I am Abdulkader Safi

In an era where accessibility and content consumption are evolving rapidly, text-to-speech (TTS) technology has become increasingly important. Whether you're creating audiobooks, accessibility tools, or voice assistants, high-quality speech synthesis is essential. However, converting technical documentation, code snippets, and markdown-formatted content into natural-sounding speech presents unique challenges. I recently built a modern Text-to-Speech application that addresses these challenges head-on by combining Coqui TTS for high-quality speech synthesis with Ollama's LLM capabilities for intelligent text preprocessing. The result is a full-stack application that can handle everything from simple text to complex technical documentation with code blocks, markdown formatting, and technical terminology. In this article, I'll walk you through the architecture, implementation details, and key learnings from building this project.

A Retrieval-Augmented Generation (RAG) system that processes PDF documents with OCR support and enables question-answering using local LLMs via Ollama. Features parallel processing, smart caching, image deduplication, and FAISS vector search for efficient document analysis.