Merge pull request #492 from marckohlbrugge/main

Add parameters support to batches.list and update README to include /v1/embeddings Batches support

Author: alexrudall

README.md

@@ -526,11 +526,9 @@ puts response.dig("data", 0, "embedding")
 ```
 
 ### Batches
-
-The Batches endpoint allows you to create and manage large batches of API requests to run asynchronously. Currently, only the `/v1/chat/completions` endpoint is supported for batches.
+The Batches endpoint allows you to create and manage large batches of API requests to run asynchronously. Currently, the supported endpoints for batches are `/v1/chat/completions` (Chat Completions API) and `/v1/embeddings` (Embeddings API).
 
 To use the Batches endpoint, you need to first upload a JSONL file containing the batch requests using the Files endpoint. The file must be uploaded with the purpose set to `batch`. Each line in the JSONL file represents a single request and should have the following format:
-
 ```json
 {
   "custom_id": "request-1",

lib/openai/batches.rb

@@ -4,8 +4,8 @@ def initialize(client:)
       @client = client.beta(assistants: OpenAI::Assistants::BETA_VERSION)
     end
 
-    def list
-      @client.get(path: "/batches")
+    def list(parameters: {})
+      @client.get(path: "/batches", parameters: parameters)
     end
 
     def retrieve(id:)

spec/openai/client/batches_spec.rb

@@ -24,7 +24,17 @@
     describe "#list", :vcr do
       let(:input_cassette) { "batches list input" }
       let(:cassette) { "batches list" }
+      let(:limit) { 10 }
       let(:response) { OpenAI::Client.new.batches.list }
+      let(:existing_batch) do
+        OpenAI::Client.new.batches.create(
+          parameters: {
+            input_file_id: input_file_id,
+            endpoint: "/v1/chat/completions",
+            completion_window: "24h"
+          }
+        )
+      end
 
       before { batch_id }
 
@@ -33,6 +43,18 @@
           expect(response.dig("data", 0, "object")).to eq("batch")
         end
       end
+
+      it "supports after and limit parameters" do
+        VCR.use_cassette(cassette) do
+          response = OpenAI::Client.new.batches.list(parameters: {
+                                                       after: existing_batch["id"],
+                                                       limit: limit
+                                                     })
+
+          expect(response.dig("data", 0, "object")).to eq("batch")
+          expect(response["data"].length).to be <= limit
+        end
+      end
     end
 
     describe "#retrieve" do