156 lines
5.2 KiB
Ruby
156 lines
5.2 KiB
Ruby
# frozen_string_literal: true
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RSpec.describe DiscourseAi::Completions::Llm do
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subject(:llm) do
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described_class.new(
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DiscourseAi::Completions::Dialects::OrcaStyle,
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canned_response,
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"hugging_face:Upstage-Llama-2-*-instruct-v2",
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)
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end
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fab!(:user)
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describe ".proxy" do
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it "raises an exception when we can't proxy the model" do
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fake_model = "unknown:unknown_v2"
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expect { described_class.proxy(fake_model) }.to(
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raise_error(DiscourseAi::Completions::Llm::UNKNOWN_MODEL),
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)
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end
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end
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describe "AiApiAuditLog" do
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it "is able to keep track of post and topic id" do
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prompt =
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DiscourseAi::Completions::Prompt.new(
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"You are fake",
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messages: [{ type: :user, content: "fake orders" }],
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topic_id: 123,
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post_id: 1,
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)
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result = <<~TEXT
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data: {"id":"chatcmpl-8xoPOYRmiuBANTmGqdCGVk4ZA3Orz","object":"chat.completion.chunk","created":1709265814,"model":"gpt-4-0125-preview","system_fingerprint":"fp_70b2088885","choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}]}
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data: {"id":"chatcmpl-8xoPOYRmiuBANTmGqdCGVk4ZA3Orz","object":"chat.completion.chunk","created":1709265814,"model":"gpt-4-0125-preview","system_fingerprint":"fp_70b2088885","choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}]}
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data: [DONE]
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TEXT
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WebMock.stub_request(:post, "https://api.openai.com/v1/chat/completions").to_return(
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status: 200,
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body: result,
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)
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result = +""
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described_class
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.proxy("open_ai:gpt-3.5-turbo")
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.generate(prompt, user: user) { |partial| result << partial }
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expect(result).to eq("Hello")
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log = AiApiAuditLog.order("id desc").first
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expect(log.topic_id).to eq(123)
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expect(log.post_id).to eq(1)
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end
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end
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describe "#generate with fake model" do
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before do
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DiscourseAi::Completions::Endpoints::Fake.delays = []
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DiscourseAi::Completions::Endpoints::Fake.chunk_count = 10
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end
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let(:llm) { described_class.proxy("fake:fake") }
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let(:prompt) do
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DiscourseAi::Completions::Prompt.new(
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"You are fake",
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messages: [{ type: :user, content: "fake orders" }],
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)
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end
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it "can generate a response" do
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response = llm.generate(prompt, user: user)
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expect(response).to be_present
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end
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it "can generate content via a block" do
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partials = []
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response = llm.generate(prompt, user: user) { |partial| partials << partial }
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expect(partials.length).to eq(10)
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expect(response).to eq(DiscourseAi::Completions::Endpoints::Fake.fake_content)
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expect(partials.join).to eq(response)
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end
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end
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describe "#generate with various style prompts" do
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let :canned_response do
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DiscourseAi::Completions::Endpoints::CannedResponse.new(["world"])
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end
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it "can generate a response to a simple string" do
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response = llm.generate("hello", user: user)
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expect(response).to eq("world")
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end
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it "can generate a response from an array" do
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response =
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llm.generate(
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[{ type: :system, content: "you are a bot" }, { type: :user, content: "hello" }],
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user: user,
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)
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expect(response).to eq("world")
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end
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end
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describe "#generate" do
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let(:prompt) do
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system_insts = (<<~TEXT).strip
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I want you to act as a title generator for written pieces. I will provide you with a text,
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and you will generate five attention-grabbing titles. Please keep the title concise and under 20 words,
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and ensure that the meaning is maintained. Replies will utilize the language type of the topic.
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TEXT
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DiscourseAi::Completions::Prompt
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.new(system_insts)
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.tap { |a_prompt| a_prompt.push(type: :user, content: (<<~TEXT).strip) }
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Here is the text, inside <input></input> XML tags:
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<input>
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To perfect his horror, Caesar, surrounded at the base of the statue by the impatient daggers of his friends,
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discovers among the faces and blades that of Marcus Brutus, his protege, perhaps his son, and he no longer
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defends himself, but instead exclaims: 'You too, my son!' Shakespeare and Quevedo capture the pathetic cry.
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</input>
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TEXT
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end
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let(:canned_response) do
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DiscourseAi::Completions::Endpoints::CannedResponse.new(
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[
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"<ai>The solitary horse.,The horse etched in gold.,A horse's infinite journey.,A horse lost in time.,A horse's last ride.</ai>",
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],
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)
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end
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context "when getting the full response" do
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it "processes the prompt and return the response" do
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llm_response = llm.generate(prompt, user: user)
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expect(llm_response).to eq(canned_response.responses[0])
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end
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end
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context "when getting a streamed response" do
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it "processes the prompt and call the given block with the partial response" do
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llm_response = +""
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llm.generate(prompt, user: user) { |partial, cancel_fn| llm_response << partial }
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expect(llm_response).to eq(canned_response.responses[0])
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end
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end
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end
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end
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