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