Investigate and resolve unexpected behavior in your custom Virtual Agent topics.
Duplicate a topic before debugging and changing it
Duplicate a topic rather than update a live topic. The unmodified original topic can serve
as both a reference and a backup, and retaining the original enables you to quickly restore
the topic. Remember to deactivate the original topic before publishing the duplicate.
Debug a topic while previewing your conversations
As you create or update a topic in Virtual Agent Designer , use the
Preview button to test a conversation. The preview pop-up window
shows the conversation as it appears within Service Portal . Elements in your
conversation might appear differently in third-party messaging applications. Test your
conversations in any third-party applications where you intend to deploy Virtual Agent .
Use the conversation preview logs to view errors and messages logged while previewing a
topic. The following steps describe how to access the conversation preview logs. Use
gs.log,
gs.print, and
gs.warn
statements in your scripts to output information in this log.
In Virtual Agent Designer , click
Preview to begin previewing a
topic.
In the topic preview window, select the Show Logs check
box.
Note: The logs record information only after you select the Show
Logs check box. Be sure to select this option immediately after the topic
preview loads to ensure that all logging information is available.
Watch for warnings on controls within your topic
Controls that are missing necessary information show a red icon in the upper left corner of
the control. The icon shows a number indicating the number of issues in that control. Point
to this icon to see a list of the issues in the control.
Another icon appears in the upper left corner of the designer to indicate the number of
issues within the entire topic.
Check for errors when a topic preview does not run
Additional information appears under the Virtual Agent Designer canvas when an
error prevents the topic from running. Use the information provided to correct any errors in
your conversation.
Common Virtual Agent
issues
Issue
Possible resolution
Cannot see module designer under collaboration
User might not have the virtual_agent_admin role.
Virtual Agent plugin
might not be activated.
Cannot edit a topic
Logged-in user must be in the same application scope as the topic.
Cannot preview topic
Make sure that all required fields are filled in on the node
properties.
Ensure that your browser is configured to permit pop-ups from your
instance.
Web client stuck at Connecting...
One or more of your topics might be missing. Check the Topics page to ensure
that topics are present on the instance and in the Active state.
Review topics that run in a conversation flow
During a conversation session, Virtual Agent captures the conversation "tasks" that occur
during the conversation. A conversation task is the runtime execution of a topic during the
conversation. For a given conversation session, Virtual Agent records the various topics
run, such as the topics that a user requests or selects. Also recorded are the setup and any
small talk topics that run during the conversation.
To see which tasks were run during the session, check the Conversation
[sys_cs_conversation] table. In the navigation filter, enter
sys_cs_conversation.list to view the Conversation table. For each
conversation, you can view two related tables:
Conversation Tasks [sys_cs_conversation_task] table — Lists all the tasks for a
conversation. The relevant fields in each record include: Topic
(name of the topic that was executed at runtime) and State .
Conversation Messages [sys_cs_message] table — The Payload
field in each record contains the message string displayed for the conversation task
(runtime topic executed).
Check NLU prediction information in the Open NLU Predict Logs
When reviewing or debugging topics that use Natural Language Understanding, use the Open
NLU Predict Logs [open_nlu_predict_log] table to view the NLU prediction records for topics.
Each record in the log identifies the utterance and corresponding intents (topics) and
entities determined by the NLU service. Each record also includes the NLU prediction scores
calculated during topic discovery (intent matching) and entity extraction.
To view the log, enter open_nlu_predict_log.list in the navigation
filter.
The log information includes:
Table 1.
Field
Description
Created
Date and time the NLU prediction record was created.
Utterance
User statement recognized by the bot, which maps to an intent defined in an
NLU model.
Request
NLU prediction parameter that contains the utterance and NLU model for the
recognized intent.
Response
NLU prediction results, which contain 0 (none) or more scored intents and
scored entities.
Duration
Length of processing time for the prediction to return intent and entity
values.
Level
Type of message: Information level
Message
Prediction results returned: Number of intents and entities.
Source
Process or area: OpenNLU - Predict.
Async
Indicator for asynchronous prediction processing: True or false. True
indicates that the prediction was performed asynchronously, allowing Virtual Agent worker
threads to continue.
