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Use Cases
The following sections give an overview of the main txtai use cases. A comprehensive set of over 50 example notebooks and applications are also available.
Semantic Search
Build semantic/similarity/vector/neural search applications.
Traditional search systems use keywords to find data. Semantic search has an understanding of natural language and identifies results that have the same meaning, not necessarily the same keywords.
Get started with the following examples.
| Notebook | Description | |
|---|---|---|
| Introducing txtai ▶️ | Overview of the functionality provided by txtai |  |
| Build an Embeddings index with Hugging Face Datasets | Index and search Hugging Face Datasets | |
| Add semantic search to Elasticsearch | Add semantic search to existing search systems | |
| Semantic Graphs | Explore topics, data connectivity and run network analysis | |
| Embeddings in the Cloud | Load and use an embeddings index from the Hugging Face Hub | |
| Customize your own embeddings database | Ways to combine vector indexes with relational databases | |
LLM Orchestration
Prompt-driven search, retrieval augmented generation (RAG), pipelines and workflows that interface with large language models (LLMs).
Integrate conversational search, LLM chains and self-critique.
| Notebook | Description | |
|---|---|---|
| Prompt-driven search with LLMs | Embeddings-guided and Prompt-driven search with Large Language Models (LLMs) | |
| Prompt templates and task chains | Build model prompts and connect tasks together with workflows | |
Language Model Workflows
Language model workflows, also known as semantic workflows, connect language models together to build intelligent applications.
While LLMs are powerful, there are plenty of smaller, more specialized models that work better and faster for specific tasks. This includes models for extractive question-answering, automatic summarization, text-to-speech, transcription and translation.
| Notebook | Description | |
|---|---|---|
| Run pipeline workflows ▶️ | Simple yet powerful constructs to efficiently process data | |
| Extractive QA with txtai | Introduction to extractive question-answering with txtai | |
| Building abstractive text summaries | Run abstractive text summarization | |
| Text to speech generation | Generate speech from text | |
| Transcribe audio to text | Convert audio files to text | |
| Translate text between languages | Streamline machine translation and language detection | |