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Deep Search Examples

Python Version Jupyter License MIT Code style: black Docs Binder

In this repository we showcase some common usage of Deep Search for Document conversion as well as Data and Knowledge exploration.

Quick links

Examples

Examples rely on having valid credentials in the file ds-auth.json (see example content in ./ds-auth.json.example). To obtain your credentials, please refer to the documentation page https://ds4sd.github.io/deepsearch-toolkit/getting_started/#authentication. The file can also be generated via deepsearch login --output ds-auth.json

Document conversion

Name Description
1. Convert documents quick start Full example on programmatic document conversion
2. Convert documents with custom settings Full example on programmatic document conversion with custom conversion settings
3. Visualize bounding boxes Visualize the bbox of the text elements
4. Extract figures from documents Given a PDF file, extract the figures
5. Extract tables Given a PDF file, extract the tables

Data queries

This section will showcase examples which query data processed via Deep Search.

Name Description
1. Data query quick start Example listing data collections, making search in one and more document collections, using source for projection
2. Chemistry search queries Search the chemistry databases for known molecules

Bring your own

This section will showcase examples for bringing your own documents, csv data, nlp models and more.

Name Description
1. Bring your own PDF Upload your own PDF documents and search on them
2. Export to JSON Export Deep Search index items to JSON
3. Bring your own DataFrame Bring your own DataFrame from CSV, XLSX, etc and explore the content in a knowledge graph

Attachments and metadata

This section will showcase examples for managing index item attachments and metadata.

Name Description
1. Manage attachments Manage index item attachments

Knowledge graphs

This section will showcase examples related to the use of knowledge graphs (KGs) in Deep Search.

Name Description
1. Using Deep Search KGs with PyTorch Geometric Download knowledge graphs from Deep Search and import them in PyTorch Geometric.

Integrations

This section will showcase examples related to the integration of Deep Search with other tools and utilities.

Name Description
1. Annotations on argilla.io Use argilla.io for annotating the content of documents.

Example dependencies

The examples contained in this catalog depend on the deepsearch-toolkit as well as other modules needed for the showcase demonstrated (e.g. pandas, matplotlib, rdkit, etc). Please refer to the poetry pyproject.toml or requirements.txt for a complete list.

Python dependencies are installed with

pip install -r requirements.txt

Additionally, some examples rely on system packages. When this is the case, the README of the individual example will contain more details on which package is required. The auxiliary file apt.txt list all such packages for a Debian-bases OS. They can be installed with

xargs sudo apt-get install < apt.txt

License

The Deep Search Toolkit codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.

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