Best AI tools for< Build Agents >

SmythOS is an AI-powered platform that allows users to create and deploy AI agents in minutes. With a user-friendly interface and drag-and-drop functionality, SmythOS enables users to build custom agents for various tasks without the need for manual coding. The platform offers pre-built agent templates, universal integration with AI models and APIs, and the flexibility to deploy agents locally or to the cloud. SmythOS is designed to streamline workflow automation, enhance productivity, and provide a seamless experience for developers and businesses looking to leverage AI technology.

LLMStack is an open-source platform that allows users to build AI Agents, workflows, and applications using their own data. It is a no-code AI app builder that supports model chaining from major providers like OpenAI, Cohere, Stability AI, and Hugging Face. Users can import various data sources such as Web URLs, PDFs, audio files, and more to enhance generative AI applications and chatbots. With a focus on collaboration, LLMStack enables users to share apps publicly or restrict access, with viewer and collaborator roles for multiple users to work together. Powered by React, LLMStack provides an easy-to-use interface for building AI applications.

Voiceflow is a powerful, flexible, and collaborative platform for building AI automation. It allows teams of any size to build agents of any scale and complexity, easily. Voiceflow's visual workflow builder is used by developers and designers to collaboratively create, iterate, and ship complex agents. Voiceflow also offers a central CMS for managing all of your agent content, including variables, intents, entities, and knowledge base sources. With Voiceflow, you can integrate with any API or service, share and test prototypes, and launch agents to any interface.

ElizaOS is a TypeScript framework designed for building autonomous AI agents that can think, learn, and act independently. It offers a wide range of capabilities, including developing unique personalities, interacting with the real world through various plugins, executing complex action chains triggered by natural language, and remembering interactions with persistent memory. The framework comes with a rich plugin ecosystem, allowing users to mix and match capabilities without modifying core code. ElizaOS is ideal for builders who want to quickly ship projects, experiment freely, and contribute to the open-source community.

AgentForge is a powerful AI application that simplifies the creation and customization of AI agents. It offers a comprehensive toolkit with pre-built agents, customizable graphs, and reusable UI components. The platform allows users to effortlessly build and customize AI agents, reducing the complexity and cost associated with developing AI solutions from scratch. With seamless integration with popular AI tools and platforms, AgentForge empowers businesses to unlock the full potential of AI technology.

Wordware is an AI toolkit that empowers cross-functional teams to build reliable high-quality agents through rapid iteration. It combines the best aspects of software with the power of natural language, freeing users from traditional no-code tool constraints. With advanced technical capabilities, multiple LLM providers, one-click API deployment, and multimodal support, Wordware offers a seamless experience for AI app development and deployment.

crewAI is a platform for Multi AI Agents Systems that offers a user-friendly framework for automating workflows with AI agents. It simplifies the process of building and deploying multi-agent automations, providing support for various AI models and templates. With a focus on privacy and security, crewAI ensures that each agent runs in isolated environments. The platform is suitable for enterprises and developers looking to leverage AI technologies effectively.

Lazy AI is an AI tool that enables users to quickly build and modify web apps with prompts and deploy them to the cloud with just one click. Users can create various applications such as customer portals, API endpoints for AI text summarization, metrics dashboards, web scrapers, chatbots, and discord bots. The platform offers a wide range of template categories and tools for automation, data mining, AI agents, dashboards, reporting, and more. Users can also access reusable templates from the Lazy AI community to streamline their development process.

Lyzr AI is a full-stack agent framework designed to build GenAI applications faster. It offers a range of AI agents for various tasks such as chatbots, knowledge search, summarization, content generation, and data analysis. The platform provides features like memory management, human-in-loop interaction, toxicity control, reinforcement learning, and custom RAG prompts. Lyzr AI ensures data privacy by running data locally on cloud servers. Enterprises and developers can easily configure, deploy, and manage AI agents using Lyzr's platform.

Runday is a business-to-business software as a service (SaaS) company that provides artificial intelligence (AI)-powered agents to help businesses with sales, service, marketing, and recruiting. Runday's AI agents can be used to answer customer questions, book appointments, collect payments, and more. The company's software is used by over 30,000 businesses and has generated over $1 billion in sales for its customers.

TestArmy is an AI-driven software testing platform that offers an army of testing agents to help users achieve software quality by balancing cost, speed, and quality. The platform leverages AI agents to generate Gherkin tests based on user specifications, automate test execution, and provide detailed logs and suggestions for test maintenance. TestArmy is designed for rapid scaling and adaptability to changes in the codebase, making it a valuable tool for both technical and non-technical users.

Composio is an integration platform for AI Agents and LLMs that allows users to access over 150 tools with just one line of code. It offers seamless integrations, managed authentication, a repository of tools, and powerful RPA tools to streamline and optimize the connection and interaction between AI Agents/LLMs and various APIs/services. Composio simplifies JSON structures, improves variable names, and enhances error handling to increase reliability by 30%. The platform is SOC Type II compliant, ensuring maximum security of user data.

Ardor is an AI tool that offers an all-in agentic software development lifecycle automation platform. It helps users build, deploy, and scale AI agents on the cloud efficiently and cost-effectively. With Ardor, users can start with a prompt, design AI agents visually, see their product get built, refine and iterate, and launch in minutes. The platform provides real-time collaboration features, simple pricing plans, and various tools like Ardor Copilot, AI Agent-Builder Canvas, Instant Build Messages, AI Debugger, Proactive Monitoring, Role-Based Access Control, and Single Sign-On.

Google Cloud is a suite of cloud computing services that runs on the same infrastructure as Google. Its services include computing, storage, networking, databases, machine learning, and more. Google Cloud is designed to make it easy for businesses to develop and deploy applications in the cloud. It offers a variety of tools and services to help businesses with everything from building and deploying applications to managing their infrastructure. Google Cloud is also committed to sustainability, and it has a number of programs in place to reduce its environmental impact.

Locale is an AI-powered platform that enables businesses to automate their business processes using AI agents. It allows users to build AI workflows for various business functions such as marketing, sales, payments, and operations. With features like AI workflow builder, drag-and-drop and SQL builders, and integrations with popular tools like Slack and Zendesk, Locale helps in streamlining processes and increasing team productivity. The platform offers advanced features like AI Copilot, drag-&-drop Workflow Builder, SQL for complex Use Cases, and Human-in-the-loop Steps to enhance automation capabilities. Locale has been successfully used by companies to optimize workflows, reduce manual effort, and improve operational efficiency.

Momen is a platform that allows users to build web applications without the need for coding. From designing to developing and scaling apps, Momen offers a smooth learning curve for users to create custom apps. The platform provides features such as dynamic canvas, live preview, interactive animations, and reusable components. With Momen, users can clarify user journeys, unleash their creativity, and build feature-rich apps with ease. The platform also ensures predictable costs, assured scalability, and advanced collaboration workflows for million-user projects. Momen AI 2.0 enables users to build AI agents. Additionally, Momen offers SEO controls, AI app development, exclusive programs for education, tailored solutions for content creators, and various resources and support options.

Retell AI is a powerful voice agent platform that enables users to build, test, deploy, and monitor AI voice agents at scale. It offers features such as call transfer, appointment booking, IVR navigation, batch calling, and post-call analysis. Retell AI provides advantages like verified phone numbers, branded call ID, custom analysis, and case studies. However, some disadvantages include the need for initial setup by an engineer, ongoing maintenance, and potential concurrent call limitations. The application is suitable for various industries and use cases, with multilingual support and compliance with industry standards.

Picovoice is an on-device Voice AI and local LLM platform designed for enterprises. It offers a range of voice AI and LLM solutions, including speech-to-text, noise suppression, speaker recognition, speech-to-index, wake word detection, and more. Picovoice empowers developers to build virtual assistants and AI-powered products with compliance, reliability, and scalability in mind. The platform allows enterprises to process data locally without relying on third-party remote servers, ensuring data privacy and security. With a focus on cutting-edge AI technology, Picovoice enables users to stay ahead of the curve and adapt quickly to changing customer needs.

Lazy AI is a platform that enables users to build full stack web applications 10 times faster by utilizing AI technology. Users can create and modify web apps with prompts and deploy them to the cloud with just one click. The platform offers a variety of features including AI Component Builder, eCommerce store creation, Crypto Arbitrage Scraper, Text to Speech Converter, Lazy Image to Video generation, PDF Chatbot, and more. Lazy AI aims to streamline the app development process and empower users to leverage AI for various tasks.

ReliveAI is a no-code AI platform that simplifies building AI-powered workflows and agents, enabling rapid business process automation with a user-friendly interface. It offers prebuilt AI Agents to transform business operations, customizable AI workflows tailored to user data, and seamless integration with multiple AI models and APIs. The platform enhances Salesforce with advanced NLP, translates natural language into precise SQL queries, and provides automation for Airtable, Gmail, Notion, Slack, and Google Drive. ReliveAI aims to optimize processes, improve decision-making, and unlock the full potential of user data.

OpenAGI is an AI agent creation package designed for researchers and developers to create intelligent agents using advanced machine learning techniques. The package provides tools and resources for building and training AI models, enabling users to develop sophisticated AI applications. With a focus on collaboration and community engagement, OpenAGI aims to facilitate the integration of AI technologies into various domains, fostering innovation and knowledge sharing among experts and enthusiasts.

GPTSwarm is a graph-based framework for LLM-based agents that enables the creation of LLM-based agents from graphs and facilitates the customized and automatic self-organization of agent swarms with self-improvement capabilities. The library includes components for domain-specific operations, graph-related functions, LLM backend selection, memory management, and optimization algorithms to enhance agent performance and swarm efficiency. Users can quickly run predefined swarms or utilize tools like the file analyzer. GPTSwarm supports local LM inference via LM Studio, allowing users to run with a local LLM model. The framework has been accepted by ICML2024 and offers advanced features for experimentation and customization.

AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. It is compatible with a range of LLM models and offers flexibility to run different models for different agents based on specific needs. The framework is designed for seamless extensibility and database-flexibility, making it an ideal playground for various AI projects. AgentForge is a beta-testing ground and future-proof hub for crafting intelligent, model-agnostic autonomous agents.

Atomic Agents is a modular and extensible framework designed for creating powerful applications. It follows the principles of Atomic Design, emphasizing small and single-purpose components. Leveraging Pydantic for data validation and serialization, the framework offers a set of tools and agents that can be combined to build AI applications. It depends on the Instructor package and supports various APIs like OpenAI, Cohere, Anthropic, and Gemini. Atomic Agents is suitable for developers looking to create AI agents with a focus on modularity and flexibility.

LongRoPE is a method to extend the context window of large language models (LLMs) beyond 2 million tokens. It identifies and exploits non-uniformities in positional embeddings to enable 8x context extension without fine-tuning. The method utilizes a progressive extension strategy with 256k fine-tuning to reach a 2048k context. It adjusts embeddings for shorter contexts to maintain performance within the original window size. LongRoPE has been shown to be effective in maintaining performance across various tasks from 4k to 2048k context lengths.

Ax is a Typescript library that allows users to build intelligent agents inspired by agentic workflows and the Stanford DSP paper. It seamlessly integrates with multiple Large Language Models (LLMs) and VectorDBs to create RAG pipelines or collaborative agents capable of solving complex problems. The library offers advanced features such as streaming validation, multi-modal DSP, and automatic prompt tuning using optimizers. Users can easily convert documents of any format to text, perform smart chunking, embedding, and querying, and ensure output validation while streaming. Ax is production-ready, written in Typescript, and has zero dependencies.

Awesome-AI-Agents is a curated list of projects, frameworks, benchmarks, platforms, and related resources focused on autonomous AI agents powered by Large Language Models (LLMs). The repository showcases a wide range of applications, multi-agent task solver projects, agent society simulations, and advanced components for building and customizing AI agents. It also includes frameworks for orchestrating role-playing, evaluating LLM-as-Agent performance, and connecting LLMs with real-world applications through platforms and APIs. Additionally, the repository features surveys, paper lists, and blogs related to LLM-based autonomous agents, making it a valuable resource for researchers, developers, and enthusiasts in the field of AI.

CodeFuse-muAgent is a Multi-Agent framework designed to streamline Standard Operating Procedure (SOP) orchestration for agents. It integrates toolkits, code libraries, knowledge bases, and sandbox environments for rapid construction of complex Multi-Agent interactive applications. The framework enables efficient execution and handling of multi-layered and multi-dimensional tasks.

CRAB is a framework for building LLM agent benchmark environments in a Python-centric way. It is cross-platform and multi-environment, allowing the creation of agent environments supporting various deployment options. The framework offers easy-to-use configuration with the ability to add new actions and define environments seamlessly. CRAB also provides a novel benchmarking suite with tasks and evaluators defined in Python, along with a unique graph evaluator method for detailed metrics.

AgentGenesis is an open-source web app that provides customizable Gen AI code snippets for building custom RAG flows and AI agents. Users can easily copy and paste components into their applications, modify the code as needed, and build on top of it. The tool aims to simplify the development process by offering pre-built code snippets that can be integrated seamlessly into projects without the need for npm installation. AgentGenesis encourages contributions, positive feedback, and support from the community to enhance and grow the project.

LangChain-Udemy-Course is a comprehensive course directory focusing on LangChain, a framework for generative AI applications. The course covers various aspects such as OpenAI API usage, prompt templates, Chains exploration, callback functions, memory techniques, RAG implementation, autonomous agents, hybrid search, LangSmith utilization, microservice architecture, and LangChain Expression Language. Learners gain theoretical knowledge and practical insights to understand and apply LangChain effectively in generative AI scenarios.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

The Live Agent Studio is a community-driven platform developed by oTTomator for exploring cutting-edge AI agents and learning how to implement them. It aims to provide practical value and serve as an educational platform for users to do incredible things with AI. The repository contains the source code/workflow JSON for all the agents on the Live Agent Studio, fostering a curated collection of cutting-edge agents and enabling learning from one another. Users can start using agents free of charge with initial tokens provided upon sign-in, and additional tokens can be purchased. The platform plans to feature new AI technologies, groundbreaking agent research, and tools/libraries for building agents, aiming to become the go-to place for AI agent innovation.

agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on multi-agent collaborative patterns, integrating domain experience to help agents solve problems in various fields. The framework includes pattern components like PEER and DOE for event interpretation, industry analysis, and financial report generation. It offers features for agent construction, multi-agent collaboration, and domain expertise integration, aiming to create intelligent applications with professional know-how.

OmAgent is an open-source agent framework designed to streamline the development of on-device multimodal agents. It enables agents to empower various hardware devices, integrates speed-optimized SOTA multimodal models, provides SOTA multimodal agent algorithms, and focuses on optimizing the end-to-end computing pipeline for real-time user interaction experience. Key features include easy connection to diverse devices, scalability, flexibility, and workflow orchestration. The architecture emphasizes graph-based workflow orchestration, native multimodality, and device-centricity, allowing developers to create bespoke intelligent agent programs.

Lecca.io is an AI platform that enables users to configure and deploy Large Language Models (LLMs) with customizable tools and workflows. Users can easily build, customize, and automate AI agents for various tasks. The platform offers features like custom LLM configuration, tool integration, workflow builder, built-in RAG functionalities, and the ability to create custom apps and triggers. Users can also automate LLMs by setting up triggers for autonomous operation. Lecca.io provides documentation for concepts, local development, creating custom apps, adding AI providers, and running Ollama locally. Contributions are welcome, and the platform is distributed under the Apache-2.0 License with Commons Clause, with enterprise features available under a Commercial License.

Synthora is a lightweight and extensible framework for LLM-driven Agents and ALM research. It aims to simplify the process of building, testing, and evaluating agents by providing essential components. The framework allows for easy agent assembly with a single config, reducing the effort required for tuning and sharing agents. Although in early development stages with unstable APIs, Synthora welcomes feedback and contributions to enhance its stability and functionality.

TapeAgents is a framework that leverages a structured, replayable log of the agent session to facilitate all stages of the LLM Agent development lifecycle. The agent reasons by processing the tape and the LLM output to produce new thoughts, actions, control flow steps, and append them to the tape. Key features include building agents as low-level state machines or high-level multi-agent team configurations, debugging agents with TapeAgent studio or TapeBrowser apps, serving agents with response streaming, and optimizing agent configurations using successful tapes. The Tape-centric design of TapeAgents provides ultimate flexibility in project development, allowing access to tapes for making prompts, generating next steps, and controlling agent behavior.

Obot is an open source AI agent platform that allows users to build agents for various use cases such as copilots, assistants, and autonomous workflows. It offers integration with leading LLM providers, built-in RAG for data, easy integration with custom web services and APIs, and OAuth 2.0 authentication.

The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The recipes provide examples on how to chain multiple LLM calls, create agents that route tasks to specialized models, run multiple LLMs in parallel, break down tasks into parallel subtasks, build agents that iteratively improve responses, perform LoRA fine-tuning and inference, fine-tune LLMs for repetition, improve summarization capabilities, fine-tune LLMs on multi-step conversations, implement retrieval-augmented generation, conduct multimodal search and conditional image generation, visualize vector embeddings, improve search results with rerankers, implement vector search with embedding models, extract structured text from images, summarize and evaluate outputs with LLMs, generate podcasts from PDF content, and get LLMs to generate knowledge graphs.

Anda is an AI agent framework built with Rust, integrating ICP blockchain and TEE support. It aims to create a network of highly composable, autonomous AI agents across industries to advance artificial intelligence. Key features include composability, simplicity, trustworthiness, autonomy, and perpetual memory. Anda's vision is to build a collaborative network of agents leading to a super AGI system, revolutionizing AI technology applications and creating value for society.

Agno is a lightweight library for building multi-modal Agents. It is designed with core principles of simplicity, uncompromising performance, and agnosticism, allowing users to create blazing fast agents with minimal memory footprint. Agno supports any model, any provider, and any modality, making it a versatile container for AGI. Users can build agents with lightning-fast agent creation, model agnostic capabilities, native support for text, image, audio, and video inputs and outputs, memory management, knowledge stores, structured outputs, and real-time monitoring. The library enables users to create autonomous programs that use language models to solve problems, improve responses, and achieve tasks with varying levels of agency and autonomy.

Pocket Flow is a 100-line minimalist LLM framework designed for (Multi-)Agents, Workflow, RAG, etc. It provides a core abstraction for LLM projects by focusing on computation and communication through a graph structure and shared store. The framework aims to support the development of LLM Agents, such as Cursor AI, by offering a minimal and low-level approach that is well-suited for understanding and usage. Users can install Pocket Flow via pip or by copying the source code, and detailed documentation is available on the project website.

Jido is a toolkit for building autonomous, distributed agent systems in Elixir. It provides the foundation for creating smart, composable workflows that can evolve and respond to their environment. Geared towards Agent builders, it contains core state primitives, composable actions, agent data structures, real-time sensors, signal system, skills, and testing tools. Jido is designed for multi-node Elixir clusters and offers rich helpers for unit and property-based testing.

Cloudflare Agents is a framework for building intelligent, stateful agents that persist, think, and evolve at the edge of the network. It allows for maintaining persistent state and memory, real-time communication, processing and learning from interactions, autonomous operation at global scale, and hibernating when idle. The project is actively evolving with focus on core agent framework, WebSocket communication, HTTP endpoints, React integration, and basic AI chat capabilities. Future developments include advanced memory systems, WebRTC for audio/video, email integration, evaluation framework, enhanced observability, and self-hosting guide.

Archon is an AI meta-agent designed to autonomously build, refine, and optimize other AI agents. It serves as a practical tool for developers and an educational framework showcasing the evolution of agentic systems. Through iterative development, Archon demonstrates the power of planning, feedback loops, and domain-specific knowledge in creating robust AI agents.

The OpenAI Agents SDK is a lightweight framework for building multi-agent workflows. It includes concepts like Agents, Handoffs, Guardrails, and Tracing to facilitate the creation and management of agents. The SDK is compatible with any model providers supporting the OpenAI Chat Completions API format. It offers flexibility in modeling various LLM workflows and provides automatic tracing for easy tracking and debugging of agent behavior. The SDK is designed for developers to create deterministic flows, iterative loops, and more complex workflows.

mcp-agent is a simple, composable framework designed to build agents using the Model Context Protocol. It handles the lifecycle of MCP server connections and implements patterns for building production-ready AI agents in a composable way. The framework also includes OpenAI's Swarm pattern for multi-agent orchestration in a model-agnostic manner, making it the simplest way to build robust agent applications. It is purpose-built for the shared protocol MCP, lightweight, and closer to an agent pattern library than a framework. mcp-agent allows developers to focus on the core business logic of their AI applications by handling mechanics such as server connections, working with LLMs, and supporting external signals like human input.

Giselle is an open source AI tool designed for agentic workflows, facilitating seamless collaboration between humans and AI. It offers cloud hosting with free agent time, self-hosting options, and a Vibe Cording Guide for using AI coding assistants. Giselle is suitable for developers and non-engineers alike, empowering users to leverage AI capabilities without extensive coding knowledge. The tool is actively developed, with a roadmap in progress, and welcomes contributions from the community under the Apache License Version 2.0.

Koog is a Kotlin-based framework for building and running AI agents entirely in idiomatic Kotlin. It allows users to create agents that interact with tools, handle complex workflows, and communicate with users. Key features include pure Kotlin implementation, MCP integration, embedding capabilities, custom tool creation, ready-to-use components, intelligent history compression, powerful streaming API, persistent agent memory, comprehensive tracing, flexible graph workflows, modular feature system, scalable architecture, and multiplatform support.

Strands Agents is a lightweight and flexible SDK that takes a model-driven approach to building and running AI agents. It supports various model providers, offers advanced capabilities like multi-agent systems and streaming support, and comes with built-in MCP server support. Users can easily create tools using Python decorators, integrate MCP servers seamlessly, and leverage multiple model providers for different AI tasks. The SDK is designed to scale from simple conversational assistants to complex autonomous workflows, making it suitable for a wide range of AI development needs.

Symfony AI is a set of components that integrate AI capabilities into PHP applications. It consists of various components and bundles such as Platform, Agent, Store, MCP SDK, AI Bundle, and MCP Bundle. Users can leverage these components to interact with AI platforms, build AI agents, store data for AI applications, and enable communication between AI agents and tools. Symfony AI provides examples and a demo application for users to get started. The repository also includes fixture licenses for testing multi-modal features with binary media content.

This repository contains the documentation for the Strands Agents SDK, a simple yet powerful framework for building and running AI agents. The documentation is built using MkDocs and provides guides, examples, and API references. The official documentation is available online at: https://strandsagents.com.

Agent Development Kit (ADK) for Java is an open-source toolkit designed for developers to build, evaluate, and deploy sophisticated AI agents with flexibility and control. It allows defining agent behavior, orchestration, and tool use directly in code, enabling robust debugging, versioning, and deployment anywhere. The toolkit offers a rich tool ecosystem, code-first development approach, and support for modular multi-agent systems, making it ideal for creating advanced AI agents integrated with Google Cloud services.

SmythOS is an operating system designed for building, deploying, and managing intelligent AI agents at scale. It provides a unified SDK and resource abstraction layer for various AI services, making it easy to scale and flexible. With an agent-first design, developer-friendly SDK, modular architecture, and enterprise security features, SmythOS offers a robust foundation for AI workloads. The system is built with a philosophy inspired by traditional operating system kernels, ensuring autonomy, control, and security for AI agents. SmythOS aims to make shipping production-ready AI agents accessible and open for everyone in the coming Internet of Agents era.

Agentic ADK is an Agent application development framework launched by Alibaba International AI Business, based on Google-ADK and Ali-LangEngine. It is used for developing, constructing, evaluating, and deploying powerful, flexible, and controllable complex AI Agents. ADK aims to make Agent development simpler and more user-friendly, enabling developers to more easily build, deploy, and orchestrate various Agent applications ranging from simple tasks to complex collaborations.

AgentFly is an extensible framework for building LLM agents with reinforcement learning. It supports multi-turn training by adapting traditional RL methods with token-level masking. It features a decorator-based interface for defining tools and reward functions, enabling seamless extension and ease of use. To support high-throughput training, it implemented asynchronous execution of tool calls and reward computations, and designed a centralized resource management system for scalable environment coordination. A suite of prebuilt tools and environments are provided.

Agent Development Kit (ADK) is an open-source, code-first toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. It is a flexible and modular framework optimized for Gemini and the Google ecosystem, model-agnostic, deployment-agnostic, and compatible with other frameworks. ADK simplifies agent development by making it feel more like software development, enabling developers to create, deploy, and orchestrate agentic architectures from simple tasks to complex workflows.

ADK-TS is a comprehensive TypeScript framework for building sophisticated AI agents with multi-LLM support, advanced tools, and flexible conversation flows. It is production-ready and enables developers to create intelligent, autonomous systems that can handle complex multi-step tasks. The framework provides features such as multi-provider LLM support, extensible tool system, advanced agent reasoning, real-time streaming, flexible authentication, persistent memory systems, multi-agent orchestration, built-in telemetry, and prebuilt MCP servers for easy deployment and management of agents.

AgentScope is an agent-oriented programming tool for building LLM (Large Language Model) applications. It provides transparent development, realtime steering, agentic tools management, model agnostic programming, LEGO-style agent building, multi-agent support, and high customizability. The tool supports async invocation, reasoning models, streaming returns, async/sync tool functions, user interruption, group-wise tools management, streamable transport, stateful/stateless mode MCP client, distributed and parallel evaluation, multi-agent conversation management, and fine-grained MCP control. AgentScope Studio enables tracing and visualization of agent applications. The tool is highly customizable and encourages customization at various levels.

AgentUp is an active development tool that provides a developer-first agent framework for creating AI agents with enterprise-grade infrastructure. It allows developers to define agents with configuration, ensuring consistent behavior across environments. The tool offers secure design, configuration-driven architecture, extensible ecosystem for customizations, agent-to-agent discovery, asynchronous task architecture, deterministic routing, and MCP support. It supports multiple agent types like reactive agents and iterative agents, making it suitable for chatbots, interactive applications, research tasks, and more. AgentUp is built by experienced engineers from top tech companies and is designed to make AI agents production-ready, secure, and reliable.

Agent Development Kit (ADK) is an open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. It is a flexible and modular framework optimized for Gemini and the Google ecosystem, but also compatible with other frameworks. ADK aims to make agent development feel more like software development, enabling developers to create, deploy, and orchestrate agentic architectures ranging from simple tasks to complex workflows.

The Agent Payments Protocol (AP2) repository contains code samples and demos showcasing the protocol. It includes curated scenarios demonstrating key components, utilizing the Agent Development Kit (ADK) and Gemini 2.5 Flash. Users are free to use any tools to build agents. The repository features various agents and servers, with source code located in specific directories. Users can run scenarios by following README instructions and using run scripts. Additionally, the repository provides guidance on setting up prerequisites, obtaining a Google API key, and installing the AP2 types package.

The AI Agent Service Toolkit is a comprehensive toolkit designed for running an AI agent service using LangGraph, FastAPI, and Streamlit. It includes a LangGraph agent, a FastAPI service, a client for interacting with the service, and a Streamlit app for providing a chat interface. The project offers a template for building and running agents with the LangGraph framework, showcasing a complete setup from agent definition to user interface. Key features include LangGraph Agent with latest features, FastAPI Service, Advanced Streaming support, Streamlit Interface, Multiple Agent Support, Asynchronous Design, Content Moderation, RAG Agent implementation, Feedback Mechanism, Docker Support, and Testing. The repository structure includes directories for defining agents, protocol schema, core modules, service, client, Streamlit app, and tests.

Rowboat is a tool that allows users to build AI agents instantly with natural language, connect tools with one-click integrations, power workflows with knowledge by adding documents for RAG, automate workflows by setting up triggers and actions, and deploy anywhere via API or SDK. Users can access a hosted version to start building agents right away. The tool provides features such as native RAG support, custom LLM providers, tools & triggers for automation, and API & SDK integration. Users can refer to the documentation to learn how to start building agents with Rowboat.

Apache Flink Agents is an Agentic AI framework based on Apache Flink. It provides a platform for building and deploying AI agents using Flink's capabilities. The framework supports both Java and Python development, allowing users to leverage the power of Flink for AI applications. With a focus on agent-based AI systems, Flink Agents offers a flexible and scalable solution for developing intelligent agents that can interact with their environment and make decisions autonomously. The framework includes tools for building, training, and deploying AI agents, making it suitable for a wide range of AI applications.

Agents Towards Production is an open-source playbook for building production-ready GenAI agents that scale from prototype to enterprise. Tutorials cover stateful workflows, vector memory, real-time web search APIs, Docker deployment, FastAPI endpoints, security guardrails, GPU scaling, browser automation, fine-tuning, multi-agent coordination, observability, evaluation, and UI development.

This repository contains code for O'Reilly Live Online Training for AI Agents A-Z and Modern Automated AI Agents video series. It provides a guide to understanding, implementing, and managing AI agents, covering frameworks like CrewAI, LangChain, and AutoGen. Participants learn to build agents from scratch using prompt engineering techniques, deploy AI agents, evaluate performance, and make informed decisions in AI projects.

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