Источник: awesome-ai-agents — синхронизируется из внешнего репозитория как sparse-субмодуль (только список).
🔮 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:
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 hello@e2b.dev 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#
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#
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#
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#
AgentPilot#
Build, manage, and chat with agents in desktop app
Category#
General purpose
Description#
- Integrated into Open Interpreter and MemGPT
- Group chats feature
Links#
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#
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#
AI Legion#
Multi-agent TS platform, similar to AutoGPT
…превью ограничено; полный список — в репозитории.