GitHub stars exceed 160,000, and the popular advanced version of AutoGPT is here: customized nodes, multi-agent collaboration

Of course, the next generation of AutoGPT is still open source.

Do you still remember the “AutoGPT” project that AI guru Andrej Karpathy vigorously promoted last year? It is an experimental open source application powered by GPT-4 that can autonomously achieve any goal set by the user, demonstrating the development trend of autonomous AI.

In more than a year, the total number of GitHub stars for this project has exceeded 160,000, which shows its continued popularity.

GitHub address: https://github.com/Significant-Gravitas/AutoGPT

Yesterday, the project author announced the arrival of the next generation "AutoGPT" on social media X, which is currently a Pre-alpha version. Compared with the previous generation, the next generation "AutoGPT" makes it easier than ever to build, run and share AI agents, while also greatly improving reliability.

                                      ^{Source: https://x.com/SigGravitas/status/1812803289739633018}

The author shows how to use the next generation "Auto GPT" quickly builds, deploys and uses Reddit marketing agents that automatically Reply to comments and perform other complex tasks. The new system is no longer as unreliable and inefficient as the first version of "AutoGPT".

When asked whether this project can build multi-agent driven applications, the author gave a positive answer and stated that this was an important reason for building this project.

Now, you can design a diagram to let multiple expert agents collaborate to solve problems. SubGraphs is also coming soon to help simplify working with complex graphs.

The project can also be customized to add nodes, and writing new blocks manually (key feature mentioned below) is very simple. The author found that Claude did an excellent job in this regard and created custom blocks flawlessly.

Of course, the two main components of the project (i.e. Server and Builder mentioned below) can run on different machines.

However, for the next generation of "AutoGPT", the author admits that it is still in a very early stage, has flaws and is relatively basic, but still hopes to share it with everyone and open source it from the beginning.

Main components and key features

This project has the following two main components, which are the AutoGPT Server on the backend and the AutoGPT Builder on the frontend. The Server is responsible for creating a composite multi-agent system, using AutoGPT agents and other non-agent components as its primitives.

• AutoGPT Server (Backend):

• https://github.com/Significant-Gravitas/AutoGPT/tree/master/rnd/autogpt_server

• AutoGPT Builder (Frontend):

• https ://github.com/Significant-Gravitas/AutoGPT/tree/master/rnd/autogpt_builder

The specific steps to set up and run Server and Builder are as follows:

• Navigate to the AutoGPT GitHub repository;

• Click the "Code" button and select "Download ZIP";

• After downloading, unzip the ZIP file to a folder of your choice;

• Open the unzipped folder and navigate to "rnd ” directory;

• Enter the “AutoGPT Server” folder;

• Open a terminal window in the “rnd” directory;

• Find and open the README file in the AutoGPT Server folder;

• Copy and paste each command in the README into your terminal (Important: wait for each command to complete before running the next one);

• If all commands run without errors, enter the last command " poetry run app";

• See that the server is running in the terminal;

• Navigate back to the "rnd" folder;

  O Ouvrez le dossier "AutoGPT Builder" ; ouvrez le fichier readme dans ce dossier ; exécutez la commande suivante dans le terminal :

• R

  npm install

  EE

• npm run devOnce the front-end is running, click the link to navigate to localhost:3000.

  E

• Après avoir exécuté le front-end, cliquez sur le lien pour accéder à " LocalHost: 3000 ";

cliquez l'option" build ";

add quelques blocs pour tester les fonctionnalités; Vérifiez la fenêtre de votre terminal. À ce stade, vous devriez voir que le serveur a reçu la demande, la traite et l'a exécutée.

• Suivez les étapes ci-dessus et vous pourrez configurer et tester avec succès AutoGPT.
                              Source vidéo : https://github.com/Significant-Gravitas/AutoGPT/tree/master/rnd/
La clé du GPT La fonctionnalité est utiliser des "Blocs" pour construire agents intelligents. Vous pouvez combiner des fonctionnalités hautement modulaires pour créer des comportements personnalisés.

• Actuellement, le projet a fourni des blocs correspondants pour des opérations telles que la publication sur Reddit, l'envoi de messages Discord et la récupération de résumés Wikipédia. En même temps, il est conçu pour être facile à créer et à utiliser. Voici un exemple de bloc tiré du résumé de Wikipédia :

class GetWikipediaSummary(Block):class Input(BlockSchema):topic: strclass Output(BlockSchema):summary: strdef **init**(self):super().__init__(id="h5e7f8g9-1b2c-3d4e-5f6g-7h8i9j0k1l2m",input_schema=GetWikipediaSummary.Input,output_schema=GetWikipediaSummary.Output,test_input={"topic": "Artificial Intelligence"},test_output={"summary": "Artificial intelligence (AI) is intelligence demonstrated by machines..."},)def run(self, input_data: Input) -> BlockOutput:response = requests.get(f"https://en.wikipedia.org/api/rest_v1/page/summary/{input_data.topic}")summary_data = response.json()        yield "summary", summary_data['extract']

• L'auteur a déclaré que ce n'est que le début et que d'autres blocs seront ajoutés à l'avenir, ainsi que l'amélioration de l'interface utilisateur, améliorant considérablement l'expérience globale. et la fonctionnalité.

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