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Pydantic AI Agent Configuration

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Linked challenge: Extract Short-Term Rental Analytics with Pydantic AI and Together AI

Format
Code-aware
Lines
9
Sections
3
Linked challenge
Extract Short-Term Rental Analytics with Pydantic AI and Together AI

Prompt source

Original prompt text with formatting preserved for inspection.

9 lines
3 sections
No variables
0 checklist items
from pydantic import BaseModel
from pydantic_ai import Agent

class VacationMarketStats(BaseModel):
    market_name: str
    peak_occupancy_rate: float
    average_daily_rate: float
    permit_capped: bool
    max_active_permits: int

agent = Agent('together:meta-llama/Llama-3.3-70B-Instruct', result_type=VacationMarketStats)

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.