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Data & context

txtai

Combines retrieval storage and model workflows in one Python application framework.

Overview

Research summary

txtai is a Python AI framework centered on an embeddings database that combines vector indexes, graph relationships, and relational data. It provides semantic search and retrieval capabilities alongside model pipelines for tasks such as question answering, summarization, and transcription. Developers can connect pipelines into workflows or agents and expose functionality through web or MCP APIs. The framework can run locally or in containerized deployments. This entry treats txtai primarily as retrieval and context infrastructure while retaining its broader application-building capabilities.

Repository summary

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Open issues
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Last push
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Commits, 90 days
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Repository activity
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Version
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Recorded catalogue figures. View repository data and provenance →

Classification

Pricing & services

Paid services unknown

Whether the provider offers paid products or services has not been established.

Licence scope

Implementation

Recorded implementation details and interfaces for txtai.

Implementation details

Python embeddings database, pipeline framework, and API service

Languages
Python
Repository type
source

Recorded interfaces and capabilities

Licence scope

Repository

Repository snapshots, release information and recorded maintenance signals.

Repository snapshot

neuml/txtai ↗

Stars
Unavailable
Open issues
Unavailable
Last push
Unavailable
Commits, 90 days
Unavailable
Repository activity
Not scored
Archived
Not recorded

Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).

Maintenance and provenance

Catalogue snapshot
2026-10-06

Documentation

Recorded references and research provenance for this entry.

Recorded sources 4

Research metadata

Research date
2026-10-02
Catalogue snapshot
2026-10-06