{"data":{"slug":"weaviate-weaviate-examples","name":"weaviate-examples","tagline":"Weaviate vector database – examples","github_url":"https://github.com/weaviate/weaviate-examples","owner":"weaviate","repo":"weaviate-examples","owner_avatar_url":"https://avatars.githubusercontent.com/u/37794290?v=4","primary_language":"HTML","stars":331,"forks":86,"topics":["deep-learning","examples","vector-database","vector-search","vector-search-engine","weaviate"],"archived":false,"github_pushed_at":"2025-08-07T17:06:59+00:00","maintenance_label":"Dormant","stars_delta_30d":-1,"url":"https://www.graphcanon.com/tools/weaviate-weaviate-examples","markdown_url":"https://www.graphcanon.com/tools/weaviate-weaviate-examples.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/weaviate-weaviate-examples","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=weaviate-weaviate-examples","description":"Weaviate vector database – examples","homepage_url":null,"license":"MIT","open_issues":12,"watchers":31,"ai_summary":"Provides examples for Weaviate, a comprehensive vector database designed for deep learning applications to facilitate efficient data retrieval through vector search.","readme_excerpt":"# Weaviate examples\n\nList of examples and tutorials of how to use the Vector Search Engine\nWeaviate for cool machine-learning related tasks.\n\n### Running Weaviate\n\n* Most examples assume you have a Weaviate running. You can run one locally by following [this installation guide](https://weaviate.io/developers/weaviate/installation/docker-compose) in the documentation.\n  * If you need a specific vectorizer module or another ML module, it will be explained in the tutorial.\n* Basic links: [Documentation](https://weaviate.io/developers/weaviate/) – [Github](https://github.com/weaviate/weaviate) - [Slack](https://weaviate.io/slack)\n\n## Examples\n\n|Title|Language|Description|\n|---|---|---|\n| [Semantic search through Wikipedia with the Weaviate vector search engine](https://github.com/weaviate/semantic-search-through-wikipedia-with-weaviate) | GraphQL | Semantic search through a vectorized Wikipedia (SentenceBERT) with the Weaviate vector search engine | \n| [PyTorch-BigGraph Wikidata search with the Weaviate vector search engine](https://github.com/weaviate/biggraph-wikidata-search-with-weaviate) | GraphQL | Search through Facebook Research's PyTorch BigGraph Wikidata-dataset with the Weaviate vector search engine |\n| [Multi-Modal Text/Image search using CLIP](clip-multi-modal-text-image-search/) | Bash, Javascript, React | Use text to search through images using CLIP (multi2vec-clip). Also acts as a demo on how to use Weaviate with React |\n| [Google Colab notebook: Getting started with the Python Client](getting-started-with-python-client-colab) | python (Google Colab) | Google Colab notebook to learn to get started with the Python client. Contains plenty of example code. |\n| [Demo dataset News Publications with Contextionary](weaviate-contextionary-newspublications) | yaml | Docker-compose configuration file of Weaviate with a News Publications demo dataset. |\n| [Demo dataset News Publications with Transformers, NER, Spellcheck and Q&A](weaviate-transformers-newspublications) | yaml | Docker-compose configuration file of Weaviate with a News Publications demo dataset. The vectorization is done by a text2vec-transformers module, and the spellcheck, Q&A and Named Entity Recognition module are connected. |\n| [Weaviate simple schema](schema-wines) | Python | Easy example of a schema and how to upload it to Weaviate with the Python client |\n| [Semantic search through wine dataset](semanticsearch-transformers-wines) | Python | Easy example to get started with Weaviate and semantic search with the Transformers module |\n| [Unmask Superheroes in 5 steps using the Weaviate NLP module and the Python client](unmask-superheroes) | Python | Super simple 5 step guide to get started with the Weaviate NLP modules. This is a basic introduction to semantic search with Weaviate and the Python client.|\n| [Information Retrieval with BERT (Weaviate without vectorizer module)](bert-information-retrieval) | Python (Jupyter Notebook) | In this example we are going to use Weaviate without vectorization module, and use it as pure vector database to use a BERT transformer to vectorize text documents, then retrieve the closest ones through Weaviate's Search | \n| [Text search with weaviate using own vectors](text-search-with-own-vectors) | Python | A basic and simple example using our own vectors(obtained using SBERT, but any other model can also be used) in weaviate|\n| [Harry Potter Question Answering with Haystack & Weaviate](harrypotter-qa-haystack-weaviate) | Python (Jupyter/Colab notebook) | A demo notebook showing how to use Weaviate as DocumentStore in [Haystack](https://haystack.deepset.ai/overview/intro).\n| [Vegetable classification using image2vec-neural](vegetable-classification) | Python  |An image classification example made using image2vec-neural and flask to classify vegetable images|\n| [Exploring multi2vec-clip with Python and flask](exploring-multi2vec-clip-with-Python-and-flask) | Python  |This example explores the multi2vec-clip module to implem","github_created_at":"2021-01-28T14:29:37+00:00","created_at":"2026-07-11T11:36:20.055896+00:00","updated_at":"2026-08-23T12:02:04.150645+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"deep-learning","name":"deep-learning"},{"slug":"examples","name":"examples"},{"slug":"vector-database","name":"vector-database"},{"slug":"vector-search","name":"vector-search"},{"slug":"vector-search-engine","name":"vector-search-engine"},{"slug":"weaviate","name":"weaviate"}],"trust":{"provenance":{"is_fork":false,"github_id":333783731,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-23T12:02:03.379Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":380,"last_release_at":null,"stars_delta_30d":-1,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:36:22.491Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-23T12:02:03.879Z"},"languages":{"value":["html"],"source":"github.language","observed_at":"2026-08-23T12:02:03.879Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-23T12:02:03.879Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["You aim to integrate vector search capabilities into your deep-learning projects and need hands-on examples to understand functionality.","Specific code snippets or configurations of Weaviate are required but not covered in the formal documentation."],"when_not_to_use":["Your project utilizes a different vector database that aligns better with its specific requirements, such as more customizability in indexing.","You seek general tutorial material on deep learning without the context of Weaviate's implementation specifics."],"source":"enrich:decision_facts","observed_at":"2026-07-15T10:21:54.485Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"weaviate-examples aids developers by providing practical usage scenarios for Weaviate vector database, optimizing deep learning applications."}]}}