id stringlengths 14 15 | text stringlengths 23 2.21k | source stringlengths 52 97 |
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e4fa732f8a3d-5 | fund� worthless. \n\nWe are choking off Russia’s access to technology that will sap its economic strength and weaken its military for years to come. \n\nTonight I say to the Russian oligarchs and corrupt leaders who have bilked billions of dollars off this violent regime no more. \n\nThe U.S. Department of Justi... | https://python.langchain.com/docs/integrations/vectorstores/annoy |
e4fa732f8a3d-6 | = Annoy.from_documents(docs, embeddings_func)query = "What did the president say about Ketanji Brown Jackson"docs = vector_store_from_docs.similarity_search(query)print(docs[0].page_content[:100]) Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights AcCreate VectorStore v... | https://python.langchain.com/docs/integrations/vectorstores/annoy |
e4fa732f8a3d-7 | via docstore id​vector_store.index_to_docstore_id {0: '2d1498a8-a37c-4798-acb9-0016504ed798', 1: '2d30aecc-88e0-4469-9d51-0ef7e9858e6d', 2: '927f1120-985b-4691-b577-ad5cb42e011c', 3: '3056ddcf-a62f-48c8-bd98-b9e57a3dfcae'}some_docstore_id = 0 # texts[0]vector_store.docstore._dict[vector_store.index_to... | https://python.langchain.com/docs/integrations/vectorstores/annoy |
e4fa732f8a3d-8 | (Document(page_content='I love salad', metadata={}), 1.0734446048736572), (Document(page_content='my car', metadata={}), 1.2895267009735107)]Construct from scratch​import uuidfrom annoy import AnnoyIndexfrom langchain.docstore.document import Documentfrom langchain.docstore.in_memory import InMemoryDocstoremetada... | https://python.langchain.com/docs/integrations/vectorstores/annoy |
e4fa732f8a3d-9 | 1.1668788194656372), (Document(page_content='my car', metadata={'x': 'stuff'}), 1.226445198059082)]PreviousAnalyticDBNextAtlasCreate VectorStore from textsCreate VectorStore from docsCreate VectorStore via existing embeddingsSearch via embeddingsSearch via docstore idSave and loadConstruct from scratchCommunityDisc... | https://python.langchain.com/docs/integrations/vectorstores/annoy |
a96338c0351e-0 | MatchingEngine | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/matchingengine |
a96338c0351e-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/matchingengine |
a96338c0351e-2 | texts=texts, project_id="<my_project_id>", region="<my_region>", gcs_bucket_uri="<my_gcs_bucket>", index_id="<my_matching_engine_index_id>", endpoint_id="<my_matching_engine_endpoint_id>",)vector_store.add_texts(texts=texts)vector_store.similarity_search("lunch", k=2)Create Index and deploy it to an Endp... | https://python.langchain.com/docs/integrations/vectorstores/matchingengine |
a96338c0351e-3 | config set project {PROJECT_ID}# Remove the if condition to run the encapsulated codeif CREATE_VPC: # Create a VPC network gcloud compute networks create {VPC_NETWORK} --bgp-routing-mode=regional --subnet-mode=auto --project={PROJECT_ID} # Add necessary firewall rules gcloud compute firewall-rules create {VPC_NET... | https://python.langchain.com/docs/integrations/vectorstores/matchingengine |
a96338c0351e-4 | Sentence Encoder as an Embedder​# Load the Universal Sentence Encoder modulemodule_url = "https://tfhub.dev/google/universal-sentence-encoder-multilingual/3"model = hub.load(module_url)# Generate embeddings for each wordembeddings = model(["banana"])Inserting a test embedding​initial_config = { "id": "banana_id"... | https://python.langchain.com/docs/integrations/vectorstores/matchingengine |
72d7a3a288b7-0 | SingleStoreDB | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/singlestoredb |
72d7a3a288b7-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/singlestoredb |
72d7a3a288b7-2 | = TextLoader("../../../state_of_the_union.txt")documents = loader.load()text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)docs = text_splitter.split_documents(documents)embeddings = OpenAIEmbeddings()There are several ways to establish a connection to the database. You can either set up environment... | https://python.langchain.com/docs/integrations/vectorstores/singlestoredb |
d284632beb03-0 | Activeloop's Deep Lake | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-2 | getpassos.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")activeloop_token = getpass.getpass("activeloop token:")embeddings = OpenAIEmbeddings()from langchain.document_loaders import TextLoaderloader = TextLoader("../../../state_of_the_union.txt")documents = loader.load()text_splitter = CharacterTextSplit... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-3 | chain_type="stuff", retriever=db.as_retriever(),)query = "What did the president say about Ketanji Brown Jackson"qa.run(query)Attribute based filtering in metadata​Let's create another vector store containing metadata with the year the documents were created.import randomfor d in docs: d.metadata["year"] = rand... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-4 | = activeloop_token# Embed and store the textsusername = "<username>" # your username on app.activeloop.aidataset_path = f"hub://{username}/langchain_testing_python" # could be also ./local/path (much faster locally), s3://bucket/path/to/dataset, gcs://path/to/dataset, etc.docs = text_splitter.split_documents(document... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-5 | whereby the query can be specified utilizing Deep Lake's Tensor Query Language (TQL).search_id = db.vectorstore.dataset.id[0].numpy()docs = db.similarity_search( query=None, tql_query=f"SELECT * WHERE id == '{search_id[0]}'",)docsCreating vector stores on AWS S3​dataset_path = f"s3://BUCKET/langchain_test" # c... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-6 | dtype compression ------- ------- ------- ------- ------- embedding generic (4, 1536) float32 None ids text (4, 1) str None metadata json (4, 1) str None text text (4, 1) str None Deep Lake API​you can access t... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-7 | text (42, 1) str None # get embeddings numpy arrayembeds = db.vectorstore.dataset.embedding.numpy()Transfer local dataset to cloud​Copy already created dataset to the cloud. You can also transfer from cloud to local.import deeplakeusername = "davitbun" # your username on app.activeloop.aisource = f"h... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-8 | / hub://davitbun/langchain_test_copy loaded successfully. Deep Lake Dataset in hub://davitbun/langchain_test_copy already exists, loading from the storage Dataset(path='hub://davitbun/langchain_test_copy', tensors=['embedding', 'ids', 'metadata', 'text']) tensor htype shape dtype comp... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
d284632beb03-9 | ------- ------- ------- ------- ------- embedding generic (8, 1536) float32 None ids text (8, 1) str None metadata json (8, 1) str None text text (8, 1) str None ['ad42f3fe-e188-11ed-b66d-41c5f7b85421', 'ad42f3... | https://python.langchain.com/docs/integrations/vectorstores/deeplake |
525e8345939d-0 | PGVector | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-2 | (0.27.7) Requirement already satisfied: requests>=2.20 in /Users/joyeed/langchain/langchain/.venv/lib/python3.9/site-packages (from openai) (2.28.2) Requirement already satisfied: tqdm in /Users/joyeed/langchain/langchain/.venv/lib/python3.9/site-packages (from openai) (4.65.0) Requirement already satisfied: a... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-3 | (from aiohttp->openai) (23.1.0) Requirement already satisfied: multidict<7.0,>=4.5 in /Users/joyeed/langchain/langchain/.venv/lib/python3.9/site-packages (from aiohttp->openai) (6.0.4) Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /Users/joyeed/langchain/langchain/.venv/lib/python3.9/site-packages... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-4 | (from tiktoken) (2023.5.5) Requirement already satisfied: requests>=2.26.0 in /Users/joyeed/langchain/langchain/.venv/lib/python3.9/site-packages (from tiktoken) (2.28.2) Requirement already satisfied: charset-normalizer<4,>=2 in /Users/joyeed/langchain/langchain/.venv/lib/python3.9/site-packages (from requests>=... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-5 | Falsefrom langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores.pgvector import PGVectorfrom langchain.document_loaders import TextLoaderfrom langchain.docstore.document import Documentloader = TextLoader("../../../state_of_the_union.txt"... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-6 | = "What did the president say about Ketanji Brown Jackson"docs_with_score = db.similarity_search_with_score(query)for doc, score in docs_with_score: print("-" * 80) print("Score: ", score) print(doc.page_content) print("-" * 80) ----------------------------------------------------------------------------... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-7 | I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. One of the most serious constitutional responsibilities a President... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-8 | 0.21730864082247825 A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appoin... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-9 | In order to do that, we can initialize it directly.store = PGVector( collection_name=COLLECTION_NAME, connection_string=CONNECTION_STRING, embedding_function=embeddings,)Add documents​We can add documents to the existing vectorstore.store.add_documents([Document(page_content="foo")]) ['048c2e14-1cf3-11ee-... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-10 | a vectorstore​If you have an existing collection, you override it by doing from_documents and setting pre_delete_collection = Truedb = PGVector.from_documents( documents=docs, embedding=embeddings, collection_name=COLLECTION_NAME, connection_string=CONNECTION_STRING, pre_delete_collection=True,)docs_wi... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
525e8345939d-11 | object at 0x29f94f880> search_type='similarity' search_kwargs={}Previouspg_embeddingNextPineconeSimilarity Search with Euclidean Distance (Default)Working with vectorstoreAdd documentsOverriding a vectorstoreUsing a VectorStore as a RetrieverCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 Lang... | https://python.langchain.com/docs/integrations/vectorstores/pgvector |
a6cf1fb45b14-0 | Zilliz | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/zilliz |
a6cf1fb45b14-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/zilliz |
a6cf1fb45b14-2 | "" # example: "username"ZILLIZ_CLOUD_PASSWORD = "" # example: "*********"ZILLIZ_CLOUD_API_KEY = "" # example: "*********" (for serverless clusters which can be used as replacements for user and password)from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterf... | https://python.langchain.com/docs/integrations/vectorstores/zilliz |
a6cf1fb45b14-3 | I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n\nOne of the most serious constitutional responsibilities a President has... | https://python.langchain.com/docs/integrations/vectorstores/zilliz |
334da13dc961-0 | ClickHouse Vector Search | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/clickhouse |
334da13dc961-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/clickhouse |
334da13dc961-2 | OpenAIEmbeddings so we have to get the OpenAI API Key.import osimport getpassif not os.environ["OPENAI_API_KEY"]: os.environ["OPENAI_API_KEY"] = getpass.getpass("OpenAI API Key:")from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstor... | https://python.langchain.com/docs/integrations/vectorstores/clickhouse |
334da13dc961-3 | Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. And I did that... | https://python.langchain.com/docs/integrations/vectorstores/clickhouse |
334da13dc961-4 | automatically created if not exist by default. Advanced users could pre-create the table with optimized settings. For distributed Clickhouse cluster with sharding, table engine should be configured as Distributed.print(f"Clickhouse Table DDL:\n\n{docsearch.schema}") Clickhouse Table DDL: CREATE TABLE IF NOT E... | https://python.langchain.com/docs/integrations/vectorstores/clickhouse |
334da13dc961-5 | = Clickhouse.from_documents(docs, embeddings) Inserting data...: 100%|██████████| 42/42 [00:00<00:00, 6939.56it/s]meta = docsearch.metadata_columnoutput = docsearch.similarity_search_with_relevance_scores( "What did the president say about Ketanji Brown Jackson?", k=4, where_str=f"{meta}... | https://python.langchain.com/docs/integrations/vectorstores/clickhouse |
ed65498ea416-0 | scikit-learn | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/sklearn |
ed65498ea416-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/sklearn |
ed65498ea416-2 | langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores import SKLearnVectorStorefrom langchain.document_loaders import TextLoaderloader = TextLoader("../../../state_of_the_union.txt")documents = loader.load()text_splitter = CharacterTextSp... | https://python.langchain.com/docs/integrations/vectorstores/sklearn |
ed65498ea416-3 | days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.Saving and loading a vector store​vector_store.persist()print("Vector store was persisted to", persist_path) Vector store was persisted t... | https://python.langchain.com/docs/integrations/vectorstores/sklearn |
ed65498ea416-4 | Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.Clean-up​os.remove(persist_path)PreviousSingleStoreDBNextStarRocksBasic usageLoad a sample document corpusCreate the SKLearnVectorStore, index the document corpus and run a sample querySaving and loading a ... | https://python.langchain.com/docs/integrations/vectorstores/sklearn |
7d6e6fa3a1a3-0 | AnalyticDB | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/analyticdb |
7d6e6fa3a1a3-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/analyticdb |
7d6e6fa3a1a3-2 | To run, you should have an AnalyticDB instance up and running:Using AnalyticDB Cloud Vector Database. Click here to fast deploy it.from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores import AnalyticDBSplit documents and get embeddi... | https://python.langchain.com/docs/integrations/vectorstores/analyticdb |
7d6e6fa3a1a3-3 | Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer... | https://python.langchain.com/docs/integrations/vectorstores/analyticdb |
781e9d57f53a-0 | Tair | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/tair |
781e9d57f53a-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/tair |
781e9d57f53a-2 | It provides rich data models and enterprise-grade capabilities to support your real-time online scenarios while maintaining full compatibility with open source Redis. Tair also introduces persistent memory-optimized instances that are based on the new non-volatile memory (NVM) storage medium.This notebook shows how to ... | https://python.langchain.com/docs/integrations/vectorstores/tair |
781e9d57f53a-3 | \n\nThe only president ever to cut the deficit by more than one trillion dollars in a single year. \n\nLowering your costs also means demanding more competition. \n\nI’m a capitalist, but capitalism without competition isn’t capitalism. \n\nIt’s exploitation—and it drives up prices. \n\nWhen corporations don’... | https://python.langchain.com/docs/integrations/vectorstores/tair |
4139eebdbcc6-0 | Atlas | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/atlas |
4139eebdbcc6-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/atlas |
4139eebdbcc6-2 | = [e.strip() for e in texts]db = AtlasDB.from_texts( texts=texts, name="test_index_" + str(time.time()), # unique name for your vector store description="test_index", # a description for your vector store api_key=ATLAS_TEST_API_KEY, index_kwargs={"build_topic_model": True},)db.project.wait_for_project_... | https://python.langchain.com/docs/integrations/vectorstores/atlas |
4139eebdbcc6-3 | } </script> <h4>Projection ID: db996d77-8981-48a0-897a-ff2c22bbf541</h4> <div class="actions"> <div id="hide" class="action" onclick="destroy()">Hide embedded project</div> <div class="action" id="out"> <a href="https://atlas.nomic.ai/map/ee2354a3-7f9a-4c6b-af43... | https://python.langchain.com/docs/integrations/vectorstores/atlas |
4139eebdbcc6-4 | .iframe { /* vh can be **very** large in vscode html. */ height: min(75vh, 66vw); width: 100%; } </style> <style> .actions { display: block; } .action { min-height: 18px; margin:... | https://python.langchain.com/docs/integrations/vectorstores/atlas |
4139eebdbcc6-5 | ""; } </style>PreviousAnnoyNextAwaDBCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/vectorstores/atlas |
95b057af9e0e-0 | Clarifai | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-2 | Check here to get or create a PAT.Dependencies# Install required dependenciespip install clarifaiImportsHere we will be setting the personal access token. You can find your PAT under settings/security on the platform.# Please login and get your API key from https://clarifai.com/settings/securityfrom getpass import get... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-3 | texts=texts, pat=CLARIFAI_PAT, number_of_docs=NUMBER_OF_DOCS, metadatas=metadatas,)docs = clarifai_vector_db.similarity_search("I would love to see you")docs [Document(page_content='I really enjoy spending time with you', metadata={'text': 'I really enjoy spending time with you', 'id': 0.0}), Document(p... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-4 | an unwavering resolve that freedom will always triumph over tyranny. \n\nSix days ago, Russia’s Vladimir Putin sought to shake the foundations of the free world thinking he could make it bend to his menacing ways. But he badly miscalculated. \n\nHe thought he could roll into Ukraine and the world would roll over. Ins... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-5 | Document(page_content='Putin’s latest attack on Ukraine was premeditated and unprovoked. \n\nHe rejected repeated efforts at diplomacy. \n\nHe thought the West and NATO wouldn’t respond. And he thought he could divide us at home. Putin was wrong. We were ready. Here is what we did. \n\nWe prepared extensively an... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-6 | \n\nTonight I say to the Russian oligarchs and corrupt leaders who have bilked billions of dollars off this violent regime no more. \n\nThe U.S. Department of Justice is assembling a dedicated task force to go after the crimes of Russian oligarchs. \n\nWe are joining with our European allies to find and seize your yac... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-7 | state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections. \n\nWe cannot let this happen.', metadata={'source': '../../../state_of_the_union.txt'}), Document(page_content='We can’t change how divided we’ve been. But we can change how we move forward—on COVID-... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
95b057af9e0e-8 | if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. \n\nWe can do both. At our border, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling. \n\nWe’ve set up joint patrols with Mexico and Guatemala to catch more human trafficke... | https://python.langchain.com/docs/integrations/vectorstores/clarifai |
7606f0f274af-0 | AwaDB | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/awadb |
7606f0f274af-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/awadb |
7606f0f274af-2 | nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.Similarity search with score​The returned distance score is between 0-1. 0 is dissimilar, 1 is the most similardocs = db.similarity_search_with_score(query)print(docs[0]) (Document(page_content='And I did that 4 days ago, when I ... | https://python.langchain.com/docs/integrations/vectorstores/awadb |
4e52e9aa7bad-0 | Alibaba Cloud OpenSearch | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/alibabacloud_opensearch |
4e52e9aa7bad-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/alibabacloud_opensearch |
4e52e9aa7bad-2 | To run, you should have an OpenSearch Vector Search Edition instance up and running:Read the help document to quickly familiarize and configure OpenSearch Vector Search Edition instance.After the instance is up and running, follow these steps to split documents, get embeddings, connect to the alibaba cloud opensearch i... | https://python.langchain.com/docs/integrations/vectorstores/alibabacloud_opensearch |
4e52e9aa7bad-3 | "id": "id", # The id field name mapping of index document. "document": "document", # The text field name mapping of index document. "embedding": "embedding", # The embedding field name mapping of index document. "name_of_the_metadata_specified_during_search": "opensearch_metadata_field_name,=", ... | https://python.langchain.com/docs/integrations/vectorstores/alibabacloud_opensearch |
4e52e9aa7bad-4 | "metadata_else": "metadata_else,="# })Create an opensearch access instance by settings.# Create an opensearch instance and index docs.opensearch = AlibabaCloudOpenSearch.from_texts( texts=docs, embedding=embeddings, config=settings)or# Create an opensearch instance.opensearch = AlibabaCloudOpenSearch(embedding=e... | https://python.langchain.com/docs/integrations/vectorstores/alibabacloud_opensearch |
4b0750257e4f-0 | Qdrant | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-2 | = getpass.getpass("OpenAI API Key:") OpenAI API Key: ········from langchain.embeddings.openai import OpenAIEmbeddingsfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.vectorstores import Qdrantfrom langchain.document_loaders import TextLoaderloader = TextLoader("../../../state_of_the_un... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-3 | if you choose to launch Qdrant locally with a Docker container, or select a Kubernetes deployment with the official Helm chart, the way you're going to connect to such an instance will be identical. You'll need to provide a URL pointing to the service.url = "<---qdrant url here --->"qdrant = Qdrant.from_documents( d... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-4 | embeddings, url, prefer_grpc=True, collection_name="my_documents", force_recreate=True,)Similarity search​The simplest scenario for using Qdrant vector store is to perform a similarity search. Under the hood, our query will be encoded with the embedding_function and used to find similar documents in Qdran... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-5 | The returned distance score is cosine distance. Therefore, a lower score is better.query = "What did the president say about Ketanji Brown Jackson"found_docs = qdrant.similarity_search_with_score(query)document, score = found_docs[0]print(document.page_content)print(f"\nScore: {score}") Tonight. I call on the Senate... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-6 | relevance search (MMR)​If you'd like to look up for some similar documents, but you'd also like to receive diverse results, MMR is method you should consider. Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.query = "What did the president say about Ketanji Brown Jac... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-7 | I recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera. They were responding to a 9-1-1 call when a man shot and killed them with a stolen gun. Officer Mora was 27 years old. Officer Rivera was 22. Both... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-8 | VectorStoreRetriever(vectorstore=<langchain.vectorstores.qdrant.Qdrant object at 0x7fc4e5720a00>, search_type='mmr', search_kwargs={})query = "What did the president say about Ketanji Brown Jackson"retriever.get_relevant_documents(query)[0] Document(page_content='Tonight. I call on the Senate to: Pass the Freedom to... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
4b0750257e4f-9 | name.Qdrant.from_documents( docs, embeddings, location=":memory:", collection_name="my_documents_2", vector_name="custom_vector",)As a Langchain user, you won't see any difference whether you use named vectors or not. Qdrant integration will handle the conversion under the hood.Metadata​Qdrant stores y... | https://python.langchain.com/docs/integrations/vectorstores/qdrant |
55eb69a560bf-0 | Tigris | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/tigris |
55eb69a560bf-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/tigris |
55eb69a560bf-2 | Tigris eliminates the infrastructure complexity of managing, operating, and synchronizing multiple tools, allowing you to focus on building great applications instead.This notebook guides you how to use Tigris as your VectorStorePre requisitesAn OpenAI account. You can sign up for an account hereSign up for a free Tigr... | https://python.langchain.com/docs/integrations/vectorstores/tigris |
55eb69a560bf-3 | index_name="my_embeddings")Similarity Search​query = "What did the president say about Ketanji Brown Jackson"found_docs = vector_store.similarity_search(query)print(found_docs)Similarity Search with score (vector distance)​query = "What did the president say about Ketanji Brown Jackson"result = vector_store.similar... | https://python.langchain.com/docs/integrations/vectorstores/tigris |
c63785fbd405-0 | Milvus | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/milvus |
c63785fbd405-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/milvus |
c63785fbd405-2 | = TextLoader("../../../state_of_the_union.txt")documents = loader.load()text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)docs = text_splitter.split_documents(documents)embeddings = OpenAIEmbeddings()vector_db = Milvus.from_documents( docs, embeddings, connection_args={"host": "127.0.0.1",... | https://python.langchain.com/docs/integrations/vectorstores/milvus |
a4cb4780b09c-0 | Redis | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/vectorstores/redis |
a4cb4780b09c-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesAlibaba Cloud OpenSearchAnalyticDBAnnoyAtlasAwaDBAzure Cognitive SearchCassandraChrom... | https://python.langchain.com/docs/integrations/vectorstores/redis |
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