Metadata-Version: 2.1
Name: txtai
Version: 1.0.0
Summary: AI-powered search engine
Home-page: https://github.com/neuml/txtai
Author: NeuML
License: Apache 2.0: http://www.apache.org/licenses/LICENSE-2.0
Project-URL: Documentation, https://github.com/neuml/txtai
Project-URL: Issue Tracker, https://github.com/neuml/txtai/issues
Project-URL: Source Code, https://github.com/neuml/txtai
Description: # txtai: AI-powered search engine
        
        txtai builds an AI-powered index over sections of text. txtai supports building text indices to perform similarity searches and create extractive question-answering based systems. 
        
        ![demo](https://raw.githubusercontent.com/neuml/txtai/master/demo.gif)
        
        NeuML uses txtai and/or the concepts behind it to power all of our Natural Language Processing (NLP) applications. Example applications:
        
        - [cord19q](https://github.com/neuml/cord19q) - COVID-19 literature analysis
        - [paperai](https://github.com/neuml/paperai) - AI-powered literature discovery and review engine for medical/scientific papers
        - [neuspo](https://neuspo.com) - a fact-driven, real-time sports event and news site
        - [codequestion](https://github.com/neuml/codequestion) - Ask coding questions directly from the terminal
        
        txtai is built on the following stack:
        
        - [sentence-transformers](https://github.com/UKPLab/sentence-transformers)
        - [transformers](https://github.com/huggingface/transformers)
        - [faiss](https://github.com/facebookresearch/faiss)
        - Python 3.6+
        
        ## Installation
        The easiest way to install is via pip and PyPI
        
            pip install txtai
        
        You can also install txtai directly from GitHub. Using a Python Virtual Environment is recommended.
        
            pip install git+https://github.com/neuml/txtai
        
        Python 3.6+ is supported
        
        ### Notes for Windows
        This project has dependencies that require compiling native code. Linux enviroments usually work without an issue. Windows requires the following extra steps.
        
        - Install C++ Build Tools - https://visualstudio.microsoft.com/visual-cpp-build-tools/
        - If PyTorch errors are encountered, run the following command before installing paperai. See [pytorch.org](https://pytorch.org) for more information.
        
            ```
            pip install torch===1.6.0 torchvision===0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
            ```
        
        ## Examples
        
        The examples directory has a series of examples and notebooks giving an overview of txtai. See the list of notebooks below.
        
        ### Notebooks
        
        | Notebook     |      Description      |   |
        |:----------|:-------------|------:|
        | [Introducing txtai](https://github.com/neuml/txtai/blob/master/examples/01_Introducing_txtai.ipynb)  | Overview of the functionality provided by txtai  |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/01_Introducing_txtai.ipynb) |
        | [Extractive QA with txtai](https://github.com/neuml/txtai/blob/master/examples/02_Extractive_QA_with_txtai.ipynb)  | Extractive question-answering with txtai  |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/02_Extractive_QA_with_txtai.ipynb) |
        | [Build an Embeddings index from a data source](https://github.com/neuml/txtai/blob/master/examples/03_Build_an_Embeddings_index_from_a_data_source.ipynb)  | Embeddings index from a data source backed by word embeddings |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/03_Build_an_Embeddings_index_from_a_data_source.ipynb) |
        | [Extractive QA with Elasticsearch](https://github.com/neuml/txtai/blob/master/examples/04_Extractive_QA_with_Elasticsearch.ipynb)  | Extractive question-answering with Elasticsearch  |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/04_Extractive_QA_with_Elasticsearch.ipynb) |
        
Keywords: search embedding machine-learning nlp
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Text Processing :: Indexing
Classifier: Topic :: Utilities
Requires-Python: >=3.6
Description-Content-Type: text/markdown
