Question & Answer

this model provides answers to questions that users ask from the knowledgebase of data that is acquired using qualetics data streaming docid\ vku08owje1j2 quxcf6 k the model is an enhanced form of semantic search and data ingestion through qualetics is required for successful execution and results in order to return successful results, the data being streamed will need to include the information required for indexing in the object docid\ l3qohcp0zpxzqtv7z4r6p data object as part of the object attributes the model is ready to return results immediately after successful streaming of the data for successful implementation of the q\&a model, usage of the sessionid is important by using the same sessionid in each execution of the q\&a model, the responses returned will be contextual and related to the previous responses the model provided enabling an intelligent conversation between the ai agent and the user, provided the relevent data exists if the relevant data does not exist, the model will respond with a generic response but this can be fine tuned by providing detailed instructions in the response guidance to not only provide the response on a successful match but also guidance to provide the right response when no information is present note data streaming docid\ vku08owje1j2 quxcf6 k integration is required for this model please complete the integration setup, verifying data connection docid 4iiuungko4l0wf64u ywk and ensure that the streaming is going live docid\ yuos evgre81ztel8fwdi before using this model rest api input example var settings = { "url" "https //mlapi qualetics com/api/datamachine/init?id=656f14aa547a5b6b791c2244", "method" "post", "headers" { //add authorization headers here }, "data" json stringify({ "input" "what types of footwear are available?", "topic" "products", "object type" "product", "response guidance" "you are qualie, an intelligent shopping assistant that is helping buyers in choosing the right product provide information based on the data present and ask questions if the query is not clear " }), }; $ ajax(settings) done(function (response) { console log(response); }); model input parameters parameter name parameter type required info input text yes the input query entered by the user topic text yes the topic of the question this can be dynamically supplied by the app where the user is performing the search object type text yes the type of the object, the queries relate to this needs to match the object docid\ l3qohcp0zpxzqtv7z4r6p entity being streamed using data streaming docid\ vku08owje1j2 quxcf6 k response guidance text detailed guidance to the model to provide a contextual response for example you are qualie, an ai agent designed to help users understand how to use data machines based on the information available if no answer is found, prompt for more detailed information and provide guidance to reach out to support\@qualetics com if the answers are not satisfactory rest api example model output result parameter name parameter type info answer text ai generated response based on the input query and search results rest api output example { "input" "what types of footwear are available?", "original input" "what types of footwear are available?", "answer" "the available types of footwear are sneakers, sandals, and boots ", "sessionid" "0568a0d9 c8a8 4ca2 a55c fde7cd16a02c", "final result" "the available types of footwear are sneakers, sandals, and boots ", "status" "completed" } standard output parameters every model execution output consists of the following standard output parameters input the input string required for the model to extract the categories original input this is the input provided to the first step in model which is retained across multiple steps in a data machine workflow final result the result of the model executed in the final step of the data machine workflow sessionid a unique session id that is generated for every execution of a data machine which can be used to retain results across multiple sessions status the result of the data machine execution if all of the steps in a sequence are successfully executed, a value of "completed" is provided if the execution is interrupted at any point, a value of "terminated" is provided with the reason for termination