txtai 7.0.0

LLM framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data.

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.

John Snow Labs Spark NLP is a natural language processing library built on top of Apache Spark ML. It provides simple, performant & accurate NLP annotations for machine learning pipelines, that scale easily in a distributed environment.

Multimodal AI services & pipelines with cloud-native stack: gRPC, Kubernetes, Docker, OpenTelemetry, Prometheus, Jaeger, etc.

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

FrogBase simplifies the download-transcribe-embed-index workflow for multi-media content. It does so by linking content from various platforms with speech-to-text models, image & text encoders and embedding stores.

Simple inference for large language models

Massive Text Embedding Benchmark

Text utilities and datasets for PyTorch