Agents

memary: Open-Source Longterm Memory for Autonomous Agents

memary demo

Why use memary?

Agents use LLMs that are currently constrained to finite context windows. memary overcomes this limitation by allowing your agents to store a large corpus of information in knowledge graphs, infer user knowledge through our memory modules, and only retrieve... See more

Introduction

VT.ai is a multi-modal AI Chatbot Assistant, offering a chat interface to interact with Large Language Models (LLMs) from various providers. Both via remote API or running locally with Ollama.

The application supports multi-modal conversations, seamlessly integrating text, images, and vision processing with LLMs.

[Beta] Multi-modal AI... See more

Large Language Model State Machine (llmstatemachine)

Introduction

llmstatemachine is a library for creating agents with GPT-based language models and state machine logic.

• Chat History as Memory : Leverages large context window models, making chat history the primary source of agent memory.


• Custom Python Functions with JSON Generation : Allows the

... See more

So right now, LLMs (Large Language Models) are all the rage. But in the future, it’s possible that the way we get things done is composing things with a combination of LLMs, SMMs (Small, Mighty Models), agents and tools.

It’s what I call Cognitive Composition (because it sounds cool and I have a longtime love affair with alliteration).

This is how we... See more

🔎 GPT Researcher

GPT Researcher is an autonomous agent designed for comprehensive online research on a variety of tasks.

The agent can produce detailed, factual and unbiased research reports, with customization options for focusing on relevant resources, outlines, and lessons. Inspired by the recent Plan-and-Solve and RAG (Retrieval Augmented... See more

📖 Introduction

XAgent is an open-source experimental Large Language Model (LLM) driven autonomous agent that can automatically solve various tasks. It is designed to be a general-purpose agent that can be applied to a wide range of tasks. XAgent is still in its early stages, and we are working hard to improve it.

🏆 Our goal is to create a... See more

The problem I've found with all of them is it is difficult to get consistent solid results that you would want to build around. Even listening to podcasts this seems to be a theme with the people at the forefront of MAS LLMs.

The LLM doesn’t call the tool directly (yet), but it does pass back to the application what functions should be called — and with which parameters. And, now, OpenAI lets multiple function calls be “invoked” at once.

But, this idea is not just about GPT. The open source world is moving towards this model as well.

This Is The Future…It’s Just Not Here... See more

The two most important problems (at least how I am thinking about them currently), are:

Finding a rigorous scientific framework for how different agent skills, personalities, and instructions combine to be most capable for different problems (think of this as social management science for AI agents) .

Figuring out how you formally validate and verify... See more