docs,examples[patch]: Replace .getRelevantDocuments with .invoke (#5749)

* docs,examples[patch]: Replace .getRelevantDocuments with .invoke * fix formatting issue
langchain-ai · Jun 13, 2024 · ce4b8ef · ce4b8ef
1 parent 09f6af2
commit ce4b8ef
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Showing 4 changed files with 8 additions and 12 deletions.
diff --git a/docs/core_docs/docs/tutorials/agents.mdx b/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]);
 
 /*

diff --git a/docs/core_docs/docs/tutorials/rag.ipynb b/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",

diff --git a/examples/src/retrievers/parent_document_retriever_rerank.ts b/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));

diff --git a/examples/src/retrievers/qdrant_self_query.ts b/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);