How to connect LiveChat and OpenAI Vision
Create a New Scenario to Connect LiveChat and OpenAI Vision
In the workspace, click the โCreate New Scenarioโ button.

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

Add the LiveChat Node
Select the LiveChat node from the app selection panel on the right.

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

LiveChat
โ
OpenAI Vision
Authenticate 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.
Configure the LiveChat and OpenAI Vision 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 LiveChat and OpenAI Vision 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 donโt 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.

JavaScript
โ
AI Anthropic Claude 3
โ
OpenAI Vision
Trigger on Webhook
โ
LiveChat
โ
โ
Iterator
โ
Webhook response
Save and Activate the Scenario
After configuring LiveChat, OpenAI Vision, and any additional nodes, donโt 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 โRun onceโ and triggering an event to check if the LiveChat and OpenAI Vision integration works as expected. Depending on your setup, data should flow between LiveChat and OpenAI Vision (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect LiveChat and OpenAI Vision
LiveChat + Slack: When a new chat comes into LiveChat, the content is analyzed (assuming an intermediate function/app handles the OpenAI Vision aspect, since it's not directly available). If concerning content is detected, a message is sent to a dedicated Slack channel.
LiveChat + Zendesk: When a new chat comes into LiveChat, the content is analyzed (assuming an intermediate function/app handles the OpenAI Vision aspect, since it's not directly available). If an issue is detected in the support image (from the message in LiveChat), a priority Zendesk ticket is created.
LiveChat and OpenAI Vision integration alternatives
About LiveChat
Integrate LiveChat into Latenode to automate support workflows. Route chats based on keywords, tag conversations, or trigger automated responses. Connect LiveChat data to other apps (CRM, databases) for unified insights. Simplify complex routing and ensure agents have context โ all visually, and without code.
Related categories
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.
Similar apps
Related categories
See how Latenode works
FAQ LiveChat and OpenAI Vision
How can I connect my LiveChat account to OpenAI Vision using Latenode?
To connect your LiveChat account to OpenAI Vision on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select LiveChat and click on "Connect".
- Authenticate your LiveChat and OpenAI Vision accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically analyze images sent via LiveChat?
Yes, you can! Latenode lets you instantly analyze images from LiveChat using OpenAI Vision, automatically tagging and routing chats based on image content, improving agent efficiency.
What types of tasks can I perform by integrating LiveChat with OpenAI Vision?
Integrating LiveChat with OpenAI Vision allows you to perform various tasks, including:
- Automatically classifying support tickets based on attached images.
- Extracting data from images shared in LiveChat conversations.
- Identifying product issues from screenshots sent by customers.
- Generating automated responses based on image analysis results.
- Flagging inappropriate content shared through LiveChat.
How does Latenode improve LiveChat data processing speed?
Latenode enables parallel processing of LiveChat data, speeding up analysis and response times. Scale effortlessly without code!
Are there any limitations to the LiveChat and OpenAI Vision integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- OpenAI Vision has rate limits; high volumes might require optimization.
- Image analysis accuracy depends on image quality and complexity.
- Very large files might impact workflow execution speed.