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71 lines
4.2 KiB
Markdown
71 lines
4.2 KiB
Markdown
#
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<p align="center">
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<img src="https://raw.githubusercontent.com/neuml/txtai/master/logo.png"/>
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</p>
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<h3 align="center">
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<p>Build AI-powered semantic search applications</p>
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</h3>
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<p align="center">
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<a href="https://github.com/neuml/txtai/releases">
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<img src="https://img.shields.io/github/release/neuml/txtai.svg?style=flat&color=success" alt="Version"/>
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</a>
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<a href="https://github.com/neuml/txtai">
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<img src="https://img.shields.io/github/last-commit/neuml/txtai.svg?style=flat&color=blue" alt="GitHub last commit"/>
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</a>
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<a href="https://github.com/neuml/txtai/issues">
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<img src="https://img.shields.io/github/issues/neuml/txtai.svg?style=flat&color=success" alt="GitHub issues"/>
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</a>
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<a href="https://join.slack.com/t/txtai/shared_invite/zt-1cagya4yf-DQeuZbd~aMwH5pckBU4vPg">
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<img src="https://img.shields.io/badge/slack-join-blue?style=flat&logo=slack&logocolor=white" alt="Join Slack"/>
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</a>
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<a href="https://github.com/neuml/txtai/actions?query=workflow%3Abuild">
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<img src="https://github.com/neuml/txtai/workflows/build/badge.svg" alt="Build Status"/>
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</a>
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<a href="https://coveralls.io/github/neuml/txtai?branch=master">
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<img src="https://img.shields.io/coveralls/github/neuml/txtai" alt="Coverage Status">
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</a>
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</p>
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-------------------------------------------------------------------------------------------------------------------------------------------------------
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txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications.
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Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords.
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Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid pace, models can understand concepts in documents, audio, images and more.
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Summary of txtai features:
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- 🔎 Large-scale similarity search with multiple index backends ([Faiss](https://github.com/facebookresearch/faiss), [Annoy](https://github.com/spotify/annoy), [Hnswlib](https://github.com/nmslib/hnswlib))
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- 📄 Create embeddings for text snippets, documents, audio, images and video. Supports transformers and word vectors.
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- 💡 Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction
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- ↪️️ Workflows that join pipelines together to aggregate business logic. txtai processes can be microservices or full-fledged indexing workflows.
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- 🔗 API bindings for [JavaScript](https://github.com/neuml/txtai.js), [Java](https://github.com/neuml/txtai.java), [Rust](https://github.com/neuml/txtai.rs) and [Go](https://github.com/neuml/txtai.go)
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- ☁️ Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes)
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Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. Semantic workflows transform and find data driven by user intent.
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The following applications are powered by txtai.
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| Application | Description |
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|:----------|:-------------|
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| [paperai](https://github.com/neuml/paperai) | AI-powered literature discovery and review engine for medical/scientific papers |
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| [tldrstory](https://github.com/neuml/tldrstory) | AI-powered understanding of headlines and story text |
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| [neuspo](https://neuspo.com) | Fact-driven, real-time sports event and news site |
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| [codequestion](https://github.com/neuml/codequestion) | Ask coding questions directly from the terminal |
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txtai is built with Python 3.7+, [Hugging Face Transformers](https://github.com/huggingface/transformers), [Sentence Transformers](https://github.com/UKPLab/sentence-transformers) and [FastAPI](https://github.com/tiangolo/fastapi)
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