llmware offers a complete localized deployment solution:
- environmental preparation: Install Python 3.8+, it is recommended to create a standalone environment using conda
- Choosing a lightweight model: The BLING series (e.g. bling-1b-gguf) is optimized for CPUs and can be run with 4GB of RAM!
- Isolated data storage: Configure SQLite or local MongoDB instances to ensure that data does not go out of bounds
- security enhancement: Enable prompt history encryption (
prompter.set_encryption_key()) - Performance Tuning: Settings
ulimit -s 160000Prevent stack overflows. The solution has been certified for penetration testing in the financial industry
This answer comes from the articlellmware: an open source framework for rapidly building enterprise-class RAG applicationsThe
May not be reproduced without permission:AI productivity tools " What are the key steps required to achieve a safe local deployment of a RAG system?
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