HTML convert to PDF

The OpenAI_Connector component allows OutSystems developers to easily integrate with OpenAI's Embedding API using the text-embedding-ada-002 model. It provides a simple and reusable way to generate vector embeddings from input text, enabling advanced use cases such as semantic search, recommendation engines, document similarity, and Retrieval-Augmented Generation (RAG). With this connector, developers can submit raw text to the Embedding API and receive a high-dimensional vector representation in return, ready to be stored in a vector database or used within machine learning workflows. The component is fully configurable via site properties, including the ability to set your own OpenAI API key and model version. It exposes public server actions for sending text and retrieving embeddings, making it easy to integrate into other modules or logic flows without needing to manage raw HTTP requests or external dependencies. This asset is designed for performance, modularity, and simplicity, allowing you to focus on building AI-powered experiences within your OutSystems applications. Ideal for developers building POCs, internal tools, or production-ready solutions that rely on semantic understanding.

Open AI Chat Completion created to connect your RAG with Open AI with your own Open AI Key.