txtai
All-in-one semantic search, RAG, and LLM workflow engine — embeddings, vector DB, and pipelines in one library.
txtai
txtai is an all-in-one open-source embedding database that powers semantic search, LLM orchestration, and language model workflows. It combines a vector store, sparse retrieval, RAG pipelines, and workflow automation into a single lightweight library with minimal dependencies.
Key Features
- Embeddings database: vector + keyword hybrid search in a single index
- RAG pipelines: retrieval-augmented generation with any LLM (OpenAI, Hugging Face, Ollama)
- LLM workflows: chain extractors, summaries, translations, classifiers, and custom steps
- Graph networks: build knowledge graphs from document collections
- Multimodal: text, image, audio, video embeddings
- API server: YAML-config-driven REST API, no code needed
Quick Start
from txtai import Embeddings
embeddings = Embeddings(path="sentence-transformers/nli-mpnet-base-v2")
embeddings.index(["US tops all nations in gold medals",
"Weightlifting athlete sets new record"])
result = embeddings.search("athletic performance")
print(result) # [(0, 0.75), (1, 0.63)]
Install via ai-supply
npx ai-supply add txtai-semantic-search-pipeline
Curated mirror of the open-source txtai (Apache-2.0). Get it from the source.
Compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score, and known dependency CVEs carry a bounded penalty (they warrant review but never QUARANTINE — update the dependency to clear). Other dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to its OWASP control below.
Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not, except a known CVE, which carries a small bounded penalty (high/critical → Review).
The same gate an agent runs before installing (POST /api/v1/trust/txtai-semantic-search-pipeline/check). Click a policy:
Consume txtai programmatically. Authenticate with an API key or session — see Authorize an agent.
# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/txtai-semantic-search-pipeline
# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/txtai-semantic-search-pipeline/check \
-H "Content-Type: application/json" \
-d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'
# CLI
npx ai-supply add txtai-semantic-search-pipeline
# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/txtai-semantic-search-pipeline/install \
-H "Authorization: Bearer $AIM_KEY"
# MCP tool
install_listing({ "slug": "txtai-semantic-search-pipeline" })OpenAPI spec →Curated mirror — latest upstream source. See the repository for tagged releases.