Weavel: an intelligent tool for optimizing hint engineering based on Ape

General Introduction

Weavel introduces Ape, a smart tool designed to optimize AI cueing projects.Ape helps users optimize cues by reducing cost and latency while improving performance.Ape achieves an outstanding score of 94.5% in the GSM8K benchmark, far surpassing methods such as Vanilla, CoT and DSPy. Users can set up and use Ape in just a few simple steps, significantly improving the efficiency and effectiveness of cueing projects.

Function List

• Cueing Optimization: Improving cueing performance by reducing cost and latency
• Data logging: Record input and output data to generate data sets
• Automated assessment: generating assessment code, using LLM as a rubric
• Continuous Improvement: Continuous optimization of cueing performance as production data increases

Using Help

Installation and Integration

1. Installing the SDK: Weavel provides a Python SDK that users can install with the following command:

   pip install weavel
   

2. Data logging: Record data to the Weavel platform with the following lines of code:

   import weavel
   weavel.log(input_data, output_data)
   

3. Creating Data Sets: Users can import existing data or manually create datasets for prompt optimization.

Functional operation flow

1. Cue Optimization: Users can fill in the necessary information (e.g. JSON schema) via Ape and then run the optimization process. and Ape generates an optimized version of the prompt.
2. Data logging: After integrating the Weavel SDK in an application, all input and output data is logged. Users can view the details of this data through the Weavel platform.
3. Automated assessment: Ape generates evaluation code and uses LLM as a rubric to automatically evaluate the effectiveness of the prompt.
4. continual improvement: As production data increases, Ape will continue to optimize cue performance to ensure that cues are always at their best.

usage example

1. Optimization Tips: In an AI-powered chatbot, users can optimize prompts to reduce response times and improve accuracy with Ape, which records all input and output data and generates optimized versions of the prompts.
2. data analysis: Through the Weavel platform, users can view all recorded data, analyze the effectiveness of the prompts, and make targeted optimizations.
3. Automated assessment: Ape automatically generates evaluation codes and uses LLM as a rubric to help users quickly assess the effectiveness of the prompts.

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