Marvin is a Python framework for producing structured outputs and building agentic AI workflows.
Marvin addresses the challenge of reliably extracting and generating structured data from language models while orchestrating complex AI-driven processes. It provides utilities for casting, classifying, extracting, and generating structured outputs from unstructured inputs, alongside a task-and-agent system for building workflows. The framework abstracts away the complexity of prompt engineering and output parsing by offering high-level APIs that handle the interaction with language models, defaulting to OpenAI but supporting any model available through Pydantic AI.
Developers should choose Marvin when they need to integrate AI capabilities that produce predictable, typed outputs rather than free-form text responses. It suits projects requiring data extraction from documents, classification pipelines, or multi-step agentic workflows where tasks need to be coordinated across specialized agents. The framework is particularly valuable for applications where the structure of AI outputs matters as much as their content, such as data processing pipelines or systems that feed AI results into downstream code.
The project shows consistent development activity with regular updates and refinement of its core abstractions. The codebase maintains a focus on developer experience through intuitive APIs and clear examples. The framework has evolved from a structured-output utility library into a more comprehensive agentic system, indicating active expansion of its capabilities. Documentation is actively maintained with examples demonstrating both simple structured-output operations and complex multi-agent orchestration patterns.
