diff --git a/cookbook/Multi_modal_RAG.ipynb b/cookbook/Multi_modal_RAG.ipynb index 72a2d1f727..ab9fde3d9e 100644 --- a/cookbook/Multi_modal_RAG.ipynb +++ b/cookbook/Multi_modal_RAG.ipynb @@ -604,7 +604,7 @@ "source": [ "# Check retrieval\n", "query = \"Give me company names that are interesting investments based on EV / NTM and NTM rev growth. Consider EV / NTM multiples vs historical?\"\n", - "docs = retriever_multi_vector_img.get_relevant_documents(query, limit=6)\n", + "docs = retriever_multi_vector_img.invoke(query, limit=6)\n", "\n", "# We get 4 docs\n", "len(docs)" @@ -630,7 +630,7 @@ "source": [ "# Check retrieval\n", "query = \"What are the EV / NTM and NTM rev growth for MongoDB, Cloudflare, and Datadog?\"\n", - "docs = retriever_multi_vector_img.get_relevant_documents(query, limit=6)\n", + "docs = retriever_multi_vector_img.invoke(query, limit=6)\n", "\n", "# We get 4 docs\n", "len(docs)" diff --git a/cookbook/Multi_modal_RAG_google.ipynb b/cookbook/Multi_modal_RAG_google.ipynb index e2b88b5317..6df5b20cda 100644 --- a/cookbook/Multi_modal_RAG_google.ipynb +++ b/cookbook/Multi_modal_RAG_google.ipynb @@ -604,7 +604,7 @@ ], "source": [ "query = \"What are the EV / NTM and NTM rev growth for MongoDB, Cloudflare, and Datadog?\"\n", - "docs = retriever_multi_vector_img.get_relevant_documents(query, limit=1)\n", + "docs = retriever_multi_vector_img.invoke(query, limit=1)\n", "\n", "# We get 2 docs\n", "len(docs)" diff --git a/cookbook/Semi_structured_and_multi_modal_RAG.ipynb b/cookbook/Semi_structured_and_multi_modal_RAG.ipynb index 82ce6faf7f..e797dfea86 100644 --- a/cookbook/Semi_structured_and_multi_modal_RAG.ipynb +++ b/cookbook/Semi_structured_and_multi_modal_RAG.ipynb @@ -562,9 +562,7 @@ ], "source": [ "# We can retrieve this table\n", - "retriever.get_relevant_documents(\n", - " \"What are results for LLaMA across across domains / subjects?\"\n", - ")[1]" + "retriever.invoke(\"What are results for LLaMA across across domains / subjects?\")[1]" ] }, { @@ -614,9 +612,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"Images / figures with playful and creative examples\")[\n", - " 1\n", - "]" + "retriever.invoke(\"Images / figures with playful and creative examples\")[1]" ] }, { diff --git a/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb b/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb index eb72ef730c..28316da0a3 100644 --- a/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb +++ b/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb @@ -501,9 +501,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"Images / figures with playful and creative examples\")[\n", - " 0\n", - "]" + "retriever.invoke(\"Images / figures with playful and creative examples\")[0]" ] }, { diff --git a/cookbook/advanced_rag_eval.ipynb b/cookbook/advanced_rag_eval.ipynb index a1c80ee6a7..8874640de6 100644 --- a/cookbook/advanced_rag_eval.ipynb +++ b/cookbook/advanced_rag_eval.ipynb @@ -342,7 +342,7 @@ "# Testing on retrieval\n", "query = \"What percentage of CPI is dedicated to Housing, and how does it compare to the combined percentage of Medical Care, Apparel, and Other Goods and Services?\"\n", "suffix_for_images = \" Include any pie charts, graphs, or tables.\"\n", - "docs = retriever_multi_vector_img.get_relevant_documents(query + suffix_for_images)" + "docs = retriever_multi_vector_img.invoke(query + suffix_for_images)" ] }, { diff --git a/cookbook/custom_agent_with_plugin_retrieval.ipynb b/cookbook/custom_agent_with_plugin_retrieval.ipynb index ac7545bcdb..c6b1bdd48b 100644 --- a/cookbook/custom_agent_with_plugin_retrieval.ipynb +++ b/cookbook/custom_agent_with_plugin_retrieval.ipynb @@ -169,7 +169,7 @@ "\n", "def get_tools(query):\n", " # Get documents, which contain the Plugins to use\n", - " docs = retriever.get_relevant_documents(query)\n", + " docs = retriever.invoke(query)\n", " # Get the toolkits, one for each plugin\n", " tool_kits = [toolkits_dict[d.metadata[\"plugin_name\"]] for d in docs]\n", " # Get the tools: a separate NLAChain for each endpoint\n", diff --git a/cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb b/cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb index 7dfa363ece..6dc58edbeb 100644 --- a/cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb +++ b/cookbook/custom_agent_with_plugin_retrieval_using_plugnplai.ipynb @@ -193,7 +193,7 @@ "\n", "def get_tools(query):\n", " # Get documents, which contain the Plugins to use\n", - " docs = retriever.get_relevant_documents(query)\n", + " docs = retriever.invoke(query)\n", " # Get the toolkits, one for each plugin\n", " tool_kits = [toolkits_dict[d.metadata[\"plugin_name\"]] for d in docs]\n", " # Get the tools: a separate NLAChain for each endpoint\n", diff --git a/cookbook/custom_agent_with_tool_retrieval.ipynb b/cookbook/custom_agent_with_tool_retrieval.ipynb index 73105ea68e..08af601dac 100644 --- a/cookbook/custom_agent_with_tool_retrieval.ipynb +++ b/cookbook/custom_agent_with_tool_retrieval.ipynb @@ -142,7 +142,7 @@ "\n", "\n", "def get_tools(query):\n", - " docs = retriever.get_relevant_documents(query)\n", + " docs = retriever.invoke(query)\n", " return [ALL_TOOLS[d.metadata[\"index\"]] for d in docs]" ] }, diff --git a/cookbook/langgraph_crag.ipynb b/cookbook/langgraph_crag.ipynb index 8ac3113900..0384531116 100644 --- a/cookbook/langgraph_crag.ipynb +++ b/cookbook/langgraph_crag.ipynb @@ -206,7 +206,7 @@ " print(\"---RETRIEVE---\")\n", " state_dict = state[\"keys\"]\n", " question = state_dict[\"question\"]\n", - " documents = retriever.get_relevant_documents(question)\n", + " documents = retriever.invoke(question)\n", " return {\"keys\": {\"documents\": documents, \"question\": question}}\n", "\n", "\n", diff --git a/cookbook/langgraph_self_rag.ipynb b/cookbook/langgraph_self_rag.ipynb index 91adaf9d6f..4790a5850f 100644 --- a/cookbook/langgraph_self_rag.ipynb +++ b/cookbook/langgraph_self_rag.ipynb @@ -213,7 +213,7 @@ " print(\"---RETRIEVE---\")\n", " state_dict = state[\"keys\"]\n", " question = state_dict[\"question\"]\n", - " documents = retriever.get_relevant_documents(question)\n", + " documents = retriever.invoke(question)\n", " return {\"keys\": {\"documents\": documents, \"question\": question}}\n", "\n", "\n", diff --git a/cookbook/multi_modal_RAG_chroma.ipynb b/cookbook/multi_modal_RAG_chroma.ipynb index 0af89590bf..1f2d268502 100644 --- a/cookbook/multi_modal_RAG_chroma.ipynb +++ b/cookbook/multi_modal_RAG_chroma.ipynb @@ -435,7 +435,7 @@ " display(HTML(image_html))\n", "\n", "\n", - "docs = retriever.get_relevant_documents(\"Woman with children\", k=10)\n", + "docs = retriever.invoke(\"Woman with children\", k=10)\n", "for doc in docs:\n", " if is_base64(doc.page_content):\n", " plt_img_base64(doc.page_content)\n", diff --git a/cookbook/multi_modal_RAG_vdms.ipynb b/cookbook/multi_modal_RAG_vdms.ipynb index 01bdd28eb2..49fcce642c 100644 --- a/cookbook/multi_modal_RAG_vdms.ipynb +++ b/cookbook/multi_modal_RAG_vdms.ipynb @@ -443,7 +443,7 @@ "\n", "\n", "query = \"Woman with children\"\n", - "docs = retriever.get_relevant_documents(query, k=10)\n", + "docs = retriever.invoke(query, k=10)\n", "\n", "for doc in docs:\n", " if is_base64(doc.page_content):\n", diff --git a/cookbook/rag_semantic_chunking_azureaidocintelligence.ipynb b/cookbook/rag_semantic_chunking_azureaidocintelligence.ipynb index b0569fa281..aa758ac865 100644 --- a/cookbook/rag_semantic_chunking_azureaidocintelligence.ipynb +++ b/cookbook/rag_semantic_chunking_azureaidocintelligence.ipynb @@ -168,7 +168,7 @@ "\n", "retriever = vector_store.as_retriever(search_type=\"similarity\", search_kwargs={\"k\": 3})\n", "\n", - "retrieved_docs = retriever.get_relevant_documents(\"\")\n", + "retrieved_docs = retriever.invoke(\"\")\n", "\n", "print(retrieved_docs[0].page_content)\n", "\n", diff --git a/cookbook/self_query_hotel_search.ipynb b/cookbook/self_query_hotel_search.ipynb index 958c78fd5e..edd8b78e4f 100644 --- a/cookbook/self_query_hotel_search.ipynb +++ b/cookbook/self_query_hotel_search.ipynb @@ -1227,7 +1227,7 @@ } ], "source": [ - "results = retriever.get_relevant_documents(\n", + "results = retriever.invoke(\n", " \"I want to stay somewhere highly rated along the coast. I want a room with a patio and a fireplace.\"\n", ")\n", "for res in results:\n", diff --git a/docs/docs/integrations/chat/maritalk.ipynb b/docs/docs/integrations/chat/maritalk.ipynb index 8518ad23b3..c184c84748 100644 --- a/docs/docs/integrations/chat/maritalk.ipynb +++ b/docs/docs/integrations/chat/maritalk.ipynb @@ -184,7 +184,7 @@ "\n", "query = \"Qual o tempo máximo para realização da prova?\"\n", "\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "\n", "chain.invoke(\n", " {\"input_documents\": docs, \"query\": query}\n", diff --git a/docs/docs/integrations/document_loaders/docugami.ipynb b/docs/docs/integrations/document_loaders/docugami.ipynb index 65b53b67e5..555e47204e 100644 --- a/docs/docs/integrations/document_loaders/docugami.ipynb +++ b/docs/docs/integrations/document_loaders/docugami.ipynb @@ -630,7 +630,7 @@ ], "source": [ "# Query retriever, should return parents (using MMR since that was set as search_type above)\n", - "retrieved_parent_docs = retriever.get_relevant_documents(\n", + "retrieved_parent_docs = retriever.invoke(\n", " \"what signs does Birch Street allow on their property?\"\n", ")\n", "for chunk in retrieved_parent_docs:\n", diff --git a/docs/docs/integrations/document_loaders/figma.ipynb b/docs/docs/integrations/document_loaders/figma.ipynb index c32739339e..fd4cc237c5 100644 --- a/docs/docs/integrations/document_loaders/figma.ipynb +++ b/docs/docs/integrations/document_loaders/figma.ipynb @@ -97,7 +97,7 @@ " # delete the gpt-4 model_name to use the default gpt-3.5 turbo for faster results\n", " gpt_4 = ChatOpenAI(temperature=0.02, model_name=\"gpt-4\")\n", " # Use the retriever's 'get_relevant_documents' method if needed to filter down longer docs\n", - " relevant_nodes = figma_doc_retriever.get_relevant_documents(human_input)\n", + " relevant_nodes = figma_doc_retriever.invoke(human_input)\n", " conversation = [system_message_prompt, human_message_prompt]\n", " chat_prompt = ChatPromptTemplate.from_messages(conversation)\n", " response = gpt_4(\n", diff --git a/docs/docs/integrations/document_loaders/spreedly.ipynb b/docs/docs/integrations/document_loaders/spreedly.ipynb index 99c1d66c8b..407afb3a14 100644 --- a/docs/docs/integrations/document_loaders/spreedly.ipynb +++ b/docs/docs/integrations/document_loaders/spreedly.ipynb @@ -99,7 +99,7 @@ ], "source": [ "# Test the retriever\n", - "spreedly_doc_retriever.get_relevant_documents(\"CRC\")" + "spreedly_doc_retriever.invoke(\"CRC\")" ] }, { diff --git a/docs/docs/integrations/document_transformers/cross_encoder_reranker.ipynb b/docs/docs/integrations/document_transformers/cross_encoder_reranker.ipynb index fd06ad72b8..a200980759 100644 --- a/docs/docs/integrations/document_transformers/cross_encoder_reranker.ipynb +++ b/docs/docs/integrations/document_transformers/cross_encoder_reranker.ipynb @@ -82,7 +82,7 @@ ")\n", "\n", "query = \"What is the plan for the economy?\"\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "pretty_print_docs(docs)" ] }, @@ -162,9 +162,7 @@ " base_compressor=compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", - " \"What is the plan for the economy?\"\n", - ")\n", + "compressed_docs = compression_retriever.invoke(\"What is the plan for the economy?\")\n", "pretty_print_docs(compressed_docs)" ] }, diff --git a/docs/docs/integrations/document_transformers/openvino_rerank.ipynb b/docs/docs/integrations/document_transformers/openvino_rerank.ipynb index 55e4f54c8a..e7961bdd7b 100644 --- a/docs/docs/integrations/document_transformers/openvino_rerank.ipynb +++ b/docs/docs/integrations/document_transformers/openvino_rerank.ipynb @@ -350,7 +350,7 @@ "retriever = FAISS.from_documents(texts, embedding).as_retriever(search_kwargs={\"k\": 20})\n", "\n", "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "pretty_print_docs(docs)" ] }, @@ -388,7 +388,7 @@ " base_compressor=ov_compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "print([doc.metadata[\"id\"] for doc in compressed_docs])" diff --git a/docs/docs/integrations/document_transformers/voyageai-reranker.ipynb b/docs/docs/integrations/document_transformers/voyageai-reranker.ipynb index 3457436e54..0ffd6afb0d 100644 --- a/docs/docs/integrations/document_transformers/voyageai-reranker.ipynb +++ b/docs/docs/integrations/document_transformers/voyageai-reranker.ipynb @@ -320,7 +320,7 @@ ").as_retriever(search_kwargs={\"k\": 20})\n", "\n", "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "pretty_print_docs(docs)" ] }, @@ -382,7 +382,7 @@ " base_compressor=compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "pretty_print_docs(compressed_docs)" diff --git a/docs/docs/integrations/platforms/google.mdx b/docs/docs/integrations/platforms/google.mdx index 17afe58f11..0ac026261b 100644 --- a/docs/docs/integrations/platforms/google.mdx +++ b/docs/docs/integrations/platforms/google.mdx @@ -623,7 +623,7 @@ docai_wh_retriever = GoogleDocumentAIWarehouseRetriever( project_number=... ) query = ... -documents = docai_wh_retriever.get_relevant_documents( +documents = docai_wh_retriever.invoke( query, user_ldap=... ) ``` diff --git a/docs/docs/integrations/providers/cohere.mdx b/docs/docs/integrations/providers/cohere.mdx index e6a1861547..a5d46f3bfc 100644 --- a/docs/docs/integrations/providers/cohere.mdx +++ b/docs/docs/integrations/providers/cohere.mdx @@ -83,7 +83,7 @@ from langchain.retrievers import CohereRagRetriever from langchain_core.documents import Document rag = CohereRagRetriever(llm=ChatCohere()) -print(rag.get_relevant_documents("What is cohere ai?")) +print(rag.invoke("What is cohere ai?")) ``` Usage of the Cohere [RAG Retriever](/docs/integrations/retrievers/cohere) diff --git a/docs/docs/integrations/providers/metal.mdx b/docs/docs/integrations/providers/metal.mdx index 473e2510e6..455830b2db 100644 --- a/docs/docs/integrations/providers/metal.mdx +++ b/docs/docs/integrations/providers/metal.mdx @@ -22,5 +22,5 @@ from metal_sdk.metal import Metal metal = Metal("API_KEY", "CLIENT_ID", "INDEX_ID"); retriever = MetalRetriever(metal, params={"limit": 2}) -docs = retriever.get_relevant_documents("search term") +docs = retriever.invoke("search term") ``` diff --git a/docs/docs/integrations/providers/ragatouille.ipynb b/docs/docs/integrations/providers/ragatouille.ipynb index 6f7da3b6dd..b5b137b6c6 100644 --- a/docs/docs/integrations/providers/ragatouille.ipynb +++ b/docs/docs/integrations/providers/ragatouille.ipynb @@ -199,7 +199,7 @@ " base_compressor=RAG.as_langchain_document_compressor(), base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What animation studio did Miyazaki found\"\n", ")" ] diff --git a/docs/docs/integrations/providers/vectara/vectara_chat.ipynb b/docs/docs/integrations/providers/vectara/vectara_chat.ipynb index 8a995ee1ea..1debc3ae85 100644 --- a/docs/docs/integrations/providers/vectara/vectara_chat.ipynb +++ b/docs/docs/integrations/providers/vectara/vectara_chat.ipynb @@ -154,9 +154,7 @@ "openai_api_key = os.environ[\"OPENAI_API_KEY\"]\n", "llm = OpenAI(openai_api_key=openai_api_key, temperature=0)\n", "retriever = vectara.as_retriever()\n", - "d = retriever.get_relevant_documents(\n", - " \"What did the president say about Ketanji Brown Jackson\", k=2\n", - ")\n", + "d = retriever.invoke(\"What did the president say about Ketanji Brown Jackson\", k=2)\n", "print(d)" ] }, diff --git a/docs/docs/integrations/retrievers/amazon_kendra_retriever.ipynb b/docs/docs/integrations/retrievers/amazon_kendra_retriever.ipynb index 7c4c78ae4a..c4d0abfe6d 100644 --- a/docs/docs/integrations/retrievers/amazon_kendra_retriever.ipynb +++ b/docs/docs/integrations/retrievers/amazon_kendra_retriever.ipynb @@ -69,7 +69,7 @@ "metadata": {}, "outputs": [], "source": [ - "retriever.get_relevant_documents(\"what is langchain\")" + "retriever.invoke(\"what is langchain\")" ] } ], diff --git a/docs/docs/integrations/retrievers/arcee.ipynb b/docs/docs/integrations/retrievers/arcee.ipynb index 1013baf72c..e8639c339b 100644 --- a/docs/docs/integrations/retrievers/arcee.ipynb +++ b/docs/docs/integrations/retrievers/arcee.ipynb @@ -83,7 +83,7 @@ "outputs": [], "source": [ "query = \"Can AI-driven music therapy contribute to the rehabilitation of patients with disorders of consciousness?\"\n", - "documents = retriever.get_relevant_documents(query=query)" + "documents = retriever.invoke(query)" ] }, { @@ -108,7 +108,7 @@ "]\n", "\n", "# Retrieve documents with filters and size params\n", - "documents = retriever.get_relevant_documents(query=query, size=5, filters=filters)" + "documents = retriever.invoke(query, size=5, filters=filters)" ] } ], diff --git a/docs/docs/integrations/retrievers/arxiv.ipynb b/docs/docs/integrations/retrievers/arxiv.ipynb index d347962dde..ee12166658 100644 --- a/docs/docs/integrations/retrievers/arxiv.ipynb +++ b/docs/docs/integrations/retrievers/arxiv.ipynb @@ -97,7 +97,7 @@ "metadata": {}, "outputs": [], "source": [ - "docs = retriever.get_relevant_documents(query=\"1605.08386\")" + "docs = retriever.invoke(\"1605.08386\")" ] }, { @@ -162,7 +162,7 @@ }, "outputs": [ { - "name": "stdin", + "name": "stdout", "output_type": "stream", "text": [ " ········\n" diff --git a/docs/docs/integrations/retrievers/azure_ai_search.ipynb b/docs/docs/integrations/retrievers/azure_ai_search.ipynb index 6151fc2227..15d3210d79 100644 --- a/docs/docs/integrations/retrievers/azure_ai_search.ipynb +++ b/docs/docs/integrations/retrievers/azure_ai_search.ipynb @@ -117,7 +117,7 @@ "metadata": {}, "outputs": [], "source": [ - "retriever.get_relevant_documents(\"what is langchain?\")" + "retriever.invoke(\"what is langchain?\")" ] }, { @@ -263,7 +263,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"What is Azure OpenAI?\")" + "retriever.invoke(\"What is Azure OpenAI?\")" ] } ], diff --git a/docs/docs/integrations/retrievers/bedrock.ipynb b/docs/docs/integrations/retrievers/bedrock.ipynb index 64a2bec90f..f34ad9d4a9 100644 --- a/docs/docs/integrations/retrievers/bedrock.ipynb +++ b/docs/docs/integrations/retrievers/bedrock.ipynb @@ -58,7 +58,7 @@ "source": [ "query = \"What did the president say about Ketanji Brown?\"\n", "\n", - "retriever.get_relevant_documents(query=query)" + "retriever.invoke(query)" ] }, { diff --git a/docs/docs/integrations/retrievers/bm25.ipynb b/docs/docs/integrations/retrievers/bm25.ipynb index 7f15bb5b9b..5e0b3fa198 100644 --- a/docs/docs/integrations/retrievers/bm25.ipynb +++ b/docs/docs/integrations/retrievers/bm25.ipynb @@ -103,7 +103,7 @@ }, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\"foo\")" + "result = retriever.invoke(\"foo\")" ] }, { diff --git a/docs/docs/integrations/retrievers/breebs.ipynb b/docs/docs/integrations/retrievers/breebs.ipynb index f9fa9d84b2..12dce27d0f 100644 --- a/docs/docs/integrations/retrievers/breebs.ipynb +++ b/docs/docs/integrations/retrievers/breebs.ipynb @@ -64,7 +64,7 @@ "source": [ "breeb_key = \"Parivoyage\"\n", "retriever = BreebsRetriever(breeb_key)\n", - "documents = retriever.get_relevant_documents(\n", + "documents = retriever.invoke(\n", " \"What are some unique, lesser-known spots to explore in Paris?\"\n", ")\n", "print(documents)" diff --git a/docs/docs/integrations/retrievers/chaindesk.ipynb b/docs/docs/integrations/retrievers/chaindesk.ipynb index 7968e1cd0c..d27e4b99c1 100644 --- a/docs/docs/integrations/retrievers/chaindesk.ipynb +++ b/docs/docs/integrations/retrievers/chaindesk.ipynb @@ -83,7 +83,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"What is Daftpage?\")" + "retriever.invoke(\"What is Daftpage?\")" ] } ], diff --git a/docs/docs/integrations/retrievers/chatgpt-plugin.ipynb b/docs/docs/integrations/retrievers/chatgpt-plugin.ipynb index 5b00552d80..13c782983a 100644 --- a/docs/docs/integrations/retrievers/chatgpt-plugin.ipynb +++ b/docs/docs/integrations/retrievers/chatgpt-plugin.ipynb @@ -150,7 +150,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"alice's phone number\")" + "retriever.invoke(\"alice's phone number\")" ] }, { diff --git a/docs/docs/integrations/retrievers/cohere-reranker.ipynb b/docs/docs/integrations/retrievers/cohere-reranker.ipynb index 2378ccec45..0441bce6be 100644 --- a/docs/docs/integrations/retrievers/cohere-reranker.ipynb +++ b/docs/docs/integrations/retrievers/cohere-reranker.ipynb @@ -314,7 +314,7 @@ ")\n", "\n", "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "pretty_print_docs(docs)" ] }, @@ -344,7 +344,7 @@ " base_compressor=compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "pretty_print_docs(compressed_docs)" diff --git a/docs/docs/integrations/retrievers/cohere.ipynb b/docs/docs/integrations/retrievers/cohere.ipynb index 55640d8f6c..e14e738d0c 100644 --- a/docs/docs/integrations/retrievers/cohere.ipynb +++ b/docs/docs/integrations/retrievers/cohere.ipynb @@ -118,7 +118,7 @@ } ], "source": [ - "_pretty_print(rag.get_relevant_documents(\"What is cohere ai?\"))" + "_pretty_print(rag.invoke(\"What is cohere ai?\"))" ] }, { @@ -172,7 +172,7 @@ } ], "source": [ - "_pretty_print(await rag.aget_relevant_documents(\"What is cohere ai?\")) # async version" + "_pretty_print(await rag.ainvoke(\"What is cohere ai?\")) # async version" ] }, { @@ -198,7 +198,7 @@ } ], "source": [ - "docs = rag.get_relevant_documents(\n", + "docs = rag.invoke(\n", " \"Does langchain support cohere RAG?\",\n", " source_documents=[\n", " Document(page_content=\"Langchain supports cohere RAG!\"),\n", diff --git a/docs/docs/integrations/retrievers/docarray_retriever.ipynb b/docs/docs/integrations/retrievers/docarray_retriever.ipynb index 51aa1f4f82..162d7914ec 100644 --- a/docs/docs/integrations/retrievers/docarray_retriever.ipynb +++ b/docs/docs/integrations/retrievers/docarray_retriever.ipynb @@ -143,7 +143,7 @@ ")\n", "\n", "# find the relevant document\n", - "doc = retriever.get_relevant_documents(\"some query\")\n", + "doc = retriever.invoke(\"some query\")\n", "print(doc)" ] }, @@ -216,7 +216,7 @@ ")\n", "\n", "# find the relevant document\n", - "doc = retriever.get_relevant_documents(\"some query\")\n", + "doc = retriever.invoke(\"some query\")\n", "print(doc)" ] }, @@ -313,7 +313,7 @@ ")\n", "\n", "# find the relevant document\n", - "doc = retriever.get_relevant_documents(\"some query\")\n", + "doc = retriever.invoke(\"some query\")\n", "print(doc)" ] }, @@ -388,7 +388,7 @@ ")\n", "\n", "# find the relevant document\n", - "doc = retriever.get_relevant_documents(\"some query\")\n", + "doc = retriever.invoke(\"some query\")\n", "print(doc)" ] }, @@ -481,7 +481,7 @@ ")\n", "\n", "# find the relevant document\n", - "doc = retriever.get_relevant_documents(\"some query\")\n", + "doc = retriever.invoke(\"some query\")\n", "print(doc)" ] }, @@ -658,7 +658,7 @@ ")\n", "\n", "# find the relevant document\n", - "doc = retriever.get_relevant_documents(\"movie about dreams\")\n", + "doc = retriever.invoke(\"movie about dreams\")\n", "print(doc)" ] }, @@ -700,7 +700,7 @@ ")\n", "\n", "# find relevant documents\n", - "docs = retriever.get_relevant_documents(\"space travel\")\n", + "docs = retriever.invoke(\"space travel\")\n", "print(docs)" ] }, @@ -743,7 +743,7 @@ ")\n", "\n", "# find relevant documents\n", - "docs = retriever.get_relevant_documents(\"action movies\")\n", + "docs = retriever.invoke(\"action movies\")\n", "print(docs)" ] }, diff --git a/docs/docs/integrations/retrievers/dria_index.ipynb b/docs/docs/integrations/retrievers/dria_index.ipynb index 5f6329ec1b..eb3b858c0e 100644 --- a/docs/docs/integrations/retrievers/dria_index.ipynb +++ b/docs/docs/integrations/retrievers/dria_index.ipynb @@ -158,7 +158,7 @@ "outputs": [], "source": [ "query = \"Find information about Dria.\"\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "for doc in result:\n", " print(doc)" ] diff --git a/docs/docs/integrations/retrievers/elastic_search_bm25.ipynb b/docs/docs/integrations/retrievers/elastic_search_bm25.ipynb index 656d9a6ee4..339e02331c 100644 --- a/docs/docs/integrations/retrievers/elastic_search_bm25.ipynb +++ b/docs/docs/integrations/retrievers/elastic_search_bm25.ipynb @@ -130,7 +130,7 @@ "metadata": {}, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\"foo\")" + "result = retriever.invoke(\"foo\")" ] }, { diff --git a/docs/docs/integrations/retrievers/elasticsearch_retriever.ipynb b/docs/docs/integrations/retrievers/elasticsearch_retriever.ipynb index 0b72a99829..e24914a80c 100644 --- a/docs/docs/integrations/retrievers/elasticsearch_retriever.ipynb +++ b/docs/docs/integrations/retrievers/elasticsearch_retriever.ipynb @@ -263,7 +263,7 @@ " url=es_url,\n", ")\n", "\n", - "vector_retriever.get_relevant_documents(\"foo\")" + "vector_retriever.invoke(\"foo\")" ] }, { @@ -313,7 +313,7 @@ " url=es_url,\n", ")\n", "\n", - "bm25_retriever.get_relevant_documents(\"foo\")" + "bm25_retriever.invoke(\"foo\")" ] }, { @@ -371,7 +371,7 @@ " url=es_url,\n", ")\n", "\n", - "hybrid_retriever.get_relevant_documents(\"foo\")" + "hybrid_retriever.invoke(\"foo\")" ] }, { @@ -424,7 +424,7 @@ " url=es_url,\n", ")\n", "\n", - "fuzzy_retriever.get_relevant_documents(\"fox\") # note the character tolernace" + "fuzzy_retriever.invoke(\"fox\") # note the character tolernace" ] }, { @@ -483,7 +483,7 @@ " url=es_url,\n", ")\n", "\n", - "filtering_retriever.get_relevant_documents(\"foo\")" + "filtering_retriever.invoke(\"foo\")" ] }, { @@ -541,7 +541,7 @@ " url=es_url,\n", ")\n", "\n", - "custom_mapped_retriever.get_relevant_documents(\"foo\")" + "custom_mapped_retriever.invoke(\"foo\")" ] } ], diff --git a/docs/docs/integrations/retrievers/embedchain.ipynb b/docs/docs/integrations/retrievers/embedchain.ipynb index 97dc8a99b7..5c4d883aac 100644 --- a/docs/docs/integrations/retrievers/embedchain.ipynb +++ b/docs/docs/integrations/retrievers/embedchain.ipynb @@ -194,9 +194,7 @@ "metadata": {}, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\n", - " \"How many companies does Elon Musk run and name those?\"\n", - ")" + "result = retriever.invoke(\"How many companies does Elon Musk run and name those?\")" ] }, { diff --git a/docs/docs/integrations/retrievers/flashrank-reranker.ipynb b/docs/docs/integrations/retrievers/flashrank-reranker.ipynb index f63605526d..6c0517afe8 100644 --- a/docs/docs/integrations/retrievers/flashrank-reranker.ipynb +++ b/docs/docs/integrations/retrievers/flashrank-reranker.ipynb @@ -328,7 +328,7 @@ "retriever = FAISS.from_documents(texts, embedding).as_retriever(search_kwargs={\"k\": 20})\n", "\n", "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "pretty_print_docs(docs)" ] }, @@ -375,7 +375,7 @@ " base_compressor=compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "print([doc.metadata[\"id\"] for doc in compressed_docs])" diff --git a/docs/docs/integrations/retrievers/fleet_context.ipynb b/docs/docs/integrations/retrievers/fleet_context.ipynb index af85caa0cb..4b20645ddb 100644 --- a/docs/docs/integrations/retrievers/fleet_context.ipynb +++ b/docs/docs/integrations/retrievers/fleet_context.ipynb @@ -131,7 +131,7 @@ "metadata": {}, "outputs": [], "source": [ - "vecstore_retriever.get_relevant_documents(\"How does the multi vector retriever work\")" + "vecstore_retriever.invoke(\"How does the multi vector retriever work\")" ] }, { @@ -176,7 +176,7 @@ "metadata": {}, "outputs": [], "source": [ - "parent_retriever.get_relevant_documents(\"How does the multi vector retriever work\")" + "parent_retriever.invoke(\"How does the multi vector retriever work\")" ] }, { diff --git a/docs/docs/integrations/retrievers/google_drive.ipynb b/docs/docs/integrations/retrievers/google_drive.ipynb index f008627c3a..5736f5d763 100644 --- a/docs/docs/integrations/retrievers/google_drive.ipynb +++ b/docs/docs/integrations/retrievers/google_drive.ipynb @@ -114,7 +114,7 @@ }, "outputs": [], "source": [ - "retriever.get_relevant_documents(\"machine learning\")" + "retriever.invoke(\"machine learning\")" ] }, { @@ -149,7 +149,7 @@ " template=\"gdrive-query\", # Search everywhere\n", " num_results=2, # But take only 2 documents\n", ")\n", - "for doc in retriever.get_relevant_documents(\"machine learning\"):\n", + "for doc in retriever.invoke(\"machine learning\"):\n", " print(\"---\")\n", " print(doc.page_content.strip()[:60] + \"...\")" ] @@ -187,7 +187,7 @@ " includeItemsFromAllDrives=False,\n", " supportsAllDrives=False,\n", ")\n", - "for doc in retriever.get_relevant_documents(\"machine learning\"):\n", + "for doc in retriever.invoke(\"machine learning\"):\n", " print(f\"{doc.metadata['name']}:\")\n", " print(\"---\")\n", " print(doc.page_content.strip()[:60] + \"...\")" @@ -222,7 +222,7 @@ " includeItemsFromAllDrives=False,\n", " supportsAllDrives=False,\n", ")\n", - "retriever.get_relevant_documents(\"machine learning\")" + "retriever.invoke(\"machine learning\")" ] } ], diff --git a/docs/docs/integrations/retrievers/google_vertex_ai_search.ipynb b/docs/docs/integrations/retrievers/google_vertex_ai_search.ipynb index 4da87c1ce7..f0c3add29d 100644 --- a/docs/docs/integrations/retrievers/google_vertex_ai_search.ipynb +++ b/docs/docs/integrations/retrievers/google_vertex_ai_search.ipynb @@ -198,7 +198,7 @@ "source": [ "query = \"What are Alphabet's Other Bets?\"\n", "\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "for doc in result:\n", " print(doc)" ] @@ -225,7 +225,7 @@ " get_extractive_answers=True,\n", ")\n", "\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "for doc in result:\n", " print(doc)" ] @@ -251,7 +251,7 @@ " engine_data_type=1,\n", ")\n", "\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "for doc in result:\n", " print(doc)" ] @@ -279,7 +279,7 @@ " engine_data_type=2,\n", ")\n", "\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "for doc in result:\n", " print(doc)" ] @@ -305,7 +305,7 @@ " engine_data_type=3,\n", ")\n", "\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "for doc in result:\n", " print(doc)" ] @@ -329,7 +329,7 @@ " project_id=PROJECT_ID, location_id=LOCATION_ID, data_store_id=DATA_STORE_ID\n", ")\n", "\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "for doc in result:\n", " print(doc)" ] diff --git a/docs/docs/integrations/retrievers/kay.ipynb b/docs/docs/integrations/retrievers/kay.ipynb index 66d8ed7b73..3cbe986cc9 100644 --- a/docs/docs/integrations/retrievers/kay.ipynb +++ b/docs/docs/integrations/retrievers/kay.ipynb @@ -92,7 +92,7 @@ "retriever = KayAiRetriever.create(\n", " dataset_id=\"company\", data_types=[\"10-K\", \"10-Q\", \"PressRelease\"], num_contexts=3\n", ")\n", - "docs = retriever.get_relevant_documents(\n", + "docs = retriever.invoke(\n", " \"What were the biggest strategy changes and partnerships made by Roku in 2023??\"\n", ")" ] diff --git a/docs/docs/integrations/retrievers/knn.ipynb b/docs/docs/integrations/retrievers/knn.ipynb index 9eb641ffe8..9ce5716103 100644 --- a/docs/docs/integrations/retrievers/knn.ipynb +++ b/docs/docs/integrations/retrievers/knn.ipynb @@ -62,7 +62,7 @@ "metadata": {}, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\"foo\")" + "result = retriever.invoke(\"foo\")" ] }, { diff --git a/docs/docs/integrations/retrievers/llmlingua.ipynb b/docs/docs/integrations/retrievers/llmlingua.ipynb index 49946f0db1..5cac38d5c3 100644 --- a/docs/docs/integrations/retrievers/llmlingua.ipynb +++ b/docs/docs/integrations/retrievers/llmlingua.ipynb @@ -296,7 +296,7 @@ "retriever = FAISS.from_documents(texts, embedding).as_retriever(search_kwargs={\"k\": 20})\n", "\n", "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "pretty_print_docs(docs)" ] }, @@ -350,7 +350,7 @@ " base_compressor=compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "pretty_print_docs(compressed_docs)" diff --git a/docs/docs/integrations/retrievers/metal.ipynb b/docs/docs/integrations/retrievers/metal.ipynb index 8a6b51ee41..973d247017 100644 --- a/docs/docs/integrations/retrievers/metal.ipynb +++ b/docs/docs/integrations/retrievers/metal.ipynb @@ -123,7 +123,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"foo1\")" + "retriever.invoke(\"foo1\")" ] }, { diff --git a/docs/docs/integrations/retrievers/outline.ipynb b/docs/docs/integrations/retrievers/outline.ipynb index c8007304c0..fcaec16866 100644 --- a/docs/docs/integrations/retrievers/outline.ipynb +++ b/docs/docs/integrations/retrievers/outline.ipynb @@ -109,7 +109,7 @@ } ], "source": [ - "retriever.get_relevant_documents(query=\"LangChain\", doc_content_chars_max=100)" + "retriever.invoke(\"LangChain\", doc_content_chars_max=100)" ] }, { diff --git a/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb b/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb index 8d7fc74849..b9916ec316 100644 --- a/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb +++ b/docs/docs/integrations/retrievers/pinecone_hybrid_search.ipynb @@ -295,7 +295,7 @@ "metadata": {}, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\"foo\")" + "result = retriever.invoke(\"foo\")" ] }, { diff --git a/docs/docs/integrations/retrievers/pubmed.ipynb b/docs/docs/integrations/retrievers/pubmed.ipynb index 7a35132838..a221bedf8c 100644 --- a/docs/docs/integrations/retrievers/pubmed.ipynb +++ b/docs/docs/integrations/retrievers/pubmed.ipynb @@ -53,7 +53,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"chatgpt\")" + "retriever.invoke(\"chatgpt\")" ] }, { diff --git a/docs/docs/integrations/retrievers/qdrant-sparse.ipynb b/docs/docs/integrations/retrievers/qdrant-sparse.ipynb index 54607f97f4..394873b4e6 100644 --- a/docs/docs/integrations/retrievers/qdrant-sparse.ipynb +++ b/docs/docs/integrations/retrievers/qdrant-sparse.ipynb @@ -227,7 +227,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"Life and ethical dilemmas of AI\",\n", ")" ] diff --git a/docs/docs/integrations/retrievers/re_phrase.ipynb b/docs/docs/integrations/retrievers/re_phrase.ipynb index 5cbf3c0f8c..45bd22afe4 100644 --- a/docs/docs/integrations/retrievers/re_phrase.ipynb +++ b/docs/docs/integrations/retrievers/re_phrase.ipynb @@ -100,7 +100,7 @@ } ], "source": [ - "docs = retriever_from_llm.get_relevant_documents(\n", + "docs = retriever_from_llm.invoke(\n", " \"Hi I'm Lance. What are the approaches to Task Decomposition?\"\n", ")" ] @@ -120,7 +120,7 @@ } ], "source": [ - "docs = retriever_from_llm.get_relevant_documents(\n", + "docs = retriever_from_llm.invoke(\n", " \"I live in San Francisco. What are the Types of Memory?\"\n", ")" ] @@ -182,7 +182,7 @@ } ], "source": [ - "docs = retriever_from_llm_chain.get_relevant_documents(\n", + "docs = retriever_from_llm_chain.invoke(\n", " \"Hi I'm Lance. What is Maximum Inner Product Search?\"\n", ")" ] diff --git a/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb index 64cdc8f670..f75c2b9792 100644 --- a/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/activeloop_deeplake_self_query.ipynb @@ -270,7 +270,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -300,7 +300,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")\n", + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")\n", "\n", "# in case if this example errored out, consider installing libdeeplake manually: `pip install libdeeplake`, and then restart notebook." ] @@ -331,7 +331,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -360,9 +360,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -391,7 +389,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -457,7 +455,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/astradb.ipynb b/docs/docs/integrations/retrievers/self_query/astradb.ipynb index a37597cf2e..441d897179 100644 --- a/docs/docs/integrations/retrievers/self_query/astradb.ipynb +++ b/docs/docs/integrations/retrievers/self_query/astradb.ipynb @@ -192,7 +192,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs?\")" + "retriever.invoke(\"What are some movies about dinosaurs?\")" ] }, { @@ -202,7 +202,7 @@ "outputs": [], "source": [ "# This example specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -212,7 +212,7 @@ "outputs": [], "source": [ "# This example only specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -222,9 +222,7 @@ "outputs": [], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5), science fiction movie ?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5), science fiction movie ?\")" ] }, { @@ -234,7 +232,7 @@ "outputs": [], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie about toys after 1990 but before 2005, and is animated\"\n", ")" ] @@ -273,7 +271,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are two movies about dinosaurs?\")" + "retriever.invoke(\"What are two movies about dinosaurs?\")" ] }, { diff --git a/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb index 08ee33c5c3..69ddb0cad2 100644 --- a/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/chroma_self_query.ipynb @@ -232,7 +232,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -262,7 +262,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -291,7 +291,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -320,9 +320,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -351,7 +349,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -418,7 +416,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] }, { diff --git a/docs/docs/integrations/retrievers/self_query/dashvector.ipynb b/docs/docs/integrations/retrievers/self_query/dashvector.ipynb index 7f58c757d9..a5c856d955 100644 --- a/docs/docs/integrations/retrievers/self_query/dashvector.ipynb +++ b/docs/docs/integrations/retrievers/self_query/dashvector.ipynb @@ -269,7 +269,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -308,7 +308,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -346,7 +346,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -384,9 +384,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -468,7 +466,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] }, { diff --git a/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb b/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb index f32359602e..6badeef82d 100644 --- a/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb +++ b/docs/docs/integrations/retrievers/self_query/databricks_vector_search.ipynb @@ -352,7 +352,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -384,7 +384,7 @@ ], "source": [ "# This example specifies a filter\n", - "retriever.get_relevant_documents(\"What are some highly rated movies (above 9)?\")" + "retriever.invoke(\"What are some highly rated movies (above 9)?\")" ] }, { @@ -416,7 +416,7 @@ ], "source": [ "# This example specifies both a relevant query and a filter\n", - "retriever.get_relevant_documents(\"What are the thriller movies that are highly rated?\")" + "retriever.invoke(\"What are the thriller movies that are highly rated?\")" ] }, { @@ -438,7 +438,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about dinosaurs, \\\n", " and preferably has a lot of action\"\n", ")" @@ -520,7 +520,7 @@ }, "outputs": [], "source": [ - "retriever.get_relevant_documents(\"What are two movies about dinosaurs?\")" + "retriever.invoke(\"What are two movies about dinosaurs?\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/dingo.ipynb b/docs/docs/integrations/retrievers/self_query/dingo.ipynb index ede98b7bc0..5afbd18720 100644 --- a/docs/docs/integrations/retrievers/self_query/dingo.ipynb +++ b/docs/docs/integrations/retrievers/self_query/dingo.ipynb @@ -265,7 +265,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -296,7 +296,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -326,7 +326,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -357,9 +357,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -389,7 +387,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -450,7 +448,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are two movies about dinosaurs\")" + "retriever.invoke(\"What are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/elasticsearch_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/elasticsearch_self_query.ipynb index 3c9798b0f0..2d8d4bf605 100644 --- a/docs/docs/integrations/retrievers/self_query/elasticsearch_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/elasticsearch_self_query.ipynb @@ -197,7 +197,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -219,7 +219,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -275,7 +275,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] }, { @@ -305,7 +305,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"what animated or comedy movies have been released in the last 30 years about animated toys?\"\n", ")" ] diff --git a/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb index 2a66e11040..18ae2263c7 100644 --- a/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/milvus_self_query.ipynb @@ -190,7 +190,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -219,7 +219,7 @@ ], "source": [ "# This example specifies a filter\n", - "retriever.get_relevant_documents(\"What are some highly rated movies (above 9)?\")" + "retriever.invoke(\"What are some highly rated movies (above 9)?\")" ] }, { @@ -248,9 +248,7 @@ ], "source": [ "# This example only specifies a query and a filter\n", - "retriever.get_relevant_documents(\n", - " \"I want to watch a movie about toys rated higher than 9\"\n", - ")" + "retriever.invoke(\"I want to watch a movie about toys rated higher than 9\")" ] }, { @@ -278,9 +276,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above or equal 9) thriller film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above or equal 9) thriller film?\")" ] }, { @@ -308,7 +304,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about dinosaurs, \\\n", " and preferably has a lot of action\"\n", ")" @@ -367,7 +363,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are two movies about dinosaurs?\")" + "retriever.invoke(\"What are two movies about dinosaurs?\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb b/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb index d7b13b47f0..045a224acd 100644 --- a/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb +++ b/docs/docs/integrations/retrievers/self_query/mongodb_atlas.ipynb @@ -209,7 +209,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -219,7 +219,7 @@ "outputs": [], "source": [ "# This example specifies a filter\n", - "retriever.get_relevant_documents(\"What are some highly rated movies (above 9)?\")" + "retriever.invoke(\"What are some highly rated movies (above 9)?\")" ] }, { @@ -229,9 +229,7 @@ "outputs": [], "source": [ "# This example only specifies a query and a filter\n", - "retriever.get_relevant_documents(\n", - " \"I want to watch a movie about toys rated higher than 9\"\n", - ")" + "retriever.invoke(\"I want to watch a movie about toys rated higher than 9\")" ] }, { @@ -241,9 +239,7 @@ "outputs": [], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above or equal 9) thriller film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above or equal 9) thriller film?\")" ] }, { @@ -253,7 +249,7 @@ "outputs": [], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about dinosaurs, \\\n", " and preferably has a lot of action\"\n", ")" @@ -293,7 +289,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are two movies about dinosaurs?\")" + "retriever.invoke(\"What are two movies about dinosaurs?\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb index 3fb8c27ea4..c26e04d0fd 100644 --- a/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/myscale_self_query.ipynb @@ -216,7 +216,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -227,7 +227,7 @@ "outputs": [], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -238,7 +238,7 @@ "outputs": [], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -249,9 +249,7 @@ "outputs": [], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -262,7 +260,7 @@ "outputs": [], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -285,7 +283,7 @@ "outputs": [], "source": [ "# You can use length(genres) to do anything you want\n", - "retriever.get_relevant_documents(\"What's a movie that have more than 1 genres?\")" + "retriever.invoke(\"What's a movie that have more than 1 genres?\")" ] }, { @@ -296,7 +294,7 @@ "outputs": [], "source": [ "# Fine-grained datetime? You got it already.\n", - "retriever.get_relevant_documents(\"What's a movie that release after feb 1995?\")" + "retriever.invoke(\"What's a movie that release after feb 1995?\")" ] }, { @@ -307,7 +305,7 @@ "outputs": [], "source": [ "# Don't know what your exact filter should be? Use string pattern match!\n", - "retriever.get_relevant_documents(\"What's a movie whose name is like Andrei?\")" + "retriever.invoke(\"What's a movie whose name is like Andrei?\")" ] }, { @@ -318,9 +316,7 @@ "outputs": [], "source": [ "# Contain works for lists: so you can match a list with contain comparator!\n", - "retriever.get_relevant_documents(\n", - " \"What's a movie who has genres science fiction and adventure?\"\n", - ")" + "retriever.invoke(\"What's a movie who has genres science fiction and adventure?\")" ] }, { @@ -364,7 +360,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb index 1f46e5e2d2..55f8ae1248 100644 --- a/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/opensearch_self_query.ipynb @@ -203,7 +203,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -233,7 +233,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -262,7 +262,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -291,9 +291,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -356,7 +354,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] }, { @@ -393,7 +391,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"what animated or comedy movies have been released in the last 30 years about animated toys?\"\n", ")" ] diff --git a/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb index 0ea1983673..3de7bfc9bb 100644 --- a/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/pgvector_self_query.ipynb @@ -188,7 +188,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -199,7 +199,7 @@ "outputs": [], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -210,7 +210,7 @@ "outputs": [], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -221,9 +221,7 @@ "outputs": [], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -234,7 +232,7 @@ "outputs": [], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -280,7 +278,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/pinecone.ipynb b/docs/docs/integrations/retrievers/self_query/pinecone.ipynb index e9248d0780..5555715585 100644 --- a/docs/docs/integrations/retrievers/self_query/pinecone.ipynb +++ b/docs/docs/integrations/retrievers/self_query/pinecone.ipynb @@ -214,7 +214,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -244,7 +244,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -273,7 +273,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -302,9 +302,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -333,7 +331,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -375,7 +373,7 @@ "outputs": [], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are two movies about dinosaurs\")" + "retriever.invoke(\"What are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb index 063fa3573d..50b162b692 100644 --- a/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/qdrant_self_query.ipynb @@ -214,7 +214,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -244,7 +244,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -273,7 +273,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -302,9 +302,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -333,7 +331,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -399,7 +397,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb index 0d5adf0ce0..a644a39e89 100644 --- a/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/redis_self_query.ipynb @@ -279,7 +279,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -310,7 +310,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.4\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.4\")" ] }, { @@ -339,7 +339,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -369,9 +369,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -400,7 +398,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -465,7 +463,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb index d1bed3d9dc..b4504f8617 100644 --- a/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/supabase_self_query.ipynb @@ -374,7 +374,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -404,7 +404,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -433,7 +433,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women?\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women?\")" ] }, { @@ -462,9 +462,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -493,7 +491,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before (or on) 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -558,7 +556,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb b/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb index c871e88083..3ab481619e 100644 --- a/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb +++ b/docs/docs/integrations/retrievers/self_query/tencentvectordb.ipynb @@ -297,7 +297,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"movies about a superhero\")" + "retriever.invoke(\"movies about a superhero\")" ] }, { @@ -323,7 +323,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"movies that were released after 2010\")" + "retriever.invoke(\"movies that were released after 2010\")" ] }, { @@ -349,9 +349,7 @@ ], "source": [ "# This example specifies both a relevant query and a filter\n", - "retriever.get_relevant_documents(\n", - " \"movies about a superhero which were released after 2010\"\n", - ")" + "retriever.invoke(\"movies about a superhero which were released after 2010\")" ] }, { @@ -413,7 +411,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"what are two movies about a superhero\")" + "retriever.invoke(\"what are two movies about a superhero\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb index f74fff3255..f78a2f107c 100644 --- a/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/timescalevector_self_query.ipynb @@ -334,7 +334,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -366,7 +366,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -396,7 +396,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -426,9 +426,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -457,7 +455,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -523,7 +521,7 @@ ], "source": [ "# This example specifies a query with a LIMIT value\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb index 807fe75be7..8434c0e6fa 100644 --- a/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/vectara_self_query.ipynb @@ -225,7 +225,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -248,7 +248,7 @@ ], "source": [ "# This example only specifies a filter\n", - "retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")" + "retriever.invoke(\"I want to watch a movie rated higher than 8.5\")" ] }, { @@ -270,7 +270,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -292,9 +292,7 @@ ], "source": [ "# This example specifies a composite filter\n", - "retriever.get_relevant_documents(\n", - " \"What's a highly rated (above 8.5) science fiction film?\"\n", - ")" + "retriever.invoke(\"What's a highly rated (above 8.5) science fiction film?\")" ] }, { @@ -316,7 +314,7 @@ ], "source": [ "# This example specifies a query and composite filter\n", - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\"\n", ")" ] @@ -374,7 +372,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb b/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb index ed29277217..df5fd9d03e 100644 --- a/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb +++ b/docs/docs/integrations/retrievers/self_query/weaviate_self_query.ipynb @@ -184,7 +184,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are some movies about dinosaurs\")" + "retriever.invoke(\"What are some movies about dinosaurs\")" ] }, { @@ -213,7 +213,7 @@ ], "source": [ "# This example specifies a query and a filter\n", - "retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")" + "retriever.invoke(\"Has Greta Gerwig directed any movies about women\")" ] }, { @@ -276,7 +276,7 @@ ], "source": [ "# This example only specifies a relevant query\n", - "retriever.get_relevant_documents(\"what are two movies about dinosaurs\")" + "retriever.invoke(\"what are two movies about dinosaurs\")" ] } ], diff --git a/docs/docs/integrations/retrievers/singlestoredb.ipynb b/docs/docs/integrations/retrievers/singlestoredb.ipynb index 9c3c9a5946..68f9dd8697 100644 --- a/docs/docs/integrations/retrievers/singlestoredb.ipynb +++ b/docs/docs/integrations/retrievers/singlestoredb.ipynb @@ -91,9 +91,7 @@ "metadata": {}, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\n", - " \"What did the president say about Ketanji Brown Jackson\"\n", - ")\n", + "result = retriever.invoke(\"What did the president say about Ketanji Brown Jackson\")\n", "print(docs[0].page_content)" ] } diff --git a/docs/docs/integrations/retrievers/svm.ipynb b/docs/docs/integrations/retrievers/svm.ipynb index 93df710d08..2fbd4f969f 100644 --- a/docs/docs/integrations/retrievers/svm.ipynb +++ b/docs/docs/integrations/retrievers/svm.ipynb @@ -125,7 +125,7 @@ }, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\"foo\")" + "result = retriever.invoke(\"foo\")" ] }, { diff --git a/docs/docs/integrations/retrievers/tf_idf.ipynb b/docs/docs/integrations/retrievers/tf_idf.ipynb index 617d9ab381..526febc9b6 100644 --- a/docs/docs/integrations/retrievers/tf_idf.ipynb +++ b/docs/docs/integrations/retrievers/tf_idf.ipynb @@ -105,7 +105,7 @@ }, "outputs": [], "source": [ - "result = retriever.get_relevant_documents(\"foo\")" + "result = retriever.invoke(\"foo\")" ] }, { @@ -185,7 +185,7 @@ } ], "source": [ - "retriever_copy.get_relevant_documents(\"foo\")" + "retriever_copy.invoke(\"foo\")" ] }, { diff --git a/docs/docs/integrations/retrievers/thirdai_neuraldb.ipynb b/docs/docs/integrations/retrievers/thirdai_neuraldb.ipynb index 6b5b12e922..c1dc337623 100644 --- a/docs/docs/integrations/retrievers/thirdai_neuraldb.ipynb +++ b/docs/docs/integrations/retrievers/thirdai_neuraldb.ipynb @@ -95,7 +95,7 @@ "outputs": [], "source": [ "# This returns a list of LangChain Document objects\n", - "documents = retriever.get_relevant_documents(\"query\", top_k=10)" + "documents = retriever.invoke(\"query\", top_k=10)" ] }, { diff --git a/docs/docs/integrations/retrievers/vespa.ipynb b/docs/docs/integrations/retrievers/vespa.ipynb index 98ce88e92f..ec8175eb57 100644 --- a/docs/docs/integrations/retrievers/vespa.ipynb +++ b/docs/docs/integrations/retrievers/vespa.ipynb @@ -110,7 +110,7 @@ }, "outputs": [], "source": [ - "retriever.get_relevant_documents(\"what is vespa?\")" + "retriever.invoke(\"what is vespa?\")" ] } ], diff --git a/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb b/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb index 7bb09c06b6..e02aef56f4 100644 --- a/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb +++ b/docs/docs/integrations/retrievers/weaviate-hybrid.ipynb @@ -202,7 +202,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"the ethical implications of AI\")" + "retriever.invoke(\"the ethical implications of AI\")" ] }, { @@ -233,7 +233,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"AI integration in society\",\n", " where_filter={\n", " \"path\": [\"author\"],\n", @@ -272,7 +272,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\n", + "retriever.invoke(\n", " \"AI integration in society\",\n", " score=True,\n", ")" diff --git a/docs/docs/integrations/retrievers/wikipedia.ipynb b/docs/docs/integrations/retrievers/wikipedia.ipynb index c17d3e6a70..e089508566 100644 --- a/docs/docs/integrations/retrievers/wikipedia.ipynb +++ b/docs/docs/integrations/retrievers/wikipedia.ipynb @@ -98,7 +98,7 @@ "metadata": {}, "outputs": [], "source": [ - "docs = retriever.get_relevant_documents(query=\"HUNTER X HUNTER\")" + "docs = retriever.invoke(\"HUNTER X HUNTER\")" ] }, { diff --git a/docs/docs/integrations/retrievers/zep_memorystore.ipynb b/docs/docs/integrations/retrievers/zep_memorystore.ipynb index fbf0ef890d..7d296a7b29 100644 --- a/docs/docs/integrations/retrievers/zep_memorystore.ipynb +++ b/docs/docs/integrations/retrievers/zep_memorystore.ipynb @@ -314,7 +314,7 @@ " api_key=zep_api_key,\n", ")\n", "\n", - "await zep_retriever.aget_relevant_documents(\"Who wrote Parable of the Sower?\")" + "await zep_retriever.ainvoke(\"Who wrote Parable of the Sower?\")" ] }, { @@ -355,7 +355,7 @@ } ], "source": [ - "zep_retriever.get_relevant_documents(\"Who wrote Parable of the Sower?\")" + "zep_retriever.invoke(\"Who wrote Parable of the Sower?\")" ] }, { @@ -407,7 +407,7 @@ " mmr_lambda=0.5,\n", ")\n", "\n", - "await zep_retriever.aget_relevant_documents(\"Who wrote Parable of the Sower?\")" + "await zep_retriever.ainvoke(\"Who wrote Parable of the Sower?\")" ] }, { @@ -445,9 +445,7 @@ "source": [ "filter = {\"where\": {\"jsonpath\": '$[*] ? (@.Label == \"WORK_OF_ART\")'}}\n", "\n", - "await zep_retriever.aget_relevant_documents(\n", - " \"Who wrote Parable of the Sower?\", metadata=filter\n", - ")" + "await zep_retriever.ainvoke(\"Who wrote Parable of the Sower?\", metadata=filter)" ] }, { @@ -491,7 +489,7 @@ " mmr_lambda=0.5,\n", ")\n", "\n", - "await zep_retriever.aget_relevant_documents(\"Who wrote Parable of the Sower?\")" + "await zep_retriever.ainvoke(\"Who wrote Parable of the Sower?\")" ] }, { diff --git a/docs/docs/integrations/text_embedding/upstage.ipynb b/docs/docs/integrations/text_embedding/upstage.ipynb index 117c89b1d6..6f2452b978 100644 --- a/docs/docs/integrations/text_embedding/upstage.ipynb +++ b/docs/docs/integrations/text_embedding/upstage.ipynb @@ -187,7 +187,7 @@ " embedding=UpstageEmbeddings(),\n", ")\n", "retriever = vectorstore.as_retriever()\n", - "docs = retriever.get_relevant_documents(\"Where did Harrison work?\")\n", + "docs = retriever.invoke(\"Where did Harrison work?\")\n", "print(docs)" ] } diff --git a/docs/docs/integrations/text_embedding/voyageai.ipynb b/docs/docs/integrations/text_embedding/voyageai.ipynb index 486f762ef0..83cc9f38c1 100644 --- a/docs/docs/integrations/text_embedding/voyageai.ipynb +++ b/docs/docs/integrations/text_embedding/voyageai.ipynb @@ -196,7 +196,7 @@ "retriever = KNNRetriever.from_texts(documents, embeddings)\n", "\n", "# retrieve the most relevant documents\n", - "result = retriever.get_relevant_documents(query)\n", + "result = retriever.invoke(query)\n", "top1_retrieved_doc = result[0].page_content # return the top1 retrieved result\n", "\n", "print(top1_retrieved_doc)" diff --git a/docs/docs/integrations/vectorstores/chroma.ipynb b/docs/docs/integrations/vectorstores/chroma.ipynb index 773db6c9dc..747abbebb8 100644 --- a/docs/docs/integrations/vectorstores/chroma.ipynb +++ b/docs/docs/integrations/vectorstores/chroma.ipynb @@ -510,7 +510,7 @@ } ], "source": [ - "retriever.get_relevant_documents(query)[0]" + "retriever.invoke(query)[0]" ] }, { diff --git a/docs/docs/integrations/vectorstores/dingo.ipynb b/docs/docs/integrations/vectorstores/dingo.ipynb index 0f9ece6f72..44e1c0616a 100644 --- a/docs/docs/integrations/vectorstores/dingo.ipynb +++ b/docs/docs/integrations/vectorstores/dingo.ipynb @@ -197,7 +197,7 @@ "outputs": [], "source": [ "retriever = docsearch.as_retriever(search_type=\"mmr\")\n", - "matched_docs = retriever.get_relevant_documents(query)\n", + "matched_docs = retriever.invoke(query)\n", "for i, d in enumerate(matched_docs):\n", " print(f\"\\n## Document {i}\\n\")\n", " print(d.page_content)" diff --git a/docs/docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb b/docs/docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb index b3972db773..fa04abd4ce 100644 --- a/docs/docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb +++ b/docs/docs/integrations/vectorstores/google_vertex_ai_vector_search.ipynb @@ -487,7 +487,7 @@ "outputs": [], "source": [ "# perform simple similarity search on retriever\n", - "retriever.get_relevant_documents(\"What are my options in breathable fabric?\")" + "retriever.invoke(\"What are my options in breathable fabric?\")" ] }, { @@ -503,7 +503,7 @@ "retriever.search_kwargs = {\"filter\": filters}\n", "\n", "# perform similarity search with filters on retriever\n", - "retriever.get_relevant_documents(\"What are my options in breathable fabric?\")" + "retriever.invoke(\"What are my options in breathable fabric?\")" ] }, { @@ -520,7 +520,7 @@ "\n", "retriever.search_kwargs = {\"filter\": filters, \"numeric_filter\": numeric_filters}\n", "\n", - "retriever.get_relevant_documents(\"What are my options in breathable fabric?\")" + "retriever.invoke(\"What are my options in breathable fabric?\")" ] }, { diff --git a/docs/docs/integrations/vectorstores/milvus.ipynb b/docs/docs/integrations/vectorstores/milvus.ipynb index b246a569ed..33677534a8 100644 --- a/docs/docs/integrations/vectorstores/milvus.ipynb +++ b/docs/docs/integrations/vectorstores/milvus.ipynb @@ -291,9 +291,9 @@ ], "source": [ "# This will only get documents for Ankush\n", - "vectorstore.as_retriever(\n", - " search_kwargs={\"expr\": 'namespace == \"ankush\"'}\n", - ").get_relevant_documents(\"where did i work?\")" + "vectorstore.as_retriever(search_kwargs={\"expr\": 'namespace == \"ankush\"'}).invoke(\n", + " \"where did i work?\"\n", + ")" ] }, { @@ -320,9 +320,9 @@ ], "source": [ "# This will only get documents for Harrison\n", - "vectorstore.as_retriever(\n", - " search_kwargs={\"expr\": 'namespace == \"harrison\"'}\n", - ").get_relevant_documents(\"where did i work?\")" + "vectorstore.as_retriever(search_kwargs={\"expr\": 'namespace == \"harrison\"'}).invoke(\n", + " \"where did i work?\"\n", + ")" ] }, { diff --git a/docs/docs/integrations/vectorstores/neo4jvector.ipynb b/docs/docs/integrations/vectorstores/neo4jvector.ipynb index 91c08ba7fd..4040101b76 100644 --- a/docs/docs/integrations/vectorstores/neo4jvector.ipynb +++ b/docs/docs/integrations/vectorstores/neo4jvector.ipynb @@ -694,7 +694,7 @@ ], "source": [ "retriever = store.as_retriever()\n", - "retriever.get_relevant_documents(query)[0]" + "retriever.invoke(query)[0]" ] }, { diff --git a/docs/docs/integrations/vectorstores/pinecone.ipynb b/docs/docs/integrations/vectorstores/pinecone.ipynb index d8ffceef6c..2877ebd004 100644 --- a/docs/docs/integrations/vectorstores/pinecone.ipynb +++ b/docs/docs/integrations/vectorstores/pinecone.ipynb @@ -256,7 +256,7 @@ ], "source": [ "retriever = docsearch.as_retriever(search_type=\"mmr\")\n", - "matched_docs = retriever.get_relevant_documents(query)\n", + "matched_docs = retriever.invoke(query)\n", "for i, d in enumerate(matched_docs):\n", " print(f\"\\n## Document {i}\\n\")\n", " print(d.page_content)" diff --git a/docs/docs/integrations/vectorstores/qdrant.ipynb b/docs/docs/integrations/vectorstores/qdrant.ipynb index 3abca8952f..1f86779f45 100644 --- a/docs/docs/integrations/vectorstores/qdrant.ipynb +++ b/docs/docs/integrations/vectorstores/qdrant.ipynb @@ -605,7 +605,7 @@ ], "source": [ "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "retriever.get_relevant_documents(query)[0]" + "retriever.invoke(query)[0]" ] }, { diff --git a/docs/docs/integrations/vectorstores/redis.ipynb b/docs/docs/integrations/vectorstores/redis.ipynb index 54bfb2b8fc..4e01352826 100644 --- a/docs/docs/integrations/vectorstores/redis.ipynb +++ b/docs/docs/integrations/vectorstores/redis.ipynb @@ -1078,7 +1078,7 @@ } ], "source": [ - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "docs" ] }, @@ -1120,7 +1120,7 @@ } ], "source": [ - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "docs" ] }, @@ -1162,7 +1162,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"foo\")" + "retriever.invoke(\"foo\")" ] }, { @@ -1196,7 +1196,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"foo\")" + "retriever.invoke(\"foo\")" ] }, { diff --git a/docs/docs/integrations/vectorstores/supabase.ipynb b/docs/docs/integrations/vectorstores/supabase.ipynb index 5db5a33947..34d43f8a8b 100644 --- a/docs/docs/integrations/vectorstores/supabase.ipynb +++ b/docs/docs/integrations/vectorstores/supabase.ipynb @@ -362,7 +362,7 @@ "metadata": {}, "outputs": [], "source": [ - "matched_docs = retriever.get_relevant_documents(query)" + "matched_docs = retriever.invoke(query)" ] }, { diff --git a/docs/docs/integrations/vectorstores/tidb_vector.ipynb b/docs/docs/integrations/vectorstores/tidb_vector.ipynb index c0630b801f..b9337ec1c2 100644 --- a/docs/docs/integrations/vectorstores/tidb_vector.ipynb +++ b/docs/docs/integrations/vectorstores/tidb_vector.ipynb @@ -418,7 +418,7 @@ " search_type=\"similarity_score_threshold\",\n", " search_kwargs={\"k\": 3, \"score_threshold\": 0.8},\n", ")\n", - "docs_retrieved = retriever.get_relevant_documents(query)\n", + "docs_retrieved = retriever.invoke(query)\n", "for doc in docs_retrieved:\n", " print(\"-\" * 80)\n", " print(doc.page_content)\n", @@ -538,7 +538,7 @@ " search_kwargs={\"k\": 3, \"score_threshold\": 0.85},\n", ")\n", "semantic_query = \"Could you recommend a US airport with clean lounges and good vegetarian dining options?\"\n", - "reviews = retriever.get_relevant_documents(semantic_query)\n", + "reviews = retriever.invoke(semantic_query)\n", "for r in reviews:\n", " print(\"-\" * 80)\n", " print(r.page_content)\n", diff --git a/docs/docs/integrations/vectorstores/tiledb.ipynb b/docs/docs/integrations/vectorstores/tiledb.ipynb index 7d74205ce2..2fe5a868a8 100644 --- a/docs/docs/integrations/vectorstores/tiledb.ipynb +++ b/docs/docs/integrations/vectorstores/tiledb.ipynb @@ -132,7 +132,7 @@ "outputs": [], "source": [ "retriever = db.as_retriever(search_type=\"mmr\")\n", - "retriever.get_relevant_documents(query)" + "retriever.invoke(query)" ] }, { diff --git a/docs/docs/integrations/vectorstores/timescalevector.ipynb b/docs/docs/integrations/vectorstores/timescalevector.ipynb index 5058b82645..0ae0b524d4 100644 --- a/docs/docs/integrations/vectorstores/timescalevector.ipynb +++ b/docs/docs/integrations/vectorstores/timescalevector.ipynb @@ -1350,7 +1350,7 @@ ], "source": [ "# This example specifies a relevant query\n", - "retriever.get_relevant_documents(\"What are improvements made to continuous aggregates?\")" + "retriever.invoke(\"What are improvements made to continuous aggregates?\")" ] }, { @@ -1381,7 +1381,7 @@ ], "source": [ "# This example specifies a filter\n", - "retriever.get_relevant_documents(\"What commits did Sven Klemm add?\")" + "retriever.invoke(\"What commits did Sven Klemm add?\")" ] }, { @@ -1412,9 +1412,7 @@ ], "source": [ "# This example specifies a query and filter\n", - "retriever.get_relevant_documents(\n", - " \"What commits about timescaledb_functions did Sven Klemm add?\"\n", - ")" + "retriever.invoke(\"What commits about timescaledb_functions did Sven Klemm add?\")" ] }, { @@ -1445,7 +1443,7 @@ ], "source": [ "# This example specifies a time-based filter\n", - "retriever.get_relevant_documents(\"What commits were added in July 2023?\")" + "retriever.invoke(\"What commits were added in July 2023?\")" ] }, { @@ -1474,9 +1472,7 @@ ], "source": [ "# This example specifies a query and a LIMIT value\n", - "retriever.get_relevant_documents(\n", - " \"What are two commits about hierarchical continuous aggregates?\"\n", - ")" + "retriever.invoke(\"What are two commits about hierarchical continuous aggregates?\")" ] }, { diff --git a/docs/docs/integrations/vectorstores/typesense.ipynb b/docs/docs/integrations/vectorstores/typesense.ipynb index d6a5b7d878..892409bfd3 100644 --- a/docs/docs/integrations/vectorstores/typesense.ipynb +++ b/docs/docs/integrations/vectorstores/typesense.ipynb @@ -216,7 +216,7 @@ "outputs": [], "source": [ "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "retriever.get_relevant_documents(query)[0]" + "retriever.invoke(query)[0]" ] } ], diff --git a/docs/docs/integrations/vectorstores/vald.ipynb b/docs/docs/integrations/vectorstores/vald.ipynb index eba72f91b1..705b97a566 100644 --- a/docs/docs/integrations/vectorstores/vald.ipynb +++ b/docs/docs/integrations/vectorstores/vald.ipynb @@ -129,7 +129,7 @@ "outputs": [], "source": [ "retriever = db.as_retriever(search_type=\"mmr\")\n", - "retriever.get_relevant_documents(query)" + "retriever.invoke(query)" ] }, { @@ -279,7 +279,7 @@ "retriever = db.as_retriever(\n", " search_kwargs={\"search_type\": \"mmr\", \"grpc_metadata\": metadata}\n", ")\n", - "retriever.get_relevant_documents(query, grpc_metadata=metadata)" + "retriever.invoke(query, grpc_metadata=metadata)" ] }, { diff --git a/docs/docs/integrations/vectorstores/vdms.ipynb b/docs/docs/integrations/vectorstores/vdms.ipynb index acfeec141f..6eeefed0b4 100644 --- a/docs/docs/integrations/vectorstores/vdms.ipynb +++ b/docs/docs/integrations/vectorstores/vdms.ipynb @@ -895,7 +895,7 @@ ], "source": [ "retriever = db.as_retriever()\n", - "relevant_docs = retriever.get_relevant_documents(query)[0]\n", + "relevant_docs = retriever.invoke(query)[0]\n", "\n", "print_document_details(relevant_docs)" ] @@ -940,7 +940,7 @@ ], "source": [ "retriever = db.as_retriever(search_type=\"mmr\")\n", - "relevant_docs = retriever.get_relevant_documents(query)[0]\n", + "relevant_docs = retriever.invoke(query)[0]\n", "\n", "print_document_details(relevant_docs)" ] diff --git a/docs/docs/integrations/vectorstores/vectara.ipynb b/docs/docs/integrations/vectorstores/vectara.ipynb index 03c1252097..70756b58d9 100644 --- a/docs/docs/integrations/vectorstores/vectara.ipynb +++ b/docs/docs/integrations/vectorstores/vectara.ipynb @@ -522,7 +522,7 @@ ], "source": [ "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "retriever.get_relevant_documents(query)[0]" + "retriever.invoke(query)[0]" ] }, { diff --git a/docs/docs/integrations/vectorstores/vespa.ipynb b/docs/docs/integrations/vectorstores/vespa.ipynb index 5f0a96863c..50cc60f4e3 100644 --- a/docs/docs/integrations/vectorstores/vespa.ipynb +++ b/docs/docs/integrations/vectorstores/vespa.ipynb @@ -408,7 +408,7 @@ "db = VespaStore.from_documents(docs, embedding_function, app=vespa_app, **vespa_config)\n", "retriever = db.as_retriever()\n", "query = \"What did the president say about Ketanji Brown Jackson\"\n", - "results = retriever.get_relevant_documents(query)\n", + "results = retriever.invoke(query)\n", "\n", "# results[0].metadata[\"id\"] == \"id:testapp:testapp::32\"" ] diff --git a/docs/docs/integrations/vectorstores/weaviate.ipynb b/docs/docs/integrations/vectorstores/weaviate.ipynb index 2020cbbbea..b2d6d72202 100644 --- a/docs/docs/integrations/vectorstores/weaviate.ipynb +++ b/docs/docs/integrations/vectorstores/weaviate.ipynb @@ -536,7 +536,7 @@ ], "source": [ "retriever = db.as_retriever(search_type=\"mmr\")\n", - "retriever.get_relevant_documents(query)[0]" + "retriever.invoke(query)[0]" ] }, { diff --git a/docs/docs/modules/agents/quick_start.ipynb b/docs/docs/modules/agents/quick_start.ipynb index 0d971dc51f..c54337c2a3 100644 --- a/docs/docs/modules/agents/quick_start.ipynb +++ b/docs/docs/modules/agents/quick_start.ipynb @@ -155,7 +155,7 @@ } ], "source": [ - "retriever.get_relevant_documents(\"how to upload a dataset\")[0]" + "retriever.invoke(\"how to upload a dataset\")[0]" ] }, { diff --git a/docs/docs/modules/data_connection/retrievers/MultiQueryRetriever.ipynb b/docs/docs/modules/data_connection/retrievers/MultiQueryRetriever.ipynb index 4f5d543cef..7574d73b30 100644 --- a/docs/docs/modules/data_connection/retrievers/MultiQueryRetriever.ipynb +++ b/docs/docs/modules/data_connection/retrievers/MultiQueryRetriever.ipynb @@ -104,7 +104,7 @@ } ], "source": [ - "unique_docs = retriever_from_llm.get_relevant_documents(query=question)\n", + "unique_docs = retriever_from_llm.invoke(question)\n", "len(unique_docs)" ] }, @@ -199,9 +199,7 @@ ") # \"lines\" is the key (attribute name) of the parsed output\n", "\n", "# Results\n", - "unique_docs = retriever.get_relevant_documents(\n", - " query=\"What does the course say about regression?\"\n", - ")\n", + "unique_docs = retriever.invoke(query=\"What does the course say about regression?\")\n", "len(unique_docs)" ] } diff --git a/docs/docs/modules/data_connection/retrievers/contextual_compression.ipynb b/docs/docs/modules/data_connection/retrievers/contextual_compression.ipynb index 28276f4edb..449e68f07d 100644 --- a/docs/docs/modules/data_connection/retrievers/contextual_compression.ipynb +++ b/docs/docs/modules/data_connection/retrievers/contextual_compression.ipynb @@ -128,9 +128,7 @@ "texts = text_splitter.split_documents(documents)\n", "retriever = FAISS.from_documents(texts, OpenAIEmbeddings()).as_retriever()\n", "\n", - "docs = retriever.get_relevant_documents(\n", - " \"What did the president say about Ketanji Brown Jackson\"\n", - ")\n", + "docs = retriever.invoke(\"What did the president say about Ketanji Brown Jackson\")\n", "pretty_print_docs(docs)" ] }, @@ -184,7 +182,7 @@ " base_compressor=compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "pretty_print_docs(compressed_docs)" @@ -245,7 +243,7 @@ " base_compressor=_filter, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "pretty_print_docs(compressed_docs)" @@ -321,7 +319,7 @@ " base_compressor=embeddings_filter, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "pretty_print_docs(compressed_docs)" @@ -398,7 +396,7 @@ " base_compressor=pipeline_compressor, base_retriever=retriever\n", ")\n", "\n", - "compressed_docs = compression_retriever.get_relevant_documents(\n", + "compressed_docs = compression_retriever.invoke(\n", " \"What did the president say about Ketanji Jackson Brown\"\n", ")\n", "pretty_print_docs(compressed_docs)" diff --git a/docs/docs/modules/data_connection/retrievers/long_context_reorder.ipynb b/docs/docs/modules/data_connection/retrievers/long_context_reorder.ipynb index f1f52d0fa5..4240264cfd 100644 --- a/docs/docs/modules/data_connection/retrievers/long_context_reorder.ipynb +++ b/docs/docs/modules/data_connection/retrievers/long_context_reorder.ipynb @@ -83,7 +83,7 @@ "query = \"What can you tell me about the Celtics?\"\n", "\n", "# Get relevant documents ordered by relevance score\n", - "docs = retriever.get_relevant_documents(query)\n", + "docs = retriever.invoke(query)\n", "docs" ] }, diff --git a/docs/docs/modules/data_connection/retrievers/multi_vector.ipynb b/docs/docs/modules/data_connection/retrievers/multi_vector.ipynb index 9e42a8f1e0..7ba6e6bff8 100644 --- a/docs/docs/modules/data_connection/retrievers/multi_vector.ipynb +++ b/docs/docs/modules/data_connection/retrievers/multi_vector.ipynb @@ -175,7 +175,7 @@ ], "source": [ "# Retriever returns larger chunks\n", - "len(retriever.get_relevant_documents(\"justice breyer\")[0].page_content)" + "len(retriever.invoke(\"justice breyer\")[0].page_content)" ] }, { @@ -208,7 +208,7 @@ "\n", "retriever.search_type = SearchType.mmr\n", "\n", - "len(retriever.get_relevant_documents(\"justice breyer\")[0].page_content)" + "len(retriever.invoke(\"justice breyer\")[0].page_content)" ] }, { @@ -357,7 +357,7 @@ "metadata": {}, "outputs": [], "source": [ - "retrieved_docs = retriever.get_relevant_documents(\"justice breyer\")" + "retrieved_docs = retriever.invoke(\"justice breyer\")" ] }, { @@ -560,7 +560,7 @@ "metadata": {}, "outputs": [], "source": [ - "retrieved_docs = retriever.get_relevant_documents(\"justice breyer\")" + "retrieved_docs = retriever.invoke(\"justice breyer\")" ] }, { diff --git a/docs/docs/modules/data_connection/retrievers/parent_document_retriever.ipynb b/docs/docs/modules/data_connection/retrievers/parent_document_retriever.ipynb index 1653e3f558..e6345c110f 100644 --- a/docs/docs/modules/data_connection/retrievers/parent_document_retriever.ipynb +++ b/docs/docs/modules/data_connection/retrievers/parent_document_retriever.ipynb @@ -190,7 +190,7 @@ "metadata": {}, "outputs": [], "source": [ - "retrieved_docs = retriever.get_relevant_documents(\"justice breyer\")" + "retrieved_docs = retriever.invoke(\"justice breyer\")" ] }, { @@ -343,7 +343,7 @@ "metadata": {}, "outputs": [], "source": [ - "retrieved_docs = retriever.get_relevant_documents(\"justice breyer\")" + "retrieved_docs = retriever.invoke(\"justice breyer\")" ] }, { diff --git a/docs/docs/modules/data_connection/retrievers/time_weighted_vectorstore.ipynb b/docs/docs/modules/data_connection/retrievers/time_weighted_vectorstore.ipynb index 5006792f20..bd0664c5ac 100644 --- a/docs/docs/modules/data_connection/retrievers/time_weighted_vectorstore.ipynb +++ b/docs/docs/modules/data_connection/retrievers/time_weighted_vectorstore.ipynb @@ -107,7 +107,7 @@ ], "source": [ "# \"Hello World\" is returned first because it is most salient, and the decay rate is close to 0., meaning it's still recent enough\n", - "retriever.get_relevant_documents(\"hello world\")" + "retriever.invoke(\"hello world\")" ] }, { @@ -183,7 +183,7 @@ ], "source": [ "# \"Hello Foo\" is returned first because \"hello world\" is mostly forgotten\n", - "retriever.get_relevant_documents(\"hello world\")" + "retriever.invoke(\"hello world\")" ] }, { @@ -225,7 +225,7 @@ "source": [ "# Notice the last access time is that date time\n", "with mock_now(datetime.datetime(2024, 2, 3, 10, 11)):\n", - " print(retriever.get_relevant_documents(\"hello world\"))" + " print(retriever.invoke(\"hello world\"))" ] }, { diff --git a/docs/docs/modules/data_connection/retrievers/vectorstore.ipynb b/docs/docs/modules/data_connection/retrievers/vectorstore.ipynb index 367dd9462a..d41db69552 100644 --- a/docs/docs/modules/data_connection/retrievers/vectorstore.ipynb +++ b/docs/docs/modules/data_connection/retrievers/vectorstore.ipynb @@ -70,7 +70,7 @@ "metadata": {}, "outputs": [], "source": [ - "docs = retriever.get_relevant_documents(\"what did he say about ketanji brown jackson\")" + "docs = retriever.invoke(\"what did he say about ketanji brown jackson\")" ] }, { @@ -100,7 +100,7 @@ "metadata": {}, "outputs": [], "source": [ - "docs = retriever.get_relevant_documents(\"what did he say about ketanji brown jackson\")" + "docs = retriever.invoke(\"what did he say about ketanji brown jackson\")" ] }, { @@ -133,7 +133,7 @@ "metadata": {}, "outputs": [], "source": [ - "docs = retriever.get_relevant_documents(\"what did he say about ketanji brown jackson\")" + "docs = retriever.invoke(\"what did he say about ketanji brown jackson\")" ] }, { @@ -174,7 +174,7 @@ } ], "source": [ - "docs = retriever.get_relevant_documents(\"what did he say about ketanji brown jackson\")\n", + "docs = retriever.invoke(\"what did he say about ketanji brown jackson\")\n", "len(docs)" ] }, diff --git a/docs/docs/use_cases/question_answering/per_user.ipynb b/docs/docs/use_cases/question_answering/per_user.ipynb index cc30729b86..de981e2ae7 100644 --- a/docs/docs/use_cases/question_answering/per_user.ipynb +++ b/docs/docs/use_cases/question_answering/per_user.ipynb @@ -105,7 +105,7 @@ ], "source": [ "# This will only get documents for Ankush\n", - "vectorstore.as_retriever(search_kwargs={\"namespace\": \"ankush\"}).get_relevant_documents(\n", + "vectorstore.as_retriever(search_kwargs={\"namespace\": \"ankush\"}).invoke(\n", " \"where did i work?\"\n", ")" ] @@ -129,9 +129,9 @@ ], "source": [ "# This will only get documents for Harrison\n", - "vectorstore.as_retriever(\n", - " search_kwargs={\"namespace\": \"harrison\"}\n", - ").get_relevant_documents(\"where did i work?\")" + "vectorstore.as_retriever(search_kwargs={\"namespace\": \"harrison\"}).invoke(\n", + " \"where did i work?\"\n", + ")" ] }, { diff --git a/libs/community/langchain_community/retrievers/arcee.py b/libs/community/langchain_community/retrievers/arcee.py index b7e645c934..90c6a996af 100644 --- a/libs/community/langchain_community/retrievers/arcee.py +++ b/libs/community/langchain_community/retrievers/arcee.py @@ -25,7 +25,7 @@ class ArceeRetriever(BaseRetriever): arcee_api_key="ARCEE-API-KEY" ) - documents = retriever.get_relevant_documents("AI-driven music therapy") + documents = retriever.invoke("AI-driven music therapy") """ _client: Optional[ArceeWrapper] = None #: :meta private: diff --git a/libs/community/langchain_community/retrievers/kendra.py b/libs/community/langchain_community/retrievers/kendra.py index b4480cae62..e2d3abc350 100644 --- a/libs/community/langchain_community/retrievers/kendra.py +++ b/libs/community/langchain_community/retrievers/kendra.py @@ -471,7 +471,7 @@ class AmazonKendraRetriever(BaseRetriever): Example: .. code-block:: python - docs = retriever.get_relevant_documents('This is my query') + docs = retriever.invoke('This is my query') """ result_items = self._kendra_query(query) diff --git a/libs/community/langchain_community/retrievers/milvus.py b/libs/community/langchain_community/retrievers/milvus.py index fc81c465c0..6c2ed1ad47 100644 --- a/libs/community/langchain_community/retrievers/milvus.py +++ b/libs/community/langchain_community/retrievers/milvus.py @@ -59,7 +59,7 @@ class MilvusRetriever(BaseRetriever): run_manager: CallbackManagerForRetrieverRun, **kwargs: Any, ) -> List[Document]: - return self.retriever.get_relevant_documents( + return self.retriever.invoke( query, run_manager=run_manager.get_child(), **kwargs ) diff --git a/libs/community/langchain_community/retrievers/thirdai_neuraldb.py b/libs/community/langchain_community/retrievers/thirdai_neuraldb.py index 9b436b3e5a..981833e924 100644 --- a/libs/community/langchain_community/retrievers/thirdai_neuraldb.py +++ b/libs/community/langchain_community/retrievers/thirdai_neuraldb.py @@ -68,7 +68,7 @@ class NeuralDBRetriever(BaseRetriever): "/path/to/doc.csv", ]) - documents = retriever.get_relevant_documents("AI-driven music therapy") + documents = retriever.invoke("AI-driven music therapy") """ NeuralDBRetriever._verify_thirdai_library(thirdai_key) from thirdai import neural_db as ndb @@ -103,7 +103,7 @@ class NeuralDBRetriever(BaseRetriever): "/path/to/doc.csv", ]) - documents = retriever.get_relevant_documents("AI-driven music therapy") + documents = retriever.invoke("AI-driven music therapy") """ NeuralDBRetriever._verify_thirdai_library(thirdai_key) from thirdai import neural_db as ndb diff --git a/libs/community/langchain_community/retrievers/zilliz.py b/libs/community/langchain_community/retrievers/zilliz.py index 43cd2c4e8c..b273ab6e57 100644 --- a/libs/community/langchain_community/retrievers/zilliz.py +++ b/libs/community/langchain_community/retrievers/zilliz.py @@ -61,7 +61,7 @@ class ZillizRetriever(BaseRetriever): run_manager: CallbackManagerForRetrieverRun, **kwargs: Any, ) -> List[Document]: - return self.retriever.get_relevant_documents( + return self.retriever.invoke( query, run_manager=run_manager.get_child(), **kwargs ) diff --git a/libs/community/tests/integration_tests/retrievers/docarray/test_backends.py b/libs/community/tests/integration_tests/retrievers/docarray/test_backends.py index 93489df24c..2e41bfc44f 100644 --- a/libs/community/tests/integration_tests/retrievers/docarray/test_backends.py +++ b/libs/community/tests/integration_tests/retrievers/docarray/test_backends.py @@ -27,7 +27,7 @@ def test_backends(request: Any, backend: Any) -> None: content_field="title", ) - docs = retriever.get_relevant_documents("my docs") + docs = retriever.invoke("my docs") assert len(docs) == 1 assert "My document" in docs[0].page_content @@ -43,7 +43,7 @@ def test_backends(request: Any, backend: Any) -> None: filters=filter_query, ) - docs = retriever.get_relevant_documents("my docs") + docs = retriever.invoke("my docs") assert len(docs) == 1 assert "My document" in docs[0].page_content @@ -61,7 +61,7 @@ def test_backends(request: Any, backend: Any) -> None: filters=filter_query, ) - docs = retriever.get_relevant_documents("my docs") + docs = retriever.invoke("my docs") assert len(docs) == 1 assert "My document" in docs[0].page_content diff --git a/libs/community/tests/integration_tests/retrievers/test_arxiv.py b/libs/community/tests/integration_tests/retrievers/test_arxiv.py index a947f5c151..c2cda25aa0 100644 --- a/libs/community/tests/integration_tests/retrievers/test_arxiv.py +++ b/libs/community/tests/integration_tests/retrievers/test_arxiv.py @@ -25,7 +25,7 @@ def assert_docs(docs: List[Document], all_meta: bool = False) -> None: def test_load_success(retriever: ArxivRetriever) -> None: - docs = retriever.get_relevant_documents(query="1605.08386") + docs = retriever.invoke("1605.08386") assert len(docs) == 1 assert_docs(docs, all_meta=False) @@ -33,18 +33,18 @@ def test_load_success(retriever: ArxivRetriever) -> None: def test_load_success_all_meta(retriever: ArxivRetriever) -> None: retriever.load_all_available_meta = True retriever.load_max_docs = 2 - docs = retriever.get_relevant_documents(query="ChatGPT") + docs = retriever.invoke("ChatGPT") assert len(docs) > 1 assert_docs(docs, all_meta=True) def test_load_success_init_args() -> None: retriever = ArxivRetriever(load_max_docs=1, load_all_available_meta=True) - docs = retriever.get_relevant_documents(query="ChatGPT") + docs = retriever.invoke("ChatGPT") assert len(docs) == 1 assert_docs(docs, all_meta=True) def test_load_no_result(retriever: ArxivRetriever) -> None: - docs = retriever.get_relevant_documents("1605.08386WWW") + docs = retriever.invoke("1605.08386WWW") assert not docs diff --git a/libs/community/tests/integration_tests/retrievers/test_azure_ai_search.py b/libs/community/tests/integration_tests/retrievers/test_azure_ai_search.py index 78e928480e..3d1c708a0b 100644 --- a/libs/community/tests/integration_tests/retrievers/test_azure_ai_search.py +++ b/libs/community/tests/integration_tests/retrievers/test_azure_ai_search.py @@ -7,7 +7,7 @@ from langchain_community.retrievers.azure_ai_search import ( ) -def test_azure_ai_search_get_relevant_documents() -> None: +def test_azure_ai_search_invoke() -> None: """Test valid call to Azure AI Search. In order to run this test, you should provide @@ -17,17 +17,17 @@ def test_azure_ai_search_get_relevant_documents() -> None: """ retriever = AzureAISearchRetriever() - documents = retriever.get_relevant_documents("what is langchain?") + documents = retriever.invoke("what is langchain?") for doc in documents: assert isinstance(doc, Document) assert doc.page_content retriever = AzureAISearchRetriever(top_k=1) - documents = retriever.get_relevant_documents("what is langchain?") + documents = retriever.invoke("what is langchain?") assert len(documents) <= 1 -async def test_azure_ai_search_aget_relevant_documents() -> None: +async def test_azure_ai_search_ainvoke() -> None: """Test valid async call to Azure AI Search. In order to run this test, you should provide @@ -35,36 +35,36 @@ async def test_azure_ai_search_aget_relevant_documents() -> None: as arguments for the AzureAISearchRetriever. """ retriever = AzureAISearchRetriever() - documents = await retriever.aget_relevant_documents("what is langchain?") + documents = await retriever.ainvoke("what is langchain?") for doc in documents: assert isinstance(doc, Document) assert doc.page_content -def test_azure_cognitive_search_get_relevant_documents() -> None: +def test_azure_cognitive_search_invoke() -> None: """Test valid call to Azure Cognitive Search. This is to test backwards compatibility of the retriever """ retriever = AzureCognitiveSearchRetriever() - documents = retriever.get_relevant_documents("what is langchain?") + documents = retriever.invoke("what is langchain?") for doc in documents: assert isinstance(doc, Document) assert doc.page_content retriever = AzureCognitiveSearchRetriever(top_k=1) - documents = retriever.get_relevant_documents("what is langchain?") + documents = retriever.invoke("what is langchain?") assert len(documents) <= 1 -async def test_azure_cognitive_search_aget_relevant_documents() -> None: +async def test_azure_cognitive_search_ainvoke() -> None: """Test valid async call to Azure Cognitive Search. This is to test backwards compatibility of the retriever """ retriever = AzureCognitiveSearchRetriever() - documents = await retriever.aget_relevant_documents("what is langchain?") + documents = await retriever.ainvoke("what is langchain?") for doc in documents: assert isinstance(doc, Document) assert doc.page_content diff --git a/libs/community/tests/integration_tests/retrievers/test_breebs.py b/libs/community/tests/integration_tests/retrievers/test_breebs.py index 1dd6b470a5..43f20a86d9 100644 --- a/libs/community/tests/integration_tests/retrievers/test_breebs.py +++ b/libs/community/tests/integration_tests/retrievers/test_breebs.py @@ -10,7 +10,7 @@ class TestBreebsRetriever: breeb_key = "Parivoyage" query = "What are the best churches to visit in Paris?" breeb_retriever = BreebsRetriever(breeb_key) - documents: List[Document] = breeb_retriever.get_relevant_documents(query) + documents: List[Document] = breeb_retriever.invoke(query) assert isinstance(documents, list), "Documents should be a list" for doc in documents: assert doc.page_content, "Document page_content should not be None" diff --git a/libs/community/tests/integration_tests/retrievers/test_dria_index.py b/libs/community/tests/integration_tests/retrievers/test_dria_index.py index 9dc683deb4..f3e3423bec 100644 --- a/libs/community/tests/integration_tests/retrievers/test_dria_index.py +++ b/libs/community/tests/integration_tests/retrievers/test_dria_index.py @@ -26,8 +26,8 @@ def test_dria_retriever(dria_retriever: DriaRetriever) -> None: ] dria_retriever.add_texts(texts) - # Assuming get_relevant_documents returns a list of Document instances - docs = dria_retriever.get_relevant_documents("Langchain") + # Assuming invoke returns a list of Document instances + docs = dria_retriever.invoke("Langchain") # Perform assertions assert len(docs) > 0, "Expected at least one document" diff --git a/libs/community/tests/integration_tests/retrievers/test_embedchain.py b/libs/community/tests/integration_tests/retrievers/test_embedchain.py index dc58938db1..fae7c5ba8f 100644 --- a/libs/community/tests/integration_tests/retrievers/test_embedchain.py +++ b/libs/community/tests/integration_tests/retrievers/test_embedchain.py @@ -37,7 +37,7 @@ def test_embedchain_retriever(mock_add: Any, mock_search: Any) -> None: ] for text in texts: retriever.add_texts(text) - docs = retriever.get_relevant_documents("doc about john") + docs = retriever.invoke("doc about john") assert len(docs) == 1 for doc in docs: assert isinstance(doc, Document) diff --git a/libs/community/tests/integration_tests/retrievers/test_google_docai_warehoure_retriever.py b/libs/community/tests/integration_tests/retrievers/test_google_docai_warehoure_retriever.py index 9574abb36f..ffe6a1f213 100644 --- a/libs/community/tests/integration_tests/retrievers/test_google_docai_warehoure_retriever.py +++ b/libs/community/tests/integration_tests/retrievers/test_google_docai_warehoure_retriever.py @@ -18,7 +18,7 @@ def test_google_documentai_warehoure_retriever() -> None: docai_wh_retriever = GoogleDocumentAIWarehouseRetriever( project_number=project_number ) - documents = docai_wh_retriever.get_relevant_documents( + documents = docai_wh_retriever.invoke( "What are Alphabet's Other Bets?", user_ldap=user_ldap ) assert len(documents) > 0 diff --git a/libs/community/tests/integration_tests/retrievers/test_google_vertex_ai_search.py b/libs/community/tests/integration_tests/retrievers/test_google_vertex_ai_search.py index f430f0378d..24d8738520 100644 --- a/libs/community/tests/integration_tests/retrievers/test_google_vertex_ai_search.py +++ b/libs/community/tests/integration_tests/retrievers/test_google_vertex_ai_search.py @@ -24,10 +24,10 @@ from langchain_community.retrievers.google_vertex_ai_search import ( @pytest.mark.requires("google.api_core") -def test_google_vertex_ai_search_get_relevant_documents() -> None: - """Test the get_relevant_documents() method.""" +def test_google_vertex_ai_search_invoke() -> None: + """Test the invoke() method.""" retriever = GoogleVertexAISearchRetriever() - documents = retriever.get_relevant_documents("What are Alphabet's Other Bets?") + documents = retriever.invoke("What are Alphabet's Other Bets?") assert len(documents) > 0 for doc in documents: assert isinstance(doc, Document) @@ -37,10 +37,10 @@ def test_google_vertex_ai_search_get_relevant_documents() -> None: @pytest.mark.requires("google.api_core") -def test_google_vertex_ai_multiturnsearch_get_relevant_documents() -> None: - """Test the get_relevant_documents() method.""" +def test_google_vertex_ai_multiturnsearch_invoke() -> None: + """Test the invoke() method.""" retriever = GoogleVertexAIMultiTurnSearchRetriever() - documents = retriever.get_relevant_documents("What are Alphabet's Other Bets?") + documents = retriever.invoke("What are Alphabet's Other Bets?") assert len(documents) > 0 for doc in documents: assert isinstance(doc, Document) @@ -66,7 +66,7 @@ def test_google_vertex_ai_search_enterprise_search_deprecation() -> None: retriever = GoogleCloudEnterpriseSearchRetriever() # Check that mapped methods still work. - documents = retriever.get_relevant_documents("What are Alphabet's Other Bets?") + documents = retriever.invoke("What are Alphabet's Other Bets?") assert len(documents) > 0 for doc in documents: assert isinstance(doc, Document) diff --git a/libs/community/tests/integration_tests/retrievers/test_kay.py b/libs/community/tests/integration_tests/retrievers/test_kay.py index 2c05fcf5f8..e96090168f 100644 --- a/libs/community/tests/integration_tests/retrievers/test_kay.py +++ b/libs/community/tests/integration_tests/retrievers/test_kay.py @@ -12,7 +12,7 @@ def test_kay_retriever() -> None: data_types=["10-K", "10-Q", "8-K", "PressRelease"], num_contexts=3, ) - docs = retriever.get_relevant_documents( + docs = retriever.invoke( "What were the biggest strategy changes and partnerships made by Roku " "in 2023?", ) diff --git a/libs/community/tests/integration_tests/retrievers/test_pubmed.py b/libs/community/tests/integration_tests/retrievers/test_pubmed.py index 387bf6548d..a13bba31e5 100644 --- a/libs/community/tests/integration_tests/retrievers/test_pubmed.py +++ b/libs/community/tests/integration_tests/retrievers/test_pubmed.py @@ -24,18 +24,18 @@ def assert_docs(docs: List[Document]) -> None: def test_load_success(retriever: PubMedRetriever) -> None: - docs = retriever.get_relevant_documents(query="chatgpt") + docs = retriever.invoke("chatgpt") assert len(docs) == 3 assert_docs(docs) def test_load_success_top_k_results(retriever: PubMedRetriever) -> None: retriever.top_k_results = 2 - docs = retriever.get_relevant_documents(query="chatgpt") + docs = retriever.invoke("chatgpt") assert len(docs) == 2 assert_docs(docs) def test_load_no_result(retriever: PubMedRetriever) -> None: - docs = retriever.get_relevant_documents("1605.08386WWW") + docs = retriever.invoke("1605.08386WWW") assert not docs diff --git a/libs/community/tests/integration_tests/retrievers/test_qdrant_sparse_vector_retriever.py b/libs/community/tests/integration_tests/retrievers/test_qdrant_sparse_vector_retriever.py index bba6a17041..7afb7a7715 100644 --- a/libs/community/tests/integration_tests/retrievers/test_qdrant_sparse_vector_retriever.py +++ b/libs/community/tests/integration_tests/retrievers/test_qdrant_sparse_vector_retriever.py @@ -131,20 +131,20 @@ def test_add_texts(retriever: QdrantSparseVectorRetriever) -> None: assert retriever.client.count(retriever.collection_name, exact=True).count == 6 -def test_get_relevant_documents(retriever: QdrantSparseVectorRetriever) -> None: +def test_invoke(retriever: QdrantSparseVectorRetriever) -> None: retriever.add_texts(["Hai there!", "Hello world!", "Foo bar baz!"]) expected = [Document(page_content="Hai there!")] retriever.k = 1 - results = retriever.get_relevant_documents("Hai there!") + results = retriever.invoke("Hai there!") assert len(results) == retriever.k assert results == expected - assert retriever.get_relevant_documents("Hai there!") == expected + assert retriever.invoke("Hai there!") == expected -def test_get_relevant_documents_with_filter( +def test_invoke_with_filter( retriever: QdrantSparseVectorRetriever, ) -> None: from qdrant_client import models @@ -165,6 +165,6 @@ def test_get_relevant_documents_with_filter( ) ] ) - results = retriever.get_relevant_documents("Some query") + results = retriever.invoke("Some query") assert results[0] == Document(page_content="Hello world!", metadata={"value": 2}) diff --git a/libs/community/tests/integration_tests/retrievers/test_thirdai_neuraldb.py b/libs/community/tests/integration_tests/retrievers/test_thirdai_neuraldb.py index b8d384f9af..1ae1f92175 100644 --- a/libs/community/tests/integration_tests/retrievers/test_thirdai_neuraldb.py +++ b/libs/community/tests/integration_tests/retrievers/test_thirdai_neuraldb.py @@ -26,7 +26,7 @@ def assert_result_correctness(documents: list) -> None: def test_neuraldb_retriever_from_scratch(test_csv: str) -> None: retriever = NeuralDBRetriever.from_scratch() retriever.insert([test_csv]) - documents = retriever.get_relevant_documents("column") + documents = retriever.invoke("column") assert_result_correctness(documents) @@ -40,7 +40,7 @@ def test_neuraldb_retriever_from_checkpoint(test_csv: str) -> None: retriever.insert([test_csv]) retriever.save(checkpoint) loaded_retriever = NeuralDBRetriever.from_checkpoint(checkpoint) - documents = loaded_retriever.get_relevant_documents("column") + documents = loaded_retriever.invoke("column") assert_result_correctness(documents) finally: if os.path.exists(checkpoint): diff --git a/libs/community/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py b/libs/community/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py index 1844c8d649..2e80347f80 100644 --- a/libs/community/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py +++ b/libs/community/tests/integration_tests/retrievers/test_weaviate_hybrid_search.py @@ -39,7 +39,7 @@ class TestWeaviateHybridSearchRetriever: client.schema.delete_all() @pytest.mark.vcr(ignore_localhost=True) - def test_get_relevant_documents(self, weaviate_url: str) -> None: + def test_invoke(self, weaviate_url: str) -> None: """Test end to end construction and MRR search.""" from weaviate import Client @@ -59,7 +59,7 @@ class TestWeaviateHybridSearchRetriever: [Document(page_content=text, metadata=metadatas[i])] ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [ Document(page_content="foo", metadata={"page": 0}), Document(page_content="baz", metadata={"page": 2}), @@ -67,7 +67,7 @@ class TestWeaviateHybridSearchRetriever: ] @pytest.mark.vcr(ignore_localhost=True) - def test_get_relevant_documents_with_score(self, weaviate_url: str) -> None: + def test_invoke_with_score(self, weaviate_url: str) -> None: """Test end to end construction and MRR search.""" from weaviate import Client @@ -87,12 +87,12 @@ class TestWeaviateHybridSearchRetriever: [Document(page_content=text, metadata=metadatas[i])] ) - output = retriever.get_relevant_documents("foo", score=True) + output = retriever.invoke("foo", score=True) for doc in output: assert "_additional" in doc.metadata @pytest.mark.vcr(ignore_localhost=True) - def test_get_relevant_documents_with_filter(self, weaviate_url: str) -> None: + def test_invoke_with_filter(self, weaviate_url: str) -> None: """Test end to end construction and MRR search.""" from weaviate import Client @@ -114,13 +114,13 @@ class TestWeaviateHybridSearchRetriever: where_filter = {"path": ["page"], "operator": "Equal", "valueNumber": 0} - output = retriever.get_relevant_documents("foo", where_filter=where_filter) + output = retriever.invoke("foo", where_filter=where_filter) assert output == [ Document(page_content="foo", metadata={"page": 0}), ] @pytest.mark.vcr(ignore_localhost=True) - def test_get_relevant_documents_with_uuids(self, weaviate_url: str) -> None: + def test_invoke_with_uuids(self, weaviate_url: str) -> None: """Test end to end construction and MRR search.""" from weaviate import Client @@ -142,5 +142,5 @@ class TestWeaviateHybridSearchRetriever: [Document(page_content=text, metadata=metadatas[i])], uuids=[uuids[i]] ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert len(output) == 1 diff --git a/libs/community/tests/integration_tests/retrievers/test_wikipedia.py b/libs/community/tests/integration_tests/retrievers/test_wikipedia.py index bddce4a8de..2388ad4fe5 100644 --- a/libs/community/tests/integration_tests/retrievers/test_wikipedia.py +++ b/libs/community/tests/integration_tests/retrievers/test_wikipedia.py @@ -25,7 +25,7 @@ def assert_docs(docs: List[Document], all_meta: bool = False) -> None: def test_load_success(retriever: WikipediaRetriever) -> None: - docs = retriever.get_relevant_documents("HUNTER X HUNTER") + docs = retriever.invoke("HUNTER X HUNTER") assert len(docs) > 1 assert len(docs) <= 3 assert_docs(docs, all_meta=False) @@ -33,7 +33,7 @@ def test_load_success(retriever: WikipediaRetriever) -> None: def test_load_success_all_meta(retriever: WikipediaRetriever) -> None: retriever.load_all_available_meta = True - docs = retriever.get_relevant_documents("HUNTER X HUNTER") + docs = retriever.invoke("HUNTER X HUNTER") assert len(docs) > 1 assert len(docs) <= 3 assert_docs(docs, all_meta=True) @@ -43,7 +43,7 @@ def test_load_success_init_args() -> None: retriever = WikipediaRetriever( lang="en", top_k_results=1, load_all_available_meta=True ) - docs = retriever.get_relevant_documents("HUNTER X HUNTER") + docs = retriever.invoke("HUNTER X HUNTER") assert len(docs) == 1 assert_docs(docs, all_meta=True) @@ -52,13 +52,13 @@ def test_load_success_init_args_more() -> None: retriever = WikipediaRetriever( lang="en", top_k_results=20, load_all_available_meta=False ) - docs = retriever.get_relevant_documents("HUNTER X HUNTER") + docs = retriever.invoke("HUNTER X HUNTER") assert len(docs) == 20 assert_docs(docs, all_meta=False) def test_load_no_result(retriever: WikipediaRetriever) -> None: - docs = retriever.get_relevant_documents( + docs = retriever.invoke( "NORESULTCALL_NORESULTCALL_NORESULTCALL_NORESULTCALL_NORESULTCALL_NORESULTCALL" ) assert not docs diff --git a/libs/community/tests/integration_tests/retrievers/test_you.py b/libs/community/tests/integration_tests/retrievers/test_you.py index e40ee7d33e..557f32b6e4 100644 --- a/libs/community/tests/integration_tests/retrievers/test_you.py +++ b/libs/community/tests/integration_tests/retrievers/test_you.py @@ -9,8 +9,8 @@ class TestYouRetriever: if not os.getenv("YDC_API_KEY"): raise ValueError("YDC_API_KEY environment variable is not set") - def test_get_relevant_documents(self) -> None: + def test_invoke(self) -> None: retriever = YouRetriever() - actual = retriever.get_relevant_documents("test") + actual = retriever.invoke("test") assert len(actual) > 0 diff --git a/libs/community/tests/integration_tests/retrievers/test_zep.py b/libs/community/tests/integration_tests/retrievers/test_zep.py index 28407add28..195cfd31d2 100644 --- a/libs/community/tests/integration_tests/retrievers/test_zep.py +++ b/libs/community/tests/integration_tests/retrievers/test_zep.py @@ -73,22 +73,18 @@ def zep_retriever( @pytest.mark.requires("zep_python") -def test_zep_retriever_get_relevant_documents( +def test_zep_retriever_invoke( zep_retriever: ZepRetriever, search_results: List[MemorySearchResult] ) -> None: - documents: List[Document] = zep_retriever.get_relevant_documents( - query="My trip to Iceland" - ) + documents: List[Document] = zep_retriever.invoke("My trip to Iceland") _test_documents(documents, search_results) @pytest.mark.requires("zep_python") -async def test_zep_retriever_aget_relevant_documents( +async def test_zep_retriever_ainvoke( zep_retriever: ZepRetriever, search_results: List[MemorySearchResult] ) -> None: - documents: List[Document] = await zep_retriever.aget_relevant_documents( - query="My trip to Iceland" - ) + documents: List[Document] = await zep_retriever.ainvoke("My trip to Iceland") _test_documents(documents, search_results) diff --git a/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py b/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py index 8069952ed6..f9b1f04d8d 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py +++ b/libs/community/tests/integration_tests/vectorstores/test_elasticsearch.py @@ -808,7 +808,7 @@ class TestElasticsearch: search_type="similarity_score_threshold", search_kwargs={"score_threshold": similarity_of_second_ranked}, ) - output = retriever.get_relevant_documents(query=query_string) + output = retriever.invoke(query_string) assert output == [ top3[0][0], diff --git a/libs/community/tests/integration_tests/vectorstores/test_kinetica.py b/libs/community/tests/integration_tests/vectorstores/test_kinetica.py index c60e99fdc2..bde61c47f8 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_kinetica.py +++ b/libs/community/tests/integration_tests/vectorstores/test_kinetica.py @@ -268,7 +268,7 @@ def test_kinetica_retriever_search_threshold(create_config: KineticaSettings) -> search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.999}, ) - output = retriever.get_relevant_documents("summer") + output = retriever.invoke("summer") assert output == [ Document(page_content="foo", metadata={"page": "0"}), ] @@ -296,5 +296,5 @@ def test_kinetica_retriever_search_threshold_custom_normalization_fn( search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.5}, ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [] diff --git a/libs/community/tests/integration_tests/vectorstores/test_lantern.py b/libs/community/tests/integration_tests/vectorstores/test_lantern.py index f50d90e508..28bc742c11 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_lantern.py +++ b/libs/community/tests/integration_tests/vectorstores/test_lantern.py @@ -258,7 +258,7 @@ def test_lantern_retriever_search_threshold() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.999}, ) - output = retriever.get_relevant_documents("summer") + output = retriever.invoke("summer") assert output == [ Document(page_content="foo", metadata={"page": "0"}), Document(page_content="bar", metadata={"page": "1"}), @@ -283,7 +283,7 @@ def test_lantern_retriever_search_threshold_custom_normalization_fn() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.9999}, ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [ Document(page_content="foo", metadata={"page": "0"}), ] diff --git a/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py b/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py index a1261de81c..87db073770 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py +++ b/libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py @@ -241,7 +241,7 @@ def test_neo4jvector_retriever_search_threshold() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.9999}, ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [ Document(page_content="foo", metadata={"page": "0"}), ] diff --git a/libs/community/tests/integration_tests/vectorstores/test_pgvector.py b/libs/community/tests/integration_tests/vectorstores/test_pgvector.py index d4bcfb64f8..48cf770a22 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_pgvector.py +++ b/libs/community/tests/integration_tests/vectorstores/test_pgvector.py @@ -332,7 +332,7 @@ def test_pgvector_retriever_search_threshold() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.999}, ) - output = retriever.get_relevant_documents("summer") + output = retriever.invoke("summer") assert output == [ Document(page_content="foo", metadata={"page": "0"}), Document(page_content="bar", metadata={"page": "1"}), @@ -357,7 +357,7 @@ def test_pgvector_retriever_search_threshold_custom_normalization_fn() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.5}, ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [] diff --git a/libs/community/tests/integration_tests/vectorstores/test_redis.py b/libs/community/tests/integration_tests/vectorstores/test_redis.py index 00762dcc00..ff2961cc73 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_redis.py +++ b/libs/community/tests/integration_tests/vectorstores/test_redis.py @@ -399,7 +399,7 @@ def test_redis_as_retriever() -> None: ) retriever = docsearch.as_retriever(search_type="similarity", search_kwargs={"k": 3}) - results = retriever.get_relevant_documents("foo") + results = retriever.invoke("foo") assert len(results) == 3 assert all([d.page_content == "foo" for d in results]) @@ -414,7 +414,7 @@ def test_redis_retriever_distance_threshold() -> None: search_type="similarity_distance_threshold", search_kwargs={"k": 3, "distance_threshold": 0.1}, ) - results = retriever.get_relevant_documents("foo") + results = retriever.invoke("foo") assert len(results) == 2 assert drop(docsearch.index_name) @@ -428,7 +428,7 @@ def test_redis_retriever_score_threshold() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.91}, ) - results = retriever.get_relevant_documents("foo") + results = retriever.invoke("foo") assert len(results) == 2 assert drop(docsearch.index_name) diff --git a/libs/community/tests/integration_tests/vectorstores/test_singlestoredb.py b/libs/community/tests/integration_tests/vectorstores/test_singlestoredb.py index da161ce7a1..57d79e56b6 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_singlestoredb.py +++ b/libs/community/tests/integration_tests/vectorstores/test_singlestoredb.py @@ -447,7 +447,7 @@ def test_singlestoredb_as_retriever(texts: List[str]) -> None: host=TEST_SINGLESTOREDB_URL, ) retriever = docsearch.as_retriever(search_kwargs={"k": 2}) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [ Document( page_content="foo", diff --git a/libs/community/tests/integration_tests/vectorstores/test_tidb_vector.py b/libs/community/tests/integration_tests/vectorstores/test_tidb_vector.py index d31a58bd1d..f627af2f44 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_tidb_vector.py +++ b/libs/community/tests/integration_tests/vectorstores/test_tidb_vector.py @@ -340,7 +340,7 @@ def test_retriever_search_threshold() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.997}, ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [ Document(page_content="foo", metadata={"page": "0"}), Document(page_content="bar", metadata={"page": "1"}), diff --git a/libs/community/tests/integration_tests/vectorstores/test_timescalevector.py b/libs/community/tests/integration_tests/vectorstores/test_timescalevector.py index 0867832dec..d6d0c06715 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_timescalevector.py +++ b/libs/community/tests/integration_tests/vectorstores/test_timescalevector.py @@ -288,7 +288,7 @@ def test_timescalevector_retriever_search_threshold() -> None: search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.999}, ) - output = retriever.get_relevant_documents("summer") + output = retriever.invoke("summer") assert output == [ Document(page_content="foo", metadata={"page": "0"}), Document(page_content="bar", metadata={"page": "1"}), @@ -313,7 +313,7 @@ def test_timescalevector_retriever_search_threshold_custom_normalization_fn() -> search_type="similarity_score_threshold", search_kwargs={"k": 3, "score_threshold": 0.5}, ) - output = retriever.get_relevant_documents("foo") + output = retriever.invoke("foo") assert output == [] diff --git a/libs/community/tests/unit_tests/retrievers/test_base.py b/libs/community/tests/unit_tests/retrievers/test_base.py index 320db0c874..92d666dbed 100644 --- a/libs/community/tests/unit_tests/retrievers/test_base.py +++ b/libs/community/tests/unit_tests/retrievers/test_base.py @@ -50,8 +50,8 @@ def test_fake_retriever_v1_upgrade(fake_retriever_v1: BaseRetriever) -> None: callbacks = FakeCallbackHandler() assert fake_retriever_v1._new_arg_supported is False assert fake_retriever_v1._expects_other_args is False - results: List[Document] = fake_retriever_v1.get_relevant_documents( - "Foo", callbacks=[callbacks] + results: List[Document] = fake_retriever_v1.invoke( + "Foo", config={"callbacks": [callbacks]} ) assert results[0].page_content == "Foo" assert callbacks.retriever_starts == 1 @@ -65,8 +65,8 @@ async def test_fake_retriever_v1_upgrade_async( callbacks = FakeCallbackHandler() assert fake_retriever_v1._new_arg_supported is False assert fake_retriever_v1._expects_other_args is False - results: List[Document] = await fake_retriever_v1.aget_relevant_documents( - "Foo", callbacks=[callbacks] + results: List[Document] = await fake_retriever_v1.ainvoke( + "Foo", config={"callbacks": [callbacks]} ) assert results[0].page_content == "Async query Foo" assert callbacks.retriever_starts == 1 @@ -111,8 +111,8 @@ def test_fake_retriever_v1_with_kwargs_upgrade( callbacks = FakeCallbackHandler() assert fake_retriever_v1_with_kwargs._new_arg_supported is False assert fake_retriever_v1_with_kwargs._expects_other_args is True - results: List[Document] = fake_retriever_v1_with_kwargs.get_relevant_documents( - "Foo", callbacks=[callbacks], where_filter={"foo": "bar"} + results: List[Document] = fake_retriever_v1_with_kwargs.invoke( + "Foo", config={"callbacks": [callbacks]}, where_filter={"foo": "bar"} ) assert results[0].page_content == "Foo" assert results[0].metadata == {"foo": "bar"} @@ -127,10 +127,8 @@ async def test_fake_retriever_v1_with_kwargs_upgrade_async( callbacks = FakeCallbackHandler() assert fake_retriever_v1_with_kwargs._new_arg_supported is False assert fake_retriever_v1_with_kwargs._expects_other_args is True - results: List[ - Document - ] = await fake_retriever_v1_with_kwargs.aget_relevant_documents( - "Foo", callbacks=[callbacks], where_filter={"foo": "bar"} + results: List[Document] = await fake_retriever_v1_with_kwargs.ainvoke( + "Foo", config={"callbacks": [callbacks]}, where_filter={"foo": "bar"} ) assert results[0].page_content == "Async query Foo" assert results[0].metadata == {"foo": "bar"} @@ -188,15 +186,15 @@ def test_fake_retriever_v2( ) -> None: callbacks = FakeCallbackHandler() assert fake_retriever_v2._new_arg_supported is True - results = fake_retriever_v2.get_relevant_documents("Foo", callbacks=[callbacks]) + results = fake_retriever_v2.invoke("Foo", config={"callbacks": [callbacks]}) assert results[0].page_content == "Foo" assert callbacks.retriever_starts == 1 assert callbacks.retriever_ends == 1 assert callbacks.retriever_errors == 0 - fake_retriever_v2.get_relevant_documents("Foo", callbacks=[callbacks]) + fake_retriever_v2.invoke("Foo", config={"callbacks": [callbacks]}) with pytest.raises(ValueError, match="Test error"): - fake_erroring_retriever_v2.get_relevant_documents("Foo", callbacks=[callbacks]) + fake_erroring_retriever_v2.invoke("Foo", config={"callbacks": [callbacks]}) assert callbacks.retriever_errors == 1 @@ -205,15 +203,13 @@ async def test_fake_retriever_v2_async( ) -> None: callbacks = FakeCallbackHandler() assert fake_retriever_v2._new_arg_supported is True - results = await fake_retriever_v2.aget_relevant_documents( - "Foo", callbacks=[callbacks] - ) + results = await fake_retriever_v2.ainvoke("Foo", config={"callbacks": [callbacks]}) assert results[0].page_content == "Async query Foo" assert callbacks.retriever_starts == 1 assert callbacks.retriever_ends == 1 assert callbacks.retriever_errors == 0 - await fake_retriever_v2.aget_relevant_documents("Foo", callbacks=[callbacks]) + await fake_retriever_v2.ainvoke("Foo", config={"callbacks": [callbacks]}) with pytest.raises(ValueError, match="Test error"): - await fake_erroring_retriever_v2.aget_relevant_documents( - "Foo", callbacks=[callbacks] + await fake_erroring_retriever_v2.ainvoke( + "Foo", config={"callbacks": [callbacks]} ) diff --git a/libs/community/tests/unit_tests/retrievers/test_remote_retriever.py b/libs/community/tests/unit_tests/retrievers/test_remote_retriever.py index b6f90b8a65..157fd67bc1 100644 --- a/libs/community/tests/unit_tests/retrievers/test_remote_retriever.py +++ b/libs/community/tests/unit_tests/retrievers/test_remote_retriever.py @@ -37,7 +37,7 @@ def mocked_requests_post(*args: Any, **kwargs: Any) -> MockResponse: ) -def test_RemoteLangChainRetriever_get_relevant_documents( +def test_RemoteLangChainRetriever_invoke( mocker: MockerFixture, ) -> None: mocker.patch("requests.post", side_effect=mocked_requests_post) @@ -45,7 +45,7 @@ def test_RemoteLangChainRetriever_get_relevant_documents( remote_langchain_retriever = RemoteLangChainRetriever( url="http://localhost:8000", ) - response = remote_langchain_retriever.get_relevant_documents("I like apples") + response = remote_langchain_retriever.invoke("I like apples") want = [ Document(page_content="I like apples", metadata={"test": 0}), Document(page_content="I like pineapples", metadata={"test": 1}), @@ -57,4 +57,4 @@ def test_RemoteLangChainRetriever_get_relevant_documents( assert r.metadata == w.metadata -# TODO: _aget_relevant_documents test +# TODO: _ainvoke test diff --git a/libs/community/tests/unit_tests/retrievers/test_svm.py b/libs/community/tests/unit_tests/retrievers/test_svm.py index 0bc85a5449..80b49bdaf7 100644 --- a/libs/community/tests/unit_tests/retrievers/test_svm.py +++ b/libs/community/tests/unit_tests/retrievers/test_svm.py @@ -37,6 +37,6 @@ class TestSVMRetriever: documents=input_docs, embeddings=FakeEmbeddings(size=100) ) query = "Have anything?" - output_docs = svm_retriever.get_relevant_documents(query=query) + output_docs = svm_retriever.invoke(query) for doc in output_docs: assert "foo" in doc.metadata diff --git a/libs/community/tests/unit_tests/retrievers/test_you.py b/libs/community/tests/unit_tests/retrievers/test_you.py index 2ac44c9bf1..2118fb0c90 100644 --- a/libs/community/tests/unit_tests/retrievers/test_you.py +++ b/libs/community/tests/unit_tests/retrievers/test_you.py @@ -16,17 +16,6 @@ from ..utilities.test_you import ( class TestYouRetriever: - @responses.activate - def test_get_relevant_documents(self) -> None: - responses.add( - responses.GET, f"{TEST_ENDPOINT}/search", json=MOCK_RESPONSE_RAW, status=200 - ) - query = "Test query text" - you_wrapper = YouRetriever(ydc_api_key="test") - results = you_wrapper.get_relevant_documents(query) - expected_result = MOCK_PARSED_OUTPUT - assert results == expected_result - @responses.activate def test_invoke(self) -> None: responses.add( @@ -74,24 +63,6 @@ class TestYouRetriever: expected_result = NEWS_RESPONSE_PARSED assert results == expected_result - @pytest.mark.asyncio - async def test_aget_relevant_documents(self) -> None: - instance = YouRetriever(ydc_api_key="test_api_key") - - # Mock response object to simulate aiohttp response - mock_response = AsyncMock() - mock_response.__aenter__.return_value = ( - mock_response # Make the context manager return itself - ) - mock_response.__aexit__.return_value = None # No value needed for exit - mock_response.status = 200 - mock_response.json = AsyncMock(return_value=MOCK_RESPONSE_RAW) - - # Patch the aiohttp.ClientSession object - with patch("aiohttp.ClientSession.get", return_value=mock_response): - results = await instance.aget_relevant_documents("test query") - assert results == MOCK_PARSED_OUTPUT - @pytest.mark.asyncio async def test_ainvoke(self) -> None: instance = YouRetriever(ydc_api_key="test_api_key") diff --git a/libs/community/tests/unit_tests/vectorstores/test_databricks_vector_search.py b/libs/community/tests/unit_tests/vectorstores/test_databricks_vector_search.py index d914d4ab0f..e2528cb04f 100644 --- a/libs/community/tests/unit_tests/vectorstores/test_databricks_vector_search.py +++ b/libs/community/tests/unit_tests/vectorstores/test_databricks_vector_search.py @@ -567,7 +567,7 @@ def test_mmr_parameters(index_details: dict) -> None: "filters": filters, }, ) - search_result = retriever.get_relevant_documents(query) + search_result = retriever.invoke(query) mock_mmr.assert_called_once() assert mock_mmr.call_args[1]["lambda_mult"] == lambda_mult @@ -593,7 +593,7 @@ def test_similarity_score_threshold(index_details: dict, threshold: float) -> No search_type="similarity_score_threshold", search_kwargs={"k": limit, "score_threshold": threshold}, ) - search_result = retriever.get_relevant_documents(query) + search_result = retriever.invoke(query) if uniform_response_score >= threshold: assert len(search_result) == len(fake_texts) else: diff --git a/libs/core/langchain_core/retrievers.py b/libs/core/langchain_core/retrievers.py index cf158da4ce..897efbef86 100644 --- a/libs/core/langchain_core/retrievers.py +++ b/libs/core/langchain_core/retrievers.py @@ -25,6 +25,7 @@ from abc import ABC, abstractmethod from inspect import signature from typing import TYPE_CHECKING, Any, Dict, List, Optional +from langchain_core._api import deprecated from langchain_core.documents import Document from langchain_core.load.dump import dumpd from langchain_core.runnables import ( @@ -262,6 +263,7 @@ class BaseRetriever(RunnableSerializable[RetrieverInput, RetrieverOutput], ABC): run_manager=run_manager.get_sync(), ) + @deprecated(since="0.1.46", alternative="invoke", removal="0.3.0") def get_relevant_documents( self, query: str, @@ -325,6 +327,7 @@ class BaseRetriever(RunnableSerializable[RetrieverInput, RetrieverOutput], ABC): ) return result + @deprecated(since="0.1.46", alternative="ainvoke", removal="0.3.0") async def aget_relevant_documents( self, query: str, diff --git a/libs/core/langchain_core/tools.py b/libs/core/langchain_core/tools.py index 8f10ce770f..d7abd121cb 100644 --- a/libs/core/langchain_core/tools.py +++ b/libs/core/langchain_core/tools.py @@ -945,7 +945,7 @@ def _get_relevant_documents( document_separator: str, callbacks: Callbacks = None, ) -> str: - docs = retriever.get_relevant_documents(query, callbacks=callbacks) + docs = retriever.invoke(query, config={"callbacks": callbacks}) return document_separator.join( format_document(doc, document_prompt) for doc in docs ) @@ -958,7 +958,7 @@ async def _aget_relevant_documents( document_separator: str, callbacks: Callbacks = None, ) -> str: - docs = await retriever.aget_relevant_documents(query, callbacks=callbacks) + docs = await retriever.ainvoke(query, config={"callbacks": callbacks}) return document_separator.join( [await aformat_document(doc, document_prompt) for doc in docs] ) diff --git a/libs/experimental/langchain_experimental/autonomous_agents/autogpt/memory.py b/libs/experimental/langchain_experimental/autonomous_agents/autogpt/memory.py index f4d7d39d73..be2b08f154 100644 --- a/libs/experimental/langchain_experimental/autonomous_agents/autogpt/memory.py +++ b/libs/experimental/langchain_experimental/autonomous_agents/autogpt/memory.py @@ -26,7 +26,7 @@ class AutoGPTMemory(BaseChatMemory): def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, Any]: input_key = self._get_prompt_input_key(inputs) query = inputs[input_key] - docs = self.retriever.get_relevant_documents(query) + docs = self.retriever.invoke(query) return { "chat_history": self.chat_memory.messages[-10:], "relevant_context": docs, diff --git a/libs/experimental/langchain_experimental/autonomous_agents/autogpt/prompt.py b/libs/experimental/langchain_experimental/autonomous_agents/autogpt/prompt.py index 356776337f..88a61e1179 100644 --- a/libs/experimental/langchain_experimental/autonomous_agents/autogpt/prompt.py +++ b/libs/experimental/langchain_experimental/autonomous_agents/autogpt/prompt.py @@ -73,7 +73,7 @@ class AutoGPTPrompt(BaseChatPromptTemplate, BaseModel): # type: ignore[misc] ) + self.token_counter(cast(str, time_prompt.content)) memory: VectorStoreRetriever = kwargs["memory"] previous_messages = kwargs["messages"] - relevant_docs = memory.get_relevant_documents(str(previous_messages[-10:])) + relevant_docs = memory.invoke(str(previous_messages[-10:])) relevant_memory = [d.page_content for d in relevant_docs] relevant_memory_tokens = sum( [self.token_counter(doc) for doc in relevant_memory] diff --git a/libs/experimental/langchain_experimental/generative_agents/memory.py b/libs/experimental/langchain_experimental/generative_agents/memory.py index 814fac0232..64791decf0 100644 --- a/libs/experimental/langchain_experimental/generative_agents/memory.py +++ b/libs/experimental/langchain_experimental/generative_agents/memory.py @@ -224,9 +224,9 @@ class GenerativeAgentMemory(BaseMemory): """Fetch related memories.""" if now is not None: with mock_now(now): - return self.memory_retriever.get_relevant_documents(observation) + return self.memory_retriever.invoke(observation) else: - return self.memory_retriever.get_relevant_documents(observation) + return self.memory_retriever.invoke(observation) def format_memories_detail(self, relevant_memories: List[Document]) -> str: content = [] diff --git a/libs/langchain/langchain/chains/conversational_retrieval/base.py b/libs/langchain/langchain/chains/conversational_retrieval/base.py index c92f18f7e8..d033c3e099 100644 --- a/libs/langchain/langchain/chains/conversational_retrieval/base.py +++ b/libs/langchain/langchain/chains/conversational_retrieval/base.py @@ -314,8 +314,8 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain): run_manager: CallbackManagerForChainRun, ) -> List[Document]: """Get docs.""" - docs = self.retriever.get_relevant_documents( - question, callbacks=run_manager.get_child() + docs = self.retriever.invoke( + question, config={"callbacks": run_manager.get_child()} ) return self._reduce_tokens_below_limit(docs) @@ -327,8 +327,8 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain): run_manager: AsyncCallbackManagerForChainRun, ) -> List[Document]: """Get docs.""" - docs = await self.retriever.aget_relevant_documents( - question, callbacks=run_manager.get_child() + docs = await self.retriever.ainvoke( + question, config={"callbacks": run_manager.get_child()} ) return self._reduce_tokens_below_limit(docs) diff --git a/libs/langchain/langchain/chains/flare/base.py b/libs/langchain/langchain/chains/flare/base.py index c2ef8f2da6..8beb5b82e2 100644 --- a/libs/langchain/langchain/chains/flare/base.py +++ b/libs/langchain/langchain/chains/flare/base.py @@ -155,7 +155,7 @@ class FlareChain(Chain): callbacks = _run_manager.get_child() docs = [] for question in questions: - docs.extend(self.retriever.get_relevant_documents(question)) + docs.extend(self.retriever.invoke(question)) context = "\n\n".join(d.page_content for d in docs) result = self.response_chain.predict( user_input=user_input, diff --git a/libs/langchain/langchain/chains/qa_with_sources/retrieval.py b/libs/langchain/langchain/chains/qa_with_sources/retrieval.py index 9642f626ad..f4a924c8dd 100644 --- a/libs/langchain/langchain/chains/qa_with_sources/retrieval.py +++ b/libs/langchain/langchain/chains/qa_with_sources/retrieval.py @@ -46,8 +46,8 @@ class RetrievalQAWithSourcesChain(BaseQAWithSourcesChain): self, inputs: Dict[str, Any], *, run_manager: CallbackManagerForChainRun ) -> List[Document]: question = inputs[self.question_key] - docs = self.retriever.get_relevant_documents( - question, callbacks=run_manager.get_child() + docs = self.retriever.invoke( + question, config={"callbacks": run_manager.get_child()} ) return self._reduce_tokens_below_limit(docs) @@ -55,8 +55,8 @@ class RetrievalQAWithSourcesChain(BaseQAWithSourcesChain): self, inputs: Dict[str, Any], *, run_manager: AsyncCallbackManagerForChainRun ) -> List[Document]: question = inputs[self.question_key] - docs = await self.retriever.aget_relevant_documents( - question, callbacks=run_manager.get_child() + docs = await self.retriever.ainvoke( + question, config={"callbacks": run_manager.get_child()} ) return self._reduce_tokens_below_limit(docs) diff --git a/libs/langchain/langchain/chains/retrieval_qa/base.py b/libs/langchain/langchain/chains/retrieval_qa/base.py index 392a0b2cc4..0a9eaafd6f 100644 --- a/libs/langchain/langchain/chains/retrieval_qa/base.py +++ b/libs/langchain/langchain/chains/retrieval_qa/base.py @@ -218,8 +218,8 @@ class RetrievalQA(BaseRetrievalQA): run_manager: CallbackManagerForChainRun, ) -> List[Document]: """Get docs.""" - return self.retriever.get_relevant_documents( - question, callbacks=run_manager.get_child() + return self.retriever.invoke( + question, config={"callbacks": run_manager.get_child()} ) async def _aget_docs( @@ -229,8 +229,8 @@ class RetrievalQA(BaseRetrievalQA): run_manager: AsyncCallbackManagerForChainRun, ) -> List[Document]: """Get docs.""" - return await self.retriever.aget_relevant_documents( - question, callbacks=run_manager.get_child() + return await self.retriever.ainvoke( + question, config={"callbacks": run_manager.get_child()} ) @property diff --git a/libs/langchain/langchain/memory/vectorstore.py b/libs/langchain/langchain/memory/vectorstore.py index b288ef57d8..b719749b1c 100644 --- a/libs/langchain/langchain/memory/vectorstore.py +++ b/libs/langchain/langchain/memory/vectorstore.py @@ -55,7 +55,7 @@ class VectorStoreRetrieverMemory(BaseMemory): """Return history buffer.""" input_key = self._get_prompt_input_key(inputs) query = inputs[input_key] - docs = self.retriever.get_relevant_documents(query) + docs = self.retriever.invoke(query) return self._documents_to_memory_variables(docs) async def aload_memory_variables( @@ -64,7 +64,7 @@ class VectorStoreRetrieverMemory(BaseMemory): """Return history buffer.""" input_key = self._get_prompt_input_key(inputs) query = inputs[input_key] - docs = await self.retriever.aget_relevant_documents(query) + docs = await self.retriever.ainvoke(query) return self._documents_to_memory_variables(docs) def _form_documents( diff --git a/libs/langchain/langchain/retrievers/contextual_compression.py b/libs/langchain/langchain/retrievers/contextual_compression.py index b41a82a2b4..d41ea489de 100644 --- a/libs/langchain/langchain/retrievers/contextual_compression.py +++ b/libs/langchain/langchain/retrievers/contextual_compression.py @@ -41,8 +41,8 @@ class ContextualCompressionRetriever(BaseRetriever): Returns: Sequence of relevant documents """ - docs = self.base_retriever.get_relevant_documents( - query, callbacks=run_manager.get_child(), **kwargs + docs = self.base_retriever.invoke( + query, config={"callbacks": run_manager.get_child()}, **kwargs ) if docs: compressed_docs = self.base_compressor.compress_documents( @@ -67,8 +67,8 @@ class ContextualCompressionRetriever(BaseRetriever): Returns: List of relevant documents """ - docs = await self.base_retriever.aget_relevant_documents( - query, callbacks=run_manager.get_child(), **kwargs + docs = await self.base_retriever.ainvoke( + query, config={"callbacks": run_manager.get_child()}, **kwargs ) if docs: compressed_docs = await self.base_compressor.acompress_documents( diff --git a/libs/langchain/langchain/retrievers/merger_retriever.py b/libs/langchain/langchain/retrievers/merger_retriever.py index 4979779c25..179fb2d0e8 100644 --- a/libs/langchain/langchain/retrievers/merger_retriever.py +++ b/libs/langchain/langchain/retrievers/merger_retriever.py @@ -72,8 +72,11 @@ class MergerRetriever(BaseRetriever): # Get the results of all retrievers. retriever_docs = [ - retriever.get_relevant_documents( - query, callbacks=run_manager.get_child("retriever_{}".format(i + 1)) + retriever.invoke( + query, + config={ + "callbacks": run_manager.get_child("retriever_{}".format(i + 1)) + }, ) for i, retriever in enumerate(self.retrievers) ] @@ -104,8 +107,11 @@ class MergerRetriever(BaseRetriever): # Get the results of all retrievers. retriever_docs = await asyncio.gather( *( - retriever.aget_relevant_documents( - query, callbacks=run_manager.get_child("retriever_{}".format(i + 1)) + retriever.ainvoke( + query, + config={ + "callbacks": run_manager.get_child("retriever_{}".format(i + 1)) + }, ) for i, retriever in enumerate(self.retrievers) ) diff --git a/libs/langchain/langchain/retrievers/multi_query.py b/libs/langchain/langchain/retrievers/multi_query.py index ca7e731c51..d468ffd627 100644 --- a/libs/langchain/langchain/retrievers/multi_query.py +++ b/libs/langchain/langchain/retrievers/multi_query.py @@ -136,8 +136,8 @@ class MultiQueryRetriever(BaseRetriever): """ document_lists = await asyncio.gather( *( - self.retriever.aget_relevant_documents( - query, callbacks=run_manager.get_child() + self.retriever.ainvoke( + query, config={"callbacks": run_manager.get_child()} ) for query in queries ) @@ -196,8 +196,8 @@ class MultiQueryRetriever(BaseRetriever): """ documents = [] for query in queries: - docs = self.retriever.get_relevant_documents( - query, callbacks=run_manager.get_child() + docs = self.retriever.invoke( + query, config={"callbacks": run_manager.get_child()} ) documents.extend(docs) return documents diff --git a/libs/langchain/langchain/retrievers/re_phraser.py b/libs/langchain/langchain/retrievers/re_phraser.py index 2ffdd45e3e..87673d1802 100644 --- a/libs/langchain/langchain/retrievers/re_phraser.py +++ b/libs/langchain/langchain/retrievers/re_phraser.py @@ -74,8 +74,8 @@ class RePhraseQueryRetriever(BaseRetriever): response = self.llm_chain(query, callbacks=run_manager.get_child()) re_phrased_question = response["text"] logger.info(f"Re-phrased question: {re_phrased_question}") - docs = self.retriever.get_relevant_documents( - re_phrased_question, callbacks=run_manager.get_child() + docs = self.retriever.invoke( + re_phrased_question, config={"callbacks": run_manager.get_child()} ) return docs diff --git a/libs/langchain/tests/integration_tests/retrievers/test_contextual_compression.py b/libs/langchain/tests/integration_tests/retrievers/test_contextual_compression.py index 54c8a170c3..020cb1133c 100644 --- a/libs/langchain/tests/integration_tests/retrievers/test_contextual_compression.py +++ b/libs/langchain/tests/integration_tests/retrievers/test_contextual_compression.py @@ -21,6 +21,6 @@ def test_contextual_compression_retriever_get_relevant_docs() -> None: base_compressor=base_compressor, base_retriever=base_retriever ) - actual = retriever.get_relevant_documents("Tell me about the Celtics") + actual = retriever.invoke("Tell me about the Celtics") assert len(actual) == 2 assert texts[-1] not in [d.page_content for d in actual] diff --git a/libs/langchain/tests/integration_tests/retrievers/test_merger_retriever.py b/libs/langchain/tests/integration_tests/retrievers/test_merger_retriever.py index 897931e65b..ec0eeb4cf3 100644 --- a/libs/langchain/tests/integration_tests/retrievers/test_merger_retriever.py +++ b/libs/langchain/tests/integration_tests/retrievers/test_merger_retriever.py @@ -27,7 +27,7 @@ def test_merger_retriever_get_relevant_docs() -> None: # The Lord of the Retrievers. lotr = MergerRetriever(retrievers=[retriever_a, retriever_b]) - actual = lotr.get_relevant_documents("Tell me about the Celtics") + actual = lotr.invoke("Tell me about the Celtics") assert len(actual) == 2 assert texts_group_a[0] in [d.page_content for d in actual] assert texts_group_b[1] in [d.page_content for d in actual] diff --git a/libs/langchain/tests/integration_tests/test_long_context_reorder.py b/libs/langchain/tests/integration_tests/test_long_context_reorder.py index 4649a150a5..b6e3c33fe4 100644 --- a/libs/langchain/tests/integration_tests/test_long_context_reorder.py +++ b/libs/langchain/tests/integration_tests/test_long_context_reorder.py @@ -25,7 +25,7 @@ def test_long_context_reorder() -> None: search_kwargs={"k": 10} ) reordering = LongContextReorder() - docs = retriever.get_relevant_documents("Tell me about the Celtics") + docs = retriever.invoke("Tell me about the Celtics") actual = reordering.transform_documents(docs) # First 2 and Last 2 elements must contain the most relevant diff --git a/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py b/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py index c4eb6397cc..0eb49e612a 100644 --- a/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py +++ b/libs/langchain/tests/unit_tests/retrievers/test_ensemble.py @@ -21,7 +21,7 @@ def test_ensemble_retriever_get_relevant_docs() -> None: ensemble_retriever = EnsembleRetriever( # type: ignore[call-arg] retrievers=[dummy_retriever, dummy_retriever] ) - docs = ensemble_retriever.get_relevant_documents("I like apples") + docs = ensemble_retriever.invoke("I like apples") assert len(docs) == 1 @@ -75,5 +75,5 @@ def test_ensemble_retriever_get_relevant_docs_with_multiple_retrievers() -> None retrievers=[dummy_retriever, tfidf_retriever, knn_retriever], weights=[0.6, 0.3, 0.1], ) - docs = ensemble_retriever.get_relevant_documents("I like apples") + docs = ensemble_retriever.invoke("I like apples") assert len(docs) == 3 diff --git a/libs/langchain/tests/unit_tests/retrievers/test_time_weighted_retriever.py b/libs/langchain/tests/unit_tests/retrievers/test_time_weighted_retriever.py index 9eeb86a8a0..5713a30851 100644 --- a/libs/langchain/tests/unit_tests/retrievers/test_time_weighted_retriever.py +++ b/libs/langchain/tests/unit_tests/retrievers/test_time_weighted_retriever.py @@ -129,11 +129,11 @@ async def test_aget_salient_docs( assert doc in want -def test_get_relevant_documents( +def test_invoke( time_weighted_retriever: TimeWeightedVectorStoreRetriever, ) -> None: query = "Test query" - relevant_documents = time_weighted_retriever.get_relevant_documents(query) + relevant_documents = time_weighted_retriever.invoke(query) want = [(doc, 0.5) for doc in _get_example_memories()] assert isinstance(relevant_documents, list) assert len(relevant_documents) == len(want) @@ -147,11 +147,11 @@ def test_get_relevant_documents( assert now - timedelta(hours=1) < d.metadata["last_accessed_at"] <= now -async def test_aget_relevant_documents( +async def test_ainvoke( time_weighted_retriever: TimeWeightedVectorStoreRetriever, ) -> None: query = "Test query" - relevant_documents = await time_weighted_retriever.aget_relevant_documents(query) + relevant_documents = await time_weighted_retriever.ainvoke(query) want = [(doc, 0.5) for doc in _get_example_memories()] assert isinstance(relevant_documents, list) assert len(relevant_documents) == len(want) diff --git a/libs/partners/exa/README.md b/libs/partners/exa/README.md index e0bcfa223d..ab06cd4f1b 100644 --- a/libs/partners/exa/README.md +++ b/libs/partners/exa/README.md @@ -21,7 +21,7 @@ exa_api_key = "YOUR API KEY" exa = ExaSearchRetriever(exa_api_key=exa_api_key) # Search for a query and save the results -results = exa.get_relevant_documents(query="What is the capital of France?") +results = exa.invoke("What is the capital of France?") # Print the results print(results) diff --git a/templates/anthropic-iterative-search/anthropic_iterative_search/retriever.py b/templates/anthropic-iterative-search/anthropic_iterative_search/retriever.py index 5377e65be3..2dba68eae6 100644 --- a/templates/anthropic-iterative-search/anthropic_iterative_search/retriever.py +++ b/templates/anthropic-iterative-search/anthropic_iterative_search/retriever.py @@ -14,4 +14,4 @@ RETRIEVER_TOOL_NAME = "search" @tool def search(query): """Search with the retriever.""" - return retriever.get_relevant_documents(query) + return retriever.invoke(query) diff --git a/templates/cohere-librarian/cohere_librarian/blurb_matcher.py b/templates/cohere-librarian/cohere_librarian/blurb_matcher.py index e550331160..c029935aaf 100644 --- a/templates/cohere-librarian/cohere_librarian/blurb_matcher.py +++ b/templates/cohere-librarian/cohere_librarian/blurb_matcher.py @@ -44,6 +44,6 @@ PROMPT = PromptTemplate( ) book_rec_chain = { - "input_documents": lambda x: docsearch.get_relevant_documents(x["message"]), + "input_documents": lambda x: docsearch.invoke(x["message"]), "message": lambda x: x["message"], } | load_qa_chain(chat, chain_type="stuff", prompt=PROMPT) diff --git a/templates/cohere-librarian/cohere_librarian/rag.py b/templates/cohere-librarian/cohere_librarian/rag.py index d45099faf9..da15f2cda1 100644 --- a/templates/cohere-librarian/cohere_librarian/rag.py +++ b/templates/cohere-librarian/cohere_librarian/rag.py @@ -5,7 +5,7 @@ rag = CohereRagRetriever(llm=ChatCohere()) def get_docs_message(message): - docs = rag.get_relevant_documents(message) + docs = rag.invoke(message) message_doc = next( (x for x in docs if x.metadata.get("type") == "model_response"), None ) diff --git a/templates/openai-functions-tool-retrieval-agent/openai_functions_tool_retrieval_agent/agent.py b/templates/openai-functions-tool-retrieval-agent/openai_functions_tool_retrieval_agent/agent.py index c20f50f218..9bf2457765 100644 --- a/templates/openai-functions-tool-retrieval-agent/openai_functions_tool_retrieval_agent/agent.py +++ b/templates/openai-functions-tool-retrieval-agent/openai_functions_tool_retrieval_agent/agent.py @@ -55,7 +55,7 @@ retriever = vector_store.as_retriever() def get_tools(query: str) -> List[Tool]: - docs = retriever.get_relevant_documents(query) + docs = retriever.invoke(query) return [ALL_TOOLS[d.metadata["index"]] for d in docs]