langchain/docs/extras/integrations/document_loaders/embaas.ipynb

Embaas

embaas is a fully managed NLP API service that offers features like embedding generation, document text extraction, document to embeddings and more. You can choose a variety of pre-trained models.

Prerequisites

Create a free embaas account at https://embaas.io/register and generate an API key

Document Text Extraction API

The document text extraction API allows you to extract the text from a given document. The API supports a variety of document formats, including PDF, mp3, mp4 and more. For a full list of supported formats, check out the API docs (link below).

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# Set API key
embaas_api_key = "YOUR_API_KEY"
# or set environment variable
os.environ["EMBAAS_API_KEY"] = "YOUR_API_KEY"

Using a blob (bytes)

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from langchain.document_loaders.embaas import EmbaasBlobLoader
from langchain.document_loaders.blob_loaders import Blob

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blob_loader = EmbaasBlobLoader()
blob = Blob.from_path("example.pdf")
documents = blob_loader.load(blob)

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# You can also directly create embeddings with your preferred embeddings model
blob_loader = EmbaasBlobLoader(params={"model": "e5-large-v2", "should_embed": True})
blob = Blob.from_path("example.pdf")
documents = blob_loader.load(blob)

print(documents[0]["metadata"]["embedding"])

Using a file

In [ ]:

from langchain.document_loaders.embaas import EmbaasLoader

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file_loader = EmbaasLoader(file_path="example.pdf")
documents = file_loader.load()

In [15]:

# Disable automatic text splitting
file_loader = EmbaasLoader(file_path="example.mp3", params={"should_chunk": False})
documents = file_loader.load()

For more detailed information about the embaas document text extraction API, please refer to the official embaas API documentation.