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Personal finance AI (v1) (#2022)
* AI sidebar * Add chat and message models with associations * Implement AI chat functionality with sidebar and messaging system - Add chat and messages controllers - Create chat and message views - Implement chat-related routes - Add message broadcasting and user interactions - Update application layout to support chat sidebar - Enhance user model with initials method * Refactor AI sidebar with enhanced chat menu and interactions - Update sidebar layout with dynamic width and improved responsiveness - Add new chat menu Stimulus controller for toggling between chat and chat list views - Improve chat list display with recent chats and empty state - Extract AI avatar to a partial for reusability - Enhance message display and interaction styling - Add more contextual buttons and interaction hints * Improve chat scroll behavior and message styling - Refactor chat scroll functionality with Stimulus controller - Optimize message scrolling in chat views - Update message styling for better visual hierarchy - Enhance chat container layout with flex and auto-scroll - Simplify message rendering across different chat views * Extract AI avatar to a shared partial for consistent styling - Refactor AI avatar rendering across chat views - Replace hardcoded avatar markup with a reusable partial - Simplify avatar display in chats and messages views * Update sidebar controller to handle right panel width dynamically - Add conditional width class for right sidebar panel - Ensure consistent sidebar toggle behavior for both left and right panels - Use specific width class for right panel (w-[375px]) * Refactor chat form and AI greeting with flexible partials - Extract message form to a reusable partial with dynamic context support - Create flexible AI greeting partial for consistent welcome messages - Simplify chat and sidebar views by leveraging new partials - Add support for different form scenarios (chat, new chat, sidebar) - Improve code modularity and reduce duplication * Add chat clearing functionality with dynamic menu options - Implement clear chat action in ChatsController - Add clear chat route to support clearing messages - Update AI sidebar with dropdown menu for chat actions - Preserve system message when clearing chat - Enhance chat interaction with new menu options * Add frontmatter to project structure documentation - Create initial frontmatter for structure.mdc file - Include description and configuration options - Prepare for potential dynamic documentation rendering * Update general project rules with additional guidelines - Add rule for using `Current.family` instead of `current_family` - Include new guidelines for testing, API routes, and solution approach - Expand project-specific rules for more consistent development practices * Add OpenAI gem and AI-friendly data representations - Add `ruby-openai` gem for AI integration - Implement `to_ai_readable_hash` methods in BalanceSheet and IncomeStatement - Include Promptable module in both models - Add savings rate calculation method in IncomeStatement - Prepare financial models for AI-powered insights and interactions * Enhance AI Financial Assistant with Advanced Querying and Debugging Capabilities - Implement comprehensive AI financial query system with function-based interactions - Add detailed debug logging for AI responses and function calls - Extend BalanceSheet and IncomeStatement models with AI-friendly methods - Create robust error handling and fallback mechanisms for AI queries - Update chat and message views to support debug mode and enhanced rendering - Add AI query routes and initial test coverage for financial assistant * Refactor AI sidebar and chat layout with improved structure and comments - Remove inline AI chat from application layout - Enhance AI sidebar with more semantic HTML structure - Add descriptive comments to clarify different sections of chat view - Improve flex layout and scrolling behavior in chat messages container - Optimize message rendering with more explicit class names and structure * Add Markdown rendering support for AI chat messages - Implement `markdown` helper method in ApplicationHelper using Redcarpet - Update message view to render AI messages with Markdown formatting - Add comprehensive Markdown rendering options (tables, code blocks, links) - Enhance AI Financial Assistant prompt to encourage Markdown usage - Remove commented Markdown CSS in Tailwind application stylesheet * Missing comma * Enhance AI response processing with chat history context * Improve AI debug logging with payload size limits and internal message flag * Enhance AI chat interaction with improved thinking indicator and scrolling behavior * Add AI consent and enable/disable functionality for AI chat * Upgrade Biome and refactor JavaScript template literals - Update @biomejs/biome to latest version with caret (^) notation - Refactor AI query and chat controllers to use template literals - Standardize npm scripts formatting in package.json * Add beta testing usage note to AI consent modal * Update test fixtures and configurations for AI chat functionality - Add family association to chat fixtures and tests - Set consistent password digest for test users - Enable AI for test users - Add OpenAI access token for test environment - Update chat and user model tests to include family context * Simplify data model and get tests passing * Remove structure.mdc from version control * Integrate AI chat styles into existing prose pattern * Match Figma design spec, implement Turbo frames and actions for chats controller * AI rules refresh * Consolidate Stimulus controllers, thinking state, controllers, and views * Naming, domain alignment * Reset migrations * Improve data model to support tool calls and message types * Tool calling tests and fixtures * Tool call implementation and test * Get assistant test working again * Test updates * Process tool calls within provider * Chat UI back to working state again * Remove stale code * Tests passing * Update openai class naming to avoid conflicts * Reconfigure test env * Rebuild gemfile * Fix naming conflicts for ChatResponse * Message styles * Use OpenAI conversation state management * Assistant function base implementation * Add back thinking messages, clean up error handling for chat * Fix sync error when security price has bad data from provider * Add balance sheet function to assistant * Add better function calling error visibility * Add income statement function * Simplify and clean up "thinking" interactions with Turbo frames * Remove stale data definitions from functions * Ensure VCR fixtures working with latest code * basic stream implementation * Get streaming working * Make AI sidebar wider when left sidebar is collapsed * Get tests working with streaming responses * Centralize provider error handling * Provider data boundaries --------- Co-authored-by: Josh Pigford <josh@joshpigford.com>
This commit is contained in:
Zach Gollwitzer
GitHub
parent
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commit
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126 changed files with 3576 additions and 462 deletions
86
test/models/assistant_test.rb
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86
test/models/assistant_test.rb
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require "test_helper"
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require "ostruct"
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class AssistantTest < ActiveSupport::TestCase
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include ProviderTestHelper
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setup do
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@chat = chats(:two)
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@message = @chat.messages.create!(
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type: "UserMessage",
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content: "Help me with my finances",
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ai_model: "gpt-4o"
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)
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@assistant = Assistant.for_chat(@chat)
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@provider = mock
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@assistant.expects(:get_model_provider).with("gpt-4o").returns(@provider)
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end
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test "responds to basic prompt" do
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text_chunk = OpenStruct.new(type: "output_text", data: "Hello from assistant")
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response_chunk = OpenStruct.new(
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type: "response",
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data: OpenStruct.new(
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id: "1",
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model: "gpt-4o",
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messages: [
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OpenStruct.new(
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id: "1",
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content: "Hello from assistant",
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)
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],
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functions: []
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)
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)
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@provider.expects(:chat_response).with do |message, **options|
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options[:streamer].call(text_chunk)
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options[:streamer].call(response_chunk)
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true
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end
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assert_difference "AssistantMessage.count", 1 do
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@assistant.respond_to(@message)
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end
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end
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test "responds with tool function calls" do
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function_request_chunk = OpenStruct.new(type: "function_request", data: "get_net_worth")
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text_chunk = OpenStruct.new(type: "output_text", data: "Your net worth is $124,200")
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response_chunk = OpenStruct.new(
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type: "response",
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data: OpenStruct.new(
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id: "1",
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model: "gpt-4o",
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messages: [
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OpenStruct.new(
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id: "1",
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content: "Your net worth is $124,200",
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)
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],
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functions: [
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OpenStruct.new(
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id: "1",
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call_id: "1",
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name: "get_net_worth",
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arguments: "{}",
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result: "$124,200"
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)
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]
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)
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)
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@provider.expects(:chat_response).with do |message, **options|
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options[:streamer].call(function_request_chunk)
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options[:streamer].call(text_chunk)
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options[:streamer].call(response_chunk)
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true
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end
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assert_difference "AssistantMessage.count", 1 do
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@assistant.respond_to(@message)
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message = @chat.messages.ordered.where(type: "AssistantMessage").last
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assert_equal 1, message.tool_calls.size
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end
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end
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end
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