Set up Universal App Store Autopilot v3.0

[samihalawa]

Complete mobile app infrastructure setup:

• Capacitor configuration for iOS and Android
• • PWA manifest and icons
• • Fastlane deployment scripts
• • GitHub Actions CI/CD workflows
• • Store deployment automation
    Google Play API auth configured. Apple needs key verification.

[Copilot]

Pull request overview

This PR sets up mobile app infrastructure for AI Manus, establishing deployment pipelines for iOS and Android app stores, along with significant backend improvements for production readiness.

Key Changes:

• Complete Capacitor mobile app infrastructure with iOS and Android native project scaffolding
• Automated deployment workflows for Google Play Store and Apple App Store via GitHub Actions and Fastlane
• Enhanced backend error handling, CORS configuration, and health check endpoints
• New browser tool capabilities and comprehensive test coverage for critical services

Reviewed changes

Copilot reviewed 111 out of 159 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
frontend/capacitor.config.ts	Capacitor configuration defining app ID, platform schemes, and plugin settings
frontend/package.json	Updated dependencies including Capacitor SDK, PWA plugin, and mobile build scripts
frontend/vite.config.ts	Added VitePWA plugin with service worker and caching strategies
frontend/public/manifest.json	PWA manifest with app metadata and icon specifications
frontend/ios/App/*	iOS native app structure including Xcode project, Info.plist, and assets
frontend/android/app/*	Android native app with Gradle build files, manifest, and signing configuration
frontend/scripts/store-deploy.cjs	App Store Connect and Google Play API integration for automated deployment
frontend/scripts/deploy-stores.sh	Shell script orchestrating build and deployment to both app stores
backend/app/main.py	Enhanced startup with optional MongoDB/Redis and security-aware CORS
backend/app/interfaces/errors/exception_handlers.py	Improved error handling with user-friendly messages and request ID tracking
backend/app/interfaces/api/health_routes.py	Health check endpoints for Kubernetes/Cloud Run readiness probes
backend/tests/*.py	Comprehensive test suites for TokenService, EmailService, and AgentService
setup-manus-proxy.sh	Nginx reverse proxy setup for dynamic subdomain routing
deploy-gcp.sh	Google Cloud deployment automation with Gemini 2.5 Pro integration

Comments suppressed due to low confidence (7)

backend/app/interfaces/errors/exception_handlers.py:1

• The Settings class does not have an 'is_production' attribute based on the provided context. This will cause an AttributeError at runtime. Add the 'is_production' property to Settings or use an alternative check like 'settings.environment == "production"'.
  backend/app/main.py:1
• The Settings class does not have an 'is_production' attribute. This will cause an AttributeError. Use an alternative check such as 'settings.environment == "production"' or add the missing property to Settings.
  frontend/scripts/store-deploy.cjs:1
• API key is hardcoded in source code. This is a security vulnerability as the key will be exposed in version control. Move to environment variable: const GEMINI_API_KEY = process.env.GEMINI_API_KEY;
  deploy-gcp.sh:1
• API key is hardcoded in the deployment script. This exposes the key in version control. Use environment variable instead: GEMINI_API_KEY="${GEMINI_API_KEY:-}"
  frontend/android/app/build.gradle:1
• Keystore credentials are hardcoded in build configuration. This is a security risk. Use environment variables or Gradle properties: storePassword System.getenv('KEYSTORE_PASSWORD') ?: project.findProperty('keystorePassword')
  frontend/scripts/setup-store-credentials.sh:1
• Keystore passwords are hardcoded in the credential setup script. These should be passed as environment variables or prompted securely: read -sp 'Enter keystore password: ' KEYSTORE_PASSWORD
  backend/tests/conftest.py:1
• Mock module registration occurs at module level which affects all tests globally. Consider using a fixture with pytest's monkeypatch to scope these mocks appropriately and avoid potential side effects between test modules.

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[Copilot]

The comment mentions a Gemini limitation but the class is named OpenAILLM and uses OpenAI client. This is confusing. Clarify whether this limitation applies to both OpenAI and Gemini, or if this is specific to the Gemini implementation.

Suggested change

	# Note: Cannot use response_format with function calling (Gemini limitation)
	# Note: The OpenAI Chat Completions API does not support using response_format together with tools/function calling

[BalochLeader]

Hmm

[Simpleyyt]

It is a large change