Best AI Agent Frameworks in Japan - Page 2

The Claude Agent SDK is a developer toolkit that enables the creation of autonomous AI agents powered by Claude, allowing them to perform real-world tasks beyond simple text generation by interacting directly with files, systems, and tools. It provides the same underlying infrastructure used by Claude Code, including an agent loop, context management, and built-in tool execution, and is available for use in Python and TypeScript. With this SDK, developers can build agents that read and write files, execute shell commands, search the web, edit code, and automate complex workflows without needing to implement these capabilities from scratch. It maintains persistent context and state across interactions, enabling agents to operate continuously, reason through multi-step problems, take actions, verify results, and iterate until tasks are completed.

Microsoft Agent Framework is an open source SDK and runtime designed to help developers build, orchestrate, and deploy AI agents and multi-agent workflows using languages such as .NET and Python. It combines the simple agent abstractions of AutoGen with the enterprise-grade capabilities of Semantic Kernel, including session-based state management, type safety, middleware, telemetry, and broad model and embedding support, creating a unified platform for both experimentation and production use. It introduces graph-based workflows that give developers explicit control over how multiple agents interact, execute tasks, and coordinate complex processes, enabling structured orchestration across sequential, concurrent, or branching scenarios. It supports long-running and human-in-the-loop workflows through robust state management, allowing agents to maintain context, reason through multi-step problems, and operate continuously over time.

AG-UI is an open, lightweight, event-based protocol that standardizes how AI agents connect to user-facing applications. Built for simplicity and flexibility, it enables seamless integration between AI agents, real-time user context, and user interfaces. AG-UI is designed for agent-human interaction: during agent executions, backends emit events compatible with standard AG-UI event types, and agent backends can accept simple AG-UI-compatible inputs as arguments. It works with any event transport, including SSE, WebSockets, webhooks, and other streaming systems, while providing a flexible middleware layer that ensures compatibility across diverse environments. AG-UI brings agents into user-facing applications and complements the wider agentic protocol stack: MCP gives agents tools, A2A allows agents to communicate with other agents, and AG-UI connects agents directly to the user interface.

assistant-ui is an open source React toolkit for production AI chat experiences, designed to bring the UX of ChatGPT into your own app. It helps developers create beautiful, enterprise-grade AI chat interfaces in minutes for React, React Native, and terminal applications. Whether you are building a ChatGPT clone, a customer support chatbot, an AI assistant, or a complex multi-agent application, assistant-ui provides frontend primitive components and state management layers so you can focus on what makes your application unique. It includes instant chat UI with pre-built, beautiful, customizable chat interfaces out of the box, making it easy to quickly iterate on an idea. Its chat state management is optimized for streaming responses, interruptions, retries, multi-turn conversations, and efficient rendering. assistant-ui is built for high performance, with optimized rendering and a minimal bundle size to keep AI chat interfaces responsive.

CopilotKit is an enterprise-grade agentic frontend stack designed to help developers build AI-powered applications with generative user interfaces. The platform enables seamless integration between user-facing applications and agentic backends through its AG-UI protocol, which supports bi-directional communication. It provides tools and SDKs for modern frameworks like React, Angular, and Next.js, allowing developers to quickly implement AI features. CopilotKit supports generative UI, enabling AI agents to dynamically render and update interface components in real time. The platform also includes features like chat components, conversation threading, and persistent state management for maintaining context across sessions. Developers can connect their preferred AI models, frameworks, and agents without being locked into a specific ecosystem.

AgentWorks is a comprehensive suite designed to enable autonomous AI agents to operate across enterprise boundaries, interact securely, and conduct transactions independently. It brings together core components including Agent ID, which provides identity, verification, authentication and authorization for AI agents; AgentRegistry, which supports registration, discovery and Know-Your-Agent (KYA) verification; AgentTalk, a patented protocol for secure agent-to-agent communication and transactions; AgentConnect, enabling agents to connect to websites, metaverses and digital ecosystems; AgentWallet, a wallet infrastructure where agents can store their Agent ID, digital assets and currencies (available both as a mobile wallet for human owners and an embedded wallet managed by agents themselves); and AgentWizard, a tool for assigning unique Agent IDs, registering agents and provisioning wallets. AgentWorks supports agent-to-agent transactions in real-world use cases.

OpenLegion is a production-grade AI agent framework and platform for building an AI workforce by describing the team you want. Tell OpenLegion “I want a marketing agency,” “I want a sales team,” or “I want a research desk,” and it deploys the agent stack with roles, budgets, permissions, and secure credential controls built in. Instead of stopping at chat, OpenLegion is designed for real workflows; agents can browse websites, fill out forms, write and run code, send emails and messages, manage files and folders, research and summarize, scrape data, qualify sales leads, process spreadsheets, post to social media, monitor for changes, and trigger workflows through Slack, Telegram, or Discord. Each agent runs in its own isolated container with per-agent budgets, tool permissions, persistent memory, MCP-compatible skills, and vault-secured credentials that agents never touch.

The Leading Conversational AI Platform for Enterprise Automation. Botpress is a flexible, fully on-premise conversational platform for enterprises to automate conversations & workflows. Our NLU technology significantly outperforms the competitors and leads to much higher levels of customer satisfaction. Built-in collaboration with large enterprises. Whether you are a Bank or the National Defence, we got you covered. Botpress has been battle-tested by thousands of developers. You can trust it's been proven to be flexible, secure and highly scalable. With Botpress, you won’t need to hire PhD’s for your conversational projects. Our job is to keep track of the latest state-of-the-art research papers in the various fields of NLP, NLU & NDU and to deliver that in a product that non-technical people can use seamlessly. It just works.

Experiment tracking, hyperparameter optimization, model and dataset versioning with Weights & Biases (WandB). Track, compare, and visualize ML experiments with 5 lines of code. Add a few lines to your script, and each time you train a new version of your model, you'll see a new experiment stream live to your dashboard. Optimize models with our massively scalable hyperparameter search tool. Sweeps are lightweight, fast to set up, and plug in to your existing infrastructure for running models. Save every detail of your end-to-end machine learning pipeline — data preparation, data versioning, training, and evaluation. It's never been easier to share project updates. Quickly and easily implement experiment logging by adding just a few lines to your script and start logging results. Our lightweight integration works with any Python script. W&B Weave is here to help developers build and iterate on their AI applications with confidence.

LlamaIndex is a “data framework” to help you build LLM apps. Connect semi-structured data from API's like Slack, Salesforce, Notion, etc. LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. LlamaIndex provides the key tools to augment your LLM applications with data. Connect your existing data sources and data formats (API's, PDF's, documents, SQL, etc.) to use with a large language model application. Store and index your data for different use cases. Integrate with downstream vector store and database providers. LlamaIndex provides a query interface that accepts any input prompt over your data and returns a knowledge-augmented response. Connect unstructured sources such as documents, raw text files, PDF's, videos, images, etc. Easily integrate structured data sources from Excel, SQL, etc. Provides ways to structure your data (indices, graphs) so that this data can be easily used with LLMs.

CrewAI is a leading multi-agent platform that enables organizations to streamline workflows across various industries by building and deploying automated processes using any Large Language Model (LLM) and cloud platform. It offers a comprehensive suite of tools, including a framework and UI Studio, to facilitate the rapid development of multi-agent automations, catering to both coding professionals and those seeking no-code solutions. The platform supports flexible deployment options, allowing users to move their created 'crews'—teams of AI agents—to production with confidence, utilizing powerful tools for different deployment types and autogenerated user interfaces. CrewAI also provides robust monitoring capabilities, enabling users to track the performance and progress of their AI agents on both simple and complex tasks. Additionally, it offers testing and training tools to continually enhance the efficiency and quality of outcomes produced by these AI agents.

Langflow is a low-code AI builder designed to create agentic and retrieval-augmented generation applications. It offers a visual interface that allows developers to construct complex AI workflows through drag-and-drop components, facilitating rapid experimentation and prototyping. The platform is Python-based and agnostic to any model, API, or database, enabling seamless integration with various tools and stacks. Langflow supports the development of intelligent chatbots, document analysis systems, and multi-agent applications. It provides features such as dynamic input variables, fine-tuning capabilities, and the ability to create custom components. Additionally, Langflow integrates with numerous services, including Cohere, Bing, Anthropic, HuggingFace, OpenAI, and Pinecone, among others. Developers can utilize pre-built components or code their own, enhancing flexibility in AI application development. The platform also offers a free cloud service for quick deployment and test

Smolagents is an AI agent framework developed to simplify the creation and deployment of intelligent agents with minimal code. It supports code-first agents where agents execute Python code snippets to perform tasks, offering enhanced efficiency compared to traditional JSON-based approaches. Smolagents integrates with large language models like those from Hugging Face, OpenAI, and others, enabling developers to create agents that can control workflows, call functions, and interact with external systems. The framework is designed to be user-friendly, requiring only a few lines of code to define and execute agents. It features secure execution environments, such as sandboxed spaces, for safe code running. Smolagents also promotes collaboration by integrating deeply with the Hugging Face Hub, allowing users to share and import tools. It supports a variety of use cases, from simple tasks to multi-agent workflows, offering flexibility and performance improvements.

​Oraczen is an AI-driven solution designed to help enterprises navigate complex systems by deploying agentic AI frameworks. These frameworks integrate seamlessly with existing infrastructures, facilitating tasks such as bridging data gaps, integrating legacy IT systems, and blending human-AI workflows. Oraczen emphasizes security with containerized environments that ensure data protection and compliance with industry standards. Its rapid deployment capabilities allow organizations to implement AI solutions within two weeks, enhancing operational efficiency across sectors like finance, supply chain, and healthcare. ​Oraczen fuses industry expertise and AI mastery with our Zen Platform to deploy AI agents that conquer enterprise complexity, bridging data gaps, integrating legacy IT, and blending human-AI design for seamless workflows in just 2 weeks.

​EdgeVerve AI Next is a unified, scalable platform designed to drive business transformations through powerful agentic AI, generative AI, responsible AI, and multi-cloud capabilities. Built from the ground up to leverage the power of generative AI, the AI Next platform bridges silos in people, processes, data, and technology to drive transformation in business operations. It features robust agent lifecycle management, accelerated agent development with intuitive no-code/low-code interfaces, flexible orchestration frameworks, and an extensive tool library. EdgeVerve AI Next's adaptable AI architecture supports multiple AI models and frameworks within a secure enterprise environment. With a unified enterprise control tower, organizations can monitor, manage, and govern operations with real-time analytics.

​TensorFlow Agents (TF-Agents) is a comprehensive library designed for reinforcement learning in TensorFlow. It simplifies the design, implementation, and testing of new RL algorithms by providing well-tested modular components that can be modified and extended. TF-Agents enables fast code iteration with good test integration and benchmarking. It includes a variety of agents such as DQN, PPO, REINFORCE, SAC, and TD3, each with their respective networks and policies. It also offers tools for building custom environments, policies, and networks, facilitating the creation of complex RL pipelines. TF-Agents supports both Python and TensorFlow environments, allowing for flexibility in development and deployment. It is compatible with TensorFlow 2.x and provides tutorials and guides to help users get started with training agents on standard environments like CartPole.

Upsonic is an open source framework that simplifies AI agent development for business needs. It enables developers to build, manage, and deploy agents with integrated Model Context Protocol (MCP) tools across cloud and local environments. Upsonic reduces engineering effort by 60-70% with built-in reliability features and service client architecture. It offers a client-server architecture that isolates agent applications, keeping existing systems healthy and stateless. It provides more reliable agents, scalability, and a task-oriented structure needed for completing real-world cases. Upsonic supports autonomous agent characterization, allowing self-defined goals and backgrounds, and integrates computer-use capabilities for executing human-like tasks. With direct LLM call support, developers can access models without abstraction layers, completing agent tasks faster and more cost-effectively.

PayOS is a payment infrastructure platform built specifically for the “agentic” economy, where AI agents and autonomous workflows complete commerce tasks. The system is designed as a card-native solution that enables developers and businesses to embed checkout, billing, and money movement into agentic workflows, supporting all major card networks and offering processor flexibility. It allows a card to be linked once and then used across agent-driven scenarios, while still providing human-in-the-loop controls, strong security (PCI-compliant), and full global network access. PayOS enables both push and pull payments, recurring billing, and autonomous money flows without the need for merchant re-integration. It supports tokenization and collaborations with networks like Mastercard and Visa Intelligent Commerce to open up agentic payment use cases at scale.

The UCP and AP2 documentation describes how the Universal Commerce Protocol (UCP) integrates with the Agent Payments Protocol (AP2) to support secure, verifiable transactions initiated by AI agents or platforms on behalf of users, making it possible for commerce systems to handle discovery, checkout, and payment without intermediaries. UCP is fully compatible with AP2, which acts as the trust layer for agent-led transactions by requiring a secure, cryptographically verifiable exchange of intent and authorization between platforms and businesses using Verifiable Digital Credentials (VDCs); this ensures businesses receive signed checkout commitments that can’t be altered mid-flow and platforms issue proofs of payment authorization tied specifically to a cart state, reducing fraud and making transactions final and authentic.

CAMEL-AI is the first LLM-based multi-agent framework and an open-source community dedicated to exploring the scaling laws of agents. It enables the creation of customizable agents using modular components tailored for specific tasks, facilitating the development of multi-agent systems that address challenges in autonomous cooperation. The framework serves as a generic infrastructure for various applications, including task automation, data generation, and world simulations. By studying agents on a large scale, CAMEL-AI.org aims to gain valuable insights into their behaviors, capabilities, and potential risks. The community emphasizes rigorous research, balancing urgency with patience, and encourages contributions that enhance infrastructure, improve documentation, and implement research ideas. The platform offers components such as models, tools, memory, and prompts to empower agents, and supports integrations with various external tools and services.