InfiniFlow maintains a notable public GitHub presence with a range of repositories primarily focused on AI and data processing. Their key projects include RAGFlow, a Retrieval-Augmented Generation engine built in Python, and infinity, an AI-native database developed in C++. The organization utilizes languages such as C++, Python, MDX, and TeX across their repositories.
Top languages
Public repositories
ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
infinity
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
ragflow-docs
No description provided for this repository.
ragflow-skills
Skills for RAGFlow dataset api
coding-tasks
No description provided for this repository.
infinity-docs
No description provided for this repository.
github-runner-dockerfile
Dockerfile for the creation of a GitHub Actions runner image to be deployed dynamically
finity
Repo for CI Testing
resource
No description provided for this repository.
faiss
A library for efficient similarity search and clustering of dense vectors.
ragflow_test
No description provided for this repository.
graspologic
Python package for graph statistics
Frequently asked questions
What does InfiniFlow build on GitHub?
InfiniFlow develops several repositories on GitHub, including RAGFlow, which is a Retrieval-Augmented Generation engine and infinity, an AI-native database. Their projects focus on enhancing AI capabilities and data management.
Which programming languages does InfiniFlow use?
InfiniFlow's public repositories are primarily built using C++, Python, MDX, and TeX. These languages support their projects' diverse functionalities, from data processing to documentation.
Are InfiniFlow's repositories public?
Yes, all of InfiniFlow's repositories on GitHub are public. This transparency allows users and developers to access, contribute to, and learn from their projects.
Is this exposure intended?
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