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https://github.com/kjanat/livedash-node.git
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- Add package.json with dependencies and scripts for Next.js and Prisma - Implement API routes for session management, user authentication, and company configuration - Create database schema for Company, User, and Session models in Prisma - Set up authentication with NextAuth and JWT - Add password reset functionality and user registration endpoint - Configure Tailwind CSS and PostCSS for styling - Implement metrics and dashboard settings API endpoints
105 lines
3.1 KiB
TypeScript
105 lines
3.1 KiB
TypeScript
// Fetches, parses, and returns chat session data for a company from a CSV URL
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import fetch from "node-fetch";
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import { parse } from "csv-parse/sync";
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// This type is used internally for parsing the CSV records
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interface CSVRecord {
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session_id: string;
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start_time: string;
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end_time?: string;
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ip_address?: string;
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country?: string;
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language?: string;
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messages_sent?: string;
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sentiment?: string;
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escalated?: string;
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forwarded_hr?: string;
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full_transcript_url?: string;
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avg_response_time?: string;
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tokens?: string;
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tokens_eur?: string;
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category?: string;
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initial_msg?: string;
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[key: string]: string | undefined;
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}
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interface SessionData {
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id: string;
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sessionId: string;
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startTime: Date;
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endTime: Date | null;
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ipAddress?: string;
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country?: string;
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language?: string | null;
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messagesSent: number;
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sentiment: number | null;
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escalated: boolean;
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forwardedHr: boolean;
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fullTranscriptUrl?: string | null;
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avgResponseTime: number | null;
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tokens: number;
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tokensEur: number;
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category?: string | null;
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initialMsg?: string;
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}
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export async function fetchAndParseCsv(url: string, username?: string, password?: string): Promise<Partial<SessionData>[]> {
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const authHeader = username && password
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? "Basic " + Buffer.from(`${username}:${password}`).toString("base64")
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: undefined;
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const res = await fetch(url, {
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headers: authHeader ? { Authorization: authHeader } : {},
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});
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if (!res.ok) throw new Error("Failed to fetch CSV: " + res.statusText);
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const text = await res.text();
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// Parse without expecting headers, using known order
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const records: CSVRecord[] = parse(text, {
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delimiter: ",",
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columns: [
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"session_id",
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"start_time",
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"end_time",
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"ip_address",
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"country",
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"language",
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"messages_sent",
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"sentiment",
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"escalated",
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"forwarded_hr",
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"full_transcript_url",
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"avg_response_time",
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"tokens",
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"tokens_eur",
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"category",
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"initial_msg",
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],
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from_line: 1,
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relax_column_count: true,
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skip_empty_lines: true,
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trim: true,
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});
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// Coerce types for relevant columns
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return records.map((r) => ({
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id: r.session_id,
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startTime: new Date(r.start_time),
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endTime: r.end_time ? new Date(r.end_time) : null,
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ipAddress: r.ip_address,
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country: r.country,
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language: r.language,
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messagesSent: Number(r.messages_sent) || 0,
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sentiment: r.sentiment ? parseFloat(r.sentiment) : null,
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escalated: r.escalated === "1" || r.escalated === "true",
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forwardedHr: r.forwarded_hr === "1" || r.forwarded_hr === "true",
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fullTranscriptUrl: r.full_transcript_url,
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avgResponseTime: r.avg_response_time ? parseFloat(r.avg_response_time) : null,
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tokens: Number(r.tokens) || 0,
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tokensEur: r.tokens_eur ? parseFloat(r.tokens_eur) : 0,
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category: r.category,
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initialMsg: r.initial_msg,
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}));
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}
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