Mirascope

The AI Engineer'sDeveloper Stack

LLM abstractions that

aren't obstructions

Mirascope

from mirascope import llm
from pydantic import BaseModel

class Book(BaseModel):
    title: str
    author: str

@llm.call(
    provider="openai", 
    model="gpt-4o-mini", 
    response_model=Book,
)
def extract_book(text: str) -> str:
    return f"Extract the book: {text}"

text = "The Name of the Wind by Patrick Rothfuss"
book: Book = extract_book(text)

from mirascope import llm
from pydantic import BaseModel

class Book(BaseModel):
    title: str
    author: str

@llm.call(
    provider="openai", 
    model="gpt-4o-mini", 
    response_model=Book,
)
def extract_book(text: str) -> str:
    return f"Extract the book: {text}"

text = "The Name of the Wind by Patrick Rothfuss"
book: Book = extract_book(text)

Mirascope Docs Join the Community

Spin up your data flywheel

with one line of code

answer_questionv2

Lilypad

Beta

import lilypad
from mirascope import llm
lilypad.configure(auto_llm=True)

@lilypad.trace(versioning="automatic") 
@llm.call(provider="openai", model="gpt-4o-mini")
def answer_question(question: str) -> str:
    return f"Answer in one word: {question}"

answer_question("What is the capital of France?")

import lilypad
from mirascope import llm
lilypad.configure(auto_llm=True)

@lilypad.trace(versioning="automatic") 
@llm.call(provider="openai", model="gpt-4o-mini")
def answer_question(question: str) -> str:
    return f"Answer in one word: {question}"

answer_question("What is the capital of France?")

Traces

Version

Label

Time

Cost

Tokens

1 min ago

$0.0012

2 mins ago

$0.0011

1 hr ago

$0.0018

1 hr ago

$0.0019

Messages

user

Answer in one word: What is the capital of France?

assistant

Paris

Lilypad Docs Open Beta