discourse-ai/spec/lib/completions/llm_spec.rb

156 lines
5.2 KiB
Ruby

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