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swarms/examples/structs/workflows/sequential/example_sequentialworkflow.py

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import os
from swarms import OpenAIChat, Agent, SequentialWorkflow
from dotenv import load_dotenv
load_dotenv()
# Load the environment variables
api_key = os.getenv("OPENAI_API_KEY")
# Initialize the language agent
llm = OpenAIChat(
temperature=0.5,
model_name="gpt-4",
openai_api_key=api_key,
max_tokens=4000,
)
# Initialize the agent with the language agent
agent1 = Agent(llm=llm, max_loops=1)
# Create another agent for a different task
agent2 = Agent(llm=llm, max_loops=1)
# Create another agent for a different task
agent3 = Agent(llm=llm, max_loops=1)
# Create the workflow
workflow = SequentialWorkflow(max_loops=1)
# Add tasks to the workflow
workflow.add(
agent1,
"Generate a 10,000 word blog on health and wellness.",
)
# Suppose the next task takes the output of the first task as input
workflow.add(
agent2,
"Summarize the generated blog",
)
# Run the workflow
workflow.run()
# Output the results
for task in workflow.tasks:
print(f"Task: {task.description}, Result: {task.result}")