Support SearchItems endpoint

README.md

@@ -72,7 +72,7 @@ NUM = 100
 PROBABILITY_PURCHASED = 0.1
 
 client = RecombeeClient('--my-database-id--', '--db-private-token--')
-client.send(ResetDatabase.new) # Clear everything from the database
+client.send(ResetDatabase.new) # Clear everything from the database (asynchronous)
 
 # We will use computers as items in this example
 # Computers have five properties 
@@ -103,7 +103,7 @@ requests = (1..NUM).map do |i|
       },
       #optional parameters:
       {
-        'cascadeCreate' => true  # Use cascadeCreate for creating item
+        :cascade_create => true  # Use cascade_create for creating item
                                  # with given itemId, if it doesn't exist
       }
     )
@@ -117,29 +117,38 @@ requests = []
 (1..NUM).map{|i| "computer-#{i}"}.each do |item_id|
   user_ids = (1..NUM).map{|i| "user-#{i}"}
   user_ids = user_ids.select { |_| rand(0.0..1.0) < PROBABILITY_PURCHASED }
-  # Use cascadeCreate to create unexisting users
-  user_ids.each { |user_id| requests.push(AddPurchase.new(user_id, item_id, 'cascadeCreate' => true)) }
+  # Use cascade_create to create unexisting users
+  user_ids.each { |user_id| requests.push(AddPurchase.new(user_id, item_id, :cascade_create => true)) }
 end
 
 # Send purchases to the recommender system
 client.send(Batch.new(requests))
 
 # Get 5 recommendations for user-42, who is currently viewing computer-6
-recommended = client.send(RecommendItemsToItem.new('computer-6', 'user-42', 5) )
-puts "Recommended items: #{recommended}"
-
 # Recommend only computers that have at least 3 cores
 recommended = client.send(
-  RecommendItemsToItem.new('computer-6', 'user-42', 5, {'filter' => "'num-cores'>=3"})
+  RecommendItemsToItem.new('computer-6', 'user-42', 5, {:filter => "'num-cores'>=3"})
   )
 puts "Recommended items with at least 3 processor cores: #{recommended}"
 
-# Recommend only items thatare more expensive then currently viewed item (up-sell)
+# Recommend only items that are more expensive then currently viewed item (up-sell)
 recommended = client.send(
   RecommendItemsToItem.new('computer-6', 'user-42', 5,
-    {'filter' => "'price' > context_item[\"price\"]"})
+    {:filter => "'price' > context_item[\"price\"]"})
   )
 puts "Recommended up-sell items: #{recommended}"
+
+# Filters, boosters and other settings can be also set in the Admin UI (admin.recombee.com)
+# when scenario is specified
+recommended = client.send(
+  RecommendItemsToItem.new('computer-6', 'user-42', 5, {:scenario => 'product_detail'})
+  )
+
+# Perform personalized full-text search with a user's search query (e.g. 'computers').
+matches = client.send(
+  SearchItems.new('user-42', 'computers', 5)
+  )
+puts "Matched items: #{matches}"
 ```
 
 ### Exception handling

lib/recombee_api_client.rb

@@ -18,7 +18,7 @@ class RecombeeClient
     include HTTParty
 
     BATCH_MAX_SIZE = 10000
-    USER_AGENT = {'User-Agent' => 'recombee-ruby-api-client/2.4.0'}
+    USER_AGENT = {'User-Agent' => 'recombee-ruby-api-client/3.0.0'}
 
     ##
     #   - +account+ -> Name of your account at Recombee

lib/recombee_api_client/api/recommend_items_to_item.rb

@@ -14,7 +14,7 @@ module RecombeeApiClient
   #The returned items are sorted by relevancy (first item being the most relevant).
   #
   class RecommendItemsToItem < ApiRequest
-    attr_reader :item_id, :target_user_id, :count, :filter, :booster, :cascade_create, :scenario, :logic, :return_properties, :included_properties, :user_impact, :diversity, :min_relevance, :rotation_rate, :rotation_time, :expert_settings, :return_ab_group
+    attr_reader :item_id, :target_user_id, :count, :scenario, :cascade_create, :return_properties, :included_properties, :filter, :booster, :logic, :user_impact, :diversity, :min_relevance, :rotation_rate, :rotation_time, :expert_settings, :return_ab_group
     attr_accessor :timeout
     attr_accessor :ensure_https
 
@@ -42,15 +42,13 @@ class RecommendItemsToItem < ApiRequest
   #   - +count+ -> Number of items to be recommended (N for the top-N recommendation).
   #
   # * *Optional arguments (given as hash optional)*
-  #   - +filter+ -> Boolean-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to filter recommended items based on the values of their attributes.
-  #   - +booster+ -> Number-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to boost recommendation rate of some items based on the values of their attributes.
-  #   - +cascadeCreate+ -> If item of given *itemId* or user of given *targetUserId* doesn't exist in the database, it creates the missing entity/entities and returns some (non-personalized) recommendations. This allows for example rotations in the following recommendations for the user of given *targetUserId*, as the user will be already known to the system.
-  #   - +scenario+ -> Scenario defines a particular application of recommendations. It can be for example "homepage", "cart" or "emailing". You can see each scenario in the UI separately, so you can check how well each application performs. The AI which optimizes models in order to get the best results may optimize different scenarios separately, or even use different models in each of the scenarios.
-  #   - +logic+ -> Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain (e-commerce, multimedia, fashion ...) and use case.
-  #See [this section](https://docs.recombee.com/recommendation_logic.html) for list of available logics and other details.
+  #   - +scenario+ -> Scenario defines a particular application of recommendations. It can be for example "homepage", "cart" or "emailing".
   #
-  #The difference between `logic` and `scenario` is that `logic` specifies mainly behavior, while `scenario` specifies the place where recommendations are shown to the users.
+  #You can set various settings to the [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com). You can also see performance of each scenario in the Admin UI separately, so you can check how well each application performs.
   #
+  #The AI which optimizes models in order to get the best results may optimize different scenarios separately, or even use different models in each of the scenarios.
+  #
+  #   - +cascadeCreate+ -> If item of given *itemId* or user of given *targetUserId* doesn't exist in the database, it creates the missing entity/entities and returns some (non-personalized) recommendations. This allows for example rotations in the following recommendations for the user of given *targetUserId*, as the user will be already known to the system.
   #   - +returnProperties+ -> With `returnProperties=true`, property values of the recommended items are returned along with their IDs in a JSON dictionary. The acquired property values can be used for easy displaying of the recommended items to the user. 
   #
   #Example response:
@@ -107,6 +105,21 @@ class RecommendItemsToItem < ApiRequest
   #  }
   #```
   #
+  #   - +filter+ -> Boolean-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to filter recommended items based on the values of their attributes.
+  #
+  #Filters can be also assigned to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
+  #
+  #   - +booster+ -> Number-returning [ReQL](https://docs.recombee.com/reql.html) expression which allows you to boost recommendation rate of some items based on the values of their attributes.
+  #
+  #Boosters can be also assigned to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
+  #
+  #   - +logic+ -> Logic specifies particular behavior of the recommendation models. You can pick tailored logic for your domain and use case.
+  #See [this section](https://docs.recombee.com/recommendation_logics.html) for list of available logics and other details.
+  #
+  #The difference between `logic` and `scenario` is that `logic` specifies mainly behavior, while `scenario` specifies the place where recommendations are shown to the users.
+  #
+  #Logic can be also set to a [scenario](https://docs.recombee.com/scenarios.html) in the [Admin UI](https://admin.recombee.com).
+  #
   #   - +userImpact+ -> **Expert option** If *targetUserId* parameter is present, the recommendations are biased towards the given user. Using *userImpact*, you may control this bias. For an extreme case of `userImpact=0.0`, the interactions made by the user are not taken into account at all (with the exception of history-based blacklisting), for `userImpact=1.0`, you'll get user-based recommendation. The default value is `0`.
   #
   #   - +diversity+ -> **Expert option** Real number from [0.0, 1.0] which determines how much mutually dissimilar should the recommended items be. The default value is 0.0, i.e., no diversification. Value 1.0 means maximal diversification.
@@ -127,13 +140,13 @@ def initialize(item_id, target_user_id, count, optional = {})
       @target_user_id = target_user_id
       @count = count
       optional = normalize_optional(optional)
-      @filter = optional['filter']
-      @booster = optional['booster']
-      @cascade_create = optional['cascadeCreate']
       @scenario = optional['scenario']
-      @logic = optional['logic']
+      @cascade_create = optional['cascadeCreate']
       @return_properties = optional['returnProperties']
       @included_properties = optional['includedProperties']
+      @filter = optional['filter']
+      @booster = optional['booster']
+      @logic = optional['logic']
       @user_impact = optional['userImpact']
       @diversity = optional['diversity']
       @min_relevance = optional['minRelevance']
@@ -145,7 +158,7 @@ def initialize(item_id, target_user_id, count, optional = {})
       @timeout = 3000
       @ensure_https = false
       @optional.each do |par, _|
-        fail UnknownOptionalParameter.new(par) unless ["filter","booster","cascadeCreate","scenario","logic","returnProperties","includedProperties","userImpact","diversity","minRelevance","rotationRate","rotationTime","expertSettings","returnAbGroup"].include? par
+        fail UnknownOptionalParameter.new(par) unless ["scenario","cascadeCreate","returnProperties","includedProperties","filter","booster","logic","userImpact","diversity","minRelevance","rotationRate","rotationTime","expertSettings","returnAbGroup"].include? par
       end
     end
 
@@ -159,13 +172,13 @@ def body_parameters
       p = Hash.new
       p['targetUserId'] = @target_user_id
       p['count'] = @count
-      p['filter'] = @optional['filter'] if @optional.include? 'filter'
-      p['booster'] = @optional['booster'] if @optional.include? 'booster'
-      p['cascadeCreate'] = @optional['cascadeCreate'] if @optional.include? 'cascadeCreate'
       p['scenario'] = @optional['scenario'] if @optional.include? 'scenario'
-      p['logic'] = @optional['logic'] if @optional.include? 'logic'
+      p['cascadeCreate'] = @optional['cascadeCreate'] if @optional.include? 'cascadeCreate'
       p['returnProperties'] = @optional['returnProperties'] if @optional.include? 'returnProperties'
       p['includedProperties'] = @optional['includedProperties'] if @optional.include? 'includedProperties'
+      p['filter'] = @optional['filter'] if @optional.include? 'filter'
+      p['booster'] = @optional['booster'] if @optional.include? 'booster'
+      p['logic'] = @optional['logic'] if @optional.include? 'logic'
       p['userImpact'] = @optional['userImpact'] if @optional.include? 'userImpact'
       p['diversity'] = @optional['diversity'] if @optional.include? 'diversity'
       p['minRelevance'] = @optional['minRelevance'] if @optional.include? 'minRelevance'