Marvin AI
The AI Engineering Framework
Build natural language interfaces that are reliable, scalable, and easy to trust.
Structure Text
🧩 AI Models
A drop-in replacement for Pydantic models that can parse natural language.
1from marvin import ai_model
2from pydantic import BaseModel, Field
3
4
5@ai_model
6class Location(BaseModel):
7 city: str
8 state: str= Field(..., description="Two-letter abbreviation")
9
10
11Location("The Big Apple")
12# Location(city="New York", state="NY")label text
🏷️ AI Classifiers
Turn standard enums into powerful classifiers without training data or examples.
1from marvin import ai_classifier
2from enum import Enum
3
4
5@ai_classifier
6class Sentiment(Enum):
7 POSITIVE = 1
8 NEUTRAL = 0
9 NEGATIVE = -1
10
11
12Sentiment("That sounds great!")
13# Sentiment.POSITIVE
1from marvin import ai_fn
2
3
4@ai_fn
5def recipe(ingredients: list[str], style: str) -> str:
6 """
7 Generate a recipe in the provided `style` that uses
8 all of the `ingredients`. Provide amounts and instructions.
9 """
10
11
12recipe(["lemon", "chicken", "olives", "coucous"], style="North Italy, spicy")
13
14
15# North Italian Spicy Chicken with Lemon, Olives, and Couscous Recipe
16#
17# Ingredients:
18# - 1 large chicken
19# - 2 lemons
20# ...work with agents
🤝 AI Applications
Interactive AI assistants that can use tools and manage states
1import random
2from marvin import AIApplication
3from marvin.tools import tool
4
5
6@tool
7def roll_dice(n_dice: int = 1) -> list[int]:
8 return [random.randint(1, 6) for _ in range(n_dice)]
9
10
11chatbot = AIApplication(
12 description="A chatbot that rolls for every action.",
13 tools=[roll_dice]
14)
15
16
17chatbot("Hi!")