The interaction id. It uniquely identifies the interaction and can be used to retrieve further information.
The input text written by the user.
The response generated by the assistant.
A detailed version of the user intent in a single sentence.
The end user interacting with the LLM.
The conversation id. It uniquely identifies the conversation the interaction belongs to.
This information can be sent via API in order to group interactions, otherwise it will be generated automatically by Nebuly.
The date when the user input was received by the LLM.
The date when the assistant response was sent back to the user.
Description of any warnings or issues detected with the LLM response.
negative_intent_message_v2
If present, it indicates that the user is having a negative experience withing the conversation.
Cost of the interaction, in microdollars.
Time elapsed between the user input and the assistant response, in seconds.
Language detected in the user input.
Number of characters in the output.
Indicates whether PII was removed from the interaction.
Text content accompanying feedback actions, if any.
Numerical rating provided as feedback (e.g., 1–5).
Actions taken or suggested via user feedback (e.g., “thumbs_up”, “thumbs_down”).
Sentiment classification of the interaction, if available (e.g., positive, neutral, negative).
List of detected emotions from the user input.
Key-value pairs showing custom tags associated with the interaction.
Key-value pairs showing custom columns associated with the interaction defined inside the platform.
Key-value pairs of manually defined aggregates associated with the interaction defined inside the platform.
Detailed metadata about each RAG item (e.g., source, query, result).