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Swarms is a modular framework that enables reliable and useful multi-agent collaboration at scale to automate real-world tasks. [![GitHub issues](https://img.shields.io/github/issues/kyegomez/swarms)](https://github.com/kyegomez/swarms/issues) [![GitHub forks](https://img.shields.io/github/forks/kyegomez/swarms)](https://github.com/kyegomez/swarms/network) [![GitHub stars](https://img.shields.io/github/stars/kyegomez/swarms)](https://github.com/kyegomez/swarms/stargazers) [![GitHub license](https://img.shields.io/github/license/kyegomez/swarms)](https://github.com/kyegomez/swarms/blob/main/LICENSE)[![GitHub star chart](https://img.shields.io/github/stars/kyegomez/swarms?style=social)](https://star-history.com/#kyegomez/swarms)[![Dependency Status](https://img.shields.io/librariesio/github/kyegomez/swarms)](https://libraries.io/github/kyegomez/swarms) [![Downloads](https://static.pepy.tech/badge/swarms/month)](https://pepy.tech/project/swarms) [![Join the Agora discord](https://img.shields.io/discord/1110910277110743103?label=Discord&logo=discord&logoColor=white&style=plastic&color=d7b023)![Share on Twitter](https://img.shields.io/twitter/url/https/twitter.com/cloudposse.svg?style=social&label=Share%20%40kyegomez/swarms)](https://twitter.com/intent/tweet?text=Check%20out%20this%20amazing%20AI%20project:%20&url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms) [![Share on Facebook](https://img.shields.io/badge/Share-%20facebook-blue)](https://www.facebook.com/sharer/sharer.php?u=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms) [![Share on LinkedIn](https://img.shields.io/badge/Share-%20linkedin-blue)](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&title=&summary=&source=) [![Share on Reddit](https://img.shields.io/badge/-Share%20on%20Reddit-orange)](https://www.reddit.com/submit?url=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&title=Swarms%20-%20the%20future%20of%20AI) [![Share on Hacker News](https://img.shields.io/badge/-Share%20on%20Hacker%20News-orange)](https://news.ycombinator.com/submitlink?u=https%3A%2F%2Fgithub.com%2Fkyegomez%2Fswarms&t=Swarms%20-%20the%20future%20of%20AI) [![Share on Pinterest](https://img.shields.io/badge/-Share%20on%20Pinterest-red)](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) [![Share on WhatsApp](https://img.shields.io/badge/-Share%20on%20WhatsApp-green)](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)
---- ## Installation `pip3 install --upgrade swarms` --- ## Usage Run example in Collab: Open In Colab ### `Flow` Example - Reliable Structure that provides LLMS autonomy - Extremely Customizeable with stopping conditions, interactivity, dynamical temperature, loop intervals, and so much more - Enterprise Grade + Production Grade: `Flow` is designed and optimized for automating real-world tasks at scale! ```python import os from dotenv import load_dotenv # Import the OpenAIChat model and the Flow struct from swarms.models import OpenAIChat from swarms.structs import Flow # Load the environment variables load_dotenv() # Get the API key from the environment api_key = os.environ.get("OPENAI_API_KEY") # Initialize the language model llm = OpenAIChat( temperature=0.5, openai_api_key=api_key, ) ## Initialize the workflow flow = Flow(llm=llm, max_loops=1, dashboard=True) # Run the workflow on a task out = flow.run("Generate a 10,000 word blog on health and wellness.") ``` ------ ### `SequentialWorkflow` - A Sequential swarm of autonomous agents where each agent's outputs are fed into the next agent - Save and Restore Workflow states! - Integrate Flow's with various LLMs and Multi-Modality Models ```python from swarms.models import OpenAIChat, BioGPT, Anthropic from swarms.structs import Flow from swarms.structs.sequential_workflow import SequentialWorkflow # Example usage api_key = ( "" # Your actual API key here ) # Initialize the language flow llm = OpenAIChat( openai_api_key=api_key, temperature=0.5, max_tokens=3000, ) biochat = BioGPT() # Use Anthropic anthropic = Anthropic() # Initialize the agent with the language flow agent1 = Flow(llm=llm, max_loops=1, dashboard=False) # Create another agent for a different task agent2 = Flow(llm=llm, max_loops=1, dashboard=False) # Create another agent for a different task agent3 = Flow(llm=biochat, max_loops=1, dashboard=False) # agent4 = Flow(llm=anthropic, max_loops="auto") # 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) # 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) # Run the workflow workflow.run() # Output the results for task in workflow.tasks: print(f"Task: {task.description}, Result: {task.result}") ``` ## `Multi Modal Autonomous Agents` - Run the flow with multiple modalities useful for various real-world tasks in manufacturing, logistics, and health. ```python from swarms.structs import Flow from swarms.models.gpt4_vision_api import GPT4VisionAPI from swarms.prompts.multi_modal_autonomous_instruction_prompt import ( MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1, ) llm = GPT4VisionAPI() task = ( "Analyze this image of an assembly line and identify any issues such as" " misaligned parts, defects, or deviations from the standard assembly" " process. IF there is anything unsafe in the image, explain why it is" " unsafe and how it could be improved." ) img = "assembly_line.jpg" ## Initialize the workflow flow = Flow( llm=llm, max_loops='auto' sop=MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1, dashboard=True, ) flow.run(task=task, img=img) ``` --- # Features 🤖 The Swarms framework is designed with a strong emphasis on reliability, performance, and production-grade readiness. Below are the key features that make Swarms an ideal choice for enterprise-level AI deployments. ## 🚀 Production-Grade Readiness - **Scalable Architecture**: Built to scale effortlessly with your growing business needs. - **Enterprise-Level Security**: Incorporates top-notch security features to safeguard your data and operations. - **Containerization and Microservices**: Easily deployable in containerized environments, supporting microservices architecture. ## ⚙️ Reliability and Robustness - **Fault Tolerance**: Designed to handle failures gracefully, ensuring uninterrupted operations. - **Consistent Performance**: Maintains high performance even under heavy loads or complex computational demands. - **Automated Backup and Recovery**: Features automatic backup and recovery processes, reducing the risk of data loss. ## 💡 Advanced AI Capabilities The Swarms framework is equipped with a suite of advanced AI capabilities designed to cater to a wide range of applications and scenarios, ensuring versatility and cutting-edge performance. ### Multi-Modal Autonomous Agents - **Versatile Model Support**: Seamlessly works with various AI models, including NLP, computer vision, and more, for comprehensive multi-modal capabilities. - **Context-Aware Processing**: Employs context-aware processing techniques to ensure relevant and accurate responses from agents. ### Function Calling Models for API Execution - **Automated API Interactions**: Function calling models that can autonomously execute API calls, enabling seamless integration with external services and data sources. - **Dynamic Response Handling**: Capable of processing and adapting to responses from APIs for real-time decision making. ### Varied Architectures of Swarms - **Flexible Configuration**: Supports multiple swarm architectures, from centralized to decentralized, for diverse application needs. - **Customizable Agent Roles**: Allows customization of agent roles and behaviors within the swarm to optimize performance and efficiency. ### Generative Models - **Advanced Generative Capabilities**: Incorporates state-of-the-art generative models to create content, simulate scenarios, or predict outcomes. - **Creative Problem Solving**: Utilizes generative AI for innovative problem-solving approaches and idea generation. ### Enhanced Decision-Making - **AI-Powered Decision Algorithms**: Employs advanced algorithms for swift and effective decision-making in complex scenarios. - **Risk Assessment and Management**: Capable of assessing risks and managing uncertain situations with AI-driven insights. ### Real-Time Adaptation and Learning - **Continuous Learning**: Agents can continuously learn and adapt from new data, improving their performance and accuracy over time. - **Environment Adaptability**: Designed to adapt to different operational environments, enhancing robustness and reliability. ## 🔄 Efficient Workflow Automation - **Streamlined Task Management**: Simplifies complex tasks with automated workflows, reducing manual intervention. - **Customizable Workflows**: Offers customizable workflow options to fit specific business needs and requirements. - **Real-Time Analytics and Reporting**: Provides real-time insights into agent performance and system health. ## 🌐 Wide-Ranging Integration - **API-First Design**: Easily integrates with existing systems and third-party applications via robust APIs. - **Cloud Compatibility**: Fully compatible with major cloud platforms for flexible deployment options. - **Continuous Integration/Continuous Deployment (CI/CD)**: Supports CI/CD practices for seamless updates and deployment. ## 📊 Performance Optimization - **Resource Management**: Efficiently manages computational resources for optimal performance. - **Load Balancing**: Automatically balances workloads to maintain system stability and responsiveness. - **Performance Monitoring Tools**: Includes comprehensive monitoring tools for tracking and optimizing performance. ## 🛡️ Security and Compliance - **Data Encryption**: Implements end-to-end encryption for data at rest and in transit. - **Compliance Standards Adherence**: Adheres to major compliance standards ensuring legal and ethical usage. - **Regular Security Updates**: Regular updates to address emerging security threats and vulnerabilities. ## 💬 Community and Support - **Extensive Documentation**: Detailed documentation for easy implementation and troubleshooting. - **Active Developer Community**: A vibrant community for sharing ideas, solutions, and best practices. - **Professional Support**: Access to professional support for enterprise-level assistance and guidance. Swarms framework is not just a tool but a robust, scalable, and secure partner in your AI journey, ready to tackle the challenges of modern AI applications in a business environment. ## 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) and our [contributing board](https://github.com/users/kyegomez/projects/1) ## Community - [Join the Swarms community on Discord!](https://discord.gg/AJazBmhKnr) - Join our Swarms Community Gathering every Thursday at 1pm NYC Time to unlock the potential of autonomous agents in automating your daily tasks [Sign up here](https://lu.ma/5p2jnc2v) ## Discovery Call Book a discovery call with the Swarms team to learn how to optimize and scale your swarm! [Click here to book a time that works for you!](https://calendly.com/swarm-corp/30min?month=2023-11) # License MIT