An open-source framework for building and debugging applications that make decisions, such as chatbots, agents, and simulations, using simple Python building blocks.
Burr
An open-source framework for building and debugging applications that make decisions, such as chatbots, agents, and simulations, using simple Python building blocks.
YouTube Video: Burr
An open-source framework for building and debugging applications that make decisions, such as chatbots, agents, and simulations, using simple Python building blocks.
Burr is an open-source framework developed by DAGWorks that facilitates the creation of decision-making applications—including chatbots, agents, and simulations—using straightforward Python components. It enables developers to model applications as state machines, providing a user interface for real-time monitoring, tracing, and debugging. Burr integrates seamlessly with various frameworks and includes pluggable persisters to save and load application states, enhancing the development and maintenance of complex AI-driven systems.
Developing AI-driven applications that require decision-making capabilities.
Modeling complex workflows as state machines for clarity and maintainability.
Real-time monitoring and debugging of application states and transitions.
Integrating with large language models (LLMs) and other frameworks for enhanced functionality.
Burr provides structured autonomy through predefined state machines and transitions, enabling automated workflows while requiring explicit human-defined actions for decision points. It allows developers to delegate specific cognitive functions (e.g., LLM responses) to automated processes while maintaining human oversight through its UI monitoring and intervention capabilities. The system supports persistent state management and conditional transitions but lacks fully self-directed decision-making without predefined rules. Its architecture enables partial autonomy within bounded operational parameters, as demonstrated in use cases like RAG chatbots where human input remains integral to workflow progression.
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