Pathway AI Pipelines
Accelerates the deployment of high-accuracy RAG and AI enterprise search applications that integrate and synchronize with diverse live data sources.
Acerca de
Pathway's AI Pipelines offer ready-to-deploy LLM (Large Language Model) App Templates designed to put high-accuracy Retrieval-Augmented Generation (RAG) and AI enterprise search applications into production quickly. These pipelines continuously sync with various live data sources like file systems, Google Drive, SharePoint, S3, Kafka, and PostgreSQL, ensuring applications always operate with the most up-to-date information. They are Docker-friendly, support cloud or on-premises deployment, and include built-in data indexing capabilities for vector, hybrid, and full-text search without external infrastructure dependencies.
Características Principales
- Provides ready-to-deploy LLM App Templates for various RAG and AI search scenarios
- Scales AI applications to handle millions of documents and pages
- Synchronizes in real-time with diverse data sources including Google Drive, SharePoint, S3, Kafka, and PostgreSQL
- 25,278 GitHub stars
- Offers Docker-friendly deployment with exposed HTTP APIs and optional Streamlit UIs
- Includes built-in, performant data indexing for vector, hybrid, and full-text search
Casos de Uso
- Building end-to-end question-answering RAG applications over live document streams
- Creating real-time document indexing and vector store services for use with Langchain or Llamaindex
- Extracting and structuring information from unstructured documents, including charts and tables, using multimodal RAG
