create a summary. The finalized summary is then saved to a new Google Docs document.
Google Cloud Speech-To-Text and LlamaCloud integration alternatives
About Google Cloud Speech-To-Text
Automate audio transcription using Google Cloud Speech-To-Text within Latenode. Convert audio files to text and use the results to populate databases, trigger alerts, or analyze customer feedback. Latenode provides visual tools to manage the flow, plus code options for custom parsing or filtering. Scale voice workflows without complex coding.
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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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FAQ Google Cloud Speech-To-Text and LlamaCloud
How can I connect my Google Cloud Speech-To-Text account to LlamaCloud using Latenode?
To connect your Google Cloud Speech-To-Text account to LlamaCloud on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Speech-To-Text and click on "Connect".
- Authenticate your Google Cloud Speech-To-Text and LlamaCloud accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I summarize audio files using Speech-To-Text and LlamaCloud?
Yes, you can! Latenode lets you automate the entire process, generating summaries with AI-powered steps and advanced logic for optimal precision.
What types of tasks can I perform by integrating Google Cloud Speech-To-Text with LlamaCloud?
Integrating Google Cloud Speech-To-Text with LlamaCloud allows you to perform various tasks, including:
- Transcribe audio and create knowledge base articles.
- Analyze customer call transcripts for sentiment.
- Automatically tag audio content with relevant keywords.
- Generate summaries from meeting recordings.
- Create interactive voice assistants with LlamaCloud's AI.
Can I use custom vocabularies with Speech-To-Text on Latenode?
Yes, Latenode supports custom vocabularies. Enhance accuracy using JavaScript blocks for advanced pre/post-processing of the audio data.
Are there any limitations to the Google Cloud Speech-To-Text and LlamaCloud integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large audio files may require significant processing time.
- The accuracy of transcriptions depends on audio quality.
- LlamaCloud's rate limits may impact high-volume workflows.