Structured Output

from pydantic import BaseModel, Field
from definable.agent import Agent

class MovieReview(BaseModel):
    title: str = Field(description="Movie title")
    rating: float = Field(description="Rating out of 10")
    summary: str = Field(description="Brief summary")
    pros: list[str] = Field(description="Positive aspects")
    cons: list[str] = Field(description="Negative aspects")

agent = Agent(model="gpt-4o", instructions="You are a movie critic.")

output = await agent.arun("Review Inception", output_schema=MovieReview)
review = output.parsed  # MovieReview instance
print(f"{review.title}: {review.rating}/10")

import json
from definable.model import OpenAIChat
from definable.model.message import Message

model = OpenAIChat(id="gpt-4o")
response = model.invoke(
    messages=[Message(role="user", content="Recommend a sci-fi movie.")],
    assistant_message=Message(role="assistant", content=""),
    response_format=MovieReview,
)

movie = MovieReview(**json.loads(response.content))

from typing import Optional
from enum import Enum

class Priority(str, Enum):
    low = "low"
    medium = "medium"
    high = "high"

class Task(BaseModel):
    title: str = Field(description="Short task title")
    priority: Priority
    subtasks: Optional[list[str]] = None

class ProjectPlan(BaseModel):
    project_name: str
    tasks: list[Task]
    total_hours: float