This release is a pre-release and may not be stable for production use.
Kitaru PydanticAI adapter
Record and replay PydanticAI agent runs with Kitaru.
Install
uv add "kitaru-pydantic-ai[openai]"
Install kitaru-pydantic-ai without the extra when your project provides another PydanticAI model implementation.
Use
import uuid
from pydantic_ai import Agent
from kitaru_pydantic_ai import KitaruAgent
agent = KitaruAgent(
Agent("openai:gpt-5-nano"),
agent_id=uuid.UUID("018f0000-0000-7000-8000-000000000100"),
)
result = agent.run_sync("Hello")
print(result.output)
The adapter accepts the same run arguments as the wrapped PydanticAI agent. Kitaru workers provide task, replay, and authentication context through the standard task environment.
Model costs
The adapter estimates each completed LLM call's USD cost from its resolved model, provider, token usage, and request time. Pricing comes from the bundled genai-prices catalog. Unsupported models and providers leave the cost unset without failing the agent run. The recorded node attributes describe whether pricing was estimated or unavailable.
Supply cost_calculator for private models, negotiated rates, or provider billing rules. The callback receives a PydanticAIUsageSummary and returns a non-negative USD amount. A supplied callback takes priority over the bundled catalog.
from decimal import Decimal
from kitaru_pydantic_ai import KitaruAgent, PydanticAIUsageSummary
def calculate_cost(usage: PydanticAIUsageSummary) -> Decimal:
uncached_input = usage.input_tokens - usage.cached_input_tokens
return (
Decimal(uncached_input) * Decimal("0.000002")
+ Decimal(usage.cached_input_tokens) * Decimal("0.0000002")
+ Decimal(usage.output_tokens) * Decimal("0.000008")
)
agent = KitaruAgent(pydantic_agent, cost_calculator=calculate_cost)
Set estimate_costs=False when cost estimation should be disabled. This does not disable a supplied cost_calculator.
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