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Memory and Context Systems · Awesome GitHub Repositories

5 repos

Awesome GitHub RepositoriesMemory and Context Systems

Provides persistent storage, state management, and retrieval mechanisms for maintaining agent history and situational awareness.

Explore 5 awesome GitHub repositories matching artificial intelligence & ml · Memory and Context Systems. Refine with filters or upvote what's useful.

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  • langchain-ai/langchain

    langchain-ai/langchain

    127,015GitHubView on GitHub↗

    LangChain is an orchestration framework designed for building, managing, and deploying applications powered by large language models. It provides a unified integration layer that normalizes disparate model provider APIs into a consistent set of primitives, enabling developers to build complex, multi-step AI workflows t

    Pythonagentsaiai-agents
  • Shubhamsaboo/awesome-llm-apps

    Shubhamsaboo/awesome-llm-apps

    96,116GitHubView on GitHub↗

    This repository serves as a comprehensive collection of resources, templates, and starter code for building artificial intelligence applications. It provides a centralized hub for developers to access practical implementations of common workflows, including retrieval-augmented generation pipelines and autonomous agent

    Pythonagentsllmspython
  • punkpeye/awesome-mcp-servers

    punkpeye/awesome-mcp-servers

    81,101GitHubView on GitHub↗

    This project serves as a centralized directory and interoperability hub for the Model Context Protocol, providing a curated collection of standardized service connectors that bridge artificial intelligence models with external software, databases, and APIs. It facilitates the integration of AI agents with diverse ecosy

    aimcp
  • modelcontextprotocol/servers

    modelcontextprotocol/servers

    79,000GitHubView on GitHub↗

    The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service envir

    TypeScript
  • dair-ai/Prompt-Engineering-Guide

    dair-ai/Prompt-Engineering-Guide

    70,526GitHubView on GitHub↗

    This project is a comprehensive educational resource and knowledge base dedicated to the development and application of large language models and autonomous agentic systems. It provides a structured framework for understanding prompt engineering, context management, and the architectural patterns required to build task

    MDXagentagentsai-agents

Explore sub-tags

  • Agent Memory Architectures2 sub-tagsFrameworks that implement tiered storage systems to manage and retrieve conversation context and historical interaction data for agents.
  • Agent Memory ModulesComponents that manage the persistence of agent logs and past environmental observations.
  • Agent Storage Backends1 sub-tagInfrastructure components that provide agents with virtualized filesystem access and controlled data persistence capabilities.
Agentic Context Management
Systems that manage, store, and retrieve relevant information to maintain continuity across long-running agent interactions.
  • Context Injection FrameworksFrameworks that augment language model reasoning by injecting structured, real-time data and documentation.
  • Conversational Memory SystemsArchitectures that manage and store historical interaction data to provide context for ongoing artificial intelligence conversations.
  • Memory SystemsArchitectures that provide long-term and short-term storage for agents to recall past experiences and data.
  • Persistence Layers1 sub-tagStorage solutions and backends used to maintain the state of machine learning applications over time.