LLM Strategy
Optimize your event ingestion for Large Language Model workloads.
Overview
The LLM Strategy is designed specifically for handling events related to language model operations, including:
- Token usage tracking
- Request/response logging
- Model performance metrics
- Cost analysis
Configuration
Basic Setup
javascript
const llmStrategy = {
type: 'llm',
model: 'gpt-4',
tracking: {
tokens: true,
latency: true,
costs: true
}
};
Advanced Configuration
javascript
const advancedConfig = {
batchSize: 1000,
compression: 'gzip',
retention: '30d',
aggregation: {
enabled: true,
interval: '1h'
}
};
Features
Token Tracking
Automatically track token usage for each request:
- Input tokens
- Output tokens
- Total tokens
- Cost per token
Performance Metrics
Monitor model performance:
- Response latency
- Throughput
- Error rates
- Success rates
Best Practices
- Enable token tracking for cost optimization
- Set appropriate batch sizes
- Use compression for large payloads
- Configure retention policies
Use Cases
Ideal for:
- AI application monitoring
- Cost optimization
- Performance analysis
- Usage analytics
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