BerriAI/reliableGPT: Ensure LLM App Reliability

BerriAI/reliableGPT

BerriAI/reliableGPT handles LLM app errors with retry, fallback, and caching mechanisms

BerriAI/reliableGPT: Ensure LLM App Reliability

BerriAI/reliableGPT is a powerful tool designed to enhance the reliability of Language Learning Model (LLM) applications. It offers a comprehensive solution to handle various types of errors that may occur in the LLM app lifecycle. One of the key features of reliableGPT is its ability to retry with alternate models. In the event of a request failure, it automatically retries with models such as GPT-4, GPT3.5, GPT3.5 16k, and text-davinci-003. This retry mechanism helps to ensure that the application continues to function smoothly even in the face of model-related issues. Another important aspect of reliableGPT is its handling of context window errors. It automatically retries the request with models that have larger context windows, thereby reducing the likelihood of errors due to insufficient context. In addition, the tool provides a caching mechanism. If the model fallback and retries fail, reliableGPT can respond with a cached response. This caching feature is particularly useful in scenarios where the application is experiencing high traffic or server overload. reliableGPT also allows for the specification of a fallback strategy. Users can define a custom list of models to try in case of errors, ensuring that the application has a well-defined plan of action in case of failures. It also supports the addition of backup tokens and keys, which can be used in case of key rotations or invalid API key errors. Overall, BerriAI/reliableGPT is a comprehensive solution that helps to ensure the smooth operation of LLM applications by effectively handling a wide range of errors and providing robust fallback mechanisms.

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