llm-integration
LLM Integration
Patterns for integrating LLMs into production applications: tool use, streaming, local inference, and fine-tuning. Each category has individual rule files in rules/ loaded on-demand.
Quick Reference
| Category | Rules | Impact | When to Use |
|---|---|---|---|
| Function Calling | 3 | CRITICAL | Tool definitions, parallel execution, input validation |
| Streaming | 3 | HIGH | SSE endpoints, structured streaming, backpressure handling |
| Local Inference | 3 | HIGH | Ollama setup, model selection, GPU optimization |
| Fine-Tuning | 3 | HIGH | LoRA/QLoRA training, dataset preparation, evaluation |
| Context Optimization | 2 | HIGH | Window management, compression, caching, budget scaling |
| Evaluation | 2 | HIGH | LLM-as-judge, RAGAS metrics, quality gates, benchmarks |
| Prompt Engineering | 4 | HIGH | CoT, few-shot, versioning, DSPy optimization, ReAct, cost optimization |
Total: 20 rules across 7 categories
Quick Start
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