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Code Issues Releases Activity Actions

Rework Assistant, Provider, and tests for better domain boundaries

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This commit is contained in:
Zach Gollwitzer 2025-03-28 19:39:48 -04:00
parent 56d78b50ce
commit b9681d9cee
10 changed files with 420 additions and 212 deletions
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25
app/models/assistant.rb
View file

@ -30,8 +30,8 @@ class Assistant
result = fn.call(args)
ToolCall::Function.new(
provider_id: function_request.provider_id,
provider_call_id: function_request.provider_call_id,
provider_id: function_request.id,
provider_call_id: function_request.call_id,
function_name: name,
function_arguments: args,
function_result: result
@ -70,7 +70,19 @@ class Assistant
ai_model: message.ai_model
)
streamer = proc do |chunk|
streamer2 = proc do |chunk|
case chunk.type
when "output_text"
stop_thinking
assistant_response.content += chunk.data
assistant_response.save!
when "response"
stop_thinking
chat.update!(latest_assistant_response_id: chunk.data.id)
end
end
streamer1 = proc do |chunk|
case chunk.type
when "output_text"
stop_thinking
@ -93,7 +105,7 @@ class Assistant
instructions: instructions,
functions: functions.map(&:to_h),
function_results: tool_calls.map(&:to_h),
streamer: streamer
streamer: streamer2
)
else
stop_thinking
@ -109,7 +121,7 @@ class Assistant
instructions: instructions,
functions: functions.map(&:to_h),
function_results: [],
streamer: streamer
streamer: streamer1
)
rescue => e
chat.add_error(e)
@ -151,7 +163,7 @@ class Assistant
- Format all responses in markdown
- Format all monetary values according to the user's preferred currency
- Format dates in the user's preferred format
- Format dates in the user's preferred format: #{preferred_date_format}
#### User's preferred currency
@ -165,7 +177,6 @@ class Assistant
- Default format: #{preferred_currency.default_format}
- Separator: #{preferred_currency.separator}
- Delimiter: #{preferred_currency.delimiter}
- Date format: #{preferred_date_format}
### Rules about financial advice

14
app/models/provider/llm_provider.rb
View file

@ -1,17 +1,13 @@
module Provider::LlmProvider
extend ActiveSupport::Concern
def chat_response(message, instructions: nil, available_functions: [], streamer: nil)
def chat_response(prompt, model:, instructions: nil, functions: [], function_results: [], streamer: nil, previous_response_id: nil)
raise NotImplementedError, "Subclasses must implement #chat_response"
end
private
StreamChunk = Data.define(:provider_type, :data)
ChatResponse = Data.define(:provider_id, :model, :messages, :function_calls) do
def final?
function_calls.empty?
end
end
Message = Data.define(:provider_id, :content)
FunctionCall = Data.define(:provider_id, :provider_call_id, :name, :arguments, :result)
Message = Data.define(:id, :output_text)
StreamChunk = Data.define(:type, :data)
ChatResponse = Data.define(:id, :model, :messages, :function_requests)
FunctionRequest = Data.define(:id, :call_id, :function_name, :function_args)
end

63
app/models/provider/openai.rb
View file

@ -1,5 +1,5 @@
class Provider::Openai < Provider
include LlmProvider
include LlmProvider, Parser
# Subclass so errors caught in this provider are raised as Provider::Openai::Error
Error = Class.new(Provider::Error)
@ -14,10 +14,42 @@ class Provider::Openai < Provider
MODELS.include?(model)
end
def chat_response(prompt, model:, instructions: nil, functions: [], function_results: [], previous_response_id: nil)
def chat_response(prompt, model:, instructions: nil, functions: [], function_results: [], streamer: nil, previous_response_id: nil)
with_provider_response do
proxy_streamer = proc do |chunk|
type = chunk.dig("type")
case type
when "response.output_text.delta", "response.refusal.delta"
streamer.call(StreamChunk.new(type: "output_text", data: chunk.dig("delta")))
when "response.completed"
raw_response = chunk.dig("response")
messages = extract_messages(raw_response).map do |message|
Message.new(
id: message[:id],
output_text: message[:output_text]
)
end
function_requests = extract_function_requests(raw_response).map do |function_request|
FunctionRequest.new(
id: function_request[:id],
call_id: function_request[:call_id],
function_name: function_request[:name],
function_args: function_request[:arguments]
)
end
response = ChatResponse.new(
id: extract_id(raw_response),
model: extract_model(raw_response),
messages: messages,
function_requests: function_requests
)
streamer.call(StreamChunk.new(type: "response", data: response))
end
end
function_results_input = function_results.map do |fn_result|
@ -40,14 +72,37 @@ class Provider::Openai < Provider
}
end
client.responses.create(parameters: {
raw_response = client.responses.create(parameters: {
model: model,
input: prompt_input + function_results_input,
instructions: instructions,
tools: tools,
previous_response_id: previous_response_id,
stream: streamer
stream: streamer.present? ? proxy_streamer : nil
})
messages = extract_messages(raw_response).map do |message|
Message.new(
id: message[:id],
output_text: message[:output_text]
)
end
function_requests = extract_function_requests(raw_response).map do |function_request|
FunctionRequest.new(
id: function_request[:id],
call_id: function_request[:call_id],
function_name: function_request[:name],
function_args: function_request[:arguments]
)
end
ChatResponse.new(
id: extract_id(raw_response),
model: extract_model(raw_response),
messages: messages,
function_requests: function_requests
)
end
end

73
test/models/assistant_test.rb
View file

@ -19,19 +19,14 @@ class AssistantTest < ActiveSupport::TestCase
test "responds to basic prompt" do
text_chunk = OpenStruct.new(type: "output_text", data: "Hello from assistant")
response_chunk = OpenStruct.new(
type: "response",
data: OpenStruct.new(
id: "1",
model: "gpt-4o",
messages: [
OpenStruct.new(
id: "1",
content: "Hello from assistant",
)
],
functions: []
type: "response",
data: OpenStruct.new(
id: "1",
model: "gpt-4o",
messages: [ OpenStruct.new(id: "1", output_text: "Hello from assistant") ],
function_requests: []
)
)
)
@provider.expects(:chat_response).with do |message, **options|
options[:streamer].call(text_chunk)
@ -45,37 +40,57 @@ class AssistantTest < ActiveSupport::TestCase
end
test "responds with tool function calls" do
function_request_chunk = OpenStruct.new(type: "function_request", data: "get_net_worth")
text_chunk = OpenStruct.new(type: "output_text", data: "Your net worth is $124,200")
response_chunk = OpenStruct.new(
Assistant::Function::GetAccounts.any_instance.stubs(:call).returns("test value")
# Call #1: Function requests
call1_response_chunk = OpenStruct.new(
type: "response",
data: OpenStruct.new(
id: "1",
model: "gpt-4o",
messages: [
OpenStruct.new(
id: "1",
content: "Your net worth is $124,200",
)
],
functions: [
messages: [],
function_requests: [
OpenStruct.new(
id: "1",
call_id: "1",
name: "get_net_worth",
arguments: "{}",
result: "$124,200"
function_name: "get_accounts",
function_arguments: "{}",
)
]
)
)
# Call #2: Text response (that uses function results)
call2_text_chunk = OpenStruct.new(type: "output_text", data: "Your net worth is $124,200")
call2_response_chunk = OpenStruct.new(type: "response", data: OpenStruct.new(
id: "2",
model: "gpt-4o",
messages: [ OpenStruct.new(id: "1", output_text: "Your net worth is $124,200") ],
function_requests: [],
function_results: [
OpenStruct.new(
provider_id: "1",
provider_call_id: "1",
name: "get_accounts",
arguments: "{}",
result: "test value"
)
],
previous_response_id: "1"
))
sequence = sequence("provider_chat_response")
@provider.expects(:chat_response).with do |message, **options|
options[:streamer].call(function_request_chunk)
options[:streamer].call(text_chunk)
options[:streamer].call(response_chunk)
options[:streamer].call(call2_text_chunk)
options[:streamer].call(call2_response_chunk)
true
end
end.returns(nil).once.in_sequence(sequence)
@provider.expects(:chat_response).with do |message, **options|
options[:streamer].call(call1_response_chunk)
true
end.returns(nil).once.in_sequence(sequence)
assert_difference "AssistantMessage.count", 1 do
@assistant.respond_to(@message)

157
test/models/provider/openai_test.rb
View file

@ -6,16 +6,11 @@ class Provider::OpenaiTest < ActiveSupport::TestCase
setup do
@subject = @openai = Provider::Openai.new(ENV.fetch("OPENAI_ACCESS_TOKEN", "test-openai-token"))
@subject_model = "gpt-4o"
@chat = chats(:two)
end
test "openai errors are automatically raised" do
VCR.use_cassette("openai/chat/error") do
response = @openai.chat_response(UserMessage.new(
chat: @chat,
content: "Error test",
ai_model: "invalid-model-that-will-trigger-api-error"
))
response = @openai.chat_response("Test", model: "invalid-model-that-will-trigger-api-error")
assert_not response.success?
assert_kind_of Provider::Openai::Error, response.error
@ -24,19 +19,14 @@ class Provider::OpenaiTest < ActiveSupport::TestCase
test "basic chat response" do
VCR.use_cassette("openai/chat/basic_response") do
message = @chat.messages.create!(
type: "UserMessage",
content: "This is a chat test. If it's working, respond with a single word: Yes",
ai_model: @subject_model
response = @subject.chat_response(
"This is a chat test. If it's working, respond with a single word: Yes",
model: @subject_model
)
response = @subject.chat_response(message)
assert response.success?
assert_equal 1, response.data.size
assert response.data.first.final?
assert_equal 1, response.data.first.messages.size
assert_includes response.data.first.messages.first.content, "Yes"
assert_equal 1, response.data.messages.size
assert_includes response.data.messages.first.output_text, "Yes"
end
end
@ -44,89 +34,120 @@ class Provider::OpenaiTest < ActiveSupport::TestCase
VCR.use_cassette("openai/chat/basic_streaming_response") do
collected_chunks = []
mock_subscriber = proc do |chunk|
mock_streamer = proc do |chunk|
collected_chunks << chunk
end
message = @chat.messages.create!(
type: "UserMessage",
content: "This is a chat test. If it's working, respond with a single word: Yes",
ai_model: @subject_model
@subject.chat_response(
"This is a chat test. If it's working, respond with a single word: Yes",
model: @subject_model,
streamer: mock_streamer
)
@subject.chat_response(message, stream_subscriber: mock_subscriber)
tool_call_chunks = collected_chunks.select { |chunk| chunk.provider_type == "function_request" }
text_chunks = collected_chunks.select { |chunk| chunk.provider_type == "output_text" }
response_chunks = collected_chunks.select { |chunk| chunk.provider_type == "response" }
text_chunks = collected_chunks.select { |chunk| chunk.type == "output_text" }
response_chunks = collected_chunks.select { |chunk| chunk.type == "response" }
assert_equal 1, text_chunks.size
assert_equal 1, response_chunks.size
assert_equal 0, tool_call_chunks.size
assert_equal "Yes", text_chunks.first.data
assert_equal "Yes", response_chunks.first.data.messages.first.content
assert_equal "Yes", response_chunks.first.data.messages.first.output_text
end
end
test "chat response with tool calls" do
VCR.use_cassette("openai/chat/tool_calls") do
response = @subject.chat_response(
tool_call_message,
test "chat response with function calls" do
VCR.use_cassette("openai/chat/function_calls") do
first_response = @subject.chat_response(
"What is my net worth?",
model: @subject_model,
instructions: "Use the tools available to you to answer the user's question.",
available_functions: [ PredictableToolFunction.new(@chat) ]
functions: [ PredictableToolFunction.new.to_h ]
)
# Two responses: one for function requests, one follow-up for text output
assert response.success?
assert_equal 2, response.data.size
assert first_response.success?
# First response has function requests / results
assert_not response.data.first.final?
assert_equal 1, response.data.first.function_calls.size
function_request = first_response.data.function_requests.first
# Second response has text output that uses the function results
assert response.data.last.final?
assert_equal 0, response.data.last.function_calls.size
assert_equal 1, response.data.last.messages.size
assert_includes response.data.last.messages.first.content, PredictableToolFunction.expected_test_result
assert function_request.present?
second_response = @subject.chat_response(
"What is my net worth?",
model: @subject_model,
function_results: [
{
provider_id: function_request.id,
provider_call_id: function_request.call_id,
name: function_request.function_name,
arguments: function_request.function_args,
result: PredictableToolFunction.expected_test_result
}
],
previous_response_id: first_response.data.id
)
assert second_response.success?
assert_equal 1, second_response.data.messages.size
assert_includes second_response.data.messages.first.output_text, PredictableToolFunction.expected_test_result
end
end
test "streams chat response with tool calls" do
VCR.use_cassette("openai/chat/streaming_tool_calls") do
VCR.use_cassette("openai/chat/streaming_tool_calls", record: :all) do
collected_chunks = []
mock_streamer = proc do |chunk|
collected_chunks << chunk
end
# Call #1: First streaming call, will return a function request
@subject.chat_response(
tool_call_message,
"What is my net worth?",
model: @subject_model,
instructions: "Use the tools available to you to answer the user's question.",
available_functions: [ PredictableToolFunction.new(@chat) ],
functions: [ PredictableToolFunction.new.to_h ],
streamer: mock_streamer
)
text_chunks = collected_chunks.select { |chunk| chunk.provider_type == "output_text" }
tool_call_chunks = collected_chunks.select { |chunk| chunk.provider_type == "function_request" }
response_chunks = collected_chunks.select { |chunk| chunk.provider_type == "response" }
text_chunks = collected_chunks.select { |chunk| chunk.type == "output_text" }
response_chunks = collected_chunks.select { |chunk| chunk.type == "response" }
assert_equal 1, tool_call_chunks.count
assert text_chunks.count >= 1
assert_equal 2, response_chunks.count
assert_equal 0, text_chunks.size
assert_equal 1, response_chunks.size
assert_not response_chunks.first.data.final?
assert response_chunks.last.data.final?
assert_includes response_chunks.last.data.messages.first.content, PredictableToolFunction.expected_test_result
first_response = response_chunks.first.data
function_request = first_response.function_requests.first
# Reset collected chunks
collected_chunks = []
# Call #2: Second streaming call, will return a function result
@subject.chat_response(
"What is my net worth?",
model: @subject_model,
function_results: [
{
provider_id: function_request.id,
provider_call_id: function_request.call_id,
name: function_request.function_name,
arguments: function_request.function_args,
result: PredictableToolFunction.expected_test_result
}
],
previous_response_id: first_response.id,
streamer: mock_streamer
)
text_chunks = collected_chunks.select { |chunk| chunk.type == "output_text" }
response_chunks = collected_chunks.select { |chunk| chunk.type == "response" }
assert text_chunks.size >= 1
assert_equal 1, response_chunks.size
assert_includes response_chunks.first.data.messages.first.output_text, PredictableToolFunction.expected_test_result
end
end
private
def tool_call_message
UserMessage.new(chat: @chat, content: "What is my net worth?", ai_model: @subject_model)
end
class PredictableToolFunction < Assistant::Function
class PredictableToolFunction
class << self
def expected_test_result
"$124,200"
@ -144,5 +165,19 @@ class Provider::OpenaiTest < ActiveSupport::TestCase
def call(params = {})
self.class.expected_test_result
end
def to_h
{
name: self.class.name,
description: self.class.description,
params_schema: {
type: "object",
properties: {},
required: [],
additionalProperties: false
},
strict: true
}
end
end
end

26
test/vcr_cassettes/openai/chat/basic_response.yml
View file

@ -24,7 +24,7 @@ http_interactions:
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@ -73,7 +73,7 @@ http_interactions:
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@ -111,10 +111,10 @@ http_interactions:
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recorded_with: VCR 6.3.1

34
test/vcr_cassettes/openai/chat/basic_streaming_response.yml
View file

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19
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142
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