request_eval_results
[' The original query is asking for all iPhone models, so the "q" parameter is correct. The "max_price" parameter is also correct, as it is set to null, meaning that no maximum price is set. The predicted query adds two additional parameters, "size" and "min_price". The "size" parameter is not necessary, as it is not relevant to the question being asked. The "min_price" parameter is also not necessary, as it is not relevant to the question being asked and it is set to 0, which is the default value. Therefore, the predicted query is not semantically the same as the original query and is not likely to produce the same answer. Final Grade: D',
 ' The original query is asking for laptops with a maximum price of 300. The predicted query is asking for laptops with a minimum price of 0 and a maximum price of 500. This means that the predicted query is likely to return more results than the original query, as it is asking for a wider range of prices. Therefore, the predicted query is not semantically the same as the original query, and it is not likely to produce the same answer. Final Grade: F',
 " The first two parameters are the same, so that's good. The third parameter is different, but it's not necessary for the query, so that's not a problem. The fourth parameter is the problem. The original query specifies a maximum price of 500, while the predicted query specifies a maximum price of null. This means that the predicted query will not limit the results to the cheapest gaming PCs, so it is not semantically the same as the original query. Final Grade: F",
rtdocs_stable/api.python.langchain.com/en/stable/use_cases/evaluation/openapi_eval.html