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coze studio

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Basic Information

Coze Studio is an open source, all-in-one AI agent development tool and visual platform designed for building, debugging, and deploying AI agents, apps, and workflows. The project provides core technologies required for agent development including prompt management, retrieval-augmented generation (RAG), plugins, workflow orchestration, and knowledge bases. It targets developers and teams by offering ready-to-use app templates, build frameworks, SDKs and OpenAPI endpoints so agents and workflows can be integrated into other systems. The codebase uses a Golang backend and a React+TypeScript frontend, follows a microservices architecture and domain-driven design, and is distributed under the Apache 2.0 license. The repository includes deployment guidance using Docker and Docker Compose, model configuration examples for services such as Volcengine and BytePlus, developer guides, API references, and community contribution guidance.

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15539
App URL
https://github.com/coze-dev/coze-studio
Github Repository
https://github.com/coze-dev/coze-studio/blob/main/README.md

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App Details

Features
Coze Studio groups features into modules covering model service management, agent and app building, workflow creation, and resource development. Model service features let you register and manage model providers and integrate services like OpenAI, Volcengine and BytePlus. Build features include creating, publishing and managing agents and apps, and configuring workflows and knowledge bases. Workflow features provide a visual canvas to create, modify, publish and delete workflows. Resource features support plugins, knowledge bases, databases and prompts. The platform exposes APIs and a Chat SDK for conversations and workflow invocation. The repository also provides templates and configuration examples, memory features for personalized responses, a plugin store model, and documentation covering deployment, model/plugin configuration and developer standards.
Use Cases
Coze Studio lowers the barrier to creating production AI agents by supplying an integrated set of tools and templates that accelerate development and deployment. Developers can reuse model configuration templates and app frameworks to avoid repetitive setup work. The visual workflow canvas and no-code/low-code capabilities enable rapid prototyping and debugging without building infrastructure from scratch. Built-in support for RAG, knowledge bases and plugins helps mitigate model hallucination and adds domain expertise. APIs and a Chat SDK enable integrating agents into external applications. Containerized deployment instructions and developer guides support reproducible setups and customization. Community docs, contribution guidelines and security notes help teams adopt, extend and operate the platform responsibly.

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