Merge pull request #36 from alexrudall/add_new_endpoints

Add Answers endpoint

Author: alexrudall

CHANGELOG.md

@@ -5,6 +5,12 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [1.2.0] - 2021-04-08
+
+### Added
+
+- Add Client#answers endpoint for question/answer response on documents or a file.
+
 ## [1.1.0] - 2021-04-07
 
 ### Added

Gemfile.lock

@@ -1,7 +1,7 @@
 PATH
   remote: .
   specs:
-    ruby-openai (1.1.0)
+    ruby-openai (1.2.0)
       dotenv (~> 2.7.6)
       httparty (~> 0.18.1)
 

README.md

@@ -92,6 +92,32 @@ You can alternatively search using the ID of a file you've uploaded:
     client.search(engine: "ada", file: "abc123", query: "happy")
 ```
 
+### Answers
+
+Pass documents, a question string, and an example question/response to get an answer to a question:
+
+```
+    response = client.answers(parameters: {
+        documents: ["Puppy A is happy.", "Puppy B is sad."],
+        question: "which puppy is happy?",
+        model: "curie",
+        examples_context: "In 2017, U.S. life expectancy was 78.6 years.",
+        examples: [["What is human life expectancy in the United States?","78 years."]],
+    })
+```
+
+You can alternatively search using the ID of a file you've uploaded:
+
+```
+    response = client.answers(parameters: {
+        file: "123abc",
+        question: "which puppy is happy?",
+        model: "curie",
+        examples_context: "In 2017, U.S. life expectancy was 78.6 years.",
+        examples: [["What is human life expectancy in the United States?","78 years."]],
+    })
+```
+
 ## Development
 
 After checking out the repo, run `bin/setup` to install dependencies. Then, run `rake spec` to run the tests. You can also run `bin/console` for an interactive prompt that will allow you to experiment.

lib/ruby/openai/client.rb

@@ -7,6 +7,17 @@ def initialize(access_token: nil)
       @access_token = access_token || ENV["OPENAI_ACCESS_TOKEN"]
     end
 
+    def answers(version: default_version, parameters: {})
+      self.class.post(
+        "/#{version}/answers",
+        headers: {
+          "Content-Type" => "application/json",
+          "Authorization" => "Bearer #{@access_token}"
+        },
+        body: parameters.to_json
+      )
+    end
+
     def completions(engine:, version: default_version, parameters: {})
       self.class.post(
         "/#{version}/engines/#{engine}/completions",

lib/ruby/openai/version.rb

@@ -1,5 +1,5 @@
 module Ruby
   module OpenAI
-    VERSION = "1.1.0".freeze
+    VERSION = "1.2.0".freeze
   end
 end

spec/fixtures/cassettes/ada_answers_documents_which_puppy_is_happy_.yml

@@ -0,0 +1,67 @@
+RSpec.describe OpenAI::Client do
+  describe "#answers", :vcr do
+    let(:question) { "which puppy is happy?" }
+    let(:examples) { [["What is human life expectancy in the United States?", "78 years."]] }
+    let(:examples_context) { "In 2017, U.S. life expectancy was 78.6 years." }
+
+    context "with a file" do
+      let(:cassette) { "#{engine} answers file #{question}".downcase }
+      let(:filename) { "puppy.jsonl" }
+      let(:file) { File.join(RSPEC_ROOT, "fixtures/files", filename) }
+      let!(:file_id) do
+        response = VCR.use_cassette("files upload answers") do
+          OpenAI::Client.new.files.upload(parameters: { file: file, purpose: "answers" })
+        end
+        JSON.parse(response.body)["id"]
+      end
+      let(:response) do
+        OpenAI::Client.new.answers(
+          parameters: {
+            model: engine,
+            question: question,
+            examples: examples,
+            examples_context: examples_context,
+            file: file_id
+          }
+        )
+      end
+
+      context "with engine: davinci" do
+        let(:engine) { "davinci" }
+
+        it "answers the question" do
+          VCR.use_cassette(cassette) do
+            expect(response.parsed_response["answers"][0]).to include("puppy A is happy")
+          end
+        end
+      end
+    end
+
+    context "with documents" do
+      let(:cassette) { "#{engine} answers documents #{question}".downcase }
+      let(:documents) { ["Puppy A is happy", "Puppy B is sad."] }
+
+      let(:response) do
+        OpenAI::Client.new.answers(
+          parameters: {
+            model: engine,
+            question: question,
+            examples: examples,
+            examples_context: examples_context,
+            documents: documents
+          }
+        )
+      end
+
+      context "with engine: ada" do
+        let(:engine) { "ada" }
+
+        it "answers the question" do
+          VCR.use_cassette(cassette) do
+            expect(response.parsed_response["answers"][0]).to include("Puppy A.")
+          end
+        end
+      end
+    end
+  end
+end

spec/fixtures/cassettes/davinci_answers_file_which_puppy_is_happy_.yml

@@ -42,7 +42,6 @@
         )
       end
       let(:best_match) { JSON.parse(response.body)["data"].max_by { |d| d["score"] }["document"] }
-      let(:cassette) { "#{engine} search #{query}".downcase }
 
       context "with engine: ada" do
         let(:engine) { "ada" }