{"data":{"slug":"kantord-seagoat","name":"SeaGOAT","tagline":"local-first semantic code search engine","github_url":"https://github.com/kantord/SeaGOAT","owner":"kantord","repo":"SeaGOAT","owner_avatar_url":"https://avatars.githubusercontent.com/u/3704904?v=4","primary_language":"Python","stars":1302,"forks":91,"topics":["ai","ai-project","code-search","code-search-engine","embeddings","grep","grep-like","hacktoberfest","hacktoberfest2023","llm","regular-expression","ripgrep","vector-database","vector-embeddings"],"archived":false,"github_pushed_at":"2026-07-21T03:16:49+00:00","maintenance_label":"Steady","stars_delta_30d":0,"url":"https://www.graphcanon.com/tools/kantord-seagoat","markdown_url":"https://www.graphcanon.com/tools/kantord-seagoat.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/kantord-seagoat","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=kantord-seagoat","description":"local-first semantic code search engine","homepage_url":"https://kantord.github.io/SeaGOAT/","license":"MIT","open_issues":44,"watchers":6,"ai_summary":"Developed in Python, SeaGOAT is a tool for performing local semantic searches over codebases. It leverages embeddings and vector databases to provide grep-like functionality but with an enhanced understanding of code semantics.","readme_excerpt":"### Install SeaGOAT\n\nIn order to install SeaGOAT, you need to have the following\ndependencies already installed on your computer:\n\n- Python 3.11 or newer\n- ripgrep\n- [bat](https://github.com/sharkdp/bat) (**optional**, highly recommended)\n\nWhen `bat` is [installed](https://github.com/sharkdp/bat#on-ubuntu-using-apt),\nit is used to display results as long as color is enabled. When SeaGOAT is\nused as part of a pipeline, a grep-line output format is used. When color is\nenabled, but `bat` is not installed, SeaGOAT will highlight the output using\npygments. Using `bat` is recommended.\n\nTo install SeaGOAT using `pipx`, use the following command:\n\n```bash\npipx install seagoat\n```\n\n---\n\n### System requirements\n\n#### Hardware\n\nShould work on any decent laptop.\n\n#### Operating system\n\nSeaGOAT is designed to work on Linux (*tested* ✅),\nmacOS ([partly tested, **help**](https://github.com/kantord/SeaGOAT/issues/178) 🙏)\nand Windows ([**help needed**](https://github.com/kantord/SeaGOAT/issues/179) 🙏).\n\n---\n\n### Install dependencies\n\nAfter cloning the repository, install dependencies using the following command:\n\n```bash\npoetry install\n```","github_created_at":"2023-06-20T14:38:16+00:00","created_at":"2026-07-07T17:44:37.705094+00:00","updated_at":"2026-08-21T18:01:44.750381+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":"ai","name":"ai"},{"slug":"code-search","name":"code-search"},{"slug":"embeddings","name":"embeddings"},{"slug":"vector-embeddings","name":"vector-embeddings"}],"trust":{"provenance":{"is_fork":false,"github_id":656242004,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T18:01:43.866Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":0,"days_since_push":31,"last_release_at":"2025-05-14T03:48:51Z","stars_delta_30d":0,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:26:13.701Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-21T18:01:44.352Z"},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-21T18:01:44.352Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-21T18:01:44.352Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-21T18:01:44.352Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Runs locally and only requires a machine setup with Python environment and possibly extra dependencies for vector database operations."],"min_ram_gb":null,"requires_docker":false},"constraints":{"min_ram_gb":null,"requires_docker":false},"when_to_use":["When you are working with large codebases that require a deeper understanding than regular expressions can provide, SeaGOAT's semantic capabilities shine.","Ideal for projects where maintaining privacy is critical since it operates locally and doesn't need external services, unlike some of its competitors."],"when_not_to_use":["If your primary need is simple pattern matching with text-based operations rather than deeper code semantics, you might find SeaGOAT overkill and prefer a straightforward grep tool instead.","When real-time updates or cloud integration are required for continuous monitoring or remote access to search data, SeaGOAT's local-first approach could be limiting."],"source":"enrich:decision_facts","observed_at":"2026-07-12T18:58:04.361Z"},"constraint_facets":{"min_ram_gb":null,"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Runs locally and only requires a machine setup with Python environment and possibly extra dependencies for vector database operations."},{"label":"Adopt for","value":"SeaGOAT leverages local-first processing and semantic embeddings to offer an enhanced understanding of codebases compared to traditional grep-based searches."}]}}