TxtAI - Simplifying RAG and Semantic Search with an All-in-One Embeddings Database

Explore the powerful capabilities of TxtAI, an all-in-one solution for advanced text processing and analysis, in this comprehensive 13-minute tutorial. Learn to leverage TxtAI for semantic search, language model workflows, and various text analysis tasks. Discover how to create embeddings, conduct semantic searches, and perform SQL queries. Delve into advanced features like keyword search, dense vector indexing, and hybrid search techniques. Gain practical skills in setting up TxtAI, managing embeddings, and creating RAG-based applications. Perfect for beginners and advanced users alike, this tutorial provides valuable insights into enhancing text processing capabilities using TxtAI's versatile platform.

- Introduction to TxtAI
- Setting Up the TxtAI Embeddings Database
- Understanding SPSE and DSE Indexing in TxtAI
- Text Vectorization and Indexing Techniques in TxtAI
- Overview of the Tutorial Content
- Creating a Conda Environment for TxtAI
- Installing and Configuring TxtAI
- Conducting Semantic Search with TxtAI
- Saving and Managing Embeddings in TxtAI
- Keyword Search and Dense Vector Indexing in TxtAI
- Hybrid Search: Combining Sparse and Dense Indexes in TxtAI
- Using LLM for Advanced Text Queries in TxtAI
- Creating a RAG Based Application with TxtAI
- Setting Up Language Model Workflows in TxtAI
- Conclusion and Final Thoughts