Agent Architecture

from agentor import Agentor

agent = Agentor(
    name="Weather Agent",
    instructions="You are a helpful weather assistant",
    model="gpt-5-mini",
    tools=["get_weather"],
)

---
name: WeatherBot
tools: [get_weather]
model: gpt-4o-mini
temperature: 0.3
---
You are a concise weather assistant.

from agentor import Agentor

agent = Agentor.from_md("agent.md")
result = agent.run("Weather in Paris?")

result = agent.run("What is the weather in London?")
print(result)

import asyncio

# Single prompt
result = await agent.arun("What is the weather in London?")

# Batch processing with concurrency control
results = await agent.arun(
    ["Weather in London?", "Weather in Paris?", "Weather in Tokyo?"],
    limit_concurrency=10,
    max_turns=20
)

result = await agent.arun(
    "Complex task",
    fallback_models=["gpt-4o-mini", "gemini/gemini-pro"]
)

async for chunk in agent.chat("Tell me about AI", stream=True):
    print(chunk, end="", flush=True)

async for event in agent.stream_chat("Question", serialize=False):
    if event.message:
        print(event.message)

from agentor import Agentor, ModelSettings

model_settings = ModelSettings(
    temperature=0.7,
    top_p=0.9,
    max_tokens=2000
)

agent = Agentor(
    name="Creative Writer",
    model="gpt-4o",
    model_settings=model_settings
)

from agents import RunContextWrapper
from agentor.tools.registry import CelestoConfig

@register_global_tool
def get_weather(wrapper: RunContextWrapper[CelestoConfig], city: str) -> str:
    """Returns the weather in the given city."""
    api_key = wrapper.context.weather_api_key
    # Use API key to fetch weather
    return f"Weather in {city}"

agent = Agentor(
    name="My Agent",
    model="gpt-4o",
    enable_tracing=True  # Requires CELESTO_API_KEY
)

export CELESTO_DISABLE_AUTO_TRACING=True