Exploring Prompt Flow in Azure Machine Learning
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Chapter 1: Introduction to Prompt Flow
Prompt Flow is a feature within Azure Machine Learning that enhances the process of developing, testing, and integrating prompt engineering workflows. As the demand for applications powered by large language models (LLMs) grows, Prompt Flow emerges as an essential tool that facilitates the prototyping, experimentation, and deployment of AI solutions.
Image Source: Google
Recently, I had the opportunity to work with this tool, which is currently in Preview mode in Azure ML. To activate Prompt Flow, simply select the option ‘Build AI solutions with Prompt Flow’ in your Azure ML Studio.
Image Source: Google
Under the ‘Authoring’ section of Azure ML Studio, Prompt Flow features several tabs, including:
- Flow — For creating a new flow
- Connection — To link with Azure OpenAI or ChatGPT
- Runtime — To invoke OpenAI for transformations
- Runs — Displays the number of flow executions by the user
Image Source: Google
To initiate a flow, you can select the create option, which presents a variety of flow types. I opted for the ‘Standard Flow’ for my exploration.
Image Source: Google
The Evaluation flows encompass a mix of LLM, Python, and prompt blocks, complete with examples to facilitate understanding and execution. There is also a ‘Batch run’ feature (labeled as Bulk Test in the image below) available for testing multiple inputs simultaneously. After completing this setup, you can proceed by clicking the ‘Run’ button.
Image Source: Google
I hope this article provides you with valuable insights into Prompt Flow.
Chapter 2: Additional Resources
To learn more about Azure Machine Learning and Prompt Flow, check out the following videos:
This video, titled "Introduction to Azure Machine Learning Prompt Flow," offers an overview of the tool and its capabilities.
The second video, "Prompt Flow: An End-to-End Tool to Streamline Prompt Engineering," delves deeper into how this feature simplifies the prompt engineering process.