723 lines
28 KiB
Ruby
723 lines
28 KiB
Ruby
# frozen_string_literal: true
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require_relative "endpoint_compliance"
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class OpenAiMock < 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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{ 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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id: "chatcmpl-6sZfAb30Rnv9Q7ufzFwvQsMpjZh8S",
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object: "chat.completion",
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created: 1_678_464_820,
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model: "gpt-3.5-turbo-0301",
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usage: {
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prompt_tokens: 8,
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completion_tokens: 13,
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total_tokens: 499,
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},
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choices: [
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{ message: { role: "assistant" }.merge(message_content), finish_reason: "stop", index: 0 },
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],
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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, "https://api.openai.com/v1/chat/completions")
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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, finish_reason: nil, tool_call: false)
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message_content =
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if tool_call
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{ tool_calls: [delta] }
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else
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{ content: delta }
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end
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+"data: " << {
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id: "chatcmpl-#{SecureRandom.hex}",
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object: "chat.completion.chunk",
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created: 1_681_283_881,
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model: "gpt-3.5-turbo-0301",
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choices: [{ delta: message_content }],
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finish_reason: finish_reason,
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index: 0,
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}.to_json
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end
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def stub_raw(chunks, body_blk: nil)
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stub = WebMock.stub_request(:post, "https://api.openai.com/v1/chat/completions")
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stub.with(body: body_blk) if body_blk
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stub.to_return(status: 200, body: chunks)
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end
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def stub_streamed_response(prompt, deltas, tool_call: false)
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chunks =
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deltas.each_with_index.map do |_, index|
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if index == (deltas.length - 1)
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stream_line(deltas[index], finish_reason: "stop_sequence", tool_call: tool_call)
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else
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stream_line(deltas[index], tool_call: tool_call)
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end
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end
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chunks = (chunks.join("\n\n") << "data: [DONE]").split("")
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WebMock
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.stub_request(:post, "https://api.openai.com/v1/chat/completions")
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.with(body: request_body(prompt, stream: true, tool_call: tool_call))
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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_deltas
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[
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{ id: tool_id, function: {} },
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{ id: tool_id, function: { name: "get_weather", arguments: "" } },
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{ id: tool_id, function: { arguments: "" } },
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{ id: tool_id, function: { arguments: "{" } },
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{ id: tool_id, function: { arguments: " \"location\": \"Sydney\"" } },
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{ id: tool_id, function: { arguments: " ,\"unit\": \"c\" }" } },
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]
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end
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def tool_response
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{
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id: tool_id,
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function: {
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name: "get_weather",
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arguments: { location: "Sydney", unit: "c" }.to_json,
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},
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}
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end
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def tool_id
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"tool_0"
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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, stream: false, 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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if stream
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b[:stream] = true
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b[:stream_options] = { include_usage: true }
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end
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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::OpenAi do
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subject(:endpoint) { described_class.new(model) }
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fab!(:user)
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fab!(:model) { Fabricate(:llm_model) }
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let(:echo_tool) do
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{
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name: "echo",
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description: "echo something",
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parameters: [{ name: "text", type: "string", description: "text to echo", required: true }],
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}
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end
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let(:tools) { [echo_tool] }
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let(:open_ai_mock) { OpenAiMock.new(endpoint) }
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let(:compliance) do
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EndpointsCompliance.new(self, endpoint, DiscourseAi::Completions::Dialects::ChatGpt, user)
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end
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let(:image100x100) { plugin_file_from_fixtures("100x100.jpg") }
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let(:upload100x100) do
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UploadCreator.new(image100x100, "image.jpg").create_for(Discourse.system_user.id)
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end
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describe "repeat calls" do
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it "can properly reset context" do
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llm = DiscourseAi::Completions::Llm.proxy("custom:#{model.id}")
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tools = [
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{
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name: "echo",
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description: "echo something",
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parameters: [
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{ name: "text", type: "string", description: "text to echo", required: true },
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],
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},
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]
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prompt =
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DiscourseAi::Completions::Prompt.new(
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"You are a bot",
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messages: [type: :user, id: "user1", content: "echo hello"],
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tools: tools,
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)
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response = {
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id: "chatcmpl-9JxkAzzaeO4DSV3omWvok9TKhCjBH",
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object: "chat.completion",
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created: 1_714_544_914,
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model: "gpt-4-turbo-2024-04-09",
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choices: [
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{
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index: 0,
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message: {
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role: "assistant",
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content: nil,
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tool_calls: [
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{
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id: "call_I8LKnoijVuhKOM85nnEQgWwd",
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type: "function",
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function: {
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name: "echo",
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arguments: "{\"text\":\"hello\"}",
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},
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},
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],
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},
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logprobs: nil,
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finish_reason: "tool_calls",
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},
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],
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usage: {
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prompt_tokens: 55,
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completion_tokens: 13,
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total_tokens: 68,
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},
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system_fingerprint: "fp_ea6eb70039",
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}.to_json
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stub_request(:post, "https://api.openai.com/v1/chat/completions").to_return(body: response)
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result = llm.generate(prompt, user: user)
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tool_call =
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DiscourseAi::Completions::ToolCall.new(
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id: "call_I8LKnoijVuhKOM85nnEQgWwd",
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name: "echo",
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parameters: {
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text: "hello",
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},
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)
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expect(result).to eq(tool_call)
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stub_request(:post, "https://api.openai.com/v1/chat/completions").to_return(
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body: { choices: [message: { content: "OK" }] }.to_json,
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)
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result = llm.generate(prompt, user: user)
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expect(result).to eq("OK")
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end
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end
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describe "forced tool use" do
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it "can properly force tool use" do
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llm = DiscourseAi::Completions::Llm.proxy("custom:#{model.id}")
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tools = [
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{
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name: "echo",
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description: "echo something",
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parameters: [
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{ name: "text", type: "string", description: "text to echo", required: true },
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],
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},
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]
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prompt =
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DiscourseAi::Completions::Prompt.new(
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"You are a bot",
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messages: [type: :user, id: "user1", content: "echo hello"],
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tools: tools,
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tool_choice: "echo",
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)
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response = {
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id: "chatcmpl-9JxkAzzaeO4DSV3omWvok9TKhCjBH",
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object: "chat.completion",
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created: 1_714_544_914,
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model: "gpt-4-turbo-2024-04-09",
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choices: [
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{
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index: 0,
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message: {
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role: "assistant",
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content: nil,
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tool_calls: [
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{
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id: "call_I8LKnoijVuhKOM85nnEQgWwd",
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type: "function",
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function: {
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name: "echo",
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arguments: "{\"text\":\"h<e>llo\"}",
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},
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},
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],
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},
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logprobs: nil,
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finish_reason: "tool_calls",
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},
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],
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usage: {
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prompt_tokens: 55,
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completion_tokens: 13,
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total_tokens: 68,
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},
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system_fingerprint: "fp_ea6eb70039",
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}.to_json
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body_json = nil
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stub_request(:post, "https://api.openai.com/v1/chat/completions").with(
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body: proc { |body| body_json = JSON.parse(body, symbolize_names: true) },
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).to_return(body: response)
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result = llm.generate(prompt, user: user)
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expect(body_json[:tool_choice]).to eq({ type: "function", function: { name: "echo" } })
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log = AiApiAuditLog.order(:id).last
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expect(log.request_tokens).to eq(55)
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expect(log.response_tokens).to eq(13)
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expected =
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DiscourseAi::Completions::ToolCall.new(
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id: "call_I8LKnoijVuhKOM85nnEQgWwd",
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name: "echo",
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parameters: {
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text: "h<e>llo",
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},
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)
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expect(result).to eq(expected)
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stub_request(:post, "https://api.openai.com/v1/chat/completions").to_return(
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body: { choices: [message: { content: "OK" }] }.to_json,
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)
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result = llm.generate(prompt, user: user)
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expect(result).to eq("OK")
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end
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end
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describe "image support" do
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it "can handle images" do
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model = Fabricate(:llm_model, vision_enabled: true)
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llm = DiscourseAi::Completions::Llm.proxy("custom:#{model.id}")
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prompt =
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DiscourseAi::Completions::Prompt.new(
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"You are image bot",
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messages: [type: :user, id: "user1", content: "hello", upload_ids: [upload100x100.id]],
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)
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encoded = prompt.encoded_uploads(prompt.messages.last)
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parsed_body = nil
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stub_request(:post, "https://api.openai.com/v1/chat/completions").with(
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body:
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proc do |req_body|
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parsed_body = JSON.parse(req_body, symbolize_names: true)
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true
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end,
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).to_return(status: 200, body: { choices: [message: { content: "nice pic" }] }.to_json)
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completion = llm.generate(prompt, user: user)
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expect(completion).to eq("nice pic")
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expected_body = {
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model: "gpt-4-turbo",
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messages: [
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{ role: "system", content: "You are image bot" },
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{
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role: "user",
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content: [
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{
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type: "image_url",
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image_url: {
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url: "data:#{encoded[0][:mime_type]};base64,#{encoded[0][:base64]}",
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},
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},
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{ type: "text", text: "hello" },
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],
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name: "user1",
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},
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],
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}
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expect(parsed_body).to eq(expected_body)
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end
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end
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describe "#perform_completion!" do
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context "when using XML tool calls format" do
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let(:xml_tool_call_response) { <<~XML }
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<function_calls>
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<invoke>
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<tool_name>get_weather</tool_name>
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<parameters>
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<location>Sydney</location>
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<unit>c</unit>
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</parameters>
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</invoke>
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</function_calls>
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XML
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it "parses XML tool calls" do
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response = {
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id: "chatcmpl-6sZfAb30Rnv9Q7ufzFwvQsMpjZh8S",
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object: "chat.completion",
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created: 1_678_464_820,
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model: "gpt-3.5-turbo-0301",
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usage: {
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prompt_tokens: 8,
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completion_tokens: 13,
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total_tokens: 499,
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},
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choices: [
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{
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message: {
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role: "assistant",
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content: xml_tool_call_response,
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},
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finish_reason: "stop",
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index: 0,
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},
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],
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}.to_json
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endpoint.llm_model.update!(provider_params: { disable_native_tools: true })
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body = nil
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open_ai_mock.stub_raw(response, body_blk: proc { |inner_body| body = inner_body })
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dialect = compliance.dialect(prompt: compliance.generic_prompt(tools: tools))
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tool_call = endpoint.perform_completion!(dialect, user)
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body_parsed = JSON.parse(body, symbolize_names: true)
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expect(body_parsed[:tools]).to eq(nil)
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expect(body_parsed[:messages][0][:content]).to include("<function_calls>")
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expect(tool_call.name).to eq("get_weather")
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expect(tool_call.parameters).to eq({ location: "Sydney", unit: "c" })
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end
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end
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context "when using regular mode" do
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context "with simple prompts" do
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it "completes a trivial prompt and logs the response" do
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compliance.regular_mode_simple_prompt(open_ai_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(open_ai_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 simple 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(open_ai_mock)
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end
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it "will automatically recover from a bad payload" do
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called = false
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# this should not happen, but lets ensure nothing bad happens
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# the row with test1 is invalid json
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raw_data = <<~TEXT.strip
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d|a|t|a|:| |{|"choices":[{"delta":{"content":"test,"}}]}
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data: {"choices":[{"delta":{"content":"test|1| |,"}}]
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data: {"choices":[{"delta":|{"content":"test2 ,"}}]}
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data: {"choices":[{"delta":{"content":"test3,"}}]|}
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data: {"choices":[{|"|d|elta":{"content":"test4"}}]|}
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data: [D|ONE]
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TEXT
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chunks = raw_data.split("|")
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open_ai_mock.with_chunk_array_support do
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open_ai_mock.stub_raw(chunks)
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partials = []
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endpoint.perform_completion!(compliance.dialect, user) { |partial| partials << partial }
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called = true
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expect(partials.join).to eq("test,test2 ,test3,test4")
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end
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expect(called).to be(true)
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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.streaming_mode_tools(open_ai_mock)
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end
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it "properly handles multiple tool calls" do
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raw_data = <<~TEXT.strip
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data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"role":"assistant","content":null},"logprobs":null,"finish_reason":null}]}
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data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"id":"call_3Gyr3HylFJwfrtKrL6NaIit1","type":"function","function":{"name":"search","arguments":""}}]},"logprobs":null,"finish_reason":null}]}
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data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\\"se"}}]},"logprobs":null,"finish_reason":null}]}
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data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"arch_"}}]},"logprobs":null,"finish_reason":null}]}
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data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"query\\""}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":": \\"D"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"iscou"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"rse AI"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":" bot"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":0,"function":{"arguments":"\\"}"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"id":"call_H7YkbgYurHpyJqzwUN4bghwN","type":"function","function":{"name":"search","arguments":""}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"{\\"qu"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"ery\\":"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":" \\"Disc"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"ours"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"e AI "}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{"tool_calls":[{"index":1,"function":{"arguments":"bot2\\"}"}}]},"logprobs":null,"finish_reason":null}]}
|
|
|
|
data: {"id":"chatcmpl-8xjcr5ZOGZ9v8BDYCx0iwe57lJAGk","object":"chat.completion.chunk","created":1709247429,"model":"gpt-4-0125-preview","system_fingerprint":"fp_91aa3742b1","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"tool_calls"}]}
|
|
|
|
data: [DONE]
|
|
TEXT
|
|
|
|
open_ai_mock.stub_raw(raw_data)
|
|
response = []
|
|
|
|
dialect = compliance.dialect(prompt: compliance.generic_prompt(tools: tools))
|
|
|
|
endpoint.perform_completion!(dialect, user) { |partial| response << partial }
|
|
|
|
tool_calls = [
|
|
DiscourseAi::Completions::ToolCall.new(
|
|
name: "search",
|
|
id: "call_3Gyr3HylFJwfrtKrL6NaIit1",
|
|
parameters: {
|
|
search_query: "Discourse AI bot",
|
|
},
|
|
),
|
|
DiscourseAi::Completions::ToolCall.new(
|
|
name: "search",
|
|
id: "call_H7YkbgYurHpyJqzwUN4bghwN",
|
|
parameters: {
|
|
query: "Discourse AI bot2",
|
|
},
|
|
),
|
|
]
|
|
|
|
expect(response).to eq(tool_calls)
|
|
end
|
|
|
|
it "properly handles newlines" do
|
|
response = <<~TEXT.strip
|
|
data: {"id":"chatcmpl-ASngi346UA9k006bF6GBRV66tEJfQ","object":"chat.completion.chunk","created":1731427548,"model":"gpt-4o-2024-08-06","system_fingerprint":"fp_159d8341cc","choices":[{"index":0,"delta":{"content":":\\n\\n"},"logprobs":null,"finish_reason":null}],"usage":null}
|
|
|
|
data: {"id":"chatcmpl-ASngi346UA9k006bF6GBRV66tEJfQ","object":"chat.completion.chunk","created":1731427548,"model":"gpt-4o-2024-08-06","system_fingerprint":"fp_159d8341cc","choices":[{"index":0,"delta":{"content":"```"},"logprobs":null,"finish_reason":null}],"usage":null}
|
|
|
|
data: {"id":"chatcmpl-ASngi346UA9k006bF6GBRV66tEJfQ","object":"chat.completion.chunk","created":1731427548,"model":"gpt-4o-2024-08-06","system_fingerprint":"fp_159d8341cc","choices":[{"index":0,"delta":{"content":"ruby"},"logprobs":null,"finish_reason":null}],"usage":null}
|
|
|
|
data: {"id":"chatcmpl-ASngi346UA9k006bF6GBRV66tEJfQ","object":"chat.completion.chunk","created":1731427548,"model":"gpt-4o-2024-08-06","system_fingerprint":"fp_159d8341cc","choices":[{"index":0,"delta":{"content":"\\n"},"logprobs":null,"finish_reason":null}],"usage":null}
|
|
|
|
data: {"id":"chatcmpl-ASngi346UA9k006bF6GBRV66tEJfQ","object":"chat.completion.chunk","created":1731427548,"model":"gpt-4o-2024-08-06","system_fingerprint":"fp_159d8341cc","choices":[{"index":0,"delta":{"content":"def"},"logprobs":null,"finish_reason":null}],"usage":null}
|
|
TEXT
|
|
|
|
open_ai_mock.stub_raw(response)
|
|
partials = []
|
|
|
|
dialect = compliance.dialect(prompt: compliance.generic_prompt)
|
|
endpoint.perform_completion!(dialect, user) { |partial| partials << partial }
|
|
|
|
expect(partials).to eq([":\n\n", "```", "ruby", "\n", "def"])
|
|
end
|
|
|
|
it "uses proper token accounting" do
|
|
response = <<~TEXT.strip
|
|
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[{"index":0,"delta":{"role":"assistant","content":""},"logprobs":null,"finish_reason":null}],"usage":null}|
|
|
|
|
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[{"index":0,"delta":{"content":"Hello"},"logprobs":null,"finish_reason":null}],"usage":null}|
|
|
|
|
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[{"index":0,"delta":{},"logprobs":null,"finish_reason":"stop"}],"usage":null}|
|
|
|
|
data: {"id":"chatcmpl-9OZidiHncpBhhNMcqCus9XiJ3TkqR","object":"chat.completion.chunk","created":1715644203,"model":"gpt-4o-2024-05-13","system_fingerprint":"fp_729ea513f7","choices":[],"usage":{"prompt_tokens":20,"completion_tokens":9,"total_tokens":29}}|
|
|
|
|
data: [DONE]
|
|
TEXT
|
|
|
|
chunks = response.split("|")
|
|
open_ai_mock.with_chunk_array_support do
|
|
open_ai_mock.stub_raw(chunks)
|
|
partials = []
|
|
|
|
dialect = compliance.dialect(prompt: compliance.generic_prompt)
|
|
endpoint.perform_completion!(dialect, user) { |partial| partials << partial }
|
|
|
|
expect(partials).to eq(["Hello"])
|
|
|
|
log = AiApiAuditLog.order("id desc").first
|
|
|
|
expect(log.request_tokens).to eq(20)
|
|
expect(log.response_tokens).to eq(9)
|
|
end
|
|
end
|
|
|
|
it "properly handles multiple params in partial tool calls" do
|
|
# this is not working and it is driving me nuts so I will use a sledghammer
|
|
# text = plugin_file_from_fixtures("openai_artifact_call.txt", "bot")
|
|
|
|
path = File.join(__dir__, "../../../fixtures/bot", "openai_artifact_call.txt")
|
|
text = File.read(path)
|
|
|
|
partials = []
|
|
open_ai_mock.with_chunk_array_support do
|
|
open_ai_mock.stub_raw(text.scan(/.*\n/))
|
|
|
|
dialect = compliance.dialect(prompt: compliance.generic_prompt(tools: tools))
|
|
endpoint.perform_completion!(dialect, user, partial_tool_calls: true) do |partial|
|
|
partials << partial.dup
|
|
end
|
|
end
|
|
|
|
expect(partials.compact.length).to eq(128)
|
|
|
|
params =
|
|
partials
|
|
.map { |p| p.parameters if p.is_a?(DiscourseAi::Completions::ToolCall) && p.partial? }
|
|
.compact
|
|
|
|
lengths = {}
|
|
params.each do |p|
|
|
p.each do |k, v|
|
|
if lengths[k] && lengths[k] > v.length
|
|
expect(lengths[k]).to be > v.length
|
|
else
|
|
lengths[k] = v.length
|
|
end
|
|
end
|
|
end
|
|
end
|
|
|
|
it "properly handles spaces in tools payload and partial tool calls" do
|
|
raw_data = <<~TEXT.strip
|
|
data: {"choices":[{"index":0,"delta":{"role":"assistant","content":null,"tool_calls":[{"index":0,"id":"func_id","type":"function","function":{"name":"go|ogle","arg|uments":""}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "{\\""}}]}}]}
|
|
|
|
data: {"ch|oices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "query"}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "\\":\\""}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "Ad"}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "a|b"}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "as"}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": |"| "}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "9"}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "."}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"argume|nts": "1"}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": [{"index": 0, "function": {"arguments": "\\"}"}}]}}]}
|
|
|
|
data: {"choices": [{"index": 0, "delta": {"tool_calls": []}}]}
|
|
|
|
data: [D|ONE]
|
|
TEXT
|
|
|
|
chunks = raw_data.split("|")
|
|
|
|
open_ai_mock.with_chunk_array_support do
|
|
open_ai_mock.stub_raw(chunks)
|
|
partials = []
|
|
|
|
dialect = compliance.dialect(prompt: compliance.generic_prompt(tools: tools))
|
|
endpoint.perform_completion!(dialect, user, partial_tool_calls: true) do |partial|
|
|
partials << partial.dup
|
|
end
|
|
|
|
tool_call =
|
|
DiscourseAi::Completions::ToolCall.new(
|
|
id: "func_id",
|
|
name: "google",
|
|
parameters: {
|
|
query: "Adabas 9.1",
|
|
},
|
|
)
|
|
|
|
expect(partials.last).to eq(tool_call)
|
|
|
|
progress = partials.map { |p| p.parameters[:query] }
|
|
expect(progress).to eq(["Ad", "Adabas", "Adabas 9.", "Adabas 9.1"])
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|
|
end
|