AI & Machine Learning projects
LLMs, agents, inference runtimes, vector databases, and ML tooling — projects pushing the AI frontier.
36 projects tracked.
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All →Top 36 in AI & Machine Learning
PopScore over the last 7 day(s)
- Pop0C++#llm#inference#cpp71.8k10.4kMinimal-dependency C/C++ LLM inference engine with broad hardware support and aggressive quantization.
Local knowledge-base QA based on Langchain and ChatGLM.
SlowingEnterprisePop0Python#rag#llm#chatbot31.4k5.8k- Pop0Python21.0k1.8k
- Pop0Python#stable-diffusion#image-gen#ai56.3k5.8k
- Pop0Python#nlp#ml#python30.4k4.5k
- Pop0Python#agents#llm#multi-agent42.8k5.1k
- Pop0C++#whisper#asr#cpp36.2k3.4k
- Pop0Python#dashboard#ml-ui#demos38.4k2.4k
- Pop0Python#llm#nlp#transformers132.0k26.5k
- Pop0Python#llm#agents#rag95.4k15.2k
Visual framework for building multi-agent and RAG applications.
SlowingEnterprisePop0Python#agents#llm#low-code28.5k4.3k- Pop0Python#image-gen#stable-diffusion42.5k3.2k
- Pop0Python#ai#convert#documents65.0k4.8k
A cloud-native vector database, storage for next-gen AI applications.
SlowingEnterprisePop0Go#vector-search#ai#similarity30.4k2.8k- Pop0Python#mlops#tracking#experiments20.4k4.2k
Easily train a good VC model with voice data <= 10 mins!
HealthyEnterprisePop0Python#change#sovits#vits37.5k4.4k- Pop0Python#openai#llm#sdk22.4k3.6k
- Pop0Python#asr#speech#openai78.5k8.4k
Enhanced ChatGPT clone with multi-provider support, agents, and plugins.
SlowingEnterprisePop0TypeScript#chatgpt#ai#llm24.5k4.2kAISelf-hostable multi-provider ChatGPT-compatible UI with agents, plugins, and code execution.expand
Self-hostable multi-provider ChatGPT-compatible UI with agents, plugins, and code execution.- Pop0Rust#vector-db#embeddings#search21.4k1.5k
Ray is a unified framework for scaling AI and Python applications.
SlowingEnterprisePop0Python#distributed#ml#scaling35.4k5.8kData framework for LLM applications — connect custom data to LLMs.
SlowingEnterprisePop0Python#rag#llm#framework38.5k5.2k- Pop0Python#machine-learning#python#models60.4k25.2k
- Pop0Go#llm#ai#local89.5k6.8k
AIOne-binary local LLM runner with a simple `ollama run` UX and broad model support.expand
One-binary local LLM runner with a simple `ollama run` UX and broad model support. - Pop0TypeScript#scraping#llm#crawler18.9k1.4k
AIWeb scraper API that turns any site into clean markdown for LLM ingestion, with JS-rendering and anti-bot handling.expand
Web scraper API that turns any site into clean markdown for LLM ingestion, with JS-rendering and anti-bot handling. - Pop0TypeScript#claude#agent#cli18.6k1.1k
- Pop0Python#llm#fine-tuning#training18.2k1.4k
Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.
SlowingMaturePop0Rust#ai#context#embedded16.4k1.2k- Pop0Python#vector-db#embeddings#rag14.8k1.3k
- Pop0C#vector-search#postgres#extension14.2k580
- Pop0Go#vector-search#ai#semantic-search11.4k720
- Pop0TypeScript#openai#llm#sdk8.9k1.2k
- Pop0Python#agents#llm#graph6.8k920
AIGraph-based orchestration for stateful LLM agents with cycles, retries, and persistence.expand
Graph-based orchestration for stateful LLM agents with cycles, retries, and persistence. - Pop0TypeScript#agents#sandbox#llm6.4k580
AIEphemeral firecracker sandboxes for AI agents — safe code execution in <200ms cold start.expand
Ephemeral firecracker sandboxes for AI agents — safe code execution in <200ms cold start. - Pop0Jupyter Notebook#llm#course#alignment6.4k580
AIHands-on, code-first course for aligning small LLMs (SFT + DPO + eval) on a single GPU.expand
Hands-on, code-first course for aligning small LLMs (SFT + DPO + eval) on a single GPU. 1M real LLM conversations with human preferences (research dataset).
SlowingMaturePop0Python#dataset#llm#research3.8k380
How GitPop ranks projects
Read the full methodology- What is PopScore?
- A 0–100 score combining star velocity (35%), fork engagement (20%), activity (25%), mentions (10%), and a noise filter (10%). Details →
- Why not just use GitHub Trending?
- Trending is dominated by awesome-* lists and tutorial repos. We weight commits and merged PRs above raw stars, and apply a noise penalty for content-only repos. Details →
- How is the AI Snapshot generated?
- An LLM summarizes each repo's README into strict JSON — TL;DR, 3 key features, difficulty rating. Cached and refreshed automatically. Details →