ReliableGPT ensures that your LLM app (Language Model), in production, will not drop any requests. The tool handles errors by using various strategies, such as retrying the request with alternative models, larger context windows, cached semantically similar responses and fallback API key.
The Key Features
Retry with an alternate model: Retry requests that failed using alternative models, such as GPT-4 or GPT3.5.
Context Window errors can be addressed by retrying requests using larger context window models.
Semantic Similarity based Cached Response: Use cached responses that are based on similarity in order to efficiently handle errors.
Fallback Key Retry: In case of Invalid Key Errors, retry the request with a backup API key.
You can seamlessly switch between Azure OpenAI (raw OpenAI) and Azure OpenAI.
Caching for overloaded servers: Use caching to handle the overload of servers and ensure smooth operations.
Handling Rotated Keys: Avoid service disruptions by handling rotated keys with ease.
Examples of Use:
Production Environment Stability: Make sure your LLM application is running in an environment that has no dropped requests. This will ensure a stable experience.
Error handling: Minimize the impact of errors on users by providing alternate solutions.
OpenAI API integration is seamless, allowing you to integrate OpenAI API with minimal errors.
ReliableGPT will ensure that your LLM application in production runs smoothly and without interruption.