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Learn Advanced Features

Streaming Responses

Get real-time responses as they’re generated

Function Calling

Let AI interact with external tools and APIs

Vision Support

Process images with multimodal models

API Documentation

Complete API reference and guides

Explore Documentation

API Reference

Complete API documentation

OpenAI API

OpenAI-compatible endpoints

Anthropic API

Anthropic Claude-compatible endpoints

Models Catalog

Browse all 70+ available models

Build Real Applications

1. Chatbot

Build an intelligent chatbot:

2. Content Generator

Generate blog posts, emails, or social media content:

3. Code Assistant

Build a coding helper:

4. Data Analyzer

Analyze data and generate insights:

Best Practices

  • GPT-4: Best for complex reasoning
  • GPT-3.5 Turbo: Fast and cost-effective
  • Claude Opus: Excellent for analysis and long context
  • Claude Sonnet: Balanced performance
  • Gemini Pro: Strong multimodal capabilities
See Models Catalog for detailed comparisons.
  • Start with cheaper models for testing
  • Use max_tokens to limit response length
  • Cache responses when possible
  • Use streaming to improve perceived performance
  • Monitor usage in your dashboard
  • Be specific and clear
  • Provide examples when needed
  • Use system messages to set context
  • Break complex tasks into steps
  • Test different temperature settings
  • Keep track of conversation history
  • Limit history to avoid token limits
  • Summarize old messages if needed
  • Use prompt caching for repeated content

Production Considerations

Security

  • Store API keys in environment variables
  • Never commit keys to version control
  • Use different keys for dev/staging/production
  • Rotate keys regularly
  • Monitor usage for anomalies

Performance

  • Use streaming for better UX
  • Implement caching where appropriate
  • Add retry logic with exponential backoff
  • Monitor response times
  • Consider using webhooks for async operations

Monitoring

  • Track token usage
  • Monitor error rates
  • Log API requests (without sensitive data)
  • Set up alerts for quota limits
  • Review costs regularly

Scaling

  • Implement rate limiting
  • Use queues for high-volume requests
  • Cache common responses
  • Consider batching requests
  • Plan for failover strategies

Join the Community

Discord

Chat with other developers

GitHub

View examples and contribute

Twitter/X

Follow for updates

YouTube

Watch tutorials

Get Help

Most common questions are answered in our FAQ.
Comprehensive guides available in Developer Docs.
Email us at support@megallm.io for technical assistance.
Found a bug? Report it on GitHub.

Useful Resources

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API Reference

Complete documentation

Support

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