# Why txtai?
New vector databases, LLM frameworks and everything in between are sprouting up daily. Why build with txtai?
- Up and running in minutes with [pip](../install/) or [Docker](../cloud/)
```python
# Get started in a couple lines
import txtai
embeddings = txtai.Embeddings()
embeddings.index(["Correct", "Not what we hoped"])
embeddings.search("positive", 1)
#[(0, 0.29862046241760254)]
```
- Built-in API makes it easy to develop applications using your programming language of choice
```yaml
# app.yml
embeddings:
path: sentence-transformers/all-MiniLM-L6-v2
```
```bash
CONFIG=app.yml uvicorn "txtai.api:app"
curl -X GET "http://localhost:8000/search?query=positive"
```
- Run local - no need to ship data off to disparate remote services
- Work with micromodels all the way up to large language models (LLMs)
- Low footprint - install additional dependencies and scale up when needed
- [Learn by example](../examples) - notebooks cover all available functionality