Multimodal Text Node Documentation
The Multimodal Node returns textual output from selected large language models (LLMs). It supports both text and image inputs. This node is particularly useful for applications that require a seamless integration of textual and visual data processing, such as image captioning where the text is generated based on the content of an image.
Features
Key Functionalities
- Textual and Visual Input Support: Accepts both text and image inputs, enabling seamless integration of multimodal data for processing. 1. Text Generation: Produces textual outputs from selected large language models (LLMs) based on the provided input. 1. Image-Based Text Generation: Generates captions and descriptive text based on the content of images, making it suitable for applications like image captioning. 1. LLM Integration: Supports integration with multiple large language models, offering flexibility to choose the best-suited model for specific use cases.
- Context-Aware Processing: Combines textual and visual data inputs to enhance the accuracy and relevance of the generated output.
Benefits
- Versatility: Enables applications in various domains, such as image captioning, multimodal analysis, and AI-driven content generation. 1. Enhanced User Experience: Provides seamless handling of both text and image inputs, improving workflow efficiency.
- Scalability: Adapts easily to a wide range of use cases, from simple text generation to complex multimodal data analysis. 1. Efficiency: Consolidates textual and visual processing into a single node, reducing the need for separate tools and streamlining workflows. 1. Advanced AI Integration: Leverages the capabilities of modern LLMs to deliver accurate and contextually rich outputs.
What can I build?
- Develop applications that seamlessly integrate text and image data processing for tasks like image captioning.
- Create tools for automatic generation of descriptive content for visual data, enhancing accessibility.
- Build interactive applications where user actions on images are analyzed to generate contextual feedback.
- Design systems that maintain consistent tone and style across generated content based on previous interactions.
Setup
Select the Multimodal Text Node
- Fill in the required parameters.
- Build the desired flow
- Deploy the Project
- Click Setup on the workflow editor to get the automatically generated instruction and add it in your application.
Configuration Reference
| Parameter | Description | Example Value |
|---|---|---|
| Generative Model Name | Select the model to generate text based on the prompt. | Gemini Model |
| Prompt Template | Define the instructions for generating the text output.Define the instructions for generating the text output. | Tell me something about Bali |
| Attachments | Select the attachments to be used for the multi modal LLM. | {{triggerNode_1.output.topic}} |
| System Prompt | System prompt to guide the LLM | You are Travel Planner |
Low-Code Example
nodes:
- nodeId: multiModalLLMNode_924
nodeType: multiModalLLMNode
nodeName: Multi Modal
values:
promptTemplate: Tell me something about ${{triggerNode_1.output.topic}}
attachments: '{{triggerNode_1.output.topic}}'
systemPrompt: You are an AI Assistant
messages: '[]'
generativeModelName:
provider_name: mistral
type: generator/text
credential_name: Mistral API
credentialId: 32bf5e3b-a8fc-4697-b95a-b1af3dcf7498
model_name: mistral/mistral-large-2402
needs:
- triggerNode_1
- nodeId: plus-node-addNode_704346
nodeType: addNode
nodeName: ''
values: {}
needs:
- multiModalLLMNode_924Troubleshooting
Common Issues
| Problem | Solution |
|---|---|
| Invalid API Key | Ensure the API key is correct and has not expired. |
| Dynamic Content Not Loaded | Increase the Wait for Page Load time in the configuration. |
Debugging
- Check Lamatic Flow logs for error details.
- Verify API Key.