Copilot's contextual understanding can be significantly improved with Persistent AI Memory:
- Integrated local memory database: After integrating the project into VS Code, Copilot can directly access locally stored expertise and code snippets
- Storage Expertise: You can pass project API documentation, programming notes, and other specialized knowledge through the
store_memoryfunction into the database - Semantic Search Support: When called by Copilot, the system matches the most relevant memory segments through semantic search, enhancing the accuracy of code completion
- Easy environment configuration: Just make sure to install the Python extension and the Copilot plugin, and the system will automatically adapt to the VS Code environment!
This type of integration provides a better understanding of the contextual needs of a particular project than relying solely on a cloud-based knowledge base.
This answer comes from the articlePersistent AI Memory: Persistent Local Memory Storage for AI AssistantsThe
May not be reproduced without permission:AI productivity tools " How to optimize the contextual accuracy of Copilot in VS Code?
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