[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-72090":3},{"id":4,"name":5,"fullName":6,"owner":5,"repo":5,"description":7,"homepage":8,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":16,"stars30d":17,"stars90d":15,"forks30d":15,"starsTrendScore":15,"compositeScore":18,"rankGlobal":9,"rankLanguage":9,"license":19,"archived":20,"fork":20,"defaultBranch":21,"hasWiki":22,"hasPages":20,"topics":23,"createdAt":9,"pushedAt":9,"updatedAt":35,"readmeContent":36,"aiSummary":37,"trendingCount":15,"starSnapshotCount":15,"syncStatus":38,"lastSyncTime":39,"discoverSource":40},72090,"TaskingAI","TaskingAI\u002FTaskingAI","The open source platform for AI-native application development.","https:\u002F\u002Fwww.tasking.ai",null,"Python",5381,358,54,30,0,4,7,38.67,"Apache License 2.0",false,"master",true,[24,25,26,27,28,29,30,31,32,33,34],"agent","ai","ai-native","function-call","generative-ai","gpt","langchain","llm","rag","retrieval-augmented-generation","vector","2026-06-12 02:02:58","\u003Cp>\n\u003Ca href=\"https:\u002F\u002Fwww.tasking.ai\">\u003Cimg src=\"static\u002Fimg\u002Flogo.png\" alt=\"https:\u002F\u002Fwww.tasking.ai\">\u003C\u002Fa>\n\u003C\u002Fp>\n\n# TaskingAI\n\n\u003Cp align=\"center\">\n  \u003Ca href=\"https:\u002F\u002Fhub.docker.com\u002Fu\u002Ftaskingai\">\u003Cimg alt=\"Docker Image Version (latest semver)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fdocker\u002Fv\u002Ftaskingai\u002Ftaskingai-server?label=docker\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fgithub.com\u002FTaskingAI\u002FTaskingAI\u002Fblob\u002Fmaster\u002FLICENSE\">\u003Cimg alt=\"GitHub License\" src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Flicense\u002Ftaskingai\u002Ftaskingai\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fpypi.org\u002Fproject\u002Ftaskingai\">\u003Cimg alt=\"PyPI version\" src=\"https:\u002F\u002Fimg.shields.io\u002Fpypi\u002Fv\u002Ftaskingai?color=blue\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Ftwitter.com\u002FTaskingAI\">\u003Cimg alt=\"X (formerly Twitter) URL\" src=\"https:\u002F\u002Fimg.shields.io\u002Ftwitter\u002Furl?url=https%3A%2F%2Ftwitter.com%2FTaskingAI\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fwww.youtube.com\u002F@TaskingAI\">\u003Cimg alt=\"YouTube Channel Subscribers\" src=\"https:\u002F\u002Fimg.shields.io\u002Fyoutube\u002Fchannel\u002Fsubscribers\u002FUCxUnOM-ZbZKmyR_Q5vAUSTA\">\u003C\u002Fa>\n  \u003Ca href=\"https:\u002F\u002Fdiscord.gg\u002FRqwcD3vG3k\">\u003Cimg alt=\"Docs\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDiscord-join-brightgreen\">\u003C\u002Fa>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\n  \u003Ca href=\".\u002FREADME.md\">\u003Cimg alt=\"Readme (English)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEnglish-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.de.md\">\u003Cimg alt=\"Readme (Deutsch)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDeutsch-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.fr.md\">\u003Cimg alt=\"Readme (Français)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FFrançais-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.es.md\">\u003Cimg alt=\"Readme (Español)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FEspañol-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.pt.md\">\u003Cimg alt=\"Readme (Português)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPortuguês-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.zh-cn.md\">\u003Cimg alt=\"Readme (简体中文)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F简体中文-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.zh-tw.md\">\u003Cimg alt=\"Readme (繁體中文)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F繁體中文-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.jp.md\">\u003Cimg alt=\"Readme (日本語)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F日本語-2EA26A\">\u003C\u002Fa>\n  \u003Ca href=\".\u002Fi18n\u002FREADME.kr.md\">\u003Cimg alt=\"Readme (한국어)\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F한국어-2EA26A\">\u003C\u002Fa>\n\u003C\u002Fp>\n\n[TaskingAI](https:\u002F\u002Fwww.tasking.ai) is a BaaS (Backend as a Service) platform for **LLM-based Agent Development and Deployment**. It unified the integration of hundreds of LLM models, and provides an intuitive user interface for managing your LLM application's functional modules, including tools, RAG systems, assistants, conversation history, and more.\n\n### Key Features\n\n1. **All-In-One LLM Platform**: Access hundreds of AI models with unified APIs.\n2. **Abundant enhancement**: Enhance LLM agent performance with hundreds of customizable built-in **tools** and advanced **Retrieval-Augmented Generation** (RAG) system\n3. **BaaS-Inspired Workflow**: Separate AI logic (server-side) from product development (client-side), offering a clear pathway from console-based prototyping to scalable solutions using RESTful APIs and client SDKs.\n4. **One-Click to Production**: Deploy your AI agents with a single click to production stage, and scale them with ease. Let TaskingAI handle the rest.\n5. **Asynchronous Efficiency**: Harness Python FastAPI's asynchronous features for high-performance, concurrent computation, enhancing the responsiveness and scalability of the applications.\n6. **Intuitive UI Console**: Simplifies project management and allows in-console workflow testing.\n\n\u003Cp>\n\u003Cimg src=\"static\u002Fimg\u002Fconsole.png\" alt=\"\">\n\u003C\u002Fp>\n\n### Integrations\n\n**Models**: TaskingAI connects with hundreds of LLMs from various providers, including OpenAI, Anthropic, and more. We also allow users to integrate local host models through Ollama, LM Studio and Local AI.\n\n\u003Cp>\n\u003Cimg src=\".\u002Fstatic\u002Fimg\u002Fmodel_providers.png\" alt=\"\">\n\u003C\u002Fp>\n\n**Plugins**: TaskingAI supports a wide range of built-in plugins to empower your AI agents, including Google search, website reader, stock market retrieval, and more. Users can also create custom tools to meet their specific needs.\n\n\u003Cp>\n\u003Cimg src=\".\u002Fstatic\u002Fimg\u002Fplugins.png\" alt=\"\">\n\u003C\u002Fp>\n\n---\n\n## Why TaskingAI?\n\n### Problems with existing solutions 🙁\n\n**LangChain** is a tool framework for LLM application development, but it faces practical limitations:\n\n- **Statelessness**: Relies on client-side or external services for data management.\n- **Scalability Challenges**: Statelessness impacts consistent data handling across sessions.\n- **External Dependencies**: Depends on outside resources like model SDKs and vector storage.\n\n**OpenAI's Assistant API** excels in delivering GPTs-like functionalities but comes with its own constraints:\n\n- **Tied Functionalities**: Integrations like tools and retrievals are tied to each assistant, not suitable for multi-tenant applications.\n- **Proprietary Limitations**: Restricted to OpenAI models, unsuitable for diverse needs.\n- **Customization Limits**: Users cannot customize agent configuration such as memory and retrieval system.\n\n### How TaskingAI solves the problem 😃\n\n- **Supports both stateful and stateless usages**: Whether to keep track of and manage the message histories and agent conversation sessions, or just make stateless chat completion requests, TaskingAI has them both covered.\n- **Decoupled modular management**: Decoupled the management of tools, RAGs systems, language models from the agent. And allows free combination of these modules to build a powerful AI agent.\n- **Multi-tenant support**: TaskingAI supports fast deployment after development, and can be used in multi-tenant scenarios. No need to worry about the cloud services, just focus on the AI agent development.\n- **Unified API**: TaskingAI provides unified APIs for all the modules, including tools, RAGs systems, language models, and more. Super easy to manage and change the AI agent's configurations.\n\n## What Can You Build with TaskingAI?\n\n- [x] **Interactive Application Demos**\n- [x] **AI Agents for Enterprise Productivity**\n- [x] **Multi-Tenant AI-Native Applications for Business**\n\n---\n\nPlease give us a **FREE STAR 🌟** if you find it helpful 😇\n\n\u003Cp>\n\u003Cimg src=\"static\u002Fimg\u002Fstar.gif\" alt=\"\">\n\u003C\u002Fp>\n\n---\n\n## Quickstart with Docker\n\nA simple way to initiate self-hosted TaskingAI community edition is through [Docker](https:\u002F\u002Fwww.docker.com\u002F).\n\n### Prerequisites\n\n- Docker and Docker Compose installed on your machine.\n- Git installed for cloning the repository.\n- Python environment (above Python 3.8) for running the client SDK.\n\n### Installation\n\nFirst, clone the TaskingAI (community edition) repository from GitHub.\n\n```bash\ngit clone https:\u002F\u002Fgithub.com\u002Ftaskingai\u002Ftaskingai.git\ncd taskingai\n```\n\nInside the cloned repository, go to the docker directory.\n\n```bash\ncd docker\n```\n\n1. **Copy `.env.example` to `.env`**:\n\n   ```sh\n   cp .env.example .env\n   ```\n\n2. **Edit the `.env` file**:\n   Open the `.env` file in your favorite text editor and update the necessary configurations. Ensure all required environment variables are set correctly.\n\n3. **Start Docker Compose**:\n   Run the following command to start all services:\n   ```sh\n   docker-compose -p taskingai --env-file .env up -d\n   ```\n\nOnce the service is up, access the TaskingAI console through your browser with the URL http:\u002F\u002Flocalhost:8080. The default username and password are `admin` and `TaskingAI321`.\n\n### Upgrade\n\nIf you have already installed TaskingAI with a previous version and want to upgrade to the latest version, first update the repository.\n\n```bash\ngit pull origin master\n```\n\nThen stop the current docker service, upgrade to the latest version by pulling the latest image, and finally restart the service.\n\n```bash\ncd docker\ndocker-compose -p taskingai down\ndocker-compose -p taskingai pull\ndocker-compose -p taskingai --env-file .env up -d\n```\n\nDon't worry about data loss; your data will be automatically migrated to the latest version schema if needed.\n\n### TaskingAI UI Console\n\n[![TaskingAI Console Demo](https:\u002F\u002Fimg.youtube.com\u002Fvi\u002F4A5uQoawETU\u002Fmaxresdefault.jpg)](https:\u002F\u002Fyoutu.be\u002F4A5uQoawETU)\n**_\u003Cp style=\"text-align: center; font-size: small; \">Click the image above to view the TaskingAI Console Demo Video.\u003C\u002Fp>_**\n\n### TaskingAI Client SDK\n\nOnce the console is up, you can programmatically interact with the TaskingAI server using the TaskingAI client SDK.\n\nEnsure you have Python 3.8 or above installed, and set up a virtual environment (optional but recommended).\nInstall the TaskingAI Python client SDK using pip.\n\n```bash\npip install taskingai\n```\n\nHere is a client code example:\n\n```python\nimport taskingai\n\ntaskingai.init(api_key='YOUR_API_KEY', host='http:\u002F\u002Flocalhost:8080')\n\n# Create a new assistant\nassistant = taskingai.assistant.create_assistant(\n    model_id=\"YOUR_MODEL_ID\",\n    memory=\"naive\",\n)\n\n# Create a new chat\nchat = taskingai.assistant.create_chat(\n    assistant_id=assistant.assistant_id,\n)\n\n# Send a user message\ntaskingai.assistant.create_message(\n    assistant_id=assistant.assistant_id,\n    chat_id=chat.chat_id,\n    text=\"Hello!\",\n)\n\n# generate assistant response\nassistant_message = taskingai.assistant.generate_message(\n    assistant_id=assistant.assistant_id,\n    chat_id=chat.chat_id,\n)\n\nprint(assistant_message)\n```\n\nNote that the `YOUR_API_KEY` and `YOUR_MODEL_ID` should be replaced with the actual API key and chat completion model ID you created in the console.\n\nYou can learn more in the [documentation](https:\u002F\u002Fdocs.tasking.ai\u002Fdocs\u002Fguide\u002Fgetting_started\u002Fself_hosting\u002Foverview).\n\n## Resources\n\n- [Documentation](https:\u002F\u002Fdocs.tasking.ai)\n- [API Reference](https:\u002F\u002Fdocs.tasking.ai\u002Fapi)\n- [Contact Us](https:\u002F\u002Fwww.tasking.ai\u002Fcontact-us)\n\n## Community and Contribution\n\nPlease see our [contribution guidelines](.\u002FCONTRIBUTING.md) for how to contribute to the project.\n\nAlso, we’re excited to announce that TaskingAI now has an official Discord community! 🎊\n\n[Join our Discord server](https:\u002F\u002Fdiscord.gg\u002FRqwcD3vG3k) to:\n\n    •\t💬 Engage in discussions about TaskingAI, share ideas, and provide feedback.\n    •\t📚 Get support, tips, and best practices from other users and our team.\n    •\t🚀 Stay updated on the latest news, updates, and feature releases.\n    •\t🤝 Network with like-minded individuals who are passionate about AI and task automation.\n\n## License and Code of Conduct\n\nTaskingAI is released under a specific [TaskingAI Open Source License](.\u002FLICENSE). By contributing to this project, you agree to abide by its terms.\n\n## Support and Contact\n\nFor support, please refer to our [documentation](https:\u002F\u002Fdocs.tasking.ai) or contact us at [support@tasking.ai](mailto:support@tasking.ai).\n","TaskingAI 是一个面向基于大语言模型（LLM）的代理开发和部署的开源平台。其核心功能包括统一访问数百种AI模型、提供丰富的内置工具与高级检索增强生成系统以提升代理性能，以及采用BaaS模式分离AI逻辑与产品开发流程，从而简化从原型到生产的全过程。该平台支持通过RESTful API和客户端SDK实现快速扩展。适用于需要高效构建和管理AI原生应用的各种场景，如智能客服、内容生成等。",2,"2026-06-11 03:40:18","high_star"]