all[patch]: Replace .getRelevantDocuments with .invoke

docs/core_docs/docs/tutorials/agents.mdx

@@ -83,9 +83,7 @@ const vectorstore = await MemoryVectorStore.fromDocuments(
 );
 const retriever = vectorstore.asRetriever();
 
-const retrieverResult = await retriever.getRelevantDocuments(
-  "how to upload a dataset"
-);
+const retrieverResult = await retriever.invoke("how to upload a dataset");
 console.log(retrieverResult[0]);
 
 /*

docs/core_docs/docs/tutorials/rag.ipynb

@@ -136,7 +136,7 @@
         "  outputParser: new StringOutputParser(),\n",
         "})\n",
         "\n",
-        "const retrievedDocs = await retriever.getRelevantDocuments(\"what is task decomposition\")"
+        "const retrievedDocs = await retriever.invoke(\"what is task decomposition\")"
       ]
     },
     {
@@ -817,7 +817,7 @@
         "  prompt: customRagPrompt,\n",
         "  outputParser: new StringOutputParser(),\n",
         "})\n",
-        "const context = await retriever.getRelevantDocuments(\"what is task decomposition\");\n",
+        "const context = await retriever.invoke(\"what is task decomposition\");\n",
         "\n",
         "await ragChain.invoke({\n",
         "  question: \"What is Task Decomposition?\",\n",

examples/src/retrievers/parent_document_retriever_rerank.ts

@@ -69,9 +69,7 @@ await retriever.addDocuments(docs);
 
 // This will search for documents in vector store and return for LLM already reranked and sorted document
 // with appropriate minimum relevance score
-const retrievedDocs = await retriever.getRelevantDocuments(
-  "What is Pam's favorite color?"
-);
+const retrievedDocs = await retriever.invoke("What is Pam's favorite color?");
 
 // Pam's favorite color is returned first!
 console.log(JSON.stringify(retrievedDocs, null, 2));

examples/src/retrievers/qdrant_self_query.ts

@@ -118,16 +118,16 @@ const selfQueryRetriever = SelfQueryRetriever.fromLLM({
  * We can also ask questions like "Which movies are either comedy or drama and are less than 90 minutes?".
  * The retriever will automatically convert these questions into queries that can be used to retrieve documents.
  */
-const query1 = await selfQueryRetriever.getRelevantDocuments(
+const query1 = await selfQueryRetriever.invoke(
   "Which movies are less than 90 minutes?"
 );
-const query2 = await selfQueryRetriever.getRelevantDocuments(
+const query2 = await selfQueryRetriever.invoke(
   "Which movies are rated higher than 8.5?"
 );
-const query3 = await selfQueryRetriever.getRelevantDocuments(
+const query3 = await selfQueryRetriever.invoke(
   "Which cool movies are directed by Greta Gerwig?"
 );
-const query4 = await selfQueryRetriever.getRelevantDocuments(
+const query4 = await selfQueryRetriever.invoke(
   "Which movies are either comedy or drama and are less than 90 minutes?"
 );
 console.log(query1, query2, query3, query4);

langchain-core/src/retrievers/index.ts

@@ -73,7 +73,7 @@ export abstract class BaseRetriever<
     input: string,
     options?: RunnableConfig
   ): Promise<DocumentInterface<Metadata>[]> {
-    return this.getRelevantDocuments(input, ensureConfig(options));
+    return this.invoke(input, ensureConfig(options));
   }
 
   /**

langchain-core/src/structured_query/functional.ts

@@ -37,7 +37,7 @@ export type FunctionFilter = (document: Document) => boolean;
  * @example
  * ```typescript
  * const functionalTranslator = new FunctionalTranslator();
- * const relevantDocuments = await functionalTranslator.getRelevantDocuments(
+ * const relevantDocuments = await functionalTranslator.invoke(
  *   "Which movies are rated higher than 8.5?",
  * );
  * ```

langchain/src/agents/toolkits/conversational_retrieval/tool.ts

@@ -16,7 +16,7 @@ export function createRetrieverTool(
     { input }: { input: string },
     runManager?: CallbackManagerForToolRun
   ) => {
-    const docs = await retriever.getRelevantDocuments(
+    const docs = await retriever.invoke(
       input,
       runManager?.getChild("retriever")
     );

langchain/src/chains/conversational_retrieval_chain.ts

@@ -230,7 +230,7 @@ export class ConversationalRetrievalQAChain
         );
       }
     }
-    const docs = await this.retriever.getRelevantDocuments(
+    const docs = await this.retriever.invoke(
       newQuestion,
       runManager?.getChild("retriever")
     );

langchain/src/chains/retrieval_qa.ts

@@ -100,7 +100,7 @@ export class RetrievalQAChain
       throw new Error(`Question key "${this.inputKey}" not found.`);
     }
     const question: string = values[this.inputKey];
-    const docs = await this.retriever.getRelevantDocuments(
+    const docs = await this.retriever.invoke(
       question,
       runManager?.getChild("retriever")
     );

langchain/src/experimental/autogpt/prompt.ts

@@ -109,7 +109,7 @@ export class AutoGPTPrompt
     const usedTokens =
       (await this.tokenCounter(basePrompt.content)) +
       (await this.tokenCounter(timePrompt.content));
-    const relevantDocs = await memory.getRelevantDocuments(
+    const relevantDocs = await memory.invoke(
       JSON.stringify(previousMessages.slice(-10))
     );
     const relevantMemory = relevantDocs.map(

langchain/src/experimental/chains/violation_of_expectations/violation_of_expectations_chain.ts

@@ -294,9 +294,7 @@ export class ViolationOfExpectationsChain
     // Only extract the first relevant doc from the retriever. We don't need more than one.
     const relevantInsightsDocuments = await Promise.all(
       insights.map(async (insight) => {
-        const relevantInsight = await this.retriever.getRelevantDocuments(
-          insight
-        );
+        const relevantInsight = await this.retriever.invoke(insight);
         return relevantInsight[0];
       })
     );

langchain/src/experimental/generative_agents/generative_agent_memory.ts

@@ -280,7 +280,7 @@ class GenerativeAgentMemoryChain extends BaseChain {
     _now?: Date,
     runManager?: CallbackManagerForChainRun
   ): Promise<Document[]> {
-    return this.memoryRetriever.getRelevantDocuments(
+    return this.memoryRetriever.invoke(
       observation,
       runManager?.getChild("memory_retriever")
     );

langchain/src/memory/vector_store.ts

@@ -98,7 +98,7 @@ export class VectorStoreRetrieverMemory
    */
   async loadMemoryVariables(values: InputValues): Promise<MemoryVariables> {
     const query = getInputValue(values, this.inputKey);
-    const results = await this.vectorStoreRetriever.getRelevantDocuments(query);
+    const results = await this.vectorStoreRetriever.invoke(query);
     return {
       [this.memoryKey]: this.returnDocs
         ? results

langchain/src/retrievers/contextual_compression.ts

@@ -27,7 +27,7 @@ export interface ContextualCompressionRetrieverArgs extends BaseRetrieverInput {
  *   baseCompressor: new LLMChainExtractor(),
  *   baseRetriever: new HNSWLib().asRetriever(),
  * });
- * const retrievedDocs = await retriever.getRelevantDocuments(
+ * const retrievedDocs = await retriever.invoke(
  *   "What did the speaker say about Justice Breyer?",
  * );
  * ```
@@ -54,7 +54,7 @@ export class ContextualCompressionRetriever extends BaseRetriever {
     query: string,
     runManager?: CallbackManagerForRetrieverRun
   ): Promise<DocumentInterface[]> {
-    const docs = await this.baseRetriever.getRelevantDocuments(
+    const docs = await this.baseRetriever.invoke(
       query,
       runManager?.getChild("base_retriever")
     );

langchain/src/retrievers/document_compressors/index.ts

@@ -50,7 +50,7 @@ export abstract class BaseDocumentCompressor {
  *     includeRawContent: true,
  *   }),
  * });
- * const retrievedDocs = await retriever.getRelevantDocuments(
+ * const retrievedDocs = await retriever.invoke(
  *   "What did the speaker say about Justice Breyer in the 2022 State of the Union?",
  * );
  * console.log({ retrievedDocs });

langchain/src/retrievers/hyde.ts

@@ -56,7 +56,7 @@ export type HydeRetrieverOptions<V extends VectorStore> =
  *     "My favourite food is pasta.",
  *   ].map((pageContent) => new Document({ pageContent })),
  * );
- * const results = await retriever.getRelevantDocuments(
+ * const results = await retriever.invoke(
  *   "What is my favourite food?",
  * );
  * ```

langchain/src/retrievers/multi_query.ts

@@ -82,7 +82,7 @@ export interface MultiQueryRetrieverInput extends BaseRetrieverInput {
  *   retriever: new MemoryVectorStore().asRetriever(),
  *   verbose: true,
  * });
- * const retrievedDocs = await retriever.getRelevantDocuments(
+ * const retrievedDocs = await retriever.invoke(
  *   "What are mitochondria made of?",
  * );
  * ```
@@ -159,10 +159,7 @@ export class MultiQueryRetriever extends BaseRetriever {
     const documents: Document[] = [];
     await Promise.all(
       queries.map(async (query) => {
-        const docs = await this.retriever.getRelevantDocuments(
-          query,
-          runManager?.getChild()
-        );
+        const docs = await this.retriever.invoke(query, runManager?.getChild());
         documents.push(...docs);
       })
     );

langchain/src/retrievers/multi_vector.ts

@@ -34,7 +34,7 @@ export interface MultiVectorRetrieverInput extends BaseRetrieverInput {
  *   parentK: 5,
  * });
  *
- * const retrieverResult = await retriever.getRelevantDocuments("justice breyer");
+ * const retrieverResult = await retriever.invoke("justice breyer");
  * console.log(retrieverResult[0].pageContent.length);
  * ```
  */

langchain/src/retrievers/parent_document.ts

@@ -61,7 +61,7 @@ export type ParentDocumentRetrieverFields = MultiVectorRetrieverInput & {
  *
  * const parentDocuments = await getDocuments();
  * await retriever.addDocuments(parentDocuments);
- * const retrievedDocs = await retriever.getRelevantDocuments("justice breyer");
+ * const retrievedDocs = await retriever.invoke("justice breyer");
  * ```
  */
 export class ParentDocumentRetriever extends MultiVectorRetriever {
@@ -107,7 +107,7 @@ export class ParentDocumentRetriever extends MultiVectorRetriever {
   async _getRelevantDocuments(query: string): Promise<Document[]> {
     let subDocs: SubDocs = [];
     if (this.childDocumentRetriever) {
-      subDocs = await this.childDocumentRetriever.getRelevantDocuments(query);
+      subDocs = await this.childDocumentRetriever.invoke(query);
     } else {
       subDocs = await this.vectorstore.similaritySearch(query, this.childK);
     }

langchain/src/retrievers/self_query/chroma.ts

@@ -28,7 +28,7 @@ import { logVersion020MigrationWarning } from "../../util/entrypoint_deprecation
  *   structuredQueryTranslator: chromaTranslator,
  * });
  *
- * const relevantDocuments = await selfQueryRetriever.getRelevantDocuments(
+ * const relevantDocuments = await selfQueryRetriever.invoke(
  *   "Which movies are directed by Greta Gerwig?",
  * );
  * ```

langchain/src/retrievers/self_query/index.ts

@@ -51,7 +51,7 @@ export interface SelfQueryRetrieverArgs<T extends VectorStore>
  *   attributeInfo: attributeInfo,
  *   structuredQueryTranslator: new FunctionalTranslator(),
  * });
- * const relevantDocuments = await selfQueryRetriever.getRelevantDocuments(
+ * const relevantDocuments = await selfQueryRetriever.invoke(
  *   "Which movies are directed by Greta Gerwig?",
  * );
  * ```

langchain/src/retrievers/self_query/pinecone.ts

@@ -28,7 +28,7 @@ import { logVersion020MigrationWarning } from "../../util/entrypoint_deprecation
  *   structuredQueryTranslator: new PineconeTranslator(),
  * });
  *
- * const queryResult = await selfQueryRetriever.getRelevantDocuments(
+ * const queryResult = await selfQueryRetriever.invoke(
  *   "Which movies are directed by Greta Gerwig?",
  * );
  * ```

langchain/src/retrievers/self_query/supabase.ts

@@ -59,7 +59,7 @@ type SupabaseMetadata = any;
  *   structuredQueryTranslator: new SupabaseTranslator(),
  * });
  *
- * const queryResult = await selfQueryRetriever.getRelevantDocuments(
+ * const queryResult = await selfQueryRetriever.invoke(
  *   "Which movies are directed by Greta Gerwig?",
  * );
  * ```

langchain/src/retrievers/self_query/tests/memory_self_query.int.test.ts

@@ -86,19 +86,19 @@ test("Memory Vector Store Self Query Retriever Test", async () => {
     structuredQueryTranslator: new FunctionalTranslator(),
   });
 
-  const query1 = await selfQueryRetriever.getRelevantDocuments(
+  const query1 = await selfQueryRetriever.invoke(
     "Which movies are less than 90 minutes?"
   );
   console.log(query1);
   expect(query1.length).toEqual(0);
 
-  const query2 = await selfQueryRetriever.getRelevantDocuments(
+  const query2 = await selfQueryRetriever.invoke(
     "Which movies are rated higher than 8.5?"
   );
   console.log(query2);
   expect(query2.length).toEqual(2);
 
-  const query3 = await selfQueryRetriever.getRelevantDocuments(
+  const query3 = await selfQueryRetriever.invoke(
     "Which movies are directed by Greta Gerwig?"
   );
   console.log(query3);
@@ -221,25 +221,25 @@ test("Memory Vector Store Self Query Retriever Test With Default Filter Or Merge
     },
   });
 
-  const query1 = await selfQueryRetriever.getRelevantDocuments(
+  const query1 = await selfQueryRetriever.invoke(
     "Which movies are less than 90 minutes?"
   );
   console.log(query1);
   expect(query1.length).toEqual(6);
 
-  const query2 = await selfQueryRetriever.getRelevantDocuments(
+  const query2 = await selfQueryRetriever.invoke(
     "Which movies are rated higher than 8.5?"
   );
   console.log(query2);
   expect(query2.length).toEqual(7);
 
-  const query3 = await selfQueryRetriever.getRelevantDocuments(
+  const query3 = await selfQueryRetriever.invoke(
     "Which movies are directed by Greta Gerwig?"
   );
   console.log(query3);
   expect(query3.length).toEqual(6);
 
-  const query4 = await selfQueryRetriever.getRelevantDocuments(
+  const query4 = await selfQueryRetriever.invoke(
     "Awawawa au au au wawawawa hello?"
   );
   console.log(query4);
@@ -362,25 +362,25 @@ test("Memory Vector Store Self Query Retriever Test With Default Filter And Merg
     },
   });
 
-  const query1 = await selfQueryRetriever.getRelevantDocuments(
+  const query1 = await selfQueryRetriever.invoke(
     "Which movies are less than 90 minutes?"
   );
   console.log(query1);
   expect(query1.length).toEqual(0);
 
-  const query2 = await selfQueryRetriever.getRelevantDocuments(
+  const query2 = await selfQueryRetriever.invoke(
     "Which movies are rated higher than 8.5?"
   );
   console.log(query2);
   expect(query2.length).toEqual(2);
 
-  const query3 = await selfQueryRetriever.getRelevantDocuments(
+  const query3 = await selfQueryRetriever.invoke(
     "Which movies are directed by Greta Gerwig?"
   );
   console.log(query3);
   expect(query3.length).toEqual(1);
 
-  const query4 = await selfQueryRetriever.getRelevantDocuments(
+  const query4 = await selfQueryRetriever.invoke(
     "Awawawa au au au wawawawa hello?"
   );
   console.log(query4);

langchain/src/retrievers/self_query/weaviate.ts

@@ -78,7 +78,7 @@ export type WeaviateStructuredQueryResult = {
  *   structuredQueryTranslator: new WeaviateTranslator(),
  * });
  *
- * const relevantDocuments = await selfQueryRetriever.getRelevantDocuments(
+ * const relevantDocuments = await selfQueryRetriever.invoke(
  *   "Which movies are rated higher than 8.5?",
  * );
  * ```

langchain/src/retrievers/tests/hyde.int.test.ts

@@ -23,9 +23,7 @@ test("Hyde retriever", async () => {
     ].map((pageContent) => new Document({ pageContent }))
   );
 
-  const results = await retriever.getRelevantDocuments(
-    "What is my favourite food?"
-  );
+  const results = await retriever.invoke("What is my favourite food?");
 
   expect(results.length).toBe(1);
   console.log(results);
@@ -51,9 +49,7 @@ test("Hyde retriever with default prompt template", async () => {
     ].map((pageContent) => new Document({ pageContent }))
   );
 
-  const results = await retriever.getRelevantDocuments(
-    "What is my favourite food?"
-  );
+  const results = await retriever.invoke("What is my favourite food?");
 
   expect(results.length).toBe(1);
   console.log(results);