dsh-llmwiki: A Local Markdown Wiki for DeepSeek Harness
dsh-llmwiki is a local-first Markdown Wiki plugin for DeepSeek Harness (DSH), designed to provide a deterministic storage and retrieval solution. The plugin leverages the local file system, SHA-256 hashing, and the BM25 algorithm to ensure that data is immutable, privacy-safe, and free of external dependencies. Users must explicitly activate the plugin via a patch and configure optional parameters to manage the Wiki root directory and file size limits. Once installed, the plugin can be used by agents as services, tools, and commands, making it suitable for development scenarios that require offline operation.
Read Moredsh-llmwiki: Local Markdown Long-term Memory Plugin for DeepSeek Harness
dsh-llmwiki is a DSH plugin developed and maintained by chancelu, designed to address the issues of limited context windows in agent models and the lack of long-term memory. It utilizes a local Markdown vault as long-term memory storage for DeepSeek Harness, enabling continuous utilization by injecting relevant Wiki knowledge into model requests. The plugin provides `memory_search` and `memory_save` tools, supports the automatic capture of daily sessions to a specified directory, and employs three retrieval strategies: keywords, Wiki link graphs, and timestamps. It combines the Reciprocal Rank Fusion (RRF) algorithm to merge results and assembles context within the token budget. It features an LRU + TTL caching mechanism and has no runtime dependencies other than Node.js (version 22 or higher).
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