Parser Model

"""
Parser Model
============

Demonstrates parser-model assisted team output parsing into rich schemas.
"""

import random
from typing import List

from agno.agent import Agent, RunOutput
from agno.models.openai import OpenAIResponses
from agno.team import Team
from pydantic import BaseModel, Field
from rich.pretty import pprint


class NationalParkAdventure(BaseModel):
    park_name: str = Field(..., description="Name of the national park")
    best_season: str = Field(
        ...,
        description="Optimal time of year to visit this park (e.g., 'Late spring to early fall')",
    )
    signature_attractions: List[str] = Field(
        ...,
        description="Must-see landmarks, viewpoints, or natural features in the park",
    )
    recommended_trails: List[str] = Field(
        ...,
        description="Top hiking trails with difficulty levels (e.g., 'Angel's Landing - Strenuous')",
    )
    wildlife_encounters: List[str] = Field(
        ..., description="Animals visitors are likely to spot, with viewing tips"
    )
    photography_spots: List[str] = Field(
        ...,
        description="Best locations for capturing stunning photos, including sunrise/sunset spots",
    )
    camping_options: List[str] = Field(
        ..., description="Available camping areas, from primitive to RV-friendly sites"
    )
    safety_warnings: List[str] = Field(
        ..., description="Important safety considerations specific to this park"
    )
    hidden_gems: List[str] = Field(
        ..., description="Lesser-known spots or experiences that most visitors miss"
    )
    difficulty_rating: int = Field(
        ...,
        ge=1,
        le=5,
        description="Overall park difficulty for average visitor (1=easy, 5=very challenging)",
    )
    estimated_days: int = Field(
        ...,
        ge=1,
        le=14,
        description="Recommended number of days to properly explore the park",
    )
    special_permits_needed: List[str] = Field(
        default=[],
        description="Any special permits or reservations required for certain activities",
    )


# ---------------------------------------------------------------------------
# Create Members
# ---------------------------------------------------------------------------
itinerary_planner = Agent(
    name="Itinerary Planner",
    model=OpenAIResponses(id="gpt-5.2"),
    description="You help people plan amazing national park adventures and provide detailed park guides.",
)

weather_expert = Agent(
    name="Weather Expert",
    model=OpenAIResponses(id="gpt-5.2"),
    description="You are a weather expert and can provide detailed weather information for a given location.",
)

# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
national_park_expert = Team(
    model=OpenAIResponses(id="gpt-5.2-mini"),
    members=[itinerary_planner, weather_expert],
    output_schema=NationalParkAdventure,
    parser_model=OpenAIResponses(id="gpt-5.2-mini"),
)

# ---------------------------------------------------------------------------
# Run Team
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    national_parks = [
        "Yellowstone National Park",
        "Yosemite National Park",
        "Grand Canyon National Park",
        "Zion National Park",
        "Grand Teton National Park",
        "Rocky Mountain National Park",
        "Acadia National Park",
        "Mount Rainier National Park",
        "Great Smoky Mountains National Park",
        "Rocky National Park",
    ]

    run: RunOutput = national_park_expert.run(
        f"What is the best season to visit {national_parks[random.randint(0, len(national_parks) - 1)]}? Please provide a detailed one week itinerary for a visit to the park."
    )
    pprint(run.content)

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/03_teams/structured_input_output

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python parser_model.py