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211 lines
8.3 KiB
211 lines
8.3 KiB
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<div align="center">
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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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[](https://github.com/kyegomez/swarms/issues) [](https://github.com/kyegomez/swarms/network) [](https://github.com/kyegomez/swarms/stargazers) [](https://github.com/kyegomez/swarms/blob/main/LICENSE)[](https://star-history.com/#kyegomez/swarms)[](https://libraries.io/github/kyegomez/swarms) [](https://pepy.tech/project/swarms)
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### Share on Social Media
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[](https://twitter.com/intent/tweet?text=Check%20out%20this%20amazing%20AI%20project:%20&url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms) [](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms) [](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&title=&summary=&source=)
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[](https://www.reddit.com/submit?url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&title=Swarms%20-%20the%20future%20of%20AI) [](https://news.ycombinator.com/submitlink?u=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&t=Swarms%20-%20the%20future%20of%20AI) [](https://pinterest.com/pin/create/button/?url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&media=https%3A%2F%2Fexample.com%2Fimage.jpg&description=Swarms%20-%20the%20future%20of%20AI) [](https://api.whatsapp.com/send?text=Check%20out%20Swarms%20-%20the%20future%20of%20AI%20%23swarms%20%23AI%0A%0Ahttps%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms)
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</div>
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## Purpose
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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.
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-----
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# 🤝 Schedule a 1-on-1 Session
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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.
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----------
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## Installation
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* `pip3 install --upgrade swarms`
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---
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## Usage
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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)
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### `MultiAgentDebate`
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- `MultiAgentDebate` is a simple class that enables multi agent collaboration.
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```python
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from swarms.workers import Worker
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from swarms.swarms import MultiAgentDebate, select_speaker
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from swarms.models import OpenAIChat
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api_key = "sk-"
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llm = OpenAIChat(
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model_name='gpt-4',
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openai_api_key=api_key,
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temperature=0.5
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)
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node = Worker(
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llm=llm,
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openai_api_key=api_key,
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ai_name="Optimus Prime",
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ai_role="Worker in a swarm",
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external_tools = None,
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human_in_the_loop = False,
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temperature = 0.5,
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)
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node2 = Worker(
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llm=llm,
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openai_api_key=api_key,
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ai_name="Bumble Bee",
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ai_role="Worker in a swarm",
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external_tools = None,
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human_in_the_loop = False,
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temperature = 0.5,
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)
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node3 = Worker(
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llm=llm,
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openai_api_key=api_key,
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ai_name="Bumble Bee",
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ai_role="Worker in a swarm",
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external_tools = None,
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human_in_the_loop = False,
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temperature = 0.5,
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)
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agents = [
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node,
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node2,
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node3
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]
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# Initialize multi-agent debate with the selection function
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debate = MultiAgentDebate(agents, select_speaker)
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# Run task
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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."
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results = debate.run(task, max_iters=4)
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# Print results
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for result in results:
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print(f"Agent {result['agent']} responded: {result['response']}")
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```
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----
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### `Worker`
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- The `Worker` is an fully feature complete agent with an llm, tools, and a vectorstore for long term memory!
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- Place your api key as parameters in the llm if you choose!
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- And, then place the openai api key in the Worker for the openai embedding model
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```python
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from swarms.models import OpenAIChat
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from swarms import Worker
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api_key = ""
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llm = OpenAIChat(
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openai_api_key=api_key,
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temperature=0.5,
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)
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node = Worker(
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llm=llm,
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ai_name="Optimus Prime",
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openai_api_key=api_key,
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ai_role="Worker in a swarm",
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external_tools=None,
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human_in_the_loop=False,
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temperature=0.5,
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)
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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."
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response = node.run(task)
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print(response)
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```
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------
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### `OmniModalAgent`
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- 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:
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```python
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from swarms.models import OpenAIChat
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from swarms.agents import OmniModalAgent
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api_key = "SK-"
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llm = OpenAIChat(model_name="gpt-4", openai_api_key=api_key)
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agent = OmniModalAgent(llm)
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agent.run("Create a video of a swarm of fish")
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```
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- OmniModal Agent has a ui in the root called `python3 omni_ui.py`
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---
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# Documentation
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For documentation, go here, [swarms.apac.ai](https://swarms.apac.ai)
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-----
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# ✨ Features
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* Easy to use Base LLMs, `OpenAI` `Palm` `Anthropic` `HuggingFace`
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* Enterprise Grade, Production Ready with robust Error Handling
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* Multi-Modality Native with Multi-Modal LLMs as tools
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* Infinite Memory Processing: Store infinite sequences of infinite Multi-Modal data, text, images, videos, audio
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* Usability: Extreme emphasis on useability, code is at it's theortical minimum simplicity factor to use
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* Reliability: Outputs that accomplish tasks and activities you wish to execute.
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* Fluidity: A seamless all-around experience to build production grade workflows
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* Speed: Lower the time to automate tasks by 90%.
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* Simplicity: Swarms is extremely simple to use, if not thee simplest agent framework of all time
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* Powerful: Swarms is capable of building entire software apps, to large scale data analysis, and handling chaotic situations
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-----
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## Contribute
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We're always looking for contributors to help us improve and expand this project. If you're interested, please check out our [Contributing Guidelines](C0NTRIBUTING.md).
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### Optimization Priorities
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1. **Reliability**: Increase the reliability of the swarm - obtaining the desired output with a basic and un-detailed input.
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2. **Speed**: Reduce the time it takes for the swarm to accomplish tasks by improving the communication layer, critiquing, and self-alignment with meta prompting.
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3. **Scalability**: Ensure that the system is asynchronous, concurrent, and self-healing to support scalability.
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Our goal is to continuously improve Swarms by following this roadmap, while also being adaptable to new needs and opportunities as they arise.
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---
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# Demos
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## Swarm Video Demo {Click for more}
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[](https://youtu.be/Br62cDMYXgc)
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---
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# Contact
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For enterprise and production ready deployments, allow us to discover more about you and your story, [book a call with us here](https://www.apac.ai/Setup-Call) |