id stringlengths 14 16 | source stringlengths 49 117 | text stringlengths 16 2.73k |
|---|---|---|
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8fed2f4241d0-17 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.013305014, 0.0006418298, 0.023802789, 0.013122218, -0.0031548813, -0.027471786, 0.005046504, 0.008545762, 0.011261604, -0.01357921, -0.01110492, -0.014845733, -0.035384286, -0.02550019, 0.008154054, -0.0058331843, -0.008702445, -0.007311882, -0.006525202, 0.03817847, 0.00372449, 0.022914914, -0.0018981516, 0.03154554... |
8fed2f4241d0-18 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.006815719, 0.009936325, 0.014192886, 0.02277129, -0.006972402, -0.029769806, 0.034862008, 0.01217559, -0.0037179615, 0.0008666539, 0.008924413, -0.026296662, -0.012678281, 0.014480138, 0.020734407, -0.012103776, -0.037499506, 0.022131499, 0.015028529, -0.033843566, 0.00020187242, 0.002650557, -0.0015113399, 0.021570... |
8fed2f4241d0-19 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.001512972, 0.013931747, -0.009642544, 0.012652168, -0.012932892, -0.027759038, -0.01085031, 0.0050236546, -0.009675186, -0.00893747, -0.0051770736, 0.036011018, 0.003528636, -0.001008648, -0.015811944, -0.008865656, 0.012364916, 0.016621474, -0.01340947, 0.03219839, 0.032955695, -0.021517823, 0.00372449, -0.04512475... |
8fed2f4241d0-20 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.020186016, -0.010217049, 0.015315781, -0.012580355, 0.01374895, 0.004948577, -0.0021854038, 0.023215225, 0.00207442, 0.029639237, 0.01391869, -0.015811944, -0.005356606, -0.022327352, -0.021844247, -0.008310737, -0.020786636, -0.022484036, 0.011411758, 0.005826656, 0.012188647, -0.020394927, -0.0013024289, -0.027315... |
8fed2f4241d0-21 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.015106871, -0.03225062, -0.010073422, 0.007285768, 0.0056079524, -0.009002754, -0.014362626, 0.010909067, 0.009779641, -0.02796795, 0.013246258, 0.025474075, -0.001247753, 0.02442952, 0.012802322, -0.032276735, 0.0029802448, 0.014179829, 0.010321504, 0.0053337566, -0.017156808, -0.010439017, 0.034444187, -0.01039331... |
8fed2f4241d0-22 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.0040574414, -0.014976301, -0.006228157, -0.016647588, 0.0035188433, -0.01919369, 0.0037506039, 0.029247528, -0.014532366, -0.049773026, -0.019624569, -0.034783665, -0.015028529, 0.0097469995, 0.016281994, 0.0047135525, -0.011294246, 0.011477043, 0.015485522, 0.03426139, 0.014323455, 0.011052692, -0.008362965, -0.0379... |
8fed2f4241d0-23 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.0075403787, 0.03812624, 0.0009988552, 0.038752973, -0.018005509, 0.013670608, 0.045882057, -0.018841153, -0.031650003, 0.010628343, -0.00459604, -0.011999321, -0.028202975, -0.018593071, 0.029743692, 0.021857304, 0.01438874, 0.00014128008, -0.006156344, -0.006691678, 0.01672593, -0.012821908, -0.0024367499, -0.03219... |
8fed2f4241d0-24 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.02456009, -0.0018850947, 0.024442578, 0.0019715966, -0.02422061, -0.02945644, -0.003443766, 0.0004945313, 0.0011522742, -0.020773578, -0.011777353, 0.008173639, -0.012325744, -0.021348083, 0.0036461484, 0.0063228197, 0.00028970066, -0.0036200345, -0.021596165, -0.003949722, -0.0006034751, 0.007305354, -0.023424136, ... |
8fed2f4241d0-25 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.012919835, 0.0014493194, -0.021857304, -0.0075730206, -0.0020695236, 0.017822713, 0.017417947, -0.034835894, -0.009159437, -0.0018573486, -0.0024840813, -0.022444865, 0.0055687814, 0.0037767177, 0.0033915383, 0.0301354, -0.012227817, 0.0021854038, -0.042878963, 0.021517823, -0.010419431, -0.0051183174, 0.01659536, 0... |
8fed2f4241d0-26 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.0051444313, -0.0044654706, -0.008826486, 0.004158633, 0.004971427, -0.017835768, 0.025017083, -0.021792019, 0.013657551, -0.01872364, 0.009100681, -0.0079582, -0.011640254, -0.01093518, -0.0147543335, -0.005000805, 0.02345025, -0.028908048, 0.0104912445, -0.00753385, 0.017561574, -0.012025435, 0.042670052, -0.0041978... |
8fed2f4241d0-27 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.02047327, 0.0019258976, -0.0068940604, -0.0014990991, 0.013305014, -0.007690533, 0.058808424, -0.0016859764, -0.0044622063, -0.0037734534, 0.01578583, -0.0018459238, -0.1196015, -0.0007075225, 0.0030341048, 0.012306159, -0.0068483613, 0.01851473, 0.015315781, 0.031388864, -0.015563863, 0.04776226, -0.008199753, -0.02... |
8fed2f4241d0-28 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.015433294, -0.0056144805, -0.0034927295, -0.00043455104, 0.008611047, 0.025748271, 0.022353467, -0.020747464, -0.015759716, 0.029038617, -0.000377631, -0.028725252, 0.018109964, -0.0016125311, -0.022719061, -0.009133324, -0.033060152, 0.011248547, -0.0019797573, -0.007181313, 0.0018867267, 0.0070899143, 0.004077027, ... |
8fed2f4241d0-29 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.016321165, 0.009929797, 0.004609097, -0.03047488, 0.002688096, -0.07264877, 0.024455635, -0.020930262, -0.015381066, -0.0033148287, 0.027236762, 0.0014501355, -0.014101488, -0.024076983, 0.026218321, -0.009009283, 0.019624569, 0.0020646274, -0.009081096, -0.01565526, -0.003358896, 0.048571788, -0.004857179, 0.022444... |
8fed2f4241d0-30 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | -0.032746784, 0.025513247, -0.0025852725, 0.014467081, -0.008617575, -0.019755138, 0.003966043, -0.0033915383, 0.0004088452, -0.025173767, 0.02796795, 0.0023763615, 0.0052358294, 0.017796598, 0.014806561, 0.0150024155, -0.005859298, 0.01259994, 0.021726735, -0.026466403, -0.017457118, -0.0025493659, 0.0070899143, 0.026... |
8fed2f4241d0-31 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.0041814824, 0.025121538, -0.036246043, -0.019428715, -0.023802789, 0.014845733, 0.015420238, 0.019650683, 0.008186696, 0.025304336, -0.03204171, 0.01774437, 0.0021233836, -0.008434778, -0.0059441687, 0.038335152, 0.022653777, -0.0066002794, 0.02149171, 0.015093814, 0.025382677, -0.007579549, 0.0030357367, -0.00141178... |
8fed2f4241d0-32 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.0038191527, -0.014702106, 0.02196176, 0.0052097156, -0.010869896, 0.0051640165, 0.030840475, -0.041468814, 0.009250836, -0.018997835, 0.020107675, 0.008421721, -0.016373392, 0.004602568, 0.0327729, -0.00812794, 0.001581521, 0.019350372, 0.016112253, 0.02132197, 0.00043944738, -0.01472822, -0.025735214, -0.03313849, 0... |
8fed2f4241d0-33 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | 0.8154189703772676)
Persistance#
Anything uploaded to weaviate is automatically persistent into the database. You do not need to call any specific method or pass any param for this to happen.
Retriever options#
Retriever options#
This section goes over different options for how to use Weaviate as a retriever.
MMR#
In a... |
8fed2f4241d0-34 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/weaviate.html | with open("../../../state_of_the_union.txt") as f:
state_of_the_union = f.read()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
texts = text_splitter.split_text(state_of_the_union)
docsearch = Weaviate.from_texts(
texts,
embeddings,
weaviate_url=WEAVIATE_URL,
by_text=False,
... |
df572f77c264-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/opensearch.html | .ipynb
.pdf
OpenSearch
Contents
Installation
similarity_search using Approximate k-NN
similarity_search using Script Scoring
similarity_search using Painless Scripting
Using a preexisting OpenSearch instance
OpenSearch#
OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytic... |
df572f77c264-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/opensearch.html | similarity_search using Approximate k-NN Search with Custom Parameters
docsearch = OpenSearchVectorSearch.from_documents(
docs,
embeddings,
opensearch_url="http://localhost:9200"
)
# If using the default Docker installation, use this instantiation instead:
# docsearch = OpenSearchVectorSearch.from_documen... |
df572f77c264-2 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/opensearch.html | similarity_search using Painless Scripting with Custom Parameters
docsearch = OpenSearchVectorSearch.from_documents(docs, embeddings, opensearch_url="http://localhost:9200", is_appx_search=False)
filter = {"bool": {"filter": {"term": {"text": "smuggling"}}}}
query = "What did the president say about Ketanji Brown Jacks... |
599394236be2-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/typesense.html | .ipynb
.pdf
Typesense
Contents
Similarity Search
Typesense as a Retriever
Typesense#
Typesense is an open source, in-memory search engine, that you can either self-host or run on Typesense Cloud.
Typesense focuses on performance by storing the entire index in RAM (with a backup on disk) and also focuses on providing ... |
599394236be2-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/typesense.html | 'typesense_collection_name': 'lang-chain'
})
Similarity Search#
query = "What did the president say about Ketanji Brown Jackson"
found_docs = docsearch.similarity_search(query)
print(found_docs[0].page_content)
Typesense as a Retriever#
Typesense, as all the other vector stores, is ... |
481851c6ac03-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/analyticdb.html | .ipynb
.pdf
AnalyticDB
AnalyticDB#
AnalyticDB for PostgreSQL is a massively parallel processing (MPP) data warehousing service that is designed to analyze large volumes of data online.
AnalyticDB for PostgreSQL is developed based on the open source Greenplum Database project and is enhanced with in-depth extensions by ... |
481851c6ac03-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/analyticdb.html | driver=os.environ.get("PG_DRIVER", "psycopg2cffi"),
host=os.environ.get("PG_HOST", "localhost"),
port=int(os.environ.get("PG_PORT", "5432")),
database=os.environ.get("PG_DATABASE", "postgres"),
user=os.environ.get("PG_USER", "postgres"),
password=os.environ.get("PG_PASSWORD", "postgres"),
)
vector_d... |
7e51dbfe2b56-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/docarray_in_memory.html | .ipynb
.pdf
DocArrayInMemorySearch
Contents
Setup
Using DocArrayInMemorySearch
Similarity search
Similarity search with score
DocArrayInMemorySearch#
DocArrayInMemorySearch is a document index provided by Docarray that stores documents in memory. It is a great starting point for small datasets, where you may not want... |
7e51dbfe2b56-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/docarray_in_memory.html | Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.
One of the most serious constitutional responsibilities a President h... |
7e51dbfe2b56-2 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/docarray_in_memory.html | Last updated on Jun 04, 2023. |
2ed24d872dae-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/pinecone.html | .ipynb
.pdf
Pinecone
Pinecone#
Pinecone is a vector database with broad functionality.
This notebook shows how to use functionality related to the Pinecone vector database.
To use Pinecone, you must have an API key.
Here are the installation instructions.
!pip install pinecone-client
import os
import getpass
PINECONE_A... |
2ed24d872dae-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/pinecone.html | print(docs[0].page_content)
previous
PGVector
next
Qdrant
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
7db4b775103f-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/myscale.html | .ipynb
.pdf
MyScale
Contents
Setting up envrionments
Get connection info and data schema
Filtering
Deleting your data
MyScale#
MyScale is a cloud-based database optimized for AI applications and solutions, built on the open-source ClickHouse.
This notebook shows how to use functionality related to the MyScale vector ... |
7db4b775103f-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/myscale.html | docs = text_splitter.split_documents(documents)
embeddings = OpenAIEmbeddings()
for d in docs:
d.metadata = {'some': 'metadata'}
docsearch = MyScale.from_documents(docs, embeddings)
query = "What did the president say about Ketanji Brown Jackson"
docs = docsearch.similarity_search(query)
Inserting data...: 100%|███... |
7db4b775103f-2 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/myscale.html | from langchain.document_loaders import TextLoader
loader = TextLoader('../../../state_of_the_union.txt')
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)
embeddings = OpenAIEmbeddings()
for i, d in enumerate(docs):
d.me... |
a5b352af876f-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/matchingengine.html | .ipynb
.pdf
MatchingEngine
Contents
Create VectorStore from texts
Create Index and deploy it to an Endpoint
Imports, Constants and Configs
Using Tensorflow Universal Sentence Encoder as an Embedder
Inserting a test embedding
Creating Index
Creating Endpoint
Deploy Index
MatchingEngine#
This notebook shows how to use ... |
a5b352af876f-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/matchingengine.html | VPC_NETWORK = "<my_vpc_network_name>"
PEERING_RANGE_NAME = "ann-langchain-me-range" # Name for creating the VPC peering.
BUCKET_URI = "gs://<bucket_uri>"
# The number of dimensions for the tensorflow universal sentence encoder.
# If other embedder is used, the dimensions would probably need to change.
DIMENSIONS = 51... |
a5b352af876f-2 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/matchingengine.html | ! gcloud compute firewall-rules create {VPC_NETWORK}-allow-rdp --network {VPC_NETWORK} --priority 65534 --project {PROJECT_ID} --allow tcp:3389
! gcloud compute firewall-rules create {VPC_NETWORK}-allow-ssh --network {VPC_NETWORK} --priority 65534 --project {PROJECT_ID} --allow tcp:22
# Reserve IP range
! g... |
a5b352af876f-3 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/matchingengine.html | my_index = aiplatform.MatchingEngineIndex.create_tree_ah_index(
display_name=DISPLAY_NAME,
contents_delta_uri=EMBEDDING_DIR,
dimensions=DIMENSIONS,
approximate_neighbors_count=150,
distance_measure_type="DOT_PRODUCT_DISTANCE"
)
Creating Endpoint#
my_index_endpoint = aiplatform.MatchingEngineIndexEnd... |
b5e81124faa8-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/docarray_hnsw.html | .ipynb
.pdf
DocArrayHnswSearch
Contents
Setup
Using DocArrayHnswSearch
Similarity search
Similarity search with score
DocArrayHnswSearch#
DocArrayHnswSearch is a lightweight Document Index implementation provided by Docarray that runs fully locally and is best suited for small- to medium-sized datasets. It stores vec... |
b5e81124faa8-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/docarray_hnsw.html | Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections.
Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army ve... |
b5e81124faa8-2 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/docarray_hnsw.html | shutil.rmtree('hnswlib_store')
previous
Deep Lake
next
DocArrayInMemorySearch
Contents
Setup
Using DocArrayHnswSearch
Similarity search
Similarity search with score
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
f01f5d0a0fe8-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/elasticsearch.html | .ipynb
.pdf
ElasticSearch
Contents
ElasticSearch
ElasticVectorSearch class
Installation
Example
ElasticKnnSearch Class
Test adding vectors
Test knn search using query vector builder
Test knn search using pre generated vector
Test source option
Test fields option
Test with es client connection rather than cloud_id
Ela... |
f01f5d0a0fe8-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/elasticsearch.html | Log in to the Elastic Cloud console at https://cloud.elastic.co
Go to “Security” > “Users”
Locate the “elastic” user and click “Edit”
Click “Reset password”
Follow the prompts to reset the password
Format for Elastic Cloud URLs is
https://username:password@cluster_id.region_id.gcp.cloud.es.io:9243.
Example:
fro... |
f01f5d0a0fe8-2 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/elasticsearch.html | In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections.
We cannot let this happen.
Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is ... |
f01f5d0a0fe8-3 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/elasticsearch.html | es_password=es_password,
)
# Initialize ElasticKnnSearch
knn_search = ElasticKnnSearch(
es_cloud_id=es_cloud_id,
es_user=es_user,
es_password=es_password,
index_name= test_index,
embedding= embeddings
)
Test adding vectors#
# Test `add_texts` method
texts = ["Hello, world!", "Machine learning is fun.", "I love... |
f01f5d0a0fe8-4 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/elasticsearch.html | print(f"Length of embedding: {len(query_embedding)}\nFirst two items in embedding: {query_embedding[:2]}")
# Test knn Search
knn_result = knn_search.knn_search(query_vector = query_embedding, k=2)
print(f"The 'text' field value from the top hit is: '{knn_result['hits']['hits'][0]['_source']['text']}'")
# Test hybrid se... |
f01f5d0a0fe8-5 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/elasticsearch.html | hybrid_result = knn_search.knn_hybrid_search(query = query, model_id= model_id, k=2, fields=['text'])
assert 'text' in hybrid_result['hits']['hits'][0]['fields'].keys()
Test with es client connection rather than cloud_id#
# Create Elasticsearch connection
es_connection = Elasticsearch(
hosts=['https://es_cluster_ur... |
42011e9ef15e-0 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/tair.html | .ipynb
.pdf
Tair
Tair#
Tair is a cloud native in-memory database service developed by Alibaba Cloud.
It provides rich data models and enterprise-grade capabilities to support your real-time online scenarios while maintaining full compatibility with open source Redis. Tair also introduces persistent memory-optimized ins... |
42011e9ef15e-1 | https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/tair.html | Document(page_content='We’re going after the criminals who stole billions in relief money meant for small businesses and millions of Americans. \n\nAnd tonight, I’m announcing that the Justice Department will name a chief prosecutor for pandemic fraud. \n\nBy the end of this year, the deficit will be down to less than... |
d5d0dc00678b-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/airbyte_json.html | .ipynb
.pdf
Airbyte JSON
Airbyte JSON#
Airbyte is a data integration platform for 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... |
d5d0dc00678b-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/airbyte_json.html | base_experience: 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:
n
previous
YouTube transcripts... |
4afac833b0ce-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/diffbot.html | .ipynb
.pdf
Diffbot
Diffbot#
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 ... |
4afac833b0ce-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/diffbot.html | [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: ... |
4afac833b0ce-2 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/diffbot.html | and examples of end to end agents.\nUse Cases\nThe above modules can be used in a variety of ways. LangChain also provides guidance and assistance in this. Below are some of the common use cases LangChain supports.\nPersonal Assistants: The main LangChain use case. Personal assistants need to take actions, remember int... |
4afac833b0ce-3 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/diffbot.html | glossary of all related terms, papers, methods, etc. Whether implemented in LangChain or not!\nGallery: A collection of our favorite projects that use LangChain. Useful for finding inspiration or seeing how things were done in other applications.\nDeployments: A collection of instructions, code snippets, and template r... |
4afac833b0ce-4 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/diffbot.html | previous
Confluence
next
Docugami
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
aefce94d06a4-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/modern_treasury.html | .ipynb
.pdf
Modern Treasury
Modern Treasury#
Modern Treasury simplifies complex payment operations. It is a unified platform to power products and processes that move money.
Connect to banks and payment systems
Track transactions and balances in real-time
Automate payment operations for scale
This notebook covers how t... |
5632c439101a-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/figma.html | .ipynb
.pdf
Figma
Figma#
Figma is a collaborative web application for interface design.
This 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 os
from langchain.document_loaders.figma import FigmaFileLoader
fr... |
5632c439101a-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/figma.html | # See https://python.langchain.com/en/latest/modules/models/chat/getting_started.html for chat info
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... |
5632c439101a-2 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/figma.html | <!DOCTYPE html>\n<html lang="en">\n<head>\n <meta charset="UTF-8">\n <meta 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... |
5632c439101a-3 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/figma.html | display: flex;\n 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... |
5632c439101a-4 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/figma.html | previous
DuckDB
next
GitBook
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on Jun 04, 2023. |
a3b3f5364097-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/epub.html | .ipynb
.pdf
EPub
Contents
Retain Elements
EPub#
EPUB is an e-book file format that uses the “.epub” file extension. The term is short for electronic publication and is sometimes styled ePub. EPUB is supported by many e-readers, and compatible software is available for most smartphones, tablets, and computers.
This co... |
cf3d4450d404-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/azure_blob_storage_file.html | .ipynb
.pdf
Azure Blob Storage File
Azure Blob Storage File#
Azure Files offers fully managed file shares in the cloud that are accessible via the industry standard Server Message Block (SMB) protocol, Network File System (NFS) protocol, and Azure Files REST API.
This covers how to load document objects from a Azure Fi... |
85fd80d03112-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/google_cloud_storage_file.html | .ipynb
.pdf
Google Cloud Storage File
Google Cloud Storage File#
Google Cloud Storage is 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-storage
from langchain.document_loaders import GCSFileLoad... |
d88c5f58b977-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/git.html | .ipynb
.pdf
Git
Contents
Load existing repository from disk
Clone repository from url
Filtering files to load
Git#
Git is a distributed version control system that tracks changes in any set of computer files, usually used for coordinating work among programmers collaboratively developing source code during software d... |
d88c5f58b977-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/git.html | Last updated on Jun 04, 2023. |
1e6df26c330d-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image.html | .ipynb
.pdf
Images
Contents
Using Unstructured
Retain Elements
Images#
This covers how to load images such as JPG or PNG into a document format that we can use downstream.
Using Unstructured#
#!pip install pdfminer
from langchain.document_loaders.image import UnstructuredImageLoader
loader = UnstructuredImageLoader("... |
1e6df26c330d-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image.html | Document(page_content="LayoutParser: A Unified Toolkit for Deep\nLearning Based Document Image Analysis\n\n\n‘Zxjiang Shen' (F3}, Ruochen Zhang”, Melissa Dell*, Benjamin Charles Germain\nLeet, Jacob Carlson, and Weining LiF\n\n\nsugehen\n\nshangthrows, et\n\n“Abstract. Recent advanocs in document image analysis (DIA) h... |
1e6df26c330d-2 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image.html | Tol\n\n\nIntroduction\n\n\n‘Deep Learning(DL)-based approaches are the state-of-the-art for a wide range of\ndoctiment image analysis (DIA) tea including document image clasiffeation [I]\n", lookup_str='', metadata={'source': 'layout-parser-paper-fast.jpg'}, lookup_index=0) |
1e6df26c330d-3 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/image.html | Retain Elements#
Under the hood, Unstructured creates different “elements” for different chunks of text. By default we combine those together, but you can easily keep that separation by specifying mode="elements".
loader = UnstructuredImageLoader("layout-parser-paper-fast.jpg", mode="elements")
data = loader.load()
dat... |
fbd903aea186-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/youtube_transcript.html | .ipynb
.pdf
YouTube transcripts
Contents
Add video info
YouTube loader from Google Cloud
Prerequisites
🧑 Instructions for ingesting your Google Docs data
YouTube transcripts#
YouTube is an online video sharing and social media platform created by Google.
This notebook covers how to load documents from YouTube transc... |
fbd903aea186-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/youtube_transcript.html | # Use a Channel
youtube_loader_channel = GoogleApiYoutubeLoader(google_api_client=google_api_client, channel_name="Reducible",captions_language="en")
# Use Youtube Ids
youtube_loader_ids = GoogleApiYoutubeLoader(google_api_client=google_api_client, video_ids=["TrdevFK_am4"], add_video_info=True)
# returns a list of Doc... |
7dab7f6a001f-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/notion.html | .ipynb
.pdf
Notion DB 1/2
Contents
🧑 Instructions for ingesting your own dataset
Notion DB 1/2#
Notion 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 tas... |
fd2bae6be801-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/evernote.html | .ipynb
.pdf
EverNote
EverNote#
EverNote is intended for archiving and creating notes in which photos, audio and saved web content can be embedded. Notes are stored in virtual “notebooks” and can be tagged, annotated, edited, searched, and exported.
This notebook shows how to load an Evernote export file (.enex) from di... |
fd2bae6be801-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/evernote.html | Document(page_content='**Jan - March 2022**', metadata={'title': 'Summer Training Program', 'created': time.struct_time(tm_year=2022, tm_mon=12, tm_mday=27, tm_hour=1, tm_min=59, tm_sec=48, tm_wday=1, tm_yday=361, tm_isdst=-1), 'note-attributes.author': 'Mike McGarry', 'note-attributes.source': 'mobile.iphone', 'source... |
9d9335e0f1be-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/google_cloud_storage_directory.html | .ipynb
.pdf
Google Cloud Storage Directory
Contents
Specifying a prefix
Google Cloud Storage Directory#
Google Cloud Storage is a managed service for storing unstructured data.
This covers how to load document objects from an Google Cloud Storage (GCS) directory (bucket).
# !pip install google-cloud-storage
from lang... |
9d9335e0f1be-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/google_cloud_storage_directory.html | [Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': '/var/folders/y6/8_bzdg295ld6s1_97_12m4lr0000gn/T/tmpz37njh7u/fake.docx'}, lookup_index=0)]
Specifying a prefix#
You can also specify a prefix for more finegrained control over what files to load.
loader = GCSDirectoryLoader(projec... |
9d9335e0f1be-2 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/google_cloud_storage_directory.html | [Document(page_content='Lorem ipsum dolor sit amet.', lookup_str='', metadata={'source': '/var/folders/y6/8_bzdg295ld6s1_97_12m4lr0000gn/T/tmpylg6291i/fake.docx'}, lookup_index=0)]
previous
Google BigQuery
next
Google Cloud Storage File
Contents
Specifying a prefix
By Harrison Chase
© Copyright 2023, Har... |
e44834c22cca-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/microsoft_onedrive.html | .ipynb
.pdf
Microsoft OneDrive
Contents
Prerequisites
🧑 Instructions for ingesting your documents from OneDrive
🔑 Authentication
🗂️ Documents loader
📑 Loading documents from a OneDrive Directory
📑 Loading documents from a list of Documents IDs
Microsoft OneDrive#
Microsoft OneDrive (formerly SkyDrive) is a file ... |
e44834c22cca-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/microsoft_onedrive.html | 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 sc... |
e44834c22cca-2 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/microsoft_onedrive.html | loader = 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 G... |
1cfad0a665b2-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/reddit.html | .ipynb
.pdf
Reddit
Reddit#
Reddit is an American social news aggregation, content rating, and discussion website.
This loader fetches the text from the Posts of Subreddits or Reddit users, using the praw Python package.
Make a Reddit Application and initialize the loader with with your Reddit API credentials.
from lang... |
1cfad0a665b2-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/reddit.html | [Document(page_content='Hello, I am not looking for investment advice. I will apply my own due diligence. However, I am interested if anyone knows as a UK resident how fees and exchange rate differences would impact performance?\n\nI am planning to create a pie of index funds (perhaps UK, US, europe) or find a fund wit... |
1cfad0a665b2-2 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/reddit.html | Document(page_content='Have a general question? Want to offer some commentary on markets? 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 sh... |
1cfad0a665b2-3 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/reddit.html | 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 G... |
1cfad0a665b2-4 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/reddit.html | 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 stoc... |
1cfad0a665b2-5 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/reddit.html | 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 ... |
a78ae9d7ff5f-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/slack.html | .ipynb
.pdf
Slack
Contents
🧑 Instructions for ingesting your own dataset
Slack#
Slack is an instant messaging program.
This 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#... |
ed5cc3d28a2c-0 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | .ipynb
.pdf
Twitter
Twitter#
Twitter is an online social media and social networking service.
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 ext... |
ed5cc3d28a2c-1 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | [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... |
ed5cc3d28a2c-2 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | [11, 15]}], 'urls': []}, 'source': '<a href="http://twitter.com/download/iphone" rel="nofollow">Twitter for iPhone</a>', 'in_reply_to_status_id': 1648134341678051328, 'in_reply_to_status_id_str': '1648134341678051328', 'in_reply_to_user_id': 2835451658, 'in_reply_to_user_id_str': '2835451658', 'in_reply_to_screen_name'... |
ed5cc3d28a2c-3 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 'default_profile_image': False, 'following': None, 'follow_request_sent': None, 'notifications': None, 'translator_type': 'none', 'withheld_in_countries': []}}), |
ed5cc3d28a2c-4 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 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... |
ed5cc3d28a2c-5 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 'id_str': '16583846', 'indices': [11, 15]}], 'urls': []}, 'source': '<a href="http://twitter.com/download/iphone" rel="nofollow">Twitter for iPhone</a>', 'in_reply_to_status_id': 1648134341678051328, 'in_reply_to_status_id_str': '1648134341678051328', 'in_reply_to_user_id': 2835451658, 'in_reply_to_user_id_str': '28354... |
ed5cc3d28a2c-6 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 'has_extended_profile': True, 'default_profile': False, 'default_profile_image': False, 'following': None, 'follow_request_sent': None, 'notifications': None, 'translator_type': 'none', 'withheld_in_countries': []}}), |
ed5cc3d28a2c-7 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 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, ... |
ed5cc3d28a2c-8 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 15]}], 'urls': []}, 'source': '<a href="http://twitter.com/download/iphone" rel="nofollow">Twitter for iPhone</a>', 'in_reply_to_status_id': 1648134341678051328, 'in_reply_to_status_id_str': '1648134341678051328', 'in_reply_to_user_id': 2835451658, 'in_reply_to_user_id_str': '2835451658', 'in_reply_to_screen_name': 'Mr... |
ed5cc3d28a2c-9 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 'default_profile_image': False, 'following': None, 'follow_request_sent': None, 'notifications': None, 'translator_type': 'none', 'withheld_in_countries': []}}), |
ed5cc3d28a2c-10 | https://python.langchain.com/en/latest/modules/indexes/document_loaders/examples/twitter.html | 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': {... |
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