LangChain integrations for Google Cloud Bigtable
Project description
Quick Start
In order to use this library, you first need to go through the following steps:
Installation
Install this library in a virtualenv using pip. virtualenv is a tool to create isolated Python environments. The basic problem it addresses is one of dependencies and versions, and indirectly permissions.
With virtualenv, it’s possible to install this library without needing system install permissions, and without clashing with the installed system dependencies.
Supported Python Versions
Python >= 3.8
Mac/Linux
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install langchain-google-bigtable
Windows
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install langchain-google-bigtable
Document Loader Usage
Use a document loader to load data as LangChain Documents.
from langchain_google_bigtable import BigtableLoader
loader = BigtableLoader(
instance_id="my-instance",
table_id="my-table-name"
)
docs = loader.lazy_load()
See the full Document Loader tutorial.
Chat Message History Usage
Use ChatMessageHistory to store messages and provide conversation history to LLMs.
from langchain_google_bigtable import BigtableChatMessageHistory
history = BigtableChatMessageHistory(
instance_id="my-instance",
table_id="my-message-store",
session_id="my-session_id"
)
See the full Chat Message History tutorial.
Contributions
Contributions to this library are always welcome and highly encouraged.
See CONTRIBUTING for more information how to get started.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. See Code of Conduct for more information.
License
Apache 2.0 - See LICENSE for more information.
Disclaimer
This is not an officially supported Google product.
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