Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesActiveloop Deep LakeAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cosmos DBAzure Cognitive SearchBagelDBCassandraChromaClarifaiClickHouseDashVectorDingoDocArray HnswSearchDocArray InMemorySearchElasticsearchEpsillaFaissHologresLanceDBLLMRailsMarqoGoogle Vertex AI MatchingEngineMeilisearchMilvusMomento Vector Index (MVI)MongoDB AtlasMyScaleNeo4j Vector IndexNucliaDBOpenSearchPostgres EmbeddingPGVectorPineconeQdrantRedisRocksetScaNNSingleStoreDBscikit-learnsqlite-vssStarRocksSupabase (Postgres)TairTencent Cloud VectorDBTigrisTimescale Vector (Postgres)TypesenseUSearchValdvearchVectaravectorstoresVespaWeaviateXataZepZillizRetrieversToolsAgents and toolkitsMemoryCallbacksChat loadersComponentsVector storesMeilisearchOn this pageMeilisearchMeilisearch is an open-source, lightning-fast, and hyper relevant search engine. It comes with great defaults to help developers build snappy search experiences. You can self-host Meilisearch or run on Meilisearch Cloud.Meilisearch v1.3 supports vector search. This page guides you through integrating Meilisearch as a vector store and using it to perform vector search.Setup‚ÄãLaunching a Meilisearch instance‚ÄãYou will need a running Meilisearch instance to use as your vector store. You can run Meilisearch in local or create a Meilisearch Cloud account.As of Meilisearch v1.3, vector storage is an experimental feature. After launching your Meilisearch instance, you need to enable vector storage. For self-hosted Meilisearch, read the docs on enabling experimental features. On Meilisearch Cloud, enable Vector Store via your project Settings page.You should now have a running Meilisearch instance with vector storage enabled. üéâCredentials‚ÄãTo interact with your
Meilisearch is an open-source, lightning-fast, and hyper relevant search engine. It comes with great defaults to help developers build snappy search experiences.
Meilisearch is an open-source, lightning-fast, and hyper relevant search engine. It comes with great defaults to help developers build snappy search experiences. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesActiveloop Deep LakeAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cosmos DBAzure Cognitive SearchBagelDBCassandraChromaClarifaiClickHouseDashVectorDingoDocArray HnswSearchDocArray InMemorySearchElasticsearchEpsillaFaissHologresLanceDBLLMRailsMarqoGoogle Vertex AI MatchingEngineMeilisearchMilvusMomento Vector Index (MVI)MongoDB AtlasMyScaleNeo4j Vector IndexNucliaDBOpenSearchPostgres EmbeddingPGVectorPineconeQdrantRedisRocksetScaNNSingleStoreDBscikit-learnsqlite-vssStarRocksSupabase (Postgres)TairTencent Cloud VectorDBTigrisTimescale Vector (Postgres)TypesenseUSearchValdvearchVectaravectorstoresVespaWeaviateXataZepZillizRetrieversToolsAgents and toolkitsMemoryCallbacksChat loadersComponentsVector storesMeilisearchOn this pageMeilisearchMeilisearch is an open-source, lightning-fast, and hyper relevant search engine. It comes with great defaults to help developers build snappy search experiences. You can self-host Meilisearch or run on Meilisearch Cloud.Meilisearch v1.3 supports vector search. This page guides you through integrating Meilisearch as a vector store and using it to perform vector search.Setup‚ÄãLaunching a Meilisearch instance‚ÄãYou will need a running Meilisearch instance to use as your vector store. You can run Meilisearch in local or create a Meilisearch Cloud account.As of Meilisearch v1.3, vector storage is an experimental feature. After launching your Meilisearch instance, you need to enable vector storage. For self-hosted Meilisearch, read the docs on enabling experimental features. On Meilisearch Cloud, enable Vector Store via your project Settings page.You should now have a running Meilisearch instance with vector storage enabled. üéâCredentials‚ÄãTo interact with your