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Get streaming working

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This commit is contained in:
Zach Gollwitzer
2025-03-27 08:02:29 -04:00
parent e03f88a18c
commit ce042fd250
9 changed files with 439 additions and 105 deletions
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62
app/models/assistant.rb
View File

@@ -1,3 +1,8 @@
# Orchestrates LLM interactions for chat conversations by:
# - Streaming generic provider responses
# - Persisting messages and tool calls
# - Broadcasting updates to chat UI
# - Handling provider errors
class Assistant
include Provided
@@ -14,42 +19,61 @@ class Assistant
end
def respond_to(message)
chat.clear_error
sleep artificial_thinking_delay
provider = get_model_provider(message.ai_model)
response = provider.chat_response(
assistant_message = AssistantMessage.new(
chat: chat,
content: "",
ai_model: message.ai_model
)
streamer = proc do |chunk|
case chunk.type
when "output_text"
stop_thinking
assistant_message.content += chunk.data
assistant_message.save!
when "function_request"
update_thinking("Analyzing your data to assist you with your question...")
when "response"
stop_thinking
assistant_message.ai_model = chunk.data.model
combined_tool_calls = chunk.data.functions.map do |tc|
ToolCall::Function.new(
provider_id: tc.id,
provider_call_id: tc.call_id,
function_name: tc.name,
function_arguments: tc.arguments,
function_result: tc.result
)
end
assistant_message.tool_calls = combined_tool_calls
assistant_message.save!
chat.update!(latest_assistant_response_id: chunk.data.id)
end
end
provider.chat_response(
message,
instructions: instructions,
available_functions: functions,
streamer: streamer
)
stop_thinking
unless response.success?
return chat.add_error(response.error)
end
Chat.transaction do
chat.clear_error
process_response_artifacts(response.data)
chat.update!(latest_assistant_response_id: response.data.id)
end
rescue => e
chat.add_error(e)
end
private
def streamer
proc do |data|
puts data
# TODO process data
end
def update_thinking(thought)
chat.broadcast_update target: "thinking-indicator", partial: "chats/thinking_indicator", locals: { chat: chat, message: thought }
end
def stop_thinking
sleep artificial_thinking_delay
chat.broadcast_remove target: "thinking-indicator"
end

4
app/models/provider/openai.rb
View File

@@ -29,9 +29,9 @@ class Provider::Openai < Provider
processor = ChatResponseProcessor.new(
client: client,
message: message,
streamer: streamer,
instructions: instructions,
available_functions: available_functions
available_functions: available_functions,
streamer: streamer
)
processor.process

30
app/models/provider/openai/chat_response_processor.rb
View File

@@ -10,7 +10,13 @@ class Provider::Openai::ChatResponseProcessor
def process
first_response = fetch_response(previous_response_id: previous_openai_response_id)
return first_response if first_response.functions.empty?
if first_response.functions.empty?
if streamer.present?
streamer.call(StreamChunk.new(type: "response", data: first_response))
end
return first_response
end
executed_functions = execute_pending_functions(first_response.functions)
@@ -19,6 +25,10 @@ class Provider::Openai::ChatResponseProcessor
previous_response_id: first_response.id
)
if streamer.present?
streamer.call(StreamChunk.new(type: "response", data: follow_up_response))
end
follow_up_response
end
@@ -59,24 +69,6 @@ class Provider::Openai::ChatResponseProcessor
streamer.call(StreamChunk.new(type: "output_text", data: chunk.dig("delta")))
when "response.function_call_arguments.done"
streamer.call(StreamChunk.new(type: "function_request", data: chunk.dig("arguments")))
when "response.completed"
res = chunk.dig("response")
res_output = res.dig("output")
functions_output = if executed_functions.any?
executed_functions
else
extract_pending_functions(res_output)
end
data = Response.new(
id: res.dig("id"),
messages: extract_messages(res_output),
functions: functions_output,
model: res.dig("model")
)
streamer.call(StreamChunk.new(type: "response", data: data))
end
end

17
test/interfaces/llm_interface_test.rb
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@@ -3,23 +3,6 @@ require "test_helper"
module LLMInterfaceTest
extend ActiveSupport::Testing::Declarative
test "provides basic chat response" do
VCR.use_cassette("#{vcr_key_prefix}/chat/basic_response") do
chat = chats(:two)
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(message)
assert response.success?
assert_equal 1, response.data.messages.size
assert_includes response.data.messages.first.content, "Yes"
end
end
private
def vcr_key_prefix
@subject.class.name.demodulize.underscore

6
test/models/assistant_test.rb
View File

@@ -12,6 +12,12 @@ class AssistantTest < ActiveSupport::TestCase
end
test "responds to basic prompt without tools" do
collected_chunks = []
streamer = proc do |chunk|
collected_chunks << chunk
end
@provider.expects(:chat_response).returns(
provider_success_response(
Assistant::Provideable::ChatResponse.new(

118
test/models/provider/openai_test.rb
View File

@@ -6,14 +6,13 @@ 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
chat = chats(:two)
response = @openai.chat_response(UserMessage.new(
chat: chat,
chat: @chat,
content: "Error test",
ai_model: "invalid-model-that-will-trigger-api-error"
))
@@ -23,10 +22,9 @@ class Provider::OpenaiTest < ActiveSupport::TestCase
end
end
test "provides basic chat response 2" do
VCR.use_cassette("openai/chat/basic_response", record: :all) do
chat = chats(:two)
message = chat.messages.create!(
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
@@ -40,35 +38,40 @@ class Provider::OpenaiTest < ActiveSupport::TestCase
end
end
test "handles chat response with tool calls" do
VCR.use_cassette("openai/chat/tool_calls", record: :all) do
class PredictableToolFunction < Assistant::Function
class << self
def expected_test_result
"$124,200"
end
test "streams basic chat response" do
VCR.use_cassette("openai/chat/basic_response") do
collected_chunks = []
def name
"get_net_worth"
end
def description
"Gets user net worth data"
end
end
def call(params = {})
self.class.expected_test_result
end
mock_streamer = proc do |chunk|
collected_chunks << chunk
end
chat = chats(:two)
initial_message = UserMessage.new(chat: chat, content: "What is my net worth?", ai_model: @subject_model)
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 = @openai.chat_response(
initial_message,
@subject.chat_response(message, streamer: mock_streamer)
tool_call_chunks = collected_chunks.select { |chunk| chunk.type == "function_request" }
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
end
end
test "chat response with tool calls" do
VCR.use_cassette("openai/chat/tool_calls") do
response = @subject.chat_response(
tool_call_message,
instructions: "Use the tools available to you to answer the user's question.",
available_functions: [ PredictableToolFunction.new(chat) ]
available_functions: [ PredictableToolFunction.new(@chat) ]
)
assert response.success?
@@ -77,4 +80,57 @@ class Provider::OpenaiTest < ActiveSupport::TestCase
assert_includes response.data.messages.first.content, PredictableToolFunction.expected_test_result
end
end
test "streams chat response with tool calls" do
VCR.use_cassette("openai/chat/tool_calls") do
collected_chunks = []
mock_streamer = proc do |chunk|
collected_chunks << chunk
end
@subject.chat_response(
tool_call_message,
instructions: "Use the tools available to you to answer the user's question.",
available_functions: [ PredictableToolFunction.new(@chat) ],
streamer: mock_streamer
)
text_chunks = collected_chunks.select { |chunk| chunk.type == "output_text" }
text_chunks = collected_chunks.select { |chunk| chunk.type == "output_text" }
tool_call_chunks = collected_chunks.select { |chunk| chunk.type == "function_request" }
response_chunks = collected_chunks.select { |chunk| chunk.type == "response" }
assert_equal 1, tool_call_chunks.count
assert text_chunks.count >= 1
assert_equal 1, response_chunks.count
assert_includes response_chunks.first.data.messages.first.content, 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 << self
def expected_test_result
"$124,200"
end
def name
"get_net_worth"
end
def description
"Gets user net worth data"
end
end
def call(params = {})
self.class.expected_test_result
end
end
end

34
test/vcr_cassettes/openai/chat/basic_response.yml
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