Appendices
There are 25 other available tables in eva, from API Key to Utterances
Last updated
There are 25 other available tables in eva, from API Key to Utterances
Last updated
The apikey table stores API keys used to validate eva’s service calls.
The automatization_test stores general information about automated tests. To execute an automated test, the user must fill a spreadsheet and insert it in the cockpit.
The automatization_test_description Stores data that was inserted in the automated test spreadsheet and are stored as an execution result.
The bot_nlp_engine table is a N-N relationship table between virtual agent and nlp_engine.
The configuration tables stores eva’s configuration keys.
The entity table stores configurations for entities created in the virtual agent. An example would be the entity “sport”.
To learn how to use Entity in eva
The entity_value table stores the entity content. So, in the entity “sport”, the values would be “football”, “basketball” or “tennis”.
The entity_sample table stores words that has a similar meaning to the entity value. For example, if the entity value is “football”, it could store “soccer” or “association football”.
The facebook_configuration stores the chat configuration in a Facebook page.
The facebook_user table stores the data of the facebook user who interacted with the virtual agent.
The intents table stores the configuration of intents created in the virtual agent.
To learn more how to use Intents in eva
The nlp_engine stores NLP integration data.
The nlp_token table stores the tokens generated by Dialogflow.
The permission table stores permissions that can be given to a user.
The role table stores the functions that can be given to a user.
The role_permission stores role and permission data, allowing to identify each user role and permission.
The sequelizemeta table stores the configuration history.
The tag_type table stores the repository types: intent, entity, answer, flow, prototype and service.
The tag_uses table stores tag data and which repository it is related to, allowing to identify the tag, repository type and which repository ID the tag is related to.
The tags table stores the tags created in the virtual agent. The tags helps to identify objects.
The training table stores virtual agent training data. When a user trains a virtual agent in the cockpit, the data is stored in this tablea.
The transactional_service table stores the transactional calls performed during a session. Is possible to identify which service was called and the answer content by the webhook.
The user table stores the cockpit users created in the keycloak, which is an access control tool responsible for eva’s user authentication.
The user_bot_role table stores user identification, virtual agent and role data.
The utterances table stores intent examples. When a user creates an intent in the virtual agent, he must add sentences that can appear in a conversation with the virtual agent.