ImportIntents

Imports intents into a workspace.

Path Parameters
namespace string — REQUIRED Namespace of the workspace.
playbook_id string — REQUIRED Unique identifier of the workspace.

Request body — REQUIRED
namespace string Namespace of the workspace.
playbook_id string Unique identifier of the workspace.
format enum Format of the imported file. Values: 1 = CSV 2 = Rasa 1 Markdown 3 = Rasa 2 YAML 4 = Botpress 6 = Dialogflow ES 7 = Humanfirst JSON
format_options IntentsDataOptions hierarchical_intent_name_disabled boolean Disables intents hierarchy encoding via the intent names. Ex: 'Parent / Sub-parent / Intent' hierarchical_delimiter string Overrides the default delimiter used for intent hierarchy. Default is '--' for Botpress and Dialogflow, '+' for Rasa, '/' for CSV zip_encoding boolean Indicates that the intents are zipped and may be splits in different files. gzip_encoding boolean Indicates that the intent file is gzipped. hierarchical_follow_up boolean To be used with Dialogflow to use intents hierarchy using intents follow-up. include_negative_phrases boolean Export negative phrases as well. intent_tag_predicate TagPredicate require_ids string[] Only include objects with ALL of the given tag ids. include_ids string[] Only include objects with ANY of the given tag ids. exclude_ids string[] Exclude objects with ANY of the given tag ids. phrase_tag_predicate TagPredicate require_ids string[] Only include objects with ALL of the given tag ids. include_ids string[] Only include objects with ANY of the given tag ids. exclude_ids string[] Exclude objects with ANY of the given tag ids. skip_empty_intents boolean Skip all intents that do not contain phrases.
import_options ImportOptions clear_intents boolean Clears workspace intents before importing. clear_entities boolean Clears workspace entities before importing. clear_tags boolean Clears workspace tags before importing. Note: should not be used in combination with extra_intent_tags or extra_phrase_tags since we will clear potentially referenced tags. merge_intents boolean Tries to merge intents into existing ones if they can be found in the workspace. merge_entities boolean Tries to merge entities into existing ones if they can be found in the workspace. merge_tags boolean Tries to merge tags into existing ones if they can be found in the workspace. extra_intent_tags TagReference[] Add extra tags to imported intents. id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled. extra_phrase_tags TagReference[] Add extra tags to imported phrases. id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled. override_metadata boolean Overrides the description, color, and metadata of the workspace with the values of the imported file if they are supported in the received format. Supported formats: INTENTS_FORMAT_HF_JSON override_name boolean Overrides the name of the workspace with the value of the imported file if they are supported in the received format. Supported formats: INTENTS_FORMAT_HF_JSON
data bytes Bytes of the file to import. The format is the one requested through the format field in request.
clear_workspace boolean Clears workspace intents, entities & tags before importing. Deprecated: use import_options
clear_intents boolean Clears workspace intents before importing. Deprecated: use import_options
clear_entities boolean Clears workspace entities before importing. Deprecated: use import_options
clear_tags boolean Clears workspace tags before importing. Note: should not be used in combination with extra_intent_tags or extra_phrase_tags since we will clear potentially referenced tags. Deprecated: use import_options
merge_intents boolean Tries to merge intents into existing ones if they can be found in the workspace. Deprecated: use import_options
merge_entities boolean Tries to merge entities into existing ones if they can be found in the workspace. Deprecated: use import_options
merge_tags boolean Tries to merge tags into existing ones if they can be found in the workspace. Deprecated: use import_options
soft_fail boolean Returns fatal problems via the problems field instead of gRPC errors. Temporary flag until front-end properly handles soft failures instead of gRPC error.
extra_intent_tags TagReference[] Add extra tags to imported intents. Deprecated: use import_options id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled.
extra_phrase_tags TagReference[] Add extra tags to imported phrases. Deprecated: use import_options id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled.

Response Body
imported_intent_count uint32 Number of intents that were imported.
imported_training_phrase_count uint32 Number of training phrases that were imported.
problems ValidationProblem[] List of problems that occurred while validating the file format. This list may not be exhaustive. If it's been limited, the total_problems indicate the total count. level enum Level of the problem. 1 = Warning 2 = Fatal message string Message of the problem. filename string (Optional) Filename in which the problem was encountered. line uint32 (Optional) Line of filename on which the problem was encountered. training_phrase TrainingPhrase id string Unique identifier translated_from_id string If this training phrase is a translation of an original training phrase, ID of the TrainingPhrase from which this training phrase was translated from. text string Verbatim text. In case of a fragment, copies the first user input processed boolean Whether this fragment has been been seen in the bottom-up response creation flow constituents string[] The divided sentences/constituents order to support multi-part. locations PhraseLocation[] Editing a training phrase appends new locations. conversation_id string The conversation / context which contains the given spans input_id string The normalized input / example id from the pipeline conversation_type uint32 Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType spans SpanIndex[] The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. fragment Fragment items FragmentItem[] Array of inputs/placeholders found in this fragment input Input text string The verbatim input text source enum Whether the input comes from an expert or user input_id string The normalized input / example id from the pipeline created_at RFC3339 The absolute timestamp when the input was uttered placeholder Placeholder tag_id string The tag identifier representing the type of agent response that would be created at this location. See zia.ai.Playbook.Tag.id location PhraseLocation conversation_id string The conversation / context which contains the given spans input_id string The normalized input / example id from the pipeline conversation_type uint32 Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType spans SpanIndex[] The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. metadata TrainingPhraseMetadata metadata MetadataEntry key string value string entities InputEntity[] Entities referenced in the training phrase text. If the parts field is provided on creation or update, this field is ignored and rebuilt from parts. reference EntityReference Sync from zia.ai.playbook.EntityReference entity_id string Unique identifier of the entity for database storage. key string Key by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key text string Text used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. value string If the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) value_id string Unique identifier of the entity value for database storage. role string If entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. span SpanIndex start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. parts InputPart[] If the training phrase contains entities, this field contains the parts of the text and the entities. The parts are concatenated to form the final text. Parts are provided to ease entity annotations. If provided at creation or update, this will override the entities field. text Text text string entity EntityMatch entity EntityReference Sync from zia.ai.playbook.EntityReference entity_id string Unique identifier of the entity for database storage. key string Key by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key text string Text used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. value string If the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) value_id string Unique identifier of the entity value for database storage. role string If entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. score float The confidence score for this match span Span start uint32 The start of this entity, as the utf8 byte index end uint32 The end of this entity, as the utf8 byte index extractor string (Rasa specific) Name of the pipeline component that found this entity tags TagReference[] Tags of the phrase. id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled. source enum Source of the training phrase source_info TrainingPhraseSourceInfo source_id string ID of the training phrase at its source (if applicable) merged_ids string[] List of unique identifiers of phrase from HumanFirst or external integrations that got merged into this phrase at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. botpress Botpress rasa Rasa metadata MetadataEntry key string value string dialogflow Dialogflow repeat_count int32 For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. created_at RFC3339 Date at which first the training phrase insert was done in database (generated by server) updated_at RFC3339 Date at which last update to training phrase was done in database (generated by server) deleted_at RFC3339 If present, the date at which the training phrase was deleted from the database (generated by server) language string Language of the training phrase. If empty, 'en' is assumed. 2 letters ISO 639-1 or BCP47 locale format (ex: 'en-US'). training_phrase_list string If training phrase is stored in a database, list in which this phrase is. hash string Hash of the normalized text of the phrase, used to join embeddings data. negative boolean If the training phrase is associated to an intent, this indicates that it's a negative phrase edited boolean Whether this phrase's text prop has been modified from its original version starred boolean intent Intent Intents define a component that match on some external input or condition. It's purpose is to activate it's outbound contexts whenever the condition is met id string UUID name string User-given name type enum Expert/User/Meta parent_id string The intent's parent intent, within the same context template_intent TemplateIntentInfo template_id string Template from which this intent was imported template_name string template_intent_id string intent id within the template parent_names string[] List of parents, from top to bottom template_intent_name string Original intent name, in the template inbound_contexts Context[] Contexts which have to be active in order for this intent to match id string UUID type enum The type of intents contained by this context position uint32 The position occupied by the intent in the current context. (only populated when fetching intents) created_at RFC3339 outbound_contexts Context[] Contexts to activate if this intent is matched id string UUID type enum The type of intents contained by this context position uint32 The position occupied by the intent in the current context. (only populated when fetching intents) created_at RFC3339 training_phrases TrainingPhrase[] Positive training phrases of the intent id string Unique identifier translated_from_id string If this training phrase is a translation of an original training phrase, ID of the TrainingPhrase from which this training phrase was translated from. text string Verbatim text. In case of a fragment, copies the first user input processed boolean Whether this fragment has been been seen in the bottom-up response creation flow constituents string[] The divided sentences/constituents order to support multi-part. locations PhraseLocation[] Editing a training phrase appends new locations. conversation_id string The conversation / context which contains the given spans input_id string The normalized input / example id from the pipeline conversation_type uint32 Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType spans SpanIndex[] The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. fragment Fragment items FragmentItem[] Array of inputs/placeholders found in this fragment input Input text string The verbatim input text source enum Whether the input comes from an expert or user input_id string The normalized input / example id from the pipeline created_at RFC3339 The absolute timestamp when the input was uttered placeholder Placeholder tag_id string The tag identifier representing the type of agent response that would be created at this location. See zia.ai.Playbook.Tag.id location PhraseLocation conversation_id string The conversation / context which contains the given spans input_id string The normalized input / example id from the pipeline conversation_type uint32 Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType spans SpanIndex[] The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. metadata TrainingPhraseMetadata metadata MetadataEntry key string value string entities InputEntity[] Entities referenced in the training phrase text. If the parts field is provided on creation or update, this field is ignored and rebuilt from parts. reference EntityReference Sync from zia.ai.playbook.EntityReference entity_id string Unique identifier of the entity for database storage. key string Key by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key text string Text used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. value string If the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) value_id string Unique identifier of the entity value for database storage. role string If entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. span SpanIndex start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. parts InputPart[] If the training phrase contains entities, this field contains the parts of the text and the entities. The parts are concatenated to form the final text. Parts are provided to ease entity annotations. If provided at creation or update, this will override the entities field. text Text text string entity EntityMatch entity EntityReference Sync from zia.ai.playbook.EntityReference entity_id string Unique identifier of the entity for database storage. key string Key by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key text string Text used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. value string If the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) value_id string Unique identifier of the entity value for database storage. role string If entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. score float The confidence score for this match span Span start uint32 The start of this entity, as the utf8 byte index end uint32 The end of this entity, as the utf8 byte index extractor string (Rasa specific) Name of the pipeline component that found this entity tags TagReference[] Tags of the phrase. id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled. source enum Source of the training phrase source_info TrainingPhraseSourceInfo source_id string ID of the training phrase at its source (if applicable) merged_ids string[] List of unique identifiers of phrase from HumanFirst or external integrations that got merged into this phrase at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. botpress Botpress rasa Rasa metadata MetadataEntry key string value string dialogflow Dialogflow repeat_count int32 For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. created_at RFC3339 Date at which first the training phrase insert was done in database (generated by server) updated_at RFC3339 Date at which last update to training phrase was done in database (generated by server) deleted_at RFC3339 If present, the date at which the training phrase was deleted from the database (generated by server) language string Language of the training phrase. If empty, 'en' is assumed. 2 letters ISO 639-1 or BCP47 locale format (ex: 'en-US'). training_phrase_list string If training phrase is stored in a database, list in which this phrase is. hash string Hash of the normalized text of the phrase, used to join embeddings data. negative boolean If the training phrase is associated to an intent, this indicates that it's a negative phrase edited boolean Whether this phrase's text prop has been modified from its original version starred boolean negative_training_phrases TrainingPhrase[] Negative training phrases of the intent id string Unique identifier translated_from_id string If this training phrase is a translation of an original training phrase, ID of the TrainingPhrase from which this training phrase was translated from. text string Verbatim text. In case of a fragment, copies the first user input processed boolean Whether this fragment has been been seen in the bottom-up response creation flow constituents string[] The divided sentences/constituents order to support multi-part. locations PhraseLocation[] Editing a training phrase appends new locations. conversation_id string The conversation / context which contains the given spans input_id string The normalized input / example id from the pipeline conversation_type uint32 Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType spans SpanIndex[] The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. fragment Fragment items FragmentItem[] Array of inputs/placeholders found in this fragment input Input text string The verbatim input text source enum Whether the input comes from an expert or user input_id string The normalized input / example id from the pipeline created_at RFC3339 The absolute timestamp when the input was uttered placeholder Placeholder tag_id string The tag identifier representing the type of agent response that would be created at this location. See zia.ai.Playbook.Tag.id location PhraseLocation conversation_id string The conversation / context which contains the given spans input_id string The normalized input / example id from the pipeline conversation_type uint32 Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType spans SpanIndex[] The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. metadata TrainingPhraseMetadata metadata MetadataEntry key string value string entities InputEntity[] Entities referenced in the training phrase text. If the parts field is provided on creation or update, this field is ignored and rebuilt from parts. reference EntityReference Sync from zia.ai.playbook.EntityReference entity_id string Unique identifier of the entity for database storage. key string Key by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key text string Text used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. value string If the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) value_id string Unique identifier of the entity value for database storage. role string If entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. span SpanIndex start SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. end SpanPosition input_index uint32 The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 character_index uint32 The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. parts InputPart[] If the training phrase contains entities, this field contains the parts of the text and the entities. The parts are concatenated to form the final text. Parts are provided to ease entity annotations. If provided at creation or update, this will override the entities field. text Text text string entity EntityMatch entity EntityReference Sync from zia.ai.playbook.EntityReference entity_id string Unique identifier of the entity for database storage. key string Key by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key text string Text used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. value string If the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) value_id string Unique identifier of the entity value for database storage. role string If entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. score float The confidence score for this match span Span start uint32 The start of this entity, as the utf8 byte index end uint32 The end of this entity, as the utf8 byte index extractor string (Rasa specific) Name of the pipeline component that found this entity tags TagReference[] Tags of the phrase. id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled. source enum Source of the training phrase source_info TrainingPhraseSourceInfo source_id string ID of the training phrase at its source (if applicable) merged_ids string[] List of unique identifiers of phrase from HumanFirst or external integrations that got merged into this phrase at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. botpress Botpress rasa Rasa metadata MetadataEntry key string value string dialogflow Dialogflow repeat_count int32 For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. created_at RFC3339 Date at which first the training phrase insert was done in database (generated by server) updated_at RFC3339 Date at which last update to training phrase was done in database (generated by server) deleted_at RFC3339 If present, the date at which the training phrase was deleted from the database (generated by server) language string Language of the training phrase. If empty, 'en' is assumed. 2 letters ISO 639-1 or BCP47 locale format (ex: 'en-US'). training_phrase_list string If training phrase is stored in a database, list in which this phrase is. hash string Hash of the normalized text of the phrase, used to join embeddings data. negative boolean If the training phrase is associated to an intent, this indicates that it's a negative phrase edited boolean Whether this phrase's text prop has been modified from its original version starred boolean training_phrase_list_id string If the intent is from database, list identifier of training phrases negative_training_phrase_list_id string If the intent is from database, list identifier of negative training phrases hidden_from_agents boolean If true, the intent will not be visible to agents from the extension (defaults to false) tags TagReference[] Tags of the intent. id string Unique identifier of the tag. name string (Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. protected boolean For internal use. There is no guarantee that this will be properly filled. color string hidden_from_follow_up_suggestions boolean If true, this intent or its children won't be available within Answer's follow-up suggestions follow_up_after_turn_count UInt32Value Wrapper message for uint32. The JSON representation for UInt32Value is JSON number. value uint32 The uint32 value. follow_up_allow_repeat_after_turn_count UInt32Value Wrapper message for uint32. The JSON representation for UInt32Value is JSON number. value uint32 The uint32 value. follow_up_implies_parent boolean hidden_from_automate_matches boolean If true, it will be considered by the classifier, but will never be returned as a match to a client generic boolean Generic intents are only used for its hierarchy, and are not expected to hold any responses source IntentSourceInfo source_id string ID of the intent at its source. merged_ids string[] List of unique identifiers of intents from HumanFirst or external integrations that got merged into this intent at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. botpress Botpress rasa Rasa metadata MetadataEntry key string value string dialogflow Dialogflow repeat_count int32 For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. cognigy Cognigy rules string[] see etl/cognigy/objects.go confirmation_sentences string[] condition string disambiguationSentence string child_features boolean entry_point string is_reject_intent boolean is_disabled boolean override_intent_default_replies_as_examples string out_of_scope boolean If true, this intent will be used as a negative class when classifying if examples are in scope or not metadata IntentMetadata metadata MetadataEntry key string value string description string Description of the intent. created_at RFC3339 updated_at RFC3339 deleted_at RFC3339
total_problems uint32 Indicates total number of problems at import.
background_operation Operation namespace string Namespace in which the operation was launched. id string Unique identifier of the operation. done boolean Indicates that the operation has completed. If error is set, the operation has failed. Otherwise, the operation has succeeded and result may be set if the operation has a response. error Error code uint32 message string response Any Any contains an arbitrary serialized protocol buffer message along with a URL that describes the type of the serialized message. Protobuf library provides support to pack/unpack Any values in the form of utility functions or additional generated methods of the Any type. Example 1: Pack and unpack a message in C++. Foo foo = ...; Any any; any.PackFrom(foo); ... if (any.UnpackTo(&foo)) { ... } Example 2: Pack and unpack a message in Java. Foo foo = ...; Any any = Any.pack(foo); ... if (any.is(Foo.class)) { foo = any.unpack(Foo.class); } // or ... if (any.isSameTypeAs(Foo.getDefaultInstance())) { foo = any.unpack(Foo.getDefaultInstance()); } Example 3: Pack and unpack a message in Python. foo = Foo(...) any = Any() any.Pack(foo) ... if any.Is(Foo.DESCRIPTOR): any.Unpack(foo) ... Example 4: Pack and unpack a message in Go foo := &pb.Foo{...} any, err := anypb.New(foo) if err != nil { ... } ... foo := &pb.Foo{} if err := any.UnmarshalTo(foo); err != nil { ... } The pack methods provided by protobuf library will by default use 'type.googleapis.com/full.type.name' as the type URL and the unpack methods only use the fully qualified type name after the last '/' in the type URL, for example "foo.bar.com/x/y.z" will yield type name "y.z". JSON ==== The JSON representation of an Any value uses the regular representation of the deserialized, embedded message, with an additional field @type which contains the type URL. Example: package google.profile; message Person { string first_name = 1; string last_name = 2; } { "@type": "type.googleapis.com/google.profile.Person", "firstName": , "lastName": } If the embedded message type is well-known and has a custom JSON representation, that representation will be embedded adding a field value which holds the custom JSON in addition to the @type field. Example (for message google.protobuf.Duration): { "@type": "type.googleapis.com/google.protobuf.Duration", "value": "1.212s" } type_url string A URL/resource name that uniquely identifies the type of the serialized protocol buffer message. This string must contain at least one "/" character. The last segment of the URL's path must represent the fully qualified name of the type (as in path/google.protobuf.Duration). The name should be in a canonical form (e.g., leading "." is not accepted). In practice, teams usually precompile into the binary all types that they expect it to use in the context of Any. However, for URLs which use the scheme http, https, or no scheme, one can optionally set up a type server that maps type URLs to message definitions as follows: If no scheme is provided, https is assumed. An HTTP GET on the URL must yield a google.protobuf.Type value in binary format, or produce an error. * Applications are allowed to cache lookup results based on the URL, or have them precompiled into a binary to avoid any lookup. Therefore, binary compatibility needs to be preserved on changes to types. (Use versioned type names to manage breaking changes.) Note: this functionality is not currently available in the official protobuf release, and it is not used for type URLs beginning with type.googleapis.com. Schemes other than http, https (or the empty scheme) might be used with implementation specific semantics. value bytes Must be a valid serialized protocol buffer of the above specified type.