LLM Request Batching System

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Build a production-ready LLM request batching system with dynamic sizing, priority queues, and comprehensive error handling for cost and throughput optimization.

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Implement a request batching system for LLM API calls to optimize throughput and costs.

## Requirements
{{batching_requirements}}

## Current Traffic Pattern
{{traffic_pattern}}

## Latency Constraints
- Max batch wait time: {{max_wait_ms}}ms
- Target batch size: {{target_batch_size}}

Implement a complete solution:

```python
class LLMBatcher:
    """
    Implement:
    - Dynamic batch sizing
    - Timeout-based flushing
    - Priority queue support
    - Error handling per request
    - Metrics collection
    """
```

Include:
- Thread-safe implementation
- Async/await support
- Backpressure handling
- Unit tests

Details

Category

Coding

Use Cases

Request batchingThroughput optimizationCost reduction

Works Best With

claude-sonnet-4-20250514gpt-4o
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