{"data":{"slug":"redis-redis-vl-python","name":"redis-vl-python","tagline":"Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.","github_url":"https://github.com/redis/redis-vl-python","owner":"redis","repo":"redis-vl-python","owner_avatar_url":"https://avatars.githubusercontent.com/u/1529926?v=4","primary_language":"Python","stars":424,"forks":95,"topics":["anthropic","embedding","huggingface","large-language-models","llm","llmcache","mcp","openai","python","redis","redis-search","retrieval-augmented-generation","search","semantic-cache","vector-database","vector-search"],"archived":false,"github_pushed_at":"2026-08-20T08:52:16+00:00","maintenance_label":"Very active","stars_delta_30d":8,"url":"https://www.graphcanon.com/tools/redis-redis-vl-python","markdown_url":"https://www.graphcanon.com/tools/redis-redis-vl-python.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/redis-redis-vl-python","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=redis-redis-vl-python","description":"Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.","homepage_url":"https://docs.redisvl.com","license":"MIT","open_issues":50,"watchers":8,"ai_summary":"A Python library providing an AI-native interface for working with Redis as a vector database. Supports large language model integrations and embedding management.","readme_excerpt":"## Installation\n\nInstall `redisvl` into your Python (>=3.10) environment using `pip`:\n\n```bash\npip install redisvl\n```\n\nInstall the MCP server extra when you want to expose one or more existing Redis indexes through MCP:\n\n```bash\npip install redisvl[mcp]\n```\n\n> For more detailed instructions, visit the [installation guide](https://docs.redisvl.com/en/latest/user_guide/installation.html).\n> For MCP concepts and setup, see the [RedisVL MCP docs](https://docs.redisvl.com/en/latest/concepts/mcp.html) and the [MCP how-to guide](https://docs.redisvl.com/en/latest/user_guide/how_to_guides/mcp.html).","github_created_at":"2022-11-04T19:36:02+00:00","created_at":"2026-07-11T11:35:37.439135+00:00","updated_at":"2026-08-23T12:01:41.630004+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":"embedding","name":"embedding"},{"slug":"huggingface","name":"huggingface"},{"slug":"large-language-models","name":"large language models"},{"slug":"llmcache","name":"llmcache"},{"slug":"openai","name":"openai"},{"slug":"python","name":"python"},{"slug":"redis-search","name":"redis-search"},{"slug":"retrieval-augmented-generation","name":"retrieval-augmented-generation"}],"trust":{"provenance":{"is_fork":false,"github_id":561914940,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-23T12:01:40.838Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":9,"days_since_push":3,"last_release_at":"2026-08-19T15:53:09Z","stars_delta_30d":8,"open_issues_delta_30d":2},"security_summary":{"status":"no_manifest","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:35:38.627Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-23T12:01:41.296Z"},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-23T12:01:41.296Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-23T12:01:41.296Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-23T12:01:41.296Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Requires a Redis server to be installed and running."],"requires_docker":false},"constraints":{"requires_docker":false},"when_to_use":["When you need to integrate your application with Redis as a vector database using the Python programming language.","If your project involves working with large language models, such as those from HuggingFace or Anthropic, and requires efficient embedding retrieval and caching.","For applications that require the use of semantic search capabilities within a familiar Python environment, leveraging the power of Redis.","When developing projects that require a backend capable of real-time indexing and searching through complex embeddings."],"when_not_to_use":["If your project does not require integration with Redis or Python is not an option for implementation.","For applications needing only basic key-value storage, as RedisVL introduces additional overhead with its specialized AI-native features.","When you are looking for a simpler vector database that doesn't support intricate embedding management and large language model integrations.","If your project requires a solution that does not carry the MIT license, implying an unwillingness or inability to handle open-source licensing conditions."],"source":"enrich:decision_facts","observed_at":"2026-07-12T17:37:17.882Z"},"constraint_facets":{"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Requires a Redis server to be installed and running."},{"label":"Adopt for","value":"RedisVL is a Python library designed for seamless integration of Redis as an AI-native vector database. It stands out with its specialized support for large language models and embedding management."},{"label":"License detail","value":"Licensed under the permissive MIT License, allowing for free use in both commercial and non-commercial projects with no warranty."}]}}