swarms/README.md

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Swarms is a modular framework that enables reliable and useful multi-agent collaboration at scale to automate real-world tasks.


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## Vision
At Swarms, we're transforming the landscape of AI from siloed AI agents to a unified 'swarm' of intelligence. Through relentless iteration and the power of collective insight from our 1500+ Agora researchers, we're developing a groundbreaking framework for AI collaboration. Our mission is to catalyze a paradigm shift, advancing Humanity with the power of unified autonomous AI agent swarms.

-----

## 🤝 Schedule a 1-on-1 Session

Book a [1-on-1 Session with Kye](https://calendly.com/swarm-corp/30min), the Creator, to discuss any issues, provide feedback, or explore how we can improve Swarms for you.


----------

## Installation
`pip3 install --upgrade swarms`

---

## Usage
We have a small gallery of examples to run here, [for more check out the docs to build your own agent and or swarms!](https://docs.apac.ai)

### `MultiAgentDebate`

- `MultiAgentDebate` is a simple class that enables multi agent collaboration.

```python
from swarms.workers import Worker
from swarms.swarms import MultiAgentDebate, select_speaker
from swarms.models import OpenAIChat


api_key = "sk-"

llm = OpenAIChat(
    model_name='gpt-4', 
    openai_api_key=api_key, 
    temperature=0.5
)

node = Worker(
    llm=llm,
    openai_api_key=api_key,
    ai_name="Optimus Prime",
    ai_role="Worker in a swarm",
    external_tools = None,
    human_in_the_loop = False,
    temperature = 0.5,
)

node2 = Worker(
    llm=llm,
    openai_api_key=api_key,
    ai_name="Bumble Bee",
    ai_role="Worker in a swarm",
    external_tools = None,
    human_in_the_loop = False,
    temperature = 0.5,
)

node3 = Worker(
    llm=llm,
    openai_api_key=api_key,
    ai_name="Bumble Bee",
    ai_role="Worker in a swarm",
    external_tools = None,
    human_in_the_loop = False,
    temperature = 0.5,
)

agents = [
    node,
    node2,
    node3
]

# Initialize multi-agent debate with the selection function
debate = MultiAgentDebate(agents, select_speaker)

# Run task
task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
results = debate.run(task, max_iters=4)

# Print results
for result in results:
    print(f"Agent {result['agent']} responded: {result['response']}")
```

## Usage
- A powerful tool for concurrent execution of tasks using multiple Language Model (LLM) instances.

```python
from swarms.swarms import GodMode
from swarms.models import OpenAIChat

api_key = ""

llm = OpenAIChat(
    openai_api_key=api_key
)


llms = [
    llm,
    llm,
    llm
]

god_mode = GodMode(llms)

task = 'Generate a 10,000 word blog on health and wellness.'

out = god_mode.run(task)
god_mode.print_responses(task)
```

------

### `OmniModalAgent`
- OmniModal Agent is an LLM that access to 10+ multi-modal encoders and diffusers! It can generate images, videos, speech, music and so much more, get started with:

```python
from swarms.models import OpenAIChat
from swarms.agents import OmniModalAgent

api_key = "SK-"

llm = OpenAIChat(model_name="gpt-4", openai_api_key=api_key)

agent = OmniModalAgent(llm)

agent.run("Create a video of a swarm of fish")

```


### `Flow` Example
- The `Flow` is a superior iteratioin of the `LLMChain` from Langchain, our intent with `Flow` is to create the most reliable loop structure that gives the agents their "autonomy" through 3 main methods of interaction, one through user specified loops, then dynamic where the agent parses a <DONE> token, and or an interactive human input verison, or a mix of all 3. 
```python

from swarms.models import OpenAIChat
from swarms.structs import Flow

api_key = ""


# Initialize the language model,
# This model can be swapped out with Anthropic, ETC, Huggingface Models like Mistral, ETC
llm = OpenAIChat(
    openai_api_key=api_key,
    temperature=0.5,
)

# Initialize the flow
flow = Flow(
    llm=llm,
    max_loops=5,
)

out = flow.run("Generate a 10,000 word blog, say Stop when done")
print(out)


```

---

## Documentation

- For documentation, go here, [swarms.apac.ai](https://swarms.apac.ai)


## Contribute

We're always looking for contributors to help us improve and expand this project. If you're interested, please check out our [Contributing Guidelines](CONTRIBUTING.md).

# License

MIT