Posts tagged with #rag

Chat With Your Documents & Files Using Ollama & RAG: Local AI That Understands Your Projects

Askimo's RAG (Retrieval-Augmented Generation) with Ollama enables chatting with your documents, research papers, notes, and project files using local AI models like Llama 3, Mistral, and Phi-3. Automatically index PDFs, Word documents, spreadsheets, and text files with smart search. Ask questions about your content in plain English—all locally with zero data leaving your machine. Perfect for researchers, writers, students, and anyone managing large collections of documents.

Askimo Desktop Updates: Built-in Terminal, MCP Integration, RAG Sources Tree, and Image Support

New in Askimo: built-in terminal emulator, Model Context Protocol (MCP) integration, a RAG sources tree to inspect exactly what the assistant used, image-model support for multimodal workflows, and major desktop improvements across performance, reliability, and UX.

Askimo 1.2.0: Smarter Answers, Better Context, and a More Comfortable Experience

Askimo 1.2.0 introduces project-based RAG for answering questions using your documents with jvector and Apache Lucene search. Attach PDFs, spreadsheets, images, or code directly in conversations. Docker AI support joins OpenAI, Claude, Gemini, and Ollama. Enhanced project sessions organize knowledge-based chats. Responsive design works across all screen sizes. macOS installer now fully notarized for secure installation.