#python #deepseek #demo #easy #embedding #flask #gpt #huggingface_transformers #llm #mcp #multimodal #openai #qwen #rag #sentence_transformers #ui #vllm #vlm

UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles.

https://github.com/OpenBMB/UltraRAG

#cplusplus #ann_search #embedded_database #rag #vector_search #vectordb

Zvec is a lightweight, open-source vector database built on Alibaba's Proxima engine that searches billions of vectors in milliseconds. You can install it instantly with a single command and start using it within seconds—no servers or complex configuration needed. It supports both dense and sparse vector embeddings, hybrid search combining semantic similarity with filters, and runs anywhere your code runs, from notebooks to edge devices. The key benefit is that you get production-grade, low-latency similarity search with minimal setup, making it ideal for AI applications like semantic search, recommendation systems, and retrieval-augmented generation without the overhead of traditional database infrastructure.

https://github.com/alibaba/zvec