elder-plinius/CL4R1T4S
CL4R1T4S is a project that provides transparency by collecting and sharing the hidden system prompts and guidelines used by major AI models and agents to promote trust and understanding of AI behavior.
Awesome AI Agents › LLM Research Repositories
vonzosten/awesome-LangGraph
Awesome LangGraph and LangChain Ecosystem is a curated index of frameworks, templates, tooling and real-world projects for building stateful, tool-using agents on the LangChain stack. The list opens with an overview of the ecosystem components and what each one is for: LangChain as the foundational library of integrations and composable components with agent abstractions built on top of LangGraph; LangGraph itself as the framework for stateful multi-agent systems with complex workflows, collaboration and memory management; Deep Agents as a harness for agents that plan, decompose complex tasks, use subagents, manage large context through filesystem tools and persist long-term memory; LangSmith as the platform layer for tracing, evaluation, prompt engineering, agent server deployment and sandboxes; LangSmith Fleet as a no-code way to build agents from templates with approvals and oversight; and the third-party integration and partner packages. Collapsible sections document core LangChain building blocks such as agents, models, messages, tools, short-term memory and streaming, along with advanced topics including long-term memory and guardrails. The bulk of the repository is a catalogue organised around the agent development lifecycle of building, observing, evaluating and deploying, plus official LangChain and LangGraph projects and prebuilt agent libraries. Community projects are grouped by use case across more than twenty categories including bio and health, web automation and scraping, business intelligence and market research, chat interfaces, cloud and DevOps, coding agents, customer operations, data platforms, data science, developer tools, finance, marketing, media, robotics and embodied AI, retrieval augmented generation and document processing, research agents, cybersecurity and sustainability. Further sections collect starter templates, learning resources, additional references and communities, and a contributing guide invites additions. It is aimed at teams choosing components or looking for prior art within this specific stack.
https://github.com/vonzosten/awesome-LangGraph
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