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- [database]
- # The database for caching, support Redis, MySQL, Postgres and MongoDB:
- # redis://<user>:<password>@<host>:<port>/<db_number>
- # rediss://<user>:<password>@<host>:<port>/<db_number>
- # postgres://bob:secret@1.2.3.4:5432/mydb?sslmode=verify-full
- # postgresql://bob:secret@1.2.3.4:5432/mydb?sslmode=verify-full
- # mongodb://[username:password@]host1[:port1][,...hostN[:portN]][/[defaultauthdb][?options]]
- # mongodb+srv://[username:password@]host1[:port1][,...hostN[:portN]][/[defaultauthdb][?options]]
- cache_store = "redis://localhost:6379/0"
- # The database for persist data, support MySQL, Postgres and MongoDB:
- # mysql://[username[:password]@][protocol[(address)]]/dbname[?param1=value1&...¶mN=valueN]
- # postgres://bob:secret@1.2.3.4:5432/mydb?sslmode=verify-full
- # postgresql://bob:secret@1.2.3.4:5432/mydb?sslmode=verify-full
- # mongodb://[username:password@]host1[:port1][,...hostN[:portN]][/[defaultauthdb][?options]]
- # mongodb+srv://[username:password@]host1[:port1][,...hostN[:portN]][/[defaultauthdb][?options]]
- data_store = "mysql://gorse:gorse_pass@tcp(localhost:3306)/gorse"
- # The naming prefix for tables (collections, keys) in databases. The default value is empty.
- table_prefix = ""
- # The naming prefix for tables (collections, keys) in cache storage databases. The default value is `table_prefix`.
- cache_table_prefix = ""
- # The naming prefix for tables (collections, keys) in data storage databases. The default value is `table_prefix`.
- data_table_prefix = ""
- [master]
- # GRPC port of the master node. The default value is 8086.
- port = 8086
- # gRPC host of the master node. The default values is "0.0.0.0".
- host = "0.0.0.0"
- # HTTP port of the master node. The default values is 8088.
- http_port = 8088
- # HTTP host of the master node. The default values is "0.0.0.0".
- http_host = "0.0.0.0"
- # AllowedDomains is a list of allowed values for Http Origin.
- # The list may contain the special wildcard string ".*" ; all is allowed
- # If empty all are allowed.
- http_cors_domains = []
- # AllowedMethods is either empty or has a list of http methods names. Checking is case-insensitive.
- http_cors_methods = []
- # Number of working jobs in the master node. The default value is 1.
- n_jobs = 1
- # Meta information timeout. The default value is 10s.
- meta_timeout = "10s"
- # Username for the master node dashboard.
- dashboard_user_name = ""
- # Password for the master node dashboard.
- dashboard_password = ""
- # Secret key for admin APIs (SSL required).
- admin_api_key = ""
- [server]
- # Default number of returned items. The default value is 10.
- default_n = 10
- # Secret key for RESTful APIs (SSL required).
- api_key = ""
- # Clock error in the cluster. The default value is 5s.
- clock_error = "5s"
- # Insert new users while inserting feedback. The default value is true.
- auto_insert_user = true
- # Insert new items while inserting feedback. The default value is true.
- auto_insert_item = true
- # Server-side cache expire time. The default value is 10s.
- cache_expire = "10s"
- [recommend]
- # The cache size for recommended/popular/latest items. The default value is 10.
- cache_size = 100
- # Recommended cache expire time. The default value is 72h.
- cache_expire = "72h"
- # The time-to-live (days) of active users, 0 means disabled. Recommendation won't be cached for inactive users. The default value is 0.
- active_user_ttl = 0
- [recommend.data_source]
- # The feedback types for positive events.
- positive_feedback_types = ["star","like"]
- # The feedback types for read events.
- read_feedback_types = ["read"]
- # The time-to-live (days) of positive feedback, 0 means disabled. The default value is 0.
- positive_feedback_ttl = 0
- # The time-to-live (days) of items, 0 means disabled. The default value is 0.
- item_ttl = 0
- [recommend.popular]
- # The time window of popular items. The default values is 4320h.
- popular_window = "720h"
- [recommend.user_neighbors]
- # The type of neighbors for users. There are three types:
- # similar: Neighbors are found by number of common labels.
- # related: Neighbors are found by number of common liked items.
- # auto: If a user have labels, neighbors are found by number of common labels.
- # If this user have no labels, neighbors are found by number of common liked items.
- # The default value is "auto".
- neighbor_type = "similar"
- # Enable approximate user neighbor searching using vector index. The default value is true.
- enable_index = true
- # Minimal recall for approximate user neighbor searching. The default value is 0.8.
- index_recall = 0.8
- # Maximal number of fit epochs for approximate user neighbor searching vector index. The default value is 3.
- index_fit_epoch = 3
- [recommend.item_neighbors]
- # The type of neighbors for items. There are three types:
- # similar: Neighbors are found by number of common labels.
- # related: Neighbors are found by number of common users.
- # auto: If a item have labels, neighbors are found by number of common labels.
- # If this item have no labels, neighbors are found by number of common users.
- # The default value is "auto".
- neighbor_type = "similar"
- # Enable approximate item neighbor searching using vector index. The default value is true.
- enable_index = true
- # Minimal recall for approximate item neighbor searching. The default value is 0.8.
- index_recall = 0.8
- # Maximal number of fit epochs for approximate item neighbor searching vector index. The default value is 3.
- index_fit_epoch = 3
- [recommend.collaborative]
- # Enable approximate collaborative filtering recommend using vector index. The default value is true.
- enable_index = true
- # Minimal recall for approximate collaborative filtering recommend. The default value is 0.9.
- index_recall = 0.9
- # Maximal number of fit epochs for approximate collaborative filtering recommend vector index. The default value is 3.
- index_fit_epoch = 3
- # The time period for model fitting. The default value is "60m".
- model_fit_period = "60m"
- # The time period for model searching. The default value is "360m".
- model_search_period = "360m"
- # The number of epochs for model searching. The default value is 100.
- model_search_epoch = 100
- # The number of trials for model searching. The default value is 10.
- model_search_trials = 10
- # Enable searching models of different sizes, which consume more memory. The default value is false.
- enable_model_size_search = false
- [recommend.replacement]
- # Replace historical items back to recommendations. The default value is false.
- enable_replacement = false
- # Decay the weights of replaced items from positive feedbacks. The default value is 0.8.
- positive_replacement_decay = 0.8
- # Decay the weights of replaced items from read feedbacks. The default value is 0.6.
- read_replacement_decay = 0.6
- [recommend.offline]
- # The time period to check recommendation for users. The default values is 1m.
- check_recommend_period = "1m"
- # The time period to refresh recommendation for inactive users. The default values is 120h.
- refresh_recommend_period = "24h"
- # Enable latest recommendation during offline recommendation. The default value is false.
- enable_latest_recommend = true
- # Enable popular recommendation during offline recommendation. The default value is false.
- enable_popular_recommend = false
- # Enable user-based similarity recommendation during offline recommendation. The default value is false.
- enable_user_based_recommend = true
- # Enable item-based similarity recommendation during offline recommendation. The default value is false.
- enable_item_based_recommend = false
- # Enable collaborative filtering recommendation during offline recommendation. The default value is true.
- enable_collaborative_recommend = true
- # Enable click-though rate prediction during offline recommendation. Otherwise, results from multi-way recommendation
- # would be merged randomly. The default value is false.
- enable_click_through_prediction = true
- # The explore recommendation method is used to inject popular items or latest items into recommended result:
- # popular: Recommend popular items to cold-start users.
- # latest: Recommend latest items to cold-start users.
- # The default values is { popular = 0.0, latest = 0.0 }.
- explore_recommend = { popular = 0.1, latest = 0.2 }
- [recommend.online]
- # The fallback recommendation method is used when cached recommendation drained out:
- # item_based: Recommend similar items to cold-start users.
- # popular: Recommend popular items to cold-start users.
- # latest: Recommend latest items to cold-start users.
- # Recommenders are used in order. The default values is ["latest"].
- fallback_recommend = ["item_based", "latest"]
- # The number of feedback used in fallback item-based similar recommendation. The default values is 10.
- num_feedback_fallback_item_based = 10
- [tracing]
- # Enable tracing for REST APIs. The default value is false.
- enable_tracing = false
- # The type of tracing exporters should be one of "jaeger", "zipkin", "otlp" and "otlphttp". The default value is "jaeger".
- exporter = "jaeger"
- # The endpoint of tracing collector.
- collector_endpoint = "http://localhost:14268/api/traces"
- # The type of tracing sampler should be one of "always", "never" and "ratio". The default value is "always".
- sampler = "always"
- # The ratio of ratio based sampler. The default value is 1.
- ratio = 1
- [experimental]
- # Enable deep learning recommenders. The default value is false.
- enable_deep_learning = false
- # Batch size for deep learning recommenders. The default value is 128.
- deep_learning_batch_size = 128
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