PromptLayer provides a Python wrapper library to log, manage, and debug prompts and OpenAI API requests. It acts as middleware, recording interactions with OpenAI's API and making them searchable and replayable via a web dashboard. This is beneficial for prompt engineers and developers seeking to track, version, and iterate on their AI model inputs and outputs.

How It Works

The library integrates by wrapping the OpenAI Python client. When initialized with a PromptLayer API key, it intercepts calls to openai.Completion.create and other methods. It logs request details, arguments, and responses locally before forwarding them to the PromptLayer service. This approach allows for seamless integration with existing codebases with minimal changes, enabling centralized tracking without altering core application logic.

Quick Start & Requirements

• Install via pip: pip install promptlayer
• Requires an account and API key from PromptLayer.
• OpenAI API key is required and handled locally.
• See PromptLayer Guide for environment variable setup.

Highlighted Details

• Logs OpenAI API requests and responses locally.
• Enables searching, exploring, and replaying past completions via a dashboard.
• Supports tagging requests (pl_tags) for better organization and filtering.
• Offers a REST API for integration with other languages.

Maintenance & Community

Contributions are welcomed via email to hello@promptlayer.com.

Licensing & Compatibility

The README does not specify a license. Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

The library currently focuses on OpenAI API requests. Support for other LLM providers or advanced debugging features like A/B testing is not mentioned. The lack of a specified license may pose a risk for commercial adoption.