Today's LLM & Language Models: Fastest-Growing Projects — April 28, 2026
Today's the LLM & Language Models space, we've seen a surge of interest in tools that enable users to build and interact with large language models in more efficient and effective ways. Specifically, there's been a focus on developing personal knowledge bases and wikis using LLMs, as well as creating systems that can remove AI-generated "slop" from language outputs.
OpenAI's privacy-filter repository has seen significant growth this week, with a Growth Score of 95.32 and 1,662 stars. This tool is designed to filter out personally identifiable information (PII) from text data, making it an essential resource for developers working with sensitive user data. Its popularity can be attributed to the growing importance of data privacy in AI development.
In contrast, hexiecs' talk-normal repository has a more modest Growth Score of 50.35, but still boasts an impressive 1,516 stars. This system prompt is designed to make any LLM "talk like a normal person" by removing AI-generated slop from language outputs. Its growth can be attributed to the increasing demand for more natural and human-like language generation in applications such as chatbots and virtual assistants.
sdyckjq-lab's llm-wiki-skill repository has a Growth Score of 48.72 and 1,152 stars, making it another popular tool this week. This skill is based on Karpathy's llm-wiki method and supports building personal knowledge bases across multiple platforms. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
chiefautism's privacy-parser repository has a Growth Score of 46.30, with 364 stars. This tool is essentially the reverse of OpenAI's privacy-filter, returning PII as structured spans instead of masking them. Its growth can be attributed to the growing demand for more nuanced and flexible data processing tools in AI development.
lucasastorian's llmwiki repository has a Growth Score of 33.10, with 701 stars. This is an open-source implementation of Karpathy's LLM Wiki, allowing users to upload documents and connect their Claude account via MCP. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
amitshekhariitbhu's llm-internals repository has a Growth Score of 32.75, with 790 stars. This resource provides a step-by-step guide to learning LLM internals, covering topics such as tokenization, attention, and inference optimization. Its growth can be attributed to the increasing demand for more in-depth knowledge about how LLMs work.
atomicmemory's llm-wiki-compiler repository has a Growth Score of 28.20, with 811 stars. This tool is designed to compile raw sources into interlinked wiki outputs, inspired by Karpathy's LLM Wiki pattern. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
xoai's sage-wiki repository has a Growth Score of 27.31, with 477 stars. This tool is an LLM-compiled personal knowledge base that extracts concepts, discovers cross-references, and makes everything searchable. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
kessler's gemma-gem repository has a Growth Score of 27.20, with 849 stars. This tool runs Google's Gemma 4 model entirely on-device via WebGPU, eliminating the need for API keys or cloud services. Its growth can be attributed to the increasing demand for more private and secure AI solutions.
VectifyAI's OpenKB repository has a Growth Score of 26.15, with 556 stars. This is an open LLM knowledge base that allows users to build and interact with their own knowledge bases using LLMs. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
OpenAI's privacy-filter repository has seen significant growth this week, with a Growth Score of 95.32 and 1,662 stars. This tool is designed to filter out personally identifiable information (PII) from text data, making it an essential resource for developers working with sensitive user data. Its popularity can be attributed to the growing importance of data privacy in AI development.
In contrast, hexiecs' talk-normal repository has a more modest Growth Score of 50.35, but still boasts an impressive 1,516 stars. This system prompt is designed to make any LLM "talk like a normal person" by removing AI-generated slop from language outputs. Its growth can be attributed to the increasing demand for more natural and human-like language generation in applications such as chatbots and virtual assistants.
sdyckjq-lab's llm-wiki-skill repository has a Growth Score of 48.72 and 1,152 stars, making it another popular tool this week. This skill is based on Karpathy's llm-wiki method and supports building personal knowledge bases across multiple platforms. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
chiefautism's privacy-parser repository has a Growth Score of 46.30, with 364 stars. This tool is essentially the reverse of OpenAI's privacy-filter, returning PII as structured spans instead of masking them. Its growth can be attributed to the growing demand for more nuanced and flexible data processing tools in AI development.
lucasastorian's llmwiki repository has a Growth Score of 33.10, with 701 stars. This is an open-source implementation of Karpathy's LLM Wiki, allowing users to upload documents and connect their Claude account via MCP. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
amitshekhariitbhu's llm-internals repository has a Growth Score of 32.75, with 790 stars. This resource provides a step-by-step guide to learning LLM internals, covering topics such as tokenization, attention, and inference optimization. Its growth can be attributed to the increasing demand for more in-depth knowledge about how LLMs work.
atomicmemory's llm-wiki-compiler repository has a Growth Score of 28.20, with 811 stars. This tool is designed to compile raw sources into interlinked wiki outputs, inspired by Karpathy's LLM Wiki pattern. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
xoai's sage-wiki repository has a Growth Score of 27.31, with 477 stars. This tool is an LLM-compiled personal knowledge base that extracts concepts, discovers cross-references, and makes everything searchable. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.
kessler's gemma-gem repository has a Growth Score of 27.20, with 849 stars. This tool runs Google's Gemma 4 model entirely on-device via WebGPU, eliminating the need for API keys or cloud services. Its growth can be attributed to the increasing demand for more private and secure AI solutions.
VectifyAI's OpenKB repository has a Growth Score of 26.15, with 556 stars. This is an open LLM knowledge base that allows users to build and interact with their own knowledge bases using LLMs. Its growth can be attributed to the increasing interest in using LLMs for knowledge management and information retrieval.