AutoRAG Optimization Report

Best Score
0.270
Custom Aggregate
Configs Tested
8
Total experiments
Improvement
+7.7%
vs. worst config
Top Parameters
k=5, t=1.0
Optimal settings
🏆

## Best Configuration

Chunk Size
500
Chunk Overlap
50
Embedding Model
all-MiniLM-L6-v2
Top K Documents
5
Temperature
1.0
Overall Score
0.270

### Custom Metrics Breakdown

Context Recall 0.000
Faithfulness 0.000
Answer Relevancy 0.500
Answer Similarity 0.481
📊

## All Configurations

Rank | Chunk | Overlap | Embedding | top_k | Temp | Score
--- | --- | --- | --- | --- | --- | ---
1 | 500 | 50 | all-MiniLM-L | 5 | 1.0 | 0.270
2 | 500 | 100 | all-MiniLM-L | 10 | 0.3 | 0.270
3 | 500 | 50 | all-MiniLM-L | 10 | 0.7 | 0.267
4 | 500 | 100 | all-MiniLM-L | 3 | 0.7 | 0.263
5 | 256 | 100 | paraphrase-M | 10 | 1.0 | 0.258
6 | 256 | 50 | paraphrase-M | 5 | 0.3 | 0.254
7 | 256 | 50 | paraphrase-M | 5 | 0.3 | 0.254
8 | 256 | 50 | all-MiniLM-L | 5 | 1.0 | 0.251

💡

## Recommendations

- 🚀

  #### Deploy Best Configuration

  Use the winning configuration in your production RAG system for optimal performance.

- 📈

  #### Monitor Performance

  Track real-world accuracy and response quality metrics after deployment.

- 🔄

  #### Periodic Re-optimization

  Run optimization again when your document base grows significantly or user query patterns change.