discourse-ai/spec/lib/completions/endpoints/ollama_spec.rb

160 lines
4.0 KiB
Ruby

# frozen_string_literal: true
require_relative "endpoint_compliance"
class OllamaMock < EndpointMock
def response(content, tool_call: false)
message_content =
if tool_call
{ content: "", tool_calls: [content] }
else
{ content: content }
end
{
created_at: "2024-09-25T06:47:21.283028Z",
model: "llama3.1",
message: { role: "assistant" }.merge(message_content),
done: true,
done_reason: "stop",
total_duration: 7_639_718_541,
load_duration: 299_886_663,
prompt_eval_count: 18,
prompt_eval_duration: 220_447_000,
eval_count: 18,
eval_duration: 220_447_000,
}
end
def stub_response(prompt, response_text, tool_call: false)
WebMock
.stub_request(:post, "http://api.ollama.ai/api/chat")
.with(body: request_body(prompt, tool_call: tool_call))
.to_return(status: 200, body: JSON.dump(response(response_text, tool_call: tool_call)))
end
def stream_line(delta)
message_content = { content: delta }
+{
model: "llama3.1",
created_at: "2024-09-25T06:47:21.283028Z",
message: { role: "assistant" }.merge(message_content),
done: false,
}.to_json
end
def stub_raw(chunks)
WebMock.stub_request(:post, "http://api.ollama.ai/api/chat").to_return(
status: 200,
body: chunks,
)
end
def stub_streamed_response(prompt, deltas)
chunks = deltas.each_with_index.map { |_, index| stream_line(deltas[index]) }
chunks =
(
chunks.join("\n\n") << {
model: "llama3.1",
created_at: "2024-09-25T06:47:21.283028Z",
message: {
role: "assistant",
content: "",
},
done: true,
done_reason: "stop",
total_duration: 7_639_718_541,
load_duration: 299_886_663,
prompt_eval_count: 18,
prompt_eval_duration: 220_447_000,
eval_count: 18,
eval_duration: 220_447_000,
}.to_json
).split("")
WebMock
.stub_request(:post, "http://api.ollama.ai/api/chat")
.with(body: request_body(prompt))
.to_return(status: 200, body: chunks)
yield if block_given?
end
def tool_response
{ function: { name: "get_weather", arguments: { location: "Sydney", unit: "c" } } }
end
def tool_payload
{
type: "function",
function: {
name: "get_weather",
description: "Get the weather in a city",
parameters: {
type: "object",
properties: {
location: {
type: "string",
description: "the city name",
},
unit: {
type: "string",
description: "the unit of measurement celcius c or fahrenheit f",
enum: %w[c f],
},
},
required: %w[location unit],
},
},
}
end
def request_body(prompt, tool_call: false)
model
.default_options
.merge(messages: prompt)
.tap do |b|
b[:stream] = false
b[:tools] = [tool_payload] if tool_call
end
.to_json
end
end
RSpec.describe DiscourseAi::Completions::Endpoints::Ollama do
subject(:endpoint) { described_class.new(model) }
fab!(:user)
fab!(:model) { Fabricate(:ollama_model) }
let(:ollama_mock) { OllamaMock.new(endpoint) }
let(:compliance) do
EndpointsCompliance.new(self, endpoint, DiscourseAi::Completions::Dialects::Ollama, user)
end
describe "#perform_completion!" do
context "when using regular mode" do
it "completes a trivial prompt and logs the response" do
compliance.regular_mode_simple_prompt(ollama_mock)
end
end
context "with tools" do
it "returns a function invocation" do
compliance.regular_mode_tools(ollama_mock)
end
end
end
describe "when using streaming mode" do
context "with simple prompts" do
it "completes a trivial prompt and logs the response" do
compliance.streaming_mode_simple_prompt(ollama_mock)
end
end
end
end