Performance pain points
When the code base exceeds a million lines, direct processing can lead to LLM context overflow.Kheish's RAG integration solution solves this problem effectively.
Optimization solutions
- chunk index: Split code into logical blocks by function via fs modules
- intelligent retrieval: The RAG module recalls only code snippets that are relevant to the current task
- caching mechanism: Long-term memory storage of code patterns for high-frequency use
Configuration points
- Set the chunk_size parameter in YAML (2048 tokens recommended)
- Enable embedding_cache to accelerate vector retrieval
- Configure tiered storage policies for rag modules
- Perform periodic index compression of the memories module
real time data
In Linux kernel source code auditing tests, the scheme reduced the average response time from 12 minutes to 47 seconds and memory consumption by 761 TP3T.
This answer comes from the articleKheish: multi-actor intelligences that review, validate and format output to produce high quality resultsThe
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