Rename dimension parameter to dimensions everywhere

lib/langchain/llm/base.rb

@@ -24,8 +24,8 @@ class Base
     # A client for communicating with the LLM
     attr_reader :client
 
-    def default_dimension
-      self.class.const_get(:DEFAULTS).dig(:dimension)
+    def default_dimensions
+      self.class.const_get(:DEFAULTS).dig(:dimensions)
     end
 
     #

lib/langchain/llm/cohere.rb

@@ -15,7 +15,7 @@ class Cohere < Base
       temperature: 0.0,
       completion_model_name: "command",
       embeddings_model_name: "small",
-      dimension: 1024,
+      dimensions: 1024,
       truncate: "START"
     }.freeze
 

lib/langchain/llm/google_palm.rb

@@ -13,7 +13,7 @@ module Langchain::LLM
   class GooglePalm < Base
     DEFAULTS = {
       temperature: 0.0,
-      dimension: 768, # This is what the `embedding-gecko-001` model generates
+      dimensions: 768, # This is what the `embedding-gecko-001` model generates
       completion_model_name: "text-bison-001",
       chat_completion_model_name: "chat-bison-001",
       embeddings_model_name: "embedding-gecko-001"

lib/langchain/llm/google_vertex_ai.rb

@@ -16,7 +16,7 @@ class GoogleVertexAi < Base
       max_output_tokens: 1000,
       top_p: 0.8,
       top_k: 40,
-      dimension: 768,
+      dimensions: 768,
       completion_model_name: "text-bison", # Optional: tect-bison@001
       embeddings_model_name: "textembedding-gecko"
     }.freeze

lib/langchain/llm/hugging_face.rb

@@ -16,7 +16,7 @@ class HuggingFace < Base
     DEFAULTS = {
       temperature: 0.0,
       embeddings_model_name: "sentence-transformers/all-MiniLM-L6-v2",
-      dimension: 384 # Vector size generated by the above model
+      dimensions: 384 # Vector size generated by the above model
     }.freeze
 
     #

lib/langchain/llm/ollama.rb

@@ -41,9 +41,9 @@ def initialize(url:, default_options: {})
 
     # Returns the # of vector dimensions for the embeddings
     # @return [Integer] The # of vector dimensions
-    def default_dimension
+    def default_dimensions
       # since Ollama can run multiple models, look it up or generate an embedding and return the size
-      @default_dimension ||=
+      @default_dimensions ||=
         EMBEDDING_SIZES.fetch(defaults[:embeddings_model_name].to_sym) do
           embed(text: "test").embedding.size
         end

lib/langchain/llm/openai.rb

@@ -184,7 +184,7 @@ def summarize(text:)
       complete(prompt: prompt)
     end
 
-    def default_dimension
+    def default_dimensions
       @defaults[:dimensions] || EMBEDDING_SIZES.fetch(defaults[:embeddings_model_name])
     end
 

lib/langchain/llm/replicate.rb

@@ -24,7 +24,7 @@ class Replicate < Base
       # TODO: Design the interface to pass and use different models
       completion_model_name: "replicate/vicuna-13b",
       embeddings_model_name: "creatorrr/all-mpnet-base-v2",
-      dimension: 384
+      dimensions: 384
     }.freeze
 
     #

lib/langchain/vectorsearch/elasticsearch.rb

@@ -104,7 +104,7 @@ def delete_default_schema
     end
 
     def default_vector_settings
-      {type: "dense_vector", dims: llm.default_dimension}
+      {type: "dense_vector", dims: llm.default_dimensions}
     end
 
     def vector_settings

lib/langchain/vectorsearch/epsilla.rb

@@ -54,7 +54,7 @@ def initialize(url:, db_name:, db_path:, index_name:, llm:)
       @db_path = db_path
       @table_name = index_name
 
-      @vector_dimension = llm.default_dimension
+      @vector_dimensions = llm.default_dimensions
 
       super(llm: llm)
     end
@@ -64,7 +64,7 @@ def create_default_schema
       status_code, response = @client.database.create_table(@table_name, [
         {"name" => "ID", "dataType" => "STRING", "primaryKey" => true},
         {"name" => "Doc", "dataType" => "STRING"},
-        {"name" => "Embedding", "dataType" => "VECTOR_FLOAT", "dimensions" => @vector_dimension}
+        {"name" => "Embedding", "dataType" => "VECTOR_FLOAT", "dimensions" => @vector_dimensions}
       ])
       raise "Failed to create table: #{response}" if status_code != 200
 

lib/langchain/vectorsearch/hnswlib.rb

@@ -26,7 +26,7 @@ def initialize(llm:, path_to_index:)
 
       super(llm: llm)
 
-      @client = ::Hnswlib::HierarchicalNSW.new(space: DEFAULT_METRIC, dim: llm.default_dimension)
+      @client = ::Hnswlib::HierarchicalNSW.new(space: DEFAULT_METRIC, dim: llm.default_dimensions)
       @path_to_index = path_to_index
 
       initialize_index

lib/langchain/vectorsearch/milvus.rb

@@ -71,7 +71,7 @@ def create_default_schema
             type_params: [
               {
                 key: "dim",
-                value: llm.default_dimension.to_s
+                value: llm.default_dimensions.to_s
               }
             ]
           }

lib/langchain/vectorsearch/pgvector.rb

@@ -101,11 +101,11 @@ def remove_texts(ids:)
     def create_default_schema
       db.run "CREATE EXTENSION IF NOT EXISTS vector"
       namespace_column = @namespace_column
-      vector_dimension = llm.default_dimension
+      vector_dimensions = llm.default_dimensions
       db.create_table? table_name.to_sym do
         primary_key :id
         text :content
-        column :vectors, "vector(#{vector_dimension})"
+        column :vectors, "vector(#{vector_dimensions})"
         text namespace_column.to_sym, default: nil
       end
     end

lib/langchain/vectorsearch/pinecone.rb

@@ -104,7 +104,7 @@ def create_default_schema
       client.create_index(
         metric: DEFAULT_METRIC,
         name: index_name,
-        dimension: llm.default_dimension
+        dimension: llm.default_dimensions
       )
     end
 

lib/langchain/vectorsearch/qdrant.rb

@@ -93,7 +93,7 @@ def create_default_schema
         collection_name: index_name,
         vectors: {
           distance: DEFAULT_METRIC.capitalize,
-          size: llm.default_dimension
+          size: llm.default_dimensions
         }
       )
     end

spec/langchain/llm/cohere_spec.rb

@@ -87,9 +87,9 @@
     end
   end
 
-  describe "#default_dimension" do
-    it "returns the default dimension" do
-      expect(subject.default_dimension).to eq(1024)
+  describe "#default_dimensions" do
+    it "returns the default dimensions" do
+      expect(subject.default_dimensions).to eq(1024)
     end
   end
 

spec/langchain/llm/hugging_face_spec.rb

@@ -17,9 +17,9 @@
     end
   end
 
-  describe "#default_dimension" do
-    it "returns the default dimension" do
-      expect(subject.default_dimension).to eq(384)
+  describe "#default_dimensions" do
+    it "returns the default dimensions" do
+      expect(subject.default_dimensions).to eq(384)
     end
   end
 end

spec/langchain/llm/ollama_spec.rb

@@ -68,52 +68,52 @@
     end
   end
 
-  describe "#default_dimension" do
+  describe "#default_dimensions" do
     it "returns size of llama2 embeddings" do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "llama2"})
 
-      expect(subject.default_dimension).to eq(4_096)
+      expect(subject.default_dimensions).to eq(4_096)
     end
 
     it "returns size of llava embeddings" do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "llava"})
 
-      expect(subject.default_dimension).to eq(4_096)
+      expect(subject.default_dimensions).to eq(4_096)
     end
 
     it "returns size of mistral embeddings" do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "mistral"})
 
-      expect(subject.default_dimension).to eq(4_096)
+      expect(subject.default_dimensions).to eq(4_096)
     end
 
     it "returns size of mixtral embeddings" do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "mixtral"})
 
-      expect(subject.default_dimension).to eq(4_096)
+      expect(subject.default_dimensions).to eq(4_096)
     end
 
     it "returns size of dolphin-mixtral embeddings" do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "dolphin-mixtral"})
-      expect(subject.default_dimension).to eq(4_096)
+      expect(subject.default_dimensions).to eq(4_096)
     end
 
     it "returns size of mistral-openorca embeddings" do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "mistral-openorca"})
-      expect(subject.default_dimension).to eq(4_096)
+      expect(subject.default_dimensions).to eq(4_096)
     end
 
     it "returns size of codellama embeddings" do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "codellama"})
-      expect(subject.default_dimension).to eq(4_096)
+      expect(subject.default_dimensions).to eq(4_096)
     end
 
     # this one has not been hardcoded, but will be looked up
     # by generating an embedding and checking its size
     it "returns size of tinydolphin embeddings", vcr: true do
       subject = described_class.new(url: "http://localhost:11434", default_options: {embeddings_model_name: "tinydolphin"})
 
-      expect(subject.default_dimension).to eq(2_048)
+      expect(subject.default_dimensions).to eq(2_048)
     end
   end
 end

spec/langchain/llm/openai_spec.rb

@@ -91,34 +91,34 @@
 
     describe "the model dimension" do
       let(:model) { "text-embedding-3-small" }
-      let(:dimension_size) { 1536 }
+      let(:dimensions_size) { 1536 }
       let(:parameters) do
-        {parameters: {input: "Hello World", model: model, dimensions: dimension_size}}
+        {parameters: {input: "Hello World", model: model, dimensions: dimensions_size}}
       end
 
-      context "when dimension is not provided" do
-        it "forwards the models default dimension" do
+      context "when dimensions is not provided" do
+        it "forwards the models default dimensions" do
           subject.embed(text: "Hello World", model: model)
 
           expect(subject.client).to have_received(:embeddings).with(parameters)
         end
       end
 
-      context "when dimension is provided" do
-        let(:dimension_size) { 1536 }
+      context "when dimensions is provided" do
+        let(:dimensions_size) { 1536 }
 
         let(:parameters) do
-          {parameters: {input: "Hello World", model: model, dimensions: dimension_size}}
+          {parameters: {input: "Hello World", model: model, dimensions: dimensions_size}}
         end
 
         let(:subject) do
           described_class.new(api_key: "123", default_options: {
             embeddings_model_name: model,
-            dimension: dimension_size
+            dimensions: dimensions_size
           })
         end
 
-        it "forwards the model's default dimension" do
+        it "forwards the model's default dimensions" do
           allow(subject.client).to receive(:embeddings).with(parameters).and_return(response)
           subject.embed(text: "Hello World", model: model)
 
@@ -369,21 +369,21 @@
     end
   end
 
-  describe "#default_dimension" do
-    it "returns the default dimension" do
-      expect(subject.default_dimension).to eq(1536)
+  describe "#default_dimensions" do
+    it "returns the default dimensions" do
+      expect(subject.default_dimensions).to eq(1536)
     end
 
-    context "when the dimension is passed as an argument" do
+    context "when the dimensions is passed as an argument" do
       let(:subject) do
         described_class.new(api_key: "123", default_options: {
           embeddings_model_name: "text-embedding-3-small",
           dimensions: 512
         })
       end
 
-      it "sets the default_dimension" do
-        expect(subject.default_dimension).to eq 512
+      it "sets the default_dimensions" do
+        expect(subject.default_dimensions).to eq 512
       end
     end
   end

spec/langchain/vectorsearch/hnswlib_spec.rb

@@ -8,7 +8,7 @@
   end
 
   before do
-    allow_any_instance_of(Langchain::LLM::GooglePalm).to receive(:default_dimension).and_return(3)
+    allow_any_instance_of(Langchain::LLM::GooglePalm).to receive(:default_dimensions).and_return(3)
   end
 
   let(:llm) { Langchain::LLM::GooglePalm.new(api_key: "123") }

spec/langchain/vectorsearch/pinecone_spec.rb

@@ -21,7 +21,7 @@
       allow(subject.client).to receive(:create_index).with(
         metric: described_class::DEFAULT_METRIC,
         name: index_name,
-        dimension: subject.llm.default_dimension
+        dimension: subject.llm.default_dimensions
       ).and_return(true)
       expect(subject.create_default_schema).to eq(true)
     end