💼 productive forces

Weavel

AI prompts engineers to optimize large language model applications

#AI
#LLM
#Assessment Tools
#Dataset management
Weavel

Product Details

Weavel is an AI prompt engineer that helps users optimize the application of large language models (LLM) through functions such as tracking, data set management, batch testing and evaluation. Used in conjunction with the Weavel SDK, Weavel automatically records and adds LLM-generated data to your dataset, enabling seamless integration and continuous improvement for specific use cases. In addition, Weavel can automatically generate evaluation codes and use LLM as an impartial referee for complex tasks, simplifying the evaluation process and ensuring accurate and detailed performance indicators.

Main Features

1
Tracking: Record and analyze data generated by LLM to optimize model performance.
2
Dataset management: Automatically record and add data via the Weavel SDK, no pre-existing datasets required.
3
Batch testing: Conduct large-scale testing to evaluate and compare the effectiveness of different prompts.
4
Evaluation: Automatically generate evaluation codes and use LLM as an evaluation tool to ensure the fairness and accuracy of the evaluation.
5
Continuous Optimization: Leverage real-world data to continuously optimize tips.
6
CI/CD integration: Prevent performance regressions with continuous integration and continuous deployment.
7
Artificial-in-the-loop: Human guidance and feedback through ratings and feedback.

How to Use

1
Visit the Weavel website and register an account.
2
Configure the Weavel SDK and integrate it into your application.
3
Use Weavel for data set management and batch testing.
4
Set evaluation criteria and let Weavel automatically generate evaluation code.
5
Adjust tips based on evaluation results to optimize LLM applications.
6
Leverage CI/CD integration to ensure continuous performance improvement.
7
Provide human feedback to help Weavel learn and improve.

Target Users

The target audience is developers and enterprises who want to improve the performance of large-scale language model applications. Weavel helps them optimize models and improve the accuracy and efficiency of applications by providing advanced hint engineering tools. It is especially suitable for users who need to handle complex natural language processing tasks.

Examples

Businesses use Weavel to optimize customer service chatbot responses.

Developers use Weavel SDK to automatically record user interaction data for model training.

Educational institutions use Weavel to evaluate the performance of teaching assistance robots.

Quick Access

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Categories

💼 productive forces
› Development and Tools
› Model training and deployment

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