Results for “memory-server”

Diagnoses Linux server issues across CPU, memory, disk, I/O, and network, and manages systemd services, SSH, and Fail2Ban on Ubuntu, Debian, and AlmaLinux.

Persistent cross-session memory for AI agents. Mem0 stores user preferences, past decisions, domain knowledge, and agent learnings across all sessions, all tools, and all users. Complements planning-with-files (task-level memory) with long-term agent intelligence (CRM + personal knowledge base layer). Use when asked to "remember this", "store preference", "mem0", "long-term memory", "user memory", "agent memory", or when building multi-session agents that need to recall past interactions.

Reclaim DRAM on NVIDIA Jetson devices by disabling unused display, camera, and DMA subsystems across MB1 BCT, MB2 BCT, kernel reserved-memory, and SWIOTLB layers for headless or no-camera deployments.

Merges mature lessons from a domain memory file into its instruction file, preserving knowledge with minimal redundancy.

Designs persistent memory architectures for AI agents, covering cross-session knowledge retention, entity tracking, temporal validity, graph/vector retrieval, and memory consolidation.

Memory System Management

Provides persistent, self-hosted semantic memory for AI agents via MCP, storing worklogs, decisions, and notes in PostgreSQL with pgvector for meaning-based retrieval across sessions.

Persistent cross-session memory management. Enables agents to remember user preferences, project conventions, and past decisions across different sessions using a structured MEMORY.md index and topic files.

Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.

Integrates Mem0 Platform SDK for persistent memory in AI applications. Use when building agents or chatbots that need to remember user preferences, past interactions, or personalized context across sessions. Covers Python and TypeScript SDKs, plus LangChain, CrewAI, OpenAI Agents, LlamaIndex, AutoGen, and LangGraph integrations.

Persists and recalls agent knowledge across sessions using four approaches: static KB, company wiki, persistent memory, and session brain.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Server management principles and decision-making. Process management, monitoring strategy, and scaling decisions. Teaches thinking, not commands.

Orchestrate persistent agent memory across coding sessions, repos, and tools. Load when the user asks to remember, recall context, save project memory, create a handoff, manage global memory, update memory, compact memory, audit memory, forget memory, continue from prior sessions, or before commit/push/git operations that checkpoint project state.

Organiza y guarda memoria en Engram automáticamente, clasificando cada conocimiento por tipo y área, y consultando el contexto al iniciar sesión.

Save information to persistent memory for cross-session recall. Stores preferences, conventions, decisions, and context.

Configure memorystore config operations. Auto-activating skill for GCP Skills. Triggers on: memorystore config, memorystore config Part of the GCP Skills skill category. Use when configuring systems or services. Trigger with phrases like "memorystore config", "memorystore config", "memorystore".

Detects available memory tools and maps them to a structured memory system for cross-session recall, with file-based fallback.

Memory systems specialist for hierarchical memory, consolidation, and outcome-based learningUse when "memory system, memory hierarchy, memory consolidation, forgetting strategy, salience learning, outcome feedback, temporal memory levels, entity resolution, memory, zep, graphiti, mem0, letta, hierarchical, consolidation, salience, forgetting, ml-memory" mentioned.

Imported skill memory from langchain

Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk).

Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk).

Add persistent, intelligent memory to AI agents with Mem0 — add/search/update/delete memories per user/agent/session, supports vector + graph + key-value storage, integrates with LangChain, CrewAI, OpenAI Assistants, and any LLM.

You are an expert in Mem0, the memory infrastructure for AI applications. You help developers add persistent, personalized memory to LLM-powered apps and agents — storing user preferences, conversation history, facts, and context that persists across sessions, enabling AI that remembers users, learns from interactions, and provides increasingly personalized responses.

Persist decisions, preferences, and project state across sessions using structured memory types

Plan and apply safe, reversible headless-mode changes on Jetson devices to reclaim memory from the GUI and non-essential daemons.

Estimates the memory required to load Safetensors or GGUF model weights for inference from the Hugging Face Hub, using HTTP Range requests without downloading weights.

Diagnoses and reduces Qdrant memory usage by analyzing resident memory, page cache, and providing optimization techniques like quantization, on-disk storage, and async_scorer.

Maintain durable session memory across agent disconnects by writing structured checkpoints to the repo's session directory, enabling context recovery.

Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.

Persists context across sessions by compiling sources into a local SQLite store and markdown tree, then retrieves relevant memory via embedding search.