Popular GitHub Repositories for Embeddings Extraction

The Memory layer for AI Agents

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

the AI-native open-source embedding database

? Easy-to-use and powerful NLP and LLM library with ? Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including ?Text Classification, ? Neural Search, ? Question Answering, ?? Information Extraction, ? Document Intelligence, ? Sentiment Analysis etc.

100+ Chinese Word Vectors 上百种预训练中文词向量

Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/

? All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

Retrieval and Retrieval-augmented LLMs

Java version of LangChain

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

An open source library for deep learning end-to-end dialog systems and chatbots.

An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more

Postgres with GPUs for ML/AI apps.

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

Modern columnar data format for ML and LLMs implemented in Rust. Convert from parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

text2vec, text to vector. 文本向量表征工具，把文本转化为向量矩阵，实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型，开箱即用。

OpenMMLab Text Detection, Recognition and Understanding Toolbox

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

农业知识图谱(AgriKG)：农业领域的信息检索，命名实体识别，关系抽取，智能问答，辅助决策

AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation