In this article, we will explore the functionality and usage of the index() function in Python. We will dive into the syntax, parameters, and various techniques to effectively utilize this function in your code. By understanding how to use the index() function, you will be equipped with a ...
Performing Data Concatenation with the Pandas concat() Function: This guide explains how to use the concat() function in Pandas to concatenate data from multiple DataFrames. Using the Pandas iloc[] Function for Indexing and Selecting Data: This tutorial demonstrates how to use the iloc[] function...
// function sub_select// 循环的读数据行直至不满足查询条件while(rc==NESTED_LOOP_OK&&join->return_tab>=join_tab){in_first_read=true;if(in_first_read){in_first_read=false;// 读第一个记录:对于 index scan 则调用 join_init_read_record// 一般的有两种方法 rr_quick(index scan) / rr_sequ...
在print_tuple函数中,我们使用std::make_index_sequence来生成一个std::index_sequence,然后将其传递给print_tuple_impl函数。 在口语交流中,我们可以这样描述这个示例: “In this example, we first define a helper functionprint_tuple_implthat takes astd::tupleand astd::index_sequenceas parameters. Then, ...
Tuple<T1,T2> Tuple<T1,T2,T3> Tuple<T1,T2,T3,T4> Tuple<T1,T2,T3,T4,T5> Tuple<T1,T2,T3,T4,T5,T6> Tuple<T1,T2,T3,T4,T5,T6,T7> Tuple<T1,T2,T3,T4,T5,T6,T7,TRest> TupleExtensions Type TypeAccessException TypeCode TypedReference TypeInitializationException TypeLoadException TypeUnload...
Tuple<T1,T2> Tuple<T1,T2,T3> Tuple<T1,T2,T3,T4> Tuple<T1,T2,T3,T4,T5> Tuple<T1,T2,T3,T4,T5,T6> Tuple<T1,T2,T3,T4,T5,T6,T7> Tuple<T1,T2,T3,T4,T5,T6,T7,TRest> TupleExtensions 類型 TypeAccessException TypeCode TypedReference TypeInitializationException TypeLoadException TypeUnload...
Tuple<T1,T2> Tuple<T1,T2,T3> Tuple<T1,T2,T3,T4> Tuple<T1,T2,T3,T4,T5> Tuple<T1,T2,T3,T4,T5,T6> Tuple<T1,T2,T3,T4,T5,T6,T7> Tuple<T1,T2,T3,T4,T5,T6,T7,TRest> TupleExtensions 类型 TypeAccessException TypeCode TypedReference TypeInitializationException T...
context_gpt4 = ServiceContext.from_defaults(llm=gpt4)# Define Faithfulness and Relevancy Evaluators which are based on GPT-4faithfulness_gpt4 = FaithfulnessEvaluator(service_context=service_context_gpt4)relevancy_gpt4 = RelevancyEvaluator(service_context=service_context_gpt4)# Define function to ...
Tuple<T1,T2> Tuple<T1,T2,T3> Tuple<T1,T2,T3,T4> Tuple<T1,T2,T3,T4,T5> Tuple<T1,T2,T3,T4,T5,T6> Tuple<T1,T2,T3,T4,T5,T6,T7> Tuple<T1,T2,T3,T4,T5,T6,T7,TRest> TupleExtensions 类型 TypeAccessException TypeCode TypedReference TypeInitializationException TypeLoadException TypeUnload...
Returns: tuple: A tuple containing the average response time, faithfulness, and relevancy metrics. """ total_response_time = 0 total_faithfulness = 0 total_relevancy = 0 # create vector index llm = OpenAI(model="gpt-3.5-turbo") service_context = ServiceContext.from_defaults(llm=llm, chunk...