The pitfalls we have encountered in the testing phase in enterpriselevel applications with large models . Rag should be the best solution at present however due to the great difference between . It and traditional software development projects there are often unexpected pitfalls and difficulties in actual . Implementation once I communicated with a friend who was also exploring rag applications and everyone . Made the same complaint that a demo was released in a week but it was . Not easy to use in half a year this practice series is the product of .
Our Exploration and Complaints in This Article
Our exploration and complaints in this article today we want to talk specifically about the . Pitfalls we have encountered in project testing switzerland email list hoping to help partners who are also struggling . In rag previous article rag practice I the gradient of knowledge assets why start with . Testing big difference from traditional development the development process of large language models is significantly . Different from that of traditional application software mainly reflected in its black box characteristics and . The uncontrollability of output in traditional application software product managers can clearly define product functions .
And the Inputoutput is Usually Certain It
Large language model it is impossible to fully predict the behavior under specific inputs and . The output is also highly what amazon courses don’t tell you about growing your business uncertain so it is also difficult to find a representative . Test set the optimization cost is small but there are benefits the large language model . Is a process of continuous selflearning and optimization providing a sufficiently realistic test environment and .
Providing Timely Feedback After the Test is
Providing timely feedback after the test is also one of the ways to improve its . Performance and the cost is relatively low three pitfalls of rag testing bzb directory when implementing rag . For enterprises we found that many enterprises need to start with knowledge question and answer . Functions such as inputs such as company rules and regulationsmanagement requirementscultural suggestions or privatization based . On a knowledge base in a certain professional field because it is widely used and . Easy to understand we will take knowledge questions and answers as an example competency model .