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* 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>
83 lines
1.8 KiB
Ruby
83 lines
1.8 KiB
Ruby
class Assistant::Function
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class << self
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def name
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raise NotImplementedError, "Subclasses must implement the name class method"
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end
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def description
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raise NotImplementedError, "Subclasses must implement the description class method"
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end
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end
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def initialize(user)
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@user = user
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end
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def call(params = {})
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raise NotImplementedError, "Subclasses must implement the call method"
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end
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def name
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self.class.name
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end
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def description
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self.class.description
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end
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def params_schema
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build_schema
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end
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# (preferred) when in strict mode, the schema needs to include all properties in required array
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def strict_mode?
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true
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end
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private
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attr_reader :user
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def build_schema(properties: {}, required: [])
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{
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type: "object",
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properties: properties,
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required: required,
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additionalProperties: false
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}
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end
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def family_account_names
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@family_account_names ||= family.accounts.active.pluck(:name)
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end
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def family_category_names
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@family_category_names ||= begin
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names = family.categories.pluck(:name)
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names << "Uncategorized"
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names
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end
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end
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def family_merchant_names
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@family_merchant_names ||= family.merchants.pluck(:name)
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end
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def family_tag_names
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@family_tag_names ||= family.tags.pluck(:name)
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end
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def family
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user.family
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end
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# To save tokens, we provide the AI metadata about the series and a flat array of
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# raw, formatted values which it can infer dates from
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def to_ai_time_series(series)
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{
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start_date: series.start_date,
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end_date: series.end_date,
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interval: series.interval,
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values: series.values.map { |v| v.trend.current.format }
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}
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end
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end
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