Add savings chat analysis feature
This commit is contained in:
Matthias
399
convex/savingsChat.ts
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399
convex/savingsChat.ts
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@@ -0,0 +1,399 @@
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import { action, internalQuery, query } from "./_generated/server";
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import { v } from "convex/values";
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import { generateText } from "ai";
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import { openai } from "@ai-sdk/openai";
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import { internal } from "./_generated/api";
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import { bookingMonth } from "./lib/month";
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import { requireUserId } from "./lib/helpers";
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import type { Doc, Id } from "./_generated/dataModel";
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import type { QueryCtx } from "./_generated/server";
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type ChatRole = "user" | "assistant";
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type ChatMessage = { role: ChatRole; content: string };
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const chatMessageValidator = v.object({
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role: v.union(v.literal("user"), v.literal("assistant")),
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content: v.string(),
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});
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const MAX_CONVERSATION_MESSAGES = 20;
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const MAX_PROMPT_CHARACTERS = 180_000;
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type ChatContextArgs = {
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from: string;
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to: string;
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accountId?: Id<"accounts">;
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basis: "effective" | "booking";
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};
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type ChatContextSummary = {
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from: string;
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to: string;
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basis: "effective" | "booking";
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accountId?: Id<"accounts">;
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accountName?: string;
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totals: { transactionCount: number; income: number; expenses: number; balance: number };
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isComplete: true;
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};
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type ChatPromptContext = ChatContextSummary & {
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transactionLines: string[];
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};
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type ChatAskResult = {
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model: string;
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answer: string;
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usedTransactions: number;
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usedBalance: { income: number; expenses: number; balance: number };
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};
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function formatEuro(value: number): string {
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return `${value.toFixed(2)}€`;
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}
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function buildSystemPrompt(context: { from: string; to: string; basis: string; accountName?: string }) {
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return [
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"Du bist ein präziser Finanz-Chat-Assistent für Privatanwender.",
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"Nutze ausschließlich die gelieferten Umsätze als Kontext und beziehe dich nur auf die angegebenen Werte.",
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"Antworte auf Deutsch, kurz und handlungsorientiert.",
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`Zeitraum: ${context.from} bis ${context.to}.`,
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`Basis: ${context.basis}.`,
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context.accountName ? `Konto: ${context.accountName}.` : "Konto: Alle Konten.",
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"Wenn eine Aussage nur grob geschätzt werden kann, kennzeichne sie als Schätzung.",
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"Verwende keine Links, keine HTML-Tags und keine Emojis.",
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].join(" ");
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}
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function buildPrompt(context: ChatPromptContext, conversation: ChatMessage[]) {
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return [
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"Kontext der Auswertung:",
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`Zeitraum: ${context.from} bis ${context.to}`,
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`Basis: ${context.basis}`,
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`Konto: ${context.accountName ?? "Alle Konten"}`,
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`Anzahl Umsätze: ${context.totals.transactionCount}`,
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`Einnahmen: ${formatEuro(context.totals.income)}`,
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`Ausgaben: ${formatEuro(context.totals.expenses)}`,
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`Saldo: ${formatEuro(context.totals.balance)}`,
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"",
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"Umsätze (neueste zuerst):",
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...(context.transactionLines.length > 0
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? context.transactionLines
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: ["Keine Umsätze im Zeitraum."]),
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"",
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"Gesprächsverlauf:",
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...conversation.map((message) => `${message.role}: ${message.content}`),
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].join("\n");
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}
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function normalizeRole(role: ChatRole): "user" | "assistant" {
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return role;
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}
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function sortTransactionsForContext(
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transactions: Doc<"transactions">[],
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basis: ChatContextArgs["basis"],
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) {
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return transactions.sort((a, b) => {
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const aMonth = basis === "effective" ? a.effectiveMonth ?? bookingMonth(a.bookingDate) ?? "" : "";
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const bMonth = basis === "effective" ? b.effectiveMonth ?? bookingMonth(b.bookingDate) ?? "" : "";
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const aDate = basis === "booking" ? a.bookingDate ?? "" : a.valueDate ?? a.bookingDate ?? "";
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const bDate = basis === "booking" ? b.bookingDate ?? "" : b.valueDate ?? b.bookingDate ?? "";
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const aKey = `${aMonth}|${aDate}|${a._creationTime}`;
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const bKey = `${bMonth}|${bDate}|${b._creationTime}`;
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return bKey.localeCompare(aKey);
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});
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}
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async function loadMatchingTransactions(
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ctx: QueryCtx,
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userId: Id<"users">,
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args: ChatContextArgs,
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): Promise<Doc<"transactions">[]> {
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const monthFrom = args.from.slice(0, 7);
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const monthTo = args.to.slice(0, 7);
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const transactions: Doc<"transactions">[] = [];
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if (args.basis === "effective") {
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if (args.accountId) {
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const accountId = args.accountId;
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const q = ctx.db
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.query("transactions")
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.withIndex("by_user_account_effmonth", (index) =>
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index
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.eq("userId", userId)
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.eq("accountId", accountId)
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.gte("effectiveMonth", monthFrom)
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.lte("effectiveMonth", monthTo),
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)
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.order("desc");
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for await (const tx of q) transactions.push(tx);
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const fallback = ctx.db
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.query("transactions")
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.withIndex("by_user_account_booking", (index) =>
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index
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.eq("userId", userId)
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.eq("accountId", accountId)
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.gte("bookingDate", args.from)
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.lte("bookingDate", args.to),
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)
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.order("desc");
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for await (const tx of fallback) {
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if (tx.effectiveMonth === undefined) transactions.push(tx);
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}
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return sortTransactionsForContext(transactions, args.basis);
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}
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const q = ctx.db
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.query("transactions")
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.withIndex("by_user_effmonth", (index) =>
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index.eq("userId", userId).gte("effectiveMonth", monthFrom).lte("effectiveMonth", monthTo),
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)
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.order("desc");
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for await (const tx of q) transactions.push(tx);
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const fallback = ctx.db
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.query("transactions")
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.withIndex("by_user_booking", (index) =>
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index.eq("userId", userId).gte("bookingDate", args.from).lte("bookingDate", args.to),
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)
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.order("desc");
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for await (const tx of fallback) {
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if (tx.effectiveMonth === undefined) transactions.push(tx);
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}
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return sortTransactionsForContext(transactions, args.basis);
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}
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if (args.accountId) {
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const accountId = args.accountId;
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const q = ctx.db
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.query("transactions")
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.withIndex("by_user_account_booking", (index) =>
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index
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.eq("userId", userId)
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.eq("accountId", accountId)
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.gte("bookingDate", args.from)
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.lte("bookingDate", args.to),
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)
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.order("desc");
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for await (const tx of q) transactions.push(tx);
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return transactions;
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}
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const q = ctx.db
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.query("transactions")
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.withIndex("by_user_booking", (index) =>
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index.eq("userId", userId).gte("bookingDate", args.from).lte("bookingDate", args.to),
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)
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.order("desc");
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for await (const tx of q) transactions.push(tx);
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return sortTransactionsForContext(transactions, args.basis);
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}
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function calculateTotals(transactions: Doc<"transactions">[]) {
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const totals = transactions.reduce(
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(acc, tx) => {
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if (tx.amount > 0) acc.income += tx.amount;
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if (tx.amount < 0) acc.expenses += tx.amount;
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acc.balance += tx.amount;
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acc.transactionCount += 1;
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return acc;
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},
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{ income: 0, expenses: 0, balance: 0, transactionCount: 0 },
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);
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return {
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transactionCount: totals.transactionCount,
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income: Math.round(totals.income * 100) / 100,
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expenses: Math.round(totals.expenses * 100) / 100,
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balance: Math.round(totals.balance * 100) / 100,
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};
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}
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async function buildContextSummary(
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ctx: QueryCtx,
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userId: Id<"users">,
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args: ChatContextArgs,
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): Promise<{ summary: ChatContextSummary; transactions: Doc<"transactions">[] }> {
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const transactions = await loadMatchingTransactions(ctx, userId, args);
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const account = args.accountId ? await ctx.db.get(args.accountId) : null;
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return {
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summary: {
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from: args.from,
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to: args.to,
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basis: args.basis,
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accountId: args.accountId,
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accountName: account?.userId === userId ? account.name : undefined,
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totals: calculateTotals(transactions),
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isComplete: true,
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},
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transactions,
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};
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}
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const contextArgsValidator = {
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from: v.string(),
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to: v.string(),
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accountId: v.optional(v.id("accounts")),
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basis: v.union(v.literal("effective"), v.literal("booking")),
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};
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const totalsValidator = v.object({
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transactionCount: v.number(),
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income: v.number(),
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expenses: v.number(),
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balance: v.number(),
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});
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const contextSummaryValidator = v.object({
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from: v.string(),
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to: v.string(),
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basis: v.union(v.literal("effective"), v.literal("booking")),
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accountId: v.optional(v.id("accounts")),
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accountName: v.optional(v.string()),
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totals: totalsValidator,
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isComplete: v.literal(true),
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});
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export const getContext = query({
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args: contextArgsValidator,
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returns: contextSummaryValidator,
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handler: async (ctx, args): Promise<ChatContextSummary> => {
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const userId = await requireUserId(ctx);
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const { summary } = await buildContextSummary(ctx, userId, args);
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return summary;
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},
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});
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function toDisplayContextLine(
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tx: Doc<"transactions">,
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categoryById: Map<Id<"categories">, string>,
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accountById: Map<Id<"accounts">, string>,
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) {
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const date = tx.valueDate || tx.bookingDate || "n/a";
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const amount = formatEuro(tx.amount);
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const name = tx.counterparty ?? "–";
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const category = tx.categoryId ? categoryById.get(tx.categoryId) : "Ohne Kategorie";
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const account = tx.accountId ? accountById.get(tx.accountId) : "Ohne Konto";
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return `${date} | ${tx.description} (${name}) | ${amount} | ${category ?? "Ohne Kategorie"} | ${account ?? "Ohne Konto"}${
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tx.isPending ? " | offen" : ""
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}`;
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}
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export const getPromptContext = internalQuery({
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args: contextArgsValidator,
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returns: v.object({
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...contextSummaryValidator.fields,
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transactionLines: v.array(v.string()),
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}),
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handler: async (ctx, args): Promise<ChatPromptContext> => {
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const userId = await requireUserId(ctx);
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const { summary, transactions } = await buildContextSummary(ctx, userId, args);
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const categories = await ctx.db
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.query("categories")
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.withIndex("by_user", (index) => index.eq("userId", userId))
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.collect();
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const accounts = await ctx.db
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.query("accounts")
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.withIndex("by_user", (index) => index.eq("userId", userId))
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.collect();
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const categoryById = new Map(categories.map((category) => [category._id, category.name]));
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const accountById = new Map(accounts.map((account) => [account._id, account.name]));
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return {
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...summary,
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transactionLines: transactions.map((tx) =>
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toDisplayContextLine(tx, categoryById, accountById),
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),
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};
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},
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});
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export const ask = action({
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args: {
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messages: v.array(chatMessageValidator),
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from: v.string(),
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to: v.string(),
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accountId: v.optional(v.id("accounts")),
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basis: v.union(v.literal("effective"), v.literal("booking")),
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},
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returns: v.object({
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model: v.string(),
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answer: v.string(),
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usedTransactions: v.number(),
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usedBalance: v.object({
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income: v.number(),
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expenses: v.number(),
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balance: v.number(),
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}),
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}),
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handler: async (ctx, args): Promise<ChatAskResult> => {
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if (args.messages.length === 0) {
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throw new Error("Kein Nutzernachrichttext vorhanden.");
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}
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if (!process.env.OPENAI_API_KEY) {
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throw new Error(
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"OPENAI_API_KEY ist nicht gesetzt. Bitte API-Key in den Convex-Umgebungsvariablen hinterlegen.",
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);
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}
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await requireUserId(ctx);
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const context: ChatPromptContext = await ctx.runQuery(internal.savingsChat.getPromptContext, {
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from: args.from,
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to: args.to,
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accountId: args.accountId,
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basis: args.basis,
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});
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const lastMessages = args.messages
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.map((message): ChatMessage => ({ role: normalizeRole(message.role), content: message.content }))
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.slice(-MAX_CONVERSATION_MESSAGES);
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const prompt = buildPrompt(context, lastMessages);
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if (prompt.length > MAX_PROMPT_CHARACTERS) {
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throw new Error(
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"Der ausgewählte Zeitraum enthält zu viele Umsatzdetails für eine vollständige KI-Anfrage. Bitte Zeitraum oder Konto eingrenzen.",
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);
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}
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const system = buildSystemPrompt(context);
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const envModel = process.env.SAVINGS_CHAT_MODEL?.trim();
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const candidates = [
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envModel,
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"gpt-5.4-mini",
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"gpt-4.1-mini",
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"gpt-4.1",
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].filter(Boolean) as string[];
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let lastError: unknown;
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for (const modelName of candidates) {
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try {
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const result = await generateText({
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model: openai(modelName),
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system,
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prompt,
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});
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return {
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model: modelName,
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answer: result.text,
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usedTransactions: context.totals.transactionCount,
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usedBalance: {
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income: context.totals.income,
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expenses: context.totals.expenses,
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balance: context.totals.balance,
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},
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};
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} catch (error) {
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lastError = error;
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}
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}
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const message =
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lastError instanceof Error
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? lastError.message
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: "Unbekannter Fehler bei der KI-Anfrage";
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throw new Error(`KI-Anfrage fehlgeschlagen: ${message}`);
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},
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});
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