Error Handling and Tracing in LLM Development(Development of Large Model Applications 21)
Learn how to handle OpenAI API errors and monitor large models with logging tools like Weights & Biases and LangSmith for improved performance and reliability.
Hello everyone, welcome to the "Development of Large Model Applications" column.
Today we'll discuss two practical issues.
First, what errors might occur when calling the OpenAI API, and how to handle them.
Second, how to monitor the performance of large models using various logging tools.
Handling OpenAI API Errors
When interacting with the OpenAI API, you might encounter various errors. Knowing how to handle these errors is crucial for ensuring your application's stability and reliability.
Understanding potential errors makes them less surprising.
Here, we'll summarize common OpenAI API errors and practical tips for handling them.
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