id stringlengths 14 15 | text stringlengths 23 2.21k | source stringlengths 52 97 |
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8862143246f3-13 | 118, 'favorite_count': 1286, 'favorited': False, 'retweeted': False, 'lang': 'en'}, 'contributors_enabled': False, 'is_translator': False, 'is_translation_enabled': False, 'profile_background_color': 'C0DEED', 'profile_background_image_url': 'http://abs.twimg.com/images/themes/theme1/bg.png', 'profile_background_image_... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
f6104a1b5c3a-0 | CSV | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-2 | a delimited text file that uses a comma to separate values. Each line of the file is a data record. Each record consists of one or more fields, separated by commas.Load csv data with a single row per document.from langchain.document_loaders.csv_loader import CSVLoaderloader = CSVLoader(file_path="./example_data/mlb_tea... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-3 | 55.37\n"Wins": 94', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 5}, lookup_index=0), Document(page_content='Team: Rangers\n"Payroll (millions)": 120.51\n"Wins": 93', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 6}, lookup_index=0), Document(page_conte... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-4 | (millions)": 95.14\n"Wins": 86', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 12}, lookup_index=0), Document(page_content='Team: White Sox\n"Payroll (millions)": 96.92\n"Wins": 85', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 13}, lookup_index=0), Doc... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-5 | Mariners\n"Payroll (millions)": 81.97\n"Wins": 75', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 19}, lookup_index=0), Document(page_content='Team: Mets\n"Payroll (millions)": 93.35\n"Wins": 74', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 20}, lookup... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-6 | lookup_index=0), Document(page_content='Team: Twins\n"Payroll (millions)": 94.08\n"Wins": 66', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 26}, lookup_index=0), Document(page_content='Team: Rockies\n"Payroll (millions)": 78.06\n"Wins": 64', lookup_str='', metadata={'source': './exampl... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-7 | './example_data/mlb_teams_2012.csv', 'row': 0}, lookup_index=0), Document(page_content='MLB Team: Nationals\nPayroll in millions: 81.34\nWins: 98', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 1}, lookup_index=0), Document(page_content='MLB Team: Reds\nPayroll in millions: 82.20\nWins:... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-8 | 'row': 7}, lookup_index=0), Document(page_content='MLB Team: Orioles\nPayroll in millions: 81.43\nWins: 93', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 8}, lookup_index=0), Document(page_content='MLB Team: Rays\nPayroll in millions: 64.17\nWins: 90', lookup_str='', metadata={'source'... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-9 | 'row': 14}, lookup_index=0), Document(page_content='MLB Team: Brewers\nPayroll in millions: 97.65\nWins: 83', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 15}, lookup_index=0), Document(page_content='MLB Team: Phillies\nPayroll in millions: 174.54\nWins: 81', lookup_str='', metadata={'... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-10 | 'row': 21}, lookup_index=0), Document(page_content='MLB Team: Blue Jays\nPayroll in millions: 75.48\nWins: 73', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 22}, lookup_index=0), Document(page_content='MLB Team: Royals\nPayroll in millions: 60.91\nWins: 72', lookup_str='', metadata={'s... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-11 | 'row': 28}, lookup_index=0), Document(page_content='MLB Team: Cubs\nPayroll in millions: 88.19\nWins: 61', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 29}, lookup_index=0), Document(page_content='MLB Team: Astros\nPayroll in millions: 60.65\nWins: 55', lookup_str='', metadata={'source... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-12 | 94', lookup_str='', metadata={'source': 'Giants', 'row': 3}, lookup_index=0), Document(page_content='Team: Braves\n"Payroll (millions)": 83.31\n"Wins": 94', lookup_str='', metadata={'source': 'Braves', 'row': 4}, lookup_index=0), Document(page_content='Team: Athletics\n"Payroll (millions)": 55.37\n"Wins": 94', lookup_s... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-13 | 88', lookup_str='', metadata={'source': 'Cardinals', 'row': 11}, lookup_index=0), Document(page_content='Team: Dodgers\n"Payroll (millions)": 95.14\n"Wins": 86', lookup_str='', metadata={'source': 'Dodgers', 'row': 12}, lookup_index=0), Document(page_content='Team: White Sox\n"Payroll (millions)": 96.92\n"Wins": 85', l... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-14 | 81.97\n"Wins": 75', lookup_str='', metadata={'source': 'Mariners', 'row': 19}, lookup_index=0), Document(page_content='Team: Mets\n"Payroll (millions)": 93.35\n"Wins": 74', lookup_str='', metadata={'source': 'Mets', 'row': 20}, lookup_index=0), Document(page_content='Team: Blue Jays\n"Payroll (millions)": 75.48\n"Wins"... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-15 | Rockies\n"Payroll (millions)": 78.06\n"Wins": 64', lookup_str='', metadata={'source': 'Rockies', 'row': 27}, lookup_index=0), Document(page_content='Team: Cubs\n"Payroll (millions)": 88.19\n"Wins": 61', lookup_str='', metadata={'source': 'Cubs', 'row': 28}, lookup_index=0), Document(page_content='Team: Astros\n"Payroll... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-16 | <td>82.20</td> <td>97</td> </tr> <tr> <td>Yankees</td> <td>197.96</td> <td>95</td> </tr> <tr> <td>Giants</td> <td>117.62</td> <td>94</td> </tr> <tr> <td>Braves</td> <td>83.31</td> <td>94</... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-17 | </tr> <tr> <td>Orioles</td> <td>81.43</td> <td>93</td> </tr> <tr> <td>Rays</td> <td>64.17</td> <td>90</td> </tr> <tr> <td>Angels</td> <td>154.49</td> <td>89</td> </tr> <tr> <td>Tige... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-18 | <td>Dodgers</td> <td>95.14</td> <td>86</td> </tr> <tr> <td>White Sox</td> <td>96.92</td> <td>85</td> </tr> <tr> <td>Brewers</td> <td>97.65</td> <td>83</td> </tr> <tr> <td>Phillies</td> <td... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-19 | <td>79</td> </tr> <tr> <td>Padres</td> <td>55.24</td> <td>76</td> </tr> <tr> <td>Mariners</td> <td>81.97</td> <td>75</td> </tr> <tr> <td>Mets</td> <td>93.35</td> <td>74</td> </tr> <tr... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-20 | <tr> <td>Marlins</td> <td>118.07</td> <td>69</td> </tr> <tr> <td>Red Sox</td> <td>173.18</td> <td>69</td> </tr> <tr> <td>Indians</td> <td>78.43</td> <td>68</td> </tr> <tr> <td>Twins</td> ... | https://python.langchain.com/docs/integrations/document_loaders/csv |
f6104a1b5c3a-21 | <td>88.19</td> <td>61</td> </tr> <tr> <td>Astros</td> <td>60.65</td> <td>55</td> </tr> </tbody> </table>PreviousCopy PasteNextCube Semantic LayerCustomizing the csv parsing and loadingSpecify a column to identify the document sourceUnstructuredCSVLoaderCo... | https://python.langchain.com/docs/integrations/document_loaders/csv |
fd94cb3e0a8a-0 | Slack | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/slack |
fd94cb3e0a8a-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/slack |
fd94cb3e0a8a-2 | notebook covers how to load documents from a Zipfile generated from a Slack export.In order to get this Slack export, follow these instructions:🧑 Instructions for ingesting your own dataset​Export your Slack data. You can do this by going to your Workspace Management page and clicking the Import/Export option ({yo... | https://python.langchain.com/docs/integrations/document_loaders/slack |
064030fdde6f-0 | Telegram | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/telegram |
064030fdde6f-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/telegram |
064030fdde6f-2 | encrypted, cloud-based and centralized instant messaging service. The application also provides optional end-to-end encrypted chats and video calling, VoIP, file sharing and several other features.This notebook covers how to load data from Telegram into a format that can be ingested into LangChain.from langchain.docume... | https://python.langchain.com/docs/integrations/document_loaders/telegram |
aaa1eaa8bc27-0 | Obsidian | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/obsidian |
aaa1eaa8bc27-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/obsidian |
aaa1eaa8bc27-2 | that works on top of your local folder of plain text files.This notebook covers how to load documents from an Obsidian database.Since Obsidian is just stored on disk as a folder of Markdown files, the loader just takes a path to this directory.Obsidian files also sometimes contain metadata which is a YAML block at the ... | https://python.langchain.com/docs/integrations/document_loaders/obsidian |
00e6fb67e039-0 | Xorbits Pandas DataFrame | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-2 | goes over how to load data from a xorbits.pandas DataFrame.#!pip install xorbitsimport xorbits.pandas as pddf = pd.read_csv("example_data/mlb_teams_2012.csv")df.head() 0%| | 0.00/100 [00:00<?, ?it/s]<div><style scoped> .dataframe tbody tr th:only-of-type { vertical-align: middle; } .datafram... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-3 | </tr> <tr> <th>2</th> <td>Yankees</td> <td>197.96</td> <td>95</td> </tr> <tr> <th>3</th> <td>Giants</td> <td>117.62</td> <td>94</td> </tr> <tr> <th>4</th> <td>Braves</td> <td>83.31</td> <td>94</td> </tr> </tbody></table></div>from langchain.... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-4 | metadata={' "Payroll (millions)"': 117.62, ' "Wins"': 94}), Document(page_content='Braves', metadata={' "Payroll (millions)"': 83.31, ' "Wins"': 94}), Document(page_content='Athletics', metadata={' "Payroll (millions)"': 55.37, ' "Wins"': 94}), Document(page_content='Rangers', metadata={' "Payroll (millions... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-5 | (millions)"': 97.65, ' "Wins"': 83}), Document(page_content='Phillies', metadata={' "Payroll (millions)"': 174.54, ' "Wins"': 81}), Document(page_content='Diamondbacks', metadata={' "Payroll (millions)"': 74.28, ' "Wins"': 81}), Document(page_content='Pirates', metadata={' "Payroll (millions)"': 63.43, ' "W... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-6 | 78.43, ' "Wins"': 68}), Document(page_content='Twins', metadata={' "Payroll (millions)"': 94.08, ' "Wins"': 66}), Document(page_content='Rockies', metadata={' "Payroll (millions)"': 78.06, ' "Wins"': 64}), Document(page_content='Cubs', metadata={' "Payroll (millions)"': 88.19, ' "Wins"': 61}), Document(... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-7 | page_content='Athletics' metadata={' "Payroll (millions)"': 55.37, ' "Wins"': 94} page_content='Rangers' metadata={' "Payroll (millions)"': 120.51, ' "Wins"': 93} page_content='Orioles' metadata={' "Payroll (millions)"': 81.43, ' "Wins"': 93} page_content='Rays' metadata={' "Payroll (millions)"': 64.17, ' "Win... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-8 | 81} page_content='Pirates' metadata={' "Payroll (millions)"': 63.43, ' "Wins"': 79} page_content='Padres' metadata={' "Payroll (millions)"': 55.24, ' "Wins"': 76} page_content='Mariners' metadata={' "Payroll (millions)"': 81.97, ' "Wins"': 75} page_content='Mets' metadata={' "Payroll (millions)"': 93.35, ' ... | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
00e6fb67e039-9 | ' "Wins"': 61} page_content='Astros' metadata={' "Payroll (millions)"': 60.65, ' "Wins"': 55}PreviousXMLNextLoading documents from a YouTube urlCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 LangChain, Inc. | https://python.langchain.com/docs/integrations/document_loaders/xorbits |
5237d644c048-0 | Microsoft Word | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/microsoft_word |
5237d644c048-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/microsoft_word |
5237d644c048-2 | by Microsoft.This covers how to load Word documents into a document format that we can use downstream.Using Docx2txt​Load .docx using Docx2txt into a document.pip install docx2txtfrom langchain.document_loaders import Docx2txtLoaderloader = Docx2txtLoader("example_data/fake.docx")data = loader.load()data [Document... | https://python.langchain.com/docs/integrations/document_loaders/microsoft_word |
79e53a7ac20a-0 | Google BigQuery | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/google_bigquery |
79e53a7ac20a-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/google_bigquery |
79e53a7ac20a-2 | BigQuery is a part of the Google Cloud Platform.Load a BigQuery query with one document per row.#!pip install google-cloud-bigqueryfrom langchain.document_loaders import BigQueryLoaderBASE_QUERY = """SELECT id, dna_sequence, organismFROM ( SELECT ARRAY ( SELECT AS STRUCT 1 AS id, "ATTCGA" AS dna_sequence... | https://python.langchain.com/docs/integrations/document_loaders/google_bigquery |
79e53a7ac20a-3 | BigQueryLoader( BASE_QUERY, page_content_columns=["dna_sequence", "organism"], metadata_columns=["id"],)data = loader.load()print(data) [Document(page_content='dna_sequence: ATTCGA\norganism: Lokiarchaeum sp. (strain GC14_75).', lookup_str='', metadata={'id': 1}, lookup_index=0), Document(page_content='dna_... | https://python.langchain.com/docs/integrations/document_loaders/google_bigquery |
79e53a7ac20a-4 | = BigQueryLoader(ALIASED_QUERY, metadata_columns=["source"])data = loader.load()print(data) [Document(page_content='id: 1\ndna_sequence: ATTCGA\norganism: Lokiarchaeum sp. (strain GC14_75).\nsource: 1', lookup_str='', metadata={'source': 1}, lookup_index=0), Document(page_content='id: 2\ndna_sequence: AGGCGA\norgani... | https://python.langchain.com/docs/integrations/document_loaders/google_bigquery |
b7faf45077fb-0 | Figma | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/figma |
b7faf45077fb-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/figma |
b7faf45077fb-2 | notebook covers how to load data from the Figma REST API into a format that can be ingested into LangChain, along with example usage for code generation.import osfrom langchain.document_loaders.figma import FigmaFileLoaderfrom langchain.text_splitter import CharacterTextSplitterfrom langchain.chat_models import ChatOpe... | https://python.langchain.com/docs/integrations/document_loaders/figma |
b7faf45077fb-3 | system_prompt_template = """You are expert coder Jon Carmack. Use the provided design context to create idomatic HTML/CSS code as possible based on the user request. Everything must be inline in one file and your response must be directly renderable by the browser. Figma file nodes and metadata: {context}""" h... | https://python.langchain.com/docs/integrations/document_loaders/figma |
b7faf45077fb-4 | name="viewport" content="width=device-width, initial-scale=1.0">\n <style>\n @import url(\'https://fonts.googleapis.com/css2?family=DM+Sans:wght@500;700&family=Inter:wght@600&display=swap\');\n\n body {\n margin: 0;\n font-family: \'DM Sans\', sans-serif;\n }\n\n .he... | https://python.langchain.com/docs/integrations/document_loaders/figma |
b7faf45077fb-5 | align-items: center;\n }\n\n .header nav a {\n font-size: 14px;\n font-weight: 500;\n text-decoration: none;\n color: #000;\n margin-left: 20px;\n }\n\n @media (max-width: 768px) {\n .header nav {\n display: non... | https://python.langchain.com/docs/integrations/document_loaders/figma |
8253fc3f5642-0 | AWS S3 File | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/aws_s3_file |
8253fc3f5642-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/aws_s3_file |
8253fc3f5642-2 | is an object storage service.AWS S3 BucketsThis covers how to load document objects from an AWS S3 File object.from langchain.document_loaders import S3FileLoader#!pip install boto3loader = S3FileLoader("testing-hwc", "fake.docx")loader.load() [Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', meta... | https://python.langchain.com/docs/integrations/document_loaders/aws_s3_file |
8435959b917a-0 | Fauna | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/fauna |
8435959b917a-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/fauna |
8435959b917a-2 | is a Document Database.Query Fauna documents#!pip install faunaQuery data example​from langchain.document_loaders.fauna import FaunaLoadersecret = "<enter-valid-fauna-secret>"query = "Item.all()" # Fauna query. Assumes that the collection is called "Item"field = "text" # The field that contains the page content. As... | https://python.langchain.com/docs/integrations/document_loaders/fauna |
40d0c2b925aa-0 | Grobid | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/grobid |
40d0c2b925aa-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/grobid |
40d0c2b925aa-2 | for extracting, parsing, and re-structuring raw documents.It is particularly good for sturctured PDFs, like academic papers.This loader uses GROBIB to parse PDFs into Documents that retain metadata associated with the section of text.For users on Mac - (Note: additional instructions can be found here.)Install Java (App... | https://python.langchain.com/docs/integrations/document_loaders/grobid |
40d0c2b925aa-3 | or GPT-3, we only use publicly available data, making our work compatible with open-sourcing, while most existing models rely on data which is either not publicly available or undocumented (e.g."Books -2TB" or "Social media conversations").There exist some exceptions, notably OPT (Zhang et al., 2022), GPT-NeoX (Black e... | https://python.langchain.com/docs/integrations/document_loaders/grobid |
40d0c2b925aa-4 | 'y': '536.27', 'h': '218.27', 'w': '9.46'}, {'page': '1', 'x': '306.14', 'y': '549.82', 'h': '218.65', 'w': '9.46'}, {'page': '1', 'x': '306.14', 'y': '563.37', 'h': '136.98', 'w': '9.46'}], [{'page': '1', 'x': '446.49', 'y': '563.37', 'h': '78.11', 'w': '9.46'}, {'page': '1', 'x': '304.69', 'y': '576.92', 'h': '138.32... | https://python.langchain.com/docs/integrations/document_loaders/grobid |
40d0c2b925aa-5 | '1')", 'section_title': 'Introduction', 'section_number': '1', 'paper_title': 'LLaMA: Open and Efficient Foundation Language Models', 'file_path': '/Users/31treehaus/Desktop/Papers/2302.13971.pdf'}PreviousGoogle DriveNextGutenbergCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright © 2023 ... | https://python.langchain.com/docs/integrations/document_loaders/grobid |
89529bbb3b72-0 | Weather | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/weather |
89529bbb3b72-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/weather |
89529bbb3b72-2 | the weather data from the OpenWeatherMap's OneCall API, using the pyowm Python package. You must initialize the loader with your OpenWeatherMap API token and the names of the cities you want the weather data for.from langchain.document_loaders import WeatherDataLoader#!pip install pyowm# Set API key either by passing i... | https://python.langchain.com/docs/integrations/document_loaders/weather |
ab7c2fa7e248-0 | Etherscan Loader | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-2 | Etherscan loader use etherscan api to load transacactions histories under specific account on Ethereum Mainnet.You will need a Etherscan api key to proceed. The free api key has 5 calls per seconds quota.The loader supports the following six functinalities:Retrieve normal transactions under specifc account on Ethereum ... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-3 | The filter is default to normal_transactionIf you have any questions, you can access Etherscan API Doc or contact me via i@inevitable.tech.All functions related to transactions histories are restricted 1000 histories maximum because of Etherscan limit. You can use the following parameters to find the transaction histor... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-4 | 'from': '0x2ceee24f8d03fc25648c68c8e6569aa0512f6ac3', 'contractAddress': '0x2ceee24f8d03fc25648c68c8e6569aa0512f6ac3', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b', 'value': '298131000000000', 'tokenName': 'ABCHANGE.io', 'tokenSymbol': 'XCH', 'tokenDecimal': '9', 'transactionIndex': '7... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-5 | 'nonce': '3155', 'blockHash': '0xc2c2207bcaf341eed07f984c9a90b3f8e8bdbdbd2ac6562f8c2f5bfa4b51299d', 'transactionIndex': '5', 'from': '0x3763e6e1228bfeab94191c856412d1bb0a8e6996', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b', 'value': '13149213761000000000', 'gas': '90000', 'gasPrice': '22655598156', 'isError': '0... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-6 | '1727090', 'timeStamp': '1466262018', 'hash': '0xd5a779346d499aa722f72ffe7cd3c8594a9ddd91eb7e439e8ba92ceb7bc86928', 'nonce': '3267', 'blockHash': '0xc0cff378c3446b9b22d217c2c5f54b1c85b89a632c69c55b76cdffe88d2b9f4d', 'transactionIndex': '20', 'from': '0x3763e6e1228bfeab94191c856412d1bb0a8e6996', 'to': '0x9dd134d14d1e65f... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-7 | Document(page_content="{'blockNumber': '1730337', 'timeStamp': '1466308222', 'hash': '0xceaffdb3766d2741057d402738eb41e1d1941939d9d438c102fb981fd47a87a4', 'nonce': '3344', 'blockHash': '0x3a52d28b8587d55c621144a161a0ad5c37dd9f7d63b629ab31da04fa410b2cfa', 'transactionIndex': '1', 'from': '0x3763e6e1228bfeab94191c856412d... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-8 | Document(page_content="{'blockNumber': '1733479', 'timeStamp': '1466352351', 'hash': '0x720d79bf78775f82b40280aae5abfc347643c5f6708d4bf4ec24d65cd01c7121', 'nonce': '3367', 'blockHash': '0x9928661e7ae125b3ae0bcf5e076555a3ee44c52ae31bd6864c9c93a6ebb3f43e', 'transactionIndex': '0', 'from': '0x3763e6e1228bfeab94191c856412d... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-9 | Document(page_content="{'blockNumber': '1734172', 'timeStamp': '1466362463', 'hash': '0x7a062d25b83bafc9fe6b22bc6f5718bca333908b148676e1ac66c0adeccef647', 'nonce': '1016', 'blockHash': '0x8a8afe2b446713db88218553cfb5dd202422928e5e0bc00475ed2f37d95649de', 'transactionIndex': '4', 'from': '0x16545fb79dbee1ad3a7f868b7661c... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-10 | Document(page_content="{'blockNumber': '1737276', 'timeStamp': '1466406037', 'hash': '0xa4e89bfaf075abbf48f96700979e6c7e11a776b9040113ba64ef9c29ac62b19b', 'nonce': '1024', 'blockHash': '0xe117cad73752bb485c3bef24556e45b7766b283229180fcabc9711f3524b9f79', 'transactionIndex': '35', 'from': '0x16545fb79dbee1ad3a7f868b7661... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-11 | Document(page_content="{'blockNumber': '1740314', 'timeStamp': '1466450262', 'hash': '0x6e1a22dcc6e2c77a9451426fb49e765c3c459dae88350e3ca504f4831ec20e8a', 'nonce': '1051', 'blockHash': '0x588d17842819a81afae3ac6644d8005c12ce55ddb66c8d4c202caa91d4e8fdbe', 'transactionIndex': '6', 'from': '0x16545fb79dbee1ad3a7f868b7661c... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-12 | Document(page_content="{'blockNumber': '1743384', 'timeStamp': '1466494099', 'hash': '0xdbfcc15f02269fc3ae27f69e344a1ac4e08948b12b76ebdd78a64d8cafd511ef', 'nonce': '1068', 'blockHash': '0x997245108c84250057fda27306b53f9438ad40978a95ca51d8fd7477e73fbaa7', 'transactionIndex': '2', 'from': '0x16545fb79dbee1ad3a7f868b7661c... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-13 | Document(page_content="{'blockNumber': '1746405', 'timeStamp': '1466538123', 'hash': '0xbd4f9602f7fff4b8cc2ab6286efdb85f97fa114a43f6df4e6abc88e85b89e97b', 'nonce': '1092', 'blockHash': '0x3af3966cdaf22e8b112792ee2e0edd21ceb5a0e7bf9d8c168a40cf22deb3690c', 'transactionIndex': '0', 'from': '0x16545fb79dbee1ad3a7f868b7661c... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-14 | 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b'}), Document(page_content="{'blockNumber': '1749459', 'timeStamp': '1466582044', 'hash': '0x28c327f462cc5013d81c8682c032f014083c6891938a7bdeee85a1c02c3e9ed4', 'nonce': '1096', 'blockHash': '0x5fc5d2a903977b35ce1239975ae23f9157d45d7bd8a8f6205e8ce270000797f9', 'transa... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-15 | 'tx_hash': '0x28c327f462cc5013d81c8682c032f014083c6891938a7bdeee85a1c02c3e9ed4', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b'}), Document(page_content="{'blockNumber': '1752614', 'timeStamp': '1466626168', 'hash': '0xc3849e550ca5276d7b3c51fa95ad3ae62c1c164799d33f4388fe60c4e1d4f7d8', 'nonce': '1118', 'blockHas... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-16 | 'tx_hash': '0xc3849e550ca5276d7b3c51fa95ad3ae62c1c164799d33f4388fe60c4e1d4f7d8', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b'}), Document(page_content="{'blockNumber': '1755659', 'timeStamp': '1466669931', 'hash': '0xb9f891b7c3d00fcd64483189890591d2b7b910eda6172e3bf3973c5fd3d5a5ae', 'nonce': '1133', 'blockHas... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-17 | 'methodId': '0x', 'functionName': ''}", metadata={'from': '0x16545fb79dbee1ad3a7f868b7661c023f372d5de', 'tx_hash': '0xb9f891b7c3d00fcd64483189890591d2b7b910eda6172e3bf3973c5fd3d5a5ae', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b'}), Document(page_content="{'blockNumber': '1758709', 'timeStamp': '1466713652', ... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-18 | 'gasUsed': '21000', 'confirmations': '15976543', 'methodId': '0x', 'functionName': ''}", metadata={'from': '0x16545fb79dbee1ad3a7f868b7661c023f372d5de', 'tx_hash': '0xd6cce5b184dc7fce85f305ee832df647a9c4640b68e9b79b6f74dc38336d5622', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b'}), Document(page_content="{'blo... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-19 | '', 'cumulativeGasUsed': '63000', 'gasUsed': '21000', 'confirmations': '15973469', 'methodId': '0x', 'functionName': ''}", metadata={'from': '0x16545fb79dbee1ad3a7f868b7661c023f372d5de', 'tx_hash': '0xd01545872629956867cbd65fdf5e97d0dde1a112c12e76a1bfc92048d37f650f', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b'})... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-20 | '', 'input': '0x', 'contractAddress': '', 'cumulativeGasUsed': '168000', 'gasUsed': '21000', 'confirmations': '15970357', 'methodId': '0x', 'functionName': ''}", metadata={'from': '0x16545fb79dbee1ad3a7f868b7661c023f372d5de', 'tx_hash': '0x620b91b12af7aac75553b47f15742e2825ea38919cfc8082c0666f404a0db28b', 'to': '0x9dd1... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-21 | 'isError': '0', 'txreceipt_status': '', 'input': '0x', 'contractAddress': '', 'cumulativeGasUsed': '21000', 'gasUsed': '21000', 'confirmations': '15967316', 'methodId': '0x', 'functionName': ''}", metadata={'from': '0x16545fb79dbee1ad3a7f868b7661c023f372d5de', 'tx_hash': '0x758efa27576cd17ebe7b842db4892eac6609e3962a4f9... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-22 | 'gas': '90000', 'gasPrice': '20000000000', 'isError': '0', 'txreceipt_status': '', 'input': '0x', 'contractAddress': '', 'cumulativeGasUsed': '21000', 'gasUsed': '21000', 'confirmations': '15964341', 'methodId': '0x', 'functionName': ''}", metadata={'from': '0x16545fb79dbee1ad3a7f868b7661c023f372d5de', 'tx_hash': '0x9d... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-23 | 'value': '9979637283000000000', 'gas': '90000', 'gasPrice': '20000000000', 'isError': '0', 'txreceipt_status': '', 'input': '0x', 'contractAddress': '', 'cumulativeGasUsed': '63000', 'gasUsed': '21000', 'confirmations': '15961208', 'methodId': '0x', 'functionName': ''}", metadata={'from': '0x16545fb79dbee1ad3a7f868b766... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-24 | 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b', 'value': '4556173496000000000', 'gas': '90000', 'gasPrice': '20000000000', 'isError': '0', 'txreceipt_status': '', 'input': '0x', 'contractAddress': '', 'cumulativeGasUsed': '168000', 'gasUsed': '21000', 'confirmations': '15958195', 'methodId': '0x', 'functionName': '... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
ab7c2fa7e248-25 | 'transactionIndex': '1', 'from': '0x16545fb79dbee1ad3a7f868b7661c023f372d5de', 'to': '0x9dd134d14d1e65f84b706d6f205cd5b1cd03a46b', 'value': '11890330240000000000', 'gas': '90000', 'gasPrice': '20000000000', 'isError': '0', 'txreceipt_status': '', 'input': '0x', 'contractAddress': '', 'cumulativeGasUsed': '42000', 'gasU... | https://python.langchain.com/docs/integrations/document_loaders/Etherscan |
b48d76a3c0e0-0 | Microsoft PowerPoint | 🦜�🔗 Langchain | https://python.langchain.com/docs/integrations/document_loaders/microsoft_powerpoint |
b48d76a3c0e0-1 | Skip to main content🦜�🔗 LangChainDocsUse casesIntegrationsAPILangSmithJS/TS DocsCTRLKIntegrationsCallbacksChat modelsDocument loadersEtherscan LoaderacreomAirbyte JSONAirtableAlibaba Cloud MaxComputeApify DatasetArxivAsyncHtmlLoaderAWS S3 DirectoryAWS S3 FileAZLyricsAzure Blob Storage ContainerAzure Blob Storag... | https://python.langchain.com/docs/integrations/document_loaders/microsoft_powerpoint |
b48d76a3c0e0-2 | by Microsoft.This covers how to load Microsoft PowerPoint documents into a document format that we can use downstream.from langchain.document_loaders import UnstructuredPowerPointLoaderloader = UnstructuredPowerPointLoader("example_data/fake-power-point.pptx")data = loader.load()data [Document(page_content='Adding a... | https://python.langchain.com/docs/integrations/document_loaders/microsoft_powerpoint |
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