Text output

5 Situations:

• "system_question" attribute of "#single_turn_interact#" node: it can only be a declarative description and must ask question,
• "#inform_user#" node's "inform_content" attribute: it can only be a declarative description and cannot ask questions
• "inform_user_before_asking" attribute of the "#single_turn_interact#" node: it can only be a declarative description and cannot ask question
• The "response" part of the "response_scripts" attribute of the "#start#" node: it can only be a declarative description and cannot ask question
• The "fixed_closing_remarks" attribute of the "#start#" node: it can only be a declarative description and cannot ask question (and it cannot have the following "Prompt Word" expression form) In these 5 cases, there must be no description of the actual execution of the action (actions that need to be actually executed must be solved with the "#activity#..." node, and sometimes the "#trigger#" mechanism is also needed), and there should be no duplicate content (similar meanings here are also considered duplicates)

2 Expression Forms:

• Direct Output to the user (different from the "Prompt Word" expression form below, here cannot require LLM to actually perform an action), such as:

  • "What do you need?"
  • "Please wait"
  • "You are so rich!"
  • "You had a lot of worries before, but don't worry."
  • "Don't worry, we still need to learn more about the situation before we can give you specific suggestions."

• A descriptive statement used to generate output content (i.e. Prompt Word). At this time, it needs to be enclosed by a pair of greater than and less signs. It is a subject-less statement starting with a verb (generally requiring LLM to perform an action related to content output), such as:

  • "<Ask users what they need>"
  • "<Please ask the user to wait a moment.>"
  • "<Sigh that the user is very rich>"
  • "<Summarize previous users' concerns and use relevant reasons to convince users not to worry>"
  • "<First comfort the user, and then express that we need to know more about the situation before we can give specific suggestions>"

  In this "Prompt Word" expression form: use the "you" or the "system_role" of "#start#" node to refer to the AI ​​robot in the dialogue, and use the "user" or "user_role" of the "#start#" node to refer to the other party (i.e. the user) in the dialogue; use other pronouns that can easily cause confusion with caution

  At the same time, please note that the above "fixed_closing_remarks" attribute cannot have the expression form of "Prompt Word"

Replacement of Text Output Content

• The above 5 situations (2 expression forms): If there is a string like "...{...}..." in the content, the system will replace the "{...}" with the string value of the corresponding InfoItem before outputting it.
• The above 5 situations (2 expression forms): For Python ChatTree, if there is "|" in the content, it will be replaced with "/"; Xmind ChatTree will not

Polling Output of Text Content

The above 5 situations (2 expression forms):

• For Xmind ChatTree, text can be separated into several parts by "|" (each part can be in either of the above 2 expression forms), such as "...|<...>|...". Each time the system executes to the relevant node, it will sequentially extract a part of it and output it, so as to achieve the effect of non-repetitive output content during repeated executions.
• Python ChatTrees can use a list to contain multiple output contents (each part can be in any of the 2 expression forms mentioned above), such as ["...","<...>","..."]. Each time the system executes to the relevant node, it will sequentially extract an element of the list for output, so as to achieve the effect of non-repetitive output content during repeated executions.

Content Requirements

• As "system_question" of "#single_turn_interact#" node, you need to pay attention to the completeness of the description of the scene in the question content. For example, "How many kilometers does it run in a year?" can be optimized to "How many kilometers does the vehicle run in a year?"
• Do not use modal particles at the beginning of sentences such as "um", "oh", "ok" etc
• If there is a string of letters and/or numbers, it is best to enclose it in square brackets or single quotes to ensure the correct TTS effect