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package meilisearch
type (
TaskType string // TaskType is the type of a task
SortFacetType string // SortFacetType is type of facet sorting, alpha or count
TaskStatus string // TaskStatus is the status of a task.
ProximityPrecisionType string // ProximityPrecisionType accepts one of the ByWord or ByAttribute
MatchingStrategy string // MatchingStrategy one of the Last, All, Frequency
)
const (
// Last returns documents containing all the query terms first. If there are not enough results containing all
// query terms to meet the requested limit, Meilisearch will remove one query term at a time,
// starting from the end of the query.
Last MatchingStrategy = "last"
// All only returns documents that contain all query terms. Meilisearch will not match any more documents even
// if there aren't enough to meet the requested limit.
All MatchingStrategy = "all"
// Frequency returns documents containing all the query terms first. If there are not enough results containing
//all query terms to meet the requested limit, Meilisearch will remove one query term at a time, starting
//with the word that is the most frequent in the dataset. frequency effectively gives more weight to terms
//that appear less frequently in a set of results.
Frequency MatchingStrategy = "frequency"
)
const (
// ByWord calculate the precise distance between query terms. Higher precision, but may lead to longer
// indexing time. This is the default setting
ByWord ProximityPrecisionType = "byWord"
// ByAttribute determine if multiple query terms are present in the same attribute.
// Lower precision, but shorter indexing time
ByAttribute ProximityPrecisionType = "byAttribute"
)
const (
// TaskStatusUnknown is the default TaskStatus, should not exist
TaskStatusUnknown TaskStatus = "unknown"
// TaskStatusEnqueued the task request has been received and will be processed soon
TaskStatusEnqueued TaskStatus = "enqueued"
// TaskStatusProcessing the task is being processed
TaskStatusProcessing TaskStatus = "processing"
// TaskStatusSucceeded the task has been successfully processed
TaskStatusSucceeded TaskStatus = "succeeded"
// TaskStatusFailed a failure occurred when processing the task, no changes were made to the database
TaskStatusFailed TaskStatus = "failed"
// TaskStatusCanceled the task was canceled
TaskStatusCanceled TaskStatus = "canceled"
)
const (
SortFacetTypeAlpha SortFacetType = "alpha"
SortFacetTypeCount SortFacetType = "count"
)
const (
// TaskTypeIndexCreation represents an index creation
TaskTypeIndexCreation TaskType = "indexCreation"
// TaskTypeIndexUpdate represents an index update
TaskTypeIndexUpdate TaskType = "indexUpdate"
// TaskTypeIndexDeletion represents an index deletion
TaskTypeIndexDeletion TaskType = "indexDeletion"
// TaskTypeIndexSwap represents an index swap
TaskTypeIndexSwap TaskType = "indexSwap"
// TaskTypeDocumentAdditionOrUpdate represents a document addition or update in an index
TaskTypeDocumentAdditionOrUpdate TaskType = "documentAdditionOrUpdate"
// TaskTypeDocumentDeletion represents a document deletion from an index
TaskTypeDocumentDeletion TaskType = "documentDeletion"
// TaskTypeSettingsUpdate represents a settings update
TaskTypeSettingsUpdate TaskType = "settingsUpdate"
// TaskTypeDumpCreation represents a dump creation
TaskTypeDumpCreation TaskType = "dumpCreation"
// TaskTypeTaskCancelation represents a task cancelation
TaskTypeTaskCancelation TaskType = "taskCancelation"
// TaskTypeTaskDeletion represents a task deletion
TaskTypeTaskDeletion TaskType = "taskDeletion"
// TaskTypeSnapshotCreation represents a snapshot creation
TaskTypeSnapshotCreation TaskType = "snapshotCreation"
// TaskTypeExport represents a task exportation
TaskTypeExport TaskType = "export"
)
type (
ContentEncoding string
EncodingCompressionLevel int
)
const (
GzipEncoding ContentEncoding = "gzip"
DeflateEncoding ContentEncoding = "deflate"
BrotliEncoding ContentEncoding = "br"
NoCompression EncodingCompressionLevel = 0
BestSpeed EncodingCompressionLevel = 1
BestCompression EncodingCompressionLevel = 9
DefaultCompression EncodingCompressionLevel = -1
HuffmanOnlyCompression EncodingCompressionLevel = -2
ConstantCompression EncodingCompressionLevel = -2
StatelessCompression EncodingCompressionLevel = -3
)
func (c ContentEncoding) String() string { return string(c) }
func (c ContentEncoding) IsZero() bool { return c == "" }
func (c EncodingCompressionLevel) Int() int { return int(c) }
// EmbedderSource The source corresponds to a service that generates embeddings from your documents.
type EmbedderSource string
const (
OpenaiEmbedderSource EmbedderSource = "openAi"
HuggingFaceEmbedderSource EmbedderSource = "huggingFace"
// RestEmbedderSource rest is a generic source compatible with any embeddings provider offering a REST API.
RestEmbedderSource EmbedderSource = "rest"
OllamaEmbedderSource EmbedderSource = "ollama"
// UserProvidedEmbedderSource Use userProvided when you want to generate embeddings manually. In this case,
// you must include vector data in your documents’ _vectors field. You must also generate
//vectors for search queries.
UserProvidedEmbedderSource EmbedderSource = "userProvided"
// CompositeEmbedderSource Choose composite to use one embedder during indexing time, and another embedder at search time.
//Must be used together with indexingEmbedder and searchEmbedder.
CompositeEmbedderSource EmbedderSource = "composite"
)
// ChatSource The source corresponds to a service that generates chat completions from your messages.
type ChatSource string
const (
OpenaiChatSource ChatSource = "openAi"
AzureOpenAiChatSource ChatSource = "azureOpenAi"
MistralChatSource ChatSource = "mistral"
GeminiChatSource ChatSource = "gemini"
VLlmChatSource ChatSource = "vLlm"
)
// EmbedderPooling Configure how Meilisearch should merge individual tokens into a single embedding.
//
// pooling is optional for embedders with the huggingFace source.
type EmbedderPooling string
const (
// UseModelEmbedderPooling Meilisearch will fetch the pooling method from the model configuration. Default value for new embedders
UseModelEmbedderPooling EmbedderPooling = "useModel"
// ForceMeanEmbedderPooling always use mean pooling. Default value for embedders created in Meilisearch <=v1.13
ForceMeanEmbedderPooling EmbedderPooling = "forceMean"
// ForceClsEmbedderPooling always use CLS pooling
ForceClsEmbedderPooling EmbedderPooling = "forceCls"
)
// ChatRole The role of a message in a chat conversation.
type ChatRole string
const (
ChatRoleUser ChatRole = "user"
ChatRoleAssistant ChatRole = "assistant"
ChatRoleSystem ChatRole = "system"
)
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