Travel Planning Agent Platform

Overview

This project requires you to build an intelligent travel planning Agent platform from scratch, based on a real PRD. You'll build a complete AI product that accepts structured input, generates daily itineraries, and supports saving and reusing plans — not just a chatbot, but a product with task management capabilities.

This is the comprehensive practical section of Stage 2. The core challenge: how to make AI generate structured, actionable itineraries instead of a wall of unstructured text.

Prerequisites

Before starting this project, you should already be familiar with:

Frontend page design and component libraries (UI Design, Modern Component Libraries)
Backend API design and development (API Code)
Database fundamentals and Supabase (Database to Supabase)
Git workflow and deployment (Git & GitHub, Web App Deployment)

Learning Objectives

After completing this project, you will be able to:

Read a PRD and extract a development task list for an Agent platform
Design structured input forms and structured output formats
Implement an Agent orchestration layer handling user input, model calls, and result storage
Build a "generate → save → reuse" business loop
Complete end-to-end integration and deliver a demo-ready AI product prototype

Project Overview

You will build an intelligent travel planning Agent platform:

Feature	Description
Itinerary Planning	Users enter origin, destination, dates, budget, and preferences; the system generates daily itineraries
Budget Breakdown	Itinerary results include budget allocation and suggestions
History Management	Users can save, regenerate, and export past plans
Admin Dashboard	Admins view popular destinations, failed tasks, and user feedback

PRD

The requirements document for this project is on GitHub: View PRD

Part 1: Requirements Analysis

1.1 Read the PRD

Open the PRD document and answer these key questions:

Should the first version only support single-destination trips?
Must the itinerary output be structured? What is the structure?
How deep should export capabilities go? (share link / PDF / image)
What is the scope of admin statistics and task logs?

WARNING

If the above questions don't have clear answers, don't start coding. Unclear requirements are the most common cause of rework.

1.2 Confirm System Architecture

mermaid

flowchart TD
  prd["PRD"] --> planner["Planning Page"]
  planner --> agent["Agent Orchestration Layer"]
  agent --> model["Model Call"]
  agent --> db["Database"]
  db --> history["Plan History"]
  db --> admin["Admin Statistics & Logs"]

Part 2: Project Scaffolding

2.1 Generate Frontend Pages

Prompt reference:

text

Based on the current PRD, help me generate a frontend scaffold for an intelligent travel planning Agent platform.

Requirements:
1. Pages: homepage, planning page, itinerary detail, history, admin dashboard
2. Planning page has a form on the left and result preview on the right
3. Only generate page structure with mock data first, no real API integration
4. Style should look like a modern AI product

2.2 Verify Page Structure

Check each item:

[ ] Planning page form fields match the PRD
[ ] Result preview area can display structured itinerary data
[ ] History page can display multiple plans
[ ] Admin dashboard can display statistics

Part 3: Iterative Development

3.1 Module-by-Module Progress

Authentication: Registration, login
Planning Form: Structured input (origin, destination, dates, budget, preferences)
Agent Orchestration: Receive input → Call model → Parse structured output
Result Display: Show itinerary by day, budget breakdown, suggestions
History Management: Save plans, regenerate, export
Admin Dashboard: Popular destinations, failed tasks, user feedback
Task Status: Generating / Success / Failed status management and error logging

3.2 Module Self-Check

Check Item	Verification Method
Input completeness	Do form fields match the PRD?
Output structure	Is the itinerary result structured data (not a wall of text)?
Data consistency	Do trip, itinerary, and logs data align?
Loop verification	Can you demo "input → generate → save → regenerate"?

Part 4: Integration & Launch

4.1 End-to-End Testing

At minimum, verify these scenarios:

Enter trip parameters → Generate daily itinerary → View budget breakdown → Save to history
Regenerate itinerary from history
Admin views task statistics and failure logs

Deliverables

After completing this project, submit the following:

[ ] Accessible live demo link
[ ] Source code repository link (with README)
[ ] PRD document
[ ] Core page screenshots (planning page, itinerary detail, history, admin dashboard)
[ ] 60-second demo video

Grading Criteria

Dimension	Basic Requirements	Advanced Requirements
PRD Alignment	Pages, features, and data structures basically match PRD	Can clearly explain design decisions
Product Loop	Plan → Save → History → Regenerate works end-to-end	Supports export and sharing
Output Quality	Itinerary results are structured and readable	Budget breakdown is reasonable, suggestions are relevant
Admin Capability	Task statistics and failure logs viewable	Has popular destination analysis
Engineering Completeness	Frontend, backend, database, model call pipeline connected	Task status management is robust, errors are traceable

Travel Planning Agent Platform ​

Overview ​

Prerequisites ​

Learning Objectives ​

Project Overview ​

Part 1: Requirements Analysis ​

1.1 Read the PRD ​

1.2 Confirm System Architecture ​

Part 2: Project Scaffolding ​

2.1 Generate Frontend Pages ​

2.2 Verify Page Structure ​

Part 3: Iterative Development ​

3.1 Module-by-Module Progress ​

3.2 Module Self-Check ​

Part 4: Integration & Launch ​

4.1 End-to-End Testing ​

Deliverables ​

Grading Criteria ​

References ​