AutoGPT is an advanced AI system that operates autonomously to accomplish user-defined goals. It utilizes large language models, such as GPT-4, to understand and break down complex tasks into smaller, manageable subtasks. AutoGPT can access the internet, use various tools and APIs, and even write and execute code to achieve its objectives. This AI agent continuously refines its approach based on the results of each subtask, demonstrating a level of adaptability and problem-solving capability that mimics human-like reasoning. AutoGPT represents a significant step towards artificial general intelligence (AGI), as it can handle a wide range of tasks across different domains without requiring specific programming for each task. 

AutoGPT

AI agent that autonomously performs tasks by breaking them down into subtasks.

MetaGPT is a sophisticated AI framework that leverages large language models to create a collaborative environment of specialized AI agents. These agents work together to handle complex software development tasks, from project planning to code generation. By encoding real-world expertise into standardized operating procedures (SOPs), MetaGPT aims to streamline the entire software development lifecycle, potentially reducing costs and improving efficiency

MetaGPT

AI-driven multi-agent framework for automated software development and project management

CrewAI is an innovative framework for creating and managing teams of AI agents that work together to accomplish complex tasks. It provides a modular structure for defining agents with specific roles, goals, and tools, as well as organizing tasks and workflows. CrewAI enables the development of sophisticated AI systems that can collaborate, delegate, and tackle multi-step problems through a combination of individual agent capabilities and coordinated teamwork.

CrewAI

Platform for Multi AI Agents System for complex task execution.

SuperAGI is an open-source autonomous AI agent framework designed for developers to build, manage, and run autonomous agents efficiently. It supports concurrent agent operations, integrates with various tools, and provides a graphical user interface for easy interaction. The framework is scalable, allowing for complex AI operations, and includes features like performance telemetry, agent memory storage, and optimized token usage to enhance functionality and cost management.

SuperAGI

A dev-first, open-source framework for building and managing autonomous AI agents.

Multi-GPT is an open-source project that creates a collaborative environment for multiple AI agents, each with specialized expertise, to work together on complex tasks. It leverages GPT-4 for text generation and features internet access, memory management, and file storage capabilities. The system allows multiple "expertGPTs" to communicate and share information, enhancing problem-solving abilities and task completion efficiency.

Multi-GPT

An experimental multi-agent system enabling collaboration between specialized AI experts.

Flowise is an innovative open-source tool designed for developers to create and manage Large Language Model (LLM) applications with ease. It offers a low-code approach, enabling quick iterations from testing to production. Flowise integrates various LLM technologies, including Langchain and LlamaIndex, and supports over 100 integrations. It allows users to build AI agents, create custom tools, and develop LLM orchestration flows, all while providing flexibility through APIs, SDKs, and embedded widgets

Flowise AI

An open-source low-code platform for building AI agents.

GPTSwarm is an open-source project that combines swarm intelligence with advanced language models to create a powerful, adaptive, and scalable framework for AI agents. It allows users to build, integrate, and automatically improve diverse LLM-based agents by representing them as computational graphs. GPTSwarm leverages collective problem-solving and distributed decision-making to outperform single models in handling complex tasks across various domains.

GPTSwarm

A scalable framework for building and optimizing AI agent swarms to tackle complex tasks.

CodeFuse-muAgent is a comprehensive Multi-Agent framework developed by the Ant CodeFuse Team. It aims to simplify the orchestration of Standard Operating Procedures (SOP) for agents in software development. The framework integrates various toolkits, code libraries, knowledge bases, and sandbox environments, enabling users to quickly build complex Multi-Agent interactive applications for efficient execution of multi-layered and multi-dimensional tasks

Codefuse

A Multi-Agent FrameWork For Faster Build Agents

LangChain is an open-source framework designed to simplify the development of applications using large language models (LLMs). It provides tools and abstractions to connect LLMs with external data sources, enabling the creation of context-aware, reasoning applications. LangChain supports the entire application lifecycle, from development and debugging to deployment and monitoring, making it easier to build robust and scalable AI-powered solutions.

LangChain

A framework for building and deploying applications powered by large language models (LLMs).

LlamaIndex is a flexible data framework designed to connect custom data sources to large language models (LLMs). It simplifies the process of building, iterating, and deploying multi-agent AI systems, enabling autonomous task execution over various data types. LlamaIndex supports both read and write functions, allowing dynamic data ingestion and modification through a reasoning loop and tool abstractions.

LlamaIndex

LlamaIndex is the leading data framework for building LLM applications

LaVague is an open-source framework designed to develop AI Web Agents using Large Action Models. These agents can automate complex web interactions by interpreting natural language commands and executing tasks such as web navigation, data extraction, and form filling. By leveraging components like the World Model and Action Engine, LaVague simplifies the process of building and deploying AI agents that can perform a wide range of web-based tasks efficiently.

LaVague

Large Action Models framework to build AI Web Agents

Praison AI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration. You also have dedicated AI Agents to perform specific tasks such as chat with your ENTIRE Codebase.

PraisonAI

Multi AI Agents Framework to Automate Tasks

AutoGen is an open-source framework developed by Microsoft Research for building next-generation Large Language Model (LLM) applications. It enables multi-agent conversations, allowing developers to create complex AI workflows with multiple specialized agents collaborating to solve tasks. AutoGen simplifies the development of LLM-powered applications and supports various LLM configurations, tool usage, and human-AI interaction.

AutoGen

An Open-Source Programming Framework for Agentic AI

ChatDev is an innovative open-source framework that revolutionizes software development by leveraging large language models (LLMs) and multi-agent collaboration. It simulates a virtual software company where AI agents with different roles (e.g., CEO, CTO, programmer) work together to design, code, test, and document software based on natural language descriptions. ChatDev aims to democratize software creation, making it accessible to non-programmers while enhancing efficiency for experienced developers.

ChatDev

Virtual software company that operates through various intelligent agents holding different roles

Internet of Agents (IoA) is an innovative open-source framework designed to create a collaborative platform for diverse AI agents. It mimics the connectivity of the internet, allowing different AI agents to team up, share their unique capabilities, and work together on complex problems that might be challenging for a single agent to solve. This framework aims to revolutionize how AI agents interact and cooperate, potentially leading to more efficient and effective problem-solving in various domains.

Internet of Agents

Open-source framework enabling AI agents to collaborate and tackle complex tasks together

LangGraph is a powerful framework designed to simplify the development of conversational AI agents. It provides an intuitive interface and robust tools for building, training, and deploying chatbots and virtual assistants. By leveraging advanced natural language processing and machine learning techniques, LangGraph enables developers to create highly interactive and context-aware AI agents. It supports various integration options, making it suitable for multiple platforms and applications.

LangGraph

A framework for building conversational AI agents.

Haystack is an open-source NLP framework developed by Deepset, designed for creating advanced search systems and conversational AI applications. It enables developers to build powerful, end-to-end search pipelines that can handle large-scale, complex queries with high accuracy. Haystack leverages state-of-the-art transformer models, supports various backends, and is highly customizable, making it ideal for enterprise-level search and Q&A systems. It also includes features for document retrieval, question answering, and semantic search.

Haystack

An open-source NLP framework for building search systems and conversational AI.

TaskWeaver is an innovative, open-source framework developed by Microsoft, designed to seamlessly plan and execute data analytics tasks through a code-first approach. It interprets user requests via code snippets and coordinates various plugins to perform tasks efficiently. Unlike traditional agent frameworks, TaskWeaver preserves both chat and code execution history, making it particularly adept at handling complex data structures and stateful execution processes. This feature-rich tool is ideal for developers aiming to automate and streamline their data workflows.

TaskWeaver

A code-first agent framework for planning and executing data analytics tasks.

DAGent is an open-source framework designed for creating AI agents structured as Directed Acyclic Graphs (DAGs). This approach allows for flexible and efficient management of decision-making processes and function executions. By organizing tasks and decisions in a DAG structure, developers can create complex, multi-step workflows that are both modular and scalable. DAGent provides tools for defining decision nodes, function nodes, and their interconnections, making it a powerful tool for building sophisticated AI systems that require a high degree of control and customization.

DAGent

A framework for building AI agents using Directed Acyclic Graphs (DAGs).

Mirascope is an open-source python toolkit designed to simplify the integration of LLMs into applications. It provides the right level of abstractions so developers remain in control. Miracsope can be used completely on its own for building with LLMs or you can pick the pieces you like from other frameworks and still get the best out of Mirascope.

Mirascope

An OSS Python toolkit for building AI agents and apps with abstractions that aren't obstructions.

AgentGenesis is a framework designed to simplify the creation and deployment of AI agents without requiring any coding expertise. It provides an intuitive interface for designing, training, and managing AI agents, making it accessible to users with minimal technical background. The platform supports integration with various data sources and tools, enabling the creation of sophisticated AI solutions quickly and efficiently.

Agent Genesis

Build custom RAG flows and AI agents using open-source, copy-paste components.

Agent Zero is an AI framework designed to be a flexible and interactive platform for creating personal AI assistants. It allows users to design agents capable of executing commands, gathering information, and cooperating with other agents. Agent Zero emphasizes full customization, enabling users to modify its behavior, tools, and interactions. It operates in a transparent environment where users can guide the agent's actions in real-time, making it highly adaptable for various use cases.

Agent Zero

A dynamic, general-purpose framework for creating custom AI Agents.

Lyzr-automata is a low-code framework designed to simplify the creation and deployment of generative AI applications. It uses an agentic approach, offering an alternative to traditional methods like LangChain's functions and DSPy’s programmatic techniques. This tool allows developers to build AI agents quickly and integrate them into various workflows and platforms, making it easier to implement sophisticated AI-driven solutions without extensive coding.

Lyzr-automata

A low-code multi-agent automation framework

ControlFlow is an open-source Python framework that enables the creation of AI-driven workflows by integrating large language models (LLMs) into structured task-based processes. It builds on Prefect’s workflow orchestration platform, allowing users to define tasks, assign specialized AI agents, and manage the flow of execution within a broader context. This approach enhances control over AI agents, reducing errors and improving task management in AI applications.

ControlFlow

A Python framework for orchestrating AI-powered workflows with task-centric design.

Griptape is a framework designed to simplify the creation and deployment of AI agents. It allows developers to build and manage AI solutions with minimal coding effort, using pre-built templates and an intuitive interface. It focuses on integrating various AI models and automating workflows to enhance productivity.

Griptape

Framework for creating AI agents with minimal coding.

L-Agent is an open-source framework for developing AI agents with a focus on ease of use and flexibility. It provides a set of tools and libraries for building, training, and deploying AI models, facilitating the creation of intelligent systems that can interact with users and handle complex tasks. The framework supports various integrations and is suitable for both research and production environments.

LAgent

Open-source framework for building and deploying AI agents.

Crab is a comprehensive framework designed by Camel AI for building and benchmarking environments tailored for large language model (LLM) agents. The platform supports the creation of cross-platform environments, allowing for deployment across in-memory systems, Docker-hosted environments, virtual machines, or distributed physical machines. Crab provides an easy-to-use Python-centric interface for defining agent environments and actions, making it flexible for various use cases. Additionally, it includes a novel benchmarking suite that provides fine-grained evaluation metrics.

Crab

Framework for building LLM agent benchmark environments in a Python-centric way.

Julep's platform is an open source managed backend to create AI agents. Developers can create stateful AI agents in 10 mins with Julep. The platform is supported by a multi-agentic framework, and automatically manages user history, supports most LLMs, built-in RAG pipeline, integrations with 100+ tools, adaptive context (management), and tasks. 

Julep's main concepts are agents, sessions, and users. You can start a session and add agents and users to it. These agents can create a plan and perform tasks.

Tasks is the most important feature of Julep and will be launched around Aug 15. Tasks are workflows for AI agents, kind of like Github actions.

Memories for users - coming soon

Julep

Framework for creating AI agents that remember past interactions and can perform complex tasks

AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. Compatible with a range of LLM models — currently supporting OpenAI, Google's Gemini, Anthropic's Claude, and Ollama or LMStudio for local LLMs — it offers the flexibility to run different models for different agents based on your specific needs.

AgentForge

A Python framework for creating, testing, and deploying LLM-powered agents.

BondAI is a Python-based framework designed to build and deploy single and multi-agent systems. It supports various integrations, including OpenAI, Azure, Google, and more, allowing for advanced capabilities like vector/semantic search, memory management, and error handling. The framework can be used via CLI, Docker, or integrated directly into your codebase, making it versatile for different development environments.

BondAI

Framework for building AI agents with memory, context, and multiple integrations.

ChatArena is a Python-based framework designed to facilitate the creation and testing of multi-agent systems using large language models (LLMs). It provides a flexible environment where agents interact through games or conversational scenarios. Developers can define custom environments, games, and interactions, making it suitable for AI research in autonomous systems, social interaction, and language model benchmarking. The framework is equipped with a web-based UI and CLI for ease of use.

ChatArena

A framework for creating multi-agent language game environments for AI models.

Langroid is an open-source Python framework designed to simplify LLM application development using a multi-agent programming paradigm. It treats agents as first-class citizens, allowing developers to configure agents with capabilities like LLMs, vector databases, and function-calling/tools. Langroid enables collaborative problem-solving through message exchange between agents, offering a "conversational programming" approach that works with both local/open and remote/proprietary LLMs.

Langroid

Multi-agent programming framework for LLM applications.

UFO is an innovative, open-source framework developed by Microsoft, designed to facilitate seamless interaction with Windows OS applications through natural language commands. Utilizing a dual-agent system—comprising the HostAgent and AppAgent—UFO can navigate and control various applications to fulfill user requests. This framework employs GPT-Vision to analyze and interact with graphical user interfaces, transforming complex, multi-application tasks into simple, automated processes. UFO is particularly effective in automating repetitive tasks and improving productivity by 

UI-focused multi-agent framework for Windows OS interactions.

LoopGPT is an open-source reimplementation of the Auto-GPT project as a Python package. It's designed with modularity and extensibility in mind, allowing developers to easily create and customize AI agents. LoopGPT supports various features like plug-and-play API, GPT-3.5 compatibility, minimal prompt overhead, human-in-the-loop functionality, and full state serialization.

LoopGPT

A modular Auto-GPT framework for building AI agents

The uAgent framework is a library developed by Fetch.ai to facilitate the creation of decentralized AI agents. It is designed to be lightweight and efficient, enabling developers to build autonomous agents that can operate within multi-agent systems. These agents are capable of self-governance, maintaining enduring memory, and communicating directly with each other. The framework supports the integration of blockchain and native AI functionalities, allowing agents to connect, search, and transact in dynamic marketplaces. This infrastructure aims to transform economic activities by enabling new forms of interaction and transaction between AI agents.

uAgent

A library that allows creating autonomous AI agents in Python

NeMo Guardrails is an open-source toolkit that allows developers to easily add programmable guardrails to LLM-based conversational applications. It provides a way to control and guide the output of large language models, enhancing safety, reliability, and functionality of AI chatbots and conversational agents

NeMo Guardrails

Toolkit for adding programmable guardrails to LLM-based conversational AI


Marvin is a lightweight toolkit that enables developers to build reliable, scalable, and trustworthy natural language interfaces. It provides AI functions and bots to easily integrate AI capabilities into existing codebases without requiring extensive AI knowledge.

Marvin

AI toolkit for building natural language interfaces

LobeChat is an open-source AI chat platform that allows users to create custom chatbots and interact with multiple AI models. It offers features like speech synthesis, visual recognition, and an extensible plugin system to enhance conversational capabilities.

LobeChat

AI conversation platform with multi-model support

LlamaGym is an innovative tool designed to simplify the process of fine-tuning large language model (LLM) agents through reinforcement learning. It provides a standardized environment for LLM agents, similar to how OpenAI's Gym standardized reinforcement learning environments. The platform allows users to easily experiment with and iterate on agent prompts and hyperparameters.

LlamaGym

Tool for fine-tuning LLM agents using reinforcement learning

LiveKit Agents is an end-to-end framework designed for creating real-time, multimodal AI agents that can interact with users through voice, video, and data channels. It provides a comprehensive set of tools and abstractions for tasks such as speech-to-text, text-to-speech, and LLM integration, allowing developers to focus on core application logic.

LiveKit Agents

Framework for building real-time, multimodal AI agents

LiteLLM is an open-source package that provides a standardized interface for calling multiple Large Language Model (LLM) APIs, including OpenAI, Azure, Anthropic, and many others. It simplifies the process of integrating different LLM providers by offering a consistent OpenAI-like input format, built-in streaming, logging, and load balancing capabilities.

LiteLLM

AgentLabs is an open-source platform that enables developers to build and deploy AI-powered chat applications without front-end experience. It provides a customizable frontend interface, real-time communication capabilities, and tools for managing AI agents, allowing users to focus on backend development while AgentLabs handles the user-facing components.

AgentLabs

Open-source universal frontend for your AI Agents

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.

FastAgency

The fastest way to bring multi-agent workflows to production.

Create, manage, and chat with AI agents using your own keys, models and local data.

Agent Pilot provides a seamless experience, whether you want to chat with a single LLM, or a complex multi-member workflow.

Branching conversations are supported, edit and resend messages as needed.

Combine models from different providers under one chat, and configure their interaction with each other in a low-code environment. 

Agent Pilot

Create, manage, and chat with AI workflows seamlessly

Agience is an open-source intelligent agent framework that connects devices, systems, and data to achieve new levels of automation and efficiency.

Agience

Airtop provides an intelligent browser automation API for AI agents, enabling seamless web interaction, including login, navigation, and data extraction from any site, even those requiring complex authentication processes. With features like natural-language instructions, human-in-the-loop integration, high-performance scalability, and robust AI framework support, Airtop simplifies the development and deployment of AI-powered agents, making it an essential tool for AI-driven projects that require dynamic web interaction.

Airtop API

Intelligent browser automation API for AI agents

KaibanJS, shorthand for "AI in a Kanban," is a JavaScript framework designed to streamline the process of constructing, managing, and visualizing multi-agent AI systems.

With KaibanJS, you can: 

- Easily assemble groups of AI agents to work collaboratively on complex tasks. 
- Monitor and manage your agents' activities through a Trello-like UI that offers a clear visual representation of tasks and workflows. 
- Operate the Kanban Board on your local system, giving you full control over the environment and ensuring privacy and data security. 
- Utilize a broad range of JavaScript libraries and APIs to enhance the functionality of your agents.

KaibanJS

KaibanJS -> Kanban for AI Agents. JavaScript Framework for Building Multi-Agent Systems.

Built on the #1 CPaaS provider, the #1 CDP, and powerful LLM infrastructure, AI Assistants unlocks a new future of customer-aware autonomous agents that will delight customers and businesses alike. AI Assistants are trained on your company’s knowledge assets, and are capable of leveraging tools that you define to make API requests to interact with other systems and complete tasks. Every autonomous agent is equipped with customer memory capabilities powered by Segment so you can create personalized customer experiences at scale. Brands can engage with their customers across a variety of channels from day one, including chat, email, SMS, WhatsApp, voice and more. Assistants are also equipped with out-of-the-box Guardrails.

Twilio AI Assistants

Opinionated framework to build and host conversational AI Assistants for customer-facing use cases

Dendrite is a devtool that makes it easy for AI agents to browse the web and:

🔓 Authenticate on websites
👆🏼 Interact with elements
💿 Extract structured data
↕️ Download/upload files
🚫 Browse without getting blocked

Dendrite

The world's first developer toolkit that makes any website fully accessible to AI Agents.

CAMEL-AI.org is the 1st LLM multi-agent framework and an open-source community dedicated to finding the scaling law of agents.

CAMEL

Multi-agent systems, synthetic data generation, task automation, world simulation.

The unofficial DSPy framework. Build LLM powered Agents and "Agentic workflows" based on the Stanford DSP paper.

Build LLM powered Agents and "Agentic workflows" 

Base AI is the first Web AI Framework. The easiest way to build Serverless autonomous AI agents with memory and tools. Start building local-first with an offline developer experience, build agentic pipes, self-healing tools, and agentic deep reasoning memory. When ready, deploy Serverless with one command `npx baseai deploy` and all your agents, pipes, tools, memories are deployed to ⌘ Langbase the serverless AI developers platform. Our mission is to make AI accessible to everyone, any developer not just AI/ML experts.



BaseAI.dev

The easiest open-source way to build Serverless autonomous AI agents with memory and tools.

Requesty's model as a service helps you fully define your requirements in an easy to use UI, providing you with built-in monitoring, observability, topic classification and much more!

Requesty

Easiest way to define create production ready AI applications.

ThynkForward’s first mover advantage by integrating vCons and SCITT positions its services at the forefront of the Agentic AI market. ThynkForward services enhance data security, compliance, and efficiency, offering any sized company a comprehensive solution to leverage AI for customer interaction and operational excellence. By addressing industry trends and capitalizing on market potential, ThynkForward is uniquely postioned to lead the next wave of innovation in Agentic AI.

Thynk Forward

GaiaHub is a central platform designed to empower developers by providing a collaborative space where they can create, share, and access reusable components or "building blocks" for developing large language model (LLM) applications. These building blocks include pre-built templates, APIs, code snippets, and tools that streamline the process of building complex applications with language models. With GaiaHub, even those new to LLMs can leverage these resources to create powerful applications with minimal setup, enabling a quick journey from beginner to proficient developer in just a few minutes.

GaiaHub

GaiaHub is a hub where developers create and share building blocks that can be used to create AI App

Mission Squad is an API & app that lets you use any AI model to create groups of agents that work together to accomplish your tasks in minutes.
Compatible with OpenAI, Anthropic, Groq, Infermatic, LM Studio and others that use the OpenAI API spec.
Create your agent and/or squad, then use them like you would any other base model. Think of squads like a chain of agents with an agent manager.

Mission Squad

Create your squad and give them a mission!

Guardrails AI is an open-source framework designed to enhance the development of Generative AI applications by simplifying LLM response validation, improving reusability, and providing robust operational features. It offers a comprehensive set of tools for working with LLMs, streamlining the development process and promoting the creation of more robust and reliable AI applications

Guardrails AI

Framework for developing safe and reliable Generative AI applications

Restack is a framework for building autonomous AI products, designed to address the challenges of developing reliable and scalable autonomous intelligence. It offers a comprehensive toolkit for engineers to create AI-powered systems that can adapt and improve over time. Restack supports polyglot development, real-time event processing, and integrates advanced features like reinforcement learning and long-term memory management.

Restack

The framework for autonomous intelligence

Flo AI is a Python framework that makes building production-ready AI agents and teams as easy as writing YAML. Think "Kubernetes for AI Agents" - compose complex AI architectures using pre-built components while maintaining the flexibility to create your own.

FloAI

 Simple way to create composable AI agents

DSPy is an open-source Python framework that enables developers to build language model applications using modular and declarative programming. It automates prompt engineering and model selection, allowing developers to focus on high-level logic rather than manual prompt crafting. DSPy optimizes prompts and models based on specified metrics, making AI systems more reliable, scalable, and efficient.

DSPy

Automated prompt optimization framework for building AI Agents

The Multi-Agent Orchestrator is an AWS-developed framework designed to manage multiple AI agents and orchestrate complex conversations. It intelligently routes queries to the most suitable agent, maintains conversational context, and integrates with various environments. The system supports both streaming and non-streaming responses, offering pre-built components for quick deployment while allowing easy integration of custom agents

Multi-Agent Orchestrator

Flexible framework for managing multiple AI agents and handling complex conversations

Gwenflow, a framework designed by Gwenlake, streamlines the creation of customized, production-ready applications built around Agents and Large Language Models (LLMs). It provides developers with the tools necessary to integrate LLMs and Agents, enabling efficient and scalable solutions tailored to specific business or user needs.

Gwenflow

A framework for orchestrating applications powered by autonomous AI agents and LLMs.

The Bee Agent Framework is an open-source toolkit designed to create scalable agent-based workflows with various AI models. It offers robust performance with IBM Granite and Llama 3.x models, providing developers with tools to build complex agentic architectures that efficiently manage workflow states and offer production-ready features for real-world deployment.

Bee Agent Framework

Open-source framework for building, deploying, and serving powerful agentic workflows at scale

Qwen-Agent is an open-source framework developed by Alibaba Cloud for creating Large Language Model (LLM) applications. It leverages the instruction-following, tool usage, planning, and memory capabilities of Qwen models. The framework provides components for LLMs, prompts, and agents, allowing developers to quickly build and customize AI agents that can use various tools and handle complex tasks

Qwen Agent

Framework for building LLM applications with Qwen models' advanced capabilities

PydanticAI is a Python framework designed to simplify the development of production-grade applications using Generative AI. It offers model-agnostic support, type-safety, structured response validation, and a novel dependency injection system. PydanticAI leverages the power of Pydantic for data validation and integrates seamlessly with various AI models, making it easier for developers to build robust AI-powered applications

PydanticAI

Python Agent Framework for building production-grade Generative AI applications

Agent Ecosystem pre-developed for you. 
Accelerate your time-to-value with specialized agents designed to simplify development and deployment, optimize performance, and ensure your agents are future-proof.

aiXplain

Production-ready AI Agents with Trusted outcomes, adaptable behavior, scalable deployment.


AI Agents Frameworks AI Agents