pip install workflowaiimport os
import workflowai
workflowai.init( # This initialization is optional when using default settings
api_key=os.environ.get("WORKFLOWAI_API_KEY"), # This is the default and can be omitted
url="https://run.workflowai.com", # This is the default and can be omitted
)
Last updated
import workflowai
from pydantic import BaseModel
from workflowai import Model
class CityInput(BaseModel):
city: str
class CapitalOutput(BaseModel):
country: str
capital: str
fun_fact: str
@workflowai.agent()
async def get_capital_info(city_input: CityInput) -> CapitalOutput:
...output = await get_capital_info.run(
CityInput(city="New York"),
model=Model.GPT_4_LATEST
)
print(output)
# {
# "country": "United States",
# "capital": "Washington, D.C.",
# "fun_fact": "New York City is known as 'The Big Apple' and is famous for its cultural diversity and iconic landmarks like Times Square and Central Park."
# }
# ==================================================
# Cost: $ 0.00091
# Latency: 1.65soutput = await get_capital_info.run(
CityInput(city="New York"),
model=Model.CLAUDE_3_5_SONNET_LATEST
)
print(output)
# Output:
# ==================================================
# {
# "country": "United States",
# "capital": "Washington, D.C.",
# "fun_fact": "New York City's Federal Reserve Bank has the largest gold storage in the world, containing approximately 7,000 tons of gold bullion stored 80 feet below street level."
# }
# ==================================================
# Cost: $ 0.001755
# Latency: 2.43soutput = await get_capital_info.run(
CityInput(city="New York"),
model=Model.GEMINI_2_0_FLASH_LATEST
)
print(output)
# Output:
# ==================================================
# {
# "country": "United States of America",
# "capital": "Washington, D.C.",
# "fun_fact": "New York City is home to over 8 million people and over 800 languages are spoken in New York City, making it the most linguistically diverse city in the world."
# }
# ==================================================
# Cost: $ 0.00005
# Latency: 1.26s# use `.stream()` to stream the output
async for chunk in get_capital_info.stream(
CityInput(city="New York"),
model=Model.GPT_4O_MINI_LATEST
):
print(chunk)
# {
# "country": "United"
# }
# {
# "country": "United States"
# }
# {
# "country": "United States"
# "capital": "Washington"
# }
# streaming continues...
# ...