awesome-ai-agents

Welcome to our list of AI agents. We structured the list into two parts:

• Open source projects
• Closed-source projects and companies

To filter the products by categories and use-cases, see the 🌟 web version of this list. 🌟

The list is done according to our best knowledge, although definitely not comprehensive. Check out also the Awesome List of SDKs for AI Agents. Discussion and feedback appreciated! :heart:

Have anything to add?

Create a pull request or fill in this form. Please keep the alphabetical order and in the correct category.

For adding AI agents'-related SDKs, frameworks and tools, please visit Awesome SDKs for AI Agents. This list is only for AI assistants and agents.

Check out E2B - Code Interpreting for AI apps

• Check out Code Interpreter SDK
• Explore examples in E2B Cookbook
• Read our docs
• Contact us at [email protected] or on Discord. Follow us on X (Twitter)

Open-source projects

Adala

Adala: Autonomous Data (Labeling) Agent framework

Category

General purpose, Build your own, Multi-agent

Description

• Reliable agents: Built on ground truth data for consistent, trustworthy results.
• Controllable output: Tailor output with flexible constraints to fit your needs.
• Specialized in data processing: Agents excel in custom data labeling and processing tasks.
• Autonomous learning: Agents evolve through observations and reflections, not just automation.
• Flexible and extensible runtime: Adaptable framework with community-driven evolution for diverse needs.
• Easily customizable: Develop agents swiftly for unique challenges, no steep learning curve.

Links

• Documentation
• Discord
• GitHub

Agent4Rec

Recommender system simulator with 1,000 agents

Category

General purpose, Build your own, Multi-agent

Description

• Agent4Rec is a recommender system simulator that utilizes 1,000 LLM-empowered generative agents.
• These agents are initialized from the MovieLens-1M dataset, embodying varied social traits and preferences.
• Each agent interacts with personalized movie recommendations in a page-by-page manner and undertakes various actions such as watching, rating, evaluating, exiting, and interviewing.

Links

• Paper

AgentForge

LLM-agnostic platform for agent building & testing

Category

General purpose, Build your own, Multi-agent

Description

• A low-code framework designed for the swift creation, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures, compatible with various LLM models.
• Facilitates building custom agents and cognitive architectures with ease.
• Supports multiple LLM models including OpenAI, Anthropic's Claude, and local Oobabooga, allowing flexibility in running different models for different agents based on specific requirements.
• Provides customizable agent memory management and on-the-fly prompt editing for rapid development and testing.
• Comes with a database-agnostic design ensuring seamless extensibility, with straightforward integration with different databases like ChromaDB for various AI projects.

Links

• GitHub
• Web
• Discord
• X

AgentGPT

Browser-based no-code version of AutoGPT

Category

General purpose

Description

• A no-code platform
• Process:
  • Assigning a goal to the agent
  • Witnessing its thinking process
  • Formulation of an execution plan
  • Taking actions accordingly
• Uses OpenAI functions
• Supports gpt-3.5-16k, pinecone and pg_vector databases
• Stack
  • Frontend: NextJS + Typescript
  • Backend: FastAPI + Python
  • DB: MySQL through docker with the option of running SQLite locally

Links

• Documentation
• Website
• GitHub

AgentPilot

Build, manage, and chat with agents in desktop app

Category

General purpose

Description

• Integrated into Open Interpreter and MemGPT
• Group chats feature

Links

• GitHub
• X

Agents

Library/framework for building language agents

Category

General purpose, Build your own, Multi-agent

Description

• Long-short Term Memory: Language agents in the library are equipped with both long-term memory implemented via VectorDB + Semantic Search and short-term memory (working memory) maintained and updated by an LLM.
• Tool Usage: Language agents in the library can use any external tools via function-calling and developers can add customized tools/APIs here.
• Web Navigation: Language agents in the library can use search engines to navigate the web and get useful information.
• Multi-agent Communication: In addition to single language agents, the library supports building multi-agent systems in which language agents can communicate with other language agents and the environment. Different from most existing frameworks for multi-agent systems that use pre-defined rules to control the order for agents' action, Agents includes a controller function that dynamically decides which agent will perform the next action using an LLM by considering the previous actions, the environment, and the target of the current states. This makes multi-agent communication more flexible.
• Human-Agent interaction: In addition to letting language agents communicate with each other in an environment, our framework seamlessly supports human users to play the role of the agent by himself/herself and input his/her own actions, and interact with other language agents in the environment.
• Symbolic Control: Different from existing frameworks for language agents that only use a simple task description to control the entire multi-agent system over the whole task completion process, Agents allows users to use an SOP (Standard Operation Process) that defines subgoals/subtasks for the overall task to customize fine-grained workflows for the language agents.

Links

• Author: AIWaves Inc.
• Paper
• GitHub Repository
• Documentation
• Tweet

AgentVerse

Platform for task-solving & simulation agents

Category

General purpose, Build your own, Multi-agent

Description

• Assembles multiple agents to collaboratively accomplish tasks.
• Allows custom environments for observing or interacting with multiple agents.

Links

• Paper: AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
• Twitter
• Discord
• Hugging Face

AI Legion

Multi-agent TS platform, similar to AutoGPT

Category

Multi-agent, Build-your-own

Description

• An LLM-powered autonomous agent platform
• A framework for autonomous agents who can work together to accomplish tasks
• Interaction with agents done via console direct messages

Links

• Author: eumemic
• Website
• GitHub
• Twitter

Aider

Use command line to edit code in your local repo

Category

Coding, GitHub

Description

• Aider is a command line tool that lets you pair program with GPT-3.5/GPT-4, to edit code stored in your local git repository
• You can start a new project or work with an existing repo. And you can fluidly switch back and forth between the aider chat where you ask GPT to edit the code and your own editor to make changes yourself
• Aider makes sure edits from you and GPT are committed to git with sensible commit messages. Aider is unique in that it works well with pre-existing, larger codebases

Links

• Website
• Author: Paul Gauthier (Github)
• Discord Invite

AIlice

Create agents-calling tree to execute your tasks

Category

General purpose, Personal assistant, Productivity

Description

• "An Agent in the form of a chatbot independently plans tasks given in natural language and dynamically creates an agents calling tree to execute tasks.
• There is an interaction mechanism between agents to ensure fault tolerance.
• External interaction modules can be automatically built for self-expansion.

Links

• GitHub

AutoGen

Multi-agent framework with diversity of agents

Category

General purpose, Build your own, Multi-agent

Description

• A framework for developing LLM (Large Language Model) applications with multiple conversational agents.
• These agents can collaborate to solve tasks and can interact seamlessly with humans.
• It simplifies complex LLM workflows, enhancing automation and optimization.
• It offers a range of working systems across various domains and complexities.
• It improves LLM inference with easy performance tuning and utility features like API unification and caching.
• It supports advanced usage patterns, including error handling, multi-config inference, and context programming.

Links

• Paper: AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
• Discord
• Twitter thread describing the system

AutoGPT

Experimental attempt to make GPT4 fully autonomous

Category

General purpose

Description

• An experimental open-source attempt to make GPT-4 fully autonomous, with >140k stars on GitHub
• Chains together LLM "thoughts", to autonomously achieve whatever goal you set
• Internet access for searches and information gathering
• Long-term and short-term memory management
• Can execute many commands such as Google Search, browse websites, write to files, and execute Python files and much more
• GPT-4 instances for text generation
• Access to popular websites and platforms
• File storage and summarization with GPT-3.5
• Extensibility with Plugins
• "A lot like BabyAGI combined with LangChain tools"
• Features added in release 0.4.0
  • File reading
  • Commands customization
  • Enhanced testing

Links

• Twitter
• GitHub
• Facebook
• Linkedin
• Discord
• Author: Significant Gravitas

Automata

Generate code based on your project context

Category

Coding

Description

• Model: GPT 4
• Automata takes your project as a context, receives tasks, and executes the instructions seamlessly.
• Features
  • Automata aims to evolve into a fully autonomous, self-programming Artificial Intelligence system.
  • It's designed for seamless integration with all available agent platforms and LLM providers.
  • Utilizes the novel code search algorithm, SymbolRank, and associated tools to build superior coding intelligence.
  • Modular, fully configurable design with minimal reliance on external dependencies

Links

• GitHub
• Docs
• Author: Owen Colegrove

AutoPR

AI-generated pull requests agent that fixes issues

Category

Coding, GitHub

Description

• Triggered by adding a label containing AutoPR to an issue, AutoPR will:
  • Plan a fix
  • Write the code
  • Push a branch
  • Open a pull request

Links

• Discord

Autonomous HR Chatbot

Agent that answers HR-related queries using tools

Category

HR, Business intelligence, Productivity

Description

• A prototype enterprise application - an Autonomous HR Assistant powered by GPT-3.5.
• An agent that can answer HR related queries autonomously using the tools it has on hand.
• Powered by GPT-3.5
• Current tools assigned to the agent (with more on the way):
  • Timekeeping Policy
  • Employee Data
  • Calculator

Links

• Medium: Creating a (mostly) Autonomous HR Assistant with ChatGPT and LangChain’s Agents and Tools
• GitHub
• Author: Stephen Bonifacio
• YouTube demo
• Blog post

BabyAGI

A simple framework for managing tasks using AI

Category

General purpose

Description

• A pared-down version of the original Task-Driven Autonomous Agent
• Creates tasks based on the result of previous tasks and a predefined objective.
• The script then uses OpenAI's NLP capabilities to create new tasks based on the objective
• Leverages OpenAI's GPT-4, pinecone vector search, and LangChainAI framework
• Default model is OpenAI GPT3-turbo
• The system maintains a task list for managing and prioritizing tasks
• It autonomously creates new tasks based on completed results and reprioritizes the task list accordingly, showcasing the adaptability of AI-powered language models

Links

• Paper: Task-driven Autonomous Agent Utilizing GPT-4, Pinecone, and LangChain for Diverse Applications
• Discord
• Founder's Twitter
• Twitter thread describing the system

BabyBeeAGI

Task management & functionality BabyAGI expansion

Category

General purpose, Productivity

Description

• A more advanced version of the original BabyAGI code
• • Improves upon the original framework, by introducing a more complex task management prompt, allowing for more comprehensive analysis and synthesis of information
• Designed to handle multiple functions within one task management prompt
• Built on top of the GPT-4 architecture, resulting in slower processing speeds and occasional errors
• Provides a framework that can be further built upon and improved, paving the way for more sophisticated AI applications
• One of the significant differences between BabyAGI and BabyBeeAGI is the complexity of the task management prompt

Links

• Tweet
• GitHub
• Replit
• Author: @yoheinakajima (Twitter)

BabyCatAGI

BabyCatAGI is a mod of BabyBeeAGI

Category

General purpose

Description

• Just 300 lines of code
• This was built as a d iteration on the original BabyAGI code in a lightweight way. Differences to BabyAGI include the following:
  • Task Creation Agent runs once
  • Execution Agent loops through tasks
  • Task dependencies for pulling relevant results
  • Two tools: search tool and text completion
  • “Mini-agent” as tool
  • Search tool combines search, scrape, chunking, and extraction.
  • Results combined to create summary report

Links

• Tweet
• GitHub
• Replit
• Author: @yoheinakajima (Twitter)

BabyDeerAGI

Mod of BabyAGI with only ~350 lines of code

Category

General purpose

Category

General purpose

Description

• Features
  • Parallel tasks (making it faster)
  • 3.5-turbo only (GPT-4 not required)
  • User input tool
  • Query rewrite in web search tool
  • Saves results

Links

• Tweet
• GitHub
• Replit
• Author: @yoheinakajima (Twitter)

BabyElfAGI

Mod of BabyDeerAGI, with ~895 lines of code

Category

General purpose

Description

• Features
  • Skills class allows for creation of new skills
  • 'Dynamic task list' example with vector search
  • Beta reflection agent
  • Can read, write, and review its own code

Links

• Tweet
• GitHub
• Replit
• Author: @yoheinakajima (Twitter)

BabyCommandAGI

Test what happens when you combine CLI and LLM

Category

General purpose, Coding

Description

• gent designed to test what happens when you combine CLI and LLM, which are more traditional interfaces than GUI (created by @saten-private)
• An AI agent based on @yoheinakajima's BabyAGI which executes shell commands
• Automatic Programming, Successfully created an app automatically just by providing feedback. The procedure can be found here.
• Automatic Environment Setup, Successfully installed a Flutter environment on Linux in a container, created the Flutter app, and launched it. The procedure can be found here.
• Aside from setting up the environment, it seems to be able to handle a bit of general tasks such as Generating text, like poems, code, scripts, musical pieces, email, and letters, translating languages
• There is a risk of breaking the environment. Please run in a virtual environment such as Docker.
• GPT-4 or higher is recommended

Links

• Founder's Twitter
• Twitter thread describing the system

BabyFoxAGI

Mod of BabyAGI with a new parallel UI panel

Category

General purpose

Description

• A mod of BabyElfAGI, in a series of mods w the naming of BabyAGI in alphabetical order
• Self-improving task lists (FOXY method)
  • By storing a final reflection at the end, and pulling the most relevant reflection to guide future runs, BabyAGI slowly generates better and better tasks lists
• Novel Chat UI w parallel tasks
  • You can chat w BabyAGI! It has an experimental UI where the chat is separate from the tasks/output panel, allowing you to request multiple tasks in parallel
  • The Chat UI can use a single skill quickly, or chain multiple skills together using a tasklist
• New skills
  • 🎨 DALLE skill with prompt assist
  • 🎶 Music player w Deezer
  • 📊 Airtable search (add your own table/base ID)
  • 🔍 Startup Analyst (example of beefy function call as a skill)
• It’s own README

Links

• Author's Twitter
• Twitter thread describing the system
• Replit

BambooAI

Data exploration and analysis for non-programmers

Category

Data analysis

Description

• BambooAI runs in a loop (until user decides to end it).
• Allows mixing of different models with different capabilities, token costs and context windows for different tasks.
• Maintains the memory of previous conversations.
• Builds the prompts dynamically utilising relevant context from Pinecone vector DB.
• Offers a narrative or asks follow up questions if required.
• For codified responses, the task is broken down into a list of steps and a pseudo-code algorithm is built.
• Based on the algorithm, it ises the python code for dataset analysis, modeling or plotting.
• Debugs the code which then executes, auto-corrects if needs to, and displays the output to user.
• Ranks the final answers, and asks user for feedback.
• Builds a vector DB knowledge-base, based on the rank and the user feedback.

Links

• GitHub
• Creators's Twitter

BeeBot

Early-stage project for wide range of tasks

Category

General purpose, Productivity

Description

• "BeeBot is currently a work in progress and should be treated as an early stage research project. Its focus is not on production usage at this time."

Links

• GitHub
• Tweet

Blinky

An open-source AI debugging agent for VSCode

Category

Coding, Debugging

Description

• Blinky is an open-source AI debugging agent for VSCode that uses LLMs to help identify and fix backend code errors (inspired by SWE-agent).
• Blinky leverages the VSCode API, Language Server Protocol (LSP), and print statement debugging to triangulate and address bugs in real-world backend systems.

Links

• VSCode Extension
• Discord
• GitHub

Bloop

AI code search, works for Rust and Typescript

Category

Coding

Description

• A GPT-4 powered semantic code search engine that uses an AI agent
• Precise code navigation
• Built on stack graphs and scope queries
• Fast code search and regex matching engine written in Rust
• Allows to find Code on Rust and Typescript
• Allows to stage changes
• The agent searches both your local and remote repositories with natural language, regex and filtered queries
• Bloop can be run via app (easy to download via GitHub)

Links

• GitHub
• "Getting started" guide
• Bloop apps

BondAI

Code interpreter with CLI & RESTful/WebSocket API

Category

Coding

Description

• A highly capable, autonomous AI Agent with an easy to use CLI, RESTful/WebSocket API, Pre-built Docker image and a robust suite of integrated tools.
• Support for all GPT-N, Embeddings and Dall-E OpenAI Models
• Support for Azure OpenAI Services
• Easy to use SDK for integration into any application
• Powerful Code Interpreter capabilities
• Powerful data query capabilities via Postgres DB integration
• Pre-built Docker image provides safe execution environment for code generation/execution
• Support for telephony applications (via BlandAI)
• Support for stock trading (via Alpaca Markets)
• Integrates with Gmail and Google Search
• Easy to install pip install bondai
• To start the CLI just run bondai
• To start the RESTful/WebSocket API just run bondai --server

Links

• BondAI Homepage/Documentation
• Github Repository
• Docker Image

bumpgen

AI agent that keeps npm dependencies up-to-date

Category

Coding

Description

• Put dependency management and upgrades on autopilot
• bumpgen BUMPs an npm package's version up then GENerates the code fixes for breaking changes
• Supports gpt-4-turbo
• Easy install > npm install -g bumpgen
• Easy start > bumpgen @tanstack/react-query 5.28.14

Links

• Repo
• Docs

Cal.ai

Open-source scheduling assistant built on Cal.com

Category

Productivity

Description

• Cal.ai can book meetings, summarize your week, and find time with others based on natural language.
• Responds flexibly to unseen tasks eg. "move my second-last meeting to tomorrow morning".
• Uses GPT-4 and LangChain Agent Executor under the hood.
• GitHub

Links

• Authors: Cal.com core team, Dexter Storey, Ted Spare

CAMEL

Architecture for “Mind” Exploration of agents

Category

General purpose

Description

• CAMEL is an open-source library designed for the study of autonomous and communicative agents. 1)AI user agent: give instructions to the AI assistant with the goal of completing the task.

2. AI assistant agent: follow AI user’s instructions and respond with solutions to the task

• CAMEL also has an open-source community dedicated to the study of autonomous and communicative agents

Links

• Web
• Paper - CAMEL: Communicative Agents for “Mind” Exploration of Large Scale Language Model Society
• Colab demo
• GitHub
• Hugging face datasets
• Slack
• Twitter
• Authors: Guohao Li∗ Hasan Abed Al Kader Hammoud* Hani Itani* Dmitrii Khizbullin, Bernard Ghanem

ChatArena

A chat tool for multi agent interaction

Category

Design, Build-your-own, SDK for AI apps, Multi-agent

Description

• ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs. ChatArena provides:
• A general framework for building interactive environments for multiple large language models (LLMs).
• A collection of pre-built or community-created environments.
• User-friendly interfaces with both Web UI and commandline interfaces.

Links

• Web
• GitHub
• X
• Slack channel

ChatDev

Communicative agents for software development

Category

Coding, Multi-agent

Description

• ChatDev is a virtual software company driven by a multitude of intelligent agents assuming different roles such as CEO, CPO, CTO, programmer, reviewer, tester, and art designer, each represented by unique icons.
• These agents collaborate in a structured organizational environment, fulfilling the company's mission to "revolutionize the digital world through programming." They engage in functional seminars focusing on design, coding, testing, and documentation.
• ChatDev aims to provide an accessible, modular, and extensible platform based on large language models, facilitating the study of collective intelligence in a controlled setting.
• The framework allows for extensive customization, empowering users to tailor the software development process, define phases, and establish specific roles within the virtual company.
• ChatDev is committed to open-source principles, encouraging contributions from the community and sharing advancements transparently.

Links

• Paper - ChatDev: Communicative Agents for Software Development
• Local demo
• GitHub

ChemCrow

LangChain agent for chemistry-related tasks

Category

Science, Chemistry

Description

• ChemCrow is an open source package for the accurate solution of reasoning-intensive chemical tasks
• It integrates 13 expert-design tools to augment LLM performance in chemistry and demonstrate effectiveness in automating chemical tasks
• Built with Langchain
• The LLM is provided with a list of tool names, descriptions of their utility, and details about the expected input/output. It is then instructed to answer a user-given prompt using the tools provided when necessary. The instruction suggests the model to follow the ReAct format - Thought, Action, Action Input, Observation. One interesting observation is that while the LLM-based evaluation concluded that GPT-4 and ChemCrow perform nearly equivalently, human evaluations with experts oriented towards the completion and chemical correctness of the solutions showed that ChemCrow outperforms GPT-4 by a large margin. This indicates a potential problem with using LLM to evaluate its own performance on domains that requires deep expertise. The lack of expertise may cause LLMs not knowing its flaws and thus cannot well judge the correctness of task results. (Source: Weng, Lilian. (Jun 2023). LLM-powered Autonomous Agents". Lil’Log. https://lilianweng.github.io/posts/2023-06-23-agent/.)

Links

• Paper
• GitHub
• HackerNews Discussion

Clippy

Agent that can plan, write, debug, and test code

Category

Coding

Description

• The purpose of Clippy is to elop code for or with the user.
• It can plan, write, debug, and test some projects autonomously.
• For harder tasks, the best way to use it is to look at its work and provide feedback to it.

Links

• GitHub
• Author: Lev Chizhov

CodeFuse-ChatBot

Agent serving entire SW development lifecycle

Category

Coding

Description

• An intelligent assistant serving the entire software development lifecycle, powered by a Multi-Agent Framework, working with DevOps Toolkits, Code&Doc Repo RAG, etc.

Links

• GitHub

Cody by ajhous44

Query and navigate your codebase

Category

Coding

Description

• An AI assistant designed to let you interactively query your codebase using natural language.
• By utilizing vector embeddings, chunking, and OpenAI's language models, Cody can help you navigate through your code in an efficient and intuitive manner.

Links

• GitHub
• Author: @ajhous44 (Github)

Cody by Sourcegraph

Agent that writes code and answers your questions

Category

Coding

Description

An AI code assistant from Sourcegraph that writes code and answers questions for you by reading your entire codebase and the code graph.

Links

• GitHub
• Author: @sourcegraph (Twitter)

Continue

Open-source autopilot for software development

Category

Coding

Description

• An open-source autopilot for software development—bring the power of ChatGPT to VS Code
• Features:
  • Answer coding questions
  • Edit in natural language
  • Generate files from scratch

Links

• Website
• GitHub
• Documentation
• Twitter

CrewAI

Framework for orchestrating role-playing agents

Category

Build-your-own, SDK for agents, Multi-agent

Description

• Cutting-edge framework for orchestrating role-playing, autonomous AI agents.
• By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
• Crew AI is a multi-agent framework built on LangChain, aiming to empower engineers to harness the collective power of AI agents. In contrast to traditional automation methods, Crew AI introduces a new approach to collaborative decision-making, enhanced creativity, and solving complex problems.
• The design philosophy of Crew AI advocates simplicity through modularity. Its main components include agents, tools, tasks, processes, and crews. Each agent is akin to a team member, possessing specific roles, background stories, goals, and memories. Through modular design, we make the intricate world of AI agents accessible, manageable, and more engaging.

Links

• GitHub
• Founder's X
• Blog post: How to use Crew AI
• Crew AI Wiki with examples and guides
• Docs
• Discord

data-to-paper

AI-driven research from data to human-verifiable research papers

Category

Science, Research, Multi-agent

Description

data-to-paper is a framework for systematically navigating the power of AI to perform complete end-to-end scientific research, starting from raw data and concluding with comprehensive, transparent, and human-verifiable scientific papers.

Towards this goal, data-to-paper systematically guides interacting LLM and rule-based agents through the conventional scientific path, from annotated data, through creating research hypotheses, conducting literature search, writing and debugging data analysis code, interpreting the results, and ultimately the step-by-step writing of a complete research paper.

The data-to-paper framework is created as a research project to understand the capacities and limitations of LLM-driven scientific research, and to develop ways of harnessing LLM to accelerate research while maintaining, and even enhancing, key scientific values, such as transparency, traceability and verifiability, and while allowing scientist to oversee and direct the process [see also: living guidelines].

Links

• GitHub
• arXiv preprint
• Demo video

Databerry

(Pivoted to Chaindesk) No-code chatbot building

Category

Build-your-own

Description

• A super-easy no-code platform for creating AI chatbots trained on your own data
• After creating new agent, picking a model, data and other settings, they are ready to be deployed to website, Slack, Crisp, or Zapier
• Limit of agent in the free version
• Stack
  • Next.js
  • Joy UI
  • LangchainJS
  • PostgreSQL
  • Prisma
  • Qdrant
• Features
  • Streamline customer support, onboard new team members, and more
  • Load data from anywhere
  • No-code: User-friendly interface to manage your datastores and chat with your data
  • Secured API endpoint for querying your data
  • Auto sync data sources (coming soon)
  • Auto generates a ChatGPT Plugin for each datastore

Links

• Documentation
• Discord
• GitHub

DemoGPT

Generates demo of a new app (of any purpose)

Category

Build-your-own, General purpose

Description

• DemoGPT leverages the power of Language Models (LLMs) to provide fast and effective demo creation for applications.
• Automates the prototyping process, making it more efficient and saving valuable time.
• Understands and processes the given prompts to generate relevant applications.
• Integrated with LangChain for generating application code through iterative parsing of LangChain's documentation with a "Tree of Transformations" (ToT) approach.
• The roadmap for DemoGPT includes constant updates and improvements based on user feedback and real-world application, working towards refining the technology and solving the hallucination problem.
• "We are planning to introduce features that will further enhance the application generation process, making it more user-friendly and efficient."

Links

• Github
• Website
• Twitter
• Streamlit App
• Hugging Face Space

DevGPT

Team of virtual developers

Category

Coding, Multi-agent

Description

• "Tell your AI team what microservice you want to build, and they will do it for you. Your imagination is the limit!!
• Welcome to Dev-GPT, where we bring your ideas to life with the power of advanced artificial intelligence! Our automated development team is designed to create microservices tailored to your specific needs, making your software development process seamless and efficient. Comprised of a virtual Product Manager, Developer, and DevOps, our AI team ensures that every aspect of your project is covered, from concept to deployment.

Links

• Discord

Devika

Agentic AI Software Engineer

Category

Coding, general purpose

Description

• Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective.
• Devika aims to be a competitive open-source alternative to Devin by Cognition AI.

Links

• GitHub

Devon

Open-source Devin alternative

Category

Coding, general purpose

Description

• Open-source alternative to Devin by Entropy research

Links

• GitHub

DevOpsGPT

AI-Driven SW Development Automation Solution

Category

Coding

Description

Welcome to the AI Driven Software Development Automation Solution, abbreviated as DevOpsGPT. We combine LLM (Large Language Model) with DevOps tools to convert natural language requirements into working software. This innovative feature greatly improves development efficiency, shortens development cycles, and reduces communication costs, resulting in higher-quality software delivery.

Features and Benefits

• Improved development efficiency: No need for tedious requirement document writing and explanations. Users can interact directly with DevOpsGPT to quickly convert requirements into functional software.
• Shortened development cycles: The automated software development process significantly reduces delivery time, accelerating software deployment and iterations.
• Reduced communication costs: By accurately understanding user requirements, DevOpsGPT minimizes the risk of communication errors and misunderstandings, enhancing collaboration efficiency between development and business teams.
• High-quality deliverables: DevOpsGPT generates code and performs validation, ensuring the quality and reliability of the delivered software.
• [Enterprise Edition] Existing project analysis: Through AI, automatic analysis of existing project information, accurate decomposition and development of required tasks on the basis of existing projects.
• [Enterprise Edition] Professional model selection: Support language model services stronger than GPT in the professional field to better complete requirements development tasks, and support private deployment.
• [Enterprise Edition] Support more DevOps platforms: can connect with more DevOps platforms to achieve the development and deployment of the whole process.

Links

• Creator Website
• Demo Video

dotagent

Deploy agents on cloud, PCs, or mobile devices

Category

Build-your-own

Description

• An agent management system that facilitates the creation of robust AI applications and experimental autonomous agents through a rich suite of developer tools.
• Enables the deployment of agents across multiple platforms including cloud, PCs, or mobile devices, and extends functionality through Python or plain English integrations.
• Advances prompt engineering with a powerful prompt compiler, offering a higher degree of control over Language Models, significantly optimizing the response generation process.
• Allows seamless export of agents into portable files for execution in any environment, along with an optional Agentbox feature for optimized computing resource management within a sandboxed environment.

Links

• YouTube video

Eidolon

Multi Agent SDK with pluggable, modular components

Category

Build-your-own (agent-builing frameworks and platforms), SDK for AI apps

Description

• Eidolon is an open source SDK for AI agents

Links

• Web
• GitHub
• LinkedIn
• Dave Brewster - LinkedIn
• Ravi Ramachandran - LinkedIn
• Luke Lalor - LinkedIn

English Compiler

Converting markdown specs into functional code

Category

Coding

Description

• OC AI based Compiler, for converting english based markdown specs, into functional code
• "We know that all great™ projects start with awesome™ detailed functional specifications. Which is typically written in English, or its many other spoken language alternatives.
• So what if, instead of writing code from functional specs, we simply compile it directly to code?
• Into a future, where we replace nearly everything, with just written text."

Links

• Creator's Twitter

evo.ninja

AI agent that adapts its persona to achive tasks

Category

General purpose, Research, Multi-agent

Description

• What makes evo.ninja special is that it adapts itself in real-time, based on the tasks at hand.
• Evo utilizes pre-defined agent personas that are tailored to specific domains of tasks.
• Each iteration of evo's execution loop it will select and adopt the persona that fits the task at hand best.

Links

• Web
• GitHub
• Discord

FastAgency

The fastest way to deploy multi-agent workflows

Category

Build-your-own (agent-builing frameworks and platforms), SDK for AI apps, Multi-agent, Supports open-source models

Description

• "FastAgency is an open-source framework designed to accelerate the transition from prototype to production for multi-agent AI workflows.
• For developers who use the AutoGen framework, FastAgency enables you to seamlessly scale Jupyter notebook prototypes into fully functional, production-ready applications.
• With multi-framework support, a unified programming interface, and powerful API integration capabilities, FastAgency streamlines the deployment process, saving time and effort while maintaining flexibility and performance.

Links

• Web
• GitHub

Flowise

Low code Agent builder

Category

Build-your-own (agent-builing frameworks and platforms)

Description

• Flowise is an open source low-code tool for developers to build customized LLM orchestration flow & AI agents

Links

• Web
• GitHub
• X (Twitter)
• LinkedIn

Friday

AI developer assistant for Node.js

Category

Coding

Description

• A developer assistant able to make whole nodejs project with unlimited prompts
• Provides a core prompt for building the foundation of your application
• Allows you to add unlimited sections, each of which is a prompt representing a specific part of your app
• Features
  • Friday utilizes GPT-4 for AI assistance, but it has been tested and optimized with GPT-4-32k for improved speed and better results.
  • It requires 2 small requests for your app's base and 1 request per section you provide.
  • Friday employs esbuild behind the scenes for every app created by it.

Links

• Author: Amirreza Salimi

GeniA

Engineering platform engineering AI team member

Category

Coding

Description

• GeniA is able to work along side you on your production enviroment, executing tasks on your behalf in your dev & cloud environments, AWS/k8s/Argo/GitHub etc.
• Allows you to enhance the platform by integrating your own tools and APIs.
• Slack App Bot integration.
• Supports GPT-3.5 & GPT-4.

Links

• Authors: Uri Shamay, Shlomi Shemesh

Godmode

Inspired by AutoGPT and BabyAGI, with nice UI

Category

General purpose

Description

• Godmode is a project inspired by Auto-GPT and BabyAGI, conducting various kinds of tasks via nice UI
• A web platform inspired by AutoGPT and BabyAGI
• What it can do:
  • Order your coffee at Starbucks
  • Perform market analysis
  • Find and negotiate a lease
• Supports GPT-3.5 & GPT-4

Links

• GitHub
• Authors: Emil Ahlbäck, Lonis
• Discord
• Tweet

GPT Discord

The ultimate AI agent integration for Discord

Category

Content creation, Productivity, General purpose, Discord

Description

• GPT Discord is a robust, all-in-one GPT interface for Discord.
• GPT Discord supports everything from multi-modality image understanding, code interpretation, advanced data analysis, Q&A on your own documents, internet-connected chat with Wolfram Alpha and Google access, AI-moderation, image generation with DALL-E, and much more!
• Featuring code execution and environment manipulation by E2B
• 
• LLMs/model providers supported:
  • OpenAI models

Links

• GitHub
• Kaveen Kumarasinghe - founder of GPT Discord - website
• [Kaveen Kumarasinghe - founder of GPT Discord - LinkedIn](https://www.linkedin.com/in/kave