Module 230 minutes
API Integration: OpenAI, Anthropic, Open Source
Integrate AI APIs into your application. Compare providers and implement production-ready integrations.
api-integrationopenaiclaudedevelopment
Learning Objectives
- ✓Choose the right AI API provider
- ✓Implement OpenAI and Anthropic APIs
- ✓Handle errors and rate limits
- ✓Build fallback strategies
Integrate AI in Your App
Learn to work with major AI APIs and build robust integrations.
Provider Comparison
OpenAI (GPT-4):
- Most capable
- Higher cost
- Fast inference
Anthropic (Claude):
- Longer context
- Good at analysis
- Safer outputs
Open Source (Llama, Mistral):
- Lower cost
- Self-hosted option
- More control
Basic Integration Example
```python
import openai
openai.api_key = "your-key"
response = openai.ChatCompletion.create(
model="gpt-4",
messages=[{"role": "user", "content": "Hello"}]
)
```
Error Handling
- Rate limit retries
- Timeout handling
- Fallback models
- Graceful degradation
Key Takeaways
- →Choose provider based on task requirements and budget
- →Always implement error handling and retries
- →Use environment variables for API keys
- →Monitor usage and costs
- →Have fallback strategies
Practice Exercises
Apply what you've learned with these practical exercises:
- 1.Integrate OpenAI API in test project
- 2.Implement retry logic
- 3.Compare costs across providers
- 4.Build error handling