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Generation of condensed representations of source code using ASTs or LLMs.
Distinct from LLM-Based Summarizations: Specifically targets source code structure via ASTs, whereas LLM-based summarizations generally target prose or web content.
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OpenViking is a multi-tenant context server and knowledge base administration system designed to provide AI agents with persistent long-term memory. It enables the indexing of diverse documents and codebases to support retrieval-augmented generation, allowing agents to recall past interactions, user preferences, and learned experiences across sessions. The project is distinguished by its use of a URI-based virtual filesystem to organize memories, resources, and skills. It implements a tiered context loading system that balances retrieval precision with token budgets by structuring data into a
Generates summaries for source code using AST skeleton extraction or LLM-based analysis.