#Weaviate

Enhance document interaction with a tool that allows chatting with PDF and DOCX files using ChatGPT. Developed during a Bellingcat hackathon, the project involves integration with Weaviate and Cloudflare R2. The tool is installed with Node v18 using a T3 Stack architecture, including Next.js, Tailwind CSS, and tRPC, suitable for efficient document vectorization and indexing.

Discover Verba, an open-source platform that streamlines Retrieval-Augmented Generation (RAG) with extensive model support from Weaviate, Ollama, Huggingface, and OpenAI. Facilitate data exploration with cutting-edge RAG techniques and a smart database, suited for local and cloud deployments. Features like predictive autocomplete and an adaptable interface make it an ideal choice for those seeking efficient data inquiry and document analysis.

Discover comprehensive examples of Weaviate's capabilities, covering technology integrations and features such as vector, hybrid, and generative search. Learn about search enhancement through reranking and media searches, along with efficiency in data handling using features like multi-tenancy and product quantization. Explore integrations with cloud hyperscalers, compute infrastructures, and data platforms. Keep updated with this dynamic project by contributing or suggesting new features.

VecTextSearch leverages OpenAI's language models to convert text into vectors, facilitating efficient similarity searches in the Weaviate database. Built with Golang, it provides a user-friendly REST API for locating related texts, making it useful for content recommendation, plagiarism detection, and intelligent Q&A systems. It improves similarity search capabilities, offering sophisticated solutions for finding similar articles and enhancing content recommendations.

Weaviate is a cloud-native, open-source vector database focused on speed and scalability. It converts data into searchable vectors using advanced ML models, enabling rapid retrieval. Modules and integration with AI/ML tools like OpenAI make it adaptable for software and data engineers as well as data scientists.