Introducing, Swarms Deploy ?? Production-grade API deployment framework for Swarms AI workflows. Easily deploy, scale, and manage your swarm-based applications seamlessly. Features ? - ?? Fast API-based deployment framework - ?? Support for synchronous and asynchronous swarm execution - ?? Built-in load balancing and scaling - ?? Real-time monitoring and logging - ??? Enterprise-grade error handling - ?? Priority-based task execution - ?? Simple deployment and configuration - ?? Extensible plugin architecture Github: https://buff.ly/494zmhC Install: $ pip3 install -U swarm-deploy pls like, repost, and share your thoughts in the comments ??
Agora
非盈利组织
Open-source AI Research Collective advancing multi-modal learning, adaptability, & collaboration. Over 8200+ members.
关于我们
Agora Lab is an open-source collective of AI engineers and creators with a clear mission: to harness the power of artificial intelligence (AI) for the betterment of humanity. Guided by core principles like “Humanity First,” open collaboration, and a focus on projects with broad, positive impacts, Agora is pushing the boundaries of AI, while keeping its work transparent and accessible to all. Agora Lab welcomes contributions from the AI community in a variety of ways. While core project development is managed by a dedicated team, we offer numerous opportunities for you to engage with our work and contribute meaningfully: Daily Paper Club: Join us every night as we review and discuss the latest AI research papers. This is a great way to stay on top of the newest developments in the field and connect with other AI enthusiasts. Paper Implementation Night: Participate in live coding sessions where we work together to implement new research papers in PyTorch. These hands-on sessions help deepen your understanding of AI models and techniques. Collaborate on Projects: If you’re passionate about AI and want to contribute, you can get involved by forking our repositories or submitting pull requests to improve existing projects. However, major contributions and resource allocation decisions are handled by the core team to ensure effective progress. You can also join the community by joining our Discord, where we discuss ongoing projects, research ideas, and other AI topics with like-minded individuals. If you’re interested in becoming part of the Agora Research team, please reach out to Kye Gomez at [email protected]. Join us in advancing AI research! Explore more at our blog: https://agoralab.ai/ Follow us on Twitter for updates: https://buff.ly/3z3qj31 Github: https://buff.ly/3ASQ72g Join our discord now and invite your friends: https://buff.ly/4bNu6Pm
- 网站
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https://agoralab.ai/
Agora的外部链接
- 所属行业
- 非盈利组织
- 规模
- 2-10 人
- 类型
- 非营利机构
- 创立
- 2023
动态
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[New Update Swarms 6.2.8] Our latest swarms update provides 10x better output formatting with clear output visualization among many bug fixes! ? Rich Agent output formatting ? Bug fixes and better error handling ? Fixed streaming for Agent with beautiful formatting ? Fixed bugs for AgentRearrange Get your update Now: $ pip3 install -U swarms Github: https://buff.ly/444kDjA Docs: https://buff.ly/3WjgVRq Like, repost, and share with friends
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Introducing FluidAPI ???? Welcome to FluidAPI, is an all-new agent-powered framework that allows you to interact with APIs using natural language. No more JSON, headers, or complex formats—simply describe your request in plain English, and FluidAPI will do the rest. Github: https://buff.ly/3YXmrta pls like, repost, and share your thoughts below ??
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New Walkthrough ? LLMs vs Agents: Why Agents Are Superior for Real-World Deployment This analysis dissects the fundamental distinctions between LLMs and agents, demonstrates why LLMs are restricted to sandbox environments, and provides empirical reasons why agents are the only viable solution for deploying AI into meaningful, value-adding activities in the world. Read Now: https://buff.ly/4i9jhvk Pls like, repost, and share your thoughts in the comments!
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Introducing Statistical Model Evaluator ???? A robust, production-ready framework for statistically rigorous evaluation of language models, implementing the methodology described in "A Statistical Approach to Model Evaluations" (2024) from Anthropic ?? Features ? Statistical Robustness: Leverages Central Limit Theorem for reliable metrics ? Clustered Standard Errors: Handles non-independent question groups ? Variance Reduction: Multiple sampling strategies and parallel processing ? Paired Difference Analysis: Sophisticated model comparison tools ? Power Analysis: Sample size determination for meaningful comparisons Github: https://buff.ly/4hTXSWJ Paper: https://buff.ly/3OijwX0 Like, repost, and share your thoughts below!
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Swarms Framework Environment Configuration? This guide details the environment variables used in the Swarms framework for configuration and customization of your agent-based applications! Read Now https://buff.ly/40WDLkQ Like, repost, and share your thoughts below ??
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How to Reach 1 Billion Americans by 2030: A Policy Blueprint for Population Growth without Immigration This analysis presents a comprehensive framework to achieve the goal of 1 Billion Americans assuming no Immigration, focusing solely on internal demographic growth through family-oriented economic incentives, policy reform, and cultural shifts. We will discuss empirical-backed methods, such as eliminating taxes for families with five or more children, enhancing parental support, and other policy innovations that could stimulate a major population boom. Read it Now: https://buff.ly/4fB9exa Like, repost, and share your thoughts in the comments!
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Introducing, BackTesterAgent ?? An enterprise-grade AI-powered backtesting framework built on the Swarms framework for automated trading strategy validation and optimization. Features ? Advanced Technical Analysis: Comprehensive suite of technical indicators (SMA, RSI, MACD) ? Real-Time Data Integration: Seamless integration with Yahoo Finance for live market data ? AI-Powered Decision Making: Leveraging GPT-4 or any LLM through the Swarms framework ? Robust Portfolio Management: Sophisticated position tracking and trade execution ? Performance Analytics: In-depth metrics including Sharpe ratio and maximum drawdown Github: https://buff.ly/3YTSD0w Installation: $pip3 install -U backtester-agent Like, repost, and share your thoughts in the comments!
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Introducing the All-New Swarms Framework Version 6.0.8 ? The latest release delivers enhanced flexibility for swarm execution (CPU/GPU), improved auto-prompt generation, and expanded output formats including PDFs, Markdown files, and more! ? ClusterOps Integration: CPU/GPU resource management for swarm mechanisms ? Async batch processing with streaming support for AgentRearrange ? Universal artifact generation (PDF/MD/TXT) in the Agent Mechanism ? Advanced agent scheduling & monitoring in the Agent Mechanism ? Many bug fixes and bootup enhancements Get your update now: pip3 install -U swarms ?? Documentation: https://buff.ly/3OeUB6L ?? GitHub: https://buff.ly/444kDjA Like, repost, and share your feedback in the comments ??
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Swarm vs. Hivemind: Understanding Collective Intelligence Learn the differences between a swarm and a hivemind with my latest blog Read Now: https://buff.ly/4eAc70a Like, repost, and share your thoughts in the comments
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