v3.0.0

txtai 3.0.0 is a major release with a significant number of new features. This release overhauls the project structure, consolidates logic into pipelines and introduces workflows. 

Summary of txtai features:

- 🔎 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))
- 📄 Create embeddings for text snippets, documents, audio and images. Supports transformers and word vectors.
- 💡 Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction
- ↪️️ Workflows that join pipelines together to aggregate business logic. txtai processes can be microservices or full-fledged indexing workflows.
- 🔗 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)
- ☁️ Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes)

New Features
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- Add Docker file for API (#59)
- Require Faiss 1.7.0 (#60)
- Add summary pipeline (#65)
- Add text extraction pipeline (#66)
- Add transcription pipeline (#67)
- Add translation pipeline (#68)
- Add workflow framework (#69)
- Add additional pipeline abstraction layer for tensor frameworks (#70)
- Add tests for new v3 functionality (#71)
- Add notebooks covering new v3 functionality (#73)
- Add Pipeline Factory (#76)
- Add API extensions (#77)
- Add workflow builder application (#80)
- Add text segmentation pipeline (#81)
- Add workflow to API (#82)
- Add service workflow task (#83)
- Add object storage workflow task (#84)
- Add URL workflow task (#85)

Improvements
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- Refactor code into smaller components and modules (#63)
- Modify pipeline to accept GPU device id (#64)
- Allow direct download of sentence-transformer models (#72)
- Update documentation, add site through GitHub pages (#75)
- Modularize the API (#78)
- Add default truncation to pipelines (#79)

Bug Fixes
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- Non intuitive behaviour of Tokenizer (#61)
- [Python 3.9, Mac OS] Code hangs while building embedding index (#62)
- embeddings.index Truncation RuntimeError: The size of tensor a (889) must match the size of tensor b (512) at non-singleton dimension 1 (#74)