kepano/obsidian-skills
Obsidian Skills provides a collection of agent skills enabling AI agents to interact with Obsidian vaults, facilitating content creation and editing of Markdown, Bases, and JSON Canvas files, as we...
Awesome AI Agents › AI Agent Development
mpaepper/llm_agents
The project "llm_agents" is a small library designed to build intelligent agents controlled by large language models (LLMs). It is inspired by the Langchain framework but aims to provide a simpler and more understandable implementation with fewer lines of code and less abstraction. The core idea is to create agents that can solve tasks by interacting with various tools under the guidance of an LLM. The agent operates in a loop consisting of Thought, Action, and Observation phases. The LLM generates the Thought and Action components, while the Observation is derived from the execution of tools such as Python code execution in a REPL, Google search via SerpAPI, and Hacker News search. The agent continuously updates its prompt with new information from each cycle, allowing it to refine its actions and eventually provide a final answer. The library is designed for ease of use and experimentation, allowing users to install it locally and run a sample agent script. It requires environment variables for API keys to access OpenAI and SerpAPI services. Users can create their own agents by combining the provided LLM interface and tools or by developing custom tools tailored to their needs. The project includes references to a Hacker News discussion and a blog post for deeper insights into the design and functionality of LLM-guided agents. Overall, this project serves as an educational and practical tool for understanding and building LLM-driven agents with a focus on simplicity and clarity, making it accessible for developers interested in AI agent architectures and tool integration.
https://github.com/mpaepper/llm_agents
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