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85d1981badec-4 | Maybe you would just like to throw out a neat fact that doesn\'t warrant a self post? Feel free to post here! \n\nIf your question is "I have $10,000, what do I do?" or other "advice for my personal situation" questions, you should include relevant information, such as the following:\n\n* How old are you? What country do you live in? \n* Are you employed/making income? How much? \n* What are your objectives with this money? (Buy a house? Retirement savings?) \n* What is your time horizon? Do you need this money next month? Next 20yrs? \n* What is your risk tolerance? (Do you mind risking it at blackjack or do you need to know its 100% safe?) \n* What are you current holdings? (Do you already have exposure to specific funds and sectors? Any other assets?) \n* Any big debts (include interest rate) or expenses? \n* And any other relevant financial information will be useful to give you a proper answer. \n\nPlease consider consulting our FAQ first - https://www.reddit.com/r/investing/wiki/faq\nAnd our [side bar](https://www.reddit.com/r/investing/about/sidebar) also has useful resources. \n\nIf you are new to investing - please refer to Wiki - [Getting Started](https://www.reddit.com/r/investing/wiki/index/gettingstarted/)\n\nThe reading list in the wiki has a list of books ranging from light reading to advanced topics depending on your knowledge level. Link here - [Reading List](https://www.reddit.com/r/investing/wiki/readinglist)\n\nCheck the resources in the sidebar.\n\nBe aware that these answers are just opinions of Redditors and should be used as a starting point for your research. | https://python.langchain.com/docs/integrations/document_loaders/reddit |
85d1981badec-5 | answers are just opinions of Redditors and should be used as a starting point for your research. You should strongly consider seeing a registered investment adviser if you need professional support before making any financial decisions!', metadata={'post_subreddit': 'r/investing', 'post_category': 'new', 'post_title': 'Daily General Discussion and Advice Thread - April 27, 2023', 'post_score': 5, 'post_id': '130eszz', 'post_url': 'https://www.reddit.com/r/investing/comments/130eszz/daily_general_discussion_and_advice_thread_april/', 'post_author': Redditor(name='AutoModerator')}), Document(page_content="Based on recent news about salt battery advancements and the overall issues of lithium, I was wondering what would be feasible ways to invest into non-lithium based battery technologies? CATL is of course a choice, but the selection of brokers I currently have in my disposal don't provide HK stocks at all.", metadata={'post_subreddit': 'r/investing', 'post_category': 'new', 'post_title': 'Investing in non-lithium battery technologies?', 'post_score': 2, 'post_id': '130d6qp', 'post_url': 'https://www.reddit.com/r/investing/comments/130d6qp/investing_in_nonlithium_battery_technologies/', 'post_author': Redditor(name='-manabreak')}), Document(page_content='Hello everyone,\n\nI would really like to invest in an ETF that follows spy or another big index, as I think this form of investment suits me best. \n\nThe problem is, that I live in Denmark where ETFs and funds are taxed annually on unrealised gains at quite a steep rate. This means that an ETF growing say 10% per year will only grow about 6%, which really ruins the long | https://python.langchain.com/docs/integrations/document_loaders/reddit |
85d1981badec-6 | ETF growing say 10% per year will only grow about 6%, which really ruins the long term effects of compounding interest.\n\nHowever stocks are only taxed on realised gains which is why they look more interesting to hold long term.\n\nI do not like the lack of diversification this brings, as I am looking to spend tonnes of time picking the right long term stocks.\n\nIt would be ideal to find a few stocks that over the long term somewhat follows the indexes. Does anyone have suggestions?\n\nI have looked at Nasdaq Inc. which quite closely follows Nasdaq 100. \n\nI really appreciate any help.', metadata={'post_subreddit': 'r/investing', 'post_category': 'new', 'post_title': 'Stocks that track an index', 'post_score': 7, 'post_id': '130auvj', 'post_url': 'https://www.reddit.com/r/investing/comments/130auvj/stocks_that_track_an_index/', 'post_author': Redditor(name='LeAlbertP')})]PreviousRecursive URL LoaderNextRoamCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/reddit |
05c0754ab09f-0 | Azure Blob Storage Container | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/azure_blob_storage_container |
05c0754ab09f-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersAzure Blob Storage ContainerOn this pageAzure Blob Storage ContainerAzure Blob Storage is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured | https://python.langchain.com/docs/integrations/document_loaders/azure_blob_storage_container |
05c0754ab09f-2 | Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data. Unstructured data is data that doesn't adhere to a particular data model or definition, such as text or binary data.Azure Blob Storage is designed for:Serving images or documents directly to a browser.Storing files for distributed access.Streaming video and audio.Writing to log files.Storing data for backup and restore, disaster recovery, and archiving.Storing data for analysis by an on-premises or Azure-hosted service.This notebook covers how to load document objects from a container on Azure Blob Storage.#!pip install azure-storage-blobfrom langchain.document_loaders import AzureBlobStorageContainerLoaderloader = AzureBlobStorageContainerLoader(conn_str="<conn_str>", container="<container>")loader.load() [Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': '/var/folders/y6/8_bzdg295ld6s1_97_12m4lr0000gn/T/tmpaa9xl6ch/fake.docx'}, lookup_index=0)]Specifying a prefix​You can also specify a prefix for more finegrained control over what files to load.loader = AzureBlobStorageContainerLoader( conn_str="<conn_str>", container="<container>", prefix="<prefix>")loader.load() [Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': '/var/folders/y6/8_bzdg295ld6s1_97_12m4lr0000gn/T/tmpujbkzf_l/fake.docx'}, lookup_index=0)]PreviousAZLyricsNextAzure Blob Storage FileSpecifying a prefixCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/azure_blob_storage_container |
f3ee0197e85d-0 | Microsoft OneDrive | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/microsoft_onedrive |
f3ee0197e85d-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersMicrosoft OneDriveOn this pageMicrosoft OneDriveMicrosoft OneDrive (formerly SkyDrive) is a file hosting service operated by Microsoft.This notebook covers how to load documents from | https://python.langchain.com/docs/integrations/document_loaders/microsoft_onedrive |
f3ee0197e85d-2 | SkyDrive) is a file hosting service operated by Microsoft.This notebook covers how to load documents from OneDrive. Currently, only docx, doc, and pdf files are supported.Prerequisites​Register an application with the Microsoft identity platform instructions.When registration finishes, the Azure portal displays the app registration's Overview pane. You see the Application (client) ID. Also called the client ID, this value uniquely identifies your application in the Microsoft identity platform.During the steps you will be following at item 1, you can set the redirect URI as http://localhost:8000/callbackDuring the steps you will be following at item 1, generate a new password (client_secret) under Application Secrets section.Follow the instructions at this document to add the following SCOPES (offline_access and Files.Read.All) to your application.Visit the Graph Explorer Playground to obtain your OneDrive ID. The first step is to ensure you are logged in with the account associated your OneDrive account. Then you need to make a request to https://graph.microsoft.com/v1.0/me/drive and the response will return a payload with a field id that holds the ID of your OneDrive account.You need to install the o365 package using the command pip install o365.At the end of the steps you must have the following values: CLIENT_IDCLIENT_SECRETDRIVE_ID🧑 Instructions for ingesting your documents from OneDrive​🔑 Authentication​By default, the OneDriveLoader expects that the values of CLIENT_ID and CLIENT_SECRET must be stored as environment variables named O365_CLIENT_ID and O365_CLIENT_SECRET respectively. You could pass those environment variables through a .env file at the root of your application or using the following command in your script.os.environ['O365_CLIENT_ID'] = "YOUR CLIENT ID"os.environ['O365_CLIENT_SECRET'] = "YOUR CLIENT SECRET"This loader uses an authentication called on behalf | https://python.langchain.com/docs/integrations/document_loaders/microsoft_onedrive |
f3ee0197e85d-3 | = "YOUR CLIENT SECRET"This loader uses an authentication called on behalf of a user. It is a 2 step authentication with user consent. When you instantiate the loader, it will call will print a url that the user must visit to give consent to the app on the required permissions. The user must then visit this url and give consent to the application. Then the user must copy the resulting page url and paste it back on the console. The method will then return True if the login attempt was succesful.from langchain.document_loaders.onedrive import OneDriveLoaderloader = OneDriveLoader(drive_id="YOUR DRIVE ID")Once the authentication has been done, the loader will store a token (o365_token.txt) at ~/.credentials/ folder. This token could be used later to authenticate without the copy/paste steps explained earlier. To use this token for authentication, you need to change the auth_with_token parameter to True in the instantiation of the loader.from langchain.document_loaders.onedrive import OneDriveLoaderloader = OneDriveLoader(drive_id="YOUR DRIVE ID", auth_with_token=True)🗂� Documents loader​📑 Loading documents from a OneDrive Directory​OneDriveLoader can load documents from a specific folder within your OneDrive. For instance, you want to load all documents that are stored at Documents/clients folder within your OneDrive.from langchain.document_loaders.onedrive import OneDriveLoaderloader = OneDriveLoader(drive_id="YOUR DRIVE ID", folder_path="Documents/clients", auth_with_token=True)documents = loader.load()📑 Loading documents from a list of Documents IDs​Another possibility is to provide a list of object_id for each document you want to load. For that, you will need to query the Microsoft Graph API to find all the documents ID that you are interested in. This link provides a list of endpoints | https://python.langchain.com/docs/integrations/document_loaders/microsoft_onedrive |
f3ee0197e85d-4 | API to find all the documents ID that you are interested in. This link provides a list of endpoints that will be helpful to retrieve the documents ID.For instance, to retrieve information about all objects that are stored at the root of the Documents folder, you need make a request to: https://graph.microsoft.com/v1.0/drives/{YOUR DRIVE ID}/root/children. Once you have the list of IDs that you are interested in, then you can instantiate the loader with the following parameters.from langchain.document_loaders.onedrive import OneDriveLoaderloader = OneDriveLoader(drive_id="YOUR DRIVE ID", object_ids=["ID_1", "ID_2"], auth_with_token=True)documents = loader.load()PreviousmhtmlNextMicrosoft PowerPointPrerequisites🧑 Instructions for ingesting your documents from OneDrive🔑 Authentication🗂� Documents loaderCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/microsoft_onedrive |
bbff206a39d7-0 | WebBaseLoader | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersWebBaseLoaderOn this pageWebBaseLoaderThis covers how to use WebBaseLoader to load all text from HTML webpages into a document format that we can use downstream. | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-2 | to load all text from HTML webpages into a document format that we can use downstream. For more custom logic for loading webpages look at some child class examples such as IMSDbLoader, AZLyricsLoader, and CollegeConfidentialLoaderfrom langchain.document_loaders import WebBaseLoaderloader = WebBaseLoader("https://www.espn.com/")To bypass SSL verification errors during fetching, you can set the "verify" option:loader.requests_kwargs = {'verify':False}data = loader.load()data [Document(page_content="\n\n\n\n\n\n\n\n\nESPN - Serving Sports Fans. Anytime. Anywhere.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n Skip to main content\n \n\n Skip to navigation\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<\n\n>\n\n\n\n\n\n\n\n\n\nMenuESPN\n\n\nSearch\n\n\n\nscores\n\n\n\nNFLNBANCAAMNCAAWNHLSoccer…MLBNCAAFGolfTennisSports BettingBoxingCFLNCAACricketF1HorseLLWSMMANASCARNBA G LeagueOlympic SportsRacingRN BBRN FBRugbyWNBAWorld Baseball ClassicWWEX GamesXFLMore | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-3 | BBRN FBRugbyWNBAWorld Baseball ClassicWWEX GamesXFLMore ESPNFantasyListenWatchESPN+\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\nSUBSCRIBE NOW\n\n\n\n\n\nNHL: Select Games\n\n\n\n\n\n\n\nXFL\n\n\n\n\n\n\n\nMLB: Select Games\n\n\n\n\n\n\n\nNCAA Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Games\n\n\n\n\n\n\n\nFantasy Baseball: Sign Up\n\n\n\n\n\n\n\nHow To Watch PGA TOUR\n\n\n\n\n\n\nFavorites\n\n\n\n\n\n\n Manage Favorites\n \n\n\n\nCustomize ESPNSign UpLog InESPN Sites\n\n\n\n\nESPN Deportes\n\n\n\n\n\n\n\nAndscape\n\n\n\n\n\n\n\nespnW\n\n\n\n\n\n\n\nESPNFC\n\n\n\n\n\n\n\nX Games\n\n\n\n\n\n\n\nSEC Network\n\n\nESPN Apps\n\n\n\n\nESPN\n\n\n\n\n\n\n\nESPN Fantasy\n\n\nFollow ESPN\n\n\n\n\nFacebook\n\n\n\n\n\n\n\nTwitter\n\n\n\n\n\n\n\nInstagram\n\n\n\n\n\n\n\nSnapchat\n\n\n\n\n\n\n\nYouTube\n\n\n\n\n\n\n\nThe ESPN Daily | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-4 | ESPN Daily Podcast\n\n\nAre you ready for Opening Day? Here's your guide to MLB's offseason chaosWait, Jacob deGrom is on the Rangers now? Xander Bogaerts and Trea Turner signed where? And what about Carlos Correa? Yeah, you're going to need to read up before Opening Day.12hESPNIllustration by ESPNEverything you missed in the MLB offseason3h2:33World Series odds, win totals, props for every teamPlay fantasy baseball for free!TOP HEADLINESQB Jackson has requested trade from RavensSources: Texas hiring Terry as full-time coachJets GM: No rush on Rodgers; Lamar not optionLove to leave North Carolina, enter transfer portalBelichick to angsty Pats fans: See last 25 yearsEmbiid out, Harden due back vs. Jokic, NuggetsLynch: Purdy 'earned the right' to start for NinersMan Utd, Wrexham plan July friendly in San DiegoOn paper, Padres overtake DodgersLAMAR WANTS OUT OF BALTIMOREMarcus Spears identifies the two teams that need Lamar Jackson the most8h2:00Would Lamar sit out? Will Ravens draft a QB? Jackson trade request insightsLamar Jackson has asked Baltimore to trade him, but Ravens coach John Harbaugh hopes the QB will be back.3hJamison HensleyBallard, Colts will consider trading for QB JacksonJackson to Indy? Washington? Barnwell ranks the QB's trade fitsSNYDER'S TUMULTUOUS 24-YEAR RUNHow Washington’s NFL franchise sank on and off the field under owner Dan SnyderSnyder purchased one of the NFL's marquee franchises in 1999. Twenty-four years later, and with the team up for sale, he leaves a legacy of on-field futility and off-field scandal.13hJohn KeimESPNIOWA STAR STEPS UP AGAINJ-Will: | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-5 | scandal.13hJohn KeimESPNIOWA STAR STEPS UP AGAINJ-Will: Caitlin Clark is the biggest brand in college sports right now8h0:47'The better the opponent, the better she plays': Clark draws comparisons to TaurasiCaitlin Clark's performance on Sunday had longtime observers going back decades to find comparisons.16hKevin PeltonWOMEN'S ELITE EIGHT SCOREBOARDMONDAY'S GAMESCheck your bracket!NBA DRAFTHow top prospects fared on the road to the Final FourThe 2023 NCAA tournament is down to four teams, and ESPN's Jonathan Givony recaps the players who saw their NBA draft stock change.11hJonathan GivonyAndy Lyons/Getty ImagesTALKING BASKETBALLWhy AD needs to be more assertive with LeBron on the court10h1:33Why Perk won't blame Kyrie for Mavs' woes8h1:48WHERE EVERY TEAM STANDSNew NFL Power Rankings: Post-free-agency 1-32 poll, plus underrated offseason movesThe free agent frenzy has come and gone. Which teams have improved their 2023 outlook, and which teams have taken a hit?12hNFL Nation reportersIllustration by ESPNTHE BUCK STOPS WITH BELICHICKBruschi: Fair to criticize Bill Belichick for Patriots' struggles10h1:27 Top HeadlinesQB Jackson has requested trade from RavensSources: Texas hiring Terry as full-time coachJets GM: No rush on Rodgers; Lamar not optionLove to leave North Carolina, enter transfer portalBelichick to angsty Pats fans: See last 25 yearsEmbiid out, Harden due back vs. Jokic, NuggetsLynch: Purdy 'earned the right' to start for NinersMan Utd, Wrexham plan July friendly in San DiegoOn paper, Padres overtake DodgersFavorites FantasyManage FavoritesFantasy | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-6 | plan July friendly in San DiegoOn paper, Padres overtake DodgersFavorites FantasyManage FavoritesFantasy HomeCustomize ESPNSign UpLog InMarch Madness LiveESPNMarch Madness LiveWatch every men's NCAA tournament game live! ICYMI1:42Austin Peay's coach, pitcher and catcher all ejected after retaliation pitchAustin Peay's pitcher, catcher and coach were all ejected after a pitch was thrown at Liberty's Nathan Keeter, who earlier in the game hit a home run and celebrated while running down the third-base line. Men's Tournament ChallengeIllustration by ESPNMen's Tournament ChallengeCheck your bracket(s) in the 2023 Men's Tournament Challenge, which you can follow throughout the Big Dance. Women's Tournament ChallengeIllustration by ESPNWomen's Tournament ChallengeCheck your bracket(s) in the 2023 Women's Tournament Challenge, which you can follow throughout the Big Dance. Best of ESPN+AP Photo/Lynne SladkyFantasy Baseball ESPN+ Cheat Sheet: Sleepers, busts, rookies and closersYou've read their names all preseason long, it'd be a shame to forget them on draft day. The ESPN+ Cheat Sheet is one way to make sure that doesn't happen.Steph Chambers/Getty ImagesPassan's 2023 MLB season preview: Bold predictions and moreOpening Day is just over a week away -- and Jeff Passan has everything you need to know covered from every possible angle.Photo by Bob Kupbens/Icon Sportswire2023 NFL free agency: Best team fits for unsigned playersWhere could Ezekiel Elliott land? Let's match remaining free agents to teams and find fits for two trade candidates.Illustration by ESPN2023 NFL mock draft: Mel Kiper's first-round pick predictionsMel Kiper Jr. makes his predictions for Round 1 of the NFL draft, including projecting a trade in the top five. Trending NowAnne-Marie Sorvin-USA TODAY SBoston Bruins record tracker: Wins, points, | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-7 | NowAnne-Marie Sorvin-USA TODAY SBoston Bruins record tracker: Wins, points, milestonesThe B's are on pace for NHL records in wins and points, along with some individual superlatives as well. Follow along here with our updated tracker.Mandatory Credit: William Purnell-USA TODAY Sports2023 NFL full draft order: AFC, NFC team picks for all roundsStarting with the Carolina Panthers at No. 1 overall, here's the entire 2023 NFL draft broken down round by round. How to Watch on ESPN+Gregory Fisher/Icon Sportswire2023 NCAA men's hockey: Results, bracket, how to watchThe matchups in Tampa promise to be thrillers, featuring plenty of star power, high-octane offense and stellar defense.(AP Photo/Koji Sasahara, File)How to watch the PGA Tour, Masters, PGA Championship and FedEx Cup playoffs on ESPN, ESPN+Here's everything you need to know about how to watch the PGA Tour, Masters, PGA Championship and FedEx Cup playoffs on ESPN and ESPN+.Hailie Lynch/XFLHow to watch the XFL: 2023 schedule, teams, players, news, moreEvery XFL game will be streamed on ESPN+. Find out when and where else you can watch the eight teams compete. Sign up to play the #1 Fantasy Baseball GameReactivate A LeagueCreate A LeagueJoin a Public LeaguePractice With a Mock DraftSports BettingAP Photo/Mike KropfMarch Madness betting 2023: Bracket odds, lines, tips, moreThe 2023 NCAA tournament brackets have finally been released, and we have everything you need to know to make a bet on all of the March Madness games. Sign up to play the #1 Fantasy game!Create A LeagueJoin Public LeagueReactivateMock Draft Now\n\nESPN+\n\n\n\n\nNHL: Select | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-8 | Public LeagueReactivateMock Draft Now\n\nESPN+\n\n\n\n\nNHL: Select Games\n\n\n\n\n\n\n\nXFL\n\n\n\n\n\n\n\nMLB: Select Games\n\n\n\n\n\n\n\nNCAA Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Games\n\n\n\n\n\n\n\nFantasy Baseball: Sign Up\n\n\n\n\n\n\n\nHow To Watch PGA TOUR\n\n\nESPN Sites\n\n\n\n\nESPN Deportes\n\n\n\n\n\n\n\nAndscape\n\n\n\n\n\n\n\nespnW\n\n\n\n\n\n\n\nESPNFC\n\n\n\n\n\n\n\nX Games\n\n\n\n\n\n\n\nSEC Network\n\n\nESPN Apps\n\n\n\n\nESPN\n\n\n\n\n\n\n\nESPN Fantasy\n\n\nFollow ESPN\n\n\n\n\nFacebook\n\n\n\n\n\n\n\nTwitter\n\n\n\n\n\n\n\nInstagram\n\n\n\n\n\n\n\nSnapchat\n\n\n\n\n\n\n\nYouTube\n\n\n\n\n\n\n\nThe ESPN Daily Podcast\n\n\nTerms of UsePrivacy PolicyYour US State Privacy RightsChildren's Online Privacy PolicyInterest-Based AdsAbout Nielsen MeasurementDo Not Sell or Share My Personal InformationContact UsDisney Ad Sales SiteWork for ESPNCopyright: © ESPN Enterprises, Inc. All rights reserved.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", lookup_str='', | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-9 | lookup_str='', metadata={'source': 'https://www.espn.com/'}, lookup_index=0)]"""# Use this piece of code for testing new custom BeautifulSoup parsersimport requestsfrom bs4 import BeautifulSouphtml_doc = requests.get("{INSERT_NEW_URL_HERE}")soup = BeautifulSoup(html_doc.text, 'html.parser')# Beautiful soup logic to be exported to langchain.document_loaders.webpage.py# Example: transcript = soup.select_one("td[class='scrtext']").text# BS4 documentation can be found here: https://www.crummy.com/software/BeautifulSoup/bs4/doc/""";Loading multiple webpages​You can also load multiple webpages at once by passing in a list of urls to the loader. This will return a list of documents in the same order as the urls passed in.loader = WebBaseLoader(["https://www.espn.com/", "https://google.com"])docs = loader.load()docs [Document(page_content="\n\n\n\n\n\n\n\n\nESPN - Serving Sports Fans. Anytime. Anywhere.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n Skip to main content\n \n\n Skip to navigation\n | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-10 | \n\n Skip to navigation\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<\n\n>\n\n\n\n\n\n\n\n\n\nMenuESPN\n\n\nSearch\n\n\n\nscores\n\n\n\nNFLNBANCAAMNCAAWNHLSoccer…MLBNCAAFGolfTennisSports BettingBoxingCFLNCAACricketF1HorseLLWSMMANASCARNBA G LeagueOlympic SportsRacingRN BBRN FBRugbyWNBAWorld Baseball ClassicWWEX GamesXFLMore ESPNFantasyListenWatchESPN+\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\nSUBSCRIBE NOW\n\n\n\n\n\nNHL: Select Games\n\n\n\n\n\n\n\nXFL\n\n\n\n\n\n\n\nMLB: Select Games\n\n\n\n\n\n\n\nNCAA Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Games\n\n\n\n\n\n\n\nFantasy Baseball: Sign Up\n\n\n\n\n\n\n\nHow To Watch PGA TOUR\n\n\n\n\n\n\nFavorites\n\n\n\n\n\n\n Manage Favorites\n \n\n\n\nCustomize ESPNSign UpLog InESPN | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-11 | \n\n\n\nCustomize ESPNSign UpLog InESPN Sites\n\n\n\n\nESPN Deportes\n\n\n\n\n\n\n\nAndscape\n\n\n\n\n\n\n\nespnW\n\n\n\n\n\n\n\nESPNFC\n\n\n\n\n\n\n\nX Games\n\n\n\n\n\n\n\nSEC Network\n\n\nESPN Apps\n\n\n\n\nESPN\n\n\n\n\n\n\n\nESPN Fantasy\n\n\nFollow ESPN\n\n\n\n\nFacebook\n\n\n\n\n\n\n\nTwitter\n\n\n\n\n\n\n\nInstagram\n\n\n\n\n\n\n\nSnapchat\n\n\n\n\n\n\n\nYouTube\n\n\n\n\n\n\n\nThe ESPN Daily Podcast\n\n\nAre you ready for Opening Day? Here's your guide to MLB's offseason chaosWait, Jacob deGrom is on the Rangers now? Xander Bogaerts and Trea Turner signed where? And what about Carlos Correa? Yeah, you're going to need to read up before Opening Day.12hESPNIllustration by ESPNEverything you missed in the MLB offseason3h2:33World Series odds, win totals, props for every teamPlay fantasy baseball for free!TOP HEADLINESQB Jackson has requested trade from RavensSources: Texas hiring Terry as full-time coachJets GM: No rush on Rodgers; Lamar not optionLove to leave North Carolina, enter transfer portalBelichick to angsty Pats fans: See last 25 yearsEmbiid out, Harden due back vs. Jokic, NuggetsLynch: Purdy 'earned the right' to start for NinersMan Utd, Wrexham plan July friendly in San DiegoOn paper, Padres overtake DodgersLAMAR WANTS OUT OF BALTIMOREMarcus Spears identifies the two teams that need Lamar Jackson the most7h2:00Would Lamar sit | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-12 | Spears identifies the two teams that need Lamar Jackson the most7h2:00Would Lamar sit out? Will Ravens draft a QB? Jackson trade request insightsLamar Jackson has asked Baltimore to trade him, but Ravens coach John Harbaugh hopes the QB will be back.3hJamison HensleyBallard, Colts will consider trading for QB JacksonJackson to Indy? Washington? Barnwell ranks the QB's trade fitsSNYDER'S TUMULTUOUS 24-YEAR RUNHow Washington’s NFL franchise sank on and off the field under owner Dan SnyderSnyder purchased one of the NFL's marquee franchises in 1999. Twenty-four years later, and with the team up for sale, he leaves a legacy of on-field futility and off-field scandal.13hJohn KeimESPNIOWA STAR STEPS UP AGAINJ-Will: Caitlin Clark is the biggest brand in college sports right now8h0:47'The better the opponent, the better she plays': Clark draws comparisons to TaurasiCaitlin Clark's performance on Sunday had longtime observers going back decades to find comparisons.16hKevin PeltonWOMEN'S ELITE EIGHT SCOREBOARDMONDAY'S GAMESCheck your bracket!NBA DRAFTHow top prospects fared on the road to the Final FourThe 2023 NCAA tournament is down to four teams, and ESPN's Jonathan Givony recaps the players who saw their NBA draft stock change.11hJonathan GivonyAndy Lyons/Getty ImagesTALKING BASKETBALLWhy AD needs to be more assertive with LeBron on the court9h1:33Why Perk won't blame Kyrie for Mavs' woes8h1:48WHERE EVERY TEAM STANDSNew NFL Power Rankings: Post-free-agency 1-32 poll, plus underrated offseason movesThe free agent frenzy has come and gone. Which teams have improved their 2023 outlook, | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-13 | movesThe free agent frenzy has come and gone. Which teams have improved their 2023 outlook, and which teams have taken a hit?12hNFL Nation reportersIllustration by ESPNTHE BUCK STOPS WITH BELICHICKBruschi: Fair to criticize Bill Belichick for Patriots' struggles10h1:27 Top HeadlinesQB Jackson has requested trade from RavensSources: Texas hiring Terry as full-time coachJets GM: No rush on Rodgers; Lamar not optionLove to leave North Carolina, enter transfer portalBelichick to angsty Pats fans: See last 25 yearsEmbiid out, Harden due back vs. Jokic, NuggetsLynch: Purdy 'earned the right' to start for NinersMan Utd, Wrexham plan July friendly in San DiegoOn paper, Padres overtake DodgersFavorites FantasyManage FavoritesFantasy HomeCustomize ESPNSign UpLog InMarch Madness LiveESPNMarch Madness LiveWatch every men's NCAA tournament game live! ICYMI1:42Austin Peay's coach, pitcher and catcher all ejected after retaliation pitchAustin Peay's pitcher, catcher and coach were all ejected after a pitch was thrown at Liberty's Nathan Keeter, who earlier in the game hit a home run and celebrated while running down the third-base line. Men's Tournament ChallengeIllustration by ESPNMen's Tournament ChallengeCheck your bracket(s) in the 2023 Men's Tournament Challenge, which you can follow throughout the Big Dance. Women's Tournament ChallengeIllustration by ESPNWomen's Tournament ChallengeCheck your bracket(s) in the 2023 Women's Tournament Challenge, which you can follow throughout the Big Dance. Best of ESPN+AP Photo/Lynne SladkyFantasy Baseball ESPN+ Cheat Sheet: Sleepers, busts, rookies and closersYou've read their names all preseason long, it'd be a shame to forget them on draft day. The ESPN+ Cheat Sheet is one way to make sure that doesn't | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-14 | forget them on draft day. The ESPN+ Cheat Sheet is one way to make sure that doesn't happen.Steph Chambers/Getty ImagesPassan's 2023 MLB season preview: Bold predictions and moreOpening Day is just over a week away -- and Jeff Passan has everything you need to know covered from every possible angle.Photo by Bob Kupbens/Icon Sportswire2023 NFL free agency: Best team fits for unsigned playersWhere could Ezekiel Elliott land? Let's match remaining free agents to teams and find fits for two trade candidates.Illustration by ESPN2023 NFL mock draft: Mel Kiper's first-round pick predictionsMel Kiper Jr. makes his predictions for Round 1 of the NFL draft, including projecting a trade in the top five. Trending NowAnne-Marie Sorvin-USA TODAY SBoston Bruins record tracker: Wins, points, milestonesThe B's are on pace for NHL records in wins and points, along with some individual superlatives as well. Follow along here with our updated tracker.Mandatory Credit: William Purnell-USA TODAY Sports2023 NFL full draft order: AFC, NFC team picks for all roundsStarting with the Carolina Panthers at No. 1 overall, here's the entire 2023 NFL draft broken down round by round. How to Watch on ESPN+Gregory Fisher/Icon Sportswire2023 NCAA men's hockey: Results, bracket, how to watchThe matchups in Tampa promise to be thrillers, featuring plenty of star power, high-octane offense and stellar defense.(AP Photo/Koji Sasahara, File)How to watch the PGA Tour, Masters, PGA Championship and FedEx Cup playoffs on ESPN, ESPN+Here's everything you need to know about how to watch the PGA Tour, Masters, PGA Championship and FedEx Cup playoffs on ESPN and ESPN+.Hailie Lynch/XFLHow to watch the XFL: 2023 schedule, teams, players, news, moreEvery XFL game | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-15 | the XFL: 2023 schedule, teams, players, news, moreEvery XFL game will be streamed on ESPN+. Find out when and where else you can watch the eight teams compete. Sign up to play the #1 Fantasy Baseball GameReactivate A LeagueCreate A LeagueJoin a Public LeaguePractice With a Mock DraftSports BettingAP Photo/Mike KropfMarch Madness betting 2023: Bracket odds, lines, tips, moreThe 2023 NCAA tournament brackets have finally been released, and we have everything you need to know to make a bet on all of the March Madness games. Sign up to play the #1 Fantasy game!Create A LeagueJoin Public LeagueReactivateMock Draft Now\n\nESPN+\n\n\n\n\nNHL: Select Games\n\n\n\n\n\n\n\nXFL\n\n\n\n\n\n\n\nMLB: Select Games\n\n\n\n\n\n\n\nNCAA Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Games\n\n\n\n\n\n\n\nFantasy Baseball: Sign Up\n\n\n\n\n\n\n\nHow To Watch PGA TOUR\n\n\nESPN Sites\n\n\n\n\nESPN Deportes\n\n\n\n\n\n\n\nAndscape\n\n\n\n\n\n\n\nespnW\n\n\n\n\n\n\n\nESPNFC\n\n\n\n\n\n\n\nX Games\n\n\n\n\n\n\n\nSEC Network\n\n\nESPN Apps\n\n\n\n\nESPN\n\n\n\n\n\n\n\nESPN | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-16 | Apps\n\n\n\n\nESPN\n\n\n\n\n\n\n\nESPN Fantasy\n\n\nFollow ESPN\n\n\n\n\nFacebook\n\n\n\n\n\n\n\nTwitter\n\n\n\n\n\n\n\nInstagram\n\n\n\n\n\n\n\nSnapchat\n\n\n\n\n\n\n\nYouTube\n\n\n\n\n\n\n\nThe ESPN Daily Podcast\n\n\nTerms of UsePrivacy PolicyYour US State Privacy RightsChildren's Online Privacy PolicyInterest-Based AdsAbout Nielsen MeasurementDo Not Sell or Share My Personal InformationContact UsDisney Ad Sales SiteWork for ESPNCopyright: © ESPN Enterprises, Inc. All rights reserved.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", lookup_str='', metadata={'source': 'https://www.espn.com/'}, lookup_index=0), Document(page_content='GoogleSearch Images Maps Play YouTube News Gmail Drive More »Web History | Settings | Sign in\xa0Advanced searchAdvertisingBusiness SolutionsAbout Google© 2023 - Privacy - Terms ', lookup_str='', metadata={'source': 'https://google.com'}, lookup_index=0)]Load multiple urls concurrently​You can speed up the scraping process by scraping and parsing multiple urls concurrently.There are reasonable limits to concurrent requests, defaulting to 2 per second. If you aren't concerned about being a good citizen, or you control the server you are scraping and don't care about load, you can change the requests_per_second parameter to increase the max concurrent requests. Note, while this will speed up the scraping process, but may cause the server to block you. Be careful!pip install nest_asyncio# fixes a bug with asyncio and jupyterimport nest_asyncionest_asyncio.apply() Requirement already satisfied: nest_asyncio in | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-17 | nest_asyncionest_asyncio.apply() Requirement already satisfied: nest_asyncio in /Users/harrisonchase/.pyenv/versions/3.9.1/envs/langchain/lib/python3.9/site-packages (1.5.6)loader = WebBaseLoader(["https://www.espn.com/", "https://google.com"])loader.requests_per_second = 1docs = loader.aload()docs [Document(page_content="\n\n\n\n\n\n\n\n\nESPN - Serving Sports Fans. Anytime. Anywhere.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n Skip to main content\n \n\n Skip to navigation\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<\n\n>\n\n\n\n\n\n\n\n\n\nMenuESPN\n\n\nSearch\n\n\n\nscores\n\n\n\nNFLNBANCAAMNCAAWNHLSoccer…MLBNCAAFGolfTennisSports BettingBoxingCFLNCAACricketF1HorseLLWSMMANASCARNBA G LeagueOlympic SportsRacingRN BBRN FBRugbyWNBAWorld Baseball ClassicWWEX GamesXFLMore | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-18 | BBRN FBRugbyWNBAWorld Baseball ClassicWWEX GamesXFLMore ESPNFantasyListenWatchESPN+\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\nSUBSCRIBE NOW\n\n\n\n\n\nNHL: Select Games\n\n\n\n\n\n\n\nXFL\n\n\n\n\n\n\n\nMLB: Select Games\n\n\n\n\n\n\n\nNCAA Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Games\n\n\n\n\n\n\n\nFantasy Baseball: Sign Up\n\n\n\n\n\n\n\nHow To Watch PGA TOUR\n\n\n\n\n\n\nFavorites\n\n\n\n\n\n\n Manage Favorites\n \n\n\n\nCustomize ESPNSign UpLog InESPN Sites\n\n\n\n\nESPN Deportes\n\n\n\n\n\n\n\nAndscape\n\n\n\n\n\n\n\nespnW\n\n\n\n\n\n\n\nESPNFC\n\n\n\n\n\n\n\nX Games\n\n\n\n\n\n\n\nSEC Network\n\n\nESPN Apps\n\n\n\n\nESPN\n\n\n\n\n\n\n\nESPN Fantasy\n\n\nFollow ESPN\n\n\n\n\nFacebook\n\n\n\n\n\n\n\nTwitter\n\n\n\n\n\n\n\nInstagram\n\n\n\n\n\n\n\nSnapchat\n\n\n\n\n\n\n\nYouTube\n\n\n\n\n\n\n\nThe ESPN Daily | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-19 | ESPN Daily Podcast\n\n\nAre you ready for Opening Day? Here's your guide to MLB's offseason chaosWait, Jacob deGrom is on the Rangers now? Xander Bogaerts and Trea Turner signed where? And what about Carlos Correa? Yeah, you're going to need to read up before Opening Day.12hESPNIllustration by ESPNEverything you missed in the MLB offseason3h2:33World Series odds, win totals, props for every teamPlay fantasy baseball for free!TOP HEADLINESQB Jackson has requested trade from RavensSources: Texas hiring Terry as full-time coachJets GM: No rush on Rodgers; Lamar not optionLove to leave North Carolina, enter transfer portalBelichick to angsty Pats fans: See last 25 yearsEmbiid out, Harden due back vs. Jokic, NuggetsLynch: Purdy 'earned the right' to start for NinersMan Utd, Wrexham plan July friendly in San DiegoOn paper, Padres overtake DodgersLAMAR WANTS OUT OF BALTIMOREMarcus Spears identifies the two teams that need Lamar Jackson the most7h2:00Would Lamar sit out? Will Ravens draft a QB? Jackson trade request insightsLamar Jackson has asked Baltimore to trade him, but Ravens coach John Harbaugh hopes the QB will be back.3hJamison HensleyBallard, Colts will consider trading for QB JacksonJackson to Indy? Washington? Barnwell ranks the QB's trade fitsSNYDER'S TUMULTUOUS 24-YEAR RUNHow Washington’s NFL franchise sank on and off the field under owner Dan SnyderSnyder purchased one of the NFL's marquee franchises in 1999. Twenty-four years later, and with the team up for sale, he leaves a legacy of on-field futility and off-field scandal.13hJohn KeimESPNIOWA STAR STEPS UP AGAINJ-Will: | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-20 | scandal.13hJohn KeimESPNIOWA STAR STEPS UP AGAINJ-Will: Caitlin Clark is the biggest brand in college sports right now8h0:47'The better the opponent, the better she plays': Clark draws comparisons to TaurasiCaitlin Clark's performance on Sunday had longtime observers going back decades to find comparisons.16hKevin PeltonWOMEN'S ELITE EIGHT SCOREBOARDMONDAY'S GAMESCheck your bracket!NBA DRAFTHow top prospects fared on the road to the Final FourThe 2023 NCAA tournament is down to four teams, and ESPN's Jonathan Givony recaps the players who saw their NBA draft stock change.11hJonathan GivonyAndy Lyons/Getty ImagesTALKING BASKETBALLWhy AD needs to be more assertive with LeBron on the court9h1:33Why Perk won't blame Kyrie for Mavs' woes8h1:48WHERE EVERY TEAM STANDSNew NFL Power Rankings: Post-free-agency 1-32 poll, plus underrated offseason movesThe free agent frenzy has come and gone. Which teams have improved their 2023 outlook, and which teams have taken a hit?12hNFL Nation reportersIllustration by ESPNTHE BUCK STOPS WITH BELICHICKBruschi: Fair to criticize Bill Belichick for Patriots' struggles10h1:27 Top HeadlinesQB Jackson has requested trade from RavensSources: Texas hiring Terry as full-time coachJets GM: No rush on Rodgers; Lamar not optionLove to leave North Carolina, enter transfer portalBelichick to angsty Pats fans: See last 25 yearsEmbiid out, Harden due back vs. Jokic, NuggetsLynch: Purdy 'earned the right' to start for NinersMan Utd, Wrexham plan July friendly in San DiegoOn paper, Padres overtake DodgersFavorites FantasyManage FavoritesFantasy | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-21 | plan July friendly in San DiegoOn paper, Padres overtake DodgersFavorites FantasyManage FavoritesFantasy HomeCustomize ESPNSign UpLog InMarch Madness LiveESPNMarch Madness LiveWatch every men's NCAA tournament game live! ICYMI1:42Austin Peay's coach, pitcher and catcher all ejected after retaliation pitchAustin Peay's pitcher, catcher and coach were all ejected after a pitch was thrown at Liberty's Nathan Keeter, who earlier in the game hit a home run and celebrated while running down the third-base line. Men's Tournament ChallengeIllustration by ESPNMen's Tournament ChallengeCheck your bracket(s) in the 2023 Men's Tournament Challenge, which you can follow throughout the Big Dance. Women's Tournament ChallengeIllustration by ESPNWomen's Tournament ChallengeCheck your bracket(s) in the 2023 Women's Tournament Challenge, which you can follow throughout the Big Dance. Best of ESPN+AP Photo/Lynne SladkyFantasy Baseball ESPN+ Cheat Sheet: Sleepers, busts, rookies and closersYou've read their names all preseason long, it'd be a shame to forget them on draft day. The ESPN+ Cheat Sheet is one way to make sure that doesn't happen.Steph Chambers/Getty ImagesPassan's 2023 MLB season preview: Bold predictions and moreOpening Day is just over a week away -- and Jeff Passan has everything you need to know covered from every possible angle.Photo by Bob Kupbens/Icon Sportswire2023 NFL free agency: Best team fits for unsigned playersWhere could Ezekiel Elliott land? Let's match remaining free agents to teams and find fits for two trade candidates.Illustration by ESPN2023 NFL mock draft: Mel Kiper's first-round pick predictionsMel Kiper Jr. makes his predictions for Round 1 of the NFL draft, including projecting a trade in the top five. Trending NowAnne-Marie Sorvin-USA TODAY SBoston Bruins record tracker: Wins, points, | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-22 | NowAnne-Marie Sorvin-USA TODAY SBoston Bruins record tracker: Wins, points, milestonesThe B's are on pace for NHL records in wins and points, along with some individual superlatives as well. Follow along here with our updated tracker.Mandatory Credit: William Purnell-USA TODAY Sports2023 NFL full draft order: AFC, NFC team picks for all roundsStarting with the Carolina Panthers at No. 1 overall, here's the entire 2023 NFL draft broken down round by round. How to Watch on ESPN+Gregory Fisher/Icon Sportswire2023 NCAA men's hockey: Results, bracket, how to watchThe matchups in Tampa promise to be thrillers, featuring plenty of star power, high-octane offense and stellar defense.(AP Photo/Koji Sasahara, File)How to watch the PGA Tour, Masters, PGA Championship and FedEx Cup playoffs on ESPN, ESPN+Here's everything you need to know about how to watch the PGA Tour, Masters, PGA Championship and FedEx Cup playoffs on ESPN and ESPN+.Hailie Lynch/XFLHow to watch the XFL: 2023 schedule, teams, players, news, moreEvery XFL game will be streamed on ESPN+. Find out when and where else you can watch the eight teams compete. Sign up to play the #1 Fantasy Baseball GameReactivate A LeagueCreate A LeagueJoin a Public LeaguePractice With a Mock DraftSports BettingAP Photo/Mike KropfMarch Madness betting 2023: Bracket odds, lines, tips, moreThe 2023 NCAA tournament brackets have finally been released, and we have everything you need to know to make a bet on all of the March Madness games. Sign up to play the #1 Fantasy game!Create A LeagueJoin Public LeagueReactivateMock Draft Now\n\nESPN+\n\n\n\n\nNHL: Select | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-23 | Public LeagueReactivateMock Draft Now\n\nESPN+\n\n\n\n\nNHL: Select Games\n\n\n\n\n\n\n\nXFL\n\n\n\n\n\n\n\nMLB: Select Games\n\n\n\n\n\n\n\nNCAA Baseball\n\n\n\n\n\n\n\nNCAA Softball\n\n\n\n\n\n\n\nCricket: Select Matches\n\n\n\n\n\n\n\nMel Kiper's NFL Mock Draft 3.0\n\n\nQuick Links\n\n\n\n\nMen's Tournament Challenge\n\n\n\n\n\n\n\nWomen's Tournament Challenge\n\n\n\n\n\n\n\nNFL Draft Order\n\n\n\n\n\n\n\nHow To Watch NHL Games\n\n\n\n\n\n\n\nFantasy Baseball: Sign Up\n\n\n\n\n\n\n\nHow To Watch PGA TOUR\n\n\nESPN Sites\n\n\n\n\nESPN Deportes\n\n\n\n\n\n\n\nAndscape\n\n\n\n\n\n\n\nespnW\n\n\n\n\n\n\n\nESPNFC\n\n\n\n\n\n\n\nX Games\n\n\n\n\n\n\n\nSEC Network\n\n\nESPN Apps\n\n\n\n\nESPN\n\n\n\n\n\n\n\nESPN Fantasy\n\n\nFollow ESPN\n\n\n\n\nFacebook\n\n\n\n\n\n\n\nTwitter\n\n\n\n\n\n\n\nInstagram\n\n\n\n\n\n\n\nSnapchat\n\n\n\n\n\n\n\nYouTube\n\n\n\n\n\n\n\nThe ESPN Daily Podcast\n\n\nTerms of UsePrivacy PolicyYour US State Privacy RightsChildren's Online Privacy PolicyInterest-Based AdsAbout Nielsen MeasurementDo Not Sell or Share My Personal InformationContact UsDisney Ad Sales SiteWork for ESPNCopyright: © ESPN Enterprises, Inc. All rights reserved.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n", lookup_str='', | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-24 | lookup_str='', metadata={'source': 'https://www.espn.com/'}, lookup_index=0), Document(page_content='GoogleSearch Images Maps Play YouTube News Gmail Drive More »Web History | Settings | Sign in\xa0Advanced searchAdvertisingBusiness SolutionsAbout Google© 2023 - Privacy - Terms ', lookup_str='', metadata={'source': 'https://google.com'}, lookup_index=0)]Loading a xml file, or using a different BeautifulSoup parser​You can also look at SitemapLoader for an example of how to load a sitemap file, which is an example of using this feature.loader = WebBaseLoader( "https://www.govinfo.gov/content/pkg/CFR-2018-title10-vol3/xml/CFR-2018-title10-vol3-sec431-86.xml")loader.default_parser = "xml"docs = loader.load()docs [Document(page_content='\n\n10\nEnergy\n3\n2018-01-01\n2018-01-01\nfalse\nUniform test method for the measurement of energy efficiency of commercial packaged boilers.\n§ 431.86\nSection § 431.86\n\nEnergy\nDEPARTMENT OF ENERGY\nENERGY CONSERVATION\nENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT\nCommercial Packaged Boilers\nTest Procedures\n\n\n\n\n§\u2009431.86\nUniform test method for the measurement of energy efficiency of commercial packaged boilers.\n(a) Scope. This section provides test procedures, pursuant to the Energy Policy and Conservation Act (EPCA), as amended, which must be followed for measuring the combustion efficiency and/or thermal efficiency of a gas- or oil-fired commercial packaged boiler.\n(b) Testing and Calculations. Determine the thermal efficiency or combustion efficiency of commercial packaged boilers by conducting | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-25 | Testing and Calculations. Determine the thermal efficiency or combustion efficiency of commercial packaged boilers by conducting the appropriate test procedure(s) indicated in Table 1 of this section.\n\nTable 1—Test Requirements for Commercial Packaged Boiler Equipment Classes\n\nEquipment category\nSubcategory\nCertified rated inputBtu/h\n\nStandards efficiency metric(§\u2009431.87)\n\nTest procedure(corresponding to\nstandards efficiency\nmetric required\nby §\u2009431.87)\n\n\n\nHot Water\nGas-fired\n≥300,000 and ≤2,500,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\nHot Water\nGas-fired\n>2,500,000\nCombustion Efficiency\nAppendix A, Section 3.\n\n\nHot Water\nOil-fired\n≥300,000 and ≤2,500,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\nHot Water\nOil-fired\n>2,500,000\nCombustion Efficiency\nAppendix A, Section 3.\n\n\nSteam\nGas-fired (all*)\n≥300,000 and ≤2,500,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\nSteam\nGas-fired (all*)\n>2,500,000 and ≤5,000,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\n\u2003\n\n>5,000,000\nThermal Efficiency\nAppendix A, Section 2.OR\nAppendix A, Section 3 with Section 2.4.3.2.\n\n\n\nSteam\nOil-fired\n≥300,000 and ≤2,500,000\nThermal Efficiency\nAppendix | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-26 | and ≤2,500,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\nSteam\nOil-fired\n>2,500,000 and ≤5,000,000\nThermal Efficiency\nAppendix A, Section 2.\n\n\n\u2003\n\n>5,000,000\nThermal Efficiency\nAppendix A, Section 2.OR\nAppendix A, Section 3. with Section 2.4.3.2.\n\n\n\n*\u2009Equipment classes for commercial packaged boilers as of July 22, 2009 (74 FR 36355) distinguish between gas-fired natural draft and all other gas-fired (except natural draft).\n\n(c) Field Tests. The field test provisions of appendix A may be used only to test a unit of commercial packaged boiler with rated input greater than 5,000,000 Btu/h.\n[81 FR 89305, Dec. 9, 2016]\n\n\nEnergy Efficiency Standards\n\n', lookup_str='', metadata={'source': 'https://www.govinfo.gov/content/pkg/CFR-2018-title10-vol3/xml/CFR-2018-title10-vol3-sec431-86.xml'}, lookup_index=0)]Using proxies​Sometimes you might need to use proxies to get around IP blocks. You can pass in a dictionary of proxies to the loader (and requests underneath) to use them.loader = WebBaseLoader( "https://www.walmart.com/search?q=parrots", proxies={ "http": "http://{username}:{password}:@proxy.service.com:6666/", "https": "https://{username}:{password}:@proxy.service.com:6666/", },)docs = loader.load()PreviousWeatherNextWhatsApp ChatLoading | https://python.langchain.com/docs/integrations/document_loaders/web_base |
bbff206a39d7-27 | },)docs = loader.load()PreviousWeatherNextWhatsApp ChatLoading multiple webpagesLoad multiple urls concurrentlyLoading a xml file, or using a different BeautifulSoup parserUsing proxiesCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/web_base |
625601e8fa92-0 | Tencent COS Directory | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/tencent_cos_directory |
625601e8fa92-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersTencent COS DirectoryOn this pageTencent COS DirectoryThis covers how to load document objects from a Tencent COS Directory.#! pip install cos-python-sdk-v5from | https://python.langchain.com/docs/integrations/document_loaders/tencent_cos_directory |
625601e8fa92-2 | how to load document objects from a Tencent COS Directory.#! pip install cos-python-sdk-v5from langchain.document_loaders import TencentCOSDirectoryLoaderfrom qcloud_cos import CosConfigconf = CosConfig( Region="your cos region", SecretId="your cos secret_id", SecretKey="your cos secret_key",)loader = TencentCOSDirectoryLoader(conf=conf, bucket="you_cos_bucket")loader.load()Specifying a prefix​You can also specify a prefix for more finegrained control over what files to load.loader = TencentCOSDirectoryLoader(conf=conf, bucket="you_cos_bucket", prefix="fake")loader.load()PreviousTelegramNextTencent COS FileSpecifying a prefixCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/tencent_cos_directory |
027d318b1ed9-0 | Snowflake | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/snowflake |
027d318b1ed9-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersSnowflakeSnowflakeThis notebooks goes over how to load documents from Snowflakepip install snowflake-connector-pythonimport settings as sfrom langchain.document_loaders import | https://python.langchain.com/docs/integrations/document_loaders/snowflake |
027d318b1ed9-2 | Snowflakepip install snowflake-connector-pythonimport settings as sfrom langchain.document_loaders import SnowflakeLoaderQUERY = "select text, survey_id from CLOUD_DATA_SOLUTIONS.HAPPY_OR_NOT.OPEN_FEEDBACK limit 10"snowflake_loader = SnowflakeLoader( query=QUERY, user=s.SNOWFLAKE_USER, password=s.SNOWFLAKE_PASS, account=s.SNOWFLAKE_ACCOUNT, warehouse=s.SNOWFLAKE_WAREHOUSE, role=s.SNOWFLAKE_ROLE, database=s.SNOWFLAKE_DATABASE, schema=s.SNOWFLAKE_SCHEMA,)snowflake_documents = snowflake_loader.load()print(snowflake_documents)from snowflakeLoader import SnowflakeLoaderimport settings as sQUERY = "select text, survey_id as source from CLOUD_DATA_SOLUTIONS.HAPPY_OR_NOT.OPEN_FEEDBACK limit 10"snowflake_loader = SnowflakeLoader( query=QUERY, user=s.SNOWFLAKE_USER, password=s.SNOWFLAKE_PASS, account=s.SNOWFLAKE_ACCOUNT, warehouse=s.SNOWFLAKE_WAREHOUSE, role=s.SNOWFLAKE_ROLE, database=s.SNOWFLAKE_DATABASE, schema=s.SNOWFLAKE_SCHEMA, metadata_columns=["source"],)snowflake_documents = snowflake_loader.load()print(snowflake_documents)PreviousSlackNextSource CodeCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/snowflake |
61652410c5c9-0 | Airbyte JSON | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/airbyte_json |
61652410c5c9-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersAirbyte JSONAirbyte JSONAirbyte is a data integration platform for ELT pipelines from APIs, databases & files to warehouses & lakes. It has the largest catalog of | https://python.langchain.com/docs/integrations/document_loaders/airbyte_json |
61652410c5c9-2 | ELT pipelines from APIs, databases & files to warehouses & lakes. It has the largest catalog of ELT connectors to data warehouses and databases.This covers how to load any source from Airbyte into a local JSON file that can be read in as a documentPrereqs: | https://python.langchain.com/docs/integrations/document_loaders/airbyte_json |
61652410c5c9-3 | Have docker desktop installedSteps:1) Clone Airbyte from GitHub - git clone https://github.com/airbytehq/airbyte.git2) Switch into Airbyte directory - cd airbyte3) Start Airbyte - docker compose up4) In your browser, just visit http://localhost:8000. You will be asked for a username and password. By default, that's username airbyte and password password.5) Setup any source you wish.6) Set destination as Local JSON, with specified destination path - lets say /json_data. Set up manual sync.7) Run the connection.7) To see what files are create, you can navigate to: file:///tmp/airbyte_local8) Find your data and copy path. That path should be saved in the file variable below. It should start with /tmp/airbyte_localfrom langchain.document_loaders import AirbyteJSONLoaderls /tmp/airbyte_local/json_data/ _airbyte_raw_pokemon.jsonlloader = AirbyteJSONLoader("/tmp/airbyte_local/json_data/_airbyte_raw_pokemon.jsonl")data = loader.load()print(data[0].page_content[:500]) abilities: ability: name: blaze url: https://pokeapi.co/api/v2/ability/66/ is_hidden: False slot: 1 ability: name: solar-power url: https://pokeapi.co/api/v2/ability/94/ is_hidden: True slot: 3 base_experience: 267 forms: name: charizard url: | https://python.langchain.com/docs/integrations/document_loaders/airbyte_json |
61652410c5c9-4 | 267 forms: name: charizard url: https://pokeapi.co/api/v2/pokemon-form/6/ game_indices: game_index: 180 version: name: red url: https://pokeapi.co/api/v2/version/1/ game_index: 180 version: name: blue url: https://pokeapi.co/api/v2/version/2/ game_index: 180 version: nPreviousacreomNextAirtableCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/airbyte_json |
3b0748c45b09-0 | ReadTheDocs Documentation | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/readthedocs_documentation |
3b0748c45b09-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersReadTheDocs DocumentationReadTheDocs DocumentationRead the Docs is an open-sourced free software documentation hosting platform. It generates documentation written with the Sphinx documentation generator.This notebook covers how | https://python.langchain.com/docs/integrations/document_loaders/readthedocs_documentation |
3b0748c45b09-2 | free software documentation hosting platform. It generates documentation written with the Sphinx documentation generator.This notebook covers how to load content from HTML that was generated as part of a Read-The-Docs build.For an example of this in the wild, see here.This assumes that the HTML has already been scraped into a folder. This can be done by uncommenting and running the following command#!pip install beautifulsoup4#!wget -r -A.html -P rtdocs https://python.langchain.com/en/latest/from langchain.document_loaders import ReadTheDocsLoaderloader = ReadTheDocsLoader("rtdocs", features="html.parser")docs = loader.load()PreviousPySpark DataFrame LoaderNextRecursive URL LoaderCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/readthedocs_documentation |
807de38c5e37-0 | Google Cloud Storage File | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/google_cloud_storage_file |
807de38c5e37-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersGoogle Cloud Storage FileGoogle Cloud Storage FileGoogle Cloud Storage is a managed service for storing unstructured data.This covers how to load document objects from an Google Cloud Storage | https://python.langchain.com/docs/integrations/document_loaders/google_cloud_storage_file |
807de38c5e37-2 | a managed service for storing unstructured data.This covers how to load document objects from an Google Cloud Storage (GCS) file object (blob).# !pip install google-cloud-storagefrom langchain.document_loaders import GCSFileLoaderloader = GCSFileLoader(project_name="aist", bucket="testing-hwc", blob="fake.docx")loader.load() /Users/harrisonchase/workplace/langchain/.venv/lib/python3.10/site-packages/google/auth/_default.py:83: UserWarning: Your application has authenticated using end user credentials from Google Cloud SDK without a quota project. You might receive a "quota exceeded" or "API not enabled" error. We recommend you rerun `gcloud auth application-default login` and make sure a quota project is added. Or you can use service accounts instead. For more information about service accounts, see https://cloud.google.com/docs/authentication/ warnings.warn(_CLOUD_SDK_CREDENTIALS_WARNING) [Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': '/var/folders/y6/8_bzdg295ld6s1_97_12m4lr0000gn/T/tmp3srlf8n8/fake.docx'}, lookup_index=0)]PreviousGoogle Cloud Storage DirectoryNextGoogle DriveCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/google_cloud_storage_file |
b7e0632059b1-0 | Notion DB 1/2 | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/notion |
b7e0632059b1-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storage FileBibTeXBiliBiliBlackboardBlockchainBrave SearchBrowserlesschatgpt_loaderCollege ConfidentialConfluenceCoNLL-UCopy PasteCSVCube Semantic LayerDatadog LogsDiffbotDiscordDocugamiDuckDBEmailEmbaasEPubEverNoteexample_dataMicrosoft ExcelFacebook ChatFaunaFigmaGeopandasGitGitBookGitHubGoogle BigQueryGoogle Cloud Storage DirectoryGoogle Cloud Storage FileGoogle DriveGrobidGutenbergHacker NewsHuggingFace datasetiFixitImagesImage captionsIMSDbIuguJoplinJupyter NotebookLarkSuite (FeiShu)MastodonMediaWikiDumpMergeDocLoadermhtmlMicrosoft OneDriveMicrosoft PowerPointMicrosoft WordModern TreasuryNotion DB 1/2Notion DB 2/2ObsidianOpen Document Format (ODT)Open City DataOrg-modePandas DataFramePsychicPySpark DataFrame LoaderReadTheDocs DocumentationRecursive URL LoaderRedditRoamRocksetRSTSitemapSlackSnowflakeSource CodeSpreedlyStripeSubtitleTelegramTencent COS DirectoryTencent COS File2MarkdownTOMLTrelloTSVTwitterUnstructured FileURLWeatherWebBaseLoaderWhatsApp ChatWikipediaXMLXorbits Pandas DataFrameLoading documents from a YouTube urlYouTube transcriptsDocument transformersLLMsMemoryRetrieversText embedding modelsAgent toolkitsToolsVector storesGrouped by providerIntegrationsDocument loadersNotion DB 1/2On this pageNotion DB 1/2Notion is a collaboration platform with modified Markdown support that integrates kanban boards, tasks, | https://python.langchain.com/docs/integrations/document_loaders/notion |
b7e0632059b1-2 | is a collaboration platform with modified Markdown support that integrates kanban boards, tasks, wikis and databases. It is an all-in-one workspace for notetaking, knowledge and data management, and project and task management.This notebook covers how to load documents from a Notion database dump.In order to get this notion dump, follow these instructions:🧑 Instructions for ingesting your own dataset​Export your dataset from Notion. You can do this by clicking on the three dots in the upper right hand corner and then clicking Export.When exporting, make sure to select the Markdown & CSV format option.This will produce a .zip file in your Downloads folder. Move the .zip file into this repository.Run the following command to unzip the zip file (replace the Export... with your own file name as needed).unzip Export-d3adfe0f-3131-4bf3-8987-a52017fc1bae.zip -d Notion_DBRun the following command to ingest the data.from langchain.document_loaders import NotionDirectoryLoaderloader = NotionDirectoryLoader("Notion_DB")docs = loader.load()PreviousModern TreasuryNextNotion DB 2/2🧑 Instructions for ingesting your own datasetCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/notion |
93f00cbf5958-0 | Text embedding models | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/ |
93f00cbf5958-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsText embedding models📄� Aleph AlphaThere are two possible ways to use Aleph Alpha's semantic embeddings. If you have texts with a dissimilar structure (e.g. a Document and a Query) you would want to use asymmetric embeddings. Conversely, for texts with comparable structures, symmetric embeddings are the suggested approach.📄� AzureOpenAILet's load the OpenAI Embedding class with environment variables set to indicate to use Azure endpoints.📄� Bedrock Embeddings📄� ClarifaiClarifai is an AI Platform that provides the full AI lifecycle ranging from data exploration, data labeling, model training, evaluation, and inference.📄� CohereLet's load the Cohere Embedding class.📄� DashScopeLet's load the DashScope Embedding class.📄� DeepInfraDeepInfra is a serverless inference as a service that provides access to a variety of LLMs and embeddings models. | https://python.langchain.com/docs/integrations/text_embedding/ |
93f00cbf5958-2 | serverless inference as a service that provides access to a variety of LLMs and embeddings models. This notebook goes over how to use LangChain with DeepInfra for text embeddings.📄� ElasticsearchWalkthrough of how to generate embeddings using a hosted embedding model in Elasticsearch📄� Embaasembaas is a fully managed NLP API service that offers features like embedding generation, document text extraction, document to embeddings and more. You can choose a variety of pre-trained models.📄� Fake EmbeddingsLangChain also provides a fake embedding class. You can use this to test your pipelines.📄� Google Cloud Platform Vertex AI PaLMNote: This is seperate from the Google PaLM integration. Google has chosen to offer an enterprise version of PaLM through GCP, and this supports the models made available through there.📄� GPT4AllThis notebook explains how to use GPT4All embeddings with LangChain.📄� Hugging Face HubLet's load the Hugging Face Embedding class.📄� InstructEmbeddingsLet's load the HuggingFace instruct Embeddings class.📄� JinaLet's load the Jina Embedding class.📄� Llama-cppThis notebook goes over how to use Llama-cpp embeddings within LangChain📄� LocalAILet's load the LocalAI Embedding class. In order to use the LocalAI Embedding class, you need to have the LocalAI service hosted somewhere and configure the embedding models. See the documentation at https//localai.io/features/embeddings/index.html.📄� MiniMaxMiniMax offers an embeddings | https://python.langchain.com/docs/integrations/text_embedding/ |
93f00cbf5958-3 | MiniMaxMiniMax offers an embeddings service.📄� ModelScopeLet's load the ModelScope Embedding class.📄� MosaicML embeddingsMosaicML offers a managed inference service. You can either use a variety of open source models, or deploy your own.📄� NLP CloudNLP Cloud is an artificial intelligence platform that allows you to use the most advanced AI engines, and even train your own engines with your own data.📄� OpenAILet's load the OpenAI Embedding class.📄� SageMaker Endpoint EmbeddingsLet's load the SageMaker Endpoints Embeddings class. The class can be used if you host, e.g. your own Hugging Face model on SageMaker.📄� Self Hosted EmbeddingsLet's load the SelfHostedEmbeddings, SelfHostedHuggingFaceEmbeddings, and SelfHostedHuggingFaceInstructEmbeddings classes.📄� Sentence Transformers EmbeddingsSentenceTransformers embeddings are called using the HuggingFaceEmbeddings integration. We have also added an alias for SentenceTransformerEmbeddings for users who are more familiar with directly using that package.📄� Spacy EmbeddingLoading the Spacy embedding class to generate and query embeddings📄� TensorflowHubLet's load the TensorflowHub Embedding class.PreviousZepNextAleph AlphaCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/ |
7f75c48da089-0 | ModelScope | 🦜�🔗 Langchain
Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsModelScopeModelScopeLet's load the ModelScope Embedding class.from langchain.embeddings import ModelScopeEmbeddingsmodel_id = "damo/nlp_corom_sentence-embedding_english-base"embeddings = ModelScopeEmbeddings(model_id=model_id)text = "This is a test document."query_result = embeddings.embed_query(text)doc_results = embeddings.embed_documents(["foo"])PreviousMiniMaxNextMosaicML embeddingsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/modelscope_hub |
cd8afa214586-0 | DashScope | 🦜�🔗 Langchain
Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsDashScopeDashScopeLet's load the DashScope Embedding class.from langchain.embeddings import DashScopeEmbeddingsembeddings = DashScopeEmbeddings( model="text-embedding-v1", dashscope_api_key="your-dashscope-api-key")text = "This is a test document."query_result = embeddings.embed_query(text)print(query_result)doc_results = embeddings.embed_documents(["foo"])print(doc_results)PreviousCohereNextDeepInfraCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/dashscope |
272032ebc7ff-0 | MosaicML embeddings | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/mosaicml |
272032ebc7ff-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsMosaicML embeddingsMosaicML embeddingsMosaicML offers a managed inference service. You can either use a variety of open source models, or deploy your own.This example goes over how to use LangChain to interact with MosaicML Inference for text embedding.# sign up for an account: https://forms.mosaicml.com/demo?utm_source=langchainfrom getpass import getpassMOSAICML_API_TOKEN = getpass()import osos.environ["MOSAICML_API_TOKEN"] = MOSAICML_API_TOKENfrom langchain.embeddings import MosaicMLInstructorEmbeddingsembeddings = MosaicMLInstructorEmbeddings( query_instruction="Represent the query for retrieval: ")query_text = "This is a test query."query_result = embeddings.embed_query(query_text)document_text = "This is a test document."document_result = embeddings.embed_documents([document_text])import numpy as npquery_numpy = np.array(query_result)document_numpy = np.array(document_result[0])similarity = np.dot(query_numpy, document_numpy) / ( np.linalg.norm(query_numpy) * | https://python.langchain.com/docs/integrations/text_embedding/mosaicml |
272032ebc7ff-2 | np.dot(query_numpy, document_numpy) / ( np.linalg.norm(query_numpy) * np.linalg.norm(document_numpy))print(f"Cosine similarity between document and query: {similarity}")PreviousModelScopeNextNLP CloudCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/mosaicml |
b5d7b7bc9874-0 | Spacy Embedding | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/spacy_embedding |
b5d7b7bc9874-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsSpacy EmbeddingOn this pageSpacy EmbeddingLoading the Spacy embedding class to generate and query embeddings​Import the necessary classes​from langchain.embeddings.spacy_embeddings import SpacyEmbeddingsInitialize SpacyEmbeddings.This will load the Spacy model into memory.​embedder = SpacyEmbeddings()Define some example texts . These could be any documents that you want to analyze - for example, news articles, social media posts, or product reviews.​texts = [ "The quick brown fox jumps over the lazy dog.", "Pack my box with five dozen liquor jugs.", "How vexingly quick daft zebras jump!", "Bright vixens jump; dozy fowl quack.",]Generate and print embeddings for the texts . The SpacyEmbeddings class generates an embedding for each document, which is a numerical representation of the document's content. These embeddings can be used for various natural language processing tasks, such as document similarity comparison or text classification.​embeddings = | https://python.langchain.com/docs/integrations/text_embedding/spacy_embedding |
b5d7b7bc9874-2 | language processing tasks, such as document similarity comparison or text classification.​embeddings = embedder.embed_documents(texts)for i, embedding in enumerate(embeddings): print(f"Embedding for document {i+1}: {embedding}")Generate and print an embedding for a single piece of text. You can also generate an embedding for a single piece of text, such as a search query. This can be useful for tasks like information retrieval, where you want to find documents that are similar to a given query.​query = "Quick foxes and lazy dogs."query_embedding = embedder.embed_query(query)print(f"Embedding for query: {query_embedding}")PreviousSentence Transformers EmbeddingsNextTensorflowHubLoading the Spacy embedding class to generate and query embeddingsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/spacy_embedding |
d7b9b35b17ed-0 | Self Hosted Embeddings | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/self-hosted |
d7b9b35b17ed-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsSelf Hosted EmbeddingsSelf Hosted EmbeddingsLet's load the SelfHostedEmbeddings, SelfHostedHuggingFaceEmbeddings, and SelfHostedHuggingFaceInstructEmbeddings classes.from langchain.embeddings import ( SelfHostedEmbeddings, SelfHostedHuggingFaceEmbeddings, SelfHostedHuggingFaceInstructEmbeddings,)import runhouse as rh# For an on-demand A100 with GCP, Azure, or Lambdagpu = rh.cluster(name="rh-a10x", instance_type="A100:1", use_spot=False)# For an on-demand A10G with AWS (no single A100s on AWS)# gpu = rh.cluster(name='rh-a10x', instance_type='g5.2xlarge', provider='aws')# For an existing cluster# gpu = rh.cluster(ips=['<ip of the cluster>'],# ssh_creds={'ssh_user': '...', 'ssh_private_key':'<path_to_key>'},# | https://python.langchain.com/docs/integrations/text_embedding/self-hosted |
d7b9b35b17ed-2 | 'ssh_private_key':'<path_to_key>'},# name='my-cluster')embeddings = SelfHostedHuggingFaceEmbeddings(hardware=gpu)text = "This is a test document."query_result = embeddings.embed_query(text)And similarly for SelfHostedHuggingFaceInstructEmbeddings:embeddings = SelfHostedHuggingFaceInstructEmbeddings(hardware=gpu)Now let's load an embedding model with a custom load function:def get_pipeline(): from transformers import ( AutoModelForCausalLM, AutoTokenizer, pipeline, ) # Must be inside the function in notebooks model_id = "facebook/bart-base" tokenizer = AutoTokenizer.from_pretrained(model_id) model = AutoModelForCausalLM.from_pretrained(model_id) return pipeline("feature-extraction", model=model, tokenizer=tokenizer)def inference_fn(pipeline, prompt): # Return last hidden state of the model if isinstance(prompt, list): return [emb[0][-1] for emb in pipeline(prompt)] return pipeline(prompt)[0][-1]embeddings = SelfHostedEmbeddings( model_load_fn=get_pipeline, hardware=gpu, model_reqs=["./", "torch", "transformers"], inference_fn=inference_fn,)query_result = embeddings.embed_query(text)PreviousSageMaker Endpoint EmbeddingsNextSentence Transformers EmbeddingsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/self-hosted |
edc8c55eae02-0 | GPT4All | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/gpt4all |
edc8c55eae02-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsGPT4AllGPT4AllThis notebook explains how to use GPT4All embeddings with LangChain.pip install gpt4allfrom langchain.embeddings import GPT4AllEmbeddingsgpt4all_embd = GPT4AllEmbeddings() 100%|████████████████████████| 45.5M/45.5M [00:02<00:00, 18.5MiB/s] Model downloaded at: /Users/rlm/.cache/gpt4all/ggml-all-MiniLM-L6-v2-f16.bin objc[45711]: Class GGMLMetalClass is implemented in both | https://python.langchain.com/docs/integrations/text_embedding/gpt4all |
edc8c55eae02-2 | objc[45711]: Class GGMLMetalClass is implemented in both /Users/rlm/anaconda3/envs/lcn2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libreplit-mainline-metal.dylib (0x29fe18208) and /Users/rlm/anaconda3/envs/lcn2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libllamamodel-mainline-metal.dylib (0x2a0244208). One of the two will be used. Which one is undefined.text = "This is a test document."query_result = gpt4all_embd.embed_query(text)doc_result = gpt4all_embd.embed_documents([text])PreviousGoogle Cloud Platform Vertex AI PaLMNextHugging Face HubCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/gpt4all |
ec7469f964bc-0 | TensorflowHub | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/tensorflowhub |
ec7469f964bc-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsTensorflowHubTensorflowHubLet's load the TensorflowHub Embedding class.from langchain.embeddings import TensorflowHubEmbeddingsembeddings = TensorflowHubEmbeddings() 2023-01-30 23:53:01.652176: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. 2023-01-30 23:53:34.362802: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.text = "This is a test document."query_result = embeddings.embed_query(text)doc_results = embeddings.embed_documents(["foo"])doc_resultsPreviousSpacy | https://python.langchain.com/docs/integrations/text_embedding/tensorflowhub |
ec7469f964bc-2 | = embeddings.embed_query(text)doc_results = embeddings.embed_documents(["foo"])doc_resultsPreviousSpacy EmbeddingNextAgent toolkitsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/tensorflowhub |
f3c8033a28da-0 | Cohere | 🦜�🔗 Langchain
Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsCohereCohereLet's load the Cohere Embedding class.from langchain.embeddings import CohereEmbeddingsembeddings = CohereEmbeddings(cohere_api_key=cohere_api_key)text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text])PreviousClarifaiNextDashScopeCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/cohere |
020ac1aeae44-0 | OpenAI | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/openai |
020ac1aeae44-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsOpenAIOpenAILet's load the OpenAI Embedding class.from langchain.embeddings import OpenAIEmbeddingsembeddings = OpenAIEmbeddings()text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text])Let's load the OpenAI Embedding class with first generation models (e.g. text-search-ada-doc-001/text-search-ada-query-001). Note: These are not recommended models - see herefrom langchain.embeddings.openai import OpenAIEmbeddingsembeddings = OpenAIEmbeddings()text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text])# if you are behind an explicit proxy, you can use the OPENAI_PROXY environment variable to pass throughos.environ["OPENAI_PROXY"] = "http://proxy.yourcompany.com:8080"PreviousNLP CloudNextSageMaker Endpoint EmbeddingsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/openai |
fe50b6637f03-0 | Elasticsearch | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/elasticsearch |
fe50b6637f03-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsElasticsearchOn this pageElasticsearchWalkthrough of how to generate embeddings using a hosted embedding model in ElasticsearchThe easiest way to instantiate the ElasticsearchEmbeddings class it eitherusing the from_credentials constructor if you are using Elastic Cloudor using the from_es_connection constructor with any Elasticsearch clusterpip -q install elasticsearch langchainimport elasticsearchfrom langchain.embeddings.elasticsearch import ElasticsearchEmbeddings# Define the model IDmodel_id = "your_model_id"Testing with from_credentials​This required an Elastic Cloud cloud_id# Instantiate ElasticsearchEmbeddings using credentialsembeddings = ElasticsearchEmbeddings.from_credentials( model_id, es_cloud_id="your_cloud_id", es_user="your_user", es_password="your_password",)# Create embeddings for multiple documentsdocuments = [ "This is an example document.", "Another example document to generate embeddings for.",]document_embeddings = embeddings.embed_documents(documents)# Print document embeddingsfor i, embedding in enumerate(document_embeddings): print(f"Embedding for document {i+1}: {embedding}")# Create an embedding for a single | https://python.langchain.com/docs/integrations/text_embedding/elasticsearch |
fe50b6637f03-2 | for document {i+1}: {embedding}")# Create an embedding for a single queryquery = "This is a single query."query_embedding = embeddings.embed_query(query)# Print query embeddingprint(f"Embedding for query: {query_embedding}")Testing with Existing Elasticsearch client connection​This can be used with any Elasticsearch deployment# Create Elasticsearch connectiones_connection = Elasticsearch( hosts=["https://es_cluster_url:port"], basic_auth=("user", "password"))# Instantiate ElasticsearchEmbeddings using es_connectionembeddings = ElasticsearchEmbeddings.from_es_connection( model_id, es_connection,)# Create embeddings for multiple documentsdocuments = [ "This is an example document.", "Another example document to generate embeddings for.",]document_embeddings = embeddings.embed_documents(documents)# Print document embeddingsfor i, embedding in enumerate(document_embeddings): print(f"Embedding for document {i+1}: {embedding}")# Create an embedding for a single queryquery = "This is a single query."query_embedding = embeddings.embed_query(query)# Print query embeddingprint(f"Embedding for query: {query_embedding}")PreviousDeepInfraNextEmbaasTesting with from_credentialsTesting with Existing Elasticsearch client connectionCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/elasticsearch |
78faee2fd576-0 | LocalAI | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/localai |
78faee2fd576-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsLocalAILocalAILet's load the LocalAI Embedding class. In order to use the LocalAI Embedding class, you need to have the LocalAI service hosted somewhere and configure the embedding models. See the documentation at https://localai.io/basics/getting_started/index.html and https://localai.io/features/embeddings/index.html.from langchain.embeddings import LocalAIEmbeddingsembeddings = LocalAIEmbeddings(openai_api_base="http://localhost:8080", model="embedding-model-name")text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text])Let's load the LocalAI Embedding class with first generation models (e.g. text-search-ada-doc-001/text-search-ada-query-001). Note: These are not recommended models - see herefrom langchain.embeddings.openai import LocalAIEmbeddingsembeddings = LocalAIEmbeddings(openai_api_base="http://localhost:8080", model="embedding-model-name")text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = | https://python.langchain.com/docs/integrations/text_embedding/localai |
78faee2fd576-2 | = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text])# if you are behind an explicit proxy, you can use the OPENAI_PROXY environment variable to pass throughos.environ["OPENAI_PROXY"] = "http://proxy.yourcompany.com:8080"PreviousLlama-cppNextMiniMaxCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/localai |
a4b7051e250c-0 | SageMaker Endpoint Embeddings | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/sagemaker-endpoint |
a4b7051e250c-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsSageMaker Endpoint EmbeddingsSageMaker Endpoint EmbeddingsLet's load the SageMaker Endpoints Embeddings class. The class can be used if you host, e.g. your own Hugging Face model on SageMaker.For instructions on how to do this, please see here. Note: In order to handle batched requests, you will need to adjust the return line in the predict_fn() function within the custom inference.py script:Change fromreturn {"vectors": sentence_embeddings[0].tolist()}to:return {"vectors": sentence_embeddings.tolist()}.pip3 install langchain boto3from typing import Dict, Listfrom langchain.embeddings import SagemakerEndpointEmbeddingsfrom langchain.embeddings.sagemaker_endpoint import EmbeddingsContentHandlerimport jsonclass ContentHandler(EmbeddingsContentHandler): content_type = "application/json" accepts = "application/json" def transform_input(self, inputs: list[str], model_kwargs: Dict) -> bytes: input_str = json.dumps({"inputs": inputs, **model_kwargs}) return | https://python.langchain.com/docs/integrations/text_embedding/sagemaker-endpoint |
a4b7051e250c-2 | = json.dumps({"inputs": inputs, **model_kwargs}) return input_str.encode("utf-8") def transform_output(self, output: bytes) -> List[List[float]]: response_json = json.loads(output.read().decode("utf-8")) return response_json["vectors"]content_handler = ContentHandler()embeddings = SagemakerEndpointEmbeddings( # endpoint_name="endpoint-name", # credentials_profile_name="credentials-profile-name", endpoint_name="huggingface-pytorch-inference-2023-03-21-16-14-03-834", region_name="us-east-1", content_handler=content_handler,)query_result = embeddings.embed_query("foo")doc_results = embeddings.embed_documents(["foo"])doc_resultsPreviousOpenAINextSelf Hosted EmbeddingsCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/sagemaker-endpoint |
33799375335e-0 | Bedrock Embeddings | 🦜�🔗 Langchain
Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsBedrock EmbeddingsBedrock Embeddings%pip install boto3from langchain.embeddings import BedrockEmbeddingsembeddings = BedrockEmbeddings( credentials_profile_name="bedrock-admin", endpoint_url="custom_endpoint_url")embeddings.embed_query("This is a content of the document")embeddings.embed_documents(["This is a content of the document"])PreviousAzureOpenAINextClarifaiCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/bedrock |
7d1d79bb5367-0 | Google Cloud Platform Vertex AI PaLM | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/google_vertex_ai_palm |
7d1d79bb5367-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsGoogle Cloud Platform Vertex AI PaLMGoogle Cloud Platform Vertex AI PaLMNote: This is seperate from the Google PaLM integration. Google has chosen to offer an enterprise version of PaLM through GCP, and this supports the models made available through there. PaLM API on Vertex AI is a Preview offering, subject to the Pre-GA Offerings Terms of the GCP Service Specific Terms. Pre-GA products and features may have limited support, and changes to pre-GA products and features may not be compatible with other pre-GA versions. For more information, see the launch stage descriptions. Further, by using PaLM API on Vertex AI, you agree to the Generative AI Preview terms and conditions (Preview Terms).For PaLM API on Vertex AI, you can process personal data as outlined in the Cloud Data Processing Addendum, subject to applicable restrictions and obligations in the Agreement (as defined in the Preview Terms).To use Vertex AI PaLM you must have the google-cloud-aiplatform Python package installed and either:Have credentials configured for your environment (gcloud, workload identity, etc...)Store the path to a service account JSON file as the | https://python.langchain.com/docs/integrations/text_embedding/google_vertex_ai_palm |
7d1d79bb5367-2 | (gcloud, workload identity, etc...)Store the path to a service account JSON file as the GOOGLE_APPLICATION_CREDENTIALS environment variableThis codebase uses the google.auth library which first looks for the application credentials variable mentioned above, and then looks for system-level auth.For more information, see: https://cloud.google.com/docs/authentication/application-default-credentials#GAChttps://googleapis.dev/python/google-auth/latest/reference/google.auth.html#module-google.auth#!pip install google-cloud-aiplatformfrom langchain.embeddings import VertexAIEmbeddingsembeddings = VertexAIEmbeddings()text = "This is a test document."query_result = embeddings.embed_query(text)doc_result = embeddings.embed_documents([text])PreviousFake EmbeddingsNextGPT4AllCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/google_vertex_ai_palm |
2dca2eb92c23-0 | Aleph Alpha | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/aleph_alpha |
2dca2eb92c23-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsAleph AlphaOn this pageAleph AlphaThere are two possible ways to use Aleph Alpha's semantic embeddings. If you have texts with a dissimilar structure (e.g. a Document and a Query) you would want to use asymmetric embeddings. Conversely, for texts with comparable structures, symmetric embeddings are the suggested approach.Asymmetric​from langchain.embeddings import AlephAlphaAsymmetricSemanticEmbeddingdocument = "This is a content of the document"query = "What is the contnt of the document?"embeddings = AlephAlphaAsymmetricSemanticEmbedding()doc_result = embeddings.embed_documents([document])query_result = embeddings.embed_query(query)Symmetric​from langchain.embeddings import AlephAlphaSymmetricSemanticEmbeddingtext = "This is a test text"embeddings = AlephAlphaSymmetricSemanticEmbedding()doc_result = embeddings.embed_documents([text])query_result = embeddings.embed_query(text)PreviousText embedding modelsNextAzureOpenAIAsymmetricSymmetricCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/text_embedding/aleph_alpha |
9b61bfd69c8f-0 | Clarifai | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/text_embedding/clarifai |
9b61bfd69c8f-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersDocument transformersLLMsMemoryRetrieversText embedding modelsAleph AlphaAzureOpenAIBedrock EmbeddingsClarifaiCohereDashScopeDeepInfraElasticsearchEmbaasFake EmbeddingsGoogle Cloud Platform Vertex AI PaLMGPT4AllHugging Face HubInstructEmbeddingsJinaLlama-cppLocalAIMiniMaxModelScopeMosaicML embeddingsNLP CloudOpenAISageMaker Endpoint EmbeddingsSelf Hosted EmbeddingsSentence Transformers EmbeddingsSpacy EmbeddingTensorflowHubAgent toolkitsToolsVector storesGrouped by providerIntegrationsText embedding modelsClarifaiClarifaiClarifai is an AI Platform that provides the full AI lifecycle ranging from data exploration, data labeling, model training, evaluation, and inference.This example goes over how to use LangChain to interact with Clarifai models. Text embedding models in particular can be found here.To use Clarifai, you must have an account and a Personal Access Token (PAT) key. | https://python.langchain.com/docs/integrations/text_embedding/clarifai |
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