Hello everyone,
I’m currently working on a Python project that integrates the GPT completion API, but I’m facing a challenge with the debugging process. I’m primarily using a library like Chainlit, the nature of my project makes it unsuitable for a Jupyter Notebook environment,
Issue: Each time I debug the program, I need to start from the beginning, which involves waiting for new outputs from the GPT API. This not only consumes time but also incurs additional costs. A significant concern is the variability in GPT’s outputs, making it difficult to reproduce and pinpoint bugs consistently.
Question: Is there an elegant method or a Python library that allows me to switch between real GPT API outputs and a mock API? Specifically, I’m looking for a way to replay former outputs from the GPT API during the debugging process. This functionality would greatly streamline my debugging workflow and help in consistently reproducing issues.
PS. * What kind of debugging tools or environments are you currently using?