Frameworks
AutoGPT is a framework for creating a GPT-powered agent. You define a series of scripts that interact with the OpenAI API to generate text, save or process the results as necessary, and then send followup queries.
Zvi (Don’t Worry about the Vase) offers a summary on AutoGPT:
AutoGPT.net is a whole web site devoted to using AutoGPT
Installation and how to get started
Twitter thread by @hasantoxr
General
Lilian Weng has an in-depth description at LLM Powered Autonomous Agents
Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.
Microsoft AutoGen
AutoGen is a GitHub-based framework for development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools.
AutoChain
AutoChain takes inspiration from LangChain and AutoGPT and aims to solve both problems by providing a lightweight and extensible framework for developers to build their own agents using LLMs with custom tools and automatically evaluating different user scenarios with simulated conversations. Experienced user of LangChain would find AutoChain is easy to navigate since they share similar but simpler concepts
ToolLLM
[ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world API
Tool use is a paradigm where a language model produces words that trigger certain APIs to be called with the output being piped back in as tokens to the language model. This means that language models can use calculators, web browsers, and even coding environments. With the recent release of powerful open source language models, you can collect 40k+ viable APIs and fine-tune the model to use them. When you do this, you get a powerful Toolformer.
MetaGPT
MetaGPT: The Multi-Agent Framework > MetaGPT: Simulates a whole software company 🤔 > > It assigns roles like product managers, architects, project managers, and engineers to GPTs. > > With just one line of code, MetaGPT generates user stories, competitive analyses, requirements, data structures, APIs, documents, and more.
via TuringPost
GPT Researcher
The agent can produce detailed, factual and unbiased research reports, with customization options for focusing on relevant resources, outlines, and lessons. Inspired by AutoGPT and the recent Plan-and-Solve paper, GPT Researcher addresses issues of speed and determinism, offering a more stable performance and increased speed through parallelized agent work, as opposed to synchronous operations.