jackmpcollins/magentic

Health v2 · maintenance only

Adoption not part of the score

2415 stars · 127 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library for seamlessly integrating LLMs into Python code via @prompt and @chatprompt decorators that return typed, structured output. It supports multiple providers (OpenAI, Anthropic, Ollama), tool/function calling, streaming, and observability for building agentic systems.

Use cases

• call an llm as if it were a python function
• get structured pydantic output from an llm
• build ai agents by mixing llm calls with python code
• add llm-powered function calling to my app
• stream structured llm responses while generating
• switch between openai anthropic and ollama providers
• add observability to llm calls with opentelemetry

When to choose

• you want typed, structured LLM outputs validated with pydantic
• you prefer decorator-based, function-style LLM integration in Python
• you need multi-provider support (OpenAI, Anthropic, Ollama) behind one API
• you're building agentic workflows combining tool calls with regular Python code

When to avoid

• you need a full agent framework with built-in memory, planning, or UI
• you're not using Python
• you want a no-code or chat-interface product rather than a library
• you need fine-grained control over raw prompt/completion APIs

Facets

library · maturity active

llm-inference agent-framework prompt-engineering sdk large-language-models developer-tools python cross-platform structured-outputs pydantic function-calling decorators openai anthropic ollama streaming opentelemetry ai-agents natural-language-processing

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