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Welcome to the comprehensive Freddy platform documentation. Here you'll find guides, tutorials, best practices, and everything you need to get started with the Freddy AI platform.

🚀 Quick Start

📖 Documentation Sections

🔰 Fundamentals

• Platform Overview - Understanding the Freddy AI platform
• Quick Start Guide - Get up and running in minutes
• Authentication Methods - Security and API access
• API Reference - Complete endpoint documentation

🔌 API Documentation

• API Reference - Complete API endpoint documentation
• Authentication Guide - How to authenticate with the API
• Debugging Guide - Understanding API responses and errors

🎯 Advanced Topics

• Best Practices - Recommended patterns and practices
• Rate Limiting - Understanding API limits and quotas
• Performance Tips - Optimizing your API usage
• Security Guidelines - Keeping your integration secure

🛠️ Integration Guides

• Web Applications - Integrate with web applications
• Mobile Applications - Mobile app integration patterns
• Webhook Integration - Real-time notifications and events
• Custom Solutions - Building custom integrations

🎓 Tutorials

🔍 Search & Navigation

🆘 Need Help?

📈 What's New

• ✅ 196+ API Endpoints documented with interactive examples
• ✅ Auto-sync documentation with backend changes
• ✅ Enhanced tutorials with step-by-step guides
• ✅ Code examples in multiple programming languages
• ✅ Postman collections for easy API testing

Documentation automatically updated with platform changes

📋 Detailed Sections

Platform Overview {#platform-overview}

Freddy is a comprehensive AI-powered backend system that provides:

• 🤖 AI Intelligence - Multiple AI model support (OpenAI, Anthropic, Google)
• 👥 User Management - Complete authentication and user lifecycle
• 🏢 Organization Tools - Multi-tenant architecture with role-based access
• 📊 Analytics & Monitoring - Real-time usage tracking and insights
• 💰 Billing & Finance - Automated usage-based billing system

Authentication {#authentication}

The Freddy API uses API keys for authentication. All requests must include your API key in the header:

curl -H "api-key: ak_your_api_key_here" https://api.freddy.ai/v2/endpoint

Getting Your API Key:

1. Log in to the Freddy Hub
2. Navigate to Settings → API Keys
3. Click "Create New API Key"
4. Copy and securely store your key

Error Handling {#error-handling}

The API returns standard HTTP status codes and structured error responses:

{
  "detail": "Error message",
  "status_code": 400,
  "error_type": "ValidationError"
}

Common Status Codes:

• 200 - Success
• 400 - Bad Request (validation error)
• 401 - Unauthorized (invalid API key)
• 429 - Too Many Requests (rate limited)
• 500 - Internal Server Error

Rate Limiting {#rate-limiting}

API requests are rate limited based on your service tier:

• Standard: 100 requests/minute
• Premium: 1000 requests/minute
• Enterprise: Custom limits

Rate limit headers are included in every response:

X-RateLimit-Limit: 100
X-RateLimit-Remaining: 95
X-RateLimit-Reset: 1234567890

Best Practices {#best-practices}

🔐 Security:

• Never expose API keys in client-side code
• Use environment variables for API keys
• Implement proper error handling
• Validate all user inputs

⚡ Performance:

• Cache responses when appropriate
• Use pagination for large datasets
• Implement exponential backoff for retries
• Monitor your usage and rate limits

🛠️ Development:

• Use the interactive API docs for testing
• Implement proper logging and monitoring
• Follow RESTful conventions
• Keep your API keys secure

Tutorial Sections

Building Your First Chat Application {#first-chat-app}

Create a simple chat interface using the Freddy API:

1. Set up authentication with your API key
2. Create a chat session using the /v2/threads endpoint
3. Send messages using the /v2/messages endpoint
4. Get AI responses using the /v2/model/response endpoint

User Authentication Setup {#auth-setup}

Implement secure user authentication:

1. User Registration - /v2/auth/register
2. Email Verification - /v2/auth/verify-email
3. User Login - /v2/auth/login
4. Session Management - Handle JWT tokens securely

Making Your First API Call {#first-api-call}

Get started with a simple API request:

curl -X GET "https://api.freddy.ai/v2/models" \
  -H "api-key: ak_your_api_key_here"

This returns a list of available AI models you can use.

Integration Guides

Web Integration {#web-integration}

Integrate Freddy into web applications:

• Use HTTPS for all API calls
• Implement proper CORS handling
• Store API keys securely on the server
• Use WebSockets for real-time features

Mobile Integration {#mobile-integration}

Best practices for mobile apps:

• Store API keys in secure storage
• Implement offline functionality
• Handle network connectivity issues
• Optimize for mobile data usage

Webhook Integration {#webhooks}

Set up real-time notifications:

• Configure webhook endpoints
• Verify webhook signatures
• Handle webhook retries
• Process events asynchronously

Custom Integration {#custom-integration}

Build custom solutions:

• Generate client SDKs
• Implement custom authentication
• Build monitoring and alerting

Performance & Scaling

Performance Tips {#performance}

Optimize your API usage:

• Use appropriate pagination
• Implement caching strategies
• Batch requests when possible
• Monitor response times

Scaling Your Application {#scaling}

Handle high-volume usage:

• Implement connection pooling
• Use load balancing
• Monitor rate limits
• Plan for traffic spikes

Security Guidelines {#security}

Keep your integration secure:

• Use HTTPS everywhere
• Validate all inputs
• Implement proper authentication
• Monitor for suspicious activity

This documentation is automatically updated with platform changes