When users interact with your published bot, session logs are generated. In these set of steps we want to show you how to,
In the Session Viewer you can inspect the questions and answers as well as view information about the user input's path through the solution to a response.
Note: if you haven't yet published your bot you will not find a 'Log Data Source' listed under Optimization. In case you have published your bot, and no one has chatted with it, the LDS will exist but be empty. Please refer to the section on how to generate session logs.
You may want to examine a particular session you discover while running queries against the LDS. In general, your query should display the 'session ID', which you can then copy and use in a more detailed query focused on that session, as well as for locating the session directly in the session viewer for a more detailed examination. We will show you how to do that in these sections.
The following steps show you how to run a query that returns a list of all sessions along with some associated information.
la s.beginTime as beginTime, s.id as sessionId, s.transactionCount as numberOfInputs order by beginTime.
Now that we have a session to explore, we can run a query to show a simple transcript of that session (inputs and outputs). Try this:
la t.id, t.time, t.e1.userInput, t.e2.answerText: s.id == "<copy your session ID here>"
Now you should see a report of each transaction, along with the user input and bot response, for an easy reading of what happened.
Sometimes you may want additional detailed information about the session, such as which listeners were active, which variables were set, etc. Perhaps you want to verify that something new that you built is working as expected. In this case, you can view a detailed report of the session, including all events of each of the individual transactions, in the session viewer.
s.id == "<paste in the session ID here>".
From this view, you can expand or hide transaction and event details. Viewing the session in such detail can also be helpful when constructing queries you need to discover more sessions in which something particular happened, e.g. a variable changing while a particular flow is active, etc.
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