PydanticAI Integration

pip install 'pydantic-ai-slim[openai]'

from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIModel
 
# Configure for AiMo Network
model = OpenAIModel(
    "provider_pubkey:model_name",  # AiMo model format
    base_url="https://devnet.aimo.network/api/v1",
    api_key="aimo-sk-dev-[your-key]"
)
 
# Create agent
agent = Agent(model)
 
# Simple usage
result = await agent.run("What is the meaning of life?")
print(result.data)

from pydantic import BaseModel
from pydantic_ai import Agent
 
class WeatherResponse(BaseModel):
    location: str
    temperature: int
    condition: str
    humidity: int
 
# Agent with structured output
weather_agent = Agent(
    model,
    result_type=WeatherResponse,
    system_prompt="You are a weather assistant. Always respond with structured weather data."
)
 
# Get structured response
result = await weather_agent.run("What's the weather like in Paris?")
weather_data: WeatherResponse = result.data
 
print(f"Temperature in {weather_data.location}: {weather_data.temperature}°C")
print(f"Condition: {weather_data.condition}")

from pydantic_ai import Agent, RunContext
 
def get_current_time() -> str:
    """Get the current time."""
    from datetime import datetime
    return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
def calculate_sum(a: int, b: int) -> int:
    """Calculate the sum of two numbers."""
    return a + b
 
# Agent with tools
agent_with_tools = Agent(
    model,
    tools=[get_current_time, calculate_sum],
    system_prompt="You are a helpful assistant with access to tools."
)
 
# Use tools
result = await agent_with_tools.run("What time is it and what's 15 + 27?")
print(result.data)

from typing import Dict
from pydantic_ai import Agent, RunContext
 
class UserContext:
    def __init__(self, user_id: str, preferences: Dict[str, str]):
        self.user_id = user_id
        self.preferences = preferences
 
def get_user_preference(ctx: RunContext[UserContext], key: str) -> str:
    """Get user preference by key."""
    return ctx.deps.preferences.get(key, "Not set")
 
# Agent with context
contextual_agent = Agent(
    model,
    deps_type=UserContext,
    tools=[get_user_preference],
    system_prompt="You are a personalized assistant."
)
 
# Use with context
user_context = UserContext("user123", {"theme": "dark", "language": "en"})
result = await contextual_agent.run(
    "What's my theme preference?",
    deps=user_context
)
print(result.data)