WorkflowAI Python SDK is a library that allows you to programmatically create and run agents in Python, while being able to use the full power of the WorkflowAI platform.
Install the SDK
workflowai requires Python >= 3.9.
pip install workflowai
to get notified when new models are added.
API Key
Get your API key from your or from your self-hosted WorkflowAI dashboard.
Set the WORKFLOWAI_API_KEY environment variable.
Initialize the SDK
import 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
)
You can also set the WORKFLOWAI_API_URL environment variable to point to your self-hosted WorkflowAI.
Write your first agent
An agent is in essence an async function with the added constraints that:
it has a single argument that is a Pydantic model, which is the input to the agent
it has a single return value that is a Pydantic model, which is the output of the agent
it is decorated with the @workflowai.agent() decorator
The following agent, given a city, returns the country, capital, and a fun fact about the city.
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: 1.65s
output = 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: 2.43s
output = 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...
# ...
You have created your first agent! Congratulations.
Next steps
run.workflowai.com is our
is a very popular and powerful library for data validation and parsing.
Agents created by the SDK are also available in the .
Runs are automatically logged as well from the section.
