10 results
Cherry Studio-style knowledge base system for DeepSeek Harness (DSH): bases, documents, chunking, embeddings (OpenAI-compatible / Ollama / local / lexical fallback), retrieval, model-facing tools, and a browser management panel
DeepSeek Harness (DSH) local-first cross-session project memory: bounded cache-friendly Hot Memory, BM25 recall/cache, provenance, lifecycle and bilingual Web GUI; no embeddings, external service or bundled runtime dependencies.
L0~L3 分层蒸馏记忆插件 for DeepSeek Harness：自动捕获对话（L0）、抽取原子记忆（L1）、整合场景块（L2）、蒸馏核心画像/团队方法论（L3），并在模型步骤前自动召回注入。移植自 MemoryCore (TencentDB Agent Memory) 的管线设计。
Cross-session plaintext memory plugin for the DeepSeek Harness — deterministic BM25 recall, human-owned, no embeddings
AiFP Cognitive Memory — persistent memory MCP server for AI assistants. Chinese-first retrieval with causal chains, Hebbian associations and graph diffusion. 记忆感知系统
Local-first RAG knowledge tools for DSH: kb_query / kb_ingest / kb_crawl / kb_related, backed by the kb-rag Python pipeline (Ollama bge-m3 + ChromaDB + SiYuan). Zero API cost, data never leaves your machine.
Cross-session long-term memory for DeepSeek Harness: dual-scope SQLite memory graph, hybrid retrieval, provenance audit, and a knowledge flywheel.
为 AI Agent 提供短期记忆缓存、长期知识沉淀、语义检索与持久化存储的统一记忆管理层
DeepSeek Harness (DSH) plugin: a self-contained semantic memory (RAG) over all your chat sessions. Indexes messages live via session/event, stores embeddings in one local JSON file, and exposes a rag_search tool.
Persistent, searchable, per-project memory for the DeepSeek Harness: decisions, rules, and sprint context in a queryable DuckDB file, rules enforced on every model request, with a full management UI in the Web Client