Ultra-Lightweight 1M Parameter OCR Model 'Indra' Released: 49 Pages per Second on CPU
Vik Paruchuri has released Indra, an ultra-lightweight 1M parameter OCR model capable of processing 49 pages per second on CPU. Delivering 11x faster speeds tha
TAU-HOME.COM stories tagged RAG.
Vik Paruchuri has released Indra, an ultra-lightweight 1M parameter OCR model capable of processing 49 pages per second on CPU. Delivering 11x faster speeds tha
Google has launched EmbeddingGemma 2, an open 740M-parameter multimodal embedding model for text, code, images, video, and audio on local devices, now on Huggin
LlamaIndex launched OpenDocRouter, placing 10 document parsing models behind one API. One-line model swaps and ParseBench quality/cost scores are the core of th
A faithful translation of the two verified entries (Unstructured and Docling) from @DivyanshT91162's list of document-parsing GitHub repositories, with official
A technical breakdown of 10 open-source web scraping tools from Crawlee and Scrapy to Crawl4AI, exploring anti-bot evasion, concurrency, and LLM RAG markdown pi
A comprehensive breakdown of 10 key open-source repositories—including Perplexica, SearXNG, Meilisearch, Qdrant, and Weaviate—for building self-hosted AI search
A step-by-step guide to connecting Google NotebookLM to Claude Code via MCP to query extensive documentation without context bloating or hallucinations.
A practical guide to 10 open-source GitHub tools—including Context7, Serena, and Repomix—and 3 specialized pipelines designed to feed AI agents minimal, high-pr
An open-source reference course and production architecture covering OpenSearch 2.19 hybrid search, Docling paper parsing, Airflow pipelines, LangGraph agentic
A repository featuring over 100 open-source AI agents, RAG applications, and agent skills ready for cloning and deployment. Supports various LLMs and released u
Tencent has released WeKnora v0.8.0, transforming its open-source LLM knowledge platform into an agentic RAG system with session sandboxing, cross-session memor
Impact-Site-Verification: 9b3ebd10-6c45-44cf-a014-5b8c19b7b285