After uploading data to Azure AI Foundry and creating an index on your data using the integration with Azure AI Search, you can implement the RAG pattern with Prompt Flow to build a generative AI application.
Prompt Flow is a development framework for defining flows that orchestrate interactions with an LLM.
A flow begins with one or more inputs, usually a question or prompt entered by a user, and in the case of iterative conversations the chat history to this point.
The flow is then defined as a series of connected tools, each of which performs a specific operation on the inputs and other environmental variables. There are multiple types of tool that you can include in a prompt flow to perform tasks such as:
- Running custom Python code
- Looking up data values in an index
- Creating prompt variants – enabling you to define multiple versions of a prompt for a large language model (LLM), varying system messages or prompt wording, and compare and evaluate the results from each variant.
- Submitting a prompt to an LLM to generate results.
Finally, the flow has one or more outputs, typically to return the generated results from an LLM.
Leave a Reply