Generative AI Components

Azure Open AI Chat Completions

Use Azure OpenAI chat-completion models (like gpt-35-turbo or ChatGPT) to enrich your documents with: summaries, table description (based on its schema), content classification, data extraction, etc. You design and configure the prompts and include whatever metadata or content from the document to query for what you want.

You'll need to configure two workflow components in the following order:

1. Azure OpenAI Connection

2. Azure OpenAI Chat Completions

Azure OpenAI Embeddings

Use Azure OpenAI models for vector embedding generation of the content extracted from the documents.

You'll need to configure two workflow components in the following order:

1. Azure OpenAI Connection

2. Azure OpenAI Embeddings

Python Bridge Embeddings

Deploy on-premise python models BERT, MiniLM, T5, GTR-T5 for vector embedding generation of the content extracted from the documents.

You'll need to configure two workflow components in the following order:

1. Python Bridge Connection

2. Python Bridge Embeddings

Text Splitter Utility

Split the text from the documents into smaller segments, these segments could later be used for vector embedding generation. 

You need to configure the following component:

1. Text Splitter Utility