{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/10"}],"enrichment":{"capability":"Marvin is a Python framework for building AI workflows that produce structured outputs and delegate tasks to language models. It provides utilities for extracting, casting, classifying, and generating data, plus a task-and-agent system for orchestrating multi-step agentic processes.","skillfed_tags":["llm-framework","structured-output","agentic-ai"],"use_cases":["Extract structured data (prices, dates, entities) from unstructured text or documents without manual parsing.","Classify user input into predefined categories (support tickets to departments, sentiment labels, etc.) with type-safe enum results.","Build multi-step workflows where specialized agents collaborate\u2014e.g., one agent researches, another writes, a third reviews.","Generate synthetic test data or examples matching a specific schema for testing or prototyping.","Delegate complex reasoning tasks to an LLM while keeping your application logic type-checked and deterministic."],"what_it_does":"Marvin bridges the gap between unstructured AI outputs and type-safe Python code. At its core, it provides four structured-output utilities\u2014extract, cast, classify, and generate\u2014that let you pull native Python types and custom objects directly from LLM responses. Built on top of Pydantic for validation, it ensures results match your schema before they reach your code.\n\nBeyond simple extraction, Marvin 3.x introduces a task-and-agent model for building agentic workflows. You define Tasks with clear instructions and result types, assign specialized Agents (which wrap LLM configurations), and optionally give tasks access to custom tools and context. Tasks can be composed into Threads for orchestrating complex multi-step behaviors. The framework is designed to make AI work observable and debuggable\u2014you see which tools were called, what the agent did, and whether it succeeded.","worth_installing":"Yes, if you are building AI-powered applications and want structured, validated outputs without writing LLM response parsing code. Marvin's combination of simple extraction utilities and a composable task-agent framework makes it suitable for both quick prototyping and more complex agentic systems. Low install friction, active maintenance, permissive license, and no known vulnerabilities. Main constraint: requires an LLM API key and incurs per-call costs."},"id":"marvin","links":{"html":"https://skillfed.io/packages/marvin","md":"https://skillfed.io/packages/marvin.md","pypi":"https://pypi.org/project/marvin/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-03-04","license_spdx":null,"license_treatment":"permissive","name":"marvin","python_support":"supports_current","summary":"a simple and powerful tool to get things done with AI"},"popularity":{"monthly_downloads":91045,"position":13547,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"3.2.7"}