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Add notebook covering txtai integration with Postgres, closes #701
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davidmezzetti committed Apr 25, 2024
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Expand Up @@ -84,7 +84,7 @@ Train NLP models.
| [Export and run models with ONNX](https://github.com/neuml/txtai/blob/master/examples/18_Export_and_run_models_with_ONNX.ipynb) | Export models with ONNX, run natively in JavaScript, Java and Rust | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/18_Export_and_run_models_with_ONNX.ipynb) |
| [Export and run other machine learning models](https://github.com/neuml/txtai/blob/master/examples/21_Export_and_run_other_machine_learning_models.ipynb) | Export and run models from scikit-learn, PyTorch and more | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/21_Export_and_run_other_machine_learning_models.ipynb) |

## Scale
## API

Run distributed txtai, integrate with the API and cloud endpoints.

Expand All @@ -98,7 +98,7 @@ Run distributed txtai, integrate with the API and cloud endpoints.

## Architecture

Deep dives into project architecture, data formats, benchmarks, and performance.
Project architecture, data formats, external integrations, scale to production, benchmarks, and performance.

| Notebook | Description | |
|:----------|:-------------|------:|
Expand All @@ -110,6 +110,7 @@ Deep dives into project architecture, data formats, benchmarks, and performance.
| [External database integration](https://github.com/neuml/txtai/blob/master/examples/49_External_database_integration.ipynb) | Store metadata in PostgreSQL, MariaDB, MySQL and more | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/49_External_database_integration.ipynb) |
| [All about vector quantization](https://github.com/neuml/txtai/blob/master/examples/50_All_about_vector_quantization.ipynb) | Benchmarking scalar and product quantization methods | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/50_All_about_vector_quantization.ipynb) |
| [External vectorization](https://github.com/neuml/txtai/blob/master/examples/56_External_vectorization.ipynb) | Vectorization with precomputed embeddings datasets and APIs | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/56_External_vectorization.ipynb) |
| [Integrate txtai with Postgres](https://github.com/neuml/txtai/blob/master/examples/61_Integrate_txtai_with_Postgres.ipynb) | Persist content, vectors and graph data in Postgres | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/61_Integrate_txtai_with_Postgres.ipynb) |

## Releases

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