@n8n/n8n-nodes-langchain
Version:
98 lines (93 loc) • 3.52 kB
text/typescript
/**
* Weaviate Vector Store Node - Version 1.3
* Discriminator: mode=retrieve
*/
interface Credentials {
weaviateApi: CredentialReference;
}
/** Retrieve documents from vector store to be used as vector store with AI nodes */
export type LcVectorStoreWeaviateV13RetrieveParams = {
mode: 'retrieve';
weaviateCollection?: { __rl: true; mode: 'list' | 'id'; value: string; cachedResultName?: string };
/**
* Whether or not to rerank results
* @default false
*/
useReranker?: boolean | Expression<boolean>;
/**
* Options
* @default {}
*/
options?: {
/** Filter pageContent or metadata using this <a href="https://weaviate.io/" target="_blank">filtering syntax</a>
*/
searchFilterJson?: IDataObject | string | Expression<string>;
/** Select the metadata to retrieve along the content
* @default source,page
*/
metadataKeys?: string | Expression<string> | PlaceholderValue;
/** Provide a query text to combine vector search with a keyword/text search
*/
hybridQuery?: string | Expression<string> | PlaceholderValue;
/** Whether to show the score fused between hybrid and vector search explanation
* @default false
*/
hybridExplainScore?: boolean | Expression<boolean>;
/** Select the fusion type for combining vector and keyword search results
* @default RelativeScore
*/
fusionType?: 'RelativeScore' | 'Ranked' | Expression<string>;
/** Limit result groups by detecting sudden jumps in score
*/
autoCutLimit?: number | Expression<number>;
/** Change the relative weights of the keyword and vector components. 1.0 = pure vector, 0.0 = pure keyword.
* @default 0.5
*/
alpha?: number | Expression<number>;
/** Comma-separated list of properties to include in the query with optionally weighted values, e.g., "question^2,answer"
*/
queryProperties?: string | Expression<string> | PlaceholderValue;
/** Set the maximum allowable distance for the vector search component
*/
maxVectorDistance?: number | Expression<number>;
/** Tenant Name. Collection must have been created with tenant support enabled.
*/
tenant?: string | Expression<string> | PlaceholderValue;
/** The key in the document that contains the embedded text
* @default text
*/
textKey?: string | Expression<string> | PlaceholderValue;
/** Whether to skip init checks while instantiating the client
* @default false
*/
skip_init_checks?: boolean | Expression<boolean>;
/** Number of timeout seconds for initial checks
* @default 2
*/
timeout_init?: number | Expression<number>;
/** Number of timeout seconds for inserts
* @default 90
*/
timeout_insert?: number | Expression<number>;
/** Number of timeout seconds for queries
* @default 30
*/
timeout_query?: number | Expression<number>;
/** Proxy to use for GRPC
*/
proxy_grpc?: string | Expression<string> | PlaceholderValue;
};
};
export interface LcVectorStoreWeaviateV13RetrieveSubnodeConfig {
embedding: EmbeddingInstance | EmbeddingInstance[];
/**
* @displayOptions.show { useReranker: [true] }
*/
reranker: RerankerInstance;
}
export type LcVectorStoreWeaviateV13RetrieveNode = {
type: '@n8n/n8n-nodes-langchain.vectorStoreWeaviate';
version: 1.3;
credentials?: Credentials;
config: NodeConfig<LcVectorStoreWeaviateV13RetrieveParams> & { subnodes: LcVectorStoreWeaviateV13RetrieveSubnodeConfig };
};