Supabase

捆绑包 (Bundles) 包含支持特定第三方与 Langflow 集成的自定义组件。

本页介绍了 Supabase 捆绑包中可用的组件。

Supabase 向量存储 (Supabase vector store)

Supabase 组件使用 SupabaseVectorStore 实例读取和写入 Supabase 向量存储。

关于向量存储实例

Because Langflow is based on LangChain, vector store components use an instance of LangChain vector store to drive the underlying read and write functions. These instances are provider-specific and configured according to the component's parameters, such as the connection string, index name, and schema.

In component code, this is often instantiated as vector_store, but some vector store components use a different name, such as the provider name.

Some LangChain classes don't expose all possible options as component parameters. Depending on the provider, these options might use default values or allow modification through environment variables, if they are supported in Langflow. For information about specific options, see the LangChain API reference and vector store provider's documentation.

If you use a vector store component to query your vector database, it produces search results that you can pass to downstream components in your flow as a list of Data objects or a tabular DataFrame. If both types are supported, you can set the format near the vector store component's output port in the visual editor.

提示

有关在流中使用向量数据库的教程，请参阅 创建向量 RAG 聊天机器人。

Supabase 向量存储参数 (Supabase vector store parameters)

您可以检查向量存储组件的参数，以了解有关其接受的输入、支持的功能以及如何配置它的更多信息。

Some parameters are hidden by default in the visual editor. You can modify all parameters through the Controls in the component's header menu.

Some parameters are conditional, and they are only available after you set other parameters or select specific options for other parameters. Conditional parameters may not be visible on the Controls pane until you set the required dependencies.

有关可接受的值和功能的详细信息，请参阅 Supabase 文档 或检查 组件代码。

名称	类型	描述
supabase_url	String	输入参数。Supabase 实例的 URL。
supabase_service_key	SecretString	输入参数。Supabase 身份验证的服务密钥。
table_name	String	输入参数。Supabase 中的表名。
query_name	String	输入参数。要使用的查询名称。
search_query	String	输入参数。用于相似性搜索的查询。
ingest_data	Data	输入参数。要摄取到向量存储中的数据。
embedding	Embeddings	输入参数。要使用的嵌入函数。
number_of_results	Integer	输入参数。搜索中返回的结果数量。