id stringlengths 14 15 | text stringlengths 17 2.72k | source stringlengths 47 115 |
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e415660008a4-0 | Tencent COS Directory
This covers how to load document objects from a Tencent COS Directory.
#! pip install cos-python-sdk-v5
from langchain.document_loaders import TencentCOSDirectoryLoader
from qcloud_cos import CosConfig
conf = CosConfig(
Region="your cos region",
SecretId="your cos secret_id",
SecretKey="your cos s... | https://python.langchain.com/docs/integrations/document_loaders/tencent_cos_directory |
0bb71cc4dcf1-0 | TensorFlow Datasets
TensorFlow Datasets is a collection of datasets ready to use, with TensorFlow or other Python ML frameworks, such as Jax. All datasets are exposed as tf.data.Datasets, enabling easy-to-use and high-performance input pipelines. To get started see the guide and the list of datasets.
This notebook show... | https://python.langchain.com/docs/integrations/document_loaders/tensorflow_datasets |
0bb71cc4dcf1-1 | FeaturesDict({
'answers': Sequence({
'answer_start': int32,
'text': Text(shape=(), dtype=string),
}),
'context': Text(shape=(), dtype=string),
'id': string,
'question': Text(shape=(), dtype=string),
'title': Text(shape=(), dtype=string),
})
import tensorflow as tf
import tensorflow_datasets as tfds
# try directly acces... | https://python.langchain.com/docs/integrations/document_loaders/tensorflow_datasets |
0bb71cc4dcf1-2 | for example in ds:
doc = mlqaen_example_to_document(example)
print(doc)
break
page_content='After completing the journey around South America, on 23 February 2006, Queen Mary 2 met her namesake, the original RMS Queen Mary, which is permanently docked at Long Beach, California. Escorted by a flotilla of smaller ships,... | https://python.langchain.com/docs/integrations/document_loaders/tensorflow_datasets |
0bb71cc4dcf1-3 | loader = TensorflowDatasetLoader(
dataset_name="mlqa/en",
split_name="test",
load_max_docs=3,
sample_to_document_function=mlqaen_example_to_document,
)
TensorflowDatasetLoader has these parameters:
dataset_name: the name of the dataset to load
split_name: the name of the split to load. Defaults to "train".
load_max_doc... | https://python.langchain.com/docs/integrations/document_loaders/tensorflow_datasets |
0bb71cc4dcf1-4 | 3
'After completing the journey around South America, on 23 February 2006, Queen Mary 2 met her namesake, the original RMS Queen Mary, which is permanently docked at Long Beach, California. Escorted by a flotilla of smaller ships, the two Queens exchanged a "whistle salute" which was heard throughout the city of Long B... | https://python.langchain.com/docs/integrations/document_loaders/tensorflow_datasets |
8e1d4c8ebde1-0 | This covers how to load document object from a Tencent COS File.
conf = CosConfig(
Region="your cos region",
SecretId="your cos secret_id",
SecretKey="your cos secret_key",
)
loader = TencentCOSFileLoader(conf=conf, bucket="you_cos_bucket", key="fake.docx") | https://python.langchain.com/docs/integrations/document_loaders/tencent_cos_file |
fcbe3c93ba58-0 | ## Contents
- [Getting Started](#getting-started)
- [Modules](#modules)
- [Use Cases](#use-cases)
- [Reference Docs](#reference-docs)
- [LangChain Ecosystem](#langchain-ecosystem)
- [Additional Resources](#additional-resources)
## Welcome to LangChain [\#](\#welcome-to-langchain "Permalink to this headline")
**LangC... | https://python.langchain.com/docs/integrations/document_loaders/tomarkdown |
fcbe3c93ba58-1 | - [Memory](https://python.langchain.com/en/latest/modules/memory.html): Memory refers to state that is persisted between calls of a chain/agent.
- [Indexes](https://python.langchain.com/en/latest/modules/data_connection.html): Language models become much more powerful when combined with application-specific data - thi... | https://python.langchain.com/docs/integrations/document_loaders/tomarkdown |
fcbe3c93ba58-2 | - [Querying Tabular Data](https://python.langchain.com/en/latest/use_cases/tabular.html): Recommended reading if you want to use language models to query structured data (CSVs, SQL, dataframes, etc).
- [Code Understanding](https://python.langchain.com/en/latest/use_cases/code.html): Recommended reading if you want to ... | https://python.langchain.com/docs/integrations/document_loaders/tomarkdown |
fcbe3c93ba58-3 | - [Deployments](https://python.langchain.com/en/latest/additional_resources/deployments.html): A collection of instructions, code snippets, and template repositories for deploying LangChain apps.
- [Tracing](https://python.langchain.com/en/latest/additional_resources/tracing.html): A guide on using tracing in LangChai... | https://python.langchain.com/docs/integrations/document_loaders/tomarkdown |
56f46bfa9b9e-0 | TOML is a file format for configuration files. It is intended to be easy to read and write, and is designed to map unambiguously to a dictionary. Its specification is open-source. TOML is implemented in many programming languages. The name TOML is an acronym for "Tom's Obvious, Minimal Language" referring to its creato... | https://python.langchain.com/docs/integrations/document_loaders/toml |
9fe4185bc9a6-0 | You can also load the table using the UnstructuredTSVLoader. One advantage of using UnstructuredTSVLoader is that if you use it in "elements" mode, an HTML representation of the table will be available in the metadata.
<table border="1" class="dataframe">
<tbody>
<tr>
<td>Nationals, 81.34, 98</td>
</tr>
<tr>
<td>Reds, ... | https://python.langchain.com/docs/integrations/document_loaders/tsv |
9fe4185bc9a6-1 | </tr>
<tr>
<td>Mariners, 81.97, 75</td>
</tr>
<tr>
<td>Mets, 93.35, 74</td>
</tr>
<tr>
<td>Blue Jays, 75.48, 73</td>
</tr>
<tr>
<td>Royals, 60.91, 72</td>
</tr>
<tr>
<td>Marlins, 118.07, 69</td>
</tr>
<tr>
<td>Red Sox, 173.18, 69</td>
</tr>
<tr>
<td>Indians, 78.43, 68</td>
</tr>
<tr>
<td>Twins, 94.08, 66</td>
</tr>
<tr... | https://python.langchain.com/docs/integrations/document_loaders/tsv |
2e0ea251ca73-0 | Trello
Trello is a web-based project management and collaboration tool that allows individuals and teams to organize and track their tasks and projects. It provides a visual interface known as a "board" where users can create lists and cards to represent their tasks and activities.
The TrelloLoader allows you to load c... | https://python.langchain.com/docs/integrations/document_loaders/trello |
2e0ea251ca73-1 | print(documents[0].page_content)
print(documents[0].metadata)
Review Tech partner pages
Comments:
{'title': 'Review Tech partner pages', 'id': '6475357890dc8d17f73f2dcc', 'url': 'https://trello.com/c/b0OTZwkZ/1-review-tech-partner-pages', 'labels': ['Demand Marketing'], 'list': 'Done', 'closed': False, 'due_date': ''}
... | https://python.langchain.com/docs/integrations/document_loaders/trello |
5e3a84b9fb33-0 | This loader fetches the text from the Tweets of a list of Twitter users, using the tweepy Python package. You must initialize the loader with your Twitter API token, and you need to pass in the Twitter username you want to extract. | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-1 | [Document(page_content='@MrAndyNgo @REI One store after another shutting down', metadata={'created_at': 'Tue Apr 18 03:45:50 +0000 2023', 'user_info': {'id': 44196397, 'id_str': '44196397', 'name': 'Elon Musk', 'screen_name': 'elonmusk', 'location': 'A Shortfall of Gravitas', 'profile_location': None, 'description': 'n... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-2 | 2835451658, 'in_reply_to_user_id_str': '2835451658', 'in_reply_to_screen_name': 'MrAndyNgo', 'geo': None, 'coordinates': None, 'place': None, 'contributors': None, 'is_quote_status': False, 'retweet_count': 118, 'favorite_count': 1286, 'favorited': False, 'retweeted': False, 'lang': 'en'}, 'contributors_enabled': False... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-3 | Document(page_content='@KanekoaTheGreat @joshrogin @glennbeck Large ships are fundamentally vulnerable to ballistic (hypersonic) missiles', metadata={'created_at': 'Tue Apr 18 03:43:25 +0000 2023', 'user_info': {'id': 44196397, 'id_str': '44196397', 'name': 'Elon Musk', 'screen_name': 'elonmusk', 'location': 'A Shortfa... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-4 | 'in_reply_to_user_id': 2835451658, 'in_reply_to_user_id_str': '2835451658', 'in_reply_to_screen_name': 'MrAndyNgo', 'geo': None, 'coordinates': None, 'place': None, 'contributors': None, 'is_quote_status': False, 'retweet_count': 118, 'favorite_count': 1286, 'favorited': False, 'retweeted': False, 'lang': 'en'}, 'contr... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-5 | Document(page_content='@KanekoaTheGreat The Golden Rule', metadata={'created_at': 'Tue Apr 18 03:37:17 +0000 2023', 'user_info': {'id': 44196397, 'id_str': '44196397', 'name': 'Elon Musk', 'screen_name': 'elonmusk', 'location': 'A Shortfall of Gravitas', 'profile_location': None, 'description': 'nothing', 'url': None, ... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-6 | '2835451658', 'in_reply_to_screen_name': 'MrAndyNgo', 'geo': None, 'coordinates': None, 'place': None, 'contributors': None, 'is_quote_status': False, 'retweet_count': 118, 'favorite_count': 1286, 'favorited': False, 'retweeted': False, 'lang': 'en'}, 'contributors_enabled': False, 'is_translator': False, 'is_translati... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-7 | Document(page_content='@KanekoaTheGreat 🧐', metadata={'created_at': 'Tue Apr 18 03:35:48 +0000 2023', 'user_info': {'id': 44196397, 'id_str': '44196397', 'name': 'Elon Musk', 'screen_name': 'elonmusk', 'location': 'A Shortfall of Gravitas', 'profile_location': None, 'description': 'nothing', 'url': None, 'entities': {... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-8 | '2835451658', 'in_reply_to_screen_name': 'MrAndyNgo', 'geo': None, 'coordinates': None, 'place': None, 'contributors': None, 'is_quote_status': False, 'retweet_count': 118, 'favorite_count': 1286, 'favorited': False, 'retweeted': False, 'lang': 'en'}, 'contributors_enabled': False, 'is_translator': False, 'is_translati... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-9 | Document(page_content='@TRHLofficial What’s he talking about and why is it sponsored by Erik’s son?', metadata={'created_at': 'Tue Apr 18 03:32:17 +0000 2023', 'user_info': {'id': 44196397, 'id_str': '44196397', 'name': 'Elon Musk', 'screen_name': 'elonmusk', 'location': 'A Shortfall of Gravitas', 'profile_location': N... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
5e3a84b9fb33-10 | 2835451658, 'in_reply_to_user_id_str': '2835451658', 'in_reply_to_screen_name': 'MrAndyNgo', 'geo': None, 'coordinates': None, 'place': None, 'contributors': None, 'is_quote_status': False, 'retweet_count': 118, 'favorite_count': 1286, 'favorited': False, 'retweeted': False, 'lang': 'en'}, 'contributors_enabled': False... | https://python.langchain.com/docs/integrations/document_loaders/twitter |
1517dd4b4775-0 | URL
This covers how to load HTML documents from a list of URLs into a document format that we can use downstream.
from langchain.document_loaders import UnstructuredURLLoader
urls = [
"https://www.understandingwar.org/backgrounder/russian-offensive-campaign-assessment-february-8-2023",
"https://www.understandingwar.org... | https://python.langchain.com/docs/integrations/document_loaders/url |
7cdc6dc435f1-0 | This notebook covers how to use Unstructured package to load files of many types. Unstructured currently supports loading of text files, powerpoints, html, pdfs, images, and more.
Under the hood, Unstructured creates different "elements" for different chunks of text. By default we combine those together, but you can ea... | https://python.langchain.com/docs/integrations/document_loaders/unstructured_file |
7cdc6dc435f1-1 | [Document(page_content='LayoutParser : A Unified Toolkit for Deep Learning Based Document Image Analysis', lookup_str='', metadata={'source': '../../layout-parser-paper.pdf'}, lookup_index=0),
Document(page_content='Zejiang Shen 1 ( (ea)\n ), Ruochen Zhang 2 , Melissa Dell 3 , Benjamin Charles Germain Lee 4 , Jacob Carl... | https://python.langchain.com/docs/integrations/document_loaders/unstructured_file |
7cdc6dc435f1-2 | Document(page_content='Zejiang Shen1 ((cid:0)), Ruochen Zhang2, Melissa Dell3, Benjamin Charles Germain Lee4, Jacob Carlson3, and Weining Li5', metadata={'source': './example_data/layout-parser-paper.pdf', 'coordinates': {'points': ((134.809, 168.64029940800003), (134.809, 192.2517444), (480.5464199080001, 192.2517444)... | https://python.langchain.com/docs/integrations/document_loaders/unstructured_file |
7cdc6dc435f1-3 | Document(page_content='1 2 0 2', metadata={'source': './example_data/layout-parser-paper.pdf', 'coordinates': {'points': ((16.34, 213.36), (16.34, 253.36), (36.34, 253.36), (36.34, 213.36)), 'system': 'PixelSpace', 'layout_width': 612, 'layout_height': 792}, 'filename': 'layout-parser-paper.pdf', 'file_directory': './e... | https://python.langchain.com/docs/integrations/document_loaders/unstructured_file |
10040a60c54e-0 | Weather
OpenWeatherMap is an open source weather service provider
This loader fetches 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.docume... | https://python.langchain.com/docs/integrations/document_loaders/weather |
399ce9da8f67-0 | BibTeX files have a .bib extension and consist of plain text entries representing references to various publications, such as books, articles, conference papers, theses, and more. Each BibTeX entry follows a specific structure and contains fields for different bibliographic details like author names, publication title,... | https://python.langchain.com/docs/integrations/document_loaders/bibtex |
37fed393b96c-0 | This loader utilizes the bilibili-api to fetch the text transcript from Bilibili.
With this BiliBiliLoader, users can easily obtain the transcript of their desired video content on the platform.
#!pip install bilibili-api-python | https://python.langchain.com/docs/integrations/document_loaders/bilibili |
bab8bdb18888-0 | Blackboard Learn (previously the Blackboard Learning Management System) is a web-based virtual learning environment and learning management system developed by Blackboard Inc. The software features course management, customizable open architecture, and scalable design that allows integration with student information sy... | https://python.langchain.com/docs/integrations/document_loaders/blackboard |
8165a4bd2275-0 | The intention of this notebook is to provide a means of testing functionality in the Langchain Document Loader for Blockchain.
It can be extended if the community finds value in this loader. Specifically:
from langchain.document_loaders.blockchain import (
BlockchainDocumentLoader,
BlockchainType,
)
contractAddress = ... | https://python.langchain.com/docs/integrations/document_loaders/blockchain |
c0b2e637409b-0 | ['I wasn’t sure whether to laugh or cry a few days back listening to radio talk show host Bill Cunningham repeatedly scream Barack <strong>Obama</strong>’<strong>s</strong> <strong>middle</strong> <strong>name</strong> — my last <strong>name</strong> — as if he had anti-Muslim Tourette’s. “Hussein,” Cunningham hissed l... | https://python.langchain.com/docs/integrations/document_loaders/brave_search |
451e33c50059-0 | Browserless is a service that allows you to run headless Chrome instances in the cloud. It's a great way to run browser-based automation at scale without having to worry about managing your own infrastructure.
To use Browserless as a document loader, initialize a BrowserlessLoader instance as shown in this notebook. No... | https://python.langchain.com/docs/integrations/document_loaders/browserless |
c9c1669ef78c-0 | This notebook covers how to load conversations.json from your ChatGPT data export folder.
You can get your data export by email by going to: https://chat.openai.com/ -> (Profile) - Settings -> Export data -> Confirm export.
[Document(page_content="AI Overlords - AI on 2065-01-24 05:20:50: Greetings, humans. I am Hal 90... | https://python.langchain.com/docs/integrations/document_loaders/chatgpt_loader |
1da42f351449-0 | This covers how to load College Confidential webpages into a document format that we can use downstream. | https://python.langchain.com/docs/integrations/document_loaders/college_confidential |
1da42f351449-1 | [Document(page_content='\n\n\n\n\n\n\n\nA68FEB02-9D19-447C-B8BC-818149FD6EAF\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n Media (2)\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nE45B8B13-33D4-450E-B7DB-F66EFE8F2097\n\n\n\n\n\n\n\n\n\nE45B8B13-33D4-450E-B7DB-F66EFE8F2097\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nAbout Brown\n\n\n\n\n\n\nBrow... | https://python.langchain.com/docs/integrations/document_loaders/college_confidential |
1da42f351449-2 | First-Year Financial Aid Package\n$59,749\n\n\n\n\nIs Brown a Good School?\n\nDifferent people have different ideas about what makes a "good" school. Some factors that can help you determine what a good school for you might be include admissions criteria, acceptance rate, tuition costs, and more.\nLet\'s take a look at... | https://python.langchain.com/docs/integrations/document_loaders/college_confidential |
1da42f351449-3 | but do a better job at meeting students\' financial need.\nBrown meets 100% of the demonstrated financial need for undergraduates. The average financial aid package for a full-time, first-year student is around $59,749 a year. \nThe average student debt for graduates in the class of 2022 was around $24,102 per student,... | https://python.langchain.com/docs/integrations/document_loaders/college_confidential |
1da42f351449-4 | list of colleges in Rhode Island and save your favorites to your college list.\n\n\n\nCollege Info\n\n\n\n\n\n\n\n\n\n Providence, RI 02912\n \n\n\n\n Campus Setting: Urban\n \n\n\n\n\n\n\n\n (401) 863-2378\n \n\n Website\n \n\n Virtual Tour\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nBrown Application Deadline\n\n\n\nFirst-Year... | https://python.langchain.com/docs/integrations/document_loaders/college_confidential |
1da42f351449-5 | $82,286\n \nIn State\n\n\n\n\n $82,286\n \nOut-of-State\n\n\n\n\n\n\n\nCost Breakdown\n\n\nIn State\n\n\nOut-of-State\n\n\n\n\nState Tuition\n\n\n\n $62,680\n \n\n\n\n $62,680\n \n\n\n\n\nFees\n\n\n\n $2,466\n \n\n\n\n $2,466\n \n\n\n\n\nHousing\n\n\n\n $15,840\n \n\n\n\n $15,840\n \n\n\n\n\nBooks\n\n\n\n $1,300\n \n\n... | https://python.langchain.com/docs/integrations/document_loaders/college_confidential |
68ff05a2b4c5-0 | Works just like the GenericLoader but concurrently for those who choose to optimize their workflow.
loader = ConcurrentLoader.from_filesystem('example_data/', glob="**/*.txt") | https://python.langchain.com/docs/integrations/document_loaders/concurrent |
43bafb7b6bcd-0 | Confluence
Confluence is a wiki collaboration platform that saves and organizes all of the project-related material. Confluence is a knowledge base that primarily handles content management activities.
A loader for Confluence pages.
This currently supports username/api_key, Oauth2 login. Additionally, on-prem installa... | https://python.langchain.com/docs/integrations/document_loaders/confluence |
43bafb7b6bcd-1 | loader = ConfluenceLoader(
url="https://yoursite.atlassian.com/wiki", username="me", api_key="12345"
)
documents = loader.load(space_key="SPACE", include_attachments=True, limit=50)
Personal Access Token (Server/On-Prem only)
This method is valid for the Data Center/Server on-prem edition only. For more information on... | https://python.langchain.com/docs/integrations/document_loaders/confluence |
6904a11eddc9-0 | This notebook demonstrates the process of retrieving Cube's data model metadata in a format suitable for passing to LLMs as embeddings, thereby enhancing contextual information.
Cube is the Semantic Layer for building data apps. It helps data engineers and application developers access data from modern data stores, org... | https://python.langchain.com/docs/integrations/document_loaders/cube_semantic |
9fd50e5fe19b-0 | Copy Paste
This notebook covers how to load a document object from something you just want to copy and paste. In this case, you don't even need to use a DocumentLoader, but rather can just construct the Document directly.
from langchain.docstore.document import Document
text = "..... put the text you copy pasted here..... | https://python.langchain.com/docs/integrations/document_loaders/copypaste |
87da7cef603d-0 | This is an example of how to load a file in CoNLL-U format. The whole file is treated as one document. The example data (conllu.conllu) is based on one of the standard UD/CoNLL-U examples.
[Document(page_content='They buy and sell books.', metadata={'source': 'example_data/conllu.conllu'})] | https://python.langchain.com/docs/integrations/document_loaders/conll-u |
029f76cb8776-0 | [Document(page_content='Team: Nationals\n"Payroll (millions)": 81.34\n"Wins": 98', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 0}, lookup_index=0), Document(page_content='Team: Reds\n"Payroll (millions)": 82.20\n"Wins": 97', lookup_str='', metadata={'source': './example_data/mlb_teams... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-1 | 'row': 8}, lookup_index=0), Document(page_content='Team: Angels\n"Payroll (millions)": 154.49\n"Wins": 89', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 9}, lookup_index=0), Document(page_content='Team: Tigers\n"Payroll (millions)": 132.30\n"Wins": 88', lookup_str='', metadata={'source... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-2 | metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 17}, lookup_index=0), Document(page_content='Team: Padres\n"Payroll (millions)": 55.24\n"Wins": 76', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 18}, lookup_index=0), Document(page_content='Team: Mariners\n"Payroll (milli... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-3 | (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': './example_data/mlb_teams_2012.csv', 'row': 27}, lookup_index=0), Docum... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-4 | See the csv module documentation for more information of what csv args are supported.
loader = CSVLoader(
file_path="./example_data/mlb_teams_2012.csv",
csv_args={
"delimiter": ",",
"quotechar": '"',
"fieldnames": ["MLB Team", "Payroll in millions", "Wins"],
},
) | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-5 | data = loader.load() | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-6 | [Document(page_content='MLB Team: Team\nPayroll in millions: "Payroll (millions)"\nWins: "Wins"', lookup_str='', metadata={'source': './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': './e... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-7 | 'row': 8}, lookup_index=0), Document(page_content='MLB Team: Rays\nPayroll in millions: 64.17\nWins: 90', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 9}, lookup_index=0), Document(page_content='MLB Team: Angels\nPayroll in millions: 154.49\nWins: 89', lookup_str='', metadata={'source'... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-8 | 'row': 17}, lookup_index=0), Document(page_content='MLB Team: Pirates\nPayroll in millions: 63.43\nWins: 79', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 18}, lookup_index=0), Document(page_content='MLB Team: Padres\nPayroll in millions: 55.24\nWins: 76', lookup_str='', metadata={'sou... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-9 | 'row': 26}, lookup_index=0), Document(page_content='MLB Team: Twins\nPayroll in millions: 94.08\nWins: 66', lookup_str='', metadata={'source': './example_data/mlb_teams_2012.csv', 'row': 27}, lookup_index=0), Document(page_content='MLB Team: Rockies\nPayroll in millions: 78.06\nWins: 64', lookup_str='', metadata={'sour... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-10 | Use the source_column argument to specify a source for the document created from each row. Otherwise file_path will be used as the source for all documents created from the CSV file.
This is useful when using documents loaded from CSV files for chains that answer questions using sources. | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-11 | [Document(page_content='Team: Nationals\n"Payroll (millions)": 81.34\n"Wins": 98', lookup_str='', metadata={'source': 'Nationals', 'row': 0}, lookup_index=0), Document(page_content='Team: Reds\n"Payroll (millions)": 82.20\n"Wins": 97', lookup_str='', metadata={'source': 'Reds', 'row': 1}, lookup_index=0), Document(page... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-12 | lookup_index=0), Document(page_content='Team: Tigers\n"Payroll (millions)": 132.30\n"Wins": 88', lookup_str='', metadata={'source': 'Tigers', 'row': 10}, lookup_index=0), Document(page_content='Team: Cardinals\n"Payroll (millions)": 110.30\n"Wins": 88', lookup_str='', metadata={'source': 'Cardinals', 'row': 11}, lookup... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-13 | 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": 73', lookup_str='', metadata={'source': 'Blue Jays', 'row': 21}, lookup_... | https://python.langchain.com/docs/integrations/document_loaders/csv |
029f76cb8776-14 | You can also load the table using the UnstructuredCSVLoader. One advantage of using UnstructuredCSVLoader is that if you use it in "elements" mode, an HTML representation of the table will be available in the metadata. | https://python.langchain.com/docs/integrations/document_loaders/csv |
803d9e7ce4d5-0 | This loader fetches the logs from your applications in Datadog using the datadog_api_client Python package. You must initialize the loader with your Datadog API key and APP key, and you need to pass in the query to extract the desired logs.
query = "service:agent status:error" | https://python.langchain.com/docs/integrations/document_loaders/datadog_logs |
803d9e7ce4d5-1 | loader = DatadogLogsLoader(
query=query,
api_key=DD_API_KEY,
app_key=DD_APP_KEY,
from_time=1688732708951, # Optional, timestamp in milliseconds
to_time=1688736308951, # Optional, timestamp in milliseconds
limit=100, # Optional, default is 100
) | https://python.langchain.com/docs/integrations/document_loaders/datadog_logs |
803d9e7ce4d5-2 | limit=100, # Optional, default is 100
)
[Document(page_content='message: grep: /etc/datadog-agent/system-probe.yaml: No such file or directory', metadata={'id': 'AgAAAYkwpLImvkjRpQAAAAAAAAAYAAAAAEFZa3dwTUFsQUFEWmZfLU5QdElnM3dBWQAAACQAAAAAMDE4OTMwYTQtYzk3OS00MmJjLTlhNDAtOTY4N2EwY2I5ZDdk', 'status': 'error', 'service': '... | https://python.langchain.com/docs/integrations/document_loaders/datadog_logs |
803d9e7ce4d5-3 | Document(page_content='message: grep: /etc/datadog-agent/system-probe.yaml: No such file or directory', metadata={'id': 'AgAAAYkwpLImvkjRpgAAAAAAAAAYAAAAAEFZa3dwTUFsQUFEWmZfLU5QdElnM3dBWgAAACQAAAAAMDE4OTMwYTQtYzk3OS00MmJjLTlhNDAtOTY4N2EwY2I5ZDdk', 'status': 'error', 'service': 'agent', 'tags': ['accessible-from-goog-gk... | https://python.langchain.com/docs/integrations/document_loaders/datadog_logs |
04117a71c95f-0 | Discord
Discord is a VoIP and instant messaging social platform. Users have the ability to communicate with voice calls, video calls, text messaging, media and files in private chats or as part of communities called "servers". A server is a collection of persistent chat rooms and voice channels which can be accessed vi... | https://python.langchain.com/docs/integrations/document_loaders/discord |
cbd5a94520e5-0 | Unlike traditional web scraping tools, Diffbot doesn't require any rules to read the content on a page. It starts with computer vision, which classifies a page into one of 20 possible types. Content is then interpreted by a machine learning model trained to identify the key attributes on a page based on its type. The r... | https://python.langchain.com/docs/integrations/document_loaders/diffbot |
cbd5a94520e5-1 | [Document(page_content='LangChain is a framework for developing applications powered by language models. We believe that the most powerful and differentiated applications will not only call out to a language model via an API, but will also:\nBe data-aware: connect a language model to other sources of data\nBe agentic: ... | https://python.langchain.com/docs/integrations/document_loaders/diffbot |
cbd5a94520e5-2 | The second big LangChain use case. Answering questions over specific documents, only utilizing the information in those documents to construct an answer.\nChatbots: Since language models are good at producing text, that makes them ideal for creating chatbots.\nQuerying Tabular Data: If you want to understand how to use... | https://python.langchain.com/docs/integrations/document_loaders/diffbot |
cbd5a94520e5-3 | to offer more comprehensive support. Please fill out this form and we’ll set up a dedicated support Slack channel.', metadata={'source': 'https://python.langchain.com/en/latest/index.html'})] | https://python.langchain.com/docs/integrations/document_loaders/diffbot |
95ef1fe705cc-0 | Drobpox is a file hosting service that brings everything-traditional files, cloud content, and web shortcuts together in one place.
This notebook covers how to load documents from Dropbox. In addition to common files such as text and PDF files, it also supports Dropbox Paper files.
`DropboxLoader`` requires you to crea... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-1 | page_content='# 🎉 Getting Started with Dropbox Paper\nDropbox Paper is great for capturing ideas and gathering quick feedback from your team. You can use words, images, code, or media from other apps, or go ahead and connect your calendar and add to-dos for projects.\n\n*Explore and edit this doc to play with some of ... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-2 | to each other and they\'ll organize automatically. Click on an image twice to start full-screen gallery view.\n\n\n\n\n\n\n\n## SoundCloud\nhttps://w.soundcloud.com/player/?url=https%3A%2F%2Fsoundcloud.com%2Ftycho%2Fspoon-inside-out-tycho-version&autoplay=false\n\n\n[https://soundcloud.com/tycho/spoon-inside-out-tych... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-4 | team** by adding them to shared folders. Invite-only folders create more privacy.\n\n\n## Comments\n\n**Add comments** on a single character, an entire document, or any asset by highlighting it. **Add stickers** by clicking the 😄 in the message box.\n\n\n## To-dos\n\n**Bring someone’s attention to a comment or to-do**... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-5 | page_content='# 🥂 Toast to Droplets\n❓ **Rationale:** Reflection, especially writing, is the key to deep learning! Let’s take a few minutes to reflect on your first day at Dropbox individually, and then one lucky person will have the chance to share their toast.\n\n✍️ **How to fill out this template:**\n\n- Option 1: ... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-6 | page_content='APPEARED IN BULLETIN OF THE AMERICAN MATHEMATICAL SOCIETY Volume 31, Number 1, July 1994, Pages 15-38\n\nA REPORT ON WILES’ CAMBRIDGE LECTURES\n\n4 9 9 1\n\nK. RUBIN AND A. SILVERBERG\n\nl u J\n\nAbstract. In lectures at the Newton Institute in June of 1993, Andrew Wiles announced a proof of a large part ... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-7 | is impossible to separate a cube into two cubes, or a fourth power into two fourth powers, or in general, any power higher than the second into two like powers. I have discovered a truly marvelous proof of this, which this margin is too narrow to contain.)\n\nWe restate Fermat’s conjecture as follows.\n\nFermat’s Last ... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-8 | the Semistable Modular Lifting Conjecture is related to a conjecture of Mazur on deformations of Galois representations (Conjecture 4.2), and in 5 we describe Wiles’ method of attack on this conjecture. In order to make this survey as acces- sible as possible to nonspecialists, the more technical details are postponed ... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-9 | between Fermat’s Last Theorem and elliptic curves\n\n1.1. Fermat’s Last Theorem follows from modularity of elliptic curves. Suppose Fermat’s Last Theorem were false. Then there would exist nonzero integers a, b, c, and n > 2 such that an + bn = cn. It is easy to see that no generality is lost by assuming that n is a pr... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-10 | posed problems which may be viewed as a weaker version of the following conjecture (see [38]).\n\nTaniyama-Shimura Conjecture. Every elliptic curve over Q is modular.\n\nThe conjecture in the present form was made by Goro Shimura around 1962–64 and has become better understood due to work of Shimura [33–37] and of Andr... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-11 | A singular point on a curve f (x, y) = 0 is a point where both partial derivatives vanish. A curve is nonsingular if it has no singular points.\n\n(ii) Two elliptic curves over Q are isomorphic if one can be obtained from the other by changing coordinates x = A2x′ + B, y = A3y′ + Cx′ + D, with A, B, C, D\n\nQ and divid... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-12 | An elliptic curve E is modular if, for some integer N , there is a holo- morphic map from X0(N ) onto E.\n\nExample. It can be shown that there is a (holomorphic) isomorphism from X0(15) onto the elliptic curve y2 = x(x + 32)(x\n\n42).\n\n−\n\nRemark . There are many equivalent definitions of modularity (see II.4.D of [... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-13 | If A and B are distinct, nonzero, relatively prime integers, write EA,B for the elliptic curve defined by y2 = x(x + A)(x + B). Since EA,B and E−A,−B are isomorphic over the complex numbers (i.e., as Riemann surfaces), EA,B is modular if and only if E−A,−B is modular. If further AB(A B) is divisible by 16, then either E... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-14 | the coefficient a0 (the value at i\n\nA modular form f satisfies f (z) = f (z + 1) (apply (3) to\n\n∈\n\n(cid:0)\n\n0 because f is holomorphic at the cusp i\n\n≥\n\n∞\n\nP\n\n) is zero. Call a cusp form normalized if a1 = 1.\n\n∞ For fixed N there are commuting linear operators (called Hecke operators) Tm, 1, on the (finite... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-15 | of modularity for an elliptic curve.\n\nDefinition. An elliptic curve E over Q is modular if there exists an eigenform\n\n∞ n=1 ane2πinz such that for all but finitely many primes q,\n\n#(E(Fq)).\n\n(5) P\n\naq = q + 1\n\n− 2. An overview\n\nThe flow chart shows how Fermat’s Last Theorem would follow if one knew the Semis... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-16 | Shimura Conjecture.\n\nA REPORT ON WILES’ CAMBRIDGE LECTURES\n\n7\n\n2.1. Semistable Modular Lifting. Let ¯Q denote the algebraic closure of Q in C, and let GQ be the Galois group Gal( ¯Q/Q). If p is a prime, write\n\nF× p\n\n¯εp : GQ\n\n→\n\nfor the character giving the action of GQ on the p-th roots of unity. For the... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-17 | and 4.2).\n\nConjecture 2.1 (Semistable Modular Lifting Conjecture). Suppose p is an odd prime and E is a semistable elliptic curve over Q satisfying\n\n(a) ¯ρE,p is irreducible, (b) there are an eigenform f (z) =\n\n∞ n=1 ane2πinz and a prime ideal λ of\n\nOf\n\nsuch that p\n\nλ and for all but finitely many primes q,\... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-18 | 3 of [35] for the definitions of the Hecke operators on the space of weight-one cusp forms for Γ1(N ).\n\nTheorem 2.2 (Langlands-Tunnell). Suppose ρ : GQ GL2(C) is a continuous irreducible representation whose image in PGL2(C) is a subgroup of S4 (the sym- metric group on four elements ), τ is complex conjugation, and d... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-19 | for every g\n\n∈ trace(ψ(g))\n\n(mod(1 + √\n\n(9)\n\ntrace(g)\n\n2))\n\n≡\n\n−\n\nand\n\n(10)\n\ndet(ψ(g))\n\ndet(g)\n\n(mod 3).\n\n≡\n\nExplicitly, ψ can be defined on generators of GL2(F3) by\n\n√\n\n1 1 1 0\n\n1 1 1 0\n\n1 1\n\n1 1\n\n2 1 1 0\n\n.\n\nψ\n\n=\n\nand ψ\n\n=\n\n− −\n\n− −\n\n−\n\n−\n\n(cid:19)\n\n(cid:18... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-20 | d\n\n0 (mod 3), 1 (mod 3), 2 (mod 3)\n\n∞\n\n≡ ≡ ≡\n\nχ(d)e2πinz where χ(d) =\n\nE(z) = 1 + 6\n\n\uf8f1 \uf8f2\n\nn=1 X\n\nXd|n\n\n−\n\n∞ n=1 cne2πinz is a weight-one modular form for Γ1(3). The product g(z)E(z) = It is now is a weight-two cusp form for Γ0(N ) with cn ≡ bn possible to find an eigenform f (z) = (mod p) f... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-21 | is isomorphic to ¯ρE,5, and (ii) ¯ρE′,3 is irreducible.\n\n(In fact there will be infinitely many such E′; see Appendix B.2.) Now by Proposi- ∞ n=1 ane2πinz be a corresponding eigenform. tion 2.3, E′ is modular. Let f (z) = Then for all but finitely many primes q, P\n\n#(E′(Fq)) trace(¯ρE,5(Frobq))\n\naq = q + 1\n\ntrace... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-22 | in E( ¯Q) of points of order dividing pn and Tp(E) for the inverse limit of the E[pn] with respect to multiplication by p. For every n, E[pn] ∼= (Z/pnZ)2, and so Tp(E) ∼= Z2 p. The action of GQ induces a representation\n\nGL2(Zp)\n\nρE,p : GQ\n\n→\n\nsuch that det(ρE,p) = εp and for all but finitely many primes q,\n\n#(... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
95ef1fe705cc-23 | = aq.\n\nThus ρf,λ is modular with ι taken to be the inclusion of\n\nOf in\n\nOf,λ.\n\n(ii) Suppose p is a prime and E is an elliptic curve over Q. If E is modular, then ρE,p and ¯ρE,p are modular by (11), (7), and (5). Conversely, if ρE,p is modular, then it follows from (11) that E is modular. This proves the followi... | https://python.langchain.com/docs/integrations/document_loaders/dropbox |
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