user-facing : Agent directly interacts with users conversationally in a Q&A fashion. Only a single user-facing Agent engages with the user when a new query is input into the chatbot.
background : Agent never interacts with users directly and instead monitors the conversation in an ongoing fashion. All background Agents are run whenever the user submits a new query to the chatbot.
human-escalation : Agent routes the user’s query to a human. Only one human-escalation agent is allowed in each chatbot. It requires GPT-trainer UI to fully use this feature.
pre-canned : Agent returns pre-canned response to user’s query
spam-defense : Agent enables the spam defending feature for the chatbot. Only one spam-defnese agent is allowed in each chatbot
List of data sources UUIDs that the agent uses. If use_all_sources in agent’s meta is set to true, this field will be disabled.
Only for user-facing agents.
A higher temperature value, such as 1, allows for more randomness and
creativity in the responses. This can lead to more diverse and unexpected
answers. On the other hand, a lower temperature value, closer to 0, produces
more focused and deterministic responses, making them more conservative and
predictable. Options are values as a float between 0 and
1
Only for user-facing agents.
How AI supervisor should be biased towards the agent. A higher value will make the AI supervisor more biased towards the agent. Options are values as a float between 0 and 1.
Only for user-facing, human-escalation, pre-canned and spam-defense agents.
How sticky the AI supervisor should be stick with the agent when the lastest user’s query is handled by this agent. Options are values as a float between 0 and 1.
Only for user-facing, human-escalation, pre-canned and spam-defense agents.