toy-poodle-love

内容来源：README.md（说明文档） · 原始地址 · 查看安装指南

原始内容

# toy-poodle-love

A multi-platform AI-powered route planning and scenario generation system.

> *The name "toy-poodle-love" comes from the WAN video generation example: "A cute toy poodle running in a sunny park"*

## Overview

**toy-poodle-love** is an end-to-end platform for AI-driven route optimization and scenario writing. It combines multiple AI services to generate tourist routes with narratives, and can even create videos from the generated scenarios.

### Key Capabilities

- **AI Text Generation** - Compare responses from Qwen (Alibaba) and Gemini (Google) models
- **Route Optimization** - Generate and optimize tourist routes using Google Maps APIs
- **Scenario Generation** - Create themed narratives for each location
- **Video Generation** - Transform scenarios into videos using WAN2.6 T2V/I2V models
- **Speech Integration** - Voice input and text-to-speech output

## Architecture

```mermaid
graph TB
    subgraph Clients
        WEB[Web App<br/>Next.js]
        MAC[macOS Viewer<br/>SwiftUI]
        IOS[iOS Handheld<br/>SwiftUI]
        AND[Android Viewer<br/>Jetpack Compose]
    end

    subgraph "Web Backend"
        API[Next.js API Routes]
        QWEN[Qwen Client]
        GEMINI[Gemini Client]
        MAPS[Google Maps Client]
    end

    subgraph "External Services"
        QWEN_API[Alibaba DashScope]
        GEMINI_API[Google AI]
        GOOGLE_API[Google Maps Platform]
        WAN_API[WAN2.6 Video API]
    end

    WEB --> API
    MAC --> API
    IOS --> API
    AND --> API

    API --> QWEN --> QWEN_API
    API --> GEMINI --> GEMINI_API
    API --> MAPS --> GOOGLE_API

    API -.-> WAN_API
```

### Platform Overview

| Platform | Directory | Technology | Min Version |
|----------|-----------|------------|-------------|
| Web | `web/` | Next.js 16, React 19, TypeScript | Node.js 18+ |
| macOS | `viewer/` | Swift 6, SwiftUI | macOS 14.0+ |
| iOS | `handheld/` | Swift 5.9, SwiftUI | iOS 17.0+ |
| Android | `viewer-android/` | Kotlin, Jetpack Compose | Android 9 (API 28) |
| Video Gen | `wan2_6_i2v/` | Python 3.x | Python 3.8+ |

## Quick Start

### Prerequisites

- Node.js 18+
- API keys for:
  - [Alibaba DashScope](https://dashscope.console.aliyun.com/) (Qwen)
  - [Google AI Studio](https://makersuite.google.com/app/apikey) (Gemini)
  - [Google Cloud Console](https://console.cloud.google.com/) (Maps APIs)

### Web Application Setup

```bash
# Navigate to web directory
cd web

# Install dependencies
npm install

# Create environment file
cp .env.example .env
```

Edit `.env` with your API keys:

```env
QWEN_API_KEY=your_qwen_api_key
GEMINI_API_KEY=your_gemini_api_key
GOOGLE_MAPS_API_KEY=your_google_maps_api_key
```

```bash
# Start development server
npm run dev
```

Open [http://localhost:3000](http://localhost:3000) to access the web interface.

### macOS Viewer Setup

```bash
cd viewer

# Generate Xcode project (requires xcodegen)
xcodegen generate

# Open in Xcode
open viewer.xcodeproj
```

### iOS Handheld Setup

```bash
cd handheld

# Generate Xcode project
xcodegen generate

# Open in Xcode
open handheld.xcodeproj
```

### Android Viewer Setup

```bash
cd viewer-android

# Open in Android Studio or build via Gradle
./gradlew assembleDebug
```

### Video Generation (Python)

```bash
cd wan2_6_i2v

# Install dependencies
pip install -r requirements.txt

# Generate a video from text
python wan_video.py "A cute toy poodle running in a sunny park"
```

## API Reference

The web application exposes a RESTful API with the following endpoints:

| Category | Endpoint | Description |
|----------|----------|-------------|
| **AI** | `POST /api/qwen` | Call Qwen model |
| | `POST /api/gemini` | Call Gemini model |
| **Places** | `POST /api/places/geocode` | Geocode addresses |
| **Routes** | `POST /api/routes/optimize` | Optimize route order |
| | `POST /api/route/generate` | AI-generated route |
| **Scenario** | `POST /api/scenario` | Generate scenario |
| | `POST /api/scenario/integrate` | Merge scenarios |
| | `POST /api/scenario/spot` | Spot-specific scenario |
| **Pipeline** | `POST /api/pipeline/route-optimize` | End-to-end pipeline |
| **Speech** | `POST /api/speech/recognize` | Speech recognition |
| | `POST /api/tts` | Text-to-speech |

### API Documentation

- **Swagger UI**: Available at `/api-docs.html` when running the dev server
- **OpenAPI Spec**: See [`web/openapi.yaml`](https://github.com/fumiya-kume/toy-poodle-love/blob/HEAD/web/openapi.yaml)

## Documentation

- **[Quick Start Guide](https://github.com/fumiya-kume/toy-poodle-love/blob/HEAD/web/QUICKSTART.md)** - Get up and running in 5 minutes
- **[API Documentation](https://github.com/fumiya-kume/toy-poodle-love/blob/HEAD/web/API_DOCUMENTATION.md)** - Comprehensive API reference
- **[Development Guide](https://github.com/fumiya-kume/toy-poodle-love/blob/HEAD/web/CLAUDE.md)** - Architecture and contribution guidelines

## Development

### Web Development

```bash
cd web

# Development server
npm run dev

# Type checking
npm run type-check

# Linting
npm run lint

# Production build
npm run build
```

### Running Tests

```bash
# Web tests
cd web && npm test

# macOS viewer tests
cd viewer && xcodebuild test -scheme viewer

# Android tests
cd viewer-android && ./gradlew test
```

### CI/CD

This project uses GitHub Actions for continuous integration:

- **web-ci.yml** - Web application build and tests
- **viewer-ci.yml** - macOS viewer build and tests
- **ios-ci.yml** - iOS handheld app build and tests

## Tech Stack

### Web
- **Framework**: Next.js 16 with App Router
- **Language**: TypeScript 5
- **UI**: React 19
- **AI SDKs**: OpenAI SDK (for Qwen), Google Generative AI SDK

### Apple Platforms
- **Language**: Swift 6 (viewer), Swift 5.9 (handheld)
- **UI**: SwiftUI
- **Concurrency**: Swift Strict Concurrency
- **Build**: XcodeGen

### Android
- **Language**: Kotlin
- **UI**: Jetpack Compose
- **DI**: Hilt
- **Networking**: Retrofit + OkHttp
- **Video**: Media3 ExoPlayer

### Python
- **Video Generation**: Alibaba WAN2.6 API

## License

ISC

toy-poodle-love

A multi-platform AI-powered route planning and scenario generation system.

The name "toy-poodle-love" comes from the WAN video generation example: "A cute toy poodle running in a sunny park"

Overview

toy-poodle-love is an end-to-end platform for AI-driven route optimization and scenario writing. It combines multiple AI services to generate tourist routes with narratives, and can even create videos from the generated scenarios.

Key Capabilities

AI Text Generation - Compare responses from Qwen (Alibaba) and Gemini (Google) models
Route Optimization - Generate and optimize tourist routes using Google Maps APIs
Scenario Generation - Create themed narratives for each location
Video Generation - Transform scenarios into videos using WAN2.6 T2V/I2V models
Speech Integration - Voice input and text-to-speech output

Architecture

graph TB
    subgraph Clients
        WEB[Web App<br/>Next.js]
        MAC[macOS Viewer<br/>SwiftUI]
        IOS[iOS Handheld<br/>SwiftUI]
        AND[Android Viewer<br/>Jetpack Compose]
    end

    subgraph "Web Backend"
        API[Next.js API Routes]
        QWEN[Qwen Client]
        GEMINI[Gemini Client]
        MAPS[Google Maps Client]
    end

    subgraph "External Services"
        QWEN_API[Alibaba DashScope]
        GEMINI_API[Google AI]
        GOOGLE_API[Google Maps Platform]
        WAN_API[WAN2.6 Video API]
    end

    WEB --> API
    MAC --> API
    IOS --> API
    AND --> API

    API --> QWEN --> QWEN_API
    API --> GEMINI --> GEMINI_API
    API --> MAPS --> GOOGLE_API

    API -.-> WAN_API

Platform Overview

Platform	Directory	Technology	Min Version
Web	`web/`	Next.js 16, React 19, TypeScript	Node.js 18+
macOS	`viewer/`	Swift 6, SwiftUI	macOS 14.0+
iOS	`handheld/`	Swift 5.9, SwiftUI	iOS 17.0+
Android	`viewer-android/`	Kotlin, Jetpack Compose	Android 9 (API 28)
Video Gen	`wan2_6_i2v/`	Python 3.x	Python 3.8+

Quick Start

Prerequisites

Node.js 18+
API keys for:
- Alibaba DashScope (Qwen)
- Google AI Studio (Gemini)
- Google Cloud Console (Maps APIs)

Web Application Setup

# Navigate to web directory
cd web

# Install dependencies
npm install

# Create environment file
cp .env.example .env

Edit .env with your API keys:

QWEN_API_KEY=your_qwen_api_key
GEMINI_API_KEY=your_gemini_api_key
GOOGLE_MAPS_API_KEY=your_google_maps_api_key

# Start development server
npm run dev

Open http://localhost:3000 to access the web interface.

macOS Viewer Setup

cd viewer

# Generate Xcode project (requires xcodegen)
xcodegen generate

# Open in Xcode
open viewer.xcodeproj

iOS Handheld Setup

cd handheld

# Generate Xcode project
xcodegen generate

# Open in Xcode
open handheld.xcodeproj

Android Viewer Setup

cd viewer-android

# Open in Android Studio or build via Gradle
./gradlew assembleDebug

Video Generation (Python)

cd wan2_6_i2v

# Install dependencies
pip install -r requirements.txt

# Generate a video from text
python wan_video.py "A cute toy poodle running in a sunny park"

API Reference

The web application exposes a RESTful API with the following endpoints:

Category	Endpoint	Description
AI	`POST /api/qwen`	Call Qwen model
	`POST /api/gemini`	Call Gemini model
Places	`POST /api/places/geocode`	Geocode addresses
Routes	`POST /api/routes/optimize`	Optimize route order
	`POST /api/route/generate`	AI-generated route
Scenario	`POST /api/scenario`	Generate scenario
	`POST /api/scenario/integrate`	Merge scenarios
	`POST /api/scenario/spot`	Spot-specific scenario
Pipeline	`POST /api/pipeline/route-optimize`	End-to-end pipeline
Speech	`POST /api/speech/recognize`	Speech recognition
	`POST /api/tts`	Text-to-speech

API Documentation

Swagger UI: Available at /api-docs.html when running the dev server
OpenAPI Spec: See web/openapi.yaml

Documentation

Quick Start Guide - Get up and running in 5 minutes
API Documentation - Comprehensive API reference
Development Guide - Architecture and contribution guidelines

Development

Web Development

cd web

# Development server
npm run dev

# Type checking
npm run type-check

# Linting
npm run lint

# Production build
npm run build

Running Tests

# Web tests
cd web && npm test

# macOS viewer tests
cd viewer && xcodebuild test -scheme viewer

# Android tests
cd viewer-android && ./gradlew test

CI/CD

This project uses GitHub Actions for continuous integration:

web-ci.yml - Web application build and tests
viewer-ci.yml - macOS viewer build and tests
ios-ci.yml - iOS handheld app build and tests

Tech Stack

Web

Framework: Next.js 16 with App Router
Language: TypeScript 5
UI: React 19
AI SDKs: OpenAI SDK (for Qwen), Google Generative AI SDK

Apple Platforms

Language: Swift 6 (viewer), Swift 5.9 (handheld)
UI: SwiftUI
Concurrency: Swift Strict Concurrency
Build: XcodeGen

Android

Language: Kotlin
UI: Jetpack Compose
DI: Hilt
Networking: Retrofit + OkHttp
Video: Media3 ExoPlayer

Python

Video Generation: Alibaba WAN2.6 API

License

ISC