Design configuration interfaces that prioritize user experience by providing sensible defaults, using clear naming conventions, and logically grouping related options. Complex tools with many configuration parameters should minimize the cognitive load on users through thoughtful interface design.
Design configuration interfaces that prioritize user experience by providing sensible defaults, using clear naming conventions, and logically grouping related options. Complex tools with many configuration parameters should minimize the cognitive load on users through thoughtful interface design.
Key principles:
--model-api-name
instead of --model
when referring to API endpoint naming)--enable-lmcache
instead of multiple LMCache-specific flags)Example of improvement:
# Before: Complex command with many explicit parameters
python3 rag.py --qps 3.5 --model mistralai/Mistral-7B-Instruct-v0.2 --dataset ~/CacheBlend/inputs/musique_s.json --system-prompt "You will be asked a question..." --query-prompt "Answer the question..." --separator "" --prompt-build-method QA --base-url "http://localhost:8000/v1" --kv-storage-size 30GB --max-tokens 32 --output summary.csv
# After: Simplified with defaults and clear grouping
python3 rag.py \
--qps 3.5 \
--model mistralai/Mistral-7B-Instruct-v0.2 \
--dataset ~/CacheBlend/inputs/musique_s.json \
--enable-lmcache \
--output summary.csv
This approach reduces user friction while maintaining the flexibility needed for advanced use cases.
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