Performance optimization solutions for low-profile equipment
For devices with less than 8GB of RAM, triple optimization is available to ensure smooth operation:
1. Resource allocation strategy
- Force the use of lightweight models:
export FAST_LLM="gemini-lite" - Turn off non-essential components:
export USE_LLM_COMPRESSOR="FALSE" - Limit concurrent requests:
export MAX_CONCURRENT=2
2. Operational parameter tuning
- Reducing timeouts::
set upSEARCH_PROCESS_TIMEOUT=120(in seconds) - Enable results caching::
establishcache/directory and addexport USE_CACHE=TRUE - Streamlining output content::
Adding Command Line Parameters--compactReduced detail output
3. Docker-specific optimization
modificationsdocker-compose.yml::
- Add resource limits for each service:
deploy: resources: limits: memory: 2GB cpus: "0.5"
- utilization
--no-gpuparameterization - Turn off front-end hot updates:
npm run build --production
Real-world data: After optimization, the 4GB RAM device can stably handle 5 concurrent search tasks.
This answer comes from the articleII-Researcher: Deep Search and Stepwise Reasoning to Answer Complex QuestionsThe
May not be reproduced without permission:AI productivity tools " How to optimize the efficiency of II-Researcher on low configuration devices?
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