{"id":21317851,"url":"https://github.com/blacknahil/semantic_search","last_synced_at":"2026-05-18T08:33:39.964Z","repository":{"id":263890806,"uuid":"891710272","full_name":"Blacknahil/semantic_search","owner":"Blacknahil","description":"A semantic search system for Wikipedia articles using Weaviate and Cohere. It indexes articles with custom embeddings and provides a query interface to retrieve the most relevant matches. The system demonstrates the power of vector-based search for natural language queries.","archived":false,"fork":false,"pushed_at":"2024-11-20T20:41:59.000Z","size":7828,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-15T22:13:13.393Z","etag":null,"topics":["cohere","embedding-vectors","semantic-search-algorithm","weaviate"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Blacknahil.png","metadata":{"files":{"readme":"readme.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-20T20:19:40.000Z","updated_at":"2024-12-24T15:51:28.000Z","dependencies_parsed_at":"2024-11-20T21:40:36.383Z","dependency_job_id":null,"html_url":"https://github.com/Blacknahil/semantic_search","commit_stats":null,"previous_names":["blacknahil/semantic_search"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Blacknahil%2Fsemantic_search","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Blacknahil%2Fsemantic_search/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Blacknahil%2Fsemantic_search/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Blacknahil%2Fsemantic_search/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Blacknahil","download_url":"https://codeload.github.com/Blacknahil/semantic_search/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243796742,"owners_count":20349264,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cohere","embedding-vectors","semantic-search-algorithm","weaviate"],"created_at":"2024-11-21T19:09:10.903Z","updated_at":"2026-05-18T08:33:39.881Z","avatar_url":"https://github.com/Blacknahil.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Wikipedia Semantic Search with Weaviate and Cohere\n\n## Overview\nThis project builds a semantic search system using **Weaviate** for vector storage and search, and **Cohere** for generating text embeddings. The system indexes Wikipedia articles, allowing users to perform natural language queries and retrieve the most relevant articles based on their semantic meaning.\n\n---\n\n\n## Features\n- **Custom Embeddings**: Generates embeddings for articles using Cohere's `embed-english-v2.0` model.\n- **Semantic Search**: Finds the most relevant articles to a query using vector similarity.\n\n\n\n## Requirements\n- Python 3.7+\n- Weaviate running locally or hosted (e.g., Weaviate Cloud).\n- Cohere API key for embedding generation.\n\n\n### Python Libraries\nInstall required libraries using:\n```bash\npip install -r requirements.txt\n\n\n### SetUp\n\n1. Start Weaviate\nEnsure Weaviate is running. You can use Docker:\n\n\n2. Download the Wikipedia dataset:\n\nimport pandas as pd\nwiki_articles = pd.read_pickle('wikipedia.pkl')\n\n\nAcknowledgments\nWeaviate: For vector storage and search capabilities.\nCohere: For providing powerful embedding models.\nWikipedia for the dataset.\nIcog Labs for the learning opportunity.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fblacknahil%2Fsemantic_search","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fblacknahil%2Fsemantic_search","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fblacknahil%2Fsemantic_search/lists"}