Weavel

What is Weavel

Weavel's Ape is an AI-powered prompt engineer designed to help developers build scalable and high-performing Large Language Model (LLM) applications. It is a web-based application that simplifies the process of building, testing, and optimizing LLMs by providing tracing, dataset curation, batch testing, and evaluation capabilities. Ape is the first AI-powered prompt engineer, which enables developers to work with real-world data, automate the process of logging and adding generations to their dataset, and receive accurate, nuanced performance metrics. It also allows for human-in-the-loop feedback, guiding Ape to improve its performance over time.

How to use Weavel

Users can use Weavel's Ape to design and optimize AI prompts for Large Language Models (LLMs), automating the process of tracing, dataset curation, batch testing, and evaluation, allowing developers to continuously improve the performance of their LLM applications.

Frequently Asked Questions

Can Ape improve the performance of my LLM application?

Yes, Ape can surpass base LLMs and DSPy on the GSM8K benchmark and continuously optimize prompts. Its tracing, dataset curation, batch testing, and evaluation capabilities allow developers to work with real-world data and receive accurate performance metrics.

How does Ape handle human feedback and guidance?

Ape is equipped with human-in-the-loop feedback, allowing developers to guide and improve its performance over time. You can provide scores and tips to help Ape learn and adapt to your specific use case.

Is Ape limited to specific datasets?

No, Ape works without a pre-existing dataset, automatically logging and adding LLM generations to your dataset as you use your application. This makes it possible to integrate with the Weavel SDK and leverage its capabilities without requiring a predefined dataset.