mirror of
https://github.com/InvoiceShelf/InvoiceShelf.git
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Second phase of the AI feature. Users can now open a slide-in chat drawer from the SiteHeader and ask natural-language questions about their company's invoices, customers, payments, and expenses. The LLM invokes pre-defined read-only tool functions (scoped to the current company at execute time) to fetch data and synthesize answers.
**Database** — new ai_conversations and ai_messages tables. Messages are stored in OpenAI's chat format so AiAssistantService serializes a conversation into an API request with zero translation. Columns: role, content, tool_call_id, tool_calls JSON, model, tokens_in, tokens_out. Conversations are scoped (company_id, user_id) — one user's chats are invisible to everyone else, even inside the same company. Foreign-key cascade deletes.
**Tool infrastructure** — AiTool abstract base + AiToolRegistry singleton (registered in a new AiServiceProvider). The base class enforces the security rule: every tool's execute() receives companyId and userId as injected parameters; tools' JSON schemas NEVER include a company_id field. An LLM physically cannot pass a company_id and escape tenancy. Modules can register their own tools by resolving the registry from their own ServiceProvider::boot().
**Nine built-in tools**: search_invoices, get_invoice, search_customers, get_customer, list_recent_payments, list_overdue_invoices, get_company_stats (aggregates for named periods), search_items, list_expense_categories. All read-only; no mutations. Each returns JSON-encodable data the LLM can parse.
**AiAssistantService orchestration loop** — the heart of Phase 2. Flow: persist user message → build payload from system prompt + recent history (40-message window) + new user message → call driver.chatCompletion with tools → if tool_calls, execute each one via the registry (with injected scope), persist tool result, loop → if plain text, persist and return. Hard cap at 5 iterations to prevent runaway LLMs. System prompt pins the assistant to this company's data and forbids mutation.
**Controllers + policy + rate limit** — POST /api/v1/ai/chat runs the orchestration loop. GET/PATCH/DELETE /api/v1/ai/conversations for CRUD. AiConversationPolicy enforces user_id+company_id match on every action. A new 'ai' RateLimiter in RouteServiceProvider throttles to 30 req/min per (user, company). New 'use ai' Gate defined in AppServiceProvider returns true for any authenticated user — the per-company kill-switch still goes through AiConfigurationService::resolveForCompany.
**Frontend** — new features/company/ai/ folder with a Pinia store (ai-chat.store.ts) holding drawer state, current conversation, messages, and loading flags. AiChatDrawer.vue is a slide-in panel teleported to <body>, mounted globally in CompanyLayout.vue when bootstrap reports ai.enabled && ai.chat_enabled. Sub-components: AiChatMessage (user bubbles vs assistant bubbles), AiChatMessageInput (Enter submits, Shift+Enter newline), AiChatConversationList (sidebar with 'new chat' button, rename, delete). A SparklesIcon button in SiteHeader toggles the drawer.
**Driver test double** — tests use a ScriptedAiDriver registered via AiDriverFactory::register('scripted', ...) that returns pre-queued AiChatResponse objects. Feature tests cover: happy path (new conversation + message persistence), tool-call loop (multi-round-trip with search_invoices), runaway-loop cap, driver-throws path, ai_enabled=NO rejection, chat role disabled rejection, per-user conversation visibility, cross-user policy enforcement, cascade delete.
388 tests pass (was 372, +16 new). Pint clean. npm run build clean. Phase 3 (WYSIWYG text generation popup) is the remaining follow-up.
86 lines
3.0 KiB
PHP
86 lines
3.0 KiB
PHP
<?php
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namespace App\Services\Ai\Tools;
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use App\Models\Invoice;
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/**
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* Fetch one invoice's full details by invoice_number, including items and taxes.
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*/
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class GetInvoiceTool extends AiTool
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{
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public function name(): string
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{
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return 'get_invoice';
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}
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public function description(): string
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{
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return 'Fetch full details for a single invoice by its invoice_number, including line items, taxes, totals, customer info, and dates. Use this after search_invoices when the user wants more detail on a specific invoice.';
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}
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public function parameterSchema(): array
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{
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return [
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'type' => 'object',
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'properties' => [
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'invoice_number' => [
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'type' => 'string',
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'description' => 'The invoice_number to look up (e.g. "INV-000001").',
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],
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],
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'required' => ['invoice_number'],
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];
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}
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public function execute(array $arguments, int $companyId, int $userId): mixed
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{
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$invoice = Invoice::query()
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->where('company_id', $companyId)
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->where('invoice_number', (string) ($arguments['invoice_number'] ?? ''))
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->with(['customer:id,name,email,phone', 'items', 'taxes'])
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->first();
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if (! $invoice) {
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return ['error' => 'invoice_not_found'];
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}
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return [
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'invoice' => [
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'id' => $invoice->id,
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'invoice_number' => $invoice->invoice_number,
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'reference_number' => $invoice->reference_number,
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'status' => $invoice->status,
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'paid_status' => $invoice->paid_status,
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'invoice_date' => $this->asDate($invoice->invoice_date),
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'due_date' => $this->asDate($invoice->due_date),
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'sub_total' => $invoice->sub_total,
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'tax' => $invoice->tax,
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'discount' => $invoice->discount,
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'total' => $invoice->total,
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'due_amount' => $invoice->due_amount,
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'overdue' => (bool) $invoice->overdue,
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'notes' => $invoice->notes,
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'customer' => $invoice->customer ? [
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'id' => $invoice->customer->id,
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'name' => $invoice->customer->name,
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'email' => $invoice->customer->email,
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'phone' => $invoice->customer->phone,
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] : null,
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'items' => $invoice->items->map(fn ($item): array => [
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'name' => $item->name,
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'description' => $item->description,
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'quantity' => $item->quantity,
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'price' => $item->price,
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'total' => $item->total,
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])->all(),
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'taxes' => $invoice->taxes->map(fn ($tax): array => [
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'name' => $tax->name,
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'percent' => $tax->percent,
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'amount' => $tax->amount,
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])->all(),
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],
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];
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}
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}
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