📄️ Overview
In AI-Flow, the node concept plays a pivotal role in defining and orchestrating data flows. These nodes enable users to structure and tailor operations, whether it's to process text, extract data from a URL, retrieve YouTube subtitles, query GPT, or even generate images.
📄️ Add an input
Input nodes play a foundational role in the application, serving as the initial point of data entry. They facilitate the injection of basic data into subsequent nodes for further processing, analysis, or action. Here, we detail three types of input nodes, each tailored for specific types of data inputs: Text, URL, and YouTube Transcript.
📄️ Add text-to-text processing
In modern applications, leveraging AI for text-to-text processing has become invaluable. Whether it's to use the power of models like GPT for generating content or to utilize generic AI actions for various tasks, integrating such nodes can transform the way you handle data. Here's how to use two primary text-to-text processing nodes in our application.
📄️ Add image generation
The integration of AI-driven image generation transforms the visual aspect of your application. Leveraging the power of renowned models like DALL-E from OpenAI or Stable Diffusion from StabilityAI, you can generate unique visuals based on textual prompts or other parameters. Below, we introduce two primary image generation nodes and their requirements.
📄️ Split input with AI
Data Splitter
📄️ Access Diverse AI Models
Replicate Node