It is a framework for agentic workflow creation and deployment, designed to integrate task execution and intelligent chat capabilities. The framework, named Alice, provides a flexible environment for creating, managing, and deploying AI agents for various purposes. It leverages a microservices architecture with MongoDB for data persistence, enabling users to build and deploy workflows efficiently.
Alice is currently in version 0.3.11 (alpha) and includes features such as task execution, intelligent chat, extensible framework design, user management, flexible model deployment, and programmatic access to tasks and chats. The framework is built around four main components, which share information through six primary methods, all represented as strings. Tasks execute a set of “inner nodes,” with execution logic defined by the `node_end_code_routing` object and the `start_node` string. These nodes can be inner methods or inner tasks, depending on whether they are part of a task or a workflow.
Installation requires Git and Docker, with optional support for local models using LM Studio. Users must create an `.env` file using the provided `template.env` file and run the appropriate script for their operating system to build and launch the containers. The frontend is accessible at `http://localhost:4000/`. Updates can be applied using `python update.py`.
Planned developments for version 0.4 include improvements to the workflow generator, additional API engines and base tasks, file input and type interfaces, complex information flows, work environments/data clusters, and journals for holistic conversation views. Contributions are welcome, particularly those expanding workflow initialization processes or adding new tasks and workflows.
The project is licensed under a BSD-style license, and support inquiries can be directed to `[email protected]`. For more details, users can refer to the repository’s ReadMe file or explore the live preview at the provided link.
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