diff --git a/README.md b/README.md index 94d6c817f..a1b9772ef 100644 --- a/README.md +++ b/README.md @@ -73,15 +73,17 @@ out = agent.run("Generate a 10,000 word blog on health and wellness.") - Integrate Agent's with various LLMs and Multi-Modality Models ```python -from swarms.models import OpenAIChat, BioGPT, Anthropic +import os +from swarms.models import OpenAIChat from swarms.structs import Agent from swarms.structs.sequential_workflow import SequentialWorkflow +from dotenv import load_dotenv + +load_dotenv() +# Load the environment variables +api_key = os.getenv("OPENAI_API_KEY") -# Example usage -api_key = ( - "" # Your actual API key here -) # Initialize the language agent llm = OpenAIChat( @@ -90,32 +92,28 @@ llm = OpenAIChat( max_tokens=3000, ) -biochat = BioGPT() - -# Use Anthropic -anthropic = Anthropic() # Initialize the agent with the language agent -agent1 = Agent(llm=llm, max_loops=1, dashboard=False) +agent1 = Agent(llm=llm, max_loops=1) # Create another agent for a different task -agent2 = Agent(llm=llm, max_loops=1, dashboard=False) +agent2 = Agent(llm=llm, max_loops=1) # Create another agent for a different task -agent3 = Agent(llm=biochat, max_loops=1, dashboard=False) - -# agent4 = Agent(llm=anthropic, max_loops="auto") +agent3 = Agent(llm=llm, max_loops=1) # Create the workflow workflow = SequentialWorkflow(max_loops=1) # Add tasks to the workflow -workflow.add("Generate a 10,000 word blog on health and wellness.", agent1) +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("Summarize the generated blog", agent2) - -workflow.add("Create a references sheet of materials for the curriculm", agent3) +workflow.add( + agent2, "Summarize the generated blog", +) # Run the workflow workflow.run() @@ -124,6 +122,7 @@ workflow.run() for task in workflow.tasks: print(f"Task: {task.description}, Result: {task.result}") + ``` ## `Multi Modal Autonomous Agents`