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Awesome GitHub RepositoriesAgentic Interaction Patterns

Reusable structural patterns for organizing AI agent communication and task processing.

Distinct from Deterministic Interaction Patterns: Focuses on high-level agent orchestration patterns like map-reduce and evaluator-optimizer, whereas the parent focuses on deterministic output consistency.

Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Agentic Interaction Patterns. Refine with filters or upvote what's useful.

Awesome Agentic Interaction Patterns GitHub Repositories

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  • facebookresearch/parlaifacebookresearch 的头像

    facebookresearch/ParlAI

    10,625在 GitHub 上查看↗

    ParlAI is a conversational AI research framework designed for training, evaluating, and sharing dialogue models using a unified interface for datasets and agents. It functions as a PyTorch-based training platform and a dialogue data collection system, providing a centralized model zoo for the distribution of versioned pretrained agents. The project distinguishes itself through a knowledge-grounded retrieval system that combines dense and sparse indexing to ground responses in external information. It also provides a comprehensive infrastructure for gathering human-AI interaction data via inte

    Defines interaction loops and environments to manage how multiple agents exchange messages in sequences or batches.

    Python
    在 GitHub 上查看↗10,625
  • lastmile-ai/mcp-agentlastmile-ai 的头像

    lastmile-ai/mcp-agent

    8,037在 GitHub 上查看↗

    mcp-agent is a framework for building AI agents that integrate with Model Context Protocol servers to execute tools and access data. It functions as a multi-agent orchestrator and protocol-compliant server, enabling the creation of agents that can discover and invoke tools from connected external servers. The project distinguishes itself through a durable workflow engine that supports long-running tasks capable of pausing, resuming, and surviving restarts. It implements complex orchestration patterns, including iterative evaluator-optimizer loops, hierarchical workflow nesting, and specialist

    Implements complex interaction patterns including parallel map-reduce and evaluator-optimizer loops.

    Pythonagentsaiai-agents
    在 GitHub 上查看↗8,037
  • kyegomez/swarmskyegomez 的头像

    kyegomez/swarms

    6,888在 GitHub 上查看↗

    Swarms 是一个多代理编排框架和自主代理工具包,旨在协调大语言模型代理。它作为一个用于管理代理关系的工作流引擎,提供了构建具有集成内存、工具调用能力和推理循环的自主代理的基础设施。 该框架的特色在于其多代理共识系统,利用投票、对抗性辩论和裁判代理来合成高质量的响应。它支持多种协作模式,包括导演-工作者层次结构、专家合成以及基于自然语言描述的自动化群体架构生成。 该系统涵盖了广泛的运营功能,包括通过领域特定语言进行基于图和顺序的工作流编排、针对不同模型提供商的统一接口,以及与 Model Context Protocol 的集成以实现动态工具发现。它还包括对检索增强生成、状态持久内存以及将代理功能公开为 Web 服务的能力的支持。 该项目提供用于代理管理的命令行界面,并支持通过 YAML 和模块化 markdown 技能文件进行配置。

    Enables the use of arbitrary callables as social algorithms to dictate how agents communicate and sequence interactions.

    Python
    在 GitHub 上查看↗6,888
  1. Home
  2. Artificial Intelligence & ML
  3. Language Model Orchestration
  4. Language Model Interaction Patterns
  5. Deterministic Interaction Patterns
  6. Agentic Interaction Patterns

探索子标签

  • Custom Communication AlgorithmsUse of arbitrary callables as social algorithms to define agent interaction sequences. **Distinct from Agentic Interaction Patterns:** Distinct from Agentic Interaction Patterns: allows the implementation of arbitrary logic (callables) to dictate communication flow.