Explore Swarm Multi-Agent Framework Locally

Swarm is an experimental sample framework to simulate lightweight multi-agent framework for educational purpose. Usually it works with Open AI Key but we can change it to use local Ollama or LM Studio Models.

Setup:

## Create a new Conda or Python Virtual Environment and activate it
conda install python==3.10
pip install torch openai
pip install transformers accelerate huggingface_hub
pip install git+ssh://git@github.com/openai/swarm.git

To use with Open AI Key:

export OPEN_API_KEY = Your Key

To use Ollama or LM Studio Local LLMs — Update to Local URL:

## Find the location site-packages/swarm on the conda or python virtual env
## Locate the file core.py
class Swarm:
    def __init__(self, client=None):
        if not client:
          # Actual Code
          #client = OpenAI()
          # Update the Base URL and API Key to Ollama / LM Studio
          # In this demo we are using LM Studio and Llama 3.1
          client = OpenAI(base_url="http://localhost:1234/v1",api_key="random")
        self.client = client

Clone Repo:

Clone the Repo — where you can find examples directory with different use cases like basic, airline and weather etc.

git clone https://github.com/openai/swarm.git
cd swarm/examples

Sample Code:

from swarm import Swarm, Agent

client = Swarm()


it_agent = Agent(
    name="IT Agent",
    instructions="You are an IT Expert with 10 Years of Experience.",
)

sales_agent = Agent(
    name="Sales Agent",
    instructions="You are a Sales Expert with 5 Years of Experience and knows about best selling mobiles.",
)

def transfer_to_sales_agent():
    print("Sales agent in action")
    """Transfer sales related questions to sales team immediately."""
    return sales_agent

def transfer_to_it_agent():
    print("IT agent in action")
    """Transfer IT users immediately."""
    return it_agent

english_agent = Agent(
    name="English Agent",
    instructions="You only speak English.",
    functions=[transfer_to_sales_agent,transfer_to_it_agent],
)


messages = [{"role": "user", "content": "How to install pandas lib?"}]
response = client.run(agent=english_agent, messages=messages)

print(response.messages[-1]["content"])

messages = [{"role": "user", "content": "What are the best selling items?"}]
response = client.run(agent=english_agent, messages=messages)

print(response.messages[-1]["content"])

References:

https://github.com/openai/swarm

https://github.com/victorb/ollama-swarm/tree/main

Given that it is an experimental release, there is still much room for improvement. The airline agent example code [swarm/examples/airline] was interesting, so try those examples. Give it a try and share your experience in the comments. Thanks.