https://github.com/e2b-dev/awesome-ai-agents
A list of AI autonomous agents
https://github.com/e2b-dev/awesome-ai-agents
List: awesome-ai-agents
agent ai artificial-intelligence autogpt autonomous-agents awesome babyagi copilot gpt gpt-4 gpt-engineer openai python
Last synced: 8 months ago
JSON representation
A list of AI autonomous agents
- Host: GitHub
- URL: https://github.com/e2b-dev/awesome-ai-agents
- Owner: e2b-dev
- License: other
- Created: 2023-06-19T00:20:06.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-23T08:31:05.000Z (almost 2 years ago)
- Last Synced: 2024-05-23T09:37:30.571Z (almost 2 years ago)
- Topics: agent, ai, artificial-intelligence, autogpt, autonomous-agents, awesome, babyagi, copilot, gpt, gpt-4, gpt-engineer, openai, python
- Homepage: https://e2b.dev/docs
- Size: 95.5 MB
- Stars: 7,211
- Watchers: 142
- Forks: 487
- Open Issues: 14
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
- awesome-openclaw-money-maker - **e2b-dev/awesome-ai-agents** - Comprehensive list of AI autonomous agents. Well-maintained with categories. (Resources & Directories / Awesome Lists)
- awesome-ai-sdks - AI agents
- awesome-artificial-intelligence-research - Awesome AI Agents - autonomous agent projects and resources. (Foundation Models, LLMs, and Agents / AI Agents)
- awesome-a2a-libraries - awesome-ai-agents - agent-papers](https://github.com/luo-junyu/Awesome-Agent-Papers) for new 📚 research on genAI & agents. (Scope / Official Resources)
- awesome-agi-agents - awesome-ai-agents - dev/awesome-ai-agents)|A list of AI autonomous agents. |基于 LLM 的 agents 精选资源.| (Curated List)
- StarryDivineSky - e2b-dev/awesome-ai-agents
- awesome-awesome-artificial-intelligence - Awesome AI Agent - dev/awesome-ai-agents?style=social) | (Agent)
- Awesome-AI-Agents - awesome-ai-agents - A list of AI autonomous agents (Reference Repo / Blog)
- awesome-awesome-llm - e2b-dev/awesome-ai-agents - dev/awesome-ai-agents.svg) | A curated list of AI agents and frameworks | | ★★★★★ | (Topics / LLM & Agents)
- awesome-list-for-developers - A list of AI autonomous agents
- awesome-ChatGPT-repositories - awesome-ai-agents - A list of AI autonomous agents (Awesome-lists)
- ultimate-awesome - awesome-ai-agents - A list of AI autonomous agents. (Other Lists / TeX Lists)
- awesome-ai-agents - e2b-dev/awesome-ai-agents
- awesome-ai-market-maps - E2B.dev - Awesome AI Agents - September 2024
- awesome-chatgpt-claude-agents - Awesome AI Agents - Comprehensive list of AI autonomous agents (📚 Educational Resources / Learning & Tutorials)
- awesome-generative-ai-data-scientist - Awesome AI Agents - dev/awesome-ai-agents) | (Curated Python AI, Data Science, and ML Compilations)
- awesome-ai-coding - awesome-ai-agents - Autonomous AI agents. (🔗 Similar Lists / By Deployment Model)
- awesome-continuous-ai - Awesome-Ai-Agents
- awesome-ai-tools - e2b-dev/awesome-ai-agents - Extensive collection of autonomous agents like AutoGPT and BabyAGI with metadata (AI Frameworks / 🔧 AI Agent Development Frameworks)
- awesome-voice-agents - awesome-ai-agents
- AiTreasureBox - e2b-dev/awesome-ai-agents - 11-03_23767_3](https://img.shields.io/github/stars/e2b-dev/awesome-ai-agents.svg)|A list of AI autonomous agents| (Repos)
- awesome-ai-agents - e2b-dev/awesome-ai-agents - A curated and comprehensive list of AI autonomous agents categorized into open-source and closed-source projects, serving as a valuable resource for exploring, building, and contributing to AI agent development. (Agent Integration & Deployment Tools / AI Application Development)
- awesome-agent-learning - e2b-dev/awesome-ai-agents
- awesome-cli-agents - e2b-dev/awesome-ai-agents - A list of AI autonomous agents [Copilot] (27k⭐) (🚀 AI Tools for Vim, Neovim, and Terminal)
- awesome-data-analysis - Awesome AI Agents - A curated list of AI autonomous agents, environments, and frameworks. (🧠 AI Applications & Platforms / Resources)
- awesome-rainmana - e2b-dev/awesome-ai-agents - A list of AI autonomous agents (Others)
- awesome-starz - e2b-dev/awesome-ai-agents - A list of AI autonomous agents (Others)
- awesome-claude-code-toolkit - awesome-ai-agents - source and closed-source AI agents | (Related Awesome Lists / Quick Setup with cc-safe-setup)
- awesome-agent-skills - e2b-dev/awesome-ai-agents - THE original awesome-ai-agents list.  (Multi-Platform Collections / Meta)
- llmops - Awesome AI Agents - AI agent resources (Resources & Learning / Awesome Lists)
- awesome-harness-engineering - e2b-dev/awesome-ai-agents
- awesome-vibe-coding - awesome-ai-agents
- awesome-agent-failures - Awesome AI Agents - AI agent frameworks and tools. (📚 Resources / Related Awesome Lists)
- awesome-open-source-ai-tools - e2b-dev/awesome-ai-agents - A list of AI autonomous agents (Chatbots & Virtual Companions)
- awesome-github-projects - awesome-ai-agents - A list of AI autonomous agents ⭐27,842 (📦 Legacy & Inactive Projects)
README
🔮 Awesome AI Agents
Add Code Interpreter to your AI App
🌟 See this list in web UI
👉 Submit new product here
Welcome to our list of AI agents.
We structured the list into two parts:
- [Open source projects](#open-source-projects)
- [Closed-source projects and companies](#closed-source-projects-and-companies)
To filter the products by categories and use-cases, see the 🌟 [web version of this list](https://e2b.dev/ai-agents). 🌟
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](https://forms.gle/UXQFCogLYrPFvfoUA). 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](https://github.com/e2b-dev/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](https://e2b.dev/docs?ref=awesome-sdk)
- Explore examples in [E2B Cookbook](https://github.com/e2b-dev/e2b-cookbook)
- Read our [docs](https://e2b.dev/docs?ref=awesome-sdks)
- Contact us at [hello@e2b.dev](mailto:hello@e2b.dev) or [on Discord](https://discord.gg/35NF4Y8WSE). Follow us on [X (Twitter)](https://twitter.com/e2b)
# Open-source projects
## [Adala](https://github.com/HumanSignal/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](https://humansignal.github.io/Adala/)
- [Discord](https://discord.gg/QBtgTbXTgU)
- [GitHub](https://github.com/HumanSignal/Adala)
## [Agent4Rec](https://github.com/LehengTHU/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](https://grouplens.org/datasets/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](https://arxiv.org/abs/2310.10108)
## [AgentForge](https://github.com/DataBassGit/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](https://github.com/DataBassGit/AgentForge)
- [Web](https://www.agentforge.net/)
- [Discord](https://discord.com/invite/ttpXHUtCW6)
- [X](https://twitter.com/AgentForge)
## [AgentGPT](https://agentgpt.reworkd.ai/)
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](https://docs.reworkd.ai/)
- [Website](https://agentgpt.reworkd.ai/)
- [GitHub](https://github.com/reworkd/AgentGPT)
## [AgentPilot](https://github.com/jbexta/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](https://github.com/jbexta/AgentPilot)
- [X ](https://twitter.com/AgentPilotAI)
-
## [Agents](https://github.com/aiwaves-cn/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](https://platform.openai.com/docs/guides/gpt/function-calling) and developers can add customized tools/APIs [here](https://github.com/aiwaves-cn/agents/blob/master/src/agents/Component/ToolComponent.py).
- **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.](https:github.com/aiwaves-cn)
- [Paper](https://arxiv.org/pdf/2309.07870.pdf)
- [GitHub Repository](https://github.com/aiwaves-cn/agents)
- [Documentation](https://agents-readthedocsio.readthedocs.io/en/latest/index.html)
- [Tweet](https://twitter.com/wangchunshu/status/1702512370785100133)
## [AgentVerse](https://github.com/OpenBMB/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](https://arxiv.org/abs/2308.10848)
- [Twitter](https://twitter.com/Agentverse71134)
- [Discord](https://discord.gg/gDAXfjMw)
- [Hugging Face](https://huggingface.co/spaces/AgentVerse/agentVerse)
## [AI Legion](https://github.com/eumemic/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](https://github.com/eumemic)
- [Website](https://gpt3demo.com/apps/ai-legion)
- [GitHub](https://github.com/eumemic/ai-legion)
- [Twitter](https://twitter.com/dysmemic)
## [Aider](https://github.com/paul-gauthier/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](https://aider.chat/)
- Author: [Paul Gauthier](https://github.com/paul-gauthier) (Github)
- [Discord Invite](https://discord.com/invite/Tv2uQnR88V)
## [AIlice](https://github.com/myshell-ai/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](https://github.com/myshell-ai/AIlice)
## [AutoGen](https://github.com/microsoft/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](https://arxiv.org/pdf/2308.08155.pdf)
- [Discord](https://discord.gg/pAbnFJrkgZ)
- [Twitter thread describing the system](https://twitter.com/pyautogen)
## [AutoGPT](https://agpt.co/?utm_source=awesome-ai-agents)
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](https://twitter.com/Auto_GPT/?utm_source=awesome-ai-agents)
- [GitHub](https://github.com/Significant-Gravitas/Auto-GPT/?utm_source=awesome-ai-agents)
- [Facebook](https://www.facebook.com/groups/1330282574368178/?utm_source=awesome-ai-agents)
- [Linkedin](https://www.linkedin.com/company/autogpt/?utm_source=awesome-ai-agents)
- [Discord](https://discord.gg/autogpt/?utm_source=awesome-ai-agents)
- Author: [Significant Gravitas](https://twitter.com/SigGravitas/?utm_source=awesome-ai-agents)
## [Automata](https://github.com/emrgnt-cmplxty/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](https://github.com/emrgnt-cmplxty/automata)
- [Docs](https://automata.readthedocs.io/en/latest/)
- Author: [Owen Colegrove](https://twitter.com/ocolegro)
## [AutoPR](https://github.com/irgolic/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](https://discord.com/invite/ykk7Znt3K6)
## [Autonomous HR Chatbot](https://github.com/stepanogil/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](https://pub.towardsai.net/creating-a-mostly-autonomous-hr-assistant-with-chatgpt-and-langchains-agents-and-tools-1cdda0aa70ef)
- [GitHub](https://github.com/stepanogil/autonomous-hr-chatbot)
- Author: [Stephen Bonifacio](https://twitter.com/Stepanogil)
- [YouTube demo](https://www.youtube.com/watch?v=id7XRcEIBvg&ab_channel=StephenBonifacio)
- [Blog post](https://pub.towardsai.net/creating-a-mostly-autonomous-hr-assistant-with-chatgpt-and-langchains-agents-and-tools-1cdda0aa70ef)
## [BabyAGI](https://github.com/yoheinakajima/babyagi)
A simple framework for managing tasks using AI
### Category
General purpose
### Description
- A pared-down version of the original [Task-Driven Autonomous Agent](https://twitter.com/yoheinakajima/status/1640934493489070080?s=20)
- 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](https://yoheinakajima.com/task-driven-autonomous-agent-utilizing-gpt-4-pinecone-and-langchain-for-diverse-applications/)
- [Discord](https://discord.com/invite/TMUw26XUcg)
- [Founder's Twitter](https://twitter.com/yoheinakajima)
- [Twitter thread describing the system](https://twitter.com/yoheinakajima/status/1640934493489070080)
## [BabyBeeAGI](https://yoheinakajima.com/babybeeagi-task-management-and-functionality-expansion-on-top-of-babyagi/)
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](https://twitter.com/yoheinakajima/status/1652732735344246784)
- [GitHub](https://github.com/yoheinakajima/babyagi/blob/main/classic/BabyBeeAGI.py)
- [Replit](https://replit.com/@YoheiNakajima/BabyBeeAGI?v=1)
- Author: [@yoheinakajima](https://twitter.com/yoheinakajima) (Twitter)
## [BabyCatAGI](https://replit.com/@YoheiNakajima/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](https://twitter.com/yoheinakajima/status/1657448504112091136)
- [GitHub](https://github.com/yoheinakajima/babyagi/blob/main/classic/BabyCatAGI.py)
- [Replit](https://replit.com/@YoheiNakajima/BabyCatAGI)
- Author: [@yoheinakajima](https://twitter.com/yoheinakajima) (Twitter)
## [BabyDeerAGI](https://twitter.com/yoheinakajima/status/1666313838868992001)
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](https://twitter.com/yoheinakajima/status/1666313838868992001)
- [GitHub](https://github.com/yoheinakajima/babyagi/blob/main/classic/BabyDeerAGI.py)
- [Replit](https://replit.com/@YoheiNakajima/BabyDeerAGI)
- Author: [@yoheinakajima](https://twitter.com/yoheinakajima) (Twitter)
## [BabyElfAGI](https://twitter.com/yoheinakajima/status/1678443482866933760)
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](https://twitter.com/yoheinakajima/status/1678443482866933760)
- [GitHub](https://github.com/yoheinakajima/babyagi/blob/main/classic/BabyElfAGI/main.py)
- [Replit](https://replit.com/@YoheiNakajima/BabyElfAGI)
- Author: [@yoheinakajima](https://twitter.com/yoheinakajima) (Twitter)
## [BabyCommandAGI](https://github.com/saten-private/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](https://github.com/yoheinakajima/babyagi) which executes shell commands
- Automatic Programming, Successfully created an app automatically just by providing feedback. The procedure can be found [here](https://twitter.com/saten_work/status/1674855573412810753).
- 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](https://twitter.com/saten_work/status/1667126272072491009).
- 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](https://anyaitools.com/babycommandagi/?utm_source=SocialAutoPoster&utm_medium=Social&utm_campaign=Twitter)
- 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](https://twitter.com/saten_work)
- [Twitter thread describing the system](https://twitter.com/saten_work/status/1654571194111393793)
## [BabyFoxAGI](https://github.com/yoheinakajima/babyagi/tree/main/classic/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](https://twitter.com/yoheinakajima)
- [Twitter thread describing the system](https://twitter.com/yoheinakajima/status/1697539193768116449)
- [Replit](https://replit.com/@YoheiNakajima)
## [BambooAI](https://github.com/pgalko/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](https://github.com/pgalko/BambooAI)
- [Creators's Twitter](https://twitter.com/pgalko)
## [BeeBot](https://github.com/AutoPackAI/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](https://github.com/AutoPackAI/beebot)
- [Tweet](https://twitter.com/Douglas_Schon/status/1681094815021187072?s=20)
## [Blinky](https://github.com/seahyinghang8/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](https://marketplace.visualstudio.com/items?itemName=blinky.blinky)
- [Discord](https://discord.gg/d3AUNHDb)
- [GitHub](https://github.com/seahyinghang8/blinky)
## [Bloop](https://bloop.ai/)
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](https://github.com/BloopAI/bloop)
- ["Getting started" guide](https://bloop.ai/docs/getting-started)
- [Bloop apps](https://github.com/BloopAI/bloop/releases)
## [BondAI](https://bondai.dev/)
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](https://bondai.dev)
- [Github Repository](https://github.com/krohling/bondai)
- [Docker Image](https://hub.docker.com/r/krohling/bondai)
## [bumpgen](https://github.com/xeol-io/bumpgen)
AI agent that keeps npm dependencies up-to-date
![demo]()
### 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](https://github.com/xeol-io/bumpgen)
- [Docs](https://docs.xeol.io/bumpgen/home)
## [Cal.ai](https://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](https://github.com/calcom/cal.com/tree/main/apps/ai)
### Links
- Authors: [Cal.com core team](https://github.com/calcom/cal.com/graphs/contributors), [Dexter Storey](https://github.com/dexterstorey), [Ted Spare](https://github.com/tedspare)
## [CAMEL](https://github.com/camel-ai/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](https://www.camel-ai.org/)
- [Paper - CAMEL: Communicative Agents for “Mind”
Exploration of Large Scale Language Model Society](https://ghli.org/camel.pdf)
- [Colab demo](https://colab.research.google.com/drive/1AzP33O8rnMW__7ocWJhVBXjKziJXPtim?usp=sharing)
- [GitHub](https://github.com/camel-ai/camel)
- [Hugging face datasets](https://huggingface.co/camel-ai)
- [Slack](https://camel-kwr1314.slack.com/join/shared_invite/zt-1vy8u9lbo-ZQmhIAyWSEfSwLCl2r2eKA#/shared-invite/email)
- [Twitter](https://twitter.com/intent/follow?original_referer=https%3A%2F%2F1508613885-atari-embeds.googleusercontent.com%2F&ref_src=twsrc%5Etfw%7Ctwcamp%5Ebuttonembed%7Ctwterm%5Efollow%7Ctwgr%5ECamelAIOrg&screen_name=CamelAIOrg)
- Authors: Guohao Li∗ Hasan Abed Al Kader Hammoud* Hani Itani* Dmitrii Khizbullin, Bernard Ghanem
## [ChatArena](https://www.chatarena.org/)
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](https://www.chatarena.org/)
- [GitHub](https://github.com/Farama-Foundation/chatarena)
- [X](https://twitter.com/_chatarena)
- [Slack channel](https://chatarena.slack.com/join/shared_invite/zt-1t5fpbiep-CbKucEHdJ5YeDLEpKWxDOg#/shared-invite/email)
## [ChatDev](https://github.com/OpenBMB/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](https://arxiv.org/abs/2307.07924)
- [Local demo](https://github.com/OpenBMB/ChatDev/blob/main/wiki.md#local-demo)
- [GitHub](https://github.com/OpenBMB/ChatDev)
## [ChemCrow](https://github.com/ur-whitelab/chemcrow-public)
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/.](https://lilianweng.github.io/posts/2023-06-23-agent/))
### Links
- [Paper](https://arxiv.org/abs/2304.05376)
- [GitHub](https://github.com/ur-whitelab/chemcrow-public)
- [HackerNews Discussion](https://news.ycombinator.com/item?id=35607616)
## [Clippy](https://github.com/ennucore/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](https://github.com/ennucore/clippy/)
- Author: [Lev Chizhov](http://lev.la/)
## [CodeFuse-ChatBot](https://github.com/codefuse-ai/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](https://github.com/codefuse-ai/codefuse-chatbot)
## [Cody by ajhous44](https://github.com/ajhous44/cody)
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](https://github.com/ajhous44/cody)
- Author: [@ajhous44](https://github.com/ajhous44/) (Github)
## [Cody by Sourcegraph](https://docs.sourcegraph.com/cody)
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](https://github.com/sourcegraph/sourcegraph/tree/main/client/cody)
- Author: [@sourcegraph](https://twitter.com/sourcegraph) (Twitter)
## [Continue](https://continue.dev/)
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](https://continue.dev/)
- [GitHub](https://github.com/continuedev/continue)
- [Documentation](https://continue.dev/docs/intro)
- [Twitter](https://twitter.com/continuedev)
## [CrewAI](https://github.com/joaomdmoura/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](https://github.com/joaomdmoura/crewai)
- [Founder's X](https://twitter.com/joaomdmoura)
- [Blog post: How to use Crew AI](https://crewai.net/posts/how-to-use-crew-ai)
- [Crew AI Wiki with examples and guides](https://github.com/joaomdmoura/CrewAI/wiki)
- [Docs](https://github.com/joaomdmoura/CrewAI/wiki)
- [Discord](https://discord.com/invite/X4JWnZnxPb)
## [data-to-paper](https://github.com/Technion-Kishony-lab/data-to-paper)
AI-driven research from data to human-verifiable research papers
### Category
Science, Research, Multi-agent
### Description
[*data-to-paper*](https://arxiv.org/abs/2404.17605) 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](https://www.nature.com/articles/d41586-023-03266-1)].
### Links
- [GitHub](https://github.com/Technion-Kishony-lab/data-to-paper)
- [arXiv preprint](https://arxiv.org/abs/2404.17605)
- [Demo video](https://www.youtube.com/watch?v=Nt_460MmM8k)
## [Databerry](https://www.databerry.ai/)
(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](https://docs.chaindesk.ai/introduction)
- [Discord](https://discord.com/invite/FSWKj49ckX)
- [GitHub](https://github.com/gmpetrov/databerry)
## [DemoGPT](https://github.com/melih-unsal/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](https://github.com/melih-unsal/DemoGPT)
- [Website](https://www.demogpt.io/)
- [Twitter](https://twitter.com/demo_gpt)
- [Streamlit App](https://demogpt.streamlit.app/)
- [Hugging Face Space](https://huggingface.co/spaces/melihunsal/demogpt)
## [DevGPT](https://github.com/jina-ai/dev-gpt)
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](https://discord.com/invite/AWXCCC6G2P)
## [Devika](https://github.com/stitionai/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](https://github.com/stitionai/devika)
## [Devon](https://github.com/entropy-research/Devon)
Open-source Devin alternative
![Image]()
### Category
Coding, general purpose
### Description
- Open-source alternative to Devin by Entropy research
### Links
- [GitHub](https://github.com/entropy-research/Devon)
## [DevOpsGPT](https://github.com/kuafuai/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](https://www.kuafuai.net/)
- [Demo Video](https://youtu.be/IWUPbGrJQOU)
## [dotagent](https://github.com/dot-agent/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](https://www.youtube.com/watch?v=uE_fykl8AVI&ab_channel=FahdMirza)
## [Eidolon](https://eidolonai.com/)
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](https://eidolonai.com/)
- [GitHub](https://github.com/eidolon-ai/eidolon)
- [LinkedIn](https://www.linkedin.com/company/august-data/)
- [Dave Brewster - LinkedIn](https://www.linkedin.com/in/dave-brewster-first/)
- [Ravi Ramachandran - LinkedIn](https://www.linkedin.com/in/ravi-nextlevelgtm/)
- [Luke Lalor - LinkedIn](https://www.linkedin.com/in/lukehlalor/)
## [English Compiler](https://github.com/uilicious/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](https://twitter.com/picocreator)
## [evo.ninja](https://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](https://evo.ninja/)
- [GitHub](https://github.com/polywrap/evo.ninja/)
- [Discord](https://discord.com/invite/r3rwh69cCa)
## [FastAgency](https://fastagency.ai/latest/)
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](https://fastagency.ai/latest/)
- [GitHub](https://github.com/airtai/fastagency)
## [Flowise](https://flowiseai.com/)
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](https://flowiseai.com/)
- [GitHub](https://github.com/FlowiseAI/Flowise)
- [X (Twitter)](https://x.com/FlowiseAI)
- [LinkedIn](https://www.linkedin.com/company/flowiseai/)
## [Friday](https://github.com/amirrezasalimi/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](https://twitter.com/amirsalimiiii)
## [GeniA](https://github.com/genia-dev/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](https://github.com/cmpxchg16), [Shlomi Shemesh](https://github.com/shlomsh)
## [Godmode](https://godmode.space/)
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](https://github.com/FOLLGAD/Godmode-GPT)
- Authors: [Emil Ahlbäck](https://twitter.com/emilahlback), [Lonis](https://twitter.com/_Lonis_)
- [Discord](https://discord.com/invite/vSzCcDDwz3)
- [Tweet](https://twitter.com/_Lonis_/status/1646641412182536196)
## [GPT Discord](https://github.com/Kav-K/GPTDiscord)
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](https://github.com/Kav-K/GPTDiscord)
- [Kaveen Kumarasinghe - founder of GPT Discord - website](https://kaveenk.com/)
- [Kaveen Kumarasinghe - founder of GPT Discord - LinkedIn](https://www.linkedin.com/in/kaveenk/)
## [GPT Engineer](https://gptengineer.app/)
Generates entire codebase based on a prompt
### Category
Coding
### Description
GPT Engineer is an AI agent that generates an entire codebase based on a prompt.
- Model: GPT 4
- Specify your project, and the AI agent asks for clarification, and then constructs the entire code base
- Features
- Made to be easy to adapt, extend, and make your agent learn how you want your code to look. It generates an entire codebase based on a prompt
- You can specify the "identity" of the AI agent by editing the files in the identity folder
- Editing the identity and evolving the main prompt is currently how you make the agent remember things between projects
- Each step in steps.py will have its communication history with GPT4 stored in the logs folder, and can be rerun with scripts/rerun_edited_message_logs.py
### Links
- [Web](https://gptengineer.app)
- [GitHub](https://github.com/AntonOsika/gpt-engineer)
- [Discord](https://discord.com/invite/8tcDQ89Ej2)
- Author: [Anton Osika](https://twitter.com/antonosika)
- [Twitter review by @Attack](https://twitter.com/Attack/status/1671165869064609792)
## [GPT Migrate](https://github.com/0xpayne/gpt-migrate)
Migrate codebase between frameworks/languages
### Category
Coding
### Description
GOT Migrate easily migrates your codebase from one framework or language to another.
- Pick from different LLMs
- Ability to allow GPT Migration to generate and run unit tests for the new codebase
- Ability to select source and target language of the migration
- Ability to customize the agent's workflow (setup -> migrate -> test)
- GPT Migrate team is working on adding [benchmarks](https://github.com/0xpayne/gpt-migrate#-benchmarks) for the agent
### Links
- [Website](https://gpt-migrate.com/)
- Author: [Josh Payne](https://twitter.com/joshpxyne)
- [Announcement](https://twitter.com/joshpxyne/status/1675254164165910528)
## [GPT Pilot](https://github.com/Pythagora-io/gpt-pilot)
Code the entire scalable app from scratch
### Category
Coding
### Description
GPT Pilot is an AI agent that codes the entire app as you oversee the code being written
- Dev tool that writes scalable apps from scratch while the developer oversees the implementation
- A research project to see how can GPT-4 be utilized to generate fully working, production-ready, apps
- The main idea is that AI can write most of the code for an app (maybe 95%) but for the rest 5%, a developer is and will be needed until we get full AGI
### Links
- [GitHub](https://github.com/Pythagora-io/gpt-pilot)
- [Discord](https://discord.com/invite/HaqXugmxr9)
## [GPT Researcher](https://github.com/assafelovic/gpt-researcher)
Agent that researches entire internet on any topic
### Category
Research, Science
### Description
GPT Researcher is a GPT-based autonomous agent that does online comprehensive research on any given topic
- Can produce detailed, factual and unbiased research reports
- Offers customization options for focusing on relevant resources, outlines, and lessons
- Addresses issues of speed and determinism, offering a more stable performance and increased speed through parallelized agent work, as opposed to synchronous operation
- Inspired by AutoGPT and the Plan-and-Solve paper
- The main idea is to run "planner" and "execution" agents, whereas the planner generates questions to research, and the execution agents seek the most related information based on each generated research question
### Links
- [Website](https://tavily.com/)
- [Discord](https://discord.com/invite/2pFkc83fRq)
- Author: [Assaf Elovic](https://twitter.com/assaf_elovic)
## [GPT Runner](https://github.com/nicepkg/gpt-runner)
Agent that converses with your files
### Category
Research, Science
### Description
- Conversation with your files which selected by you, no embedding, no vector database!
- It's also a AI Prompt Storybook. You can use it to manage some AI preset with your team. It support any IDE and language developer. We provide cli to run web and VSCode extension, Jetbrains plugin is coming soon.
- Private first, all data is local.
- We support both OpenAI and Anthropic (Claude-2)
- It support support for multiple languages.
### Links
- [Website](https://github.com/nicepkg/gpt-runner)
- Author: [Jinming Yang](https://github.com/2214962083)
## [GPTSwarm](https://gptswarm.org/)
Language Agents as Optimizable Graphs
### Category
Build-your-own (agent-builing frameworks and platforms), General purpose, Multi-agent
### Description
- 🐝 GPTSwarm is a graph-based framework for LLM-based agents, providing two high-level features:
- It lets you build LLM-based agents from graphs.
- It enables the customized and automatic self-organization of agent swarms with self-improvement capabilities.
- Various human-designed prompt engineering techniques have been proposed to improve problem solvers based on Large Language Models (LLMs), yielding many disparate code bases. We unify these approaches by describing LLM-based agents as computational graphs. Each node implements a function to process multimodal data or query other LLMs. Each edge describes the information flow between operations and agents. Graphs can be recursively combined into larger composite graphs representing hierarchies of inter-agent collaboration. Our novel automatic graph optimizers (1) refine node-level LLM prompts (node optimization) and (2) improve agent orchestration by changing graph connectivity (edge optimization). Experiments demonstrate that our framework can be used to efficiently develop, integrate, and automatically improve diverse LLM agents.
### Links
- [Web](https://gptswarm.org/)
- [GitHub](https://github.com/metauto-ai/GPTSwarm)
- [Founder's X (Twitter)](https://twitter.com/MingchenZhuge)
## [IX](https://github.com/kreneskyp/ix)
Agents building, debugging, and deploying platform
### Category
Build your own, Multi-agent
### Description
IX is a platform for building, debugging, and deploying collaborative Agents and cognitive workflows.
-IX is a LangChain-based agent platform that includes all the tools to build and deploy fleets of agents that
collaborate to complete tasks. IX is both an editor and a runtime. The editor is a no-code graph style editor for
the design of agents, chains, tools, retrieval functions, and collaborative workflows.
- Intuitive graph style no-code editor.
- Horizontally scaling agent worker fleet.
- Multi-user, multi-agent chat interface.
- Smart input auto-completes `@mentions` and `{file}` references.
- Supports Chroma and other vector databases for document search.
- Supports OpenAI API, Anthropic, PaLM, and LLama based models.
- Component library is easily extended.
- Powered by LangChain
### Links
- [Youtube](https://www.youtube.com/watch?v=hAJ8ectypas&list=PLR8AMvFecu1hyMHFzaehbfFcMcECMafVs)
- [Discord](https://discord.gg/jtrMKxzZZQ)
- [Author's Twitter](https://twitter.com/kreneskyp)
## [JARVIS](https://github.com/microsoft/JARVIS)
System that connects LLMs with the ML community
### Category
General purpose
### Description
JARVIS is a system to connect LLMs with the ML community.
- Task Planning: Using ChatGPT to analyze the requests of users to understand their intention, and disassemble them into possible solvable tasks.
- Model Selection: To solve the planned tasks, ChatGPT selects expert models hosted on Hugging Face based on their descriptions.
- Task Execution: Invokes and executes each selected model, and returns the results to ChatGPT.
- Response Generation: Use ChatGPT to integrate the prediction of all models, and generate responses.
### Links
- [Paper](https://arxiv.org/abs/2303.17580)
## [Langroid](https://github.com/langroid/langroid)
Multi-agent framework for building LLM apps
### Category
General purpose, Build your own
### Description
`Langroid` is an intuitive, lightweight, extensible and principled
Python framework to easily build LLM-powered applications.
You set up Agents, equip them with optional components (LLM,
vector-store and methods), assign them tasks, and have them
collaboratively solve a problem by exchanging messages.
This Multi-Agent paradigm is inspired by the
[Actor Framework](https://en.wikipedia.org/wiki/Actor_model)
(but you do not need to know anything about this!).
`Langroid` is a fresh take on LLM app-development, where considerable thought has gone
into simplifying the developer experience; it does not use `Langchain`.
- Works with most commercial/remote and open/local LLMs.
- Set up Multi-agent, multi-LLM system: use stronger LLMs for agents requiring strong reasoning and instruction-following, and delegate simpler tasks to weaker/local LLMs.
- Supports OpenAI function-calling as well as native equivalent called `ToolMessage`, which works with LLMs that
do not have built-in function-calling. Simply specify structure as a (nested) Pydantic object.
- Batteries-included: vector-databases for RAG (Retrieval-Augmented Generation), caching, logging/observability.
- Specialized agents available: `DocChatAgent`, `SQLChatAgent`, `TableChatAgent` (for tabular data, e.g. csv/dataframes).
- `DocChatAgent` handles text, PDF, Docx files/URLS, and has state-of-the art techniques
for retrieval combining lexical and semantic search.
- Documentation: https://langroid.github.io/langroid/
## [Lemon Agent](https://github.com/felixbrock/lemon-agent)
Plan-Validate-Solve agent for workflow automation
### Category
Productivity, Coding
### Description
Lemon agent is a Plan-Validate-Solve (PVS) Agent for accurate, reliable and reproducable workflow automation
- A standalone supervised Plan and Solve Agent specialized on performing read and write operations on various tools like GitHub, HubSpot or Airtable _(ACL 2023 Paper "[Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models](https://arxiv.org/abs/2305.04091)")_
- **Separation of tasks and human-in-the-loop interactions**: Lemon Agent is currently holding a Planner Agent and a Solver Agent to keep the agents focussed and increase accuracy. We are planning on adding additional agents real soon. In addition, Lemon Agent will ask for approval at relevant workflow steps to make sure the intended actions are executed.
- **Unlimited configuration options**: Lemon Agent gives you unlimited configuration options (see example here) when defining your workflow. For instance, you can tell Lemon Agent to ask for permission before executing a workflow step or to drop a 🧔♀️ dad joke every time the model executes a workflow step.
- **UI flexibility**: Build any UI on top or engage with Lemon Agent via the built-in CLI.
- **[Soon] Model & framework agnostic operations**: Lemon Agent is a standalone agent, but can easily be integrated into frameworks like LangChain and be used with any model.
- **Bonus**: Identify weak spots in your agent’s decision-making capabilities and move to a more deterministic behavior by further configuring your Lemon Agent workflows. **(.html file that can be run without any additional installation)**
### Links
- [Discord](https://discord.gg/fWU4rDYSxw)
- [Author's Twitter](https://twitter.com/felixbrockm)
## [LLM Agents](https://github.com/mpaepper/llm_agents)
Library for building agents, using tools, planning
### Category
Coding
### Description
A minimalistic library for building agents that leverage large language models to automate tasks through a loop of commands and tool integrations.
- Executing Python code in a REPL environment.
- Conducting searches on Google and Hacker News.
- Iterating through a cycle of Thought, Action, Observation, and New Thought based on the output of integrated tools.
- Dynamically appending new information to the prompt for informed decision-making by the agent.
### Links
- [GitHub](https://github.com/mpaepper/llm_agents)
- [Blog](https://www.paepper.com/blog/posts/intelligent-agents-guided-by-llms/)
## [LLM Stack](https://llmstack.ai/)
No-code platform to build LLM Agents
### Category
Build-your-own, no-code, web UI
### Description
- LLM Stack is a no-code platform to build LLM Agents, workflows and applications with your data
- LLMStack supports all major model providers, like OpenAI, Cohere, Stability AI, Hugging Face, and more. Easily use these models to build powerful apps.
- With LLM Stack, you can build generative AI agents like AI SDRs, Research Analysts, RPA Automations etc., without writing any code. Connect agents to your internal or external tools, search the web or browse the internet with agents.
- LLMs/model providers supported
- OpenAI
- Cohere
- Stability AI
- Hugging Face
### Links
- [Web](https://llmstack.ai/)
- [GitHub](https://github.com/trypromptly/LLMStack)
- [Blog](https://llmstack.ai/blog)
## [Local GPT](https://github.com/PromtEngineer/localGPT)
Chat with documents without compromising privacy
### Category
Research, Data analysis, General purpose
### Description
LocalGPT is an open-source initiative that allows you to converse with your documents without compromising your privacy. Inspired by privateGPT, allows using your own documents as an information source
- Chat with your documents on your local device using GPT models. No data leaves your device and 100% private
- With everything running locally, you can be assured that no data ever leaves your computer
- Dive into the world of secure, local document interactions with LocalGPT
- Most of the description on readme is inspired by the original privateGPT
- Model: Vicuna-7B
- Using InstructorEmbeddings
- Both Embeddings as well as LLM will run on GPU. It also has CPU support if you do not have a GPU
- Built with Langchain
### Links
- [GitHub](https://github.com/PromtEngineer/localGPT)
- [Subreddit](https://www.reddit.com/r/LocalGPT/)
- [YouTube - LocalGPT: OFFLINE CHAT FOR YOUR FILES [Installation & Code Walkthrough]](https://www.youtube.com/watch?v=MlyoObdIHyo&ab_channel=PromptEngineering)
## [Loop GPT](https://github.com/farizrahman4u/loopgpt/tree/main)
Re-implementation of AutoGPT as a Python package
### Category
General purpose
### Description
Loop GPT is a re-implementation of the popular Auto-GPT project as a proper python package, written with modularity and extensibility in mind
- Languages: Python
- Default model: GPT-3.5-turbo (also possible with GPT-4)
- Modular Auto-GPT Framework
- Plug N Play" API - Extensible and modular "Pythonic" framework, not just a command line tool
- Features
- "Easy to add new features, integrations and custom agent capabilities, all from python code, no nasty config files!"
- "Minimal prompt overhead - Every token counts. We are continuously working on getting the best results with the least possible number of tokens."
- "Human in the Loop - Ability to "course correct" agents who go astray via human feedback."
- "Full state serialization - can save the complete state of an agent, including memory and the states of its tools to a file or python object. No external databases or vector stores required (but they are still supported)!"
## [L2MAC](https://github.com/samholt/l2mac)
Agent framework able to produce large complex codebases and entire books
### Category
Multi-agent, Coding, Build your own
### Description
L2MAC is a multi-agent generation framework that, a single input prompt can generate an extensive unbounded output, such as an entire codebase or an entire book.
- L2MAC can create near unbounded outputs that align exactly with the user input prompt over very long generation tasks
- It achieves strong empirical performance of state-of-the-art generation for large codebase tasks and is in the top 3 for the HumanEval coding global benchmark. As L2MAC can detect invalid code and failing unit tests when generating code and automatically error corrects them.
- Internally persists a complete file-store memory that enables LLM agents to read files and write to files, creating a large output over many iterations
- It can be instructed to follow an exact prompt program
- As it generates the output one part at a time, it enables an LLM with a fixed context token limit to be bypassed
- The paper, peer-reviewed and recently accepted and published at ICLR 2024, introduces L2MAC.
### Links
- [GitHub](https://github.com/samholt/l2mac)
- [Discord](https://discord.gg/z27CxnwdhY)
- [Twitter](https://twitter.com/samianholt)
- [Paper - L2MAC: Large Language Model Automatic Computer for Extensive Code Generation](https://arxiv.org/abs/2310.02003)
## [Maige](https://maige.app)
Natural-language workflows for your GitHub repo.
### Category
Coding, Productivity, Debugging, Multi-agent
### Description
- Maige is a codebase agent that runs when new issues and pull requests come up. Its core features are labelling, assigning, and answering questions.
- Maige can search the entire codebase, spin up a sandbox to run scripts, and even write basic code.
### Links
- [Web](https://maige.app)
- [GitHub](https://github.com/RubricLab/maige)
- [Video - testing Maige](https://www.youtube.com/watch?v=YN-y-iweZTc&ab_channel=TerezaTizkova)
- [Interview - founder about building Maige](https://e2b.dev/blog/building-open-source-codebase-copilot-with-code-execution-layer)
- [X (Twitter)](https://twitter.com/rubriclabs)
- [Founder's X - Ted Spare](https://twitter.com/tedspare)
## [Magick](https://www.magickml.com/)
AIDE for creating, deploying, monetizing agents
### Category
Coding, SDK for agents, Build-your-own
### Description
Magick is an AIDE for creating, deploying, scaling, and monetizing useful AI agents, and prompt chaining.
- A full suite, model agnostic AIDE for creating, deploying, scaling, and monetizing useful AI agents, and prompt chaining.
- Magick allows to build things like BabyAGI within an hour. You can watch the graph executing in real time, watch the thought process as it executes, and understand the flow.
- "Visual development of autonomous agents is incoming. We have built Magick specifically for the rapid development of cognitive architecture and scalable event-driven autonomous agents."
### Links
- [Web](https://www.magickml.com/)
- [GitHub](https://github.com/Oneirocom/Magick)
- [X](https://twitter.com/magickml)
- [Discord](https://discord.com/invite/7Xx5DmbJCe)
- [LinkedIn](https://www.linkedin.com/company/magickml/)
- [Founder's LinkedIn - Jesse Alton](https://www.linkedin.com/in/mrmetaverse/)
- [Founder's LinkedIn - Michael Sharpe](https://www.linkedin.com/in/michaelpsharpe/)
## [MemFree](https://github.com/memfreeme/memfree)
Open Source Hybrid AI Search Engine
### Category
Open Source, AI Search, Build your own
### Description
Open Source Hybrid AI Search Engine, Instantly Get Accurate Answers from the Internet, Bookmarks, Notes, and Docs.
- One-Click Chrome Bookmarks Sync and Index
- Support multiple traditional search engines as source
- Self-hosted Super Fast Serverless Vector Database
- Self-hosted Super Fast Local Embedding and Rerank Service
- Full Code Open Source
- One-Click Deployment On Production
### Links
- [Documentation](https://www.memfree.me/docs)
- [Discord](https://discord.com/invite/7QqyMSTaRq)
- [Twitter](https://twitter.com/ahaapple2023)
- [Website](https://www.memfree.me)
## [MemGPT](https://github.com/cpacker/MemGPT)
Memory management system, providing context to LLM
### Category
Memory management, Data analysis
### Description
- A system that intelligently manages different memory tiers in LLMs to effectively provide the extended context within the LLM's limited context window.
- Chat with your data - talk to your local files or SQL database
- Create perpetual chatbots with self-editing memory
### Links
- [Paper](https://arxiv.org/abs/2310.08560)
- [Documentation](https://memgpt.readthedocs.io/)
- [Discord](https://discord.gg/9GEQrxmVyE)
- [Hugging Face](https://huggingface.co/MemGPT)
## [Mentat](https://github.com/biobootloader/mentat)
Assists you with coding task from command line
### Category
Coding
### Description
Mentat is the AI tool that assists you with any coding task, right from your command line.
Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project - no copy and pasting required!
### Links
- [Website](https://www.mentat.codes/)
- [Youtube](https://www.youtube.com/watch?v=lODjaWclwpY)
- Author: [Bio Bootloader](https://twitter.com/bio_bootloader) (Twitter)
- [Discord Invite](https://discord.com/invite/zbvd9qx9Pb)
## [MetaGPT](https://github.com/geekan/MetaGPT)
Agent framework returning Design, Tasks, or Repo
### Category
Multi-agent, Coding, Build your own
### Description
MetaGPT is a multi-agent framework that, given one line requirement, returns PRD, Design, Tasks, or Repo.
- MetaGPT allows to assign different roles to GPTs to form a collaborative software entity for complex tasks
- It takes a one line requirement as input and outputs user stories / competitive analysis / requirements / data structures / APIs / documents, etc.
- Internally, MetaGPT includes product managers / architects / project managers / engineers
- It provides the entire process of a software company along with carefully orchestrated SOPs. Code = SOP(Team) is the core philosophy
- The paper about LLM-based multi-agent work spushes forward the idea of autonomous agents collaborating with each other to do more than one can on its own.
- MetaGPT incorporates efficient human workflows as a meta programming approach into LLM-based multi-agent collaboration
### Links
- [GitHub](https://github.com/geekan/MetaGPT)
- [Discord](https://discord.com/invite/4WdszVjv)
- [Twitter](https://twitter.com/DeepWisdom2019)
- [Paper - MetaGPT: Meta Programming for Multi-Agent Collaborative Framework](https://arxiv.org/abs/2308.00352)
## [Mini AGI](https://github.com/muellerberndt/mini-agi)
General-purpose agent based on GPT-3.5 / GPT-4
### Category
General purpose
### Description
- MiniAGI is a minimal general-purpose autonomous agent based on GPT-3.5 / GPT-4
- Can analyze stock prices, perform network security tests, create art, and order pizza
- MiniAGI is a simple autonomous agent compatible with GPT-3.5-Turbo and GPT-4
- It combines a robust prompt with a minimal set of tools, chain-of-thoughts, and short-term memory with summarization
- Capable of inner monologue and self-criticism
### Links
- [GitHub](https://github.com/muellerberndt/mini-agi)
## [Multiagent Debate](https://github.com/composable-models/llm_multiagent_debate)
Implementation of a paper on Multiagent Debate
### Category
General purpose, Multi-agent
### Description
Multiagent Debate is an implementation of the paper "Improving Factuality and Reasoning in Language Models through Multiagent Debate".
- The paper illustrates how we may treat different instances of the same language models as a "multiagent society", where individual language model generate and critique the language generations of other instances of the language model
- The authors find that the final answer generated after such a procedure is both more factually accurate and solves reasoning questions more accurately
- Illustrating the quantitative difference between multiagent debate and single agent generation on different domains in reasoning and factual validity
### Links
- [GitHub](https://github.com/composable-models/llm_multiagent_debate)
- [Project page](https://composable-models.github.io/llm_debate/)
- [Paper](https://arxiv.org/abs/2305.14325)
## [Multi GPT](https://github.com/rumpfmax/Multi-GPT)
Experimental multi-agent system
### Category
General purpose
### Description
- An experimental open-source attempt to make GPT-4 fully autonomous
- Multiple "expertGPTs" collaborate to perform a task
- Each with their own short and long-term memory and the ability to communicate with each other
- Features
- Set a task and watch the experts get to work.
- Internet access for searches and information gathering
- Long-Term and Short-Term memory management
- GPT-4 instances for text generation
- Access to popular websites and platforms
- File storage and summarization with GPT-3.5
### Links
- [Demo](https://www.loom.com/share/b6bec93065794eb8a47e2109697afa39)
- Authors: [Max Rumpf](https://twitter.com/md_rumpf) and [Significant Gravitas](https://twitter.com/SigGravitas)
## [MutahunterAI](https://github.com/codeintegrity-ai/mutahunter)
MutahunterAI: Accelerate developer productivity and code security with our open-source AI
### Category
Developer tools, Software security, Multi-agent, General purpose
### Description
- Use Mutahunter to generate unit tests for your codebase, that specifically target the code vulnerabilities. By targeting the exact weaknesses in the code, we boost developer productivity.
- Unlike copilots which blindly generates test cases for your code, Mutahunter makes use of our mutation testing engine to generate unit tests that specifically target the vulnerabilities in your code
- Features
- Support all major languages.
- We can be used locally or can be integrated into any CI/CD runner as part of your existing workflow
- You can use Mutahunter with your own LLM APIs for privacy.
### Links
- [Documentation](https://github.com/codeintegrity-ai/mutahunter?tab=readme-ov-file#mutahunter)
- [Discord](https://discord.gg/9P5V9qmKJn)
- [GitHub](https://github.com/codeintegrity-ai/mutahunter)
## [NLSOM](https://github.com/mczhuge/NLSOM)
Natural Language-Based Societies of Mind
### Category
Science, Multimodal, Social, Multi-agent
### Description
- Natural Language-Based Societies of Mind - concept with societies and communities of agents
- Concept, which contains societies and communities of agents
- Agents can be either LLMs, NN-based experts, APIs and role-players. They all communicate in natural language.
- To solve tasks, these agents use a collaborative "Mindstorm" process involving mutual interviews.
- Additional components for NLSOM can be easily added in a modular way.
- "What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle." — Marvin Minsky, The Society of Mind, p. 308
### Links
- [GitHub](https://github.com/mczhuge/NLSOM)
- [Paper](https://arxiv.org/pdf/2305.17066.pdf)
- [Author's X - Jürgen Schmidhuber](https://twitter.com/SchmidhuberAI)
- [Author's X - Mingchen Zhuge](https://twitter.com/MingchenZhuge)
## [OpenAgents](https://github.com/xlang-ai/OpenAgents)
Multi-agent general purpose platform
### Category
General purpose
### Description
OpenAgents is an Open Platform for Language Agents in the Wild, ChatGPT Plus Replica for Researchers, Developers, and General Users.
- User-centric
- Chat Web UI
- Productive Agents
- Online Demo
- Fully open-sourced
- Full-stack
- Easy deployment
- Extensible
- LLMs
- Tools
- Agent methods
### Links
- [GitHub](https://github.com/xlang-ai/OpenAgents)
- [Paper](https://arxiv.org/abs/2310.10634)
- [Demo](https://chat.xlang.ai/)
## [OpenAGI](https://github.com/agiresearch/OpenAGI)
R&D agents platform
### Category
General purpose
### Description
OpenAGI is an open-source AGI R&D platform that enables agents for both benchmark tasks and open-ended tasks
- Powered by various language models such as GPT-4, Vicuna, LLaMA, and Flan-T5
- Supports multi-modality tool learning and task solving such as text, image, video and audio
- Supports task decomposition into both linear task-solving plans and non-linear task-solving plans
- Allows both benchmark task solving and open-ended task solving
- Provides easy-to-use evaluation protocols to evaluate task-solving ability
- Provide Reinforcement Learning from Task Feedback (RLTF) to allow continuously self-improving agent
### Links
- [GitHub](https://github.com/agiresearch/OpenAGI)
- [Paper](https://arxiv.org/abs/2304.04370)
- [Demo](https://www.youtube.com/watch?v=7RaXPPXi0-Y)
## [OpenDevin](https://github.com/OpenDevin/OpenDevin)
OpenDevin: Code Less, Make More
### Category
Coding, general purpose
### Description
- The OpenDevin project is born out of a desire to replicate, enhance, and innovate beyond the original Devin model.
- By engaging the open-source community, we aim to tackle the challenges faced by Code LLMs in practical scenarios, producing works that significantly contribute to the community and pave the way for future advancements.
### Links
- [GitHub](https://github.com/OpenDevin/OpenDevin)
## [Open Interpreter](https://openinterpreter.com/)
Code interpreter that lets LLMs execute code
### Category
Coding
### Description
Open Interpreter is an open-source interpreter that lets LLMs run code on your computer to complete tasks
- Runs locally
- Can for example summarize PDFs, visualize datasets, control your browser
- Works from a ChatGPT-like interface in your terminal.
### Links
- [Web](https://openinterpreter.com/)
- [GitHub](https://github.com/KillianLucas/open-interpreter)
- [Author's Twitter](https://twitter.com/hellokillian)
## [Pezzo](https://www.pezzo.ai/)
Development toolkit for prompt management & more
### Category
Coding
### Description
Pezzo is a development toolkit designed to streamline prompt design, version management, publishing, collaboration, troubleshooting, observability and more
- "Whether you are a technical person or a stakeholder, you can use Pezzo effectively. We don't believe that AI prompts should be designed in a developer's code editor. Aside from the technical issues with this approach, it blocks productivity."
- Features
- Centralized Prompt Management: Manage all AI prompts in one place for maximum visibility and efficiency.
- Streamlined Prompt Design, Publishing & Versioning: Create, edit, test and publish prompts with ease.
- Observability: Access detailed prompt execution history, stats and metrics (duration, prompt cost, completion cost, etc.) for better insights.
- Troubleshooting: Effortlessly resolve issues with your prompts. Time travel to retroactively fine-tune failed prompts and commit the fix instantly.
- Cost Transparency: Gain comprehensive cost transparency across all prompts and AI models.
- Simplified Integration: Reduce code overhead by 90% by consuming your AI prompts using the Pezzo Client, regardless of the model provider.
### Links
- [Documentation](https://docs.pezzo.ai/docs/intro.html)
- [GitHub](https://github.com/pezzolabs/pezzo)
## [Private GPT](https://www.privategpt.io/)
Tool for private interaction with your documents
### Category
Research, Data analysis
### Description
Private GPT is A tool for private interaction with documents, without a need for internet connection
- Built with LangChain, GPT4All, LlamaCpp, Chroma and SentenceTransformers
- A test project to validate the feasibility of a fully private solution for question answering using LLMs and Vector embeddings, not production ready
### Links
- [GitHub](https://github.com/imartinez/privateGPT)
## [PromethAI](https://github.com/topoteretes/PromethAI-Backend)
AI agent that helps with nutrition and other goals
### Category
Productivity, General purpose
### Description
- "Personalized AI assistant that decomposes problems, offers solutions, and lets you use Agent actions to automate your flows"
- Features
- Helps users reach a solution by decomposing their requests into categories with a set of options (cuisine -> European)
- Has a dynamic UX/UI that helps avoid prompting
- Voice input supported
- Provides users with results of their queries and automates actions around them
- Remembers your past preferences and uses them to optimize your choices
- Tech
- Powered by Langchain, decomposable async prompts + vector DB + Redis cache
- App built with Flutter + Dart
- Connected to Zapier NLP
### Links
- [GitHub](https://github.com/topoteretes/)
- [Website](https://prometh.ai)
- Author: [Vasilije M](https://twitter.com/tricalt)
## [React Agent](https://reactagent.io/)
Open-source React.js Autonomous LLM Agent
### Category
Coding
## Description
- An experimental autonomous agent
- Model: GPT-4
- Purpose: Gnerate and compose React components from user stories
- Stack
- React
- TailwindCSS
- Typescript
- Radix UI
- Shandcn UI
- OpenAI API
- The agent is taking a user story text and generating and composing multiple react components to generate the relevant screens, based on atomic design principles
- Features
- Generate React Components from user stories
- Compose React Components from existing components
- Use a local design system to generate React Components
- Use React, TailwindCSS, Typescript, Radix UI, Shandcn UI
- Built with Atomic Design Principles
- It is still experimental but very interesting results, It is completely open-sourced, looking for contributors!
## Links
- [GitHub](https://github.com/eylonmiz/react-agent)
- [Documentation](https://docs.reactagent.io/)
- Authors: [Eylon Miz and](https://twitter.com/EylonMiz) and [Lee Twito](https://twitter.com/LeeTwito)
## [Self-operating computer](https://www.hyperwriteai.com/self-operating-computer)
Let multimodal models operate a computer
### Category
Productivity, Research
### Description
- Using the same inputs and outputs as a human operator, the model views the screen and decides on a series of mouse and keyboard actions to reach an objective.
### Links
- [Web](https://www.hyperwriteai.com/self-operating-computer)
- [GitHub](https://github.com/OthersideAI/self-operating-computer)
## [Smol developer](https://github.com/smol-ai/developer)
Your own junior AI developer, deployed via E2B UI
### Category
Coding
### Description
Smol is your own junior developer. [Deployed in few seconds via e2b](https://app.e2b.dev/agent/smol-developer/?utm_source=awesome-ai-agents)
- Human-centric, coherent whole program synthesis
- Your own junior developer
- Allows to develop, debug, and decompile
- 200 LOC, half english
- 100k context can summarize both content and codebases
- Markdown is the best prompting DSL
- Copy and paste your errors as prompts
- Copy and paste curl output as prompts
- Write CSS animation by describing what u want
- GPT4 >>> GPT3.5/Anthropic Claude for codegen
### Links
- Author: [Swyx](https://twitter.com/swyx)
- [Demo](https://www.youtube.com/watch?v=UCo7YeTy-aE)
- [Twitter](https://twitter.com/SmolModels)
- [Meme](https://smol.ai/)
## [Stackwise](https://github.com/stackwiseai/stackwise)
VSCode extension that writes nodejs functions
### Category
Tool for agents, Coding
### Description
Stackwise is a VS Code extension that writes and imports nodejs functions so that you can write code without context switching
- The open source function collection
- Explain what you want a function to do, and AI builds it.
- Stackwise is a VS Code extension that automatically writes and imports nodejs functions so that you can write code without context switching. No more hunting for documentation to integrate with APIs or back and forth with ChatGPT. Just pure functionality within your code!
### Links
- [GitHub](https://github.com/stackwiseai/stackwise)
- [X](https://twitter.com/stackwiseai)
- [Founder's X - Wayne](https://twitter.com/merwanehamadi)
- [Founder's X - Silen Naihin](https://twitter.com/silennai)
## [Superagent](https://www.superagent.sh/)
Tool that allows creating agents without coding
![image](https://api.typedream.com/v0/document/public/b9d688ba-8f34-40e4-a24a-c