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automation

txtai: Supercharge Your AI Projects with One-Click Workflows

Python framework that lets startup founders build semantic search, LLM agents, and intelligent workflows without deep AI engineering expertise.
12,622 stars827 forksPythonUpdated 6/1/2026100% free · open source
What it does

Creates intelligent search and AI workflows by turning text data into smart, semantically-aware indexes that can be queried conversationally

When to use it
  • •Building a custom knowledge base search for your startup's documentation
  • •Creating an AI assistant that can understand context across your company's data
  • •Automating information retrieval and summarization from large text collections
Quick start
  1. 1Install via pip: pip install txtai
  2. 2Create a simple semantic index of your documents
  3. 3Configure search and retrieval parameters
  4. 4Query your index using natural language questions
Ready-to-paste prompt
from txtai import Embeddings

embeddings = Embeddings({'path': 'sentence-transformers/all-MiniLM-L6-v2'})
embeddings.index([(0, 'first document'), (1, 'second document')])
results = embeddings.search('find documents about X', limit=3)

Topics

agents
ai
ai-agents
embeddings
information-retrieval
language-model
large-language-models
llm
nlp
python
rag
retrieval-augmented-generation
search
search-engine
semantic-search
sentence-embeddings
transformers
txtai
vector-database
vector-search
Quick Actions
Details
Creator
neuml
Language
Python
Category
automation
Published
8/9/2020

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