Retrieval Augmented Generation

AlloyDB is a fork of PostgreSQL on Google Cloud, optimized for high performance with vector embedding & retrieval workloads. As a PostgreSQL-compatible database, AlloyDB can be used as a drop-in replacement for any application that relies on a Postgres backend.…

Local Embeddings with Hugging Face Text Embedding Inference

AI Infrastructure

Embeddings Models, Generative AI, LibreChat, Open Source AI, pgVector, Retrieval Augmented Generation, Vector Databases

Embeddings models convert data into numerical representations that can be stored in a vector database, and retrieved by a large language model through a framework such as LangChain for retrieval augmented generation. A common use case is embedding unstructured data,…

RAG with any AI Model using Postgres pgVector + LibreChat

AI Infrastructure

Anthropic, Azure, Generative AI, LibreChat, LiteLLM, Ollama, OpenAI Alternative, pgVector, PostgreSQL, Retrieval Augmented Generation, Vector Databases

The addition of the RAG API microservice to LibreChat in version 0.7.0, the most rapidly trending open source ChatGPT clone, swings the door open to chatting with PDFs and documents using any supported AI model, in a private, self-hosted environment.…

Integrating Azure OpenAI with Search & Retrieval Plugins for RAG

AI Infrastructure

Azure, Azure AI Search, Cognitive Search, Generative AI, LangChain, LibreChat, OpenAI Compatible API, Retrieval Augmented Generation

If you have ever used ChatGPT Plus, OpenAI’s SaaS GenAI offering, you are likely familiar with the Browsing extension which retrieves current information from the Internet using Bing search to inform the GPT model’s response to the user’s prompts. One…

AI Retrieval Augmented Generation in the (Virtual) Private Cloud

AI Infrastructure

ChatGPT Alternative, GenAI, Generative AI, Open LLM Models, Open Source AI, Private AI, Retrieval Augmented Generation

Retrieval Augmented Generation (RAG) is an AI technique for getting more tailored responses from a foundation model, without the need for training or fine-tuning a model from scratch. Large Language Models, such as Meta’s LLaMA 2, provide high quality responses…