ToolLLM is a project that aims to create a large-scale dataset for training language models with tool-use capabilities. They collect instructions involving real-world APIs and develop a new annotation approach to improve efficiency. The project provides the ToolLLaMA model, which performs well in handling single-tool and complex multi-tool instructions. They also release the ToolLLaMA-7b, ToolLLaMA-7b-LoRA, and ToolLLaMA-2-7b models, along with a tool retriever. They evaluate the models using pass rate and preference metrics, showing good performance compared to other models. Overall, ToolLLM empowers language models to understand and use real-world tools effectively.

OlaGPT is a newly developed framework that enhances large language models by simulating human-like problem-solving abilities. It incorporates six cognitive modules, including attention, memory, reasoning, learning, decision-making, and action selection. The model was evaluated on algebraic word problems and analogical reasoning questions, showing superior performance against existing benchmarks. OlaGPT is integrated with pre-existing models such as GPT-3 as base models, with different cognitive modules added. Although the framework has limitations that prevent it from providing a creative solution, it is a promising tool that could approximate the human brain model.

https://www.mlwires.com/2023/06/olagpt-boosts-llms-with-human-like.html

DreamGPT, the first GPT-based solution that uses hallucinations from LLMs for divergent thinking to generate new innovative ideas. Hallucinations are often seen as a negative thing, but what if they could be used for our advantage? dreamGPT is here to show you how. The goal of dreamGPT is to explore as many possibilities as possible, as opposed to most other GPT-based solutions which are focused on solving specific problems.

Tree-of-Thought (ToT) aims to enhance the problem-solving capabilities of large language models (LLMs) like GPT-4. The framework utilizes a deliberate 'System 2' tree search approach to tackle complex and general problems that LLMs struggle with. The author demonstrates significant improvements on three tasks: the game of 24, creative writing, and crosswords, which GPT-4 and CoT (chain of thought, another approach) find challenging due to the need for planning and searching. The limitations of token-by-token decoding, which lacks lookahead, backtrack, and global exploration, are highlighted as the reason for these difficulties. ToT achieves a tenfold performance boost by leveraging the LLM's ability to generate diverse intermediate thoughts, self-evaluate them through deliberate reasoning, and employ search algorithms like breadth-first search (bfs) or depth-first search (dfs) to systematically explore the problem space.

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SmartGPT is an experimental program meant to provide LLMs (particularly GPT-3.5 and GPT-4) with the ability to complete complex tasks without user input by breaking them down into smaller problems, and collecting information using the internet and other external sources.

An experiment where an autonomous GPT (Generative Pre-trained Transformer) agent is given access to a browser to perform tasks. For example adding text to a webpage and making restaurant reservations. gpt-assistant requires Node.js, an OpenAI API key, and a Postgres database.

MiniChain is a library used to link prompts together in a sequence, with the ability to manipulate and visualize them using Gradio. Users can ensure the prompt output matches specific criteria through the use of data classes and typed prompts. The library does not manage documents or provide tools, but suggests using the Hugging Face Datasets library for that purpose. Additionally, users can include their own backends.

Demo

The AutoGPT website offers an AI buddy that can be set up with initial roles and goals without the requirement of human supervision. This AI tool automatically leverages all available resources to achieve your set goal. The tool is inspired by Auto-GPT and features internet access for information gathering and searches. It also allows users to save chat history, credentials, and definition of AI directly in the browser.

The paper explores the potential of developing autonomous cooperation for conversational language models without relying heavily on human input. The proposed framework named role-playing utilizes inception prompting to direct chat agents toward tasks that align with human intentions while enhancing consistency. The role-playing framework produces conversational data for investigating the behaviors and capabilities of language models, resulting in a valuable resource for studying conversational language models. The authors' contributions include the introduction of a novel communicative agent framework, offering a scalable approach for investigating multi-agent systems, and making the library available for further research on communicative agents.

This project aimed to develop a minimal autonomous llm agent using Python code and shell commands, with minimal external dependencies. The agent is expected to solve the objective without relying on additional resources beyond what is provided.

Taxy AI is an organization focused on transforming the role of AI in human-computer interaction. They currently offer a self-hosted browser extension that interacts with a user's browser to execute natural language commands. The organization is working towards implementing new features such as voice-to-command, support for future LLMs, and auto-streamlined workflows.

Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, Auto-GPT pushes the boundaries of what is possible with AI.