Today's AI Frameworks & SDKs: Fastest-Growing Projects — May 22, 2026
Today's the AI Frameworks & SDKs space, we see a continued surge in projects focused on enhancing performance and scalability for large language models (LLMs). The most notable trend is the emergence of tools designed to optimize LLM inference engines and multi-agent frameworks tailored specifically for financial analysis and gaming. One standout project is lightseekorg/tokenspeed, which offers a high-performance solution for speeding up LLM inferences.
TokenSpeed by lightseekorg is a speed-of-light LLM inference engine that aims to accelerate the processing of large language models. With its impressive growth score of 61.88 and over 1,074 stars on GitHub, it's clear that developers are keenly interested in tools that can significantly enhance performance for tasks requiring rapid model evaluations.
Simonlin1212/TradingAgents-astock introduces a multi-agent investment research framework specifically designed for the A-share market, offering unique features such as bull/bear debates and risk assessments. This project has gained traction with a growth score of 56.61 and 485 stars, indicating strong interest from developers seeking sophisticated AI-driven tools for financial analysis.
The MaaNTE repository by 1bananachicken is an automation assistant for Neverness to Everness that includes features such as auto-fishing and daily reward claiming. Despite its unique gaming focus, it has amassed a significant following with 1,445 stars, reflecting the growing demand for AI-driven tools in gaming communities.
Noonghunna/club-3090 is another noteworthy project, providing community recipes to serve LLMs on RTX 3090 GPUs, making it model-agnostic and compatible with various engines. This repository's growth score of 37.12 and 1,029 stars suggest that developers are actively seeking solutions for optimizing GPU performance in diverse AI applications.
Jhaizhou-ops/pinrule offers a universal framework for setting rules to guide AI behavior during long tasks, ensuring consistency without requiring continuous network access or dependency on specific language models. This tool's growth score of 35.11 and modest star count hint at its niche but growing importance in scenarios where strict control over AI behavior is essential.
TheRunicDev/MaaNTE, also related to gaming automation, provides an assistant for auto-fishing and other tasks within the Neverness to Everness game world. With a growth score of 27.75 and 540 stars, it demonstrates steady interest from gamers looking to enhance their in-game experiences through AI.
Stoaaadev/stoa introduces a multi-agent swarm framework with seven autonomous agents designed for decentralized operations without requiring infrastructure setup. Its growth score of 25.88 and 30 stars indicate ongoing development but suggest that the project is still finding its footing within the broader developer community.
Ontos-AI/knowhere focuses on extracting, parsing, and outputting structured data suitable for AI agents and retrieval-augmented generation tasks. This tool's growth score of 24.66 and 371 stars highlight its growing importance in scenarios where structured data processing is critical for efficient AI operation.
Alash3al/stash offers a persistent memory layer for AI agents, storing episodes, facts, and working context within Postgres databases. Its growth score of 23.34 and 698 stars reflect strong developer interest in tools that enhance the operational capabilities of AI agents by providing robust data management features.
Lastly, OmYarewar/PHANTOM presents an AI-powered pentesting command center designed for autonomous security testing with real-time streaming and self-improving AI capabilities. With a growth score of 19.88 and 39 stars, PHANTOM is gaining traction among cybersecurity professionals looking to leverage AI for more efficient penetration testing operations.
Overall, Today's report highlights the diversity and depth of innovation in AI frameworks and SDKs, with projects catering to everything from gaming automation to financial analysis and cybersecurity, each demonstrating unique growth patterns reflective of their respective niches.
TokenSpeed by lightseekorg is a speed-of-light LLM inference engine that aims to accelerate the processing of large language models. With its impressive growth score of 61.88 and over 1,074 stars on GitHub, it's clear that developers are keenly interested in tools that can significantly enhance performance for tasks requiring rapid model evaluations.
Simonlin1212/TradingAgents-astock introduces a multi-agent investment research framework specifically designed for the A-share market, offering unique features such as bull/bear debates and risk assessments. This project has gained traction with a growth score of 56.61 and 485 stars, indicating strong interest from developers seeking sophisticated AI-driven tools for financial analysis.
The MaaNTE repository by 1bananachicken is an automation assistant for Neverness to Everness that includes features such as auto-fishing and daily reward claiming. Despite its unique gaming focus, it has amassed a significant following with 1,445 stars, reflecting the growing demand for AI-driven tools in gaming communities.
Noonghunna/club-3090 is another noteworthy project, providing community recipes to serve LLMs on RTX 3090 GPUs, making it model-agnostic and compatible with various engines. This repository's growth score of 37.12 and 1,029 stars suggest that developers are actively seeking solutions for optimizing GPU performance in diverse AI applications.
Jhaizhou-ops/pinrule offers a universal framework for setting rules to guide AI behavior during long tasks, ensuring consistency without requiring continuous network access or dependency on specific language models. This tool's growth score of 35.11 and modest star count hint at its niche but growing importance in scenarios where strict control over AI behavior is essential.
TheRunicDev/MaaNTE, also related to gaming automation, provides an assistant for auto-fishing and other tasks within the Neverness to Everness game world. With a growth score of 27.75 and 540 stars, it demonstrates steady interest from gamers looking to enhance their in-game experiences through AI.
Stoaaadev/stoa introduces a multi-agent swarm framework with seven autonomous agents designed for decentralized operations without requiring infrastructure setup. Its growth score of 25.88 and 30 stars indicate ongoing development but suggest that the project is still finding its footing within the broader developer community.
Ontos-AI/knowhere focuses on extracting, parsing, and outputting structured data suitable for AI agents and retrieval-augmented generation tasks. This tool's growth score of 24.66 and 371 stars highlight its growing importance in scenarios where structured data processing is critical for efficient AI operation.
Alash3al/stash offers a persistent memory layer for AI agents, storing episodes, facts, and working context within Postgres databases. Its growth score of 23.34 and 698 stars reflect strong developer interest in tools that enhance the operational capabilities of AI agents by providing robust data management features.
Lastly, OmYarewar/PHANTOM presents an AI-powered pentesting command center designed for autonomous security testing with real-time streaming and self-improving AI capabilities. With a growth score of 19.88 and 39 stars, PHANTOM is gaining traction among cybersecurity professionals looking to leverage AI for more efficient penetration testing operations.
Overall, Today's report highlights the diversity and depth of innovation in AI frameworks and SDKs, with projects catering to everything from gaming automation to financial analysis and cybersecurity, each demonstrating unique growth patterns reflective of their respective niches.